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9,292,595 | 1 | 2 | 1. A method of creating a new document, the method comprising the steps of: a computer receiving keywords specifying a subject matter of the new document; the computer determining metadata of documents or metadata of parts of the documents matches one or more keywords included in the received keywords; the computer retrieving the documents or the parts of the documents whose metadata matches the one or more keywords; based on a section or subsection being created in the new document, the computer generating a ranked list of the retrieved documents or parts of the documents; the computer receiving a selection of a document or a part of a document included in the ranked list; the computer adding content to the new document, the added content being the document or the part of the document whose selection was received; the computer determining the new document is not complete; the computer refining the keywords based in part on the added content; and based in part on the subject matter and the refined keywords, the computer completing the new document by repeating the steps of determining the metadata, retrieving the documents, generating the ranked list, receiving the selection, and adding the content. | 1. A method of creating a new document, the method comprising the steps of: a computer receiving keywords specifying a subject matter of the new document; the computer determining metadata of documents or metadata of parts of the documents matches one or more keywords included in the received keywords; the computer retrieving the documents or the parts of the documents whose metadata matches the one or more keywords; based on a section or subsection being created in the new document, the computer generating a ranked list of the retrieved documents or parts of the documents; the computer receiving a selection of a document or a part of a document included in the ranked list; the computer adding content to the new document, the added content being the document or the part of the document whose selection was received; the computer determining the new document is not complete; the computer refining the keywords based in part on the added content; and based in part on the subject matter and the refined keywords, the computer completing the new document by repeating the steps of determining the metadata, retrieving the documents, generating the ranked list, receiving the selection, and adding the content. 2. The method of claim 1 , further comprising the steps of: the computer system receiving an outline of sections and subsections in the new document; and the computer receiving an association between the outline and the received keywords, wherein the step of completing the new document is based in part on the outline and the association between the outline and the received keywords. | 0.863861 |
8,568,144 | 1 | 26 | 1. A reading comprehension training system, comprising: a computing device; a game logic portion that generates a reading comprehension challenge that comprises language micro-variables including one or more verb micro-variables, one or more agent micro-variables, and one or more reference micro-variables at a particular level of difficulty to test a user's comprehension of the reading comprehension challenge; a user interface portion that generates a user interface to display the reading comprehension challenge at the particular skill level on the computing device; and wherein the game logic portion comprises a game administrator portion that: receives a response from the user to the reading comprehension challenge based on controlled manipulation of the language micro-variables in the reading comprehension challenge, isolates one or more language micro-variables that are impeding the user's comprehension of the reading comprehension challenge based on the response from the user, provides direct instruction to train the user to become more proficient at the isolated one or more language micro-variables based on controlled manipulation of the isolated one or more language micro-variables, and determines, once the user becomes more proficient at the isolated one or more language micro-variables, a next reading comprehension challenge that comprises language micro-variables including one or more verb micro-variables, one or more agent micro-variables, and one or more reference micro-variables at a particular level of difficulty to test the user's comprehension of the next reading comprehension challenge. | 1. A reading comprehension training system, comprising: a computing device; a game logic portion that generates a reading comprehension challenge that comprises language micro-variables including one or more verb micro-variables, one or more agent micro-variables, and one or more reference micro-variables at a particular level of difficulty to test a user's comprehension of the reading comprehension challenge; a user interface portion that generates a user interface to display the reading comprehension challenge at the particular skill level on the computing device; and wherein the game logic portion comprises a game administrator portion that: receives a response from the user to the reading comprehension challenge based on controlled manipulation of the language micro-variables in the reading comprehension challenge, isolates one or more language micro-variables that are impeding the user's comprehension of the reading comprehension challenge based on the response from the user, provides direct instruction to train the user to become more proficient at the isolated one or more language micro-variables based on controlled manipulation of the isolated one or more language micro-variables, and determines, once the user becomes more proficient at the isolated one or more language micro-variables, a next reading comprehension challenge that comprises language micro-variables including one or more verb micro-variables, one or more agent micro-variables, and one or more reference micro-variables at a particular level of difficulty to test the user's comprehension of the next reading comprehension challenge. 26. The system of claim 1 , wherein the game administrator portion further comprises an assessment unit that assesses the skill level of a student at a particular reading comprehension challenge, the assessment unit further comprising the step of asking the student what his skill level is for the particular reading comprehension challenge and testing the student at the skill level. | 0.72093 |
8,527,450 | 10 | 11 | 10. The apparatus of claim 8 , wherein obtaining the models and classification are performed using a Gradient Boosted Decision Trees algorithm, wherein the processor and/or memory are further configured to generate a particular lexicon for a particular class by: manually classifying a sample of messages as belonging to the particular class; forming the particular lexicon from a top percentage of most frequently used tokens from the sample of messages; automatically clustering a larger sample of messages into a plurality of topics; and to the particular lexicon, adding tokens from one or more topics that also include one or more tokens from the particular lexicon. | 10. The apparatus of claim 8 , wherein obtaining the models and classification are performed using a Gradient Boosted Decision Trees algorithm, wherein the processor and/or memory are further configured to generate a particular lexicon for a particular class by: manually classifying a sample of messages as belonging to the particular class; forming the particular lexicon from a top percentage of most frequently used tokens from the sample of messages; automatically clustering a larger sample of messages into a plurality of topics; and to the particular lexicon, adding tokens from one or more topics that also include one or more tokens from the particular lexicon. 11. The apparatus of claim 10 , wherein the processor and/or memory are further configured to rank the messages from the larger sample based on the messages that are most likely to belong to the particular class and only clustering a percentage of the highest ranked messages for the particular class. | 0.5 |
7,720,804 | 1 | 20 | 1. A method of generating and maintaining a data warehouse, the method comprising: providing a predefined reusable metadata model having a data information model including metadata describing models for generating a data warehouse including metadata describing business logic for extracting information from one or more source systems and transforming the information into a data warehouse structure, and an information needs model including metadata regarding information needs for building reports, wherein the information needs model of the data information model comprises metadata defining user roles, metadata defining measures important to the user roles, members of the user roles, and context filters that apply to the members; providing data management services by a data warehouse solution system engine that generates a source framework model which is a semantic layer providing a logical business representation of the one or more source systems, to automatically generate a data warehouse from the one or more source systems using the data information model and the source framework model; providing a modeling user interface for presenting the data information model to a user for allowing the user to manipulate objects of the data warehouse; automatically generating the data warehouse from the one or more source systems using the data information model and the source framework model; and automatically generating reports using the information needs model and the data warehouse based on the metadata defining user roles, metadata defining measures important to the user roles, members of the user roles, and context filters that apply to the members. | 1. A method of generating and maintaining a data warehouse, the method comprising: providing a predefined reusable metadata model having a data information model including metadata describing models for generating a data warehouse including metadata describing business logic for extracting information from one or more source systems and transforming the information into a data warehouse structure, and an information needs model including metadata regarding information needs for building reports, wherein the information needs model of the data information model comprises metadata defining user roles, metadata defining measures important to the user roles, members of the user roles, and context filters that apply to the members; providing data management services by a data warehouse solution system engine that generates a source framework model which is a semantic layer providing a logical business representation of the one or more source systems, to automatically generate a data warehouse from the one or more source systems using the data information model and the source framework model; providing a modeling user interface for presenting the data information model to a user for allowing the user to manipulate objects of the data warehouse; automatically generating the data warehouse from the one or more source systems using the data information model and the source framework model; and automatically generating reports using the information needs model and the data warehouse based on the metadata defining user roles, metadata defining measures important to the user roles, members of the user roles, and context filters that apply to the members. 20. The method as claimed in claim 1 , wherein the providing data management services comprises: managing creation and modification of warehouse tables in the data warehouse; and managing loading of the data into the warehouse tables from the source systems. | 0.720174 |
9,613,004 | 4 | 5 | 4. The method of claim 1 wherein the disambiguating which entities are being referred to in the indicated text segment by determining of the one or more mostly likely entities which are referred to in the text segment by comparing, using both linguistic and contextual information, the entity profiles generated for each potential entity name with attributes of one or more candidate entities further comprises: searching a knowledge repository for a set of candidate entities that have similar characteristics to the properties of one or more of the generated entity profiles; ranking the candidate entities in the set of candidate entities to determine a set of mostly likely entities which are referred to in the text segment; and providing the determined set of mostly likely entities. | 4. The method of claim 1 wherein the disambiguating which entities are being referred to in the indicated text segment by determining of the one or more mostly likely entities which are referred to in the text segment by comparing, using both linguistic and contextual information, the entity profiles generated for each potential entity name with attributes of one or more candidate entities further comprises: searching a knowledge repository for a set of candidate entities that have similar characteristics to the properties of one or more of the generated entity profiles; ranking the candidate entities in the set of candidate entities to determine a set of mostly likely entities which are referred to in the text segment; and providing the determined set of mostly likely entities. 5. The method of claim 4 wherein the ranking the candidate entities weights the candidate entities according to contextual information surrounding portions of the text segment that refer to the potential entity names. | 0.5 |
5,408,412 | 1 | 5 | 1. A system for use in diagnosing a malfunction in an aircraft engine from engine sensor signals including signals corresponding to engine faults, said system comprising: a diagnostic supervisory signal generator means for generating system command signals; an input/output device for receiving signals from and sending signals to a technician; a knowledge memory means having stored therein signals corresponding to a database of engine sensor signal values and facts and rules relating each of said engine sensor signal values and facts with selected ones thereof, each of said rules including a logical premise and conclusion; an inference engine means for receiving said knowledge memory means signals and, in response to said system command signals, for performing an inference engine test to establish the cause of the engine faults and generating signals indicative thereof, said inference engine test including the steps of: determining from said engine sensor signals a first series of rules to be tested; searching said knowledge memory means for signals corresponding to one of said engine sensor signal values and facts that establishes the validity of a first rule conclusion; generating signals for said input/output means for querying said technician for input signals that establishes the validity of said first rule conclusion; receiving signals from said input/output means indicative of technician input signals; inferring the value of a first rule premise signal corresponding to a first rule premise associated with said first rule conclusion in dependence on the establishment of the validity of said first rule conclusion, determining a second series of rules to be tested in dependence on said first rule premise signal value; and a retroceding means for receiving a signal indicative of an erroneous input signal and, in response thereto, determining all of said first rule conclusion and premise signal values established as a result of said erroneous input signal; said retroceding means further for removing all the erroneously established signal values from said knowledge database. | 1. A system for use in diagnosing a malfunction in an aircraft engine from engine sensor signals including signals corresponding to engine faults, said system comprising: a diagnostic supervisory signal generator means for generating system command signals; an input/output device for receiving signals from and sending signals to a technician; a knowledge memory means having stored therein signals corresponding to a database of engine sensor signal values and facts and rules relating each of said engine sensor signal values and facts with selected ones thereof, each of said rules including a logical premise and conclusion; an inference engine means for receiving said knowledge memory means signals and, in response to said system command signals, for performing an inference engine test to establish the cause of the engine faults and generating signals indicative thereof, said inference engine test including the steps of: determining from said engine sensor signals a first series of rules to be tested; searching said knowledge memory means for signals corresponding to one of said engine sensor signal values and facts that establishes the validity of a first rule conclusion; generating signals for said input/output means for querying said technician for input signals that establishes the validity of said first rule conclusion; receiving signals from said input/output means indicative of technician input signals; inferring the value of a first rule premise signal corresponding to a first rule premise associated with said first rule conclusion in dependence on the establishment of the validity of said first rule conclusion, determining a second series of rules to be tested in dependence on said first rule premise signal value; and a retroceding means for receiving a signal indicative of an erroneous input signal and, in response thereto, determining all of said first rule conclusion and premise signal values established as a result of said erroneous input signal; said retroceding means further for removing all the erroneously established signal values from said knowledge database. 5. The diagnostic system of claim 1 wherein said knowledge database is divided into a plurality of knowledge database portions, and said diagnostic system further comprises a means for moving a selected one of said knowledge database portions into a computer memory means for communicating with said diagnostic system. | 0.637813 |
8,725,511 | 1 | 4 | 1. A method comprising: comparing, via a processor, received speech to a first grammar based on a database, to yield a comparison; and when the comparison is below a threshold: compiling a second grammar based on data added to the database after compilation of the first grammar; and comparing the received speech to the second grammar. | 1. A method comprising: comparing, via a processor, received speech to a first grammar based on a database, to yield a comparison; and when the comparison is below a threshold: compiling a second grammar based on data added to the database after compilation of the first grammar; and comparing the received speech to the second grammar. 4. The method of claim 1 , wherein the database comprises a directory of names. | 0.729452 |
9,431,028 | 30 | 31 | 30. The method of claim 22 , wherein the creating the dialogue agent comprises: generating a network-based platform; connecting the network-based platform to a dialogue agent front end; and completing dialogue agent application. | 30. The method of claim 22 , wherein the creating the dialogue agent comprises: generating a network-based platform; connecting the network-based platform to a dialogue agent front end; and completing dialogue agent application. 31. The method of claim 30 , wherein the dialogue agent application further comprises dialogue cloud with key words for search engines, and the populating the created dialogue agent application comprises: populating on a social media platform; generating links accessible from Internet and smart phone applications; and updating wrapper description identifications. | 0.5 |
9,720,814 | 1 | 8 | 1. A method to control testing of one or more services by one or more computing devices using inferred template identification, the method comprising: inferring templates, by the one or more computing devices, that are likely used for documents for respective services of a service provider that are available via corresponding universal resource locators (URLs) to form an inferred dataset; identifying an overlap, by the one or more computing devices, in the inferred dataset to cluster services together that have likely used corresponding templates; removing one or more duplicates, by the one or more computing devices, in the inferred dataset based on the identified overlap to form a de-duplicated dataset to be used to test the clustered services; and controlling testing, by the one or more computing devices, of the one or more services based at least in part on the clustered services and the de-duplicated dataset. | 1. A method to control testing of one or more services by one or more computing devices using inferred template identification, the method comprising: inferring templates, by the one or more computing devices, that are likely used for documents for respective services of a service provider that are available via corresponding universal resource locators (URLs) to form an inferred dataset; identifying an overlap, by the one or more computing devices, in the inferred dataset to cluster services together that have likely used corresponding templates; removing one or more duplicates, by the one or more computing devices, in the inferred dataset based on the identified overlap to form a de-duplicated dataset to be used to test the clustered services; and controlling testing, by the one or more computing devices, of the one or more services based at least in part on the clustered services and the de-duplicated dataset. 8. The method as described in claim 1 , wherein the removing includes at least some duplicate templates that are used to validate quality. | 0.705128 |
6,151,571 | 1 | 7 | 1. A method for monitoring a conversation between a pair of speakers for detecting an emotion of at least one of the speakers using voice analysis comprising the steps of: (a) receiving a voice signal representing voices of speakers in a conversation; (b) extracting at least one feature of the voice signal selected from a group of features consisting of a maximum value of a fundamental frequency, a standard deviation of the fundamental frequency, a range of the fundamental frequency, a mean of the fundamental frequency, a mean of a bandwidth of a first formant, a mean of a bandwidth of a second formant, a standard deviation of energy, a speaking rate, a slope of the fundamental frequency, a maximum value of the first formant, a maximum value of the energy, a range of the energy, a range of the second formant, and a range of the first formant; (c) determining an emotion associated with the voice signal based on the extracted feature; (d) determining whether the emotion matches a negative emotion selected from a predefined group of negative emotions consisting of anger, sadness and fear; and (e) outputting the determined emotion to a third party during the conversation if the emotion matches one of the negative emotions. | 1. A method for monitoring a conversation between a pair of speakers for detecting an emotion of at least one of the speakers using voice analysis comprising the steps of: (a) receiving a voice signal representing voices of speakers in a conversation; (b) extracting at least one feature of the voice signal selected from a group of features consisting of a maximum value of a fundamental frequency, a standard deviation of the fundamental frequency, a range of the fundamental frequency, a mean of the fundamental frequency, a mean of a bandwidth of a first formant, a mean of a bandwidth of a second formant, a standard deviation of energy, a speaking rate, a slope of the fundamental frequency, a maximum value of the first formant, a maximum value of the energy, a range of the energy, a range of the second formant, and a range of the first formant; (c) determining an emotion associated with the voice signal based on the extracted feature; (d) determining whether the emotion matches a negative emotion selected from a predefined group of negative emotions consisting of anger, sadness and fear; and (e) outputting the determined emotion to a third party during the conversation if the emotion matches one of the negative emotions. 7. A method as recited in claim 1, wherein the voice signal is received from an emergency response system. | 0.913115 |
7,526,477 | 1 | 9 | 1. A method for using a computer system, in response to a reader's request for display of electronic text, to automatically identify and provide additional reading material related to concepts referred to within said electronic text comprising, in sequence, the steps of: a) on a client system, a.1. accepting a request for display of electronic text; a.2. sending said request for display of electronic text over a network; a.3. receiving said electronic text, said electronic text containing at least one text section; and a.4. without further user input, sending a search request over said network, from said client system, for additional information related to a concept referred to in said at least one text section; and b) on a server system, responsive to step (a.4) b.1. searching an index, wherein i) said index contains a plurality of terms by which it may be searched; ii) substantially all terms in said index are associated with at least one pointer to a text section; and iii) at least one term in said index is associated with a plurality of pointers, at least two of said plurality of pointers pointing to different text sections; b.2. as a result of step (b.1), identifying additional reading material related to said concept; and b.3. providing, via the network, to said client system, for display on the same page as a portion of the electronic text section referred to in step (a.3), an indicator of said additional reading material identified in step (b.2). | 1. A method for using a computer system, in response to a reader's request for display of electronic text, to automatically identify and provide additional reading material related to concepts referred to within said electronic text comprising, in sequence, the steps of: a) on a client system, a.1. accepting a request for display of electronic text; a.2. sending said request for display of electronic text over a network; a.3. receiving said electronic text, said electronic text containing at least one text section; and a.4. without further user input, sending a search request over said network, from said client system, for additional information related to a concept referred to in said at least one text section; and b) on a server system, responsive to step (a.4) b.1. searching an index, wherein i) said index contains a plurality of terms by which it may be searched; ii) substantially all terms in said index are associated with at least one pointer to a text section; and iii) at least one term in said index is associated with a plurality of pointers, at least two of said plurality of pointers pointing to different text sections; b.2. as a result of step (b.1), identifying additional reading material related to said concept; and b.3. providing, via the network, to said client system, for display on the same page as a portion of the electronic text section referred to in step (a.3), an indicator of said additional reading material identified in step (b.2). 9. The method of claim 1 , wherein said search request comprises additional information from said client computer. | 0.779923 |
8,180,633 | 16 | 19 | 16. A neural network implemented in a computer readable non-transitory storage medium comprising a computer readable program, wherein the computer readable program when executed on a computer performs semantic extraction and semantic role labeling, comprising: an indexer configured to index an input sentence and provide position information for a word of interest and a verb of interest; at least one lookup table for converting words into vectors using features obtained from the indexer for the input sentence; a first linear layer configured to integrate verb position in the input sentence of the verb of interest into a block-column structure that is adapted to the input sentence; and a second linear layer configured to perform a linear transformation using the block-column structure and the word vectors; and a squashing layer configured to interpret outputs of the linear layer as class probabilities for semantic role labels for the input sentence. | 16. A neural network implemented in a computer readable non-transitory storage medium comprising a computer readable program, wherein the computer readable program when executed on a computer performs semantic extraction and semantic role labeling, comprising: an indexer configured to index an input sentence and provide position information for a word of interest and a verb of interest; at least one lookup table for converting words into vectors using features obtained from the indexer for the input sentence; a first linear layer configured to integrate verb position in the input sentence of the verb of interest into a block-column structure that is adapted to the input sentence; and a second linear layer configured to perform a linear transformation using the block-column structure and the word vectors; and a squashing layer configured to interpret outputs of the linear layer as class probabilities for semantic role labels for the input sentence. 19. The neural network as recited in claim 16 , wherein the neural network architecture includes a multi-layer perceptron. | 0.768939 |
7,711,573 | 203 | 204 | 203. A system for using a computer to improve a precision ratio when searching a resume database, comprising: means for receiving a resume; means for parsing the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; means for storing the resume in the resume database; means for creating a parsed resume based on the resume, the parsed resume including each said at least one skill or experience-related phrase located in the resume, the term of experience computed for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase; means for storing the parsed resume in the resume database; means for sending a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and means for receiving a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. | 203. A system for using a computer to improve a precision ratio when searching a resume database, comprising: means for receiving a resume; means for parsing the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; means for storing the resume in the resume database; means for creating a parsed resume based on the resume, the parsed resume including each said at least one skill or experience-related phrase located in the resume, the term of experience computed for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase; means for storing the parsed resume in the resume database; means for sending a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and means for receiving a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. 204. The system of claim 203 , wherein the received resume is one of a number of resumes. | 0.912229 |
8,533,188 | 8 | 10 | 8. The method of claim 1 , wherein ranking the set of indexed semantic user profiles employs a ranking model developed using machine learning. | 8. The method of claim 1 , wherein ranking the set of indexed semantic user profiles employs a ranking model developed using machine learning. 10. The method of claim 8 , further comprising developing the ranking model offline. | 0.5 |
