patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
0.99
|
|---|---|---|---|---|---|
8,244,038 | 8 | 11 | 8. A vectorization system for scanned document, comprising: a memory that stores computer-executable instructions for: performing an optical character recognition (OCR) algorithm that detects a text character in the scanned document; performing a table lookup of a rule database that identifies one or more dominant point detection rules for detecting dominant pointr; applying the one or more identified dominant point detection rules to the text character to detect dominant points on the text character; fitting one or more curves to each text character outline between neighboring dominant points using the detected dominant points; and storing a vectorized text character for use in a vector representation of the scanned document; and a processor that executes the computer-executable instructions. | 8. A vectorization system for scanned document, comprising: a memory that stores computer-executable instructions for: performing an optical character recognition (OCR) algorithm that detects a text character in the scanned document; performing a table lookup of a rule database that identifies one or more dominant point detection rules for detecting dominant pointr; applying the one or more identified dominant point detection rules to the text character to detect dominant points on the text character; fitting one or more curves to each text character outline between neighboring dominant points using the detected dominant points; and storing a vectorized text character for use in a vector representation of the scanned document; and a processor that executes the computer-executable instructions. 11. The system of claim 8 , wherein the dominant point is a maximum or minimum of the text character for a certain direction. | 0.825905 |
7,895,232 | 8 | 9 | 8. Apparatus for searching a corpus of documents, the apparatus comprising: an interface, for receiving a query that is defined as a twig comprising a root annotation operator having an associated tag specifying a span and having an associated expression indicative of one or more terms whose occurrence within the span will satisfy the query; and a processor, which is configured to process the query by recursively selecting an object from a group of objects that consists of the tag and the expression, and advancing through the corpus using the selected object until a candidate document is found that contains the tag and satisfies the expression, and evaluating the candidate document to determine whether the one or more terms indicated by the expression occur within the span in the candidate document so as to satisfy the annotation operator, and to retrieve the candidate document from the corpus upon determining that the annotation operator is satisfied. | 8. Apparatus for searching a corpus of documents, the apparatus comprising: an interface, for receiving a query that is defined as a twig comprising a root annotation operator having an associated tag specifying a span and having an associated expression indicative of one or more terms whose occurrence within the span will satisfy the query; and a processor, which is configured to process the query by recursively selecting an object from a group of objects that consists of the tag and the expression, and advancing through the corpus using the selected object until a candidate document is found that contains the tag and satisfies the expression, and evaluating the candidate document to determine whether the one or more terms indicated by the expression occur within the span in the candidate document so as to satisfy the annotation operator, and to retrieve the candidate document from the corpus upon determining that the annotation operator is satisfied. 9. The apparatus according to claim 8 , wherein the one or more terms comprise at least two terms, and wherein the expression comprises an intermediate operator that defines a relation between the terms. | 0.838889 |
6,163,769 | 8 | 11 | 8. An apparatus for generating speech from text, comprising: storage means for storing a set of decision tree based context-dependent phoneme-based units of a target speaker, wherein a central phoneme-based unit is selected from a group consisting of a phoneme and a diphone, wherein each context-dependent phoneme-based unit is arranged based on context of at least one immediately preceding and succeeding phoneme-based unit, and wherein at least one of the context-dependent phoneme-based units represents other non-stored context-dependent phoneme-based units of similar sound due to similar contexts; a text analyzer for obtaining a string of phonetic symbols representative of a text to be converted to speech; and a concatenation module for selecting stored decision tree base context-dependent phoneme-based units from the set of decision tree based context-dependent phoneme-based units based on the context of the phonetic symbols and synthesizing the selected context-dependent phoneme-based units to generate speech corresponding to the text. | 8. An apparatus for generating speech from text, comprising: storage means for storing a set of decision tree based context-dependent phoneme-based units of a target speaker, wherein a central phoneme-based unit is selected from a group consisting of a phoneme and a diphone, wherein each context-dependent phoneme-based unit is arranged based on context of at least one immediately preceding and succeeding phoneme-based unit, and wherein at least one of the context-dependent phoneme-based units represents other non-stored context-dependent phoneme-based units of similar sound due to similar contexts; a text analyzer for obtaining a string of phonetic symbols representative of a text to be converted to speech; and a concatenation module for selecting stored decision tree base context-dependent phoneme-based units from the set of decision tree based context-dependent phoneme-based units based on the context of the phonetic symbols and synthesizing the selected context-dependent phoneme-based units to generate speech corresponding to the text. 11. The apparatus of claim 8 wherein the storage means includes at least two decision tree based context-dependent phoneme-based units representing other non-stored decision tree base context-dependent phoneme-based units of similar sound due to similar context, and wherein the concatenation module selects one of said at least two decision tree based context-dependent phoneme-based units to minimize a joint distortion function. | 0.5 |
9,715,490 | 9 | 17 | 9. The computer program product of claim 8 , the stored program instructions further comprising: responsive to determining the at least one language associated with the text of the one or more previous conversations between the first user and the at least one second user is not detected with the second confidence level that exceeds the second pre-defined threshold, program instructions to retrieve text from one or more previous conversations by at least one of the first user and the at least one second user; program instructions to detect at least one language associated with the text of the one or more previous conversations by at least one of the first user and the at least one second user; and program instructions to determine the at least one language associated with the text of the one or more previous conversations by at least one of the first user and the at least one second user is detected with a third confidence level that exceeds a third pre-defined threshold. | 9. The computer program product of claim 8 , the stored program instructions further comprising: responsive to determining the at least one language associated with the text of the one or more previous conversations between the first user and the at least one second user is not detected with the second confidence level that exceeds the second pre-defined threshold, program instructions to retrieve text from one or more previous conversations by at least one of the first user and the at least one second user; program instructions to detect at least one language associated with the text of the one or more previous conversations by at least one of the first user and the at least one second user; and program instructions to determine the at least one language associated with the text of the one or more previous conversations by at least one of the first user and the at least one second user is detected with a third confidence level that exceeds a third pre-defined threshold. 17. The computer program product of claim 9 , the stored program instructions further comprising, responsive to determining the at least one language associated with the text of the one or more previous conversations by at least one of the first user and the at least one second user is not detected with the second confidence level that exceeds the second pre-defined threshold, program instructions to retrieve one or more preferred languages of the first user and the at least one second user. | 0.5 |
7,770,104 | 11 | 13 | 11. A method for telephone-based electronic communication, said method comprising: receiving an incoming telephone call from a user; allowing said user to enter login and password information using predetermined codes; verifying login and password information for said user to provide access to a menu of communication options; presenting a menu of communication options to said user including: interacting with an e-mail account; and interacting with the internet; and allowing said user to select one of said communication options using a predetermined code, wherein said communication option of interacting with the internet includes: accepting a document location from said user specified by at least one of a favorites menu and user input; retrieving a document specified by said document location; building a new text body based on the text document, wherein the new text body includes HTML document table text in accordance with a subscript tag and a superscript tag; and further comprising adding comma length pauses in accordance with at least one of: a list item tag, a hyperlink tag, a paragraph tag, a horizontal line tag, and a table element end tag in the HTML document; audibly transmitting the contents of said document to said user, wherein said contents include at least one link to an additional document; accepting an instruction from said user to retrieve said additional document; and retrieving said additional document, wherein said communication option of interacting with an e-mail account includes: retrieving an e-mail from a mail account; listing the subject line and send name of said e-mail for said user; presenting the user with the option of sending one of several preselected replies by entering a code; and sending an e-mail reply when selected by said user. | 11. A method for telephone-based electronic communication, said method comprising: receiving an incoming telephone call from a user; allowing said user to enter login and password information using predetermined codes; verifying login and password information for said user to provide access to a menu of communication options; presenting a menu of communication options to said user including: interacting with an e-mail account; and interacting with the internet; and allowing said user to select one of said communication options using a predetermined code, wherein said communication option of interacting with the internet includes: accepting a document location from said user specified by at least one of a favorites menu and user input; retrieving a document specified by said document location; building a new text body based on the text document, wherein the new text body includes HTML document table text in accordance with a subscript tag and a superscript tag; and further comprising adding comma length pauses in accordance with at least one of: a list item tag, a hyperlink tag, a paragraph tag, a horizontal line tag, and a table element end tag in the HTML document; audibly transmitting the contents of said document to said user, wherein said contents include at least one link to an additional document; accepting an instruction from said user to retrieve said additional document; and retrieving said additional document, wherein said communication option of interacting with an e-mail account includes: retrieving an e-mail from a mail account; listing the subject line and send name of said e-mail for said user; presenting the user with the option of sending one of several preselected replies by entering a code; and sending an e-mail reply when selected by said user. 13. The method of claim 11 wherein said selecting one of said communication options using a predetermined code includes using a voice generated code. | 0.579096 |
7,917,398 | 14 | 15 | 14. The system of claim 13 , further wherein: the ticket information in the web browsing language comprises a ticket listing corresponding to tickets of the filtered ticket set located in a plurality of sections; the interactive graphics-based event venue map accepts a particular section of interest; and ticket information is displayed in the web browsing language corresponding to the tickets of the filtered ticket set located in the particular section of interest. | 14. The system of claim 13 , further wherein: the ticket information in the web browsing language comprises a ticket listing corresponding to tickets of the filtered ticket set located in a plurality of sections; the interactive graphics-based event venue map accepts a particular section of interest; and ticket information is displayed in the web browsing language corresponding to the tickets of the filtered ticket set located in the particular section of interest. 15. The system of claim 14 , wherein the ticket information in the web browsing language corresponding to the tickets of the filtered ticket set located in the particular section of interest is displayed as an overlay on the particular section of interest on the interactive graphics-based event venue map. | 0.5 |
7,962,328 | 16 | 17 | 16. An apparatus comprising: discriminant representation means for providing, to a user, representations of a plurality of discriminants of meanings of a plurality of symbols in a natural language, wherein each of the plurality of discriminants is associated with a corresponding finite set of mutually exclusive answers to the discriminant, and wherein the plurality of discriminants are orthogonal to each other; means for receiving, from the user, input representing a plurality of answers to the plurality of discriminants, wherein each of the plurality of answers from the user is selected from the finite set of mutually exclusive answers to the corresponding discriminant, wherein the means for receiving comprises: means for receiving first input from the user representing a first answer to a first one of the plurality of discriminants; and means for receiving second input, independent of the first input, from the user representing a second answer to a second one of the plurality of discriminants; and means for generating, in response to the input, a data structure tangibly stored in a computer-readable memory, the data structure comprising data representing the plurality of answers from the user, including the first answer and the second answer, and thereby representing a meaning of one of the plurality of symbols in the natural language; wherein the plurality of discriminants includes at least one Realm-related discriminant and one discriminant for distinguishing between composite and characteristic meanings in the natural language, wherein Realm-related discriminants include a discriminant for distinguishing between natural and artificial meanings in the natural language and a discriminant for distinguishing between concrete and information meanings in the natural language. | 16. An apparatus comprising: discriminant representation means for providing, to a user, representations of a plurality of discriminants of meanings of a plurality of symbols in a natural language, wherein each of the plurality of discriminants is associated with a corresponding finite set of mutually exclusive answers to the discriminant, and wherein the plurality of discriminants are orthogonal to each other; means for receiving, from the user, input representing a plurality of answers to the plurality of discriminants, wherein each of the plurality of answers from the user is selected from the finite set of mutually exclusive answers to the corresponding discriminant, wherein the means for receiving comprises: means for receiving first input from the user representing a first answer to a first one of the plurality of discriminants; and means for receiving second input, independent of the first input, from the user representing a second answer to a second one of the plurality of discriminants; and means for generating, in response to the input, a data structure tangibly stored in a computer-readable memory, the data structure comprising data representing the plurality of answers from the user, including the first answer and the second answer, and thereby representing a meaning of one of the plurality of symbols in the natural language; wherein the plurality of discriminants includes at least one Realm-related discriminant and one discriminant for distinguishing between composite and characteristic meanings in the natural language, wherein Realm-related discriminants include a discriminant for distinguishing between natural and artificial meanings in the natural language and a discriminant for distinguishing between concrete and information meanings in the natural language. 17. The apparatus of claim 16 , wherein the finite set of mutually exclusive answers to at least one of the plurality of discriminants consists of exactly two answers. | 0.663306 |
7,899,657 | 32 | 51 | 32. A computer-based system for parameterizing a steady-state model of an in-situ hydrocarbon reservoir, the model having a plurality of model parameters for mapping model input to model output through a stored representation of said reservoir, the system comprising: a computer, comprising: a processor; and a memory medium coupled to the processor; an input coupled to the processor and the memory medium, wherein the input is operable to receive a training data set comprising a plurality of input values and a plurality of target output values, wherein the training data set is representative of production operations of said reservoir; and an output coupled to the processor and the memory medium; wherein the memory medium stores program instructions which are executable by the processor to: receive a next at least one input value of the plurality of input values and a next target output value of the plurality of target output values; parameterize the model with a predetermined algorithm using said next at least one input value and said next target output value, and one or more derivative constraints, wherein the one or more derivative constraints are imposed to constrain relationships between the at least one input value and a resulting model output value, wherein said parameterizing comprises using an optimizer to perform constrained optimization on the plurality of model parameters to satisfy an objective function subject to the derivative constraints; iteratively perform said receiving and said parameterizing using the optimizer to generate a parameterized model, wherein the model comprises a model function, wherein the one or more derivative constraints comprise upper and/or lower bounds on one or more model function derivatives, wherein one or more of the model function derivatives comprise one or more of: a first order derivative of the model function, wherein the first order derivative represents inter-well transmissibilities; a second order derivative of the model function, wherein the second order derivative of the model function represents curvature of the inter-well transmissibilities; and/or a third order derivative of the model function, wherein the third order derivative of the model function represents rate of curvature of the inter-well transmissibilities; and store the parameterized model in the memory medium, wherein the parameterized model is usable to analyze reservoir operations; and wherein the output is operable to provide the parameterized model and/or the resulting model output values to other systems or processes to manage the reservoir operations. | 32. A computer-based system for parameterizing a steady-state model of an in-situ hydrocarbon reservoir, the model having a plurality of model parameters for mapping model input to model output through a stored representation of said reservoir, the system comprising: a computer, comprising: a processor; and a memory medium coupled to the processor; an input coupled to the processor and the memory medium, wherein the input is operable to receive a training data set comprising a plurality of input values and a plurality of target output values, wherein the training data set is representative of production operations of said reservoir; and an output coupled to the processor and the memory medium; wherein the memory medium stores program instructions which are executable by the processor to: receive a next at least one input value of the plurality of input values and a next target output value of the plurality of target output values; parameterize the model with a predetermined algorithm using said next at least one input value and said next target output value, and one or more derivative constraints, wherein the one or more derivative constraints are imposed to constrain relationships between the at least one input value and a resulting model output value, wherein said parameterizing comprises using an optimizer to perform constrained optimization on the plurality of model parameters to satisfy an objective function subject to the derivative constraints; iteratively perform said receiving and said parameterizing using the optimizer to generate a parameterized model, wherein the model comprises a model function, wherein the one or more derivative constraints comprise upper and/or lower bounds on one or more model function derivatives, wherein one or more of the model function derivatives comprise one or more of: a first order derivative of the model function, wherein the first order derivative represents inter-well transmissibilities; a second order derivative of the model function, wherein the second order derivative of the model function represents curvature of the inter-well transmissibilities; and/or a third order derivative of the model function, wherein the third order derivative of the model function represents rate of curvature of the inter-well transmissibilities; and store the parameterized model in the memory medium, wherein the parameterized model is usable to analyze reservoir operations; and wherein the output is operable to provide the parameterized model and/or the resulting model output values to other systems or processes to manage the reservoir operations. 51. The system of claim 32 , wherein the program instructions are further executable to: receive a second objective function, wherein the second objective function represents a specified objective of reservoir operations; and use the optimizer and the parameterized model to determine operation of the reservoir that satisfies the second objective function. | 0.544643 |
9,747,284 | 5 | 7 | 5. The method of claim 1 , wherein searching the source string to identify all portions of the source string that meet a search criterion comprises: searching to identify a match between a string in the glossary data and a portion of the source string; searching to identify a match between a string in the translation memory data and a portion of the source string; or applying at least one regular expression of the source-identification rule data to identify any portions of the source string as private information for sequestration. | 5. The method of claim 1 , wherein searching the source string to identify all portions of the source string that meet a search criterion comprises: searching to identify a match between a string in the glossary data and a portion of the source string; searching to identify a match between a string in the translation memory data and a portion of the source string; or applying at least one regular expression of the source-identification rule data to identify any portions of the source string as private information for sequestration. 7. The method of claim 5 , wherein the sequestered data comprises names, account numbers, addresses and telephone numbers. | 0.837333 |
8,719,016 | 11 | 15 | 11. A method of determining scripts within speech associated with a contact center, comprising: translating a speech into text using a text-to-speech communication processing system; receiving a transcript of the speech; analyzing the transcript to determine repetitions within the speech that are indicative of structured speech, wherein the text is analyzed using Large Vocabulary Continuous Speech Recognition (LVCSR); and determining a duration distribution and length of the repetitions with the speed to determine which repetitions are scripts; comparing probability of correct translation of the text-to-speech communication for each word in the text to an appropriate occurrence table, wherein the occurrence table is selected based upon dialect or language of the speech, and domain in which the speech was obtained; and modifying the occurrence table based on the probability of correct translation for each word in the text. | 11. A method of determining scripts within speech associated with a contact center, comprising: translating a speech into text using a text-to-speech communication processing system; receiving a transcript of the speech; analyzing the transcript to determine repetitions within the speech that are indicative of structured speech, wherein the text is analyzed using Large Vocabulary Continuous Speech Recognition (LVCSR); and determining a duration distribution and length of the repetitions with the speed to determine which repetitions are scripts; comparing probability of correct translation of the text-to-speech communication for each word in the text to an appropriate occurrence table, wherein the occurrence table is selected based upon dialect or language of the speech, and domain in which the speech was obtained; and modifying the occurrence table based on the probability of correct translation for each word in the text. 15. The method of claim 11 , wherein modification of the occurrence table changes the occurrence probability by a fixed percentage or a variable percentage based on the probability of correct translation of a given word. | 0.5 |
8,027,966 | 5 | 8 | 5. A document searching program stored on a tangible computer-useable medium, wherein the documents are written in a plurality of languages, the program comprising: a module for identifying keywords from each of the plurality of documents; a module for translating each identified keyword into each of the plurality of languages; a module for creating an index in each of the plurality of languages; a module for receiving a first query that includes at least one keyword in a first language; a module for generating a second query by translating the at least one keyword into a second language; a module for applying the first query against documents written in both the first language and the second language; a module for applying the second query against documents written in the second language; a module for generating a first set of results that includes each document written in the first language that matches the first query; and a module for generating a second set of results that includes each document written in the second language that matches at least one of the first query or the second query. | 5. A document searching program stored on a tangible computer-useable medium, wherein the documents are written in a plurality of languages, the program comprising: a module for identifying keywords from each of the plurality of documents; a module for translating each identified keyword into each of the plurality of languages; a module for creating an index in each of the plurality of languages; a module for receiving a first query that includes at least one keyword in a first language; a module for generating a second query by translating the at least one keyword into a second language; a module for applying the first query against documents written in both the first language and the second language; a module for applying the second query against documents written in the second language; a module for generating a first set of results that includes each document written in the first language that matches the first query; and a module for generating a second set of results that includes each document written in the second language that matches at least one of the first query or the second query. 8. The program of claim 5 , further comprising a module for determining a native language of a user. | 0.702381 |
8,832,543 | 12 | 13 | 12. A computer system for formatting a table in a target document, the system comprising: a memory storage; and a processing unit coupled to the memory storage, the processing unit being configured to: determine a selection of a document element from a source table in a source document, determine a paste point in a target document, determine whether the paste point is adjacent to a target table in the target document, compare source formatting properties associated with the document element to target formatting properties associated with the target table in order to determine intended formatting properties for the document element as to be applied in the target table, determine if the document element and the target table have a same number of columns when the paste point is adjacent to the target table in the target document, and merge the document element with the target table with the intended formatting properties when the document element and the target table have the same number of columns. | 12. A computer system for formatting a table in a target document, the system comprising: a memory storage; and a processing unit coupled to the memory storage, the processing unit being configured to: determine a selection of a document element from a source table in a source document, determine a paste point in a target document, determine whether the paste point is adjacent to a target table in the target document, compare source formatting properties associated with the document element to target formatting properties associated with the target table in order to determine intended formatting properties for the document element as to be applied in the target table, determine if the document element and the target table have a same number of columns when the paste point is adjacent to the target table in the target document, and merge the document element with the target table with the intended formatting properties when the document element and the target table have the same number of columns. 13. The computer system of claim 12 , wherein the processing unit is further configured to: display a recovery user interface comprising a selectable action for pasting the document element at the paste point with formatting of the source document; and paste the document element at the paste point with the formatting of the source document in response to receiving the selected action from the recovery user interface. | 0.748503 |
4,350,342 | 8 | 10 | 8. The game apparatus of claim 1 wherein said first and second letter supply means each comprises separate containers having disposed therein a plurality of separate tiles, said tiles displaying said letters and said numerical point values on at least one surface thereof. | 8. The game apparatus of claim 1 wherein said first and second letter supply means each comprises separate containers having disposed therein a plurality of separate tiles, said tiles displaying said letters and said numerical point values on at least one surface thereof. 10. The game apparatus of claim 8 wherein said first letter supply is provided with coloration different from that of said second letter supply. | 0.5 |
8,046,675 | 9 | 11 | 9. A system for supplementing a web graph of linked web documents, the system comprising: a server coupled to one or more client devices via a network, the server comprising: a user interface; a tag module; an identification module operative to: identify an existing web graph of web documents wherein web documents associated with a given category are linked together in the existing web graph; identify one or more experts for one of one or more categories; identify one or more documents tagged by the one or more experts for the given category; and determine a corresponding category of the one or more web documents tagged by the one or more experts for the given category; and a graph module operative to: assign a proxy web document to each one of the one or more experts identified for the given category, the proxy web document representative of a corresponding one of the one or more experts; and link the one or more web documents in the existing web graph corresponding to the given category to one or more proxy web documents and the one or more documents tagged by the one or more experts for the given category. | 9. A system for supplementing a web graph of linked web documents, the system comprising: a server coupled to one or more client devices via a network, the server comprising: a user interface; a tag module; an identification module operative to: identify an existing web graph of web documents wherein web documents associated with a given category are linked together in the existing web graph; identify one or more experts for one of one or more categories; identify one or more documents tagged by the one or more experts for the given category; and determine a corresponding category of the one or more web documents tagged by the one or more experts for the given category; and a graph module operative to: assign a proxy web document to each one of the one or more experts identified for the given category, the proxy web document representative of a corresponding one of the one or more experts; and link the one or more web documents in the existing web graph corresponding to the given category to one or more proxy web documents and the one or more documents tagged by the one or more experts for the given category. 11. The system of claim 9 wherein the graph module is operative to identify one or more documents tagged by the one or more experts for the given category located within the existing web graph of web documents. | 0.511628 |
8,719,696 | 13 | 14 | 13. A method of producing a document comprising the steps of: marking-up an unmarked-up document according to a schema, the marked-up document having explicit structural information corresponding to implicit linguistic content of words in said unmarked-up document; assisting a user to select one of a plurality of stored formats, including providing an interactive interface for the user to select or modify one or more parameters of said selected format specifying a special formatting for representing said implicit linguistic content; receiving a user selection of one of said plurality of stored formats over an electronic network, including said one or more parameters; and generating a user-requested document in electronic form from said marked-up document using said user-selected format and said parameters, said generated user-requested document containing said words of the unmarked-up document modified with said special formatting representing said implicit linguistic content to enhance readability of the generated user-requested document. | 13. A method of producing a document comprising the steps of: marking-up an unmarked-up document according to a schema, the marked-up document having explicit structural information corresponding to implicit linguistic content of words in said unmarked-up document; assisting a user to select one of a plurality of stored formats, including providing an interactive interface for the user to select or modify one or more parameters of said selected format specifying a special formatting for representing said implicit linguistic content; receiving a user selection of one of said plurality of stored formats over an electronic network, including said one or more parameters; and generating a user-requested document in electronic form from said marked-up document using said user-selected format and said parameters, said generated user-requested document containing said words of the unmarked-up document modified with said special formatting representing said implicit linguistic content to enhance readability of the generated user-requested document. 14. The method of claim 13 , wherein said marked-up document includes a plurality of minor structural mark-up elements that contain text, and said document production processor includes each said minor structural mark-up element in said generated user-requested document. | 0.762697 |
8,918,796 | 1 | 6 | 1. A computer implemented method comprising: selecting a first software program and a second software program by placing a first icon on a graphical display screen in a prespecified relationship with a second icon on said display screen; extracting first metadata from at least one database, wherein the first metadata describe a first set of constraints that apply to installation of the first software program on a data processing system; extracting second metadata from the at least one database, wherein the second metadata describe a second set of constraints that apply to installation of the second software program on the data processing system; generating a third set of constraints from the first metadata and the second metadata, wherein the third set of constraints comprise an intersection of the first set of constraints and the second set of constraints; determining whether installation of both the first program and the second program on the data processing system violates any constraint contained in the third set of constraints; and storing the third set of constraints in a tooling mechanism configured to perform extracting the first metadata, extracting the second metadata, generating the third set of constraints, and determining whether installation violates any constraint. | 1. A computer implemented method comprising: selecting a first software program and a second software program by placing a first icon on a graphical display screen in a prespecified relationship with a second icon on said display screen; extracting first metadata from at least one database, wherein the first metadata describe a first set of constraints that apply to installation of the first software program on a data processing system; extracting second metadata from the at least one database, wherein the second metadata describe a second set of constraints that apply to installation of the second software program on the data processing system; generating a third set of constraints from the first metadata and the second metadata, wherein the third set of constraints comprise an intersection of the first set of constraints and the second set of constraints; determining whether installation of both the first program and the second program on the data processing system violates any constraint contained in the third set of constraints; and storing the third set of constraints in a tooling mechanism configured to perform extracting the first metadata, extracting the second metadata, generating the third set of constraints, and determining whether installation violates any constraint. 6. The method of claim 1 further comprising: extracting the first metadata and the second metadata on a static or dynamic basis. | 0.748031 |
8,886,552 | 1 | 5 | 1. A computer system for collecting and analyzing structured user feedback on websites, said computer system comprising: website user structured feedback form generation functionality operative to generate structured feedback forms for providing website user feedback on website user interaction with a website-based process, said structured feedback forms comprising user selectable feedback messages provided in a categorized and nested structure; website user cancellation or abandonment prediction functionality operative to determine, based on a website action of a given user, that the given user intends to cancel a transaction associated with the website-based process or abandon the website-based process and, upon making said determination, automatically present the given user with at least one of the generated website user structured feedback forms or an invitation to enter feedback using at least one of the generated website user structured feedback forms; website user feedback analyzing functionality operative to automatically collect and analyze website user feedback entered in said structured feedback forms and to provide at least one analysis report based on feedback from a multiplicity of website users, said at least one analysis report comprising a structured analysis report based on said categorized and nested structure; and a web analytics interfacing functionality operative to interface with a web analytics service and receive web behavior analysis relating to behaviors of the multiplicity of website users; wherein, said automatic analysis of website user feedback includes factoring the received web behavior analysis in said automatic analysis and producing at least one analysis report that includes an integration of said received web behavior analysis wherein said analyzing functionality is further operative to analyze website user feedback in relation to each of two or more stages in the website-based process separately for each stage, factor into the stage specific analysis web behavior analysis relating to each of the two or more stages and report the results of the analysis in relation to the each of two or more stages separately for each stage. | 1. A computer system for collecting and analyzing structured user feedback on websites, said computer system comprising: website user structured feedback form generation functionality operative to generate structured feedback forms for providing website user feedback on website user interaction with a website-based process, said structured feedback forms comprising user selectable feedback messages provided in a categorized and nested structure; website user cancellation or abandonment prediction functionality operative to determine, based on a website action of a given user, that the given user intends to cancel a transaction associated with the website-based process or abandon the website-based process and, upon making said determination, automatically present the given user with at least one of the generated website user structured feedback forms or an invitation to enter feedback using at least one of the generated website user structured feedback forms; website user feedback analyzing functionality operative to automatically collect and analyze website user feedback entered in said structured feedback forms and to provide at least one analysis report based on feedback from a multiplicity of website users, said at least one analysis report comprising a structured analysis report based on said categorized and nested structure; and a web analytics interfacing functionality operative to interface with a web analytics service and receive web behavior analysis relating to behaviors of the multiplicity of website users; wherein, said automatic analysis of website user feedback includes factoring the received web behavior analysis in said automatic analysis and producing at least one analysis report that includes an integration of said received web behavior analysis wherein said analyzing functionality is further operative to analyze website user feedback in relation to each of two or more stages in the website-based process separately for each stage, factor into the stage specific analysis web behavior analysis relating to each of the two or more stages and report the results of the analysis in relation to the each of two or more stages separately for each stage. 5. The system according to claim 1 , wherein said structured feedback forms do not include a freetext response item. | 0.839335 |
8,275,775 | 9 | 10 | 9. The method of claim 1 , wherein the object access protocol format recognized by a plurality of business intelligence systems is an extensible markup language for analytics (XMLA). | 9. The method of claim 1 , wherein the object access protocol format recognized by a plurality of business intelligence systems is an extensible markup language for analytics (XMLA). 10. The method of claim 9 , wherein the data set output is in a second format not supported by XMLA. | 0.5 |
7,613,452 | 1 | 6 | 1. A routing system for providing a communications service via a network comprising: a switch; a first link coupled to the switch and operable to relay a signal between a calling communications device and the switch; a second link coupled to the switch and operable to relay the signal between a called communications device and the switch; a third link coupled to the switch and operable to relay the signal between an operator communications device and the switch; a processor coupled to the switch operable to receive the signal from the first link and selectively activate the switch as a function of the signal to communicably couple the first link to the second link; and a line condition module in a memory of a computer; wherein the line condition module is operable to monitor the signal as the signal is relayed between the first link and the second link, and to selectively activate the switch as a function of the signal to communicably couple the first link and the second link to the third link. | 1. A routing system for providing a communications service via a network comprising: a switch; a first link coupled to the switch and operable to relay a signal between a calling communications device and the switch; a second link coupled to the switch and operable to relay the signal between a called communications device and the switch; a third link coupled to the switch and operable to relay the signal between an operator communications device and the switch; a processor coupled to the switch operable to receive the signal from the first link and selectively activate the switch as a function of the signal to communicably couple the first link to the second link; and a line condition module in a memory of a computer; wherein the line condition module is operable to monitor the signal as the signal is relayed between the first link and the second link, and to selectively activate the switch as a function of the signal to communicably couple the first link and the second link to the third link. 6. The routing system of claim 1 , wherein the signal is an audio signal. | 0.903183 |
7,673,254 | 1 | 2 | 1. An apparatus, comprising: a processor to receive a control signal from a navigation controller and to display a user interface on a display device, wherein the user interface includes a data entry menu having one or more menu selections, and based on the control signal the processor to activate one of the one or more menu selections to display a data entry method, wherein the data entry method is context and language specific to the activated menu selection by displaying only one or more virtual keys that are necessary for a user to enter data required by the activated menu selection, wherein only a virtual alphabetic keyboard is displayed in the data entry method on the display device when alphabetic user input is required by the activated user selection, and only a virtual numeric keypad is displayed in the data entry method on the display device when numeric user input is required by the activated user selection. | 1. An apparatus, comprising: a processor to receive a control signal from a navigation controller and to display a user interface on a display device, wherein the user interface includes a data entry menu having one or more menu selections, and based on the control signal the processor to activate one of the one or more menu selections to display a data entry method, wherein the data entry method is context and language specific to the activated menu selection by displaying only one or more virtual keys that are necessary for a user to enter data required by the activated menu selection, wherein only a virtual alphabetic keyboard is displayed in the data entry method on the display device when alphabetic user input is required by the activated user selection, and only a virtual numeric keypad is displayed in the data entry method on the display device when numeric user input is required by the activated user selection. 2. The apparatus of claim 1 , wherein the one or more menu selections comprise one or more data entry boxes. | 0.767241 |
8,350,964 | 1 | 6 | 1. A captioned image reproducing device comprising: a memory unit that stores plural caption texts, plural images, and plural pieces of reproduction start information each indicating a timing of starting reproduction of each caption text in the plural caption texts; a caption list creating unit that refers to the memory unit and creates a caption list including therein a predetermined number of caption texts in accordance with a reproduction order; a caption text selecting unit that selects any one of the caption texts included in the caption list; a reproducing unit that reproduces a first caption text selected by the caption text selecting unit and at least one of the plural images corresponding to the reproduction start information of the first caption text; a determination unit that refers to the memory unit, acquires the reproduction start information of the first caption text and reproduction start information of a second caption text different from the first caption text, and compares a difference between the reproduction start information of the first caption text and the reproduction start information of the second caption text with predetermined reference information; a setting unit that sets new reproduction start information between a reproduction order of the first caption text and a reproduction order of the second caption text based on a determination result by the determination unit; and a control unit that controls the memory unit to store the new reproduction start information in association with a predetermined dummy caption, at least one of the plural images, and dummy caption reproduction start information indicating a timing of starting reproduction of the dummy caption. | 1. A captioned image reproducing device comprising: a memory unit that stores plural caption texts, plural images, and plural pieces of reproduction start information each indicating a timing of starting reproduction of each caption text in the plural caption texts; a caption list creating unit that refers to the memory unit and creates a caption list including therein a predetermined number of caption texts in accordance with a reproduction order; a caption text selecting unit that selects any one of the caption texts included in the caption list; a reproducing unit that reproduces a first caption text selected by the caption text selecting unit and at least one of the plural images corresponding to the reproduction start information of the first caption text; a determination unit that refers to the memory unit, acquires the reproduction start information of the first caption text and reproduction start information of a second caption text different from the first caption text, and compares a difference between the reproduction start information of the first caption text and the reproduction start information of the second caption text with predetermined reference information; a setting unit that sets new reproduction start information between a reproduction order of the first caption text and a reproduction order of the second caption text based on a determination result by the determination unit; and a control unit that controls the memory unit to store the new reproduction start information in association with a predetermined dummy caption, at least one of the plural images, and dummy caption reproduction start information indicating a timing of starting reproduction of the dummy caption. 6. The captioned image reproducing device according to claim 1 , wherein: the caption text contains a received caption contained in broadcasting data transmitted from an external device and the dummy caption; the captioned image reproducing device further comprises a caption list display unit that displays the caption list and a switching unit that switches a mode between a first mode that the caption list includes therein only the received caption and a second mode that the caption list includes therein the received caption and the dummy caption; the control unit adds an identifier indicating that a caption text is the received caption or the dummy caption to a caption text stored in the memory unit; and when the switching unit switches the mode, the caption list creating unit determines the identifier added to the caption text, and creates a caption list based on a determination result. | 0.5 |
7,707,566 | 1 | 5 | 1. One or more computer-readable media with computer-executable instructions for implementing a software development architecture comprising: a software development scenario-independent intermediate representation format; one or more exception handling models operable to support a plurality of programming language specific exception handling models for a plurality of different source languages; a type system operable to represent the type representations of the plurality of different source languages; and a code generator operable to generate code targeted for a plurality of execution architectures; wherein the code generator constructs one or more software development components of a plurality of different software development tools using the software development scenario-independent intermediate representation format, the one or more exception handling models operable to support the plurality of programming language specific exception handling models for the plurality of different source languages, and the type system operable to represent the plurality of different source languages; wherein the code generator further integrates the one or more software development components of the plurality of different software development tools into a software development scenario-independent framework; and wherein the code generator further creates the plurality of different software development tools by compiling the one or more software development components and the software development scenario-independent framework. | 1. One or more computer-readable media with computer-executable instructions for implementing a software development architecture comprising: a software development scenario-independent intermediate representation format; one or more exception handling models operable to support a plurality of programming language specific exception handling models for a plurality of different source languages; a type system operable to represent the type representations of the plurality of different source languages; and a code generator operable to generate code targeted for a plurality of execution architectures; wherein the code generator constructs one or more software development components of a plurality of different software development tools using the software development scenario-independent intermediate representation format, the one or more exception handling models operable to support the plurality of programming language specific exception handling models for the plurality of different source languages, and the type system operable to represent the plurality of different source languages; wherein the code generator further integrates the one or more software development components of the plurality of different software development tools into a software development scenario-independent framework; and wherein the code generator further creates the plurality of different software development tools by compiling the one or more software development components and the software development scenario-independent framework. 5. The one or more computer-readable media of claim 1 wherein the software development architecture is operable to produce a software development tool by dynamically linking a binary version of the software development scenario-independent framework to a modification component. | 0.5 |
8,311,967 | 1 | 2 | 1. A computer-implemented system comprising: one or more computers; one or more data storage devices coupled to the one or more computers, storing: a predictive model repository of a plurality of trained predictive models, information that describes each of the trained predictive models, which information includes an indication for each trained predictive model of one or more input types of input data that are compatible with the trained predictive model and an output type of a predictive output that can be generated using the trained predictive model, and instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a request from a client-subscriber computing system for access to a trained predictive model from the predictive model repository, which trained predictive model can generate a predictive output in response to receiving input data having one or more input types, wherein the one or more input types can be determined from the request; determining from the information that describes each of the trained predictive models that one or more models included in the predictive model repository match the request from the client-subscriber computing system, wherein determining a match is based at least in part on a comparison of the one or more input types determined from the request to input types included in the information that describes the trained predictive models; and providing access to at least one of the one or more models to the client-subscriber computing system; wherein the one or more models that match the request are models that were trained using training data provided by a computing system other than the client-subscriber computing system. | 1. A computer-implemented system comprising: one or more computers; one or more data storage devices coupled to the one or more computers, storing: a predictive model repository of a plurality of trained predictive models, information that describes each of the trained predictive models, which information includes an indication for each trained predictive model of one or more input types of input data that are compatible with the trained predictive model and an output type of a predictive output that can be generated using the trained predictive model, and instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a request from a client-subscriber computing system for access to a trained predictive model from the predictive model repository, which trained predictive model can generate a predictive output in response to receiving input data having one or more input types, wherein the one or more input types can be determined from the request; determining from the information that describes each of the trained predictive models that one or more models included in the predictive model repository match the request from the client-subscriber computing system, wherein determining a match is based at least in part on a comparison of the one or more input types determined from the request to input types included in the information that describes the trained predictive models; and providing access to at least one of the one or more models to the client-subscriber computing system; wherein the one or more models that match the request are models that were trained using training data provided by a computing system other than the client-subscriber computing system. 2. The system of claim 1 , the operations further comprising: determining an output type for predictive output for the client-subscriber computing system, wherein: if the output type is included in the request, then determining the output type comprises receiving the output type in the request; and if the output type is not included in the request, then determining the output type comprises determining from the information that describes each of the trained predictive models that one or more models included in the predictive model repository are compatible with the one or more input types determined from the request to input types and that the one or more models can generate output of one or more output types, and selecting the output type from the one or more output types. | 0.5 |