9,032,364 | 9 | 11 | 9. A computer program product comprising a computer usable storage medium embodying computer usable program code for configuring a test plan for serialization, the computer program product comprising: computer usable program code for selecting a template of the test plan through a graphical user interface of a test plan markup generation module executing in memory by a processor of a host computer; computer usable program code for extracting a table of contents from the selected template, the table of contents including at least one reference to at least one test case; and, computer usable program code for transforming at least one portion of the table of contents including the at least one test case into a markup language representation of the selected template of the test plan. | 9. A computer program product comprising a computer usable storage medium embodying computer usable program code for configuring a test plan for serialization, the computer program product comprising: computer usable program code for selecting a template of the test plan through a graphical user interface of a test plan markup generation module executing in memory by a processor of a host computer; computer usable program code for extracting a table of contents from the selected template, the table of contents including at least one reference to at least one test case; and, computer usable program code for transforming at least one portion of the table of contents including the at least one test case into a markup language representation of the selected template of the test plan. 11. The computer program product of claim 9 , further comprising: computer usable program code for loading the markup language representation into a text editor; computer usable program code for accepting edits to the markup language representation through the text editor; and, computer usable program code for persisting the edited markup language representation in fixed storage as a customized markup language representation of the test plan. | 0.5 |
8,819,029 | 2 | 7 | 2. The method of claim 1 , comprising: receiving a second content item request that specifies a second phrase of one or more words; determining that two keywords in a same content distribution campaign are both eligible to be selected as a controlling keyword for the second content item request; identifying a tiebreaker rule based on data associated with the two keywords; identifying, from the two keywords, a second controlling keyword based on the tiebreaker rule; and providing, in response to the second request, data associated with the second controlling keyword. | 2. The method of claim 1 , comprising: receiving a second content item request that specifies a second phrase of one or more words; determining that two keywords in a same content distribution campaign are both eligible to be selected as a controlling keyword for the second content item request; identifying a tiebreaker rule based on data associated with the two keywords; identifying, from the two keywords, a second controlling keyword based on the tiebreaker rule; and providing, in response to the second request, data associated with the second controlling keyword. 7. The method of claim 2 , wherein identifying a second controlling keyword based on the tiebreaker rule comprises: determining that a first keyword from the two keywords has a less specific match with the phrase than a second keyword from the two keywords; determining that a first quality score for the first keyword exceeds a second quality score for the second keyword; associating, with the first keyword, an adjusted bid that does not exceed a maximum bid associated with the second keyword; ranking the first keyword and second keyword based on selection scores, a selection score for the first keyword being based on the adjusted bid and the first quality score, a selection score for the second keyword being based on the maximum bid and the second quality score; and selecting, as the second controlling keyword, a highest ranking keyword. | 0.5 |
8,661,029 | 18 | 20 | 18. The computer-readable medium of claim 13 wherein the weight is further based on using a viewing length differentiator. | 18. The computer-readable medium of claim 13 wherein the weight is further based on using a viewing length differentiator. 20. The computer-readable medium of claim 18 , wherein the viewing length differentiator includes a factor governed by a determined type of a user generating the individual selections, and the weight is further based at least in part on the determined type of the user. | 0.5 |
7,752,417 | 1 | 3 | 1. A computer-implemented method, comprising, during execution of a first application: receiving, on behalf of said first application, a first memory request directed to a first virtual memory address; translating said first virtual memory address to a corresponding first physical address according to a first address translation technique; analyzing performance of said first application; dynamically selecting a second address translation technique for translating virtual memory addresses to corresponding physical memory addresses on behalf of said first application; and subsequent to said selecting a second address translation technique, receiving, on behalf of said first application, a second memory request directed to a second virtual memory address, and translating said second virtual memory address to a corresponding second physical address according to said second address translation technique; wherein said dynamically selecting a second address translation technique is dependent, at least in part, on a user policy and on results of said analyzing; and wherein said dynamically selecting and said translating according to said second address translation technique are performed transparently to said first application. | 1. A computer-implemented method, comprising, during execution of a first application: receiving, on behalf of said first application, a first memory request directed to a first virtual memory address; translating said first virtual memory address to a corresponding first physical address according to a first address translation technique; analyzing performance of said first application; dynamically selecting a second address translation technique for translating virtual memory addresses to corresponding physical memory addresses on behalf of said first application; and subsequent to said selecting a second address translation technique, receiving, on behalf of said first application, a second memory request directed to a second virtual memory address, and translating said second virtual memory address to a corresponding second physical address according to said second address translation technique; wherein said dynamically selecting a second address translation technique is dependent, at least in part, on a user policy and on results of said analyzing; and wherein said dynamically selecting and said translating according to said second address translation technique are performed transparently to said first application. 3. The method of claim 1 , wherein said analyzing performance of said first application comprises: measuring one or more of: a number of translation lookaside buffer (TLB) misses, a number of trap handler calls, a memory access time, a number of table look-up operations, a distribution of memory accesses, and a size of a data structure; and comparing results of said measuring to one or more performance criteria. | 0.745711 |
4,493,655 | 9 | 10 | 9. A radio-controlled teaching device comprising in combination: a teacher transmitter unit containing tone generation means, timing means associated with and controlling the duration of tones generated by said tone generation means, a first manual switching means operatively connected to said timing means for actuating said timing means and said tone generation means at selected points during oral reading of textual or test material, counting and readout means operatively associated with said timing means for counting and displaying the number of times said tone generation means are actuated, manual reset means operatively connected to said counting and readout means for selectively resetting said readout means to zero, a radio transmitter operatively coupled to the output of said tone generation means for transmitting tones generated by said tone generation means, a second manual switching means operatively connected between said timing means and associated timing resistors for reducing the duration of said timing means when using said teacher transmitter unit as a tone signal source for recording tone signals at designated points on one channel of a plural tape record during the recording of programmed instruction, and an audio output jack operatively connected to the output of said tone generation means for connecting said teacher transmitter unit to one record input of a plural channel tape recorder during said recording of programmed instruction; and a plurality of portable student receiver units containing a battery power supply, a radio receiver tuned to the carrier frequency of said transmitter, a tone decoder operatively connected to the output of said radio receiver, a first timing means operatively connected to and actuated by the output of said tone decoder for providing a short time period during which a student is expected to respond at said selected points during oral reading of textual or test material, a response switch which is momentarily closed by the student at said selected points during oral reading of textual or test material, a second timing means operatively connected to and actuated by said response switch for providing a brief time period when said response switch is momentarily closed, a first logic gate and a second logic gate operatively connected to said first and second timing means, wherein a "right" pulse is conducted by said first logic gate when said response switch is momentarily closed during said short time period of said first timing means and, wherein a "wrong" pulse is conducted by said second logic gate when said response switch is momentarily closed when said short time period of said first timing means is not occuring, a third timing means operatively connected to the outputs of said first logic gate and second logic gate and actuated by said "right" pulse or "wrong" pulse for momentarily disabling said second timing means and said first logic gate and second logic gate when said response switch is momentarily closed, a first counter opearatively connected to the output of said first logic gate, whereby a said "right" pulse advances said first counter one count when said "right" pulse occurs, a second counter operatively connected to said second logic gate, whereby said "wrong" pulse advances said second counter one count when said "wrong" pulse occurs, first decoder/drivers and liquid crystal readouts operatively connected to the outputs of said first counter for displaying the current count of said first counter, and second decoder/drivers and liquid crystal readouts operatively connected to the outputs of said second counter for displaying the current count of said second counter. | 9. A radio-controlled teaching device comprising in combination: a teacher transmitter unit containing tone generation means, timing means associated with and controlling the duration of tones generated by said tone generation means, a first manual switching means operatively connected to said timing means for actuating said timing means and said tone generation means at selected points during oral reading of textual or test material, counting and readout means operatively associated with said timing means for counting and displaying the number of times said tone generation means are actuated, manual reset means operatively connected to said counting and readout means for selectively resetting said readout means to zero, a radio transmitter operatively coupled to the output of said tone generation means for transmitting tones generated by said tone generation means, a second manual switching means operatively connected between said timing means and associated timing resistors for reducing the duration of said timing means when using said teacher transmitter unit as a tone signal source for recording tone signals at designated points on one channel of a plural tape record during the recording of programmed instruction, and an audio output jack operatively connected to the output of said tone generation means for connecting said teacher transmitter unit to one record input of a plural channel tape recorder during said recording of programmed instruction; and a plurality of portable student receiver units containing a battery power supply, a radio receiver tuned to the carrier frequency of said transmitter, a tone decoder operatively connected to the output of said radio receiver, a first timing means operatively connected to and actuated by the output of said tone decoder for providing a short time period during which a student is expected to respond at said selected points during oral reading of textual or test material, a response switch which is momentarily closed by the student at said selected points during oral reading of textual or test material, a second timing means operatively connected to and actuated by said response switch for providing a brief time period when said response switch is momentarily closed, a first logic gate and a second logic gate operatively connected to said first and second timing means, wherein a "right" pulse is conducted by said first logic gate when said response switch is momentarily closed during said short time period of said first timing means and, wherein a "wrong" pulse is conducted by said second logic gate when said response switch is momentarily closed when said short time period of said first timing means is not occuring, a third timing means operatively connected to the outputs of said first logic gate and second logic gate and actuated by said "right" pulse or "wrong" pulse for momentarily disabling said second timing means and said first logic gate and second logic gate when said response switch is momentarily closed, a first counter opearatively connected to the output of said first logic gate, whereby a said "right" pulse advances said first counter one count when said "right" pulse occurs, a second counter operatively connected to said second logic gate, whereby said "wrong" pulse advances said second counter one count when said "wrong" pulse occurs, first decoder/drivers and liquid crystal readouts operatively connected to the outputs of said first counter for displaying the current count of said first counter, and second decoder/drivers and liquid crystal readouts operatively connected to the outputs of said second counter for displaying the current count of said second counter. 10. A radio-controlled teaching device according to claim 9, wherein said second manual switching means of said teacher transmitter unit further comprise a DPDT switch, the second terminals of said DPDT switch simultaneously disabling said radio transmitter during said recording of programmed instruction. | 0.5 |
9,753,753 | 13 | 15 | 13. A non-transitory computer-readable medium storing a set of instructions that, when executed by a hardware processor, causes the hardware processor to perform a Dynamic Java Message Service Emulation method, the method comprising: instantiating a Dynamic Enterprise Java Bean (DEJB); receiving, from a source system, a request at the DEJB, the request queued in a request queue of the source system, the request received in accordance with a priority level of the request; identifying, based on the request, a system for which system integration testing is to be performed; generating, based on identifying the system for which system integration testing is to be performed, a query for business rules for processing the request; receiving, responsive to the query, via a Java Bean framework, the business rules; configuring, via the Java Bean framework, the DEJB using the business rules; processing the request using the configured DEJB to perform integration testing of the system identified based on the request and generate a respective response; and providing, via the hardware processor, the response as an output of the configured DEJB. | 13. A non-transitory computer-readable medium storing a set of instructions that, when executed by a hardware processor, causes the hardware processor to perform a Dynamic Java Message Service Emulation method, the method comprising: instantiating a Dynamic Enterprise Java Bean (DEJB); receiving, from a source system, a request at the DEJB, the request queued in a request queue of the source system, the request received in accordance with a priority level of the request; identifying, based on the request, a system for which system integration testing is to be performed; generating, based on identifying the system for which system integration testing is to be performed, a query for business rules for processing the request; receiving, responsive to the query, via a Java Bean framework, the business rules; configuring, via the Java Bean framework, the DEJB using the business rules; processing the request using the configured DEJB to perform integration testing of the system identified based on the request and generate a respective response; and providing, via the hardware processor, the response as an output of the configured DEJB. 15. The medium of claim 13 , wherein the DEJB is configured using the business rules to emulate the system for which system integration testing is to be performed. | 0.573298 |
7,865,358 | 15 | 16 | 15. A method as set forth in claim 12 , wherein said step of second using comprises modifying said first transformation information to establish modified first transformation information and said method further comprises the step of exporting said modified first transformation information to said first storage structure. | 15. A method as set forth in claim 12 , wherein said step of second using comprises modifying said first transformation information to establish modified first transformation information and said method further comprises the step of exporting said modified first transformation information to said first storage structure. 16. A method as set forth in claim 15 , further comprising the step of operating said computer-based processing tool to address any potential inconsistencies between said first transformation information and said modified first transformation information. | 0.5 |
5,515,455 | 7 | 8 | 7. The method according to claim 1 wherein said classifying comprises: determining the length and direction of each of said primitives; and comparing said length, direction and sequence of said primitives for said word with primitives of words stored in a memory device and generating a list of words having a high probability of matching said word. | 7. The method according to claim 1 wherein said classifying comprises: determining the length and direction of each of said primitives; and comparing said length, direction and sequence of said primitives for said word with primitives of words stored in a memory device and generating a list of words having a high probability of matching said word. 8. The method according to claim 7 wherein said step of determining the length and direction comprises: counting the number of said pixels constituting said primitive, said primitive having an original feature point and a terminal feature point; and measuring: the angle formed with horizontal by an imaginary straight line between said original and terminal feature points, the angle formed with horizontal by an imaginary straight line between said original feature point and a pixel adjacent said original feature point; and the angle formed with horizontal by an imaginary straight line between said terminal feature point and a pixel adjacent said terminal feature point. | 0.5 |
7,493,327 | 13 | 26 | 13. A computer-readable storage media embodying a schema comprising: multiple nodes arranged in a hierarchical structure, wherein the hierarchical structure describes a printer's properties and capabilities; wherein individual nodes are associated with printer properties or data values; and wherein the schema is protocol-independent allowing one or more standardized schema queries to be constructed by one or more devices to query the printer for information associated with its properties and capabilities, wherein each of the one or more schema queries is defined by the schema, at least one schema query being directed to discovering a particular data value by having syntax expressly identifying a data value node associated with the particular data value, and wherein one property node comprises at least one of: a printer information node that pertains to data that is associated with the printer, wherein the printer information node comprises a child manufacturer node associated with a printer manufacturer; a configuration node that pertains to configuration data that is associated with the printer, and wherein the configuration node comprises at least one of: a child memory node that contains values associated with the memory installed on the printer, and wherein the memory node comprises a child node associated with memory size and a child node associated with an amount of memory available to a Postscript interpreter; or a child hard disk node that contains values associated with a hard disk that is installed on the printer, and wherein the hard disk node comprises a child node that represents whether a hard disk is installed on the printer, a child node that represents the capacity of an installed hard disk, and a child node that represents currently available free space of an installed hard disk; a consumables node that pertains to information associated with consumable supplies in the printer, and wherein the consumables node comprises a child type node that corresponds to a consumable type on the printer, wherein the child type node comprises a child color node that corresponds to the color of a consumable, wherein the color node comprises a child installed node that represents whether a consumable is installed on the printer, a child display name node that represents a localized name for a particular consumable, and a child level node that represents a current level of a referenced consumable; or a layout node that pertains to data associated with how a print job is applied on a page, wherein the layout node comprises a child number up node that contains information associated with how many logical pages should be placed on a single page of media and which direction to layout multiple pages. | 13. A computer-readable storage media embodying a schema comprising: multiple nodes arranged in a hierarchical structure, wherein the hierarchical structure describes a printer's properties and capabilities; wherein individual nodes are associated with printer properties or data values; and wherein the schema is protocol-independent allowing one or more standardized schema queries to be constructed by one or more devices to query the printer for information associated with its properties and capabilities, wherein each of the one or more schema queries is defined by the schema, at least one schema query being directed to discovering a particular data value by having syntax expressly identifying a data value node associated with the particular data value, and wherein one property node comprises at least one of: a printer information node that pertains to data that is associated with the printer, wherein the printer information node comprises a child manufacturer node associated with a printer manufacturer; a configuration node that pertains to configuration data that is associated with the printer, and wherein the configuration node comprises at least one of: a child memory node that contains values associated with the memory installed on the printer, and wherein the memory node comprises a child node associated with memory size and a child node associated with an amount of memory available to a Postscript interpreter; or a child hard disk node that contains values associated with a hard disk that is installed on the printer, and wherein the hard disk node comprises a child node that represents whether a hard disk is installed on the printer, a child node that represents the capacity of an installed hard disk, and a child node that represents currently available free space of an installed hard disk; a consumables node that pertains to information associated with consumable supplies in the printer, and wherein the consumables node comprises a child type node that corresponds to a consumable type on the printer, wherein the child type node comprises a child color node that corresponds to the color of a consumable, wherein the color node comprises a child installed node that represents whether a consumable is installed on the printer, a child display name node that represents a localized name for a particular consumable, and a child level node that represents a current level of a referenced consumable; or a layout node that pertains to data associated with how a print job is applied on a page, wherein the layout node comprises a child number up node that contains information associated with how many logical pages should be placed on a single page of media and which direction to layout multiple pages. 26. The computer-readable storage media of claim 13 , wherein the layout node comprises a child orientation node that contains information associated with which orientation pages should be printed. | 0.909049 |
8,700,673 | 1 | 2 | 1. A method comprising: accessing metadata items that specify at least structural constraints on data objects within a data repository, the metadata items being separate from the data objects for which the metadata items specify the structural constraints; generating an index, the index mapping the metadata items to terms associated with the metadata items; generating a graph describing relationships between each of the metadata items; receiving a search request comprising at least one or more search terms; based on the one or more search terms and the index, locating a candidate set of the metadata items; performing a link analysis of the graph to determine a relationship score for each particular metadata item in at least the candidate set of metadata items; for each particular metadata item in the candidate set of the metadata items, calculating a ranking score based at least on the relationship score for the particular metadata item; generating a ranked result set based on comparing the ranking scores for the candidate set of metadata items, the ranked result set including at least one metadata item in the candidate set; providing information indicating the ranked result set in response to the search request; wherein the method is performed by one or more computing devices. | 1. A method comprising: accessing metadata items that specify at least structural constraints on data objects within a data repository, the metadata items being separate from the data objects for which the metadata items specify the structural constraints; generating an index, the index mapping the metadata items to terms associated with the metadata items; generating a graph describing relationships between each of the metadata items; receiving a search request comprising at least one or more search terms; based on the one or more search terms and the index, locating a candidate set of the metadata items; performing a link analysis of the graph to determine a relationship score for each particular metadata item in at least the candidate set of metadata items; for each particular metadata item in the candidate set of the metadata items, calculating a ranking score based at least on the relationship score for the particular metadata item; generating a ranked result set based on comparing the ranking scores for the candidate set of metadata items, the ranked result set including at least one metadata item in the candidate set; providing information indicating the ranked result set in response to the search request; wherein the method is performed by one or more computing devices. 2. The method of claim 1 , further comprising: determining one or more term scores for at least each particular metadata item in the candidate set of metadata items, the one or more term scores being based on at least one of the frequency with which the term appears in the particular metadata item or the frequency with which the term appears in all of the metadata items; wherein calculating the ranking score for each particular metadata item is further based on the one or more term scores for the particular metadata item. | 0.707547 |
8,972,259 | 14 | 18 | 14. A non-transitory processor-readable medium storing code representing instructions to be executed by a processor, the code comprising code to cause the processor to: encode a first prosodic speech signal to generate a musically encoded first prosodic speech signal by mapping each syllable of the first prosodic speech signal to a musical note; store the musically encoded first prosodic speech signal; audibly play the musically encoded first prosodic speech signal to a language student; prompt the student to recite the speech segment from which the musically encoded first prosodic speech signal originated; record an utterance from the language student in response to the prompt; delexicalize the utterance to generate a second prosodic speech signal; and calculate at least one error signal based on a difference between: a difference between a duration of a first syllable in the first prosodic speech signal and a duration of a second syllable in the first prosodic speech signal, the first syllable in the first prosodic speech signal being non-adjacent to the second syllable in the first prosodic speech signal; and a difference between a duration of a first syllable in the second prosodic speech signal and a duration of a second syllable in the second prosodic speech signal, the first syllable in the second prosodic speech signal being non-adjacent to the second syllable in the second prosodic speech signal. | 14. A non-transitory processor-readable medium storing code representing instructions to be executed by a processor, the code comprising code to cause the processor to: encode a first prosodic speech signal to generate a musically encoded first prosodic speech signal by mapping each syllable of the first prosodic speech signal to a musical note; store the musically encoded first prosodic speech signal; audibly play the musically encoded first prosodic speech signal to a language student; prompt the student to recite the speech segment from which the musically encoded first prosodic speech signal originated; record an utterance from the language student in response to the prompt; delexicalize the utterance to generate a second prosodic speech signal; and calculate at least one error signal based on a difference between: a difference between a duration of a first syllable in the first prosodic speech signal and a duration of a second syllable in the first prosodic speech signal, the first syllable in the first prosodic speech signal being non-adjacent to the second syllable in the first prosodic speech signal; and a difference between a duration of a first syllable in the second prosodic speech signal and a duration of a second syllable in the second prosodic speech signal, the first syllable in the second prosodic speech signal being non-adjacent to the second syllable in the second prosodic speech signal. 18. The non-transitory processor-readable medium of claim 14 , wherein the musically encoded first prosodic speech signal is encoded in a musical instrument digital interface (MIDI) framework. | 0.875 |