9,720,984 | 9 | 12 | 9. A method, comprising: receiving, by a processor, a visualization request relating to information stored in an ontology; parsing, by the processor, the visualization request to generate a search query; submitting, by the processor, the search query to the ontology, wherein the ontology is dynamically created to store retrieved data that is collected from a data source; perform data mitigation to process the retrieved data to detect and resolve conflicts among classified tokens provided by data agent, wherein the data mitigation uses quality score, trust score, and rate of decay for the data source; receiving, by the processor, in response to the query, a result comprising a plurality of instances associated with the classified tokens and a plurality of relationships between the instances; and generating, by the processor, a visual representation of the result using visualization rules stored in a memory, the visualization rules comprising level of detail rules, reduction rules, and rewriting rules, wherein generating the visual representation of the result using the visualization rules comprises: identifying a relationship between a first instance and a second instance from the plurality of instances within the results; removing the relationship between the first instance and the second instance from the results; and removing the first instance from the results when the first instance has no relationships with any other instances from the plurality of instances. | 9. A method, comprising: receiving, by a processor, a visualization request relating to information stored in an ontology; parsing, by the processor, the visualization request to generate a search query; submitting, by the processor, the search query to the ontology, wherein the ontology is dynamically created to store retrieved data that is collected from a data source; perform data mitigation to process the retrieved data to detect and resolve conflicts among classified tokens provided by data agent, wherein the data mitigation uses quality score, trust score, and rate of decay for the data source; receiving, by the processor, in response to the query, a result comprising a plurality of instances associated with the classified tokens and a plurality of relationships between the instances; and generating, by the processor, a visual representation of the result using visualization rules stored in a memory, the visualization rules comprising level of detail rules, reduction rules, and rewriting rules, wherein generating the visual representation of the result using the visualization rules comprises: identifying a relationship between a first instance and a second instance from the plurality of instances within the results; removing the relationship between the first instance and the second instance from the results; and removing the first instance from the results when the first instance has no relationships with any other instances from the plurality of instances. 12. The method of claim 9 , wherein generating the visual representation of the result using the visualization rules comprises selecting a third instance and a fourth instance from the plurality of instances to be combined into a consolidated instance based on the visualization rules. | 0.5 |
8,667,051 | 1 | 3 | 1. A method for communication processing, the method comprising: storing, by a client device, information records comprising a table of one or more keywords and associated operative functions, the table having at least one keyword programmed by a user of the client device; determining, by the client device, whether audio or text data of a broadcast includes one or more broadcasted keywords; and performing, by the client device, a series of the associated operative functions based on said one or more broadcasted keywords in response to determining that the one or more broadcasted keywords match one or more of the keywords in the table, while concurrently presenting output corresponding to said audio or text data during said broadcast, wherein the series of said associated operative functions comprises at least four of: placing a call using the one or more broadcasted keywords; comparing a performance history associated with the one or more broadcasted keywords; storing contact information derived from the one or more broadcasted keywords; determining a domain name having the one or more broadcasted keywords at least partially therein and generating a hyperlink from the domain name; searching a database device for advertising associated with the one or more broadcasted keywords; and performing an Internet search with the one or more broadcasted keywords. | 1. A method for communication processing, the method comprising: storing, by a client device, information records comprising a table of one or more keywords and associated operative functions, the table having at least one keyword programmed by a user of the client device; determining, by the client device, whether audio or text data of a broadcast includes one or more broadcasted keywords; and performing, by the client device, a series of the associated operative functions based on said one or more broadcasted keywords in response to determining that the one or more broadcasted keywords match one or more of the keywords in the table, while concurrently presenting output corresponding to said audio or text data during said broadcast, wherein the series of said associated operative functions comprises at least four of: placing a call using the one or more broadcasted keywords; comparing a performance history associated with the one or more broadcasted keywords; storing contact information derived from the one or more broadcasted keywords; determining a domain name having the one or more broadcasted keywords at least partially therein and generating a hyperlink from the domain name; searching a database device for advertising associated with the one or more broadcasted keywords; and performing an Internet search with the one or more broadcasted keywords. 3. The method, as set forth in claim 1 , wherein performing the Internet search further comprises presenting results of said Internet search. | 0.845733 |
9,081,782 | 21 | 22 | 21. A computer program product for implementing within a computer system a method for dynamically generating a graphical memorabilia project, the computer program product comprising: a computer-readable, non-transitory, medium for providing computer program code means utilized to implement the method, wherein the computer program code means is comprised of executable code for implementing a process comprising: receiving user input relating to a selection of: multiple dynamic page layout templates comprising a first dynamic page layout template and a second dynamic page layout template that each comprise a first well of a first well type and multiple wells of a second well type, wherein a location of the first well of the first well type and locations of the wells of the second well type are fixed with respect to their corresponding template, wherein the first well type will accept an image while preventing one or more background design elements from being disposed therein, wherein each of the one or more background design elements comprises a virtual design that is configured to resemble a decorative element placed in a physical memorabilia project, wherein each of the wells of the second well type will each accept an individual background design element while preventing the image from being disposed therein, wherein the wells of the second well type are divided into well classes, and wherein wells of the second well type that are of the same well class are governed by similar pre-determined rules, such that a change to one of the wells that is of the second well type and of a first well class will cause a similar change to another well of the second well type and of the first well class; a first image to be placed in the first well; and multiple pieces of the one or more background design elements to be placed in the wells of the second well type. | 21. A computer program product for implementing within a computer system a method for dynamically generating a graphical memorabilia project, the computer program product comprising: a computer-readable, non-transitory, medium for providing computer program code means utilized to implement the method, wherein the computer program code means is comprised of executable code for implementing a process comprising: receiving user input relating to a selection of: multiple dynamic page layout templates comprising a first dynamic page layout template and a second dynamic page layout template that each comprise a first well of a first well type and multiple wells of a second well type, wherein a location of the first well of the first well type and locations of the wells of the second well type are fixed with respect to their corresponding template, wherein the first well type will accept an image while preventing one or more background design elements from being disposed therein, wherein each of the one or more background design elements comprises a virtual design that is configured to resemble a decorative element placed in a physical memorabilia project, wherein each of the wells of the second well type will each accept an individual background design element while preventing the image from being disposed therein, wherein the wells of the second well type are divided into well classes, and wherein wells of the second well type that are of the same well class are governed by similar pre-determined rules, such that a change to one of the wells that is of the second well type and of a first well class will cause a similar change to another well of the second well type and of the first well class; a first image to be placed in the first well; and multiple pieces of the one or more background design elements to be placed in the wells of the second well type. 22. The computer program product of claim 21 , wherein computer program code means is further comprised of executable code for automatically receiving and retaining the image in a first orientation when the template is rotated about its center by 90 degrees and 180 degrees. | 0.615169 |
7,809,564 | 13 | 15 | 13. A computer program product for matching voice based keywords to keyword indexed search items, the computer program product comprising: a non-transitory computer readable medium storing computer usable program code tangibly embodied thereon, the computer usable program code comprising: computer usable program code for identifying, in response to receiving a spoken search request from a caller, keywords within the spoken search request; computer usable program code for creating a list of candidates comprising a match to at least one of the keywords, wherein each candidate in the list is assigned a level of confidence in the match; computer usable program code for locating keyword indexed search items having at least one of the keywords as an index and an original matching score; computer usable program code for weighting the original matching score of each keyword indexed search item with the level of confidence in the list of candidates to form weighted matching scores; computer usable program code for sorting the keyword indexed search items based on the weighted matching scores; and computer usable program code for creating a list of the sorted keyword indexed search items. | 13. A computer program product for matching voice based keywords to keyword indexed search items, the computer program product comprising: a non-transitory computer readable medium storing computer usable program code tangibly embodied thereon, the computer usable program code comprising: computer usable program code for identifying, in response to receiving a spoken search request from a caller, keywords within the spoken search request; computer usable program code for creating a list of candidates comprising a match to at least one of the keywords, wherein each candidate in the list is assigned a level of confidence in the match; computer usable program code for locating keyword indexed search items having at least one of the keywords as an index and an original matching score; computer usable program code for weighting the original matching score of each keyword indexed search item with the level of confidence in the list of candidates to form weighted matching scores; computer usable program code for sorting the keyword indexed search items based on the weighted matching scores; and computer usable program code for creating a list of the sorted keyword indexed search items. 15. The computer program product of claim 13 , further comprising: computer usable program code for determining, in response to creating the list of candidates, that at least one candidate in the list of candidates comprises a plurality of keywords; and computer usable program code for assigning an individual level of confidence to each of the plurality of keywords. | 0.5 |
8,131,552 | 3 | 4 | 3. The method of claim 2 , further comprising: segmenting the audio components, the visual components, and the text components of the multimedia data stream based on semantic differences, wherein frame level features are extracted from the audio component in a plurality of subbands. | 3. The method of claim 2 , further comprising: segmenting the audio components, the visual components, and the text components of the multimedia data stream based on semantic differences, wherein frame level features are extracted from the audio component in a plurality of subbands. 4. The method of claim 3 , further comprising: identifying at least one target speaker using the audio components and the visual components. | 0.5 |
8,539,463 | 17 | 31 | 17. A method for processing source code comprising: receiving source code; parsing the source code to obtain a high level intermediate representation of the source code; detecting, in the high level intermediate representation of the source code, high level constructs in the high level intermediate representation of the source code that satisfy constraints for parallel-merging high level constructs; and parallel-merging the high level constructs to generate new high level parallel-merged constructs in a modified high level intermediate representation of the source code that enable runtime operations of the high level constructs to execute in parallel using executable code generated from the modified high level intermediate representation; and executing, if the parallel execution of the runtime operations causes an error, executable code generated from unmodified representations of the high level constructs so the runtime operations of the high level constructs execute sequentially during runtime. | 17. A method for processing source code comprising: receiving source code; parsing the source code to obtain a high level intermediate representation of the source code; detecting, in the high level intermediate representation of the source code, high level constructs in the high level intermediate representation of the source code that satisfy constraints for parallel-merging high level constructs; and parallel-merging the high level constructs to generate new high level parallel-merged constructs in a modified high level intermediate representation of the source code that enable runtime operations of the high level constructs to execute in parallel using executable code generated from the modified high level intermediate representation; and executing, if the parallel execution of the runtime operations causes an error, executable code generated from unmodified representations of the high level constructs so the runtime operations of the high level constructs execute sequentially during runtime. 31. The method of claim 17 , including lowering the parallel-merged high level constructs from the high level intermediate representation to direct assembly code using new templates. | 0.78487 |
8,442,812 | 4 | 5 | 4. The method as in claim 1 , wherein the text data represents one or more Web pages. | 4. The method as in claim 1 , wherein the text data represents one or more Web pages. 5. The method as in claim 4 , wherein the step of formulating an expression further comprises the step of automatically parsing code representing the one or more Web pages to identify the one or more parts. | 0.5 |
8,615,664 | 1 | 28 | 1. A system, comprising: an inference data acquisition module configured to acquire inference data that indicate an inferred mental state of an authoring user in connection with a particular item of an electronic message, the inference data derived based, at least in part, on at least one physical characteristic of the authoring user; one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message; a source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors; an inference data association module configured to associate the inference data with the particular item, the inference data association module including at least an inference data inclusion module configured to include the inference data into the electronic message; and a source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module; and wherein the electronic message thereby includes at least a data pair that includes at least the inference data that indicate the inferred mental state of the authoring user in connection with the particular item and the one or more identities of the one or more sensors used to derive, at least in part, the inference data. | 1. A system, comprising: an inference data acquisition module configured to acquire inference data that indicate an inferred mental state of an authoring user in connection with a particular item of an electronic message, the inference data derived based, at least in part, on at least one physical characteristic of the authoring user; one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message; a source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors; an inference data association module configured to associate the inference data with the particular item, the inference data association module including at least an inference data inclusion module configured to include the inference data into the electronic message; and a source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module; and wherein the electronic message thereby includes at least a data pair that includes at least the inference data that indicate the inferred mental state of the authoring user in connection with the particular item and the one or more identities of the one or more sensors used to derive, at least in part, the inference data. 28. The system of claim 1 , wherein said inference data inclusion module configured to include the inference data into the electronic message comprises: an inference data inclusion module configured to include into the electronic message a time stamp associated with the inference data, the time stamp corresponding to a time stamp associated with an action performed by the authoring user in connection with the particular item. | 0.779774 |
9,798,720 | 8 | 10 | 8. The method according to claim 7 , wherein the hybrid machine translation engine further receives weighted inputs from statistical and rule based translation models and performs the translating based on the weighted inputs. | 8. The method according to claim 7 , wherein the hybrid machine translation engine further receives weighted inputs from statistical and rule based translation models and performs the translating based on the weighted inputs. 10. The method according to claim 8 , wherein the rule based models include a rule based syntactic model, a rule based semantic model, a rule based grammatical model and a rule based transfer system model. | 0.5 |
9,122,727 | 14 | 15 | 14. The method of claim 1 , wherein: the queries in the plurality of queries are past queries submitted by prior users; and selecting one or more of the candidate queries is further based on a frequency that the respective candidate queries were submitted by the prior users. | 14. The method of claim 1 , wherein: the queries in the plurality of queries are past queries submitted by prior users; and selecting one or more of the candidate queries is further based on a frequency that the respective candidate queries were submitted by the prior users. 15. The method of claim 14 , wherein: selecting one or more of the candidate queries is further based on elapsed times since the respective candidate queries were submitted by the prior users. | 0.5 |
8,452,795 | 6 | 7 | 6. The system of claim 1 , wherein the instructions further cause the one or more computers to perform operations comprising generating only query specializations that are included on a query whitelist. | 6. The system of claim 1 , wherein the instructions further cause the one or more computers to perform operations comprising generating only query specializations that are included on a query whitelist. 7. The system of claim 6 wherein the query whitelist is a list of the plurality of candidate text queries. | 0.5 |
5,553,084 | 8 | 15 | 8. An apparatus for decoding a machine-readable symbol representing encoded information, the symbol having symbol characters, a series of repeating characters, and error correction characters derived from the symbol and repeating characters, the apparatus comprising: a sensor that receives light reflected by the symbol and produces an output signal therefore; a receiver that receives the output signal and produces a data signal indicative of at least some of the symbol characters, repeating characters and error correction characters, but which fails to accurately indicate at least some of the symbol and repeating characters; and a processor for processing the data signal and producing a signal indicative of the information encoded in the symbol, the processor being programmed to (i) attempt to decode the symbol, (ii) determine if the symbol has any repeating characters if the symbol cannot be decoded, (iii) locate at least two repeating characters in the symbol, (iv) replace the repeating characters that failed to be accurately indicated in the data signal with accurately indicated repeating characters, and (v) attempt to decode the symbol again alter replacing the repeating character with accurately indicated repeating characters that failed to be indicated in the data signal. | 8. An apparatus for decoding a machine-readable symbol representing encoded information, the symbol having symbol characters, a series of repeating characters, and error correction characters derived from the symbol and repeating characters, the apparatus comprising: a sensor that receives light reflected by the symbol and produces an output signal therefore; a receiver that receives the output signal and produces a data signal indicative of at least some of the symbol characters, repeating characters and error correction characters, but which fails to accurately indicate at least some of the symbol and repeating characters; and a processor for processing the data signal and producing a signal indicative of the information encoded in the symbol, the processor being programmed to (i) attempt to decode the symbol, (ii) determine if the symbol has any repeating characters if the symbol cannot be decoded, (iii) locate at least two repeating characters in the symbol, (iv) replace the repeating characters that failed to be accurately indicated in the data signal with accurately indicated repeating characters, and (v) attempt to decode the symbol again alter replacing the repeating character with accurately indicated repeating characters that failed to be indicated in the data signal. 15. The apparatus of claim 8 wherein the processor locates at least two repeating characters in the symbol that are most proximate to one of the symbol or error correction characters. | 0.862199 |
8,564,541 | 21 | 23 | 21. The method of claim 14 , wherein the primary and the secondary key planes each includes a shift key that is operable to trigger key plane switching in the virtual keyboard between the primary and the secondary key planes when invoked by user input. | 21. The method of claim 14 , wherein the primary and the secondary key planes each includes a shift key that is operable to trigger key plane switching in the virtual keyboard between the primary and the secondary key planes when invoked by user input. 23. The method of claim 21 , further comprising: while presenting the secondary key plane of the virtual keyboard, receiving a second user input invoking the shift key on the secondary key plane; and upon receiving the second user input, presenting the primary key plane of the virtual keyboard in place of the secondary key plane. | 0.5 |
7,574,652 | 1 | 14 | 1. A computer implemented method of interactively determining transformations for use in mapping at least one source data component from at least one source to target data component, said method comprising the steps of: (a) using a computer to detect selection of at least one said source data component; (b) for each said selected source data component, generating a corresponding list of representative data examples; (c) using a computer to compile a resulting list of representative data examples for said target data component from said lists of representative data examples of said selected source data components, said resulting list of representative data examples being a limited subset of the source data components and representative of said target data component; (d) using a computer to display said resulting list of examples in a graphical user interface; (e) using a computer to identify a user generated modification of a single textual entity example from said resulting list of examples, wherein said user generated modification is made by a user selecting the single textual entity example from said resulting list of examples displayed in the graphical user interface and then directly modifying the single textual entity example; and (f) using a computer to determine at least one transformation to be applied to the at least one source data component including its corresponding representative data examples displayed in the graphical user interface, said at least one transformation being selected from a list of solutions, each solution of the list of solutions being based on the modified example and comprising at least one function, wherein said at least one transformation is selected from the list of solutions according to one of: a length of connectors between said functions; and a weight assigned to said functions. | 1. A computer implemented method of interactively determining transformations for use in mapping at least one source data component from at least one source to target data component, said method comprising the steps of: (a) using a computer to detect selection of at least one said source data component; (b) for each said selected source data component, generating a corresponding list of representative data examples; (c) using a computer to compile a resulting list of representative data examples for said target data component from said lists of representative data examples of said selected source data components, said resulting list of representative data examples being a limited subset of the source data components and representative of said target data component; (d) using a computer to display said resulting list of examples in a graphical user interface; (e) using a computer to identify a user generated modification of a single textual entity example from said resulting list of examples, wherein said user generated modification is made by a user selecting the single textual entity example from said resulting list of examples displayed in the graphical user interface and then directly modifying the single textual entity example; and (f) using a computer to determine at least one transformation to be applied to the at least one source data component including its corresponding representative data examples displayed in the graphical user interface, said at least one transformation being selected from a list of solutions, each solution of the list of solutions being based on the modified example and comprising at least one function, wherein said at least one transformation is selected from the list of solutions according to one of: a length of connectors between said functions; and a weight assigned to said functions. 14. A method according to claim 1 , wherein said transformation is an n-ary operation involving at least two data operands, and solutions in which a sequence of binary transforms are performed with the first operand of each step in the transform sequence being the result of the previous step are considered. | 0.908115 |
9,875,258 | 5 | 8 | 5. A computer-implemented method, comprising: analyzing an image including a representation of an object using a first classifier to determine a product category associated with the object; analyzing the image using a second classifier algorithm to determine a term representing a visual characteristic of the image; analyzing the image using the second classifier algorithm with the term to determine a sequence of words describing visual characteristics associated with the object; determining that the sequence of words satisfies a search condition; generating, in response to the sequence of words satisfying the search condition, a search string query that includes a subset of the sequence of words and search string refinement terms associated with the product category and the sequence of words; determining a set of search results based at least in part on the search string query that includes an item from a catalog of items; and displaying the set of search results and the search string refinement terms on a computing device, the search string refinement terms being selectable, the search string query being configured to be editable in response to a selection of one of the search string refinement terms. | 5. A computer-implemented method, comprising: analyzing an image including a representation of an object using a first classifier to determine a product category associated with the object; analyzing the image using a second classifier algorithm to determine a term representing a visual characteristic of the image; analyzing the image using the second classifier algorithm with the term to determine a sequence of words describing visual characteristics associated with the object; determining that the sequence of words satisfies a search condition; generating, in response to the sequence of words satisfying the search condition, a search string query that includes a subset of the sequence of words and search string refinement terms associated with the product category and the sequence of words; determining a set of search results based at least in part on the search string query that includes an item from a catalog of items; and displaying the set of search results and the search string refinement terms on a computing device, the search string refinement terms being selectable, the search string query being configured to be editable in response to a selection of one of the search string refinement terms. 8. The computer-implemented method of claim 5 , wherein the set of search results is a first set of search results, and wherein the method further comprises: generating a second search string query, an additional set of search string refinement terms based on the visual characteristics of the object; determining a second set of search results corresponding to the second search string query; and displaying the second set of search results and the additional set of search string refinement terms to the computing device. | 0.5 |