8,359,190 | 9 | 10 | 9. The method of claim 8 , further comprising: for each portion i following the first portion, computing a second semantic position of the portion i based on a current semantic position and semantic portions of words in the portion i, and combining the current semantic position with the second semantic position to determine a new current semantic position to be used in determining a semantic position of a subsequent portion. | 9. The method of claim 8 , further comprising: for each portion i following the first portion, computing a second semantic position of the portion i based on a current semantic position and semantic portions of words in the portion i, and combining the current semantic position with the second semantic position to determine a new current semantic position to be used in determining a semantic position of a subsequent portion. 10. The method of claim 9 , wherein combining the current semantic position and the second semantic position of each portion i comprises performing a weighted avenge of the current semantic position and the second semantic position. | 0.5 |
9,697,192 | 19 | 20 | 19. A non-transitory computer-readable medium storing instructions which, when executed by one or more processors, cause one or more computers to perform functions that include: reading text data corresponding to one or more messages; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by at least one trained statistical language model trained by machine learning, one or more predictive labels as annotations corresponding to language patterns associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store, wherein the aggregating comprises constructing a global knowledge representation associated with the aggregated one or more annotated messages; and performing an automated process, based at least in part on the global knowledge representation, the automated process comprising one or more global analytics functions that include: (a) identifying an annotation error in the created one or more semantic annotations, (b) automatically updating the respective semantic annotation in the global knowledge representation to correct the annotation error, to form an updated semantic annotation, and (c) back-propagating the updated semantic annotation into training data for further language model training by machine learning, wherein the back-propagating comprises forming updated training data, that includes the updated semantic annotation, for additional training of the at least one statistical language model, wherein the additional training comprises training the at least one statistical language model to perform one or more local analytics functions and to generate predictive labels for additional semantic annotations to text data; and performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed. | 19. A non-transitory computer-readable medium storing instructions which, when executed by one or more processors, cause one or more computers to perform functions that include: reading text data corresponding to one or more messages; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by at least one trained statistical language model trained by machine learning, one or more predictive labels as annotations corresponding to language patterns associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store, wherein the aggregating comprises constructing a global knowledge representation associated with the aggregated one or more annotated messages; and performing an automated process, based at least in part on the global knowledge representation, the automated process comprising one or more global analytics functions that include: (a) identifying an annotation error in the created one or more semantic annotations, (b) automatically updating the respective semantic annotation in the global knowledge representation to correct the annotation error, to form an updated semantic annotation, and (c) back-propagating the updated semantic annotation into training data for further language model training by machine learning, wherein the back-propagating comprises forming updated training data, that includes the updated semantic annotation, for additional training of the at least one statistical language model, wherein the additional training comprises training the at least one statistical language model to perform one or more local analytics functions and to generate predictive labels for additional semantic annotations to text data; and performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed. 20. The non-transitory computer-readable medium of claim 19 , wherein the stored instructions, when executed by one or more processors, further cause the one or more computers to record the update to the semantic annotation in a change log prior to back-propagating the updated semantic annotation. | 0.615979 |
9,633,671 | 19 | 20 | 19. A media device according to claim 16 , wherein the noise suppressor applies a selected one of a spectral gain and a binary mask to the input signal responsive to the estimated signal-to-noise ratio of near-end speech in the input signal falling below a predefined signal-to-noise threshold. | 19. A media device according to claim 16 , wherein the noise suppressor applies a selected one of a spectral gain and a binary mask to the input signal responsive to the estimated signal-to-noise ratio of near-end speech in the input signal falling below a predefined signal-to-noise threshold. 20. A media device according to claim 19 , wherein the predefined signal-to-noise threshold comprises a first signal-to-noise threshold corresponding to a first frequency bin of the input signal, the spectral gain or the binary mask comprises a first spectral gain or a first binary mask, respectively, and the noise suppressor applies the selected one of the first spectral gain and the first binary mask to the first frequency bin of the input signal responsive to the estimated signal-to-noise ratio of near-end speech in the first frequency bin falling below the first signal-to-noise threshold, and wherein the noise suppressor applies a selected one of a second spectral gain and a second binary mask to a second frequency bin of the input signal in correspondence with an estimated signal-to-noise ratio of near-end speech in the second frequency bin of the input signal. | 0.5 |
10,127,245 | 9 | 16 | 9. A computing device for interpreting geographical search queries, the computing device comprising: one or more processors; and a non-transitory computer-readable memory coupled to the one or more processors and storing instructions thereon that, when executed by the one or more processors, cause the computing device to: receive a geographical search query from a client computer; obtain a plurality of geographical search queries, each of the plurality of geographical search queries having a plurality of terms; determine a plurality of query templates based on the plurality of geographical search queries, each of the plurality of query templates including an ordering of several geographic term types determined from the plurality of terms, wherein at least some of the plurality of query templates have a different ordering of geographic term types for different locales or languages; determine one or more query templates of the plurality of query templates corresponding to different locales or languages; provide the one or more query templates as one or more interpretation candidates for interpreting the geographical search query corresponding to a locale or language from which the geographical search query was received; and provide search results to the client computer for the geographical search query based on the one or more interpretation candidates. | 9. A computing device for interpreting geographical search queries, the computing device comprising: one or more processors; and a non-transitory computer-readable memory coupled to the one or more processors and storing instructions thereon that, when executed by the one or more processors, cause the computing device to: receive a geographical search query from a client computer; obtain a plurality of geographical search queries, each of the plurality of geographical search queries having a plurality of terms; determine a plurality of query templates based on the plurality of geographical search queries, each of the plurality of query templates including an ordering of several geographic term types determined from the plurality of terms, wherein at least some of the plurality of query templates have a different ordering of geographic term types for different locales or languages; determine one or more query templates of the plurality of query templates corresponding to different locales or languages; provide the one or more query templates as one or more interpretation candidates for interpreting the geographical search query corresponding to a locale or language from which the geographical search query was received; and provide search results to the client computer for the geographical search query based on the one or more interpretation candidates. 16. The computing device of claim 9 , wherein the plurality of query templates are determined based on the plurality of geographical search queries and user actions associated with the plurality of geographical search queries, the user actions including at least one of: (i) selecting a search result or (ii) refining the geographical search query. | 0.640496 |
7,930,183 | 8 | 13 | 8. A computer implemented method of analyzing dialog between a user and an interactive application having dialog turns, wherein a turn comprises a prompt from the application and a response received from the user, the method comprising: accessing stored log data including information indicative of a plurality of dialog turns between the application and at least one user, the stored log data comprising recorded audio; identifying at least one failed recognition situation from the information indicative of the plurality of dialog turns between the application and at least one user; based on identifying the at least one failed recognition situation, accessing the recorded audio to identify a portion of expected audio that was received by the application when the application was expecting a response from the at least one user for a prompt that was given, the prompt being associated with the at least one failed recognition situation; accessing the recorded audio to identify a portion of unexpected audio that was received by the application when the application was not expecting a response from the at least one user for the prompt that was given; isolating the portion of expected audio and the portion of unexpected audio to form an actual response provided by the user, the actual response including both the expected audio and the unexpected audio; and performing recognition on the actual response using a processor of the computer. | 8. A computer implemented method of analyzing dialog between a user and an interactive application having dialog turns, wherein a turn comprises a prompt from the application and a response received from the user, the method comprising: accessing stored log data including information indicative of a plurality of dialog turns between the application and at least one user, the stored log data comprising recorded audio; identifying at least one failed recognition situation from the information indicative of the plurality of dialog turns between the application and at least one user; based on identifying the at least one failed recognition situation, accessing the recorded audio to identify a portion of expected audio that was received by the application when the application was expecting a response from the at least one user for a prompt that was given, the prompt being associated with the at least one failed recognition situation; accessing the recorded audio to identify a portion of unexpected audio that was received by the application when the application was not expecting a response from the at least one user for the prompt that was given; isolating the portion of expected audio and the portion of unexpected audio to form an actual response provided by the user, the actual response including both the expected audio and the unexpected audio; and performing recognition on the actual response using a processor of the computer. 13. The method of claim 8 , wherein the accessed information comprising information related to operation of the application for the at least one failed recognition situation, wherein performing recognition on the actual response comprises performing recognition using a second grammar, wherein terms from the prompt are added to the second grammar. | 0.5 |
9,262,474 | 15 | 16 | 15. The computer program product of claim 14 , wherein the user input includes a string name of a model object. | 15. The computer program product of claim 14 , wherein the user input includes a string name of a model object. 16. The computer program product of claim 15 , further comprising including the string name in the dynamically built query expression which is executed to identify current service features for one or more services offered by the one or more back-end servers, and using the string name to locate at the dynamic system model a metadata object corresponding to the string name. | 0.5 |
7,711,573 | 376 | 379 | 376. The method of claim 375 , wherein the required term of experience is rounded up to a unit of time. | 376. The method of claim 375 , wherein the required term of experience is rounded up to a unit of time. 379. The method of claim 376 , wherein the unit of time is not an integer. | 0.905612 |
7,480,856 | 13 | 14 | 13. An apparatus for processing one or more XML documents where the processing includes a plurality of stylesheets using an abstract machine, the apparatus comprising: a processor; a memory coupled to the processor; means for reading a stylesheet of the plurality of stylesheets; means for parsing at least some Xpath expressions within the plurality of stylesheets into a respective tree of nodes; means for annotating the respective tree of nodes of the Xpath expressions with a data type of the Xpath expression; means for compiling the respective annotated tree of nodes of the Xpath expressions into a set of abstract machine instructions specialized for stylesheet processing, wherein the set of abstract machine instructions comprises a plurality of blocks of abstract machine instructions for the compiled stylesheet and includes a backtracking abstract machine instruction for each block of the plurality of blocks; and means for executing the instructions on an abstract machine to produce an output document, wherein the abstract machine uses a plurality of types of contiguous memory storage to match requirements of the stylesheet processing and wherein the plurality of types of contiguous memory storage includes a code stack, a heap stack and a transform allocator; means for resetting the code stack and the heap stack upon processing completing of each block of the plurality of blocks; and means for calling a block of the plurality of blocks via a pattern match for imports which calls a template that can match with a lower import precedence than a current template, wherein the executing the abstract machine instruction set in the abstract machine further comprises means for processing a representation of the one or more XML documents. | 13. An apparatus for processing one or more XML documents where the processing includes a plurality of stylesheets using an abstract machine, the apparatus comprising: a processor; a memory coupled to the processor; means for reading a stylesheet of the plurality of stylesheets; means for parsing at least some Xpath expressions within the plurality of stylesheets into a respective tree of nodes; means for annotating the respective tree of nodes of the Xpath expressions with a data type of the Xpath expression; means for compiling the respective annotated tree of nodes of the Xpath expressions into a set of abstract machine instructions specialized for stylesheet processing, wherein the set of abstract machine instructions comprises a plurality of blocks of abstract machine instructions for the compiled stylesheet and includes a backtracking abstract machine instruction for each block of the plurality of blocks; and means for executing the instructions on an abstract machine to produce an output document, wherein the abstract machine uses a plurality of types of contiguous memory storage to match requirements of the stylesheet processing and wherein the plurality of types of contiguous memory storage includes a code stack, a heap stack and a transform allocator; means for resetting the code stack and the heap stack upon processing completing of each block of the plurality of blocks; and means for calling a block of the plurality of blocks via a pattern match for imports which calls a template that can match with a lower import precedence than a current template, wherein the executing the abstract machine instruction set in the abstract machine further comprises means for processing a representation of the one or more XML documents. 14. The apparatus of claim 13 wherein at least some of the set of abstract machine instructions further comprise abstract machine instructions for tree searches of the one or more XML documents. | 0.587234 |
8,706,715 | 23 | 24 | 23. A system for improving a query in a multi-tenant database system, the system comprising: a processor; a network interface; and a computer-readable medium tangibly embodied with instructions to: receiving at a network interface of a server in a multi-tenant database system an original query transmitted to the multi-tenant database system by a user associated with a tenant, wherein the original query is associated with data accessible only by the tenant, and wherein the multi-tenant database system includes at least a first index and a second index, wherein the first index is a standard index and wherein the second index is a custom index to provide a private sharing paradigm within the multi-tenant database system that allows groups defined within one or more particular tenants to share information only among members of that group; retrieving, using a processor of the server, metadata associated with the data accessible only by the tenant in the multi-tenant database system, wherein at least a portion of the data accessible only by the tenant is stored in a common table within the multi-tenant database system; scanning a first index column to identify a first set of rows, wherein the first index column is selected based on the original query; scanning a second index column to identify a second set of rows, wherein the second index column is based on the original query; determining a third set of rows corresponding to an intersection of the first set of rows and the second set of rows; determining, using the processor, a tenant-selective query syntax, wherein determining comprises analyzing at least one of metadata generated from information about the tenant or metadata generated from the data accessible by the tenant; and generating, using the processor, an improved query using the query syntax, wherein the improved query is based upon the original query and the third set of rows. | 23. A system for improving a query in a multi-tenant database system, the system comprising: a processor; a network interface; and a computer-readable medium tangibly embodied with instructions to: receiving at a network interface of a server in a multi-tenant database system an original query transmitted to the multi-tenant database system by a user associated with a tenant, wherein the original query is associated with data accessible only by the tenant, and wherein the multi-tenant database system includes at least a first index and a second index, wherein the first index is a standard index and wherein the second index is a custom index to provide a private sharing paradigm within the multi-tenant database system that allows groups defined within one or more particular tenants to share information only among members of that group; retrieving, using a processor of the server, metadata associated with the data accessible only by the tenant in the multi-tenant database system, wherein at least a portion of the data accessible only by the tenant is stored in a common table within the multi-tenant database system; scanning a first index column to identify a first set of rows, wherein the first index column is selected based on the original query; scanning a second index column to identify a second set of rows, wherein the second index column is based on the original query; determining a third set of rows corresponding to an intersection of the first set of rows and the second set of rows; determining, using the processor, a tenant-selective query syntax, wherein determining comprises analyzing at least one of metadata generated from information about the tenant or metadata generated from the data accessible by the tenant; and generating, using the processor, an improved query using the query syntax, wherein the improved query is based upon the original query and the third set of rows. 24. The system of claim 23 , wherein the computer-readable medium is tangibly embodied with further instructions to: receiving information identifying the user; retrieving, using the processor, metadata about the user; and wherein determining, using the processor, comprises analyzing at least one of the group consisting of metadata generated from information about the user, metadata generated from information about the tenant, and metadata generated from the data accessible by the tenant. | 0.5 |
9,507,867 | 1 | 4 | 1. A system for semantically searching a group of documents containing words, exclusive of stop words of the documents, thereby improving efficiency by flatly looking at the words being searched without attempting to understand the meaning of the words, comprising: a memory containing a set of instructions; and a processor for processing the set of instructions, wherein the instructions cause the processor to perform a method comprising: receiving by the processor a current instance of a search criteria containing words; determining by the processor a first total number of the words, exclusive of stop words, in the current instance of the search criteria; storing in the memory by the processor the first total number; for each of the words, exclusive of stop words, respectively, in the current instance of the search criteria, determining by the processor a respective first number of times that the word appears in the current instance of the search criteria; storing in the memory by the processor the respective first number of times; for each of the words, exclusive of stop words, respectively, in the current instance of the search criteria, calculating by the processor a first uniqueness score, respectively, for the word, respectively, based on the respective first number and the first total number; storing in the memory by the processor the first uniqueness score, respectively, for the word, respectively; for each of the words, exclusive of stop words, respectively, of the current instance of the search criteria and the documents, determining by the processor a respective second number of times that the word appears in the current instance of the search criteria and the documents; storing in the memory by the processor the respective second number of times, as a first frequency score, respectively; for each of the words, exclusive of stop words, of the current instance of the search criteria and the each of the documents, respectively, calculating by the processor a respective first significance magnitude factor based on the first frequency score, respectively, and the first uniqueness score, respectively; storing in the memory by the processor the respective first significance magnitude factor; determining by the processor a second total number of the words, exclusive of stop words, in the documents of the group; storing in the memory by the processor the second total number; for each of the words, exclusive of stop words, respectively, of the documents, respectively, determining by the processor a respective third number of times that the word appears in the documents of the group; storing in the memory by the processor the respective third number of times; for each of the words, exclusive of stop words, respectively, of the documents, calculating by the processor a second uniqueness score, respectively, for the word, respectively, based on the respective third number and the second total number; storing in the memory by the processor the second uniqueness score, respectively, for the word, respectively; for each of the words, exclusive of stop words of the documents, respectively, in each of the documents, respectively, determining by the processor a respective fourth number of times that the word appears in the document; storing in the memory by the processor the respective fourth number, as a second frequency score, respectively; for each of the words, exclusive of stop words, of the documents, calculating by the processor a respective second significance magnitude factor based on the second frequency score, respectively, and the second uniqueness score, respectively; storing in the memory by the processor the respective second significance magnitude factor; and for each document of the group, generating by the processor a respective similarity score of contents of the document to the current instance of the search criteria, wherein generating the respective similarity score includes characterizing each document based on the respective second significance magnitude factor compared to the respective first significance magnitude factor. | 1. A system for semantically searching a group of documents containing words, exclusive of stop words of the documents, thereby improving efficiency by flatly looking at the words being searched without attempting to understand the meaning of the words, comprising: a memory containing a set of instructions; and a processor for processing the set of instructions, wherein the instructions cause the processor to perform a method comprising: receiving by the processor a current instance of a search criteria containing words; determining by the processor a first total number of the words, exclusive of stop words, in the current instance of the search criteria; storing in the memory by the processor the first total number; for each of the words, exclusive of stop words, respectively, in the current instance of the search criteria, determining by the processor a respective first number of times that the word appears in the current instance of the search criteria; storing in the memory by the processor the respective first number of times; for each of the words, exclusive of stop words, respectively, in the current instance of the search criteria, calculating by the processor a first uniqueness score, respectively, for the word, respectively, based on the respective first number and the first total number; storing in the memory by the processor the first uniqueness score, respectively, for the word, respectively; for each of the words, exclusive of stop words, respectively, of the current instance of the search criteria and the documents, determining by the processor a respective second number of times that the word appears in the current instance of the search criteria and the documents; storing in the memory by the processor the respective second number of times, as a first frequency score, respectively; for each of the words, exclusive of stop words, of the current instance of the search criteria and the each of the documents, respectively, calculating by the processor a respective first significance magnitude factor based on the first frequency score, respectively, and the first uniqueness score, respectively; storing in the memory by the processor the respective first significance magnitude factor; determining by the processor a second total number of the words, exclusive of stop words, in the documents of the group; storing in the memory by the processor the second total number; for each of the words, exclusive of stop words, respectively, of the documents, respectively, determining by the processor a respective third number of times that the word appears in the documents of the group; storing in the memory by the processor the respective third number of times; for each of the words, exclusive of stop words, respectively, of the documents, calculating by the processor a second uniqueness score, respectively, for the word, respectively, based on the respective third number and the second total number; storing in the memory by the processor the second uniqueness score, respectively, for the word, respectively; for each of the words, exclusive of stop words of the documents, respectively, in each of the documents, respectively, determining by the processor a respective fourth number of times that the word appears in the document; storing in the memory by the processor the respective fourth number, as a second frequency score, respectively; for each of the words, exclusive of stop words, of the documents, calculating by the processor a respective second significance magnitude factor based on the second frequency score, respectively, and the second uniqueness score, respectively; storing in the memory by the processor the respective second significance magnitude factor; and for each document of the group, generating by the processor a respective similarity score of contents of the document to the current instance of the search criteria, wherein generating the respective similarity score includes characterizing each document based on the respective second significance magnitude factor compared to the respective first significance magnitude factor. 4. The system of claim 1 wherein the method further comprises: sorting the respective similarity scores for at least a portion of the documents of the group for creating a set of the respective similarity scores associated with the current instance of the search criteria; enabling a document corresponding to one of the respective similarity scores of the set to be designated as a next instance of the search criteria; and causing the method to be performed for the next instance of the search criteria as the current instance of the search criteria. | 0.5 |
6,144,968 | 1 | 8 | 1. A computer software menu management system consisting of, storing a keyword in a controlled vocabulary and its predetermined code in a database that links each said keyword to a parent keyword at a parent level thereby creating a hierarchical organization that has a plurality of levels, selecting a set of keywords from said database that are linked to the same said parent keyword and are located at an identical level in said hierarchical organization, generating a list menu based on said set of keywords, adding a navigation control to said menu system, adding a search control to said menu system, displaying said list menu, fetching a selection made by an end-user associated with said navigation control, with said search control, and with said set of keywords in said list menu, generating another said list menu representing a parent and a child level in said hierarchical organization depending upon the type of navigation control selected by said end-user, fetching at least one said keyword selected by said end-user from said list menu selected when said search control is selected by said end-user, generating a database query that includes at least one said keyword selected by said end-user in said list menu when said search control is selected by said end-user. | 1. A computer software menu management system consisting of, storing a keyword in a controlled vocabulary and its predetermined code in a database that links each said keyword to a parent keyword at a parent level thereby creating a hierarchical organization that has a plurality of levels, selecting a set of keywords from said database that are linked to the same said parent keyword and are located at an identical level in said hierarchical organization, generating a list menu based on said set of keywords, adding a navigation control to said menu system, adding a search control to said menu system, displaying said list menu, fetching a selection made by an end-user associated with said navigation control, with said search control, and with said set of keywords in said list menu, generating another said list menu representing a parent and a child level in said hierarchical organization depending upon the type of navigation control selected by said end-user, fetching at least one said keyword selected by said end-user from said list menu selected when said search control is selected by said end-user, generating a database query that includes at least one said keyword selected by said end-user in said list menu when said search control is selected by said end-user. 8. The menu management system of claim 1 further includes a database query that includes a plurality of embedded expressions. | 0.648876 |
8,787,702 | 9 | 10 | 9. The method of claim 1 , further comprising: setting said current line of text to a new line of text; generating a per text line difference value for said current line of text; and updating the cumulative difference value based on the per text line difference value for the current line of text. | 9. The method of claim 1 , further comprising: setting said current line of text to a new line of text; generating a per text line difference value for said current line of text; and updating the cumulative difference value based on the per text line difference value for the current line of text. 10. The method of claim 9 , further comprising: inverting said page when said page is determined to be inverted; and storing, in memory, said inverted page in place of said page. | 0.5 |
5,528,742 | 10 | 13 | 10. A computer system for processing a document contained in a document file using an embedded font stored in a font file, the font file being contained in the document file, the document file having been created on a host computer, the computer system including a remote computer, the font file having an associated font file name, the embedded font stored in the font file having one of a plurality of font types, the computer system also including a software program that provides a plurality of functions, the system comprising: means for receiving the document file in the remote computer; means for retrieving the font file from the document file; means for assigning a new font file name to the retrieved font file; means for storing the retrieved font file under the new font name; means for determining the font type of the embedded font; means for determining if the embedded font type is a predetermined one of the plurality of font types; means for recognizing if a user of the remote computer has selected a predetermined one of the plurality of functions; and means for deleting the font file in response to the recognizing means recognizing the selection of the predetermined function. | 10. A computer system for processing a document contained in a document file using an embedded font stored in a font file, the font file being contained in the document file, the document file having been created on a host computer, the computer system including a remote computer, the font file having an associated font file name, the embedded font stored in the font file having one of a plurality of font types, the computer system also including a software program that provides a plurality of functions, the system comprising: means for receiving the document file in the remote computer; means for retrieving the font file from the document file; means for assigning a new font file name to the retrieved font file; means for storing the retrieved font file under the new font name; means for determining the font type of the embedded font; means for determining if the embedded font type is a predetermined one of the plurality of font types; means for recognizing if a user of the remote computer has selected a predetermined one of the plurality of functions; and means for deleting the font file in response to the recognizing means recognizing the selection of the predetermined function. 13. The system of claim 10 wherein the predetermined font type is a preview and print font type, and wherein the predetermined function is a function to edit the document file. | 0.704698 |
9,179,061 | 4 | 9 | 4. A computer-implemented method, comprising: acquiring an image of an object using a camera of a computing device; determining a foreground area and a background area of the image, the foreground area including a representation of the object, applying a color to the background area; cropping the image to remove the background area from the image; analyzing the foreground area to recognize text associated with the object; receiving a selection of at least one text input field; determining a set of words from recognized text that are associated with the at least one text input field; displaying a set of words from the recognized text; and enabling a user of the computing device to select at least one word from the set of words to perform at least one operation. | 4. A computer-implemented method, comprising: acquiring an image of an object using a camera of a computing device; determining a foreground area and a background area of the image, the foreground area including a representation of the object, applying a color to the background area; cropping the image to remove the background area from the image; analyzing the foreground area to recognize text associated with the object; receiving a selection of at least one text input field; determining a set of words from recognized text that are associated with the at least one text input field; displaying a set of words from the recognized text; and enabling a user of the computing device to select at least one word from the set of words to perform at least one operation. 9. The computer-implemented method of claim 4 , wherein the at least one operation includes at least one of submitting a product for purchase to an electronic marketplace, or copying the at least one word from the set of words to a clipboard, notepad, or browser. | 0.808588 |
9,032,343 | 3 | 4 | 3. The system of claim 1 , further comprising means for generating an exclusion list of resources to be reserved for the secret portion. | 3. The system of claim 1 , further comprising means for generating an exclusion list of resources to be reserved for the secret portion. 4. The system of claim 3 , wherein, based on the HDL or netlist implementation of the public portion without the secret portion included, the HDL or netlist implementation of the interface, and the exclusion list, a computer-aided design (CAD) or synthesis tool can integrate the public portion and the interface with a circuit design of the user to generate an integrated design in which the resources specified in the exclusion list are reserved for the secret portion. | 0.5 |
7,503,008 | 1 | 8 | 1. A method of dispensing notes from a note dispenser, the method comprising the steps, performed by a data processing system, of: moving an indicator of the data processing system to the note dispenser residing at a first location and activating a control while the indicator is over the note dispenser to pop up a note at a second location without moving the indicator to the second location, wherein the first and second locations are different locations moving the note to a third location by use of the indicator and, attaching the note to the third location only if the third location is a location that can accept the note. | 1. A method of dispensing notes from a note dispenser, the method comprising the steps, performed by a data processing system, of: moving an indicator of the data processing system to the note dispenser residing at a first location and activating a control while the indicator is over the note dispenser to pop up a note at a second location without moving the indicator to the second location, wherein the first and second locations are different locations moving the note to a third location by use of the indicator and, attaching the note to the third location only if the third location is a location that can accept the note. 8. The method of claim 1 further comprising the step of attaching the note to an object so that the note moves with the object. | 0.769928 |
8,436,753 | 1 | 7 | 1. A method comprising: reading compressed audio data from a first audio file, the first audio file comprising audio data compressed using a first compression algorithm and bookkeeping data having a first format, the bookkeeping data specifying a location of the compressed audio data within the first audio file; and generating a universal representation of the first audio file without decompressing and recompressing the audio data, the universal representation having bookkeeping data of a second format specifying the location of compressed audio data within the universal representation. | 1. A method comprising: reading compressed audio data from a first audio file, the first audio file comprising audio data compressed using a first compression algorithm and bookkeeping data having a first format, the bookkeeping data specifying a location of the compressed audio data within the first audio file; and generating a universal representation of the first audio file without decompressing and recompressing the audio data, the universal representation having bookkeeping data of a second format specifying the location of compressed audio data within the universal representation. 7. The method as in claim 1 wherein the bookkeeping data having the first format comprises an edit list with a media start time indicating the start of playable audio content within the first audio file and a duration indicating a length of the playable audio content within the first audio file. | 0.789474 |
9,542,612 | 4 | 5 | 4. The method of claim 1 , further comprising: generating a superresolution version of the candidate text region. | 4. The method of claim 1 , further comprising: generating a superresolution version of the candidate text region. 5. The method of claim 4 , wherein generating the superresolution version of the candidate text region comprises: obtaining a plurality of versions of the candidate text region, each version obtained from a corresponding image of the plurality of images; aligning the versions of the candidate text region to a high resolution grid; and compositing the aligned versions of the candidate text region to generate the superresolution version of the candidate text region. | 0.5 |
4,724,523 | 50 | 51 | 50. A method according to claim 44 in which said second pattern storing step comprises storing a signal representative of an exceptional inflectional form expression corresponding to at least one said partial paradigm-representative signal. | 50. A method according to claim 44 in which said second pattern storing step comprises storing a signal representative of an exceptional inflectional form expression corresponding to at least one said partial paradigm-representative signal. 51. A method according to claim 50 in which said exceptional inflectional expression-representative signal storing step comprises storing a signal indicative of at least one of a grammatical classification and an inflectional classification. | 0.510163 |
7,765,206 | 1 | 8 | 1. A Meta-Web apparatus, comprising: a browser for a user entering a search query and for displaying result pages to said user, the result pages comprising Web pages; a search engine for receiving said search query and for generating search results in response thereto; a registry for receiving and storing user annotations and other metadata; a Meta-Web server for creating said result pages dynamically from said search results generated by said search engine by performing a look-up in said registry to determine if there is a user annotation or other metadata associated with said search results and by ordering said search results according to their relevance, said relevance dynamically determined according to said user annotations and other metadata stored in said registry, said Meta-web server subsequently sending said result pages to said browser for viewing by said user entering said query; and an annotation bar for providing a mechanism to input said user annotations and other metadata to be stored in said registry, said annotation bar dynamically added to any content that is served to a user by said Meta-Web server; wherein said annotation bar comprises user-actuated buttons which provide functions that allow a user to comment, ask questions related to the search result, indicate that the search result is relevant, and to indicate that the search result is not relevant, all of which is stored in said registry; wherein each annotation provided by a user and stored in said registry dynamically alters subsequent searches, thereby providing more relevant search results; wherein said user selects portions of documents which are then used by said Meta-Web server to identify annotations in said registry and dynamically generate information relating thereto; a related items button for a portion of text that is highlighted by said user that provides related items and information for said highlighted text. | 1. A Meta-Web apparatus, comprising: a browser for a user entering a search query and for displaying result pages to said user, the result pages comprising Web pages; a search engine for receiving said search query and for generating search results in response thereto; a registry for receiving and storing user annotations and other metadata; a Meta-Web server for creating said result pages dynamically from said search results generated by said search engine by performing a look-up in said registry to determine if there is a user annotation or other metadata associated with said search results and by ordering said search results according to their relevance, said relevance dynamically determined according to said user annotations and other metadata stored in said registry, said Meta-web server subsequently sending said result pages to said browser for viewing by said user entering said query; and an annotation bar for providing a mechanism to input said user annotations and other metadata to be stored in said registry, said annotation bar dynamically added to any content that is served to a user by said Meta-Web server; wherein said annotation bar comprises user-actuated buttons which provide functions that allow a user to comment, ask questions related to the search result, indicate that the search result is relevant, and to indicate that the search result is not relevant, all of which is stored in said registry; wherein each annotation provided by a user and stored in said registry dynamically alters subsequent searches, thereby providing more relevant search results; wherein said user selects portions of documents which are then used by said Meta-Web server to identify annotations in said registry and dynamically generate information relating thereto; a related items button for a portion of text that is highlighted by said user that provides related items and information for said highlighted text. 8. The apparatus of claim 1 , wherein one or more items selected by said user lead to a product node, wherein said Meta-Web server performs an independent search to collect data with regard to a particular product, and wherein said Meta-Web server dynamically creates a Web page for said user that comprises information collected in real time. | 0.619734 |
9,626,348 | 1 | 4 | 1. A method, comprising: receiving, from a plurality of different computing devices and over a respective plurality of network connections, a plurality of data packets, wherein the plurality of different computing devices are operated by a plurality of different users, wherein each data packet in the plurality of data packets comprises: an annotation that has been assigned to a document by a respective user, wherein the annotation is a tuple that comprises a first word or phrase extracted from the document, a second word or phrase extracted from the document, and a third word or phrase extracted from the document, wherein the third word or phrase relates the first word or phrase to the second word or phrase; and relationship data that indicates that the annotation has been assigned to the document, wherein each data packet comprises a different annotation, and each data packet in the plurality of data packets has a same format; aggregating the plurality of data packets in a data repository to form a network of knowledge, wherein the data repository is accessible to a processor; and utilizing the processor to perform at least one processing function over at least one data packet in the data repository. | 1. A method, comprising: receiving, from a plurality of different computing devices and over a respective plurality of network connections, a plurality of data packets, wherein the plurality of different computing devices are operated by a plurality of different users, wherein each data packet in the plurality of data packets comprises: an annotation that has been assigned to a document by a respective user, wherein the annotation is a tuple that comprises a first word or phrase extracted from the document, a second word or phrase extracted from the document, and a third word or phrase extracted from the document, wherein the third word or phrase relates the first word or phrase to the second word or phrase; and relationship data that indicates that the annotation has been assigned to the document, wherein each data packet comprises a different annotation, and each data packet in the plurality of data packets has a same format; aggregating the plurality of data packets in a data repository to form a network of knowledge, wherein the data repository is accessible to a processor; and utilizing the processor to perform at least one processing function over at least one data packet in the data repository. 4. The method of claim 1 , wherein the annotation is automatically generated by extracting the tuple from a sentence of the document, and wherein the user assigns the annotation to the document in response to the annotation being generated. | 0.591837 |
8,204,182 | 1 | 5 | 1. A method comprising acts of: establishing a real-time communication session between a text exchange client and a speech enabled application; identifying a translation table that includes a plurality of entries, each entry including a text exchange item and a corresponding conversational translation item; receiving a text exchange message that was entered into a text exchange client; detecting at least one text exchange item in the text exchange message, which corresponds to an entry included in the translation table; in the text exchange message, substituting a corresponding conversational translation item for each detected text exchange item; sending the substitute message to a text input interface of a voice server to be processed; receiving, from the speech enabled application, an automatic output message responsive to the text entered into the text exchange client; and sending output text related to the automatic output message to the text exchange client, wherein the substituting act occurs in a manner transparent to the text exchange client and to the speech enabled application. | 1. A method comprising acts of: establishing a real-time communication session between a text exchange client and a speech enabled application; identifying a translation table that includes a plurality of entries, each entry including a text exchange item and a corresponding conversational translation item; receiving a text exchange message that was entered into a text exchange client; detecting at least one text exchange item in the text exchange message, which corresponds to an entry included in the translation table; in the text exchange message, substituting a corresponding conversational translation item for each detected text exchange item; sending the substitute message to a text input interface of a voice server to be processed; receiving, from the speech enabled application, an automatic output message responsive to the text entered into the text exchange client; and sending output text related to the automatic output message to the text exchange client, wherein the substituting act occurs in a manner transparent to the text exchange client and to the speech enabled application. 5. The method of claim 1 , wherein the text exchange client is an instant messaging interface, a chat interface, and/or a text-messaging exchange interface. | 0.787466 |
8,203,767 | 1 | 3 | 1. An auto document feeding device comprising: a first conveying path configured to reach from a document placing unit to a first image reading unit, the first conveying path including a first reversing unit formed in an arc shape, the first conveying path being an OUT path including the first reversing unit, a second conveying path configured to reach from the document placing unit to the first image reading unit and have a path different from the first conveying path, the second conveying path having a second reversing unit formed in an arc shape, the second conveying path being an IN path including the second reversing unit having a radius smaller than a radius of the first reversing unit; a gate unit configured to direct original documents, which are sent from the document placing unit, to either the first conveying path or the second conveying path, the gate directing the original document to the OUT path when the original document has a thickness equal to or larger than a fixed thickness; a document conveying unit includes a first conveyance mode which conveying the original documents with overlap a trailing edge of a preceding original document and a leading edge of a following original document, when the gate unit alternately directs the original documents from the document placing unit to the first conveying path or the second conveying path; and a separating unit configured to separate the overlap of the trailing edge of the preceding original document and the leading edge of the following original document before the leading edge of the following original document reaches the first image reading unit. | 1. An auto document feeding device comprising: a first conveying path configured to reach from a document placing unit to a first image reading unit, the first conveying path including a first reversing unit formed in an arc shape, the first conveying path being an OUT path including the first reversing unit, a second conveying path configured to reach from the document placing unit to the first image reading unit and have a path different from the first conveying path, the second conveying path having a second reversing unit formed in an arc shape, the second conveying path being an IN path including the second reversing unit having a radius smaller than a radius of the first reversing unit; a gate unit configured to direct original documents, which are sent from the document placing unit, to either the first conveying path or the second conveying path, the gate directing the original document to the OUT path when the original document has a thickness equal to or larger than a fixed thickness; a document conveying unit includes a first conveyance mode which conveying the original documents with overlap a trailing edge of a preceding original document and a leading edge of a following original document, when the gate unit alternately directs the original documents from the document placing unit to the first conveying path or the second conveying path; and a separating unit configured to separate the overlap of the trailing edge of the preceding original document and the leading edge of the following original document before the leading edge of the following original document reaches the first image reading unit. 3. The device according to claim 1 , wherein adjusting the first conveying mode is in accordance with a slip of the original document in the first conveying path or the second conveying path. | 0.686885 |
9,509,884 | 8 | 9 | 8. A method for estimating a skew angle of a document, the method comprising: receiving a plurality of segments an image of the document, each segment comprising a plurality of rows of pixels; generating, by a hardware processor, an estimate of skew for each segment; and generating a combined estimate of the skew angle, based on the estimates of skew for at least of the segments; determining a confidence value of the combined estimate of the skew angle, wherein determining the confidence value comprises: determining an angle of a line joining two pixels for each side of the image; calculating a side confidence value for each angle; combining the angles by clustering them into groups; calculating a group confidence value for each group based on a sum of the side confidence values of the angles in the group; selecting the group having a highest group confidence value; and estimating the confidence value based on a comparison between the highest group confidence value and a second highest group confidence value. | 8. A method for estimating a skew angle of a document, the method comprising: receiving a plurality of segments an image of the document, each segment comprising a plurality of rows of pixels; generating, by a hardware processor, an estimate of skew for each segment; and generating a combined estimate of the skew angle, based on the estimates of skew for at least of the segments; determining a confidence value of the combined estimate of the skew angle, wherein determining the confidence value comprises: determining an angle of a line joining two pixels for each side of the image; calculating a side confidence value for each angle; combining the angles by clustering them into groups; calculating a group confidence value for each group based on a sum of the side confidence values of the angles in the group; selecting the group having a highest group confidence value; and estimating the confidence value based on a comparison between the highest group confidence value and a second highest group confidence value. 9. The method of claim 8 , wherein generating the combined estimate of the skew angle comprises: generating a first estimate of the skew angle based on a mutual alignment of peripheral boundary points of the document itself or peripheral boundary points of foreground content of the document; and generating a second estimate of the skew angle based on the orientation of foreground or background content in the interior of the document. | 0.5 |
9,158,816 | 1 | 14 | 1. A system comprising: a memory; an input adapter configured to receive an event from a source and generate an event object based on the event, wherein the event object includes a payload, a validity start time, and a validity end time; a processor including a query engine configured to execute a query with respect to the event object to produce a result object, wherein the query is represented by an extensible markup language (XML) file that is based on a reusable XML query template that is bindable to a plurality of input adapters and a plurality of output adapters, wherein the query is executed by comparing the event object to static reference data received from a static reference source, and wherein the result object is produced based on an application of at least one operator of the query; and an output adapter configured to generate a result based on the result object and to transmit the result to a sink. | 1. A system comprising: a memory; an input adapter configured to receive an event from a source and generate an event object based on the event, wherein the event object includes a payload, a validity start time, and a validity end time; a processor including a query engine configured to execute a query with respect to the event object to produce a result object, wherein the query is represented by an extensible markup language (XML) file that is based on a reusable XML query template that is bindable to a plurality of input adapters and a plurality of output adapters, wherein the query is executed by comparing the event object to static reference data received from a static reference source, and wherein the result object is produced based on an application of at least one operator of the query; and an output adapter configured to generate a result based on the result object and to transmit the result to a sink. 14. The system of claim 1 , wherein at least one of the input adapter, the query engine, and the output adapter are integrated into a complex event processing (CEP) system. | 0.78117 |
8,813,046 | 1 | 7 | 1. A computer system for analyzing and transforming computer source code, the system comprising: a memory, storing computer executable instructions; and a processor operatively coupled to said memory and configured to execute the instructions to perform the following steps: analyze at least one source code file that processes character text data in an original format to determine compliance with a target locale neutral encoding format, the target locale neutral encoding format being selected from a plurality of locale neutral encoding formats based on a first estimation of the source code file's compliance with at least one of the plurality of locale neutral encoding formats and a second estimation of encoding conversions required to achieve compliance with the at least one of the plurality of locale neutral encoding formats; and transform the source code into a transformed source code that is capable of processing character text data in the target locale encoding format. | 1. A computer system for analyzing and transforming computer source code, the system comprising: a memory, storing computer executable instructions; and a processor operatively coupled to said memory and configured to execute the instructions to perform the following steps: analyze at least one source code file that processes character text data in an original format to determine compliance with a target locale neutral encoding format, the target locale neutral encoding format being selected from a plurality of locale neutral encoding formats based on a first estimation of the source code file's compliance with at least one of the plurality of locale neutral encoding formats and a second estimation of encoding conversions required to achieve compliance with the at least one of the plurality of locale neutral encoding formats; and transform the source code into a transformed source code that is capable of processing character text data in the target locale encoding format. 7. The system of claim 1 , further comprising the step of: analyzing image files referenced by the source code file, wherein text embedded in an image file is detected and flagged. | 0.5 |