9,684,699 | 2 | 3 | 2. The non-transitory computer-readable medium of claim 1 , wherein the computer-readable instructions further cause the computing device to store the accessed data in an output database. | 2. The non-transitory computer-readable medium of claim 1 , wherein the computer-readable instructions further cause the computing device to store the accessed data in an output database. 3. The non-transitory computer-readable medium of claim 2 , wherein the input database is structured using a first type of database management/architecture system (DBMS) and the output database is structured using a second type of DBMS. | 0.5 |
9,245,088 | 11 | 14 | 11. A non-transitory computer readable medium storing instructions that, when executed by a processor, perform a method for increasing the reliability of a circuit design by managing safe operating area assertion violations, the processor-implemented method comprising: transforming simulator output into descriptive data, regarding safe operating area assertion violations, wherein the descriptive data is compatible with a database; executing queries with the database on the descriptive data regarding the safe operating area assertion violations according to user input; and generating tangible query results regarding the safe operating area assertion violations for the circuit design to work for its intended purpose. | 11. A non-transitory computer readable medium storing instructions that, when executed by a processor, perform a method for increasing the reliability of a circuit design by managing safe operating area assertion violations, the processor-implemented method comprising: transforming simulator output into descriptive data, regarding safe operating area assertion violations, wherein the descriptive data is compatible with a database; executing queries with the database on the descriptive data regarding the safe operating area assertion violations according to user input; and generating tangible query results regarding the safe operating area assertion violations for the circuit design to work for its intended purpose. 14. The medium of claim 11 wherein a simulator program performs the transforming and produces the descriptive data. | 0.719512 |
9,516,004 | 1 | 2 | 1. A system, comprising: a non-transitory memory storing a list of common credentials; a network interface component, configured to receive a credential associated with a user authentication attempt; and one or more hardware processors configured to execute instructions to cause the system to perform operations comprising: determining if the received credential is correct; comparing the received credential to the list of common credentials when the received credential is not correct; and when the received credential matches a common credential on the list of common credentials: increasing a score by a weighted factor based on the received credential matching the common credential, wherein increasing the score indicates an increased likelihood that an attacker is entering common credentials in a horizontal attack in order to gain access to a user account; storing a time associated with the score increase; and making a security determination based on the score; wherein the weighted factor is lower when a time since a previous score increase is greater than a threshold time than when the time since the previous score increase is less than or equal to the threshold time. | 1. A system, comprising: a non-transitory memory storing a list of common credentials; a network interface component, configured to receive a credential associated with a user authentication attempt; and one or more hardware processors configured to execute instructions to cause the system to perform operations comprising: determining if the received credential is correct; comparing the received credential to the list of common credentials when the received credential is not correct; and when the received credential matches a common credential on the list of common credentials: increasing a score by a weighted factor based on the received credential matching the common credential, wherein increasing the score indicates an increased likelihood that an attacker is entering common credentials in a horizontal attack in order to gain access to a user account; storing a time associated with the score increase; and making a security determination based on the score; wherein the weighted factor is lower when a time since a previous score increase is greater than a threshold time than when the time since the previous score increase is less than or equal to the threshold time. 2. The system of claim 1 , wherein the network interface component is further configured to receive the list of common credentials. | 0.636111 |
8,935,152 | 1 | 2 | 1. A method for analyzing a search of a source of computer-accessible content, comprising the following steps: accepting, performed at least in part with a configuration of computing hardware and programmable memory, a first search result comprised of a first set of records and a first set of frame instances, wherein each member of the first set of records has a corresponding instance in the first set of frame instances, selecting, performed at least in part with a configuration of computing hardware and programmable memory, role values, from the first set of frame instances, to produce a first set of candidate representative role values, wherein the selecting is performed as part of a determination, from the first set of frame instances, of a first set of representative role values; merging, performed at least in part with a configuration of computing hardware and programmable memory, a first candidate representative role value and a second candidate representative role value, of the first set of candidate representative role values, when it is determined that a first and a second meaning of, respectively, the first and second candidate representative role values, are sufficiently similar, wherein the merging is performed as part of a determination, from the first set of frame instances, of a first set of representative role values; and making accessible, performed at least in part with a configuration of computing hardware and programmable memory, to a user, at least a portion of the first set of representative role values. | 1. A method for analyzing a search of a source of computer-accessible content, comprising the following steps: accepting, performed at least in part with a configuration of computing hardware and programmable memory, a first search result comprised of a first set of records and a first set of frame instances, wherein each member of the first set of records has a corresponding instance in the first set of frame instances, selecting, performed at least in part with a configuration of computing hardware and programmable memory, role values, from the first set of frame instances, to produce a first set of candidate representative role values, wherein the selecting is performed as part of a determination, from the first set of frame instances, of a first set of representative role values; merging, performed at least in part with a configuration of computing hardware and programmable memory, a first candidate representative role value and a second candidate representative role value, of the first set of candidate representative role values, when it is determined that a first and a second meaning of, respectively, the first and second candidate representative role values, are sufficiently similar, wherein the merging is performed as part of a determination, from the first set of frame instances, of a first set of representative role values; and making accessible, performed at least in part with a configuration of computing hardware and programmable memory, to a user, at least a portion of the first set of representative role values. 2. The method of claim 1 , wherein the step of merging further comprises: including, performed at least in part with a configuration of computing hardware and programmable memory, a single value, in the first set of representative role values, to represent the first and second candidate representative role values. | 0.688119 |
9,558,183 | 3 | 4 | 3. The system of claim 1 wherein the system further includes: a data derivation component including a program for deriving training data and testing data from the annotated utterances. | 3. The system of claim 1 wherein the system further includes: a data derivation component including a program for deriving training data and testing data from the annotated utterances. 4. The system of claim 3 wherein the deriving component further includes program instructions for further separating the training data into training data and development data. | 0.5 |
8,498,974 | 11 | 14 | 11. A system comprising: one or more processors programmed operable to perform operations comprising: obtaining a plurality of search results responsive to a search query submitted by a user, wherein each search result refers to a respective document that is associated with a respective plurality of click measures, each click measure relating to a different respective natural language and representing, at least, a measure of behavior of users associated with the respective language in regards to the document when the document was referred to in a search result previously provided in response to the search query; for each of a first plurality of the search results, reducing the click measure associated with the document referred to by the search result, wherein the click measure relates to a respective natural language that is incompatible with a natural language of the user; calculating a respective scoring factor for each of the first plurality of search results based on the respective click measures associated with the document referred to by the first search result; and ranking the search results based upon, at least, the calculated scoring factors. | 11. A system comprising: one or more processors programmed operable to perform operations comprising: obtaining a plurality of search results responsive to a search query submitted by a user, wherein each search result refers to a respective document that is associated with a respective plurality of click measures, each click measure relating to a different respective natural language and representing, at least, a measure of behavior of users associated with the respective language in regards to the document when the document was referred to in a search result previously provided in response to the search query; for each of a first plurality of the search results, reducing the click measure associated with the document referred to by the search result, wherein the click measure relates to a respective natural language that is incompatible with a natural language of the user; calculating a respective scoring factor for each of the first plurality of search results based on the respective click measures associated with the document referred to by the first search result; and ranking the search results based upon, at least, the calculated scoring factors. 14. The system of claim 11 wherein a plurality of the users are located in a different country than the user. | 0.793561 |
8,996,437 | 16 | 17 | 16. The computer program product of claim 15 , wherein the third program instructions to update the value metric scores of experts are further to: increase the value metric score of a first expert as a function of an elapsed time of a response of the first expert to a sent survey question that is less than a normal response time; and decrease the value metric score of a second expert in response to a failure to receive a response to a sent survey question from the second expert within an allowable time for response to the sent survey question. | 16. The computer program product of claim 15 , wherein the third program instructions to update the value metric scores of experts are further to: increase the value metric score of a first expert as a function of an elapsed time of a response of the first expert to a sent survey question that is less than a normal response time; and decrease the value metric score of a second expert in response to a failure to receive a response to a sent survey question from the second expert within an allowable time for response to the sent survey question. 17. The computer program product of claim 16 , wherein the third program instructions to update the value metric scores of experts are further to: send a reminder to the second expert in response to the failure to receive the response to the sent survey question from the second expert within the threshold allowable time for response; and remove the second expert from the updated set of experts in response to a failure to receive a response to the reminder within an allowable time for response to the reminder. | 0.557659 |
8,244,694 | 7 | 11 | 7. A computer-readable storage medium containing a program which, when executed, performs an operation for providing dynamic schema assembly to accommodate application specific metadata in data objects managed by a content management system (CMS), the operation comprising: receiving a request to access a document from the CMS, wherein the document is associated with a base storage schema, wherein content of the document is composed according to a the base storage schema, and wherein the base storage schema specifies a valid set of markup language tags and markup language attributes for use in the document; modifying an instance of the document by embedding the application specific metadata in the document, wherein the application specific metadata includes at least one of a markup language tag and a markup language attribute that is not valid according to the base storage schema; modifying the base storage schema associated with the document to accommodate the application specific metadata by adding the at least one markup language tag and markup language attribute from the application specific metadata to the base storage schema, thereby creating a transient schema, wherein the modified instance of the document is valid according to the transient schema; providing the modified instance of the document and the transient schema separately to a requesting application in response to the request; receiving the modified instance of the document back from the requesting application; stripping the application specific metadata from the modified instance of the document, wherein the modified, stripped instance of the document received back from the requesting application is valid according to the base storage schema; and storing the modified, stripped instance of the instance of the document in the CMS. | 7. A computer-readable storage medium containing a program which, when executed, performs an operation for providing dynamic schema assembly to accommodate application specific metadata in data objects managed by a content management system (CMS), the operation comprising: receiving a request to access a document from the CMS, wherein the document is associated with a base storage schema, wherein content of the document is composed according to a the base storage schema, and wherein the base storage schema specifies a valid set of markup language tags and markup language attributes for use in the document; modifying an instance of the document by embedding the application specific metadata in the document, wherein the application specific metadata includes at least one of a markup language tag and a markup language attribute that is not valid according to the base storage schema; modifying the base storage schema associated with the document to accommodate the application specific metadata by adding the at least one markup language tag and markup language attribute from the application specific metadata to the base storage schema, thereby creating a transient schema, wherein the modified instance of the document is valid according to the transient schema; providing the modified instance of the document and the transient schema separately to a requesting application in response to the request; receiving the modified instance of the document back from the requesting application; stripping the application specific metadata from the modified instance of the document, wherein the modified, stripped instance of the document received back from the requesting application is valid according to the base storage schema; and storing the modified, stripped instance of the instance of the document in the CMS. 11. The computer-readable storage medium of claim 7 , wherein the document is an XML document, and wherein the base storage schema is an XML schema. | 0.79558 |
8,719,006 | 1 | 2 | 1. A computer-implemented method for text-to-speech (TTS) synthesis, comprising: in response to a word of a text sequence, generating a first part-of-speech POS tag using a statistical POS tagger based on a corpus of trained text sequences, each representing a likely POS of a word for a given text sequence, wherein the first POS tag is selected from a first POS tag set; generating a second POS tag using a rule-based POS tagger based on a set of one or more rules associated with a type of an application associated with the text sequence, wherein the second POS tag is selected from a second POS tag set that is different from the first POS tag set; calculating a first confidence score for the second POS tag based on a statistic data of applying a rule associated with the second POS tag, wherein the first confidence score is calculated based on a percentage of successful applications of the rule in previous TTS synthesis; designating the second POS tag as the final POS tag if the first confidence score is greater than or equal to a first predetermined threshold; designating the first POS tag as the final POS tag if the first confidence score is less than the first predetermined threshold; assigning a final POS tag to the word of the text sequence for TTS synthesis based on the first POS tag and the second POS tag; adjusting the first confidence score for the rule for future TTS synthesis based on whether the second POS tag has been selected as the final POS tag; and removing the rule from the set of one or more rules if the first confidence score is below a second predetermined threshold. | 1. A computer-implemented method for text-to-speech (TTS) synthesis, comprising: in response to a word of a text sequence, generating a first part-of-speech POS tag using a statistical POS tagger based on a corpus of trained text sequences, each representing a likely POS of a word for a given text sequence, wherein the first POS tag is selected from a first POS tag set; generating a second POS tag using a rule-based POS tagger based on a set of one or more rules associated with a type of an application associated with the text sequence, wherein the second POS tag is selected from a second POS tag set that is different from the first POS tag set; calculating a first confidence score for the second POS tag based on a statistic data of applying a rule associated with the second POS tag, wherein the first confidence score is calculated based on a percentage of successful applications of the rule in previous TTS synthesis; designating the second POS tag as the final POS tag if the first confidence score is greater than or equal to a first predetermined threshold; designating the first POS tag as the final POS tag if the first confidence score is less than the first predetermined threshold; assigning a final POS tag to the word of the text sequence for TTS synthesis based on the first POS tag and the second POS tag; adjusting the first confidence score for the rule for future TTS synthesis based on whether the second POS tag has been selected as the final POS tag; and removing the rule from the set of one or more rules if the first confidence score is below a second predetermined threshold. 2. The method of claim 1 , wherein assigning a final POS tag comprises assigning either the first POS tag or the second POS tag as the final POS tag if the first POS tag and the second POS tag are identical. | 0.779318 |
4,829,572 | 26 | 27 | 26. The method of claim 25 and additionally comprising the steps of generating a difference profile for substantially each pair of phonemes by subtracting each profile of one phoneme from the equivalent profile of each pair phoneme, identifying adjacent sections of each difference profile which exceed positive and negative thresholds respectively, and computing the likelihood that an unknown phoneme will be one or the other of a phoneme pair based on the relative areas in the identified sections of the difference profiles. | 26. The method of claim 25 and additionally comprising the steps of generating a difference profile for substantially each pair of phonemes by subtracting each profile of one phoneme from the equivalent profile of each pair phoneme, identifying adjacent sections of each difference profile which exceed positive and negative thresholds respectively, and computing the likelihood that an unknown phoneme will be one or the other of a phoneme pair based on the relative areas in the identified sections of the difference profiles. 27. The method of claim 26 and additionally comprising the steps of constructing equivalent profiles of a phoneme of an unknown utterance, and choosing the more likely phoneme of each phoneme pair based on the relative areas in the identified sections of the profiles of the unknown phoneme. | 0.5 |
9,517,418 | 11 | 18 | 11. A non-transitory computer program product comprising a computer usable storage medium storing computer usable program code for conversation management in a virtual world data processing system, the computer program product comprising: computer usable program code for recording a sequence of statements from different avatars in a virtual world; computer usable program code for locating a position of each of the avatars in the virtual world; computer usable program code for computing a temporal proximity of each of the recorded statements to others of the recorded statements; computer usable program code for grouping selected ones of the recorded statements in the virtual world if corresponding ones of the avatars are geographically proximate to one another in the virtual world and if the selected ones of the statements have occurred within a threshold temporal proximity of one another; and, persisting the grouped statements in the virtual world as a conversation. | 11. A non-transitory computer program product comprising a computer usable storage medium storing computer usable program code for conversation management in a virtual world data processing system, the computer program product comprising: computer usable program code for recording a sequence of statements from different avatars in a virtual world; computer usable program code for locating a position of each of the avatars in the virtual world; computer usable program code for computing a temporal proximity of each of the recorded statements to others of the recorded statements; computer usable program code for grouping selected ones of the recorded statements in the virtual world if corresponding ones of the avatars are geographically proximate to one another in the virtual world and if the selected ones of the statements have occurred within a threshold temporal proximity of one another; and, persisting the grouped statements in the virtual world as a conversation. 18. The computer program product of claim 11 , wherein the computer usable program code for grouping the statements in the virtual world if the avatars are geographically proximate to one another in the virtual world and if the statements have occurred within a threshold temporal proximity of one another, comprises, computer usable program code for grouping the statements in the virtual world if the avatars are geographically proximate to one another in the virtual world and if the statements have occurred within a threshold temporal proximity of one another and neither of the avatars is in a private chat with a different avatar. | 0.521772 |
9,177,550 | 6 | 7 | 6. The computing device of claim 1 , the recognition system being a speech recognition system, the captured observation being a spoken utterance, and the context-dependent units being senones. | 6. The computing device of claim 1 , the recognition system being a speech recognition system, the captured observation being a spoken utterance, and the context-dependent units being senones. 7. The computing device of claim 6 , wherein the adapted DNN is provided with the features corresponding to the spoken utterance immediately subsequent to the adaptor component adapting the at least one parameter of the DNN, the speech recognition system further comprises a decoder component that decodes at least one word in the spoken utterance utilizing the adapted DNN. | 0.5 |
8,364,670 | 1 | 10 | 1. A method for electronically searching for an item, the method comprising the steps of: providing a search index comprising a set of predefined categories, wherein each predefined category is defined by a taxonomy of attributes comprising a set of predefined attributes, wherein each predefined attribute is defined by at least one question and one or more answers to each question; receiving a search request for the item from a user, wherein the search request comprises a requested category for the item selected from the set of predefined item categories, and one or more requested attributes of the item selected from the set of predefined attributes by providing at least one of the answers to at least one of the questions defining the requested attribute of the item; storing the search request for the item in the search index based on the requested category for the item and the requested attribute(s) of the item; searching the search index for any previously stored search requests from other users that match the requested category and the requested attribute(s); determining a result of the search; sending a search response comprising the result of the search; persistently searching the search index for the item by monitoring the search index for a trigger event until the search request is terminated; whenever the trigger event is detected, searching the search index for any stored search results that match the requested category and the requested attributes, and determining a new result of the search; whenever the new result differs from the result, sending an updated search response comprising the new result of the search; determining a relevancy score for each found stored search request; wherein the step of determining the relevancy score for each found stored result comprises the step of summing the relevancy scores for each requested attribute in the search request divided by the number of requested attributes in the search request; and wherein the relevancy score for each requested attribute comprises a first value whenever the requested attribute is not specified in the stored search request, a second value whenever the requested attribute matches the attribute of the stored search request and the requested attribute is Must Have, a third value whenever the requested attribute that matches the attribute of the stored search request and the requested attribute is not Must Have, a fourth value whenever the requested attribute that does not match the attribute of the stored search request and the requested attribute is Must Have, and a fifth value whenever the requested attribute does not match the attribute of the stored search request and the requested attribute is not Must Have. | 1. A method for electronically searching for an item, the method comprising the steps of: providing a search index comprising a set of predefined categories, wherein each predefined category is defined by a taxonomy of attributes comprising a set of predefined attributes, wherein each predefined attribute is defined by at least one question and one or more answers to each question; receiving a search request for the item from a user, wherein the search request comprises a requested category for the item selected from the set of predefined item categories, and one or more requested attributes of the item selected from the set of predefined attributes by providing at least one of the answers to at least one of the questions defining the requested attribute of the item; storing the search request for the item in the search index based on the requested category for the item and the requested attribute(s) of the item; searching the search index for any previously stored search requests from other users that match the requested category and the requested attribute(s); determining a result of the search; sending a search response comprising the result of the search; persistently searching the search index for the item by monitoring the search index for a trigger event until the search request is terminated; whenever the trigger event is detected, searching the search index for any stored search results that match the requested category and the requested attributes, and determining a new result of the search; whenever the new result differs from the result, sending an updated search response comprising the new result of the search; determining a relevancy score for each found stored search request; wherein the step of determining the relevancy score for each found stored result comprises the step of summing the relevancy scores for each requested attribute in the search request divided by the number of requested attributes in the search request; and wherein the relevancy score for each requested attribute comprises a first value whenever the requested attribute is not specified in the stored search request, a second value whenever the requested attribute matches the attribute of the stored search request and the requested attribute is Must Have, a third value whenever the requested attribute that matches the attribute of the stored search request and the requested attribute is not Must Have, a fourth value whenever the requested attribute that does not match the attribute of the stored search request and the requested attribute is Must Have, and a fifth value whenever the requested attribute does not match the attribute of the stored search request and the requested attribute is not Must Have. 10. The method as recited in claim 1 , wherein one of: each stored search request relates to an item posted for advertisement, exchange, lease, sale, trade or transfer by the user that submitted the stored search request; each stored search request relates to an item sought by the user that submitted the stored search request for advertisement, exchange, lease, sale, trade or transfer; each stored search request comprises information posted about an item provided by the user that submitted the stored search request; and each stored search request comprises information about an item sought by the user that submitted the stored search request. | 0.739775 |