9,967,211 | 12 | 13 | 12. A system for automatic assessment of machine generated responses, said system comprising: at least one processor; and a memory storage device associated with the at least one processor, the memory storage device comprising a memory area storing a response assessment engine, wherein the at least one processor executes the response assessment engine to: calculate an assessment metric for at least one machine-generated response, based on a set of multi-reference responses, a set of ratings and contextual data being associated with the set of multi-reference responses; generate at least one metric score indicating a quality of the at least one machine-generated response relative to at least one multi-reference response from the set of multi-reference responses; and update a set of parameters associated with the response generation system based on the at least one metric score. | 12. A system for automatic assessment of machine generated responses, said system comprising: at least one processor; and a memory storage device associated with the at least one processor, the memory storage device comprising a memory area storing a response assessment engine, wherein the at least one processor executes the response assessment engine to: calculate an assessment metric for at least one machine-generated response, based on a set of multi-reference responses, a set of ratings and contextual data being associated with the set of multi-reference responses; generate at least one metric score indicating a quality of the at least one machine-generated response relative to at least one multi-reference response from the set of multi-reference responses; and update a set of parameters associated with the response generation system based on the at least one metric score. 13. The system of claim 12 , wherein the metric score is a score within a scale from zero to one, and wherein the at least one processor further executes the response assessment engine to: calculate an amount of word sequence overlap between the machine-generated response and a reference response in the set of multi-reference responses, wherein an overlap of zero indicates no words in common between the machine-generated response and the reference response, and wherein an overlap of one indicates the machine-generated response is identical to the reference response. | 0.5 |
10,083,263 | 10 | 14 | 10. A system comprising at least one data processor, and memory storing instructions which, when executed by the at least one data processor, causes the at least one data processor to perform operations comprising: accessing, from at least one database, data from a plurality of disparate data sources; automatically building, using the data obtained from the accessed data sources, a first test model and a second test model, the first test model and the second test model having predetermined predictive variables and the first test model and the second test model built from one or more of the plurality of disparate data sources; determining a set of predictive variables from the predetermined predictive variables in the first test model and the second test model by comparing a predictive power of the predictive variables of the first test model and the second test model, the set of predictive variables being a subset of the predetermined predictive variables; generating a dataset comprising data selected from the disparate data sources and corresponding to the determined set of predictive variables; and building, from the dataset, a model that combines the set of predictive variables, the model characterizing a quantitative estimate of a probability that an entity will display a defined behavior. | 10. A system comprising at least one data processor, and memory storing instructions which, when executed by the at least one data processor, causes the at least one data processor to perform operations comprising: accessing, from at least one database, data from a plurality of disparate data sources; automatically building, using the data obtained from the accessed data sources, a first test model and a second test model, the first test model and the second test model having predetermined predictive variables and the first test model and the second test model built from one or more of the plurality of disparate data sources; determining a set of predictive variables from the predetermined predictive variables in the first test model and the second test model by comparing a predictive power of the predictive variables of the first test model and the second test model, the set of predictive variables being a subset of the predetermined predictive variables; generating a dataset comprising data selected from the disparate data sources and corresponding to the determined set of predictive variables; and building, from the dataset, a model that combines the set of predictive variables, the model characterizing a quantitative estimate of a probability that an entity will display a defined behavior. 14. The system of claim 10 , the operations further comprising merging data across multiple disparate data sources and in one or more varying combinations of the disparate data sources. | 0.748641 |
9,325,508 | 50 | 53 | 50. The method of claim 49 , wherein each of the operational policies and procedures under which the registration authority operates has a policy identifier. | 50. The method of claim 49 , wherein each of the operational policies and procedures under which the registration authority operates has a policy identifier. 53. The method of claim 50 , wherein the policy identifier of the registration authority is included in a Reason entry of the signature field. | 0.665094 |
8,065,360 | 10 | 14 | 10. The computationally-implemented system of claim 1 , wherein said means for acquiring source identity data providing one or more identities of one or more sources that provide a basis, at least in part, for the inference data indicative of the inferred mental state of the authoring user comprises: means for acquiring source identity data providing one or more identities of one or more sensors used to sense one or more physical characteristics of the authoring user, the inference data indicative of the inferred mental state of the authoring user being based, at least in part, on the one or more physical characteristics of the authoring user sensed by the one or more sensors. | 10. The computationally-implemented system of claim 1 , wherein said means for acquiring source identity data providing one or more identities of one or more sources that provide a basis, at least in part, for the inference data indicative of the inferred mental state of the authoring user comprises: means for acquiring source identity data providing one or more identities of one or more sensors used to sense one or more physical characteristics of the authoring user, the inference data indicative of the inferred mental state of the authoring user being based, at least in part, on the one or more physical characteristics of the authoring user sensed by the one or more sensors. 14. The computationally-implemented system of claim 10 , wherein said means for acquiring source identity data providing one or more identities of one or more sensors used to sense one or more physical characteristics of the authoring user, the inference data indicative of the inferred mental state of the authoring user being based, at least in part, on the one or more physical characteristics of the authoring user sensed by the one or more sensors comprises: means for acquiring an identity for at least an electroencephalography (EEG) device that was used to sense the one or more physical characteristics of the authoring user. | 0.5722 |
8,195,795 | 11 | 12 | 11. The system according to claim 10 , further comprising: a CMS interface adapted to interface the real-time CMS data to enable setup of the real-time CMS on the fake conversation client; a media data generation module that is adapted to generate synthetic CMS data intended for causing an originator of the real-time CMS to provide said fake conversation client with further real-time CMS data. | 11. The system according to claim 10 , further comprising: a CMS interface adapted to interface the real-time CMS data to enable setup of the real-time CMS on the fake conversation client; a media data generation module that is adapted to generate synthetic CMS data intended for causing an originator of the real-time CMS to provide said fake conversation client with further real-time CMS data. 12. The system according to claim 11 , where said media data generation module is configured to use or more of the following to generate the synthetic CMS data: a set of a heuristics; a certain logic; prerecorded CMS media data. | 0.5 |
8,200,495 | 15 | 23 | 15. An apparatus for recognizing speech and implementing a speech recognition function, the apparatus comprising: circuitry for initiating a speech dialog with at least one point in the dialog where there is a grammar of possible responses and a set of at least one expected response and wherein the set is a subset of the grammar and the set includes the most likely response or responses expected to be uttered by a user at the at least one point in the speech dialog, the set of at least one expected response for the at least one point being known in the speech recognition system before receiving input speech from the user; circuitry operable for receiving input speech from the user for progressing through the speech dialog; circuitry configured for generating acoustic features of the input speech received from a user; processing circuitry including a match/search algorithm having acoustic models, the acoustic models including acoustic models that are associated with the set of at least one expected response; the processing circuitry operable for comparing the generated input speech acoustic features to acoustic models associated with words in the grammar to generate a hypothesis and further operable for comparing the hypothesis with at least one expected response in the set to determine if the hypothesis matches the at least one expected response in the set; the processing circuitry further operable, if the hypothesis matches the at least one expected response in the set to adapt at least one acoustic model corresponding to the matched expected response using the acoustic features of the input speech to use the at least one adapted model with future input speech in the speech recognition system, otherwise, not adapting the at least one acoustic model corresponding to the expected response. | 15. An apparatus for recognizing speech and implementing a speech recognition function, the apparatus comprising: circuitry for initiating a speech dialog with at least one point in the dialog where there is a grammar of possible responses and a set of at least one expected response and wherein the set is a subset of the grammar and the set includes the most likely response or responses expected to be uttered by a user at the at least one point in the speech dialog, the set of at least one expected response for the at least one point being known in the speech recognition system before receiving input speech from the user; circuitry operable for receiving input speech from the user for progressing through the speech dialog; circuitry configured for generating acoustic features of the input speech received from a user; processing circuitry including a match/search algorithm having acoustic models, the acoustic models including acoustic models that are associated with the set of at least one expected response; the processing circuitry operable for comparing the generated input speech acoustic features to acoustic models associated with words in the grammar to generate a hypothesis and further operable for comparing the hypothesis with at least one expected response in the set to determine if the hypothesis matches the at least one expected response in the set; the processing circuitry further operable, if the hypothesis matches the at least one expected response in the set to adapt at least one acoustic model corresponding to the matched expected response using the acoustic features of the input speech to use the at least one adapted model with future input speech in the speech recognition system, otherwise, not adapting the at least one acoustic model corresponding to the expected response. 23. The apparatus of claim 15 wherein the at least one acoustic model is adapted by creating a new acoustic model based upon the input speech. | 0.688596 |
10,108,723 | 1 | 8 | 1. A method of analyzing data, comprising: generating, by an entity, a query based at least in part on a topic of interest; executing the query on a plurality of data sources, at least one of the plurality of data sources comprising travel related information; selecting, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; monitoring, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; extracting data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; determining an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; determining a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; dynamically adjusting the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; analyzing, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; establishing a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; transmitting, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and receiving, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. | 1. A method of analyzing data, comprising: generating, by an entity, a query based at least in part on a topic of interest; executing the query on a plurality of data sources, at least one of the plurality of data sources comprising travel related information; selecting, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; monitoring, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; extracting data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; determining an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; determining a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; dynamically adjusting the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; analyzing, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; establishing a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; transmitting, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and receiving, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. 8. The method of claim 1 , further comprising analyzing, by an entity user corresponding to the entity, the results of the query in view of the topic of interest and a sub-topic of interest; and determining, by the entity user, the correlation between the data source and the topic of interest based on the analysis of the results of the query. | 0.5 |
9,448,995 | 1 | 2 | 1. Method, in particular computer-implemented method or method implemented by digital electronic components, for retrieving results in response to a query, in particular a user-defined natural language query, from semantically structured resources stored in at least one database, comprising the steps of: i. tokenizing the query by segmenting the query into terms, in particular one or multiple words, and mapping them into semantic tokens using at least one lexicon, wherein such lexicon contains at least the token type of a semantic token, in particular class, role, instance and/or constraint, ii. generating a representation, in particular a representation Incorporating a mathematical graph, of the semantic tokens associated with the segmentation performed in step (i), and determining the representation's focus, by employing a set of rules or patterns for such focus based on the token type, in particular class, role, instance and/or constraint, of the semantic tokens, wherein the rules or patterns define one or more nodes, and/or one or more relationships between nodes, associated with the token type of the semantic tokens, and the rules or patterns distinguish between terminal and non-terminal nodes and relationships, and characterize one of the non-terminal nodes or relationships as the query's focus, iii. generating a database query, in particular an SQL, SPARQL or XQuery query, from the graph-based intermediate representation determined in steps i) and ii) and sending it to the at least one database, iv. retrieving a response from the at least one database. | 1. Method, in particular computer-implemented method or method implemented by digital electronic components, for retrieving results in response to a query, in particular a user-defined natural language query, from semantically structured resources stored in at least one database, comprising the steps of: i. tokenizing the query by segmenting the query into terms, in particular one or multiple words, and mapping them into semantic tokens using at least one lexicon, wherein such lexicon contains at least the token type of a semantic token, in particular class, role, instance and/or constraint, ii. generating a representation, in particular a representation Incorporating a mathematical graph, of the semantic tokens associated with the segmentation performed in step (i), and determining the representation's focus, by employing a set of rules or patterns for such focus based on the token type, in particular class, role, instance and/or constraint, of the semantic tokens, wherein the rules or patterns define one or more nodes, and/or one or more relationships between nodes, associated with the token type of the semantic tokens, and the rules or patterns distinguish between terminal and non-terminal nodes and relationships, and characterize one of the non-terminal nodes or relationships as the query's focus, iii. generating a database query, in particular an SQL, SPARQL or XQuery query, from the graph-based intermediate representation determined in steps i) and ii) and sending it to the at least one database, iv. retrieving a response from the at least one database. 2. Method according to claim 1 , wherein the step of tokenizing the query includes the steps of a) segmenting the query into terms, in particular one or multiple words, b) mapping the terms into semantic tokens using at least one lexicon, wherein such lexicon contains at least the token type of a token, in particular class, role, instance and/or constraint, c) calculating the probability that such segmentation is appropriate, d) repeating steps a) to c) at least one more time for a different segmentation, e) comparing the probabilities of different said segmentations and selecting a segmentation with a high probability, in particular the segmentation with the highest probability, f) performing step ii) of claim 1 based on the selected segmentation. | 0.519036 |
7,519,589 | 108 | 109 | 108. The method of claim 106 , further comprising: creating a batch of data and automatically batch assigning the data based on current reviewer performance characteristics of similar data-types. | 108. The method of claim 106 , further comprising: creating a batch of data and automatically batch assigning the data based on current reviewer performance characteristics of similar data-types. 109. The method of claim 108 , further comprising: projecting review completion time, based on a current number of documents, currently available reviewers, batch type assignments, and the current reviewer performance characteristics. | 0.5 |
10,108,661 | 1 | 2 | 1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: creating a structured resource from a corpus of documents, wherein the structured resource comprises a plurality of first member entities and a plurality of second member entities; identifying a plurality of sentences in the corpus of documents that each comprises one of the plurality of first member entities and one of the plurality of second member entities; constructing a natural language context, for each of the plurality of sentences, based on a sentence context of the first member entity included in the sentence relative to the second member entity included in the sentence, wherein the constructing produces a plurality of natural language contexts that are different from each other; generating a plurality of database queries based on the plurality of natural language contexts, wherein each of the plurality of database queries are different from each other; creating a plurality of pattern maps that each comprise one of the plurality of natural language contexts and one of the plurality of database queries corresponding to the natural language context; in response to matching a question to each of the plurality of natural language contexts, assigning a priority score to each of the plurality of pattern maps based upon a relative amount at which their corresponding one of the plurality of natural language contexts have been matched against one or more previous questions; and invoking each of the plurality of database queries corresponding to the each of the plurality of the patterns maps in an order based on the corresponding priority score assigned to each of the plurality of the pattern maps, until a data resource match is reached. | 1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: creating a structured resource from a corpus of documents, wherein the structured resource comprises a plurality of first member entities and a plurality of second member entities; identifying a plurality of sentences in the corpus of documents that each comprises one of the plurality of first member entities and one of the plurality of second member entities; constructing a natural language context, for each of the plurality of sentences, based on a sentence context of the first member entity included in the sentence relative to the second member entity included in the sentence, wherein the constructing produces a plurality of natural language contexts that are different from each other; generating a plurality of database queries based on the plurality of natural language contexts, wherein each of the plurality of database queries are different from each other; creating a plurality of pattern maps that each comprise one of the plurality of natural language contexts and one of the plurality of database queries corresponding to the natural language context; in response to matching a question to each of the plurality of natural language contexts, assigning a priority score to each of the plurality of pattern maps based upon a relative amount at which their corresponding one of the plurality of natural language contexts have been matched against one or more previous questions; and invoking each of the plurality of database queries corresponding to the each of the plurality of the patterns maps in an order based on the corresponding priority score assigned to each of the plurality of the pattern maps, until a data resource match is reached. 2. The method of claim 1 wherein the plurality of first member entities and the plurality of second member entities are represented by a plurality of synthetic event relations linked to a synthetic event, and wherein the one or more processors perform additional actions comprising: creating a database from the structured resource based upon the plurality of synthetic event relations; and generating a first set of results in response to a first one of the plurality of database queries performing a structured lookup on the database. | 0.5 |
5,584,024 | 2 | 9 | 2. The database query system of claim 1 wherein said QAES includes: a storage system for maintaining state information about the current state of a database query; and a query expert logic system specifying to said QAUI said selectable sets by analyzing said state information maintained in said storage system and said conceptual information stored by said conceptual layer manager. | 2. The database query system of claim 1 wherein said QAES includes: a storage system for maintaining state information about the current state of a database query; and a query expert logic system specifying to said QAUI said selectable sets by analyzing said state information maintained in said storage system and said conceptual information stored by said conceptual layer manager. 9. The database query system of claim 2 wherein if said current state of said database query includes an aggregate column operation on a column in a first table, said query expert logic system excludes from said selectable table set any other of said tables that is more detailed than said first table or is joinable with said first table only through another more detailed table. | 0.515306 |
7,574,428 | 1 | 7 | 1. A computer-implemented method for determining a requested map location, comprising: providing a database holding a plurality of map objects having respective descriptors and loci; accepting a search query comprising one or more query terms that describe the requested map location; identifying in the database two or more matched map objects such that the respective descriptors of the matched map objects each match at least one of the query terms; rendering the matched map objects onto a common grid using the loci; identifying grid cells overlapped by at least one of the rendered map objects; assigning respective scores to the identified grid cells based on a number of the matched map objects that overlap each of the identified grid cells; and determining the requested map location responsively to the scores. | 1. A computer-implemented method for determining a requested map location, comprising: providing a database holding a plurality of map objects having respective descriptors and loci; accepting a search query comprising one or more query terms that describe the requested map location; identifying in the database two or more matched map objects such that the respective descriptors of the matched map objects each match at least one of the query terms; rendering the matched map objects onto a common grid using the loci; identifying grid cells overlapped by at least one of the rendered map objects; assigning respective scores to the identified grid cells based on a number of the matched map objects that overlap each of the identified grid cells; and determining the requested map location responsively to the scores. 7. The method according to claim 1 , wherein accepting the search query comprises accepting free text input comprising the one or more query terms. | 0.832192 |
9,405,832 | 8 | 10 | 8. A non-transitory computer-readable storage medium containing program instructions, which when executed by a processor cause the processor to execute a method of responding to a search query requesting relevant software applications from a database of software applications, the method comprising: receiving, at a server, the search query from an electronic device of a user, the search query including one or more terms; analyzing the one or more terms to assign a search category to the search query, the search category being selected from a plurality of potential search categories, wherein each category of the plurality of potential search categories relates to a different search technique for searching the database of software applications, wherein a first search technique emphasizes exact textual matches more than a second search technique emphasizes exact textual matches, and wherein the analysis utilizes empirical data associated with the one or more terms; determining a search technique based on the search category; using the determined search technique to search, at the server, the database for one or more relevant software applications based on the search query; and sending, to the electronic device, a list of the one or more relevant software applications; wherein analyzing the one or more terms comprises: identifying a set of previous search queries from other users including the term or an equivalent term; identifying, for each search query in the set of previous search queries, an application selected or downloaded by a respective other user subsequent to receiving results from the previous search query; and analyzing a distribution over the selected or downloaded applications; and wherein analyzing the distribution includes: determining a statistical value of the distribution; and comparing the statistical value to a threshold, wherein the functional category is assigned to the search query when the statistical value exceeds the threshold. | 8. A non-transitory computer-readable storage medium containing program instructions, which when executed by a processor cause the processor to execute a method of responding to a search query requesting relevant software applications from a database of software applications, the method comprising: receiving, at a server, the search query from an electronic device of a user, the search query including one or more terms; analyzing the one or more terms to assign a search category to the search query, the search category being selected from a plurality of potential search categories, wherein each category of the plurality of potential search categories relates to a different search technique for searching the database of software applications, wherein a first search technique emphasizes exact textual matches more than a second search technique emphasizes exact textual matches, and wherein the analysis utilizes empirical data associated with the one or more terms; determining a search technique based on the search category; using the determined search technique to search, at the server, the database for one or more relevant software applications based on the search query; and sending, to the electronic device, a list of the one or more relevant software applications; wherein analyzing the one or more terms comprises: identifying a set of previous search queries from other users including the term or an equivalent term; identifying, for each search query in the set of previous search queries, an application selected or downloaded by a respective other user subsequent to receiving results from the previous search query; and analyzing a distribution over the selected or downloaded applications; and wherein analyzing the distribution includes: determining a statistical value of the distribution; and comparing the statistical value to a threshold, wherein the functional category is assigned to the search query when the statistical value exceeds the threshold. 10. The computer-readable medium of claim 8 wherein the empirical data includes data identifying other users' downloads of software applications subsequent to initiating same or equivalent search queries. | 0.5 |