8,645,390 | 27 | 28 | 27. A system, comprising: one or more processors; memory; one or more programs stored in the memory to be executed by the one or more processors, the one or more programs comprising: instructions for determining a correlation, for each search context of a plurality of search contexts, for each scoring primitive of a plurality of scoring primitives, and for a set of previously executed search queries that are consistent with the search context, between the scoring primitive and actual user selections of results of the previously executed search queries by a plurality of users; instructions for performing machine learning on the correlations to identify a predicted performance function comprising a weighted subset of the scoring primitives that meet predefined predictive quality criteria; and instructions for receiving and executing a user submitted search query, submitted by a user, to produce a set of search results, including associating the user submitted search query with a respective search context of the plurality of search contexts, and ordering at least a portion of the search results in accordance with the identified predicted performance function and the search context associated with the user submitted search query. | 27. A system, comprising: one or more processors; memory; one or more programs stored in the memory to be executed by the one or more processors, the one or more programs comprising: instructions for determining a correlation, for each search context of a plurality of search contexts, for each scoring primitive of a plurality of scoring primitives, and for a set of previously executed search queries that are consistent with the search context, between the scoring primitive and actual user selections of results of the previously executed search queries by a plurality of users; instructions for performing machine learning on the correlations to identify a predicted performance function comprising a weighted subset of the scoring primitives that meet predefined predictive quality criteria; and instructions for receiving and executing a user submitted search query, submitted by a user, to produce a set of search results, including associating the user submitted search query with a respective search context of the plurality of search contexts, and ordering at least a portion of the search results in accordance with the identified predicted performance function and the search context associated with the user submitted search query. 28. The system of claim 27 , wherein each search context is associated with a respective group of users. | 0.911111 |
8,131,786 | 1 | 8 | 1. A system, comprising: one or more computers; and a computer-readable storage device storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: storing data identifying a plurality of training images for a query, wherein each of the training images is classified as being in a positive group of images for the query or a negative group of images for the query according to a respective query-specific preference measure for the image; selecting a first image from either the positive group of images or the negative group of images, and applying a scoring model to the first image to determine a score for the first image; selecting a plurality of candidate images from the other group of images; applying the scoring model to each of the candidate images to determine a respective score for each candidate image, and then selecting a second image from the candidate images, the second image having a highest score; and determining that the scores for the first image and the second image fail to satisfy a criterion, wherein the criterion requires that a result of the score of the image selected from the positive group of images minus the score of the image selected from the negative group of images exceeds a threshold that is greater than zero, updating the scoring model, and storing the updated scoring model. | 1. A system, comprising: one or more computers; and a computer-readable storage device storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: storing data identifying a plurality of training images for a query, wherein each of the training images is classified as being in a positive group of images for the query or a negative group of images for the query according to a respective query-specific preference measure for the image; selecting a first image from either the positive group of images or the negative group of images, and applying a scoring model to the first image to determine a score for the first image; selecting a plurality of candidate images from the other group of images; applying the scoring model to each of the candidate images to determine a respective score for each candidate image, and then selecting a second image from the candidate images, the second image having a highest score; and determining that the scores for the first image and the second image fail to satisfy a criterion, wherein the criterion requires that a result of the score of the image selected from the positive group of images minus the score of the image selected from the negative group of images exceeds a threshold that is greater than zero, updating the scoring model, and storing the updated scoring model. 8. The system of claim 1 , wherein selecting the first image comprises: selecting a plurality of first candidate images from either the positive group of images or the negative group of images; applying the scoring model to each of the first candidate images to determine a respective score for each first candidate image; and selecting as the first image an image having a highest score from among the first candidate images. | 0.546809 |
8,152,636 | 17 | 20 | 17. The party kit of claim 1 , further comprising marketing materials. | 17. The party kit of claim 1 , further comprising marketing materials. 20. The party kit of claim 17 , wherein the marketing materials include a computer readable medium storing computer executable code for causing a computer to display demonstrations of actions of the one or more animated characters in combination with the at least one character. | 0.5 |
8,515,940 | 1 | 7 | 1. A method, comprising: ranking categories of a keyword detected in a query; ranking a category based on human assisted searches performed for queries indicating the keyword; choosing a human search assistant based on the keyword; providing content identifying the query, the keyword and the category to the human search assistant when the category is ranked highest; and qualifying the query based on the category and an action received when the human search assistant is performing a search. | 1. A method, comprising: ranking categories of a keyword detected in a query; ranking a category based on human assisted searches performed for queries indicating the keyword; choosing a human search assistant based on the keyword; providing content identifying the query, the keyword and the category to the human search assistant when the category is ranked highest; and qualifying the query based on the category and an action received when the human search assistant is performing a search. 7. The method of claim 1 further comprising: presenting a search result obtained by submitting the query to a search resource ranked highest for the category and the keyword to the human search assistant. | 0.604651 |
8,495,701 | 7 | 12 | 7. A computer system for indexing security policies, the computer system comprising: a bus; a storage device connected to the bus, wherein the storage device stores computer-executable instructions; and a processor unit connected to the bus, wherein the processor unit executes the computer-executable instructions to direct the computer system to: determine a policy vocabulary to form a set of policy elements; create an index from the set of policy elements, wherein creating the index from the set of policy elements comprises: determining policy element combinations to form determined policy element combinations; assigning a rule number to each distinct policy element combination within the determined policy element combinations to create a set of rules, wherein each rule in the set of rules includes a target portion and a condition portion; removing inequality expressions located in subject entries of the target portion of the set of rules; placing the inequality expressions removed from the target portion into the condition portion of the set of rules; transforming each of the inequality expressions removed from the target portion and placed in the condition portion of the set of rules from a subject entry to an apply entry; responsive to determining that two or more rules having distinct policy element combinations in the set of rules are equivalent, assigning a same rule number to each of the two or more rules having the distinct policy element combinations determined to be equivalent; receive a request to form requested policy elements; locate requested policy elements in the index to form a set of returned policy elements; and identify a rule for the set of returned policy elements. | 7. A computer system for indexing security policies, the computer system comprising: a bus; a storage device connected to the bus, wherein the storage device stores computer-executable instructions; and a processor unit connected to the bus, wherein the processor unit executes the computer-executable instructions to direct the computer system to: determine a policy vocabulary to form a set of policy elements; create an index from the set of policy elements, wherein creating the index from the set of policy elements comprises: determining policy element combinations to form determined policy element combinations; assigning a rule number to each distinct policy element combination within the determined policy element combinations to create a set of rules, wherein each rule in the set of rules includes a target portion and a condition portion; removing inequality expressions located in subject entries of the target portion of the set of rules; placing the inequality expressions removed from the target portion into the condition portion of the set of rules; transforming each of the inequality expressions removed from the target portion and placed in the condition portion of the set of rules from a subject entry to an apply entry; responsive to determining that two or more rules having distinct policy element combinations in the set of rules are equivalent, assigning a same rule number to each of the two or more rules having the distinct policy element combinations determined to be equivalent; receive a request to form requested policy elements; locate requested policy elements in the index to form a set of returned policy elements; and identify a rule for the set of returned policy elements. 12. The computer system of claim 7 wherein executing the computer-executable instructions to identify the rule further directs the computer system to evaluate each rule, in turn, for the set of returned policy elements. | 0.600365 |
7,516,229 | 4 | 8 | 4. The method according to claim 1 , wherein the communication server is further arranged for: pre-specifying semantic constraints and associating them with deployment contexts; the deriving of the set of constraints for that entity comprising defining a particular deployment context for the common interactions protocol, and determining which of the pre-specified semantic constraints are applicable to said particular deployment context. | 4. The method according to claim 1 , wherein the communication server is further arranged for: pre-specifying semantic constraints and associating them with deployment contexts; the deriving of the set of constraints for that entity comprising defining a particular deployment context for the common interactions protocol, and determining which of the pre-specified semantic constraints are applicable to said particular deployment context. 8. The method according to claim 4 , wherein pre-specifying comprises specifying constraints applicable to whole classes of objects/processes. | 0.692641 |
9,971,581 | 13 | 14 | 13. The system of claim 8 , wherein the model includes recognizing standardized features in the first programming framework and converting into standardized features in the second programming framework. | 13. The system of claim 8 , wherein the model includes recognizing standardized features in the first programming framework and converting into standardized features in the second programming framework. 14. The system of claim 13 , wherein the standardized features include code semantics, modularity, layering, strong cohesion, loose coupling, or design time class relationships including association, aggregation, dependency, generalization, or realization. | 0.5 |
9,442,747 | 6 | 7 | 6. The method of claim 5 , further comprising: processing a qualified mnemonic in the computer program comprising the mnemonic and a qualification character; interpreting the qualified mnemonic according to the user defined definition for the mnemonic in response to previously processing a local qualifier command associating the qualification character with the user defined definition, wherein a use of the qualification character with the local qualifier command specifying the user defined definition overrides any mnemonic command specifying the mnemonic and the translator definition which precedes the local qualifier command specifying the user defined definition; and interpreting the qualified mnemonic according to the translator definition for the mnemonic in response to previously processing a local qualifier command associating the qualification character with the translator definition, wherein a use of the qualification character with the local qualifier command specifying the translator definition overrides any mnemonic command specifying the mnemonic and the user defined definition which precedes the local qualifier command specifying the translator definition. | 6. The method of claim 5 , further comprising: processing a qualified mnemonic in the computer program comprising the mnemonic and a qualification character; interpreting the qualified mnemonic according to the user defined definition for the mnemonic in response to previously processing a local qualifier command associating the qualification character with the user defined definition, wherein a use of the qualification character with the local qualifier command specifying the user defined definition overrides any mnemonic command specifying the mnemonic and the translator definition which precedes the local qualifier command specifying the user defined definition; and interpreting the qualified mnemonic according to the translator definition for the mnemonic in response to previously processing a local qualifier command associating the qualification character with the translator definition, wherein a use of the qualification character with the local qualifier command specifying the translator definition overrides any mnemonic command specifying the mnemonic and the user defined definition which precedes the local qualifier command specifying the translator definition. 7. The method of claim 6 , wherein the local qualifier command and the local mnemonic command are defined within a macro in the computer program. | 0.5 |
8,015,007 | 11 | 12 | 11. A speech recognition program stored in a non-transitory computer-readable medium and being executable in a computer, the computer comprising: a model storage unit having a plurality of phrases expressed on basis of grammar and one or more continuous phrase segments obtained by dividing the respective phrase segments, the model storage unit configured to store state transition models which express time series changes of the speech features for respective phrase segments as state-to-state transition relating to the speech features; a first grammar storage unit configured to store respective instructed grammar segments relating to one or more continuous phrase segments which belong to each of the phrases; and a second grammar storage unit configured to store at least part of the grammar segments transferred from the first grammar storage unit and to be able to read out information stored therein in a reading time shorter than that required for the first grammar storage unit; the program comprising: a generating instruction of generating sequences of speech features from characteristics of entered speech for respective frames having an arbitrary temporal width; a first decoding instruction of obtaining forward probabilities of respective states of the state transition models for the sequence of speech features generated by the generating instruction with respect to each of the frames, by referring to the grammar segments stored in the second grammar storage unit and the state transition models stored in the model storage unit; a grammar transferring instruction of transferring a trailing grammar segment relating to a trailing phrase segment which trails one of said continuous phrase segments, from the first grammar storage unit to the second grammar storage unit when the forward probability of final state among said states of the state transition models is obtained by the first decoding instruction; a second decoding instruction of obtaining the forward probabilities of the respective states of the state transition models for a sequence of trailing speech features as the sequence of speech features for the trailing segment as generated the generating instruction with respect to each of the frames, continuously after the speech feature sequences, by referring to the grammar segments stored in the second grammar storage unit and the state transition models stored in the model storage unit; a third decoding instruction of obtaining the forward probabilities of the respective states of the state transition models for the trailing speech feature sequences for the respective frames, by referring to the trailing grammar segment transferred to the second grammar storage unit and the state transition models stored in the model storage unit; a recognition controlling instruction of (1) carrying out recognition for the respective phrases, (2) activating the first decoding instruction until the transfer of the trailing grammar segment is started, (3) activating the second decoding instruction in parallel to the transfer from the start to the completion of the transfer, (4) activating the third decoding instruction upon completion of the transfer, and (5) repeating the operations from (2) to (4) until all the operations for the phrase segments belonging to the respective phrases to obtain final forward probabilities for the respective phrases; and a recognizing instruction of outputting the phrase which gives the highest forward probability from among the respective final forward probabilities of the plurality of phrases as a result of recognition of the speech feature sequence. | 11. A speech recognition program stored in a non-transitory computer-readable medium and being executable in a computer, the computer comprising: a model storage unit having a plurality of phrases expressed on basis of grammar and one or more continuous phrase segments obtained by dividing the respective phrase segments, the model storage unit configured to store state transition models which express time series changes of the speech features for respective phrase segments as state-to-state transition relating to the speech features; a first grammar storage unit configured to store respective instructed grammar segments relating to one or more continuous phrase segments which belong to each of the phrases; and a second grammar storage unit configured to store at least part of the grammar segments transferred from the first grammar storage unit and to be able to read out information stored therein in a reading time shorter than that required for the first grammar storage unit; the program comprising: a generating instruction of generating sequences of speech features from characteristics of entered speech for respective frames having an arbitrary temporal width; a first decoding instruction of obtaining forward probabilities of respective states of the state transition models for the sequence of speech features generated by the generating instruction with respect to each of the frames, by referring to the grammar segments stored in the second grammar storage unit and the state transition models stored in the model storage unit; a grammar transferring instruction of transferring a trailing grammar segment relating to a trailing phrase segment which trails one of said continuous phrase segments, from the first grammar storage unit to the second grammar storage unit when the forward probability of final state among said states of the state transition models is obtained by the first decoding instruction; a second decoding instruction of obtaining the forward probabilities of the respective states of the state transition models for a sequence of trailing speech features as the sequence of speech features for the trailing segment as generated the generating instruction with respect to each of the frames, continuously after the speech feature sequences, by referring to the grammar segments stored in the second grammar storage unit and the state transition models stored in the model storage unit; a third decoding instruction of obtaining the forward probabilities of the respective states of the state transition models for the trailing speech feature sequences for the respective frames, by referring to the trailing grammar segment transferred to the second grammar storage unit and the state transition models stored in the model storage unit; a recognition controlling instruction of (1) carrying out recognition for the respective phrases, (2) activating the first decoding instruction until the transfer of the trailing grammar segment is started, (3) activating the second decoding instruction in parallel to the transfer from the start to the completion of the transfer, (4) activating the third decoding instruction upon completion of the transfer, and (5) repeating the operations from (2) to (4) until all the operations for the phrase segments belonging to the respective phrases to obtain final forward probabilities for the respective phrases; and a recognizing instruction of outputting the phrase which gives the highest forward probability from among the respective final forward probabilities of the plurality of phrases as a result of recognition of the speech feature sequence. 12. The program according to claim 11 , wherein the first decoding instruction and the third decoding instruction are integrated with each other. | 0.926545 |
9,542,456 | 5 | 7 | 5. The method of claim 1 further comprising forming a plurality of regular expression rules, each rule being formed to correspond to a different predetermined set of non-standard features, and said processing comprising processing said distinct name using a selected regular expression rule tailored to the non-standard feature set of said distinct name. | 5. The method of claim 1 further comprising forming a plurality of regular expression rules, each rule being formed to correspond to a different predetermined set of non-standard features, and said processing comprising processing said distinct name using a selected regular expression rule tailored to the non-standard feature set of said distinct name. 7. The method of claim 5 , wherein said processing comprises removing from said distinct name all of the features in the feature set of said distinct name to convert the distinct name to said standard name format. | 0.522422 |
7,827,177 | 24 | 25 | 24. The computer-readable storage medium of claim 23 , wherein said statement includes an expression that references the parent document and represents an expansion said parent document. | 24. The computer-readable storage medium of claim 23 , wherein said statement includes an expression that references the parent document and represents an expansion said parent document. 25. The computer-readable storage medium of claim 24 , wherein said expression includes an operator based on said parent document. | 0.5 |
9,892,104 | 19 | 24 | 19. A method of annotating digital content comprising: causing displaying of a menu including all of a first option to create an annotation such that the annotation is not associated with a volume of digital content, a second option to create the annotation such that the annotation is associated with an entire of the volume of digital content, a third option to create the annotation such that the annotation is associated with a page of the volume of digital content, and a fourth option to create the annotation such that the annotation is associated with selected text contained within the volume of digital content, the menu including a privacy setting associated with each of the first option, the second option, the third option, and the fourth option, and the second option, the third option, and the fourth option including a spoiler alert checkbox; receiving the annotation that is to be in association with the entire, page, or selected text of the volume of digital content, the annotation being created by a first user using a device that is remotely connected to a server via a network, and the annotation being stored in a computer-readable memory at the server in a manner that maintains a logical connection between the annotation and the associated entire, page, or selected text of the volume of the digital content; receiving an indication of a collection of annotations into which annotations are to be added, the collection of annotations being created by the first user indicating a desire to create the collection via a user interface and by providing a name for the collection via the user interface, the collection including a privacy setting associated therewith; adding the annotation into the collection of annotations so created; providing access to annotations of the collection of annotations, said providing including specifying and causing displaying of the collection of annotations; and sharing the collection of annotations with one or more other users via the server, the collection of annotations being selected from among a plurality of collections of annotations. | 19. A method of annotating digital content comprising: causing displaying of a menu including all of a first option to create an annotation such that the annotation is not associated with a volume of digital content, a second option to create the annotation such that the annotation is associated with an entire of the volume of digital content, a third option to create the annotation such that the annotation is associated with a page of the volume of digital content, and a fourth option to create the annotation such that the annotation is associated with selected text contained within the volume of digital content, the menu including a privacy setting associated with each of the first option, the second option, the third option, and the fourth option, and the second option, the third option, and the fourth option including a spoiler alert checkbox; receiving the annotation that is to be in association with the entire, page, or selected text of the volume of digital content, the annotation being created by a first user using a device that is remotely connected to a server via a network, and the annotation being stored in a computer-readable memory at the server in a manner that maintains a logical connection between the annotation and the associated entire, page, or selected text of the volume of the digital content; receiving an indication of a collection of annotations into which annotations are to be added, the collection of annotations being created by the first user indicating a desire to create the collection via a user interface and by providing a name for the collection via the user interface, the collection including a privacy setting associated therewith; adding the annotation into the collection of annotations so created; providing access to annotations of the collection of annotations, said providing including specifying and causing displaying of the collection of annotations; and sharing the collection of annotations with one or more other users via the server, the collection of annotations being selected from among a plurality of collections of annotations. 24. The method according to claim 19 , further comprising: storing a plurality of annotations by the server in association with a plurality of volumes; filtering the annotations by specifying one or more collections and one or more additional filtering criteria; and causing displaying of the filtered annotations. | 0.531343 |