8,401,854 | 1 | 20 | 1. A speech recognition method in which an entry corresponding to a speech input is selected from a list of entries, the method comprising: detecting the speech input; recognizing a phoneme sequence of the speech input; providing a list of fragments of entries in a list of entries, the fragments being based on a subword or phoneme level; and comparing the phoneme sequence of the recognized speech input to the list of fragments to generate a candidate list of best matching entries based on comparison scores, wherein a comparison score is calculated for a fragment when the recognized speech input is compared to the fragment, the comparison score being a measure of how well the recognized speech input fits to the fragment, wherein a score for one list entry is calculated based on the comparison scores of all the fragments that build the list entry, where the fragment is accompanied by different wildcards, each wildcard representing the part of the list entry not considered in the fragment of the list entry and each wildcard having a different weight when the recognized speech input is compared to the fragment. | 1. A speech recognition method in which an entry corresponding to a speech input is selected from a list of entries, the method comprising: detecting the speech input; recognizing a phoneme sequence of the speech input; providing a list of fragments of entries in a list of entries, the fragments being based on a subword or phoneme level; and comparing the phoneme sequence of the recognized speech input to the list of fragments to generate a candidate list of best matching entries based on comparison scores, wherein a comparison score is calculated for a fragment when the recognized speech input is compared to the fragment, the comparison score being a measure of how well the recognized speech input fits to the fragment, wherein a score for one list entry is calculated based on the comparison scores of all the fragments that build the list entry, where the fragment is accompanied by different wildcards, each wildcard representing the part of the list entry not considered in the fragment of the list entry and each wildcard having a different weight when the recognized speech input is compared to the fragment. 20. The method of claim 1 further comprising comparing the recognized speech input to at least some of the complete entries in order to generate the candidate list. | 0.824034 |
9,846,841 | 1 | 7 | 1. A computer-implemented method, comprising: determining, by a data processing apparatus, a potential match candidate from among candidates ranked by predictors, each predictor respectively ranking the candidates according to likelihoods for matching an object as predicted by the respective predictor, and each predictor being different from each other predictor; identifying, for each predictor and by the data processing apparatus, a first value that specifies a likelihood of the potential match candidate for matching the object as predicted by the predictor; identifying, for each predictor and by the data processing apparatus, a second value that is proportional to the ranking of the potential match candidate as predicted by the predictor; determining, by the data processing apparatus, a class probability score for the potential match candidate using the first value for each predictor and the second value for each predictor, the class probability score representing a probability that the potential match candidate is a match to the object; determining, by the data processing apparatus, that the class probability score satisfies a threshold; and determining, by the data processing apparatus, that the potential match candidate matches the object in response to determining that the class probability score satisfies the threshold. | 1. A computer-implemented method, comprising: determining, by a data processing apparatus, a potential match candidate from among candidates ranked by predictors, each predictor respectively ranking the candidates according to likelihoods for matching an object as predicted by the respective predictor, and each predictor being different from each other predictor; identifying, for each predictor and by the data processing apparatus, a first value that specifies a likelihood of the potential match candidate for matching the object as predicted by the predictor; identifying, for each predictor and by the data processing apparatus, a second value that is proportional to the ranking of the potential match candidate as predicted by the predictor; determining, by the data processing apparatus, a class probability score for the potential match candidate using the first value for each predictor and the second value for each predictor, the class probability score representing a probability that the potential match candidate is a match to the object; determining, by the data processing apparatus, that the class probability score satisfies a threshold; and determining, by the data processing apparatus, that the potential match candidate matches the object in response to determining that the class probability score satisfies the threshold. 7. The method of claim 1 , further comprising training the predictors, each predictor being trained using a different number of training candidates. | 0.90525 |
9,594,837 | 13 | 14 | 13. A computer-readable storage device including computer-executable instructions that, when executed by a processor, cause the processor to perform acts including: identifying one or more features of a query; determining, by employing a query classifier, whether the query is intrinsically diverse or not intrinsically diverse based on the one or more features of the query, wherein the query is intrinsically diverse when included in an intrinsically diverse session, wherein the intrinsically diverse session is directed towards a task, and wherein queries included in the intrinsically diverse session are directed towards respective subtasks of the task; receiving search results retrieved by a search engine responsive to executing the query; receiving related queries that correspond to the search results; evaluating an objective function to compute an optimized value when the query is determined to be intrinsically diverse, wherein: the objective function is based on relevance of differing search results to the query, the differing search results returned responsive to the related queries; and the objective function is based on redundancy between the related queries; and controlling presentation of the search results on a display screen according to the optimized value when the query is determined to be intrinsically diverse. | 13. A computer-readable storage device including computer-executable instructions that, when executed by a processor, cause the processor to perform acts including: identifying one or more features of a query; determining, by employing a query classifier, whether the query is intrinsically diverse or not intrinsically diverse based on the one or more features of the query, wherein the query is intrinsically diverse when included in an intrinsically diverse session, wherein the intrinsically diverse session is directed towards a task, and wherein queries included in the intrinsically diverse session are directed towards respective subtasks of the task; receiving search results retrieved by a search engine responsive to executing the query; receiving related queries that correspond to the search results; evaluating an objective function to compute an optimized value when the query is determined to be intrinsically diverse, wherein: the objective function is based on relevance of differing search results to the query, the differing search results returned responsive to the related queries; and the objective function is based on redundancy between the related queries; and controlling presentation of the search results on a display screen according to the optimized value when the query is determined to be intrinsically diverse. 14. The computer-readable storage device of claim 13 , wherein the query classifier is trained based upon features of intrinsically diverse sessions from an intrinsically diverse session database. | 0.803213 |
8,271,958 | 19 | 20 | 19. A tangible computer readable storage device storing instructions that when executed perform a method for remapping user script code, developed to be run in a host application, to debuggable script code, comprising: determining one or more capabilities of a virtual machine (VM) that is utilized for executing the host application in a runtime environment of an application execution and development framework; instrumenting a function in the user script code with one or more guards based on at least one of the one or more capabilities of the VM, the instrumenting comprising at least one of: instrumenting a first guard into the user script code at a first location associated with a first potential debugging stopping operation based on at least one of the one or more capabilities of the VM; instrumenting a second guard into the user script code at a second location associated with a second potential debugging stopping operation if a functional call speed capability of the VM is above a first threshold; instrumenting a third guard into the user script code at a third location associated with a beginning of the function if the functional call speed capability of the VM is below a second threshold; and instrumenting a fourth guard into the user script code at a fourth location associated with a third potential debugging stopping operation and a fifth guard into the user script code at a fifth location associated with a fourth potential debugging stopping operation if the functional call speed capability of the VM is between the first threshold and the second threshold; executing the user script code in the runtime environment; and responsive to detecting an explicit debugging gesture using at least one of the one or more guards, transforming the function to generate debuggable script code. | 19. A tangible computer readable storage device storing instructions that when executed perform a method for remapping user script code, developed to be run in a host application, to debuggable script code, comprising: determining one or more capabilities of a virtual machine (VM) that is utilized for executing the host application in a runtime environment of an application execution and development framework; instrumenting a function in the user script code with one or more guards based on at least one of the one or more capabilities of the VM, the instrumenting comprising at least one of: instrumenting a first guard into the user script code at a first location associated with a first potential debugging stopping operation based on at least one of the one or more capabilities of the VM; instrumenting a second guard into the user script code at a second location associated with a second potential debugging stopping operation if a functional call speed capability of the VM is above a first threshold; instrumenting a third guard into the user script code at a third location associated with a beginning of the function if the functional call speed capability of the VM is below a second threshold; and instrumenting a fourth guard into the user script code at a fourth location associated with a third potential debugging stopping operation and a fifth guard into the user script code at a fifth location associated with a fourth potential debugging stopping operation if the functional call speed capability of the VM is between the first threshold and the second threshold; executing the user script code in the runtime environment; and responsive to detecting an explicit debugging gesture using at least one of the one or more guards, transforming the function to generate debuggable script code. 20. The tangible computer readable storage device of claim 19 , the method comprising splitting the function into a function header and a function body. | 0.5 |
9,288,321 | 10 | 11 | 10. A method comprising: determining, using one or more hardware processors, interactive voice response (IVR) flow information from each webpage element of a plurality of webpage elements in a webpage, wherein the IVR flow information comprises a sequence of audio outputs for presentation of the plurality of webpage elements to a user using a device; transmitting a software component library to the device for processing on a user initiation to present an IVR interface to the user using the IVR flow information, wherein the user utilizes the IVR interface to enter at least one input to at least one of the plurality of webpage elements in response to the sequence of the audio outputs; and receiving the at least one input from the user. | 10. A method comprising: determining, using one or more hardware processors, interactive voice response (IVR) flow information from each webpage element of a plurality of webpage elements in a webpage, wherein the IVR flow information comprises a sequence of audio outputs for presentation of the plurality of webpage elements to a user using a device; transmitting a software component library to the device for processing on a user initiation to present an IVR interface to the user using the IVR flow information, wherein the user utilizes the IVR interface to enter at least one input to at least one of the plurality of webpage elements in response to the sequence of the audio outputs; and receiving the at least one input from the user. 11. The method of claim 10 , wherein the at least one input comprises one of a text input and a voice input. | 0.642384 |
8,141,065 | 13 | 15 | 13. A non-transitory computer-readable medium storing a software program that, when executed by a computer, causes the computer to perform a method for dynamically instantiating a portion of a call flow graph having a plurality of states and a plurality of state transitions, comprising: executing the graph, wherein the graph comprises a defined portion and an undefined portion, wherein a plurality of tokens traverse the graph executing functions; in response to one of the tokens detecting the undefined portion of the graph, suspending the one of the tokens that detected the undefined portion of the graph; generating a new portion of the graph for the undefined portion of the graph, said step of generating the new portion of the graph comprising: generating at least one definition file for the undefined portion of the graph; and executing the at least one definition file to form thereby the new portion of the graph; replacing the undefined portion of the graph with the new portion of the graph; and releasing the suspended token. | 13. A non-transitory computer-readable medium storing a software program that, when executed by a computer, causes the computer to perform a method for dynamically instantiating a portion of a call flow graph having a plurality of states and a plurality of state transitions, comprising: executing the graph, wherein the graph comprises a defined portion and an undefined portion, wherein a plurality of tokens traverse the graph executing functions; in response to one of the tokens detecting the undefined portion of the graph, suspending the one of the tokens that detected the undefined portion of the graph; generating a new portion of the graph for the undefined portion of the graph, said step of generating the new portion of the graph comprising: generating at least one definition file for the undefined portion of the graph; and executing the at least one definition file to form thereby the new portion of the graph; replacing the undefined portion of the graph with the new portion of the graph; and releasing the suspended token. 15. The computer-readable medium of claim 13 , wherein replacing the undefined portion of the graph with the new portion of the graph comprises: reading the new portion of the graph into the graph. | 0.679153 |
9,619,024 | 1 | 8 | 1. A virtual inputting device, comprising: a signal collection unit including a bioelectrical sensor for collecting bioelectrical signals and an acceleration sensor for collecting acceleration signals, the bioelectrical signals and the acceleration signals reflecting a user's gesture; a signal preprocessing unit for performing preprocessing for the bioelectrical signals and the acceleration signals collected by the signal collection unit; a signal segmentation unit for performing segmentation processing for the preprocessed bioelectrical signals and acceleration signals so as to obtain a plurality of gesture segments; a feature extracting unit for extracting feature values from the bioelectrical signals and the acceleration signals for respective gesture segments; a feature combination unit for combining feature values extracted from the feature extracting unit to form a combined feature vector; a gesture recognition unit for performing gesture recognition based on the combined feature vector; and a character mapping unit for obtaining characters corresponding to the recognized gesture according to a predetermined mapping relationship between characters and gestures, wherein the segmentation processing comprises: determining starting points and ending points for the preprocessed bioelectrical signals and the preprocessed acceleration signals respectively; and averaging the starting points so as to obtain a starting point of a gesture segment, and averaging the ending points so as to obtain an ending point of the gesture segment. | 1. A virtual inputting device, comprising: a signal collection unit including a bioelectrical sensor for collecting bioelectrical signals and an acceleration sensor for collecting acceleration signals, the bioelectrical signals and the acceleration signals reflecting a user's gesture; a signal preprocessing unit for performing preprocessing for the bioelectrical signals and the acceleration signals collected by the signal collection unit; a signal segmentation unit for performing segmentation processing for the preprocessed bioelectrical signals and acceleration signals so as to obtain a plurality of gesture segments; a feature extracting unit for extracting feature values from the bioelectrical signals and the acceleration signals for respective gesture segments; a feature combination unit for combining feature values extracted from the feature extracting unit to form a combined feature vector; a gesture recognition unit for performing gesture recognition based on the combined feature vector; and a character mapping unit for obtaining characters corresponding to the recognized gesture according to a predetermined mapping relationship between characters and gestures, wherein the segmentation processing comprises: determining starting points and ending points for the preprocessed bioelectrical signals and the preprocessed acceleration signals respectively; and averaging the starting points so as to obtain a starting point of a gesture segment, and averaging the ending points so as to obtain an ending point of the gesture segment. 8. The virtual input device of claim 1 , wherein the feature extracting unit combines multi-channel bioelectrical signals to form a multi-dimensional feature vector, and calculates speed changes in each axis of a three-dimensional space for the acceleration signals to form a three-dimensional feature vector; and wherein the feature combination unit combines the multi-dimensional feature vector and the three-dimensional feature vector to form the combined feature vector. | 0.564338 |
9,201,945 | 1 | 5 | 1. A computer-implemented method comprising: identifying a category from a knowledge base, the category including a plurality of entities; identifying a set of queries including terms related to the entities included in the category from a query stream; calculating a specificity value for the category, based at least on the entities included in the category and the set of queries, comprising: determining a probability distribution for co-occurrence of the terms in the set of queries with the entities associated with the category; determining a background probability distribution for the occurrence of the terms in the set of queries; and comparing the probability distribution of the co-occurrence of the terms in the set of queries with the entities associated with the category and the background probability distribution to obtain the specificity value for the category; and classifying the category as a coherent category, wherein a coherent category is a category whose specificity value satisfies a threshold. | 1. A computer-implemented method comprising: identifying a category from a knowledge base, the category including a plurality of entities; identifying a set of queries including terms related to the entities included in the category from a query stream; calculating a specificity value for the category, based at least on the entities included in the category and the set of queries, comprising: determining a probability distribution for co-occurrence of the terms in the set of queries with the entities associated with the category; determining a background probability distribution for the occurrence of the terms in the set of queries; and comparing the probability distribution of the co-occurrence of the terms in the set of queries with the entities associated with the category and the background probability distribution to obtain the specificity value for the category; and classifying the category as a coherent category, wherein a coherent category is a category whose specificity value satisfies a threshold. 5. The method of claim 1 , further comprising determining that the category is a useful category when it is a coherent category and the category is associated with a number of entities that satisfies a threshold. | 0.554622 |
7,920,968 | 1 | 3 | 1. A machine-readable medium encoded with instructions, that when executed by a processor, cause the processor to carry out a process for generating human-centric driving directions, the process comprising: generating a route in response to a user request for travel directions, the request specifying at least a target destination; identifying distinctive waypoints along the route, wherein the waypoints are physical structures along the route and are in addition to road names and road topology and each waypoint is associated with a distinctiveness score, wherein the distinctiveness score of each waypoint is based at least in part on a visual prominence of the respective waypoint and based at least in part on an advertising fee per use for incorporating the respective waypoint in travel directions; and incorporating one or more of the waypoints into travel directions responsive to the associated distinctiveness score. | 1. A machine-readable medium encoded with instructions, that when executed by a processor, cause the processor to carry out a process for generating human-centric driving directions, the process comprising: generating a route in response to a user request for travel directions, the request specifying at least a target destination; identifying distinctive waypoints along the route, wherein the waypoints are physical structures along the route and are in addition to road names and road topology and each waypoint is associated with a distinctiveness score, wherein the distinctiveness score of each waypoint is based at least in part on a visual prominence of the respective waypoint and based at least in part on an advertising fee per use for incorporating the respective waypoint in travel directions; and incorporating one or more of the waypoints into travel directions responsive to the associated distinctiveness score. 3. The machine-readable medium of claim 1 wherein identifying distinctive waypoints along the route includes accessing a waypoint database. | 0.78681 |
10,074,125 | 5 | 6 | 5. The method of claim 1 , wherein: the message is from a source; the method further comprises identifying a seller of the product item based on the source; and the generating of the draft version of the item listing generates the draft version of the item listing as being for sale by the seller on a marketplace website. | 5. The method of claim 1 , wherein: the message is from a source; the method further comprises identifying a seller of the product item based on the source; and the generating of the draft version of the item listing generates the draft version of the item listing as being for sale by the seller on a marketplace website. 6. The method of claim 5 , wherein the identifying of the seller comprises detecting a match between the source and a seller telephone number associated with the seller, the seller telephone number being included in a seller record corresponding to the seller. | 0.5 |
8,185,399 | 1 | 4 | 1. A method comprising: training, via a processor, an automatic speech recognition module, a spoken language understanding module and a dialog management module using task-independent call-types of a previous application; recognizing a received user utterance in response to a prompt to a user using the automatic speech recognition module to yield a recognized user utterance; classifying the recognized user utterance using the spoken language understanding module to yield a classification; if the recognized user utterance is classifiable by the spoken language understanding module with a confidence more than an acceptance threshold, then acting according to a call-type associated with the classification; and if the recognized user utterance is not classifiable by the spoken language understanding module to a predetermined rejection threshold and if a dialog-wide re-prompt counter is exceeded, then transferring the user to a human, wherein the received user utterance is transcribed, labeled and used for training the spoken dialog system, and wherein at least one of the acceptance threshold and the predetermined rejection threshold are related to an entity referenced in the recognized user utterance. | 1. A method comprising: training, via a processor, an automatic speech recognition module, a spoken language understanding module and a dialog management module using task-independent call-types of a previous application; recognizing a received user utterance in response to a prompt to a user using the automatic speech recognition module to yield a recognized user utterance; classifying the recognized user utterance using the spoken language understanding module to yield a classification; if the recognized user utterance is classifiable by the spoken language understanding module with a confidence more than an acceptance threshold, then acting according to a call-type associated with the classification; and if the recognized user utterance is not classifiable by the spoken language understanding module to a predetermined rejection threshold and if a dialog-wide re-prompt counter is exceeded, then transferring the user to a human, wherein the received user utterance is transcribed, labeled and used for training the spoken dialog system, and wherein at least one of the acceptance threshold and the predetermined rejection threshold are related to an entity referenced in the recognized user utterance. 4. The method of claim 1 , wherein the method is performed by an automated hidden human. | 0.851351 |
7,904,300 | 22 | 25 | 22. An in-vehicle system comprising: at least a first console adapted to be operated by a first user; at least a second console adapted to be operated by a second user; and a speech processor to receive and process speech requests from the first and second consoles, wherein the in-vehicle system is configured to service speech requests received simultaneously at the first console and the second console, wherein the speech processor is configured to: process a first speech processing request received from the first console and send a first result to the first console, the first result being responsive to the first speech processing request; and process a second speech processing request received from the second console and send a second result to the second console, the second result being responsive to the second speech processing request; and wherein the first console and the second console each is configured to run at least one speech-enabled application. | 22. An in-vehicle system comprising: at least a first console adapted to be operated by a first user; at least a second console adapted to be operated by a second user; and a speech processor to receive and process speech requests from the first and second consoles, wherein the in-vehicle system is configured to service speech requests received simultaneously at the first console and the second console, wherein the speech processor is configured to: process a first speech processing request received from the first console and send a first result to the first console, the first result being responsive to the first speech processing request; and process a second speech processing request received from the second console and send a second result to the second console, the second result being responsive to the second speech processing request; and wherein the first console and the second console each is configured to run at least one speech-enabled application. 25. The in-vehicle system of claim 22 , wherein the first console has a dock that allows at least one external device to interoperate with the first console. | 0.563889 |
8,442,831 | 10 | 11 | 10. A system of identifying words in a speech segment, said system comprising: a device to obtain a speech segment, and to determine one or more words of the speech segment, wherein to determine a word of the speech segment, the device performs a plurality of actions comprising: identifying one or more soundlets within the word, wherein a soundlet of the one or more soundlets has a sound wave associated therewith, the sound wave having a sound wave contour, and the identifying for the soundlet comprises: analyzing the sound wave contour of at least a portion of the sound wave of the soundlet to determine one or more variations within the sound wave contour; assigning one or more features to the one or more variations; and mapping the one or more features to one or more sound constructs, wherein the one or more sound constructs are at least part of the word. | 10. A system of identifying words in a speech segment, said system comprising: a device to obtain a speech segment, and to determine one or more words of the speech segment, wherein to determine a word of the speech segment, the device performs a plurality of actions comprising: identifying one or more soundlets within the word, wherein a soundlet of the one or more soundlets has a sound wave associated therewith, the sound wave having a sound wave contour, and the identifying for the soundlet comprises: analyzing the sound wave contour of at least a portion of the sound wave of the soundlet to determine one or more variations within the sound wave contour; assigning one or more features to the one or more variations; and mapping the one or more features to one or more sound constructs, wherein the one or more sound constructs are at least part of the word. 11. The system of claim 10 , wherein to assign a feature to a variation comprises selecting a feature from a plurality of features based on slope characteristics of the sound wave contour representing the soundlet. | 0.633562 |