8,195,683 | 8 | 13 | 8. A machine-readable medium including instructions, which when executed by a machine cause the machine to perform operations comprising: receiving a search query including a token, the search query to be performed on data in a database stored on the machine-readable medium or a different machine-readable medium, the database including items of data that are represented by data strings; determining a synonym candidate for the token; adding the synonym candidate as a synonym for the token into an expansion dictionary in response to a determination that the number of data strings having the synonym candidate exceeds a threshold and a determination that the synonym candidate and the token are in a same category for a level of a tree hierarchy in the database, the tree hierarchy including a plurality of nodes having parent-child relationships; expanding the search query to include the synonym to form an expanded search query; and performing a search, using the expanded search query, for data in the database. | 8. A machine-readable medium including instructions, which when executed by a machine cause the machine to perform operations comprising: receiving a search query including a token, the search query to be performed on data in a database stored on the machine-readable medium or a different machine-readable medium, the database including items of data that are represented by data strings; determining a synonym candidate for the token; adding the synonym candidate as a synonym for the token into an expansion dictionary in response to a determination that the number of data strings having the synonym candidate exceeds a threshold and a determination that the synonym candidate and the token are in a same category for a level of a tree hierarchy in the database, the tree hierarchy including a plurality of nodes having parent-child relationships; expanding the search query to include the synonym to form an expanded search query; and performing a search, using the expanded search query, for data in the database. 13. The machine-readable medium of claim 8 , wherein determining the synonym candidate for the token comprises determining a plural form of a singular form of the token. | 0.691606 |
9,263,042 | 13 | 14 | 13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining, by a server for each of multiple words or sub-words, audio data corresponding to multiple users speaking the word or sub-word; training, by the server for each of the multiple words or sub-words, a hotword model for the word or sub-word based on the audio data for the word or sub-word, wherein the hotword model for the word or sub-word is a model that is used to detect an utterance of the word or sub-word in audio input data without transcribing the word or sub-word from input audio data; storing each of the trained hotword models as a pre-computed hotword model; receiving, by the server, a candidate hotword from a computing device; identifying, by the server, one or more of the stored pre-computed hotword models that correspond to the candidate hotword; and providing, by the server, the identified, one or more of the stored pre-computed hotword models to the computing device. | 13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining, by a server for each of multiple words or sub-words, audio data corresponding to multiple users speaking the word or sub-word; training, by the server for each of the multiple words or sub-words, a hotword model for the word or sub-word based on the audio data for the word or sub-word, wherein the hotword model for the word or sub-word is a model that is used to detect an utterance of the word or sub-word in audio input data without transcribing the word or sub-word from input audio data; storing each of the trained hotword models as a pre-computed hotword model; receiving, by the server, a candidate hotword from a computing device; identifying, by the server, one or more of the stored pre-computed hotword models that correspond to the candidate hotword; and providing, by the server, the identified, one or more of the stored pre-computed hotword models to the computing device. 14. The system of claim 13 , wherein identifying one or more of the stored pre-computed hotword models comprises: obtaining two or more sub-words that correspond to the candidate hotword; and obtaining, for each of the two or more sub-words that correspond to the candidate hotword, a pre-computed hotword model that corresponds to the sub-word. | 0.801724 |
6,107,945 | 4 | 6 | 4. A character detection circuit for determining a character value for a signal having a frequency, said character detection circuit comprising: a delay element having an input for receiving sample values derived from the signal and an output adapted for providing a sample value received on said input after a predetermined period of time; and a subtractor having a first input coupled to said output of said delay element, a second input coupled to said input of said delay element, and an output adapted for providing a difference between a value provided to said first input and a value provided to said second input. | 4. A character detection circuit for determining a character value for a signal having a frequency, said character detection circuit comprising: a delay element having an input for receiving sample values derived from the signal and an output adapted for providing a sample value received on said input after a predetermined period of time; and a subtractor having a first input coupled to said output of said delay element, a second input coupled to said input of said delay element, and an output adapted for providing a difference between a value provided to said first input and a value provided to said second input. 6. The character detection circuit of claim 4, further including: a peak detector having an input coupled to the output of said subtractor and a servo bit output adapted for signaling a positive peak value on the output of said subtractor based on said differences provided by said subtractor. | 0.825803 |
9,817,819 | 1 | 6 | 1. A method comprising, by one or more computing devices: sending, to a client system of a first user, instructions configured to present a translation prompt comprising a first text string; receiving, from the client system, a first input by the first user, wherein the first input corresponds to a first translation for the first text string; and calculating, by one or more of the computing devices, a reliability-value for the first translation based on the first input and a credibility-score of the first user, wherein the credibility-score of the first user is based on responses by the first user to checker-translation prompts, wherein the checker-translation prompts each comprise a control string for which a correct translation is known, and wherein the credibility-score is based on a number of responses by the first user that match the respective correct translations for the control strings. | 1. A method comprising, by one or more computing devices: sending, to a client system of a first user, instructions configured to present a translation prompt comprising a first text string; receiving, from the client system, a first input by the first user, wherein the first input corresponds to a first translation for the first text string; and calculating, by one or more of the computing devices, a reliability-value for the first translation based on the first input and a credibility-score of the first user, wherein the credibility-score of the first user is based on responses by the first user to checker-translation prompts, wherein the checker-translation prompts each comprise a control string for which a correct translation is known, and wherein the credibility-score is based on a number of responses by the first user that match the respective correct translations for the control strings. 6. The method of claim 1 , wherein the correct translation is a translation that has a reliability-value greater than a threshold reliability-value. | 0.872193 |
7,614,052 | 23 | 26 | 23. A distributed computing system for developing and deploying a smart client application from a server to a client machine via a network, said system comprising: a server-side application comprising at least one markup document and at least one business logic component, wherein said markup document is written using any declarative Extensible Markup Language (XML) and said business logic component is written using any programming language; a compiler for compiling said business logic component into a specific executable code, wherein said compiler is adapted to receive a business logic component written in any programming language and to compile said business logic component into a specific executable code that can be executed by a specific execution engine in said client machine; a markup language converter for converting said markup document into a specific markup language document, wherein said markup language converter is adapted to receive a markup document written in any XML language and to convert said markup document into a specific markup language document that is compatible with a specific client runtime environment (CRE) of said client machine; and a network server for deploying said specific markup document and said specific executable code to said client machine via said network. | 23. A distributed computing system for developing and deploying a smart client application from a server to a client machine via a network, said system comprising: a server-side application comprising at least one markup document and at least one business logic component, wherein said markup document is written using any declarative Extensible Markup Language (XML) and said business logic component is written using any programming language; a compiler for compiling said business logic component into a specific executable code, wherein said compiler is adapted to receive a business logic component written in any programming language and to compile said business logic component into a specific executable code that can be executed by a specific execution engine in said client machine; a markup language converter for converting said markup document into a specific markup language document, wherein said markup language converter is adapted to receive a markup document written in any XML language and to convert said markup document into a specific markup language document that is compatible with a specific client runtime environment (CRE) of said client machine; and a network server for deploying said specific markup document and said specific executable code to said client machine via said network. 26. The system of claim 23 further comprising caching said compiled specific executable code and said converted specific markup language document by a server cache. | 0.767045 |
8,719,278 | 2 | 3 | 2. The computer-implemented method of claim 1 , further comprising: determining a commonality between the query term and at least one member of the set of attributes. | 2. The computer-implemented method of claim 1 , further comprising: determining a commonality between the query term and at least one member of the set of attributes. 3. The computer-implement method of claim 2 , wherein determining the attribute score for each document comprises: determining a number of matches or a probability weight of a match between the set of attributes and each document. | 0.5 |
9,241,195 | 5 | 7 | 5. The computer-implemented method of claim 1 , further comprising transmitting identifications of more than one of the programs associated with matching dialog text; and ranking the more than one of the programs for displaying according to rank. | 5. The computer-implemented method of claim 1 , further comprising transmitting identifications of more than one of the programs associated with matching dialog text; and ranking the more than one of the programs for displaying according to rank. 7. The computer-implemented method according to claim 5 , further comprising: associating a different plurality of images with each program of the more than one of the programs, wherein each image is associated with a different grouping of dialog text associated with each program; and determining, for each program of the more than one of the programs and, one of the plurality of images associated with the matching dialog text for displaying to the particular user. | 0.5 |
8,196,090 | 1 | 2 | 1. A computerized method which, when executed by one or more processors, cause the one or more processors to perform operations comprising: creating a model, wherein the model comprises one or more associated profiles; reading a stereotype of a first profile, wherein the stereotype defines constraints to be applied to the model associated with the first profile; determining that the stereotype indicates a second profile and a third profile; accessing the second profile and the third profile; and aggregating a plurality of constraints from across the second and the third profiles for use as constraints for the stereotype of the first profile, wherein the profiles and the stereotype comport with semantics of a modeling language and wherein said aggregating comprises writing references to the plurality of constraints into a definition of the stereotype of the first profile. | 1. A computerized method which, when executed by one or more processors, cause the one or more processors to perform operations comprising: creating a model, wherein the model comprises one or more associated profiles; reading a stereotype of a first profile, wherein the stereotype defines constraints to be applied to the model associated with the first profile; determining that the stereotype indicates a second profile and a third profile; accessing the second profile and the third profile; and aggregating a plurality of constraints from across the second and the third profiles for use as constraints for the stereotype of the first profile, wherein the profiles and the stereotype comport with semantics of a modeling language and wherein said aggregating comprises writing references to the plurality of constraints into a definition of the stereotype of the first profile. 2. The computerized method of claim 1 , wherein said aggregating comprises: copying the plurality of constraints into a definition of the stereotype of the first profile. | 0.564103 |
8,112,425 | 1 | 15 | 1. A computer-implemented method for time searching data, comprising: receiving time series data streams from an information processing environment that includes a plurality of servers; organizing the time series data stream for subsequent searching by performing actions, including: determining at least one domain that corresponds to data in the time series data streams, wherein data in the time series data streams is aggregated based on at least the one determined domain; time stamping the time series data streams to create at least one time stamped event that includes at least a portion of aggregated data from the time series data streams, wherein the time stamped event represents a statistic and a pattern of behavior; employing at least one feature of the included aggregated data to determine at least one boundary for each time stamped event; segmenting each time stamped event into a plurality of segments, wherein a segment is a substring of event text; time indexing the time stamped events to create time bucketed indices based on the time stamps and segments; and receiving a time series search request; and executing the time series search request at least in part by searching the time bucketed indices. | 1. A computer-implemented method for time searching data, comprising: receiving time series data streams from an information processing environment that includes a plurality of servers; organizing the time series data stream for subsequent searching by performing actions, including: determining at least one domain that corresponds to data in the time series data streams, wherein data in the time series data streams is aggregated based on at least the one determined domain; time stamping the time series data streams to create at least one time stamped event that includes at least a portion of aggregated data from the time series data streams, wherein the time stamped event represents a statistic and a pattern of behavior; employing at least one feature of the included aggregated data to determine at least one boundary for each time stamped event; segmenting each time stamped event into a plurality of segments, wherein a segment is a substring of event text; time indexing the time stamped events to create time bucketed indices based on the time stamps and segments; and receiving a time series search request; and executing the time series search request at least in part by searching the time bucketed indices. 15. The method of claim 1 wherein the step of executing the time series search request comprises creating meta events. | 0.79078 |
7,711,573 | 76 | 80 | 76. A method for using a computer to improve a precision ratio when searching a resume database, comprising: receiving a resume in a memory device resident in the computer; 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, by the computer, 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; storing the resume in the resume database; 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; storing the parsed resume in the resume database; 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 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. | 76. A method for using a computer to improve a precision ratio when searching a resume database, comprising: receiving a resume in a memory device resident in the computer; 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, by the computer, 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; storing the resume in the resume database; 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; storing the parsed resume in the resume database; 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 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. 80. The method of claim 76 , wherein the receiving of the resume is from a candidate. | 0.910714 |
9,251,475 | 1 | 3 | 1. A method for selecting strangers for information spreading on a social network, the method comprising: training statistical models with history data of the information spreading of strangers on the social network, the strangers on the social network being not known to a requester who requests the strangers on the social network to conduct the information spreading; computing information spreading probabilities based on features of the strangers on the social network; computing information reach of the strangers on the social network; computing information spreading probabilities based on a wait time of the strangers on the social network, the wait time being a period of time for the strangers on the social network to initiate information spreading in response to being requested by the requester; computing fitness scores of the strangers on the social network, the fitness scores being a function of: the information spreading probabilities based on features, the information reach, and the information spreading probabilities based on the wait time; ranking the strangers on the social network in a sorted set, based on the fitness scores; selecting one or more of the strangers for the information spreading from the sorted set; and wherein the one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, the interval satisfies an optimization objective of minimizing time for the information spreading within a confidence probability. | 1. A method for selecting strangers for information spreading on a social network, the method comprising: training statistical models with history data of the information spreading of strangers on the social network, the strangers on the social network being not known to a requester who requests the strangers on the social network to conduct the information spreading; computing information spreading probabilities based on features of the strangers on the social network; computing information reach of the strangers on the social network; computing information spreading probabilities based on a wait time of the strangers on the social network, the wait time being a period of time for the strangers on the social network to initiate information spreading in response to being requested by the requester; computing fitness scores of the strangers on the social network, the fitness scores being a function of: the information spreading probabilities based on features, the information reach, and the information spreading probabilities based on the wait time; ranking the strangers on the social network in a sorted set, based on the fitness scores; selecting one or more of the strangers for the information spreading from the sorted set; and wherein the one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, the interval satisfies an optimization objective of minimizing time for the information spreading within a confidence probability. 3. The method of claim 1 , wherein the one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, the interval satisfies an optimization objective of maximizing unit information reach per stranger, the unit information reach per stranger is a sum of followers of strangers conducting the information spreading normalized by a number of strangers being asked to conduct the information spreading. | 0.761805 |
7,558,408 | 27 | 38 | 27. One or more processor-readable digital data storage media having programming instructions embedded therein for programming a processor to classify images including face regions that are acquired with an image acquisition device, the programming instructions comprising: a workflow module providing for the automatic or semiautomatic processing of identified face regions within digital images from which normalized face classifier parameter values are extracted and collectively referred to as a faceprint, the processing comprising: comparing said extracted faceprint to a database of archived faceprints previously determined to correspond to one or more known identities, determining based on the comparing whether a new faceprint corresponds to any of the one or more known identities, and associating the new faceprint and a normalized face region from which said faceprint is derived with a new or known identity within a database comprising other data corresponding to the archived faceprints and associated parent images for performing further comparisons with further faceprints, to permit data corresponding to the new faceprint and its associated parent image to be archived according to the associating by the workflow module within one or more digital data storage media; and a set of user interface modules for obtaining user input in the classifying of faceprints and their associated normalized face regions and parent images; and wherein one or more archived faceprints have been previously determined to correspond to the one or more known identities, and the comparing by the workflow module comprises determining proximities of the values of the face classifier parameters of the new face print image with values corresponding to the one or more archived faceprints, and wherein the determining by the workflow module comprises a further confirmation to determine whether the new faceprint corresponds to a known identity when comparisons of the face classifier parameter values of a first faceprint with multiple archived faceprints corresponding to a same known identity result in at least one determination of an identity match and at least one determination that the identities do not match. | 27. One or more processor-readable digital data storage media having programming instructions embedded therein for programming a processor to classify images including face regions that are acquired with an image acquisition device, the programming instructions comprising: a workflow module providing for the automatic or semiautomatic processing of identified face regions within digital images from which normalized face classifier parameter values are extracted and collectively referred to as a faceprint, the processing comprising: comparing said extracted faceprint to a database of archived faceprints previously determined to correspond to one or more known identities, determining based on the comparing whether a new faceprint corresponds to any of the one or more known identities, and associating the new faceprint and a normalized face region from which said faceprint is derived with a new or known identity within a database comprising other data corresponding to the archived faceprints and associated parent images for performing further comparisons with further faceprints, to permit data corresponding to the new faceprint and its associated parent image to be archived according to the associating by the workflow module within one or more digital data storage media; and a set of user interface modules for obtaining user input in the classifying of faceprints and their associated normalized face regions and parent images; and wherein one or more archived faceprints have been previously determined to correspond to the one or more known identities, and the comparing by the workflow module comprises determining proximities of the values of the face classifier parameters of the new face print image with values corresponding to the one or more archived faceprints, and wherein the determining by the workflow module comprises a further confirmation to determine whether the new faceprint corresponds to a known identity when comparisons of the face classifier parameter values of a first faceprint with multiple archived faceprints corresponding to a same known identity result in at least one determination of an identity match and at least one determination that the identities do not match. 38. The system of claim 27 , wherein the programming instructions are stored on or accessible by a stand alone processor-based device configured for receiving raw image data from a digital camera, and the device being coupled with or including user interface hardware, and upon which the classifying is performed. | 0.510938 |
9,111,260 | 1 | 5 | 1. A method comprising: causing, to be displayed to a user, data that identifies a plurality of packages to which the user may subscribe; receiving, from the user, input that indicates a subscription, by the user, to one or more packages of the plurality of packages, each of which includes a plurality of pre-defined suggested words that were not selected for inclusion in the package by the user; sending, to a server over a network, a list that identifies each of the one or more packages for which the user has indicated a subscription; after sending the list to the server, receiving, from the server, the plurality of pre-defined suggested words associated with each package identified in the list; after receiving the plurality of pre-defined suggested words associated with each package in the list, determining whether any text within an electronic messaging (EM) conversation qualifies as a suggested word for the user in the EM conversation based, at least in part, on whether the text matches any of the plurality of pre-defined suggested words of the one or more packages; causing text within the EM conversation that qualifies as a suggested word to be displayed in a manner that visually distinguishes the suggested word from text of the EM conversation that does not qualify as a suggested word; in response to receiving, from the user, second input relative to the suggested word in the EM conversation, causing, to be initiated, an operation to retrieve information related to the suggested word; in response to receiving results of said operation, causing a display that reflects the results to be generated; wherein the one or more packages includes a first package that is associated with a first set of suggested words; after causing the display that reflects the results to be generated, receiving a second set of suggested words that are different than the first set of suggested words and that are to be associated with the first package; wherein the method is performed by one or more computing devices. | 1. A method comprising: causing, to be displayed to a user, data that identifies a plurality of packages to which the user may subscribe; receiving, from the user, input that indicates a subscription, by the user, to one or more packages of the plurality of packages, each of which includes a plurality of pre-defined suggested words that were not selected for inclusion in the package by the user; sending, to a server over a network, a list that identifies each of the one or more packages for which the user has indicated a subscription; after sending the list to the server, receiving, from the server, the plurality of pre-defined suggested words associated with each package identified in the list; after receiving the plurality of pre-defined suggested words associated with each package in the list, determining whether any text within an electronic messaging (EM) conversation qualifies as a suggested word for the user in the EM conversation based, at least in part, on whether the text matches any of the plurality of pre-defined suggested words of the one or more packages; causing text within the EM conversation that qualifies as a suggested word to be displayed in a manner that visually distinguishes the suggested word from text of the EM conversation that does not qualify as a suggested word; in response to receiving, from the user, second input relative to the suggested word in the EM conversation, causing, to be initiated, an operation to retrieve information related to the suggested word; in response to receiving results of said operation, causing a display that reflects the results to be generated; wherein the one or more packages includes a first package that is associated with a first set of suggested words; after causing the display that reflects the results to be generated, receiving a second set of suggested words that are different than the first set of suggested words and that are to be associated with the first package; wherein the method is performed by one or more computing devices. 5. The method of claim 1 , wherein: at least one of the one or more packages contains at least one regular expression used to specify a pattern; words within the EM conversation are treated as suggested words when the words match the pattern specified by the regular expression. | 0.772131 |
4,118,788 | 23 | 24 | 23. The method defined in claim 22 wherein said mapping step includes converting an input word having a variable length to an output word having a predetermined length via a hashing process. | 23. The method defined in claim 22 wherein said mapping step includes converting an input word having a variable length to an output word having a predetermined length via a hashing process. 24. The method defined in claim 23 wherein said sequence generating step includes generating an output sequence for i = 1,2,3, . . . given by EQU Z.sub.i = [(A .times. Z.sub.i-1) + C].sub.modulo M, wherein A and C are constants and Z.sub.0 is said integer value. | 0.5 |
8,156,160 | 1 | 4 | 1. A computer-implemented method of generating a poet personality comprising: analyzing by one or more computers a plurality of poems, each of the poems containing a plurality of words; generating by the one or more computers a plurality of analysis models, each of said analysis models representing one of said plurality of poems, by marking by the one or more computers words in the poems with rhyme numbers with words that rhyme with each other having the same rhyme number; generating by the one or more computers a data structure that specifies n-grams found in the text, with each analysis model haying a set of weights, bigram, trigram and quadgram exponents; and storing the plurality of analysis models in a personality data structure including a set of parameters that control poetry generation using the personality data structure. | 1. A computer-implemented method of generating a poet personality comprising: analyzing by one or more computers a plurality of poems, each of the poems containing a plurality of words; generating by the one or more computers a plurality of analysis models, each of said analysis models representing one of said plurality of poems, by marking by the one or more computers words in the poems with rhyme numbers with words that rhyme with each other having the same rhyme number; generating by the one or more computers a data structure that specifies n-grams found in the text, with each analysis model haying a set of weights, bigram, trigram and quadgram exponents; and storing the plurality of analysis models in a personality data structure including a set of parameters that control poetry generation using the personality data structure. 4. The computer-implemented method of claim 1 , wherein the poems have corresponding authors, the method further comprising: defining weight value of authors corresponding to the poems within the personality data structure. | 0.510965 |
9,530,417 | 1 | 2 | 1. A method of text independent speaker recognition, comprising: extracting feature vectors from initial frames of speech generated responsive to text-independent speech from a user; clustering the extracted feature vectors to generate a plurality of clusters; modelling each of the plurality of clusters as a Gaussian Mixture Model that collectively form a speaker profile for the user; setting a different-state transition probability and a same-state transition probability for each of the Gaussian Mixture Models, the same-state transition probability having a much greater value than the different-state transition probability; capturing additional frames of speech from additional text-independent speech from a speaker; extracting feature vectors from the additional frames; and determining likelihoods that each of the additional frames belongs to each of the Gaussian Mixture Models based on the same-state and different-state transition probabilities, wherein the determining likelihoods includes, for each additional frame of speech, determining a log likelihood (loglk) variable for each cluster to determine the probability that the additional frame of speech belongs to that particular cluster; and determining whether the speaker is an authorized user from the determined likelihoods. | 1. A method of text independent speaker recognition, comprising: extracting feature vectors from initial frames of speech generated responsive to text-independent speech from a user; clustering the extracted feature vectors to generate a plurality of clusters; modelling each of the plurality of clusters as a Gaussian Mixture Model that collectively form a speaker profile for the user; setting a different-state transition probability and a same-state transition probability for each of the Gaussian Mixture Models, the same-state transition probability having a much greater value than the different-state transition probability; capturing additional frames of speech from additional text-independent speech from a speaker; extracting feature vectors from the additional frames; and determining likelihoods that each of the additional frames belongs to each of the Gaussian Mixture Models based on the same-state and different-state transition probabilities, wherein the determining likelihoods includes, for each additional frame of speech, determining a log likelihood (loglk) variable for each cluster to determine the probability that the additional frame of speech belongs to that particular cluster; and determining whether the speaker is an authorized user from the determined likelihoods. 2. The method of claim 1 wherein setting a different-state transition probability and a same-state transition probability for each of the Gaussian Mixture Models comprises setting the different-state transition probability between Gaussian Mixture Models to a value of 0.05 and setting the same-state transition probability for each Gaussian Mixture Model to a value of 0.95. | 0.5 |
8,073,827 | 4 | 12 | 4. A processing method performed by a processing apparatus having a processing unit, the processing method comprising: inputting a first process description document; performing a service, by the processing unit, in accordance with a procedure written in the first process description document including first, second, third and fourth description parts, the first description part describing a receiving processing for receiving data from a client via a network and a service processing for performing the service, the second description part describing a call processing for calling a second processing apparatus which is connected to the network and provides a second web service, the third description part describing a conversion from a variable used by the second processing apparatus to a variable used by a third processing apparatus, and the fourth description part describing a call processing for calling the third processing apparatus which is connected to the network and provides a third web service; generating, by the processing unit, a second process description document including the first and fourth description parts by deleting, from the first process description document, second and third description parts; and sending the second process description document to the next processing apparatus described in the deleted second description part. | 4. A processing method performed by a processing apparatus having a processing unit, the processing method comprising: inputting a first process description document; performing a service, by the processing unit, in accordance with a procedure written in the first process description document including first, second, third and fourth description parts, the first description part describing a receiving processing for receiving data from a client via a network and a service processing for performing the service, the second description part describing a call processing for calling a second processing apparatus which is connected to the network and provides a second web service, the third description part describing a conversion from a variable used by the second processing apparatus to a variable used by a third processing apparatus, and the fourth description part describing a call processing for calling the third processing apparatus which is connected to the network and provides a third web service; generating, by the processing unit, a second process description document including the first and fourth description parts by deleting, from the first process description document, second and third description parts; and sending the second process description document to the next processing apparatus described in the deleted second description part. 12. The processing method according to claim 4 , wherein the first and second process description documents are sequential process description documents. | 0.746689 |
9,870,345 | 18 | 19 | 18. A computing device comprising: one or more processors; and a non-transitory computer-readable storage medium having a plurality of instructions stored thereon, which, when executed by the one or more processors, cause the one or more processors to perform operations comprising: executing a communication application; receiving a received textual message from a sender user, the received textual message including text content; determining an insertion point for the received textual message based on the text content, the insertion point corresponding to a particular location of a plurality of possible locations in a graphical user interface of the communication application, each of the plurality of possible locations corresponding to a position in the graphical user interface subsequent to a preceding textual message; displaying the received textual message in the graphical user interface of the communication application at the determined insertion point; and analyzing, at the computing device, the text content to determine whether the text content includes two or more potentially semantically distinct segments, wherein, when the text content includes two or more potentially semantically distinct segments: the determining the insertion point for the received textual message comprises determining, for each particular potentially semantically distinct segment, a segment insertion point based on the particular potentially semantically distinct segment, and the displaying the received textual message in the graphical user interface of the communication application at the determined insertion point comprises displaying each particular potentially semantically distinct segment at its corresponding segment insertion point. | 18. A computing device comprising: one or more processors; and a non-transitory computer-readable storage medium having a plurality of instructions stored thereon, which, when executed by the one or more processors, cause the one or more processors to perform operations comprising: executing a communication application; receiving a received textual message from a sender user, the received textual message including text content; determining an insertion point for the received textual message based on the text content, the insertion point corresponding to a particular location of a plurality of possible locations in a graphical user interface of the communication application, each of the plurality of possible locations corresponding to a position in the graphical user interface subsequent to a preceding textual message; displaying the received textual message in the graphical user interface of the communication application at the determined insertion point; and analyzing, at the computing device, the text content to determine whether the text content includes two or more potentially semantically distinct segments, wherein, when the text content includes two or more potentially semantically distinct segments: the determining the insertion point for the received textual message comprises determining, for each particular potentially semantically distinct segment, a segment insertion point based on the particular potentially semantically distinct segment, and the displaying the received textual message in the graphical user interface of the communication application at the determined insertion point comprises displaying each particular potentially semantically distinct segment at its corresponding segment insertion point. 19. The computing device of claim 18 , wherein analyzing the text content to determine whether the text content includes two or more potentially semantically distinct segments comprises: analyzing the text content to determine whether the text content includes one or more text split points; and when the text content includes one or more text split points, splitting the text content at the one or more text split points to obtain the two or more potentially semantically distinct segments. | 0.5 |
7,580,937 | 1 | 3 | 1. A method for generating and transmitting a calendar of different legal events capable of occurring in the course of a legal proceeding, the method comprising: maintaining in a database at least one rule set including a plurality of date calculation instructions for calculating a plurality of different legal events; receiving, under control of a server, an initial trigger date for an initial trigger legal event; selecting, under control of the server, one or more date calculation instructions from the database based on the initial trigger legal event; calculating, under control of the server, one or more event dates based on the initial trigger date and the retrieved date calculation instructions; transmitting, under control of the server, the one or more calculated event dates to a user client; maintaining, under control of the server, a transaction record of the one or more date calculation instructions used for generating the one or more event dates for the user client; monitoring, under control of the server, a changes table for changes in the plurality of date calculation instructions, the changes table identifying the changed date calculation instructions; automatically determining, under control of the server, whether the one or more date calculation instructions identified in the record are identified in the changes table; for each one of the one or more date calculation instructions identified in the changes table, recalculating, under control of the server, the associated event date based on the change to the corresponding date calculation instruction; and transmitting, under control of the server, the recalculated one or more event dates to the user client. | 1. A method for generating and transmitting a calendar of different legal events capable of occurring in the course of a legal proceeding, the method comprising: maintaining in a database at least one rule set including a plurality of date calculation instructions for calculating a plurality of different legal events; receiving, under control of a server, an initial trigger date for an initial trigger legal event; selecting, under control of the server, one or more date calculation instructions from the database based on the initial trigger legal event; calculating, under control of the server, one or more event dates based on the initial trigger date and the retrieved date calculation instructions; transmitting, under control of the server, the one or more calculated event dates to a user client; maintaining, under control of the server, a transaction record of the one or more date calculation instructions used for generating the one or more event dates for the user client; monitoring, under control of the server, a changes table for changes in the plurality of date calculation instructions, the changes table identifying the changed date calculation instructions; automatically determining, under control of the server, whether the one or more date calculation instructions identified in the record are identified in the changes table; for each one of the one or more date calculation instructions identified in the changes table, recalculating, under control of the server, the associated event date based on the change to the corresponding date calculation instruction; and transmitting, under control of the server, the recalculated one or more event dates to the user client. 3. The method of claim 1 further comprising: identifying, under control of the server, a customer affected by the recalculated one or more event dates; and transmitting, under control of the server, a notification to the customer of the recalculated one or more event dates. | 0.712185 |
9,792,825 | 1 | 3 | 1. A system for interacting with a user of a device through a character presented by the device, the system comprising one or more computers configured to: determine that a trigger event has occurred by processing (i) information about the trigger event and (ii) data received from the device of the user or data received from a calendar of the user; cause, in response to determining that the trigger event has occurred, a session with the character to be started on the device; select a first script for interactions between the user and the character presented by the device; select a first movie clip data item from a data store of movie clip data items, wherein the first movie clip data item corresponds to a first movie clip and comprises an identifier of a character in the first movie clip; obtain information about the character in the first movie clip using the identifier; cause the device to present the first movie clip to the user; construct a phrase using the script and the information about the character in the first movie clip; and cause the character presented by device to present the phrase to the user. | 1. A system for interacting with a user of a device through a character presented by the device, the system comprising one or more computers configured to: determine that a trigger event has occurred by processing (i) information about the trigger event and (ii) data received from the device of the user or data received from a calendar of the user; cause, in response to determining that the trigger event has occurred, a session with the character to be started on the device; select a first script for interactions between the user and the character presented by the device; select a first movie clip data item from a data store of movie clip data items, wherein the first movie clip data item corresponds to a first movie clip and comprises an identifier of a character in the first movie clip; obtain information about the character in the first movie clip using the identifier; cause the device to present the first movie clip to the user; construct a phrase using the script and the information about the character in the first movie clip; and cause the character presented by device to present the phrase to the user. 3. The system of claim 1 , wherein the trigger event is associated with a plurality of scripts and the one or more computers are configured to select the first script by selecting the first script from the plurality of scripts. | 0.800176 |
8,065,246 | 5 | 6 | 5. The storage medium as set forth in claim 4 , wherein the first majorization process generates an upper bound of the form: log ∑ k = 1 K ⅇ x k ≤ α + ∑ k = 1 K log ( 1 + ⅇ x k - α ) where α ∈ K . | 5. The storage medium as set forth in claim 4 , wherein the first majorization process generates an upper bound of the form: log ∑ k = 1 K ⅇ x k ≤ α + ∑ k = 1 K log ( 1 + ⅇ x k - α ) where α ∈ K . 6. The storage medium as set forth in claim 5 , wherein the second majorization process modifies the upper bound of the form: log ∑ k = 1 K ⅇ x k ≤ α + ∑ k = 1 K log ( 1 + ⅇ x k - α ) to the form: log ∑ k = 1 K ⅇ x k ≤ α + ∑ k = 1 K x k - α - ξ x 2 + λ ( ξ k ) ( ( x k - α ) 2 - ξ k 2 ) + log ( 1 + ⅇ ξ k ) for α ∈ K and ξ ∈ [ 0 , ∞ ) K where : λ ( ξ ) = 1 2 ξ [ 1 1 + ⅇ - ξ - 1 2 ] . | 0.5 |
8,744,839 | 12 | 13 | 12. A target word recognition system, comprising: one or more processors configured to: obtain a candidate word set and corresponding characteristic computation data, the candidate word set comprising text data, and characteristic computation data being associated with the candidate word set; perform segmentation of the characteristic computation data to generate a plurality of text segments; combine the plurality of text segments to form a text data combination set; determine an intersection of the candidate word set and the text data combination set, the intersection comprising a plurality of text data combinations; determine a plurality of designated characteristic values for the plurality of text data combinations; determine a criterion, including: obtain a training sample word set and sample characteristic computation data, the sample characteristic computation data comprising a plurality of sample words and designated characteristic values of the plurality of sample words; obtain a sample text data combination set based on the plurality of sample words; determine a plurality of designated characteristic values of sample text data combinations in an intersection of the sample text data combination set and the training sample word set; and set a threshold value of a designated characteristic value of a sample text data combination in the intersection as a part of the criterion; and based at least in part on the plurality of designated characteristic values for the plurality of text data combinations and according to at least the criterion, recognize among the plurality of text data combinations, target words whose characteristic values fulfill the criterion; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions. | 12. A target word recognition system, comprising: one or more processors configured to: obtain a candidate word set and corresponding characteristic computation data, the candidate word set comprising text data, and characteristic computation data being associated with the candidate word set; perform segmentation of the characteristic computation data to generate a plurality of text segments; combine the plurality of text segments to form a text data combination set; determine an intersection of the candidate word set and the text data combination set, the intersection comprising a plurality of text data combinations; determine a plurality of designated characteristic values for the plurality of text data combinations; determine a criterion, including: obtain a training sample word set and sample characteristic computation data, the sample characteristic computation data comprising a plurality of sample words and designated characteristic values of the plurality of sample words; obtain a sample text data combination set based on the plurality of sample words; determine a plurality of designated characteristic values of sample text data combinations in an intersection of the sample text data combination set and the training sample word set; and set a threshold value of a designated characteristic value of a sample text data combination in the intersection as a part of the criterion; and based at least in part on the plurality of designated characteristic values for the plurality of text data combinations and according to at least the criterion, recognize among the plurality of text data combinations, target words whose characteristic values fulfill the criterion; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions. 13. The system of claim 12 , wherein the candidate word set is based on user-inputted query keywords to a website. | 0.853846 |
9,189,475 | 7 | 9 | 7. A method for perform advanced leveraging for translation, comprising: creating an index structure on a computer by parsing a first target string that comprises a first sentence and a second target string that comprises a second sentence that is different from the first sentence; matching said index structure to index structures previously stored on the computer; and obtaining a translation of the first target string and the second target string, using the computer, corresponding to a match between said index structure and said index structures previously stored on the computer, wherein said index structure comprises phrasal and sub-phrasal markers, each marker having a constituent, a constituent name, and a number that corresponds to numbering each node according to a depth-first visit of the first target string and the second target string, wherein parsing the first target string and the second target string comprises dynamically parsing the first target string and the second target string, wherein in response to the match being determined at a higher sub-phrase level, a lower sub-phrase level of the higher sub-phrase level is not parsed, and wherein the index structure comprises a first phrasal marker corresponding to the first target string and a second phrasal marker corresponding to the second target string. | 7. A method for perform advanced leveraging for translation, comprising: creating an index structure on a computer by parsing a first target string that comprises a first sentence and a second target string that comprises a second sentence that is different from the first sentence; matching said index structure to index structures previously stored on the computer; and obtaining a translation of the first target string and the second target string, using the computer, corresponding to a match between said index structure and said index structures previously stored on the computer, wherein said index structure comprises phrasal and sub-phrasal markers, each marker having a constituent, a constituent name, and a number that corresponds to numbering each node according to a depth-first visit of the first target string and the second target string, wherein parsing the first target string and the second target string comprises dynamically parsing the first target string and the second target string, wherein in response to the match being determined at a higher sub-phrase level, a lower sub-phrase level of the higher sub-phrase level is not parsed, and wherein the index structure comprises a first phrasal marker corresponding to the first target string and a second phrasal marker corresponding to the second target string. 9. The method according to claim 7 , wherein the number is an index_entry_range. | 0.792746 |
7,676,786 | 10 | 14 | 10. The method of claim 9 , wherein the first set of components comprises: a data component, a presentation component and a message component. | 10. The method of claim 9 , wherein the first set of components comprises: a data component, a presentation component and a message component. 14. The method of claim 10 , further comprising converting a syntax and a format of the data component, the message component and the presentation component, and the cross-component mapping into a format suitable for importing by the modeling tool. | 0.720721 |
8,239,334 | 2 | 3 | 2. The method as recited in claim 1 further comprising: maximizing an average of pair-wise labeled information of a query such that 1 d i > d j : q k ∑ d i > d j : qk tr { W T ( ( 2 q k - d i - d j ) ( d i - d j ) T ) W } ξ kij represents the pair-wise ranked data for the query represented as q k , wherein: |d i <d j :q k | represents the number of the pair-wise labeled data, and ξ kij represents a weight characterizing importance of a ranked pair for a given query. | 2. The method as recited in claim 1 further comprising: maximizing an average of pair-wise labeled information of a query such that 1 d i > d j : q k ∑ d i > d j : qk tr { W T ( ( 2 q k - d i - d j ) ( d i - d j ) T ) W } ξ kij represents the pair-wise ranked data for the query represented as q k , wherein: |d i <d j :q k | represents the number of the pair-wise labeled data, and ξ kij represents a weight characterizing importance of a ranked pair for a given query. 3. The method as recited in claim 2 wherein optimizing 1 d i > d j : q k ∑ d i > d j : qk tr { W T ( ( 2 q k - d i - d j ) ( d i - d j ) T ) W } ξ kij embodies a closed form solution. | 0.5 |
7,647,210 | 1 | 10 | 1. An electronic method for parametric modeling of a conceptual vehicle design, the method comprising the steps of: (a) receiving dimensional input including one or more vehicle level parameters and one or more component level parameters; (b) receiving geometrical input including one or more non-dimensional design inputs; and (c) generating a parametric concept model based on the dimensional input and the geometrical input, wherein the parametric concept model includes a parametric skeleton having one or more control profiles and one or more control openings associated therewith; and (d) adjusting the one or more control profiles or the one or more control openings to modify the parametric concept model; (e) generating a generic skeleton, having generic geometry associated therewith, based on the parametric skeleton; (f) generating a design skeleton, having vehicle specific geometry associated therewith; and (g) either iterating the generic skeleton without updating the design skeleton or iterating the design skeleton without updating the generic skeleton. | 1. An electronic method for parametric modeling of a conceptual vehicle design, the method comprising the steps of: (a) receiving dimensional input including one or more vehicle level parameters and one or more component level parameters; (b) receiving geometrical input including one or more non-dimensional design inputs; and (c) generating a parametric concept model based on the dimensional input and the geometrical input, wherein the parametric concept model includes a parametric skeleton having one or more control profiles and one or more control openings associated therewith; and (d) adjusting the one or more control profiles or the one or more control openings to modify the parametric concept model; (e) generating a generic skeleton, having generic geometry associated therewith, based on the parametric skeleton; (f) generating a design skeleton, having vehicle specific geometry associated therewith; and (g) either iterating the generic skeleton without updating the design skeleton or iterating the design skeleton without updating the generic skeleton. 10. The electronic method of claim 1 wherein at least a portion of the dimensional input comprises one or more control parameters. | 0.74 |
7,958,501 | 7 | 9 | 7. A system comprising: program code comprising: an object management system to call a constructor to register an interface to a description of a persistent class; and a database management system kernel to access the registered interface to determine an internal structure of the persistent class, to process an instance of the persistent class based on the determined internal structure, wherein the instance of the persistent class is a persistent database object, to determine, based on the determined internal structure, members of the persistent database object that are filled with default values, to store the persistent database object in a database, to reduce storage demands on the database by removing the default values from the persistent database object before the storing of the persistent database object in the database, to read the persistent database object from the database after the storing of the persistent database object in the database, to populate the determined members of the persistent database object with the default values after the reading of the persistent database object from the database, to define an index associated with one or more members of the instance based on the determined internal structure and to verify referential integrity of the instance; and at least one processor to execute the program code. | 7. A system comprising: program code comprising: an object management system to call a constructor to register an interface to a description of a persistent class; and a database management system kernel to access the registered interface to determine an internal structure of the persistent class, to process an instance of the persistent class based on the determined internal structure, wherein the instance of the persistent class is a persistent database object, to determine, based on the determined internal structure, members of the persistent database object that are filled with default values, to store the persistent database object in a database, to reduce storage demands on the database by removing the default values from the persistent database object before the storing of the persistent database object in the database, to read the persistent database object from the database after the storing of the persistent database object in the database, to populate the determined members of the persistent database object with the default values after the reading of the persistent database object from the database, to define an index associated with one or more members of the instance based on the determined internal structure and to verify referential integrity of the instance; and at least one processor to execute the program code. 9. The system according to claim 7 , the database management system kernel further to define a key associated with one or more members of the instance based on the determined internal structure. | 0.755051 |
9,588,653 | 17 | 19 | 17. A method comprising: providing a GUI document browser-editor configured to load at least one GUI document from an address, the address being associated with a location of one of the following: a GUI document and a world wide web page, wherein the GUI document browser-editor is configured to enable multiple editors of the GUI document to collaboratively edit the GUI documents; retrieving the GUI document from the address, wherein retrieving the GUI document comprises accessing a GUI document storage file; loading, within the GUI document browser-editor, the GUI document retrieved from the GUI document address, wherein loading the GUI document comprises reading the GUI storage file and, based on the reading, placing presentation elements on a page window of the GUI document browser-editor; enabling, by the GUI document browser-editor, a user to edit the GUI document within the page window, wherein enabling the user to edit the GUI the GUI document comprises enabling: a placement of at least one presentation element within the GUI document, wherein the at least one presentation element comprises an instance of a GUI class object and metadata; a modification of at least one property within the GUI document by providing editing tools configured to modify properties, functions, and events of the at least one presentation element and enabling the user to select from a plurality of properties, functions and events predefined by the GUI Document browser-editor; and saving the modified GUI document comprising the at least one presentation element in the storage file format comprising the metadata of the at least one presentation element. | 17. A method comprising: providing a GUI document browser-editor configured to load at least one GUI document from an address, the address being associated with a location of one of the following: a GUI document and a world wide web page, wherein the GUI document browser-editor is configured to enable multiple editors of the GUI document to collaboratively edit the GUI documents; retrieving the GUI document from the address, wherein retrieving the GUI document comprises accessing a GUI document storage file; loading, within the GUI document browser-editor, the GUI document retrieved from the GUI document address, wherein loading the GUI document comprises reading the GUI storage file and, based on the reading, placing presentation elements on a page window of the GUI document browser-editor; enabling, by the GUI document browser-editor, a user to edit the GUI document within the page window, wherein enabling the user to edit the GUI the GUI document comprises enabling: a placement of at least one presentation element within the GUI document, wherein the at least one presentation element comprises an instance of a GUI class object and metadata; a modification of at least one property within the GUI document by providing editing tools configured to modify properties, functions, and events of the at least one presentation element and enabling the user to select from a plurality of properties, functions and events predefined by the GUI Document browser-editor; and saving the modified GUI document comprising the at least one presentation element in the storage file format comprising the metadata of the at least one presentation element. 19. The method of claim 17 , wherein editing further comprises: receiving a selection of at least one presentation element; displaying a means for modifying at least one property associated with the selected at least one presentation element; receiving an indication of modification to the at least one property; and modifying the at least one property based on the received modification indication. | 0.5 |
9,824,122 | 5 | 7 | 5. A non-transitory computer readable medium having instructions therein which, if executed, cause at least one processor to: generate a natural language description for each section of text in a plurality of source code files, wherein to generate the natural language description for each section, the at least one processor is to delineate each section of the source code text in the source code files, wherein each delineated section of the source code text is substantially similar to a predefined source code template; parse a request for a particular type of source code text that specifies a particular action to be performed by a computer; and obtain each section of text whose description at least partially matches the parsed request, each obtained section being adaptable for generating at least some of the type of source code text requested. | 5. A non-transitory computer readable medium having instructions therein which, if executed, cause at least one processor to: generate a natural language description for each section of text in a plurality of source code files, wherein to generate the natural language description for each section, the at least one processor is to delineate each section of the source code text in the source code files, wherein each delineated section of the source code text is substantially similar to a predefined source code template; parse a request for a particular type of source code text that specifies a particular action to be performed by a computer; and obtain each section of text whose description at least partially matches the parsed request, each obtained section being adaptable for generating at least some of the type of source code text requested. 7. The non-transitory computer readable medium of claim 5 , wherein the instructions therein, if executed, further instruct the at least one processor to rank each obtained section of the source code text in accordance with a similarity between the request and the natural language description of each obtained section of the source code text. | 0.5 |
9,275,046 | 1 | 5 | 1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: providing an interface for selecting a vertical language text translation box corresponding to one or more words in the first language, wherein the first language is an Asian language comprising a plurality of characters having a vertical alignment; cropping a frame of the real-time video feed of the one or more words of the first language to fit inside the vertical language text translation box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments; performing character recognition on the merged character segments to produce a plurality of recognized characters; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language in augmented reality in the real-time video feed. | 1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: providing an interface for selecting a vertical language text translation box corresponding to one or more words in the first language, wherein the first language is an Asian language comprising a plurality of characters having a vertical alignment; cropping a frame of the real-time video feed of the one or more words of the first language to fit inside the vertical language text translation box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments; performing character recognition on the merged character segments to produce a plurality of recognized characters; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language in augmented reality in the real-time video feed. 5. The method of claim 1 , wherein the step of performing the character merging further comprises: performing vertical and/or horizontal merging on the character segments with recognition feedback to produce the plurality of merged character segments. | 0.777482 |
9,760,828 | 1 | 5 | 1. A method, in a data processing system comprising a processor and a memory configured to implement a question and answer system (QA), for utilizing temporal indicators to weight semantic values, the method comprising: in response to receiving an input question, identifying a set of temporal characteristics for a set of candidate answers for the input question; associating an initial confidence score with each candidate answer of the set of candidate answers; refine each initial confidence score associated with each candidate answer in the set of initial candidate answers based on the set of temporal characteristics, wherein each confidence score associated with each candidate answer is refined based on the set of temporal characteristics using a reference time of the input question and a respective reference time associated with the candidate answer thereby forming a temporally refined confidence score associated with the candidate answer, wherein the temporally refined confidence score associated with the candidate answer is identified by: generating a distance value in terms of years for the respective reference time associated with the candidate answer and the reference time of the input question; determining a multiplier value with which to weight the confidence score associated with the candidate answer using the distance value using multiplier function: Multiplier value=1/(2*distance value+0.5); determining a sentiment value of the candidate answer to weight the determined multiplier value; and determining a final weight value for the temporally refined confidence score associated with the candidate answer using the multiplier value, the sentiment value, and the initial confidence score associated with the initial candidate answer; and providing a set of candidate answers with the temporally refined confidence scores to the user. | 1. A method, in a data processing system comprising a processor and a memory configured to implement a question and answer system (QA), for utilizing temporal indicators to weight semantic values, the method comprising: in response to receiving an input question, identifying a set of temporal characteristics for a set of candidate answers for the input question; associating an initial confidence score with each candidate answer of the set of candidate answers; refine each initial confidence score associated with each candidate answer in the set of initial candidate answers based on the set of temporal characteristics, wherein each confidence score associated with each candidate answer is refined based on the set of temporal characteristics using a reference time of the input question and a respective reference time associated with the candidate answer thereby forming a temporally refined confidence score associated with the candidate answer, wherein the temporally refined confidence score associated with the candidate answer is identified by: generating a distance value in terms of years for the respective reference time associated with the candidate answer and the reference time of the input question; determining a multiplier value with which to weight the confidence score associated with the candidate answer using the distance value using multiplier function: Multiplier value=1/(2*distance value+0.5); determining a sentiment value of the candidate answer to weight the determined multiplier value; and determining a final weight value for the temporally refined confidence score associated with the candidate answer using the multiplier value, the sentiment value, and the initial confidence score associated with the initial candidate answer; and providing a set of candidate answers with the temporally refined confidence scores to the user. 5. The method of claim 1 , wherein the set of candidate answers with the temporally refined confidence scores is ranked according to the determined final weight values. | 0.511628 |
9,020,932 | 16 | 17 | 16. The computer program product of claim 15 , wherein the retrieved search history data comprises unique user search history data that is associated with identity indicia that is unique to the user, and generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having common same occupational identity indicia; and wherein the computer readable program code instructions, when executed by the computer processing unit, further cause the computer processing unit to classify the text string search query into the constituent primary search terms by weighting classifications determined as a function of the unique user search history data more highly than classifications determined as a function of the generic occupational identity search data, and weighting classifications determined as a function of the generic occupational identity search data more highly than any classifications generated by application of universal search history popularities common to all user histories. | 16. The computer program product of claim 15 , wherein the retrieved search history data comprises unique user search history data that is associated with identity indicia that is unique to the user, and generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having common same occupational identity indicia; and wherein the computer readable program code instructions, when executed by the computer processing unit, further cause the computer processing unit to classify the text string search query into the constituent primary search terms by weighting classifications determined as a function of the unique user search history data more highly than classifications determined as a function of the generic occupational identity search data, and weighting classifications determined as a function of the generic occupational identity search data more highly than any classifications generated by application of universal search history popularities common to all user histories. 17. The computer program product of claim 16 , wherein the computer readable program code instructions, when executed by the computer processing unit, further cause the computer processing unit to identify the generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having the common occupational identity indicia by: recognizing a type of network access used by the user to submit the text string query; determining a predominant occupational identity associated with the recognized type of network access; and retrieving search history common to pluralities of users that share the determined predominant occupational identity as the generic occupational identity search data. | 0.749351 |
9,288,275 | 25 | 44 | 25. A computer-implemented method for implementing an event centric social networking platform, said method comprising the following steps: storing, in a first repository, at least user related information including at least registration information; storing, in a second repository, at least the information corresponding to catalog offerings; storing, in a third repository, at least event-related information corresponding to said users, information corresponding to resources uploaded onto a social networking platform by said users, information corresponding to access privileges and action permissions granted to user roles with respect to event-related information; receiving a request from a user towards organizing an event based on at least one of catalog offerings/catalog offering related activities, said request including at least event related information; searching said second repository for catalog offerings related to said event related information, and generating a list of catalog offerings related to event specified by a user based on user related information; enabling selection of at least one vendor offering from said list of catalog offerings and updating the event-related information stored in said third repository to reflect the vendor offering selected by said user; searching friend list for users, based on a pre-defined criteria, and categorizing users in search result into pre-determined invitee categories; generating an invitee list for an event including user names selected from at least one of said pre-determined invitee categories and non-registered invitees, and selectively transmitting an invitation inviting users included in said invitee list to attend said event, enabling said registered/non-registered invitees to respond to the event invitation, and tracking the responses of invited users; and displaying a list of event invitations including past events and the events planned for future dates, controlling users' access to said list of event invitations, providing users with selective access to contents of the event invitations, enabling said users to view the listed event invitation, edit the listed event invitation, comment on the listed event invitation and add image/social media files on to the listed event invitation; generating notifications corresponding to at least the activities performed by said users on said social networking platform, and transmitting said notifications to at least one other user whose name is included in the friend list associated with the users. | 25. A computer-implemented method for implementing an event centric social networking platform, said method comprising the following steps: storing, in a first repository, at least user related information including at least registration information; storing, in a second repository, at least the information corresponding to catalog offerings; storing, in a third repository, at least event-related information corresponding to said users, information corresponding to resources uploaded onto a social networking platform by said users, information corresponding to access privileges and action permissions granted to user roles with respect to event-related information; receiving a request from a user towards organizing an event based on at least one of catalog offerings/catalog offering related activities, said request including at least event related information; searching said second repository for catalog offerings related to said event related information, and generating a list of catalog offerings related to event specified by a user based on user related information; enabling selection of at least one vendor offering from said list of catalog offerings and updating the event-related information stored in said third repository to reflect the vendor offering selected by said user; searching friend list for users, based on a pre-defined criteria, and categorizing users in search result into pre-determined invitee categories; generating an invitee list for an event including user names selected from at least one of said pre-determined invitee categories and non-registered invitees, and selectively transmitting an invitation inviting users included in said invitee list to attend said event, enabling said registered/non-registered invitees to respond to the event invitation, and tracking the responses of invited users; and displaying a list of event invitations including past events and the events planned for future dates, controlling users' access to said list of event invitations, providing users with selective access to contents of the event invitations, enabling said users to view the listed event invitation, edit the listed event invitation, comment on the listed event invitation and add image/social media files on to the listed event invitation; generating notifications corresponding to at least the activities performed by said users on said social networking platform, and transmitting said notifications to at least one other user whose name is included in the friend list associated with the users. 44. The method as claimed in claim 25 , wherein the method further includes the step of generating an open choice invitation with a limited number of choices provided to invitees regarding catalog offerings and related time/date schedules. | 0.833565 |
7,640,531 | 18 | 19 | 18. A method of managing application development, comprising: maintaining, in a first document, a first list of interactions between a plurality of applications; maintaining, in a second document, a second list of interactions within one or more of the plurality of applications; maintaining, in a third document, a third list of existing interactions; providing a tool that communicates with the first, the second, and the third documents; using the tool to count a number of business operation points based on the interactions in the first list and the second list, the tool monitors the third list and reduces the count for interactions in the first list and the second list having associated existing interactions in the third list, wherein the first list of interactions and the second list of interactions include a plurality of types of interactions, the plurality of types of interactions includes two or more of group consisting of internal logical files types of interactions, external interfaces files types of interactions, external inputs types of interactions, external outputs types of interactions, and external queries types of interactions, and wherein the business operation points include interactions between applications and interactions within an application between components of the application, but do not include the components of the applications themselves or interactions with external non-application entities; measuring hours expended developing the application; calculating a productivity metric for developing the application based on a count of business operation points delivered by an outsourcing firm developing the application and the hours expended by the outsourcing firm developing the application; calculating a productivity rate of change based on the productivity metric of the outsourcing firm for developing the one or more applications and a productivity metric of the outsourcing firm for developing a previous one or more applications; and designing incentive packages for the outsourcing firm based on the productivity rate of change. | 18. A method of managing application development, comprising: maintaining, in a first document, a first list of interactions between a plurality of applications; maintaining, in a second document, a second list of interactions within one or more of the plurality of applications; maintaining, in a third document, a third list of existing interactions; providing a tool that communicates with the first, the second, and the third documents; using the tool to count a number of business operation points based on the interactions in the first list and the second list, the tool monitors the third list and reduces the count for interactions in the first list and the second list having associated existing interactions in the third list, wherein the first list of interactions and the second list of interactions include a plurality of types of interactions, the plurality of types of interactions includes two or more of group consisting of internal logical files types of interactions, external interfaces files types of interactions, external inputs types of interactions, external outputs types of interactions, and external queries types of interactions, and wherein the business operation points include interactions between applications and interactions within an application between components of the application, but do not include the components of the applications themselves or interactions with external non-application entities; measuring hours expended developing the application; calculating a productivity metric for developing the application based on a count of business operation points delivered by an outsourcing firm developing the application and the hours expended by the outsourcing firm developing the application; calculating a productivity rate of change based on the productivity metric of the outsourcing firm for developing the one or more applications and a productivity metric of the outsourcing firm for developing a previous one or more applications; and designing incentive packages for the outsourcing firm based on the productivity rate of change. 19. The method of claim 18 wherein the interactions and existing interactions define business operations points and wherein the tool calculates the net business operation points for development of the application. | 0.574 |
8,725,505 | 1 | 6 | 1. A computer implemented method of recognizing speech, the method comprising: identifying a valid speech recognition command that includes a pairing of a valid verb with one of a plurality of different valid objects pre-specified for the valid verb, wherein each one of the valid objects, in combination with the valid verb, defines a different action to be performed by a computing system; receiving an utterance from a user; determining that the utterance includes the valid verb in combination with an invalid object, the invalid object being determined to be invalid based at least in part upon a comparison of the invalid object to said plurality of different valid objects pre-specified for the valid verb; responding to the determination that the utterance includes the valid verb in combination with an invalid object by informing the user that the invalid object does not correspond to the valid verb and providing, in response to the determination, inductive feedback that induces the user to select one of two options for proceeding, comprising: prompting the user to submit an additional utterance that again includes the valid verb in combination with the invalid object but is preceded by a valid command word other than the valid verb, to convert the valid verb and the invalid object into a textual representation to be inserted as dictation; and prompting the user to select one of the different valid objects, that are prespecified for the valid verb, to use with the valid verb, by rendering a list of at least some of the different valid objects to the user; if the user submits the additional utterance, proceeding with the first one of the options by inserting the textual representation of the valid verb and the invalid object into a displayed collection of text generated based on other utterances received from the user; and if the user selects one of the different valid objects from the list, proceeding with the second one of the options by executing, using a processor of the computing system, the action defined by the valid verb and selected valid object. | 1. A computer implemented method of recognizing speech, the method comprising: identifying a valid speech recognition command that includes a pairing of a valid verb with one of a plurality of different valid objects pre-specified for the valid verb, wherein each one of the valid objects, in combination with the valid verb, defines a different action to be performed by a computing system; receiving an utterance from a user; determining that the utterance includes the valid verb in combination with an invalid object, the invalid object being determined to be invalid based at least in part upon a comparison of the invalid object to said plurality of different valid objects pre-specified for the valid verb; responding to the determination that the utterance includes the valid verb in combination with an invalid object by informing the user that the invalid object does not correspond to the valid verb and providing, in response to the determination, inductive feedback that induces the user to select one of two options for proceeding, comprising: prompting the user to submit an additional utterance that again includes the valid verb in combination with the invalid object but is preceded by a valid command word other than the valid verb, to convert the valid verb and the invalid object into a textual representation to be inserted as dictation; and prompting the user to select one of the different valid objects, that are prespecified for the valid verb, to use with the valid verb, by rendering a list of at least some of the different valid objects to the user; if the user submits the additional utterance, proceeding with the first one of the options by inserting the textual representation of the valid verb and the invalid object into a displayed collection of text generated based on other utterances received from the user; and if the user selects one of the different valid objects from the list, proceeding with the second one of the options by executing, using a processor of the computing system, the action defined by the valid verb and selected valid object. 6. The method of claim 1 , wherein providing, in response to the determination that the utterance includes the valid verb in combination with the invalid object, comprises providing upon a first utterance received from the user that includes the invalid object. | 0.5 |
8,941,870 | 15 | 16 | 15. Apparatus comprising a storage