7,698,694 | 1 | 6 | 1. A method comprising: extracting, with a preprocessing device, macroinstructions that are hard-coded into parser code of a command line interface (CLI) parser, wherein the macroinstructions define parse nodes utilized by the CLI parser to analyze whether one or more CLI commands input to a CLI prompt have a proper CLI syntax; generating a parse graph from the macroinstructions with the preprocessing device, wherein the parse graph includes a representation of the parse nodes defined by the macroinstructions, and wherein the macroinstructions and the parse graph are written in different programming languages; generating an AND/OR command tree structure from the parse graph; generating an unsimplified command data model from the AND/OR command tree structure by expressing the AND/OR command tree structure as a command tree using elements of EBNF (Extended Backus-Naur-Form) notation; and simplifying selected structures within the unsimplified command data model according to one or more simplification rules, wherein the simplifying creates a simplified command data model that is available for use by an external management system in at least one of device validation or testing processes. | 1. A method comprising: extracting, with a preprocessing device, macroinstructions that are hard-coded into parser code of a command line interface (CLI) parser, wherein the macroinstructions define parse nodes utilized by the CLI parser to analyze whether one or more CLI commands input to a CLI prompt have a proper CLI syntax; generating a parse graph from the macroinstructions with the preprocessing device, wherein the parse graph includes a representation of the parse nodes defined by the macroinstructions, and wherein the macroinstructions and the parse graph are written in different programming languages; generating an AND/OR command tree structure from the parse graph; generating an unsimplified command data model from the AND/OR command tree structure by expressing the AND/OR command tree structure as a command tree using elements of EBNF (Extended Backus-Naur-Form) notation; and simplifying selected structures within the unsimplified command data model according to one or more simplification rules, wherein the simplifying creates a simplified command data model that is available for use by an external management system in at least one of device validation or testing processes. 6. The method of claim 1 , further comprises refining the simplified command data model by allowing renaming of selected elements of the command data model based on user-specified instructions to create a refined command data model. | 0.541502 |
9,842,096 | 15 | 17 | 15. An apparatus comprising: a processor, and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive, by a natural language processing pipeline configured to execute in the data processing system, an input document to be ingested into a corpus; divide, by the natural language processing pipeline, the input document into a plurality of input passages; identify, by a filter component of the natural language processing pipeline, whether each input passage is a nonsense passage based on a value of a metric determined according to a set of feature counts, wherein identifying whether a given input passage is a nonsense passage comprises: annotating, by an annotator in the natural language processing pipeline, the given input passage within the plurality of input passages with linguistic features to form an annotated passage; counting, by metric counters component in the natural language processing pipeline, a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts; determining, by the metric counters component of the natural language processing pipeline, a value for a metric based on the set of feature counts; and comparing, by a comparator component of the natural language processing pipeline, the value for the metric to a predetermined model threshold; filter, by the natural language processing pipeline, each input passage in the plurality of input passages based on whether the input passage is identified as a nonsense passage or not identified as a nonsense passage to form a filtered plurality of input passages; and add, by the natural language processing pipeline, the filtered plurality of input passages into the corpus. | 15. An apparatus comprising: a processor, and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive, by a natural language processing pipeline configured to execute in the data processing system, an input document to be ingested into a corpus; divide, by the natural language processing pipeline, the input document into a plurality of input passages; identify, by a filter component of the natural language processing pipeline, whether each input passage is a nonsense passage based on a value of a metric determined according to a set of feature counts, wherein identifying whether a given input passage is a nonsense passage comprises: annotating, by an annotator in the natural language processing pipeline, the given input passage within the plurality of input passages with linguistic features to form an annotated passage; counting, by metric counters component in the natural language processing pipeline, a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts; determining, by the metric counters component of the natural language processing pipeline, a value for a metric based on the set of feature counts; and comparing, by a comparator component of the natural language processing pipeline, the value for the metric to a predetermined model threshold; filter, by the natural language processing pipeline, each input passage in the plurality of input passages based on whether the input passage is identified as a nonsense passage or not identified as a nonsense passage to form a filtered plurality of input passages; and add, by the natural language processing pipeline, the filtered plurality of input passages into the corpus. 17. The apparatus of claim 15 , wherein filtering each input passage comprises marking a given input passage responsive to the given input passage being identified as a nonsense passage. | 0.518135 |
8,893,031 | 6 | 8 | 6. A computing system comprising: a memory storing processor-executable program instructions; and a processor to execute the processor-executable program instructions to cause the system to: receive instruction from a user to create a user-customized virtual association between a first user-selected element and a second user-selected element of one or more business object models of a UI component model; determine a node of a first business object model of the virtual association; determine a second business object model node of the virtual association; define foreign key parameters in the UI component model describing a foreign key relationship associating a user-selected attribute of the first business object model node with a user-selected attribute of an element of the second business object model node, wherein the foreign key relationship creates the virtual association; propagate the virtual association to a service layer configured to evaluate the foreign key relationship and provide corresponding data of the associated elements; and create metadata in the UI component model associating the element of the UI component model with the second attribute of the element of the second business object model, the metadata comprising the foreign key parameters. | 6. A computing system comprising: a memory storing processor-executable program instructions; and a processor to execute the processor-executable program instructions to cause the system to: receive instruction from a user to create a user-customized virtual association between a first user-selected element and a second user-selected element of one or more business object models of a UI component model; determine a node of a first business object model of the virtual association; determine a second business object model node of the virtual association; define foreign key parameters in the UI component model describing a foreign key relationship associating a user-selected attribute of the first business object model node with a user-selected attribute of an element of the second business object model node, wherein the foreign key relationship creates the virtual association; propagate the virtual association to a service layer configured to evaluate the foreign key relationship and provide corresponding data of the associated elements; and create metadata in the UI component model associating the element of the UI component model with the second attribute of the element of the second business object model, the metadata comprising the foreign key parameters. 8. The system according to claim 6 , wherein the element of a UI component model comprises a data structure. | 0.898305 |
10,140,880 | 10 | 13 | 10. A system, comprising: one or more processors; non-transitory computer readable media that include instructions thereon that, in response to execution by the one or more processors, control performance of operations comprising: locating a plurality of occurrences of a knowledge point in a learning material; selecting one or more candidate initial points from the plurality of occurrences of the knowledge point; setting a first candidate initial point of the one or more candidate initial points as a first initial point; creating a first window in the learning material that includes the first initial point, wherein the first window includes a first-window size that corresponds to one or more basic units; creating a second window in the learning material that is adjacent to the first window, wherein a start of the second window follows a start of the first window by a first separation size, and wherein the second window includes a second-window size that corresponds to the one or more basic units; calculating a window similarity between first-window content of the first window and second-window content of the second window; in response to the window similarity between the first-window content of the first window and the second-window content of the second window meeting a similarity threshold, generating a first segment with first-segment content that includes at least the first-window content and the second-window content; detecting a position for a first segment border of the first segment that indicates an end of the first segment in which the detecting includes: sliding the first window and the second window through the learning material by a step size to create a first new window and a second new window such that the second-window content of the second window is the same as first new-window content of the first new window, and determining whether a new-window similarity between the first new-window content and second new-window content meet the similarity threshold; calculating a first-segment consistency measurement for the first segment based on a first-segment similarity between the first-segment content in the first segment and the knowledge point; ranking, according to one or more computer-executable expressions, the first segment with respect to one or more of the following: a second segment in the learning material and a third segment in a different learning material, wherein the ranking of the first segment is based on one or more of the following: a quality measurement, a learning material type of the learning material, a length of the first segment, and the first-segment consistency measurement of the first segment; and recommending the first segment to a learner based on the ranking of the first segment. | 10. A system, comprising: one or more processors; non-transitory computer readable media that include instructions thereon that, in response to execution by the one or more processors, control performance of operations comprising: locating a plurality of occurrences of a knowledge point in a learning material; selecting one or more candidate initial points from the plurality of occurrences of the knowledge point; setting a first candidate initial point of the one or more candidate initial points as a first initial point; creating a first window in the learning material that includes the first initial point, wherein the first window includes a first-window size that corresponds to one or more basic units; creating a second window in the learning material that is adjacent to the first window, wherein a start of the second window follows a start of the first window by a first separation size, and wherein the second window includes a second-window size that corresponds to the one or more basic units; calculating a window similarity between first-window content of the first window and second-window content of the second window; in response to the window similarity between the first-window content of the first window and the second-window content of the second window meeting a similarity threshold, generating a first segment with first-segment content that includes at least the first-window content and the second-window content; detecting a position for a first segment border of the first segment that indicates an end of the first segment in which the detecting includes: sliding the first window and the second window through the learning material by a step size to create a first new window and a second new window such that the second-window content of the second window is the same as first new-window content of the first new window, and determining whether a new-window similarity between the first new-window content and second new-window content meet the similarity threshold; calculating a first-segment consistency measurement for the first segment based on a first-segment similarity between the first-segment content in the first segment and the knowledge point; ranking, according to one or more computer-executable expressions, the first segment with respect to one or more of the following: a second segment in the learning material and a third segment in a different learning material, wherein the ranking of the first segment is based on one or more of the following: a quality measurement, a learning material type of the learning material, a length of the first segment, and the first-segment consistency measurement of the first segment; and recommending the first segment to a learner based on the ranking of the first segment. 13. The system of claim 10 , wherein an analysis server is configured to: set a score for each of the plurality of occurrences of the knowledge point in the learning material, wherein the score for an occurrence of the knowledge point in a title of the learning material is higher than the score for an occurrence of the knowledge point in a text of the learning material; and adjust the first-segment consistency measurement based on a sum of the scores for each of the plurality of occurrences of the knowledge point in the learning material. | 0.819269 |
7,640,158 | 15 | 21 | 15. A computer program product, comprising a first computer-readable medium having computer readable program code tangible embodied therein, said computer readable program code adapted to be executed by a processor to implement a method, the method comprising: (A) tangibly storing, on a second computer-readable medium, a data structure representing a plurality of editing patterns of the form T=(D,E,C), wherein each of the plurality of editing patterns relates particular content D in an original document corpus to corresponding content E in an edited document corpus in a context C shared by contents D and E, wherein the original document corpus and the edited document corpus are tangibly stored on a third and fourth computer-readable medium, respectively; (B) deriving a plurality of correction rules, tangibly stored on a fifth computer-readable medium, from the plurality of editing patterns; and (C) deriving a classifier, tangibly stored on a sixth computer-readable medium, for particular content D based on the plurality of editing patterns, the classifier defining decision criteria for selecting one of the plurality of correction rules to apply to content D based on a context C* of content D. | 15. A computer program product, comprising a first computer-readable medium having computer readable program code tangible embodied therein, said computer readable program code adapted to be executed by a processor to implement a method, the method comprising: (A) tangibly storing, on a second computer-readable medium, a data structure representing a plurality of editing patterns of the form T=(D,E,C), wherein each of the plurality of editing patterns relates particular content D in an original document corpus to corresponding content E in an edited document corpus in a context C shared by contents D and E, wherein the original document corpus and the edited document corpus are tangibly stored on a third and fourth computer-readable medium, respectively; (B) deriving a plurality of correction rules, tangibly stored on a fifth computer-readable medium, from the plurality of editing patterns; and (C) deriving a classifier, tangibly stored on a sixth computer-readable medium, for particular content D based on the plurality of editing patterns, the classifier defining decision criteria for selecting one of the plurality of correction rules to apply to content D based on a context C* of content D. 21. The computer program product of claim 15 , wherein (A) comprises: (A)(1) identifying editing actions performed on the original document corpus to produce the edited document corpus; and (A)(2) generating the plurality of editing patterns to reflect the editing actions. | 0.777687 |
9,734,217 | 12 | 16 | 12. A non-transitory computer-readable medium storing a set of instructions that are executable by one or more processors of one or more servers to cause the one or more servers to perform a method for analyzing entity performance, the method comprising: receiving, from a user computer via a network, a request with one or more filter selections; accessing, by a server computer, a data structure in a memory, the data structure comprising a plurality of categories of information showing interactions related to multiple entities; identifying, by the server computer, a set of categories of the plurality of categories within the data structure based on the one or more filter selections, wherein the set of categories within the data structure includes location information related to at least one of the multiple entities, wherein the plurality of categories of the data structure include at least one of: an interaction number category, a consuming entity identification category, a consuming entity location category, a provisioning entity identification category, a provisioning entity location category, a type of provisioning entity category, an interaction amount category, and a time of interaction category; determining, by the server computer, the location information of the at least one of the multiple entities to update the data structure, wherein the location information is determined based on a computed affinity score that is based on computed travel times so that the affinity score can have an inverse proportionality with computed travel times such that a higher affinity score can have a lower travel time, wherein the computed affinity score is used to estimate the location information within an estimated area location for the provisioning entity without an identified location information, wherein the determining includes verifying that a populated category of the plurality of categories is valid data that signifies the location information; updating, by the server computer, the data structure with the determined location information within the area location; processing, by the server computer, the location information of the identified set of the plurality of categories to analyze a performance of one or more entities of the multiple entities in accordance with the one or more filter selections; and providing the processed location information to display the performance of the one or more entities on a graphical user interface of the user computer. | 12. A non-transitory computer-readable medium storing a set of instructions that are executable by one or more processors of one or more servers to cause the one or more servers to perform a method for analyzing entity performance, the method comprising: receiving, from a user computer via a network, a request with one or more filter selections; accessing, by a server computer, a data structure in a memory, the data structure comprising a plurality of categories of information showing interactions related to multiple entities; identifying, by the server computer, a set of categories of the plurality of categories within the data structure based on the one or more filter selections, wherein the set of categories within the data structure includes location information related to at least one of the multiple entities, wherein the plurality of categories of the data structure include at least one of: an interaction number category, a consuming entity identification category, a consuming entity location category, a provisioning entity identification category, a provisioning entity location category, a type of provisioning entity category, an interaction amount category, and a time of interaction category; determining, by the server computer, the location information of the at least one of the multiple entities to update the data structure, wherein the location information is determined based on a computed affinity score that is based on computed travel times so that the affinity score can have an inverse proportionality with computed travel times such that a higher affinity score can have a lower travel time, wherein the computed affinity score is used to estimate the location information within an estimated area location for the provisioning entity without an identified location information, wherein the determining includes verifying that a populated category of the plurality of categories is valid data that signifies the location information; updating, by the server computer, the data structure with the determined location information within the area location; processing, by the server computer, the location information of the identified set of the plurality of categories to analyze a performance of one or more entities of the multiple entities in accordance with the one or more filter selections; and providing the processed location information to display the performance of the one or more entities on a graphical user interface of the user computer. 16. The non-transitory computer-readable medium of claim 12 , wherein the one or more filter selections are associated with a particular user interface of a plurality of user interfaces, the particular user interface displays a representation associated with the one or more filter selections overlaid on a geographic region. | 0.52346 |
8,027,975 | 16 | 17 | 16. The method of claim 1 , wherein the obtaining at least one search result step is performed periodically. | 16. The method of claim 1 , wherein the obtaining at least one search result step is performed periodically. 17. The method of claim 16 , wherein periodicity of performing the obtaining step is based on a user characteristic. | 0.567164 |
8,122,001 | 11 | 14 | 11. A search engine search method in a computer system including at least one client computer including a processor, a memory, and an interface, a plurality of search engines coupled to the client computer via a network, and a management computer coupled to the client computer and the search engines, the method comprising the steps of: collecting logs of access from the client computer; specifying a parameter transferred from the client computer to an access destination of the client computer by analyzing the collected logs of access; judging whether the specified parameter is a search query; judging that an access including the parameter judged as the search query is an access to a given search engine of the plurality of search engines; selecting a log of access to each of the plurality of search engines from the collected logs of access; extracting an address of the search engine and a search query from the selected log of access to the search engine; and storing, for each of the plurality of search engines, a correspondence between the extracted address of the search engine and the extracted search query in a search engine profile, further comprising the steps of: receiving a search request of a search engine containing a search query from the client computer; specifying an address of the search engine corresponding to the search query contained in the received search request by referring to the search engine profile; and transmitting the specified address of the search engine to the client computer as a search result. | 11. A search engine search method in a computer system including at least one client computer including a processor, a memory, and an interface, a plurality of search engines coupled to the client computer via a network, and a management computer coupled to the client computer and the search engines, the method comprising the steps of: collecting logs of access from the client computer; specifying a parameter transferred from the client computer to an access destination of the client computer by analyzing the collected logs of access; judging whether the specified parameter is a search query; judging that an access including the parameter judged as the search query is an access to a given search engine of the plurality of search engines; selecting a log of access to each of the plurality of search engines from the collected logs of access; extracting an address of the search engine and a search query from the selected log of access to the search engine; and storing, for each of the plurality of search engines, a correspondence between the extracted address of the search engine and the extracted search query in a search engine profile, further comprising the steps of: receiving a search request of a search engine containing a search query from the client computer; specifying an address of the search engine corresponding to the search query contained in the received search request by referring to the search engine profile; and transmitting the specified address of the search engine to the client computer as a search result. 14. The search engine search method according to claim 11 , further comprising the steps of: obtaining an attribute indicating characteristics of usage of the search engine based on the selected log of access to the search engine; storing a correspondence between the extracted address of the search engine and the obtained attribute of the search engine in a search engine attribute file; and specifying the attribute of the search engine corresponding to the specified address of the search engine by referring to the search engine attribute file, wherein the step of transmitting the specified address of the search engine to the client computer as a search result includes transmitting the specified attribute of the search engine together with the specified address of the search engine. | 0.5 |
9,576,495 | 1 | 8 | 1. A computerized teaching system for providing an in-class assessment for evaluating one or more students to determine whether the one or more students are learning STEM principles being taught by a teacher in a class, the system comprising: a communications network; at least one teacher computer; and at least one student computer; wherein each of the at least one teacher computer and the at least one student computer includes an input device and a touch sensitive screen for receiving handwritten input via the input device; wherein the at least one student computer is operably connected to the at least one teacher computer via the communications network; wherein the at least one teacher computer includes a computer-readable storage medium containing program instructions for implementing a teacher administered assessment application comprising one or more program instructions for performing the steps of: receiving at least one question description handwritten by the teacher in math notation on the screen of the at least one teacher computer; storing the at least one question description; receiving at least one correct answer corresponding to the at least one question description, the at least one correct answer being handwritten by the teacher in math notation on the screen of the at least one teacher computer; storing the at least one correct answer; receiving at least one student response from the at least one student computer via the communications network, the at least one student response being input by the student by handwriting the at least one student response in math notation on the screen of the at least one student computer; reading and interpreting the at least one student response; comparing the at least one student response to the at least one correct answer corresponding to the at least one question description, the comparing step including the sub-step of automatically evaluating whether the at least one student response handwritten in math notation is algebraically equivalent to the at least one correct answer handwritten in math notation; and if the at least one student response includes a plurality of student responses, determining and displaying the number of student responses of the plurality of student responses which are correct on the screen of the at least one teacher computer. | 1. A computerized teaching system for providing an in-class assessment for evaluating one or more students to determine whether the one or more students are learning STEM principles being taught by a teacher in a class, the system comprising: a communications network; at least one teacher computer; and at least one student computer; wherein each of the at least one teacher computer and the at least one student computer includes an input device and a touch sensitive screen for receiving handwritten input via the input device; wherein the at least one student computer is operably connected to the at least one teacher computer via the communications network; wherein the at least one teacher computer includes a computer-readable storage medium containing program instructions for implementing a teacher administered assessment application comprising one or more program instructions for performing the steps of: receiving at least one question description handwritten by the teacher in math notation on the screen of the at least one teacher computer; storing the at least one question description; receiving at least one correct answer corresponding to the at least one question description, the at least one correct answer being handwritten by the teacher in math notation on the screen of the at least one teacher computer; storing the at least one correct answer; receiving at least one student response from the at least one student computer via the communications network, the at least one student response being input by the student by handwriting the at least one student response in math notation on the screen of the at least one student computer; reading and interpreting the at least one student response; comparing the at least one student response to the at least one correct answer corresponding to the at least one question description, the comparing step including the sub-step of automatically evaluating whether the at least one student response handwritten in math notation is algebraically equivalent to the at least one correct answer handwritten in math notation; and if the at least one student response includes a plurality of student responses, determining and displaying the number of student responses of the plurality of student responses which are correct on the screen of the at least one teacher computer. 8. The system according to claim 1 , wherein the at least one student response includes at least one hand drawn sketch. | 0.80363 |
7,818,179 | 22 | 24 | 22. The method of claim 21 , wherein processing speech input from the speaker comprises analyzing the speech input of the speaker for detecting one or more words or expressions or sounds, if any, in the speech input, which are specified in a vocabulary list. | 22. The method of claim 21 , wherein processing speech input from the speaker comprises analyzing the speech input of the speaker for detecting one or more words or expressions or sounds, if any, in the speech input, which are specified in a vocabulary list. 24. The method of claim 22 , wherein an identified speech habit comprises a repetitive use of a word or expression specified in the vocabulary list. | 0.5 |
8,463,592 | 1 | 5 | 1. A method of converting strings to a common language comprising: determining a user-selected target language; associating a user-selected primary input language and at least one user-selected secondary input language with the target language, wherein the target language is common to, and different from, the primary input language and the at least one secondary input language; obtaining a string of at least one character; converting the obtained string from the primary input language to the target language if the obtained string corresponds to a valid string in the primary input language by using a phonetic lexicon to interpret the obtained string in the target language based upon a phonetic correspondence of the obtained string in the primary input language; converting the obtained string from at least one secondary input language to the target language if the obtained string corresponds to a valid string in the corresponding secondary input language and is not a valid string in the primary input language by using a translation lexicon to translate the obtained string from the secondary language to the target language; and outputting the converted string in the target language to an output device. | 1. A method of converting strings to a common language comprising: determining a user-selected target language; associating a user-selected primary input language and at least one user-selected secondary input language with the target language, wherein the target language is common to, and different from, the primary input language and the at least one secondary input language; obtaining a string of at least one character; converting the obtained string from the primary input language to the target language if the obtained string corresponds to a valid string in the primary input language by using a phonetic lexicon to interpret the obtained string in the target language based upon a phonetic correspondence of the obtained string in the primary input language; converting the obtained string from at least one secondary input language to the target language if the obtained string corresponds to a valid string in the corresponding secondary input language and is not a valid string in the primary input language by using a translation lexicon to translate the obtained string from the secondary language to the target language; and outputting the converted string in the target language to an output device. 5. The method according to claim 1 , further comprising: a phonetic lexicon associated with the conversion from the primary input language to the target language; and a translation lexicon associated with the conversion from the secondary language to the target language; wherein: converting the obtained string from the primary input language to the target language comprises using the phonetic lexicon to interpret the obtained string in the target language based upon a phonetic correspondence of the obtained string in the primary input language; and converting the obtained string from the second input language to the target language comprises using the translation lexicon to translate the obtained string from the secondary language to the target language. | 0.5 |
7,672,436 | 16 | 17 | 16. The method of claim 12 , wherein said reply message comprises a voice memo in response to a specific portion of said original email message, and wherein the method further comprises the step of processing said email message to detect a tag associated with said voice memo, and responsively rendering said voice memo as speech. | 16. The method of claim 12 , wherein said reply message comprises a voice memo in response to a specific portion of said original email message, and wherein the method further comprises the step of processing said email message to detect a tag associated with said voice memo, and responsively rendering said voice memo as speech. 17. The method of claim 16 , wherein said tag comprises a pointer to an object comprising said voice memo. | 0.5 |
8,615,708 | 19 | 25 | 19. A method comprising: parsing a meta-language style sheet comprising at least one meta-language style sheet variable declaration and at least one meta-language style sheet rule definition referencing the at least one meta-language style sheet variable; generating, based on the parsing, an intermediate representation of the meta-language style sheet variable declaration and an intermediate representation of the meta-language style sheet rule definition; generating executable code based at least on both the intermediate representation of the meta-language style sheet variable declaration and the intermediate representation of the meta-language style sheet rule definition; obtaining a plurality of new values for the meta-language style sheet variable; and in response to obtaining each new value, performing the operations of: executing the executable code using the each new value to produce a web browser style sheet that reflects the each new value, and updating display of a web page using the web browser style sheet that reflects the each new value; wherein the method is performed by one or more computing devices. | 19. A method comprising: parsing a meta-language style sheet comprising at least one meta-language style sheet variable declaration and at least one meta-language style sheet rule definition referencing the at least one meta-language style sheet variable; generating, based on the parsing, an intermediate representation of the meta-language style sheet variable declaration and an intermediate representation of the meta-language style sheet rule definition; generating executable code based at least on both the intermediate representation of the meta-language style sheet variable declaration and the intermediate representation of the meta-language style sheet rule definition; obtaining a plurality of new values for the meta-language style sheet variable; and in response to obtaining each new value, performing the operations of: executing the executable code using the each new value to produce a web browser style sheet that reflects the each new value, and updating display of a web page using the web browser style sheet that reflects the each new value; wherein the method is performed by one or more computing devices. 25. The method of claim 19 , wherein the intermediate representation of the meta-language style sheet rule comprises data that specifies that the intermediate representation of the meta-language style sheet rule represents a meta-language style sheet rule. | 0.578947 |
9,727,925 | 14 | 21 | 14. A non-transitory computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process comprising: identifying an internal social network for an enterprise; collecting a set of messages from the internal social network; performing semantic filtering to the set of messages, the semantic filtering reducing an excess noise associated with data that is not relevant to the enterprise; performing semantic analysis upon the set of messages collected from the internal social network to determine a contextual significance of one or more terms in the set of messages; identifying themes in the set of messages, the themes pertaining to at least one of customer preferences, demographic information, industry trends, customer view points: as a result of the performed semantic analysis, clustering together messages that are similar to each other; categorizing the set of messages into a plurality of categories based at least in part on the contextual significance of the one or more terms in the set of messages; associating each category of the plurality of categories with one or more tags; associating respective tags to the set of messages that are categorized as a result of the semantic analysis to generate a set of tagged messages; determining associations between the one or more tags and one or more enterprise applications corresponding to the enterprise such that the set of tagged messages are sent to respective ones of the one or more enterprise applications based at least in part on the determined associations: and storing the tagged messages in an actionable social message store, the actionable message store storing in a table format for each message, one or more of a source of the message, a topic parameter associated with the message, data associated with the message, and the one or more tags associated with the message, wherein the semantic analysis performed comprises latent semantic analysis (LSAT), the LSA referring to a form of statistical language modeling that distinguishes two identical words based on a semantic significance of the word. | 14. A non-transitory computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process comprising: identifying an internal social network for an enterprise; collecting a set of messages from the internal social network; performing semantic filtering to the set of messages, the semantic filtering reducing an excess noise associated with data that is not relevant to the enterprise; performing semantic analysis upon the set of messages collected from the internal social network to determine a contextual significance of one or more terms in the set of messages; identifying themes in the set of messages, the themes pertaining to at least one of customer preferences, demographic information, industry trends, customer view points: as a result of the performed semantic analysis, clustering together messages that are similar to each other; categorizing the set of messages into a plurality of categories based at least in part on the contextual significance of the one or more terms in the set of messages; associating each category of the plurality of categories with one or more tags; associating respective tags to the set of messages that are categorized as a result of the semantic analysis to generate a set of tagged messages; determining associations between the one or more tags and one or more enterprise applications corresponding to the enterprise such that the set of tagged messages are sent to respective ones of the one or more enterprise applications based at least in part on the determined associations: and storing the tagged messages in an actionable social message store, the actionable message store storing in a table format for each message, one or more of a source of the message, a topic parameter associated with the message, data associated with the message, and the one or more tags associated with the message, wherein the semantic analysis performed comprises latent semantic analysis (LSAT), the LSA referring to a form of statistical language modeling that distinguishes two identical words based on a semantic significance of the word. 21. The computer readable medium of claim 14 , wherein the sequence of instructions further comprises steps to utilize results of the semantic to tailor communications to employees. | 0.601322 |
10,019,438 | 5 | 6 | 5. The method of claim 2 , wherein a hidden layer of the external word embedding neural network language model applies a hidden layer weight matrix to the input features. | 5. The method of claim 2 , wherein a hidden layer of the external word embedding neural network language model applies a hidden layer weight matrix to the input features. 6. The method of claim 5 , wherein the external embedding neural network language model determines an output of the hidden layer, h i , as follows:
h i =σ( x i W ), where σ is a point-wise sigmoid function, x i represents the input features, and W is the hidden layer weight matrix. | 0.5 |
9,965,561 | 17 | 20 | 17. The computing device of claim 15 , wherein the search record includes the code corresponding to the instance of execution of the browser-executable component, and wherein the browser-executable component is configured to request a resource corresponding to the browser from the computing device. | 17. The computing device of claim 15 , wherein the search record includes the code corresponding to the instance of execution of the browser-executable component, and wherein the browser-executable component is configured to request a resource corresponding to the browser from the computing device. 20. The computing device of claim 17 , wherein the code is one of a random set of numbers or characters or an incremented number. | 0.783557 |
9,164,983 | 2 | 3 | 2. The method of claim 1 , the identification of the contextual similarity further comprising: identifying a first weight vector including a first plurality of weights with each weight in the first plurality of weights being an identified weight for one token in the first plurality of tokens; identifying a second weight vector including a second plurality of weights with each weight in the second plurality of weights being an identified weight for one token in the second plurality of tokens; identifying a sum of products of the first plurality of weights in the first weight vector multiplied by corresponding weights in the second plurality of weights in the second weight vector; identifying a first square root of a sum of squared values of the first plurality of weights in the first weight vector; identifying a second square root of a sum of squared values of the second plurality of weights in the second weight vector; and identifying the contextual similarity with reference to the identified sum divided by a product of the first square root multiplied by the second square root. | 2. The method of claim 1 , the identification of the contextual similarity further comprising: identifying a first weight vector including a first plurality of weights with each weight in the first plurality of weights being an identified weight for one token in the first plurality of tokens; identifying a second weight vector including a second plurality of weights with each weight in the second plurality of weights being an identified weight for one token in the second plurality of tokens; identifying a sum of products of the first plurality of weights in the first weight vector multiplied by corresponding weights in the second plurality of weights in the second weight vector; identifying a first square root of a sum of squared values of the first plurality of weights in the first weight vector; identifying a second square root of a sum of squared values of the second plurality of weights in the second weight vector; and identifying the contextual similarity with reference to the identified sum divided by a product of the first square root multiplied by the second square root. 3. The method of claim 2 , the identification of one weight in the first plurality of weights for one token in the first plurality of tokens further comprising: identifying a first number of occurrences of the one token in the text corpus in a location that is proximate to the non-standard token; identifying a total number of occurrences of the one token in the text corpus; identifying a number of messages in the text corpus that include at least one occurrence of the one token; and identifying the one weight in the first plurality of weights for the one token in the first plurality of tokens with reference to a product of a ratio of the first number of occurrences of the one token to the total number of occurrences of the first token multiplied by a logarithm of a ratio of a predetermined total number of messages in the text corpus to the identified number of messages in the text corpus that include the at least one occurrence of the one token. | 0.5 |
8,306,822 | 5 | 9 | 5. The method of claim 1 and further comprising: utilizing a user interface element to provide online help information that is associated with the portion of the text. | 5. The method of claim 1 and further comprising: utilizing a user interface element to provide online help information that is associated with the portion of the text. 9. The method of claim 5 , wherein providing the online help information includes providing information related to a meaning of a word in the portion of the text. | 0.517857 |
9,524,307 | 3 | 4 | 3. The method of claim 1 , further comprising performing by the second thread: storing the error checking result in a second queue. | 3. The method of claim 1 , further comprising performing by the second thread: storing the error checking result in a second queue. 4. The method of claim 3 , further comprising performing by the first thread: retrieving one or more error checking results from the second queue; and for each retrieved error checking result: determining whether an element currently exists within the document that has an ID that is the same as the ID associated with the retrieved error checking result; and in response to determining that the element currently exists within the document that has the ID that is the same as the ID associated with the retrieved error checking result, generating an indication that the element is in error. | 0.5 |
9,311,505 | 10 | 12 | 10. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, determine an ontology for specifying a hierarchy of one or more abstraction levels for items data used in latent factorization models; generate one or more user models for the items data corresponding to each abstraction level of the ontology; process at least one request for one or more recommendations (a) to determine a requested abstraction level, and (b) to determine a privacy level, a security level, or a combination thereof associated with the at least one request; process the privacy level, the security level, or the combination thereof against one or more privacy policies, one or more security policies, or a combination thereof to determine permission to access the requested abstraction level; generate and/or retrieve the at least one of the one or more user models based, at least in part, on whether the at least one of the one or more user models exists at the requested abstraction level, select at least one of the one or more user models for generating the one or more recommendations for one or more applications, one or more services, or a combination thereof based, at least in part, on the one or more privacy policies, the one or more security policies, or the combination thereof; and wherein the one or more abstraction levels correspond to different levels of the privacy policies and the security policies of the one or more user models. | 10. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, determine an ontology for specifying a hierarchy of one or more abstraction levels for items data used in latent factorization models; generate one or more user models for the items data corresponding to each abstraction level of the ontology; process at least one request for one or more recommendations (a) to determine a requested abstraction level, and (b) to determine a privacy level, a security level, or a combination thereof associated with the at least one request; process the privacy level, the security level, or the combination thereof against one or more privacy policies, one or more security policies, or a combination thereof to determine permission to access the requested abstraction level; generate and/or retrieve the at least one of the one or more user models based, at least in part, on whether the at least one of the one or more user models exists at the requested abstraction level, select at least one of the one or more user models for generating the one or more recommendations for one or more applications, one or more services, or a combination thereof based, at least in part, on the one or more privacy policies, the one or more security policies, or the combination thereof; and wherein the one or more abstraction levels correspond to different levels of the privacy policies and the security policies of the one or more user models. 12. An apparatus of claim 10 , wherein the apparatus is further caused to: process the at least one request to determine a requested segment of the selected at least one user model; and generate and/or retrieve the requested segment based, at least in part, on whether the requested segment exists. | 0.720974 |
8,713,117 | 14 | 24 | 14. In a mobile consumer messaging system (MCMS), in which the MCMS is in electronic communications with a plurality of mobile device users via one or more mobile carrier networks and is in electronic communications with one or more chat agents utilizing one or more chat platforms, a method for facilitating messages between the plurality of mobile devices users and the one or more chat agents, comprising the steps of: receiving a particular chat message at the MCMS from a specific mobile device user via a respective mobile carrier network, wherein the particular chat message includes message content and message identifying information; extracting via the MCMS the message content and message identifying information from the particular chat message and storing the message content and message identifying information in an MCMS database; comparing the message identifying information to stored message identifying information in the MCMS database, wherein the stored message identifying information is associated with one or more ongoing chat sessions between mobile device users and chat agents; if match exists between the message identifying information and the stored message identifying information, retrieving a specific chat session associated with the stored message identifying information and associating the particular chat message with the specific chat session; generating via the MCMS a new message in a format acceptable to a respective chat platform, wherein the new message includes the message content and is based on the stored message identifying information associated with the specific chat session; and transmitting the new message from the MCMS to a respective chat agent associated with the specific chat session and utilizing a respective chat platform. | 14. In a mobile consumer messaging system (MCMS), in which the MCMS is in electronic communications with a plurality of mobile device users via one or more mobile carrier networks and is in electronic communications with one or more chat agents utilizing one or more chat platforms, a method for facilitating messages between the plurality of mobile devices users and the one or more chat agents, comprising the steps of: receiving a particular chat message at the MCMS from a specific mobile device user via a respective mobile carrier network, wherein the particular chat message includes message content and message identifying information; extracting via the MCMS the message content and message identifying information from the particular chat message and storing the message content and message identifying information in an MCMS database; comparing the message identifying information to stored message identifying information in the MCMS database, wherein the stored message identifying information is associated with one or more ongoing chat sessions between mobile device users and chat agents; if match exists between the message identifying information and the stored message identifying information, retrieving a specific chat session associated with the stored message identifying information and associating the particular chat message with the specific chat session; generating via the MCMS a new message in a format acceptable to a respective chat platform, wherein the new message includes the message content and is based on the stored message identifying information associated with the specific chat session; and transmitting the new message from the MCMS to a respective chat agent associated with the specific chat session and utilizing a respective chat platform. 24. The method of claim 14 , wherein the MCMS includes a management computer system for performing functions of the MCMS. | 0.954648 |
6,122,617 | 9 | 12 | 9. A method of distributing information to an end-user in text form for subsequent conversion into audible speech at an end-user location, the method comprising the steps of: receiving at a collection site an information item from an information provider, wherein the information item includes text data in a format suitable for input to a text-to-speech synthesizer at an end-user location and for conversion into audible speech thereby; detecting at the collection site a portion of the text data of the information item that will cause the generation of improperly spoken speech therefrom by the text-to-speech synthesizer; editing at the collection site the detected portion of the text data of the information item to produce an edited information item that will cause the generation of properly spoken speech therefrom by the text-to-speech synthesizer; and, communicating the edited information item from the collection site through a communication channel to the end-user location for subsequent input to the text-to-speech synthesizer for conversion into audible speech. | 9. A method of distributing information to an end-user in text form for subsequent conversion into audible speech at an end-user location, the method comprising the steps of: receiving at a collection site an information item from an information provider, wherein the information item includes text data in a format suitable for input to a text-to-speech synthesizer at an end-user location and for conversion into audible speech thereby; detecting at the collection site a portion of the text data of the information item that will cause the generation of improperly spoken speech therefrom by the text-to-speech synthesizer; editing at the collection site the detected portion of the text data of the information item to produce an edited information item that will cause the generation of properly spoken speech therefrom by the text-to-speech synthesizer; and, communicating the edited information item from the collection site through a communication channel to the end-user location for subsequent input to the text-to-speech synthesizer for conversion into audible speech. 12. The method of claim 9, wherein the method further includes the steps of receiving at the collection site a plurality of information items that include text data in a format suitable for input to the text-to-speech synthesizer at the end-user location and for conversion into audible speech thereby, wherein the information item is one information item of the plurality of information items, receiving at the collection site selection criteria from the end-user location, wherein the received selection criteria identifies a type of information item desired for receipt by an end-user at the end-user location, and, selecting at the collection site for communication to the end-user location information items from the plurality of information items using the received selection criteria. | 0.5 |
9,323,827 | 19 | 20 | 19. A computer system for identifying at least one key term related to a similar passage comprising: a hardware processor; and a non-transitory computer-readable storage medium storing executable instructions configured to, when executed by the processor, perform steps comprising: identifying a plurality of documents stored in a corpus, wherein each identified document contains an instance of the similar passage; for each similar passage instance within the identified documents, extracting each word that appears within a threshold number of words before the similar passage instance within the identified document and each word that appears within a threshold number of words after the similar passage within the identified document, the extracted words associated with the similar passage instance; combining the extracted words associated with each similar passage instance to form a context aggregation; determining a plurality of key terms related to the similar passage based on the context aggregation, each key term associated with a subset of similar passage instances, at least one key term determined by comparing words within the context aggregation to a terms database specifying possible key terms and extracting a word within the context aggregation that matches a term in the terms database; presenting each of one or more key terms as a hyperlink in a user interface; receiving a selection of a key term presented as a hyperlink; and presenting the subset of similar passage instances associated with the selected key term in the user interface. | 19. A computer system for identifying at least one key term related to a similar passage comprising: a hardware processor; and a non-transitory computer-readable storage medium storing executable instructions configured to, when executed by the processor, perform steps comprising: identifying a plurality of documents stored in a corpus, wherein each identified document contains an instance of the similar passage; for each similar passage instance within the identified documents, extracting each word that appears within a threshold number of words before the similar passage instance within the identified document and each word that appears within a threshold number of words after the similar passage within the identified document, the extracted words associated with the similar passage instance; combining the extracted words associated with each similar passage instance to form a context aggregation; determining a plurality of key terms related to the similar passage based on the context aggregation, each key term associated with a subset of similar passage instances, at least one key term determined by comparing words within the context aggregation to a terms database specifying possible key terms and extracting a word within the context aggregation that matches a term in the terms database; presenting each of one or more key terms as a hyperlink in a user interface; receiving a selection of a key term presented as a hyperlink; and presenting the subset of similar passage instances associated with the selected key term in the user interface. 20. The computer system of claim 19 , wherein the means for determining at least one key term further comprises: means for performing a TF-IDF analysis of the context aggregation to determine the at least one key term. | 0.68314 |
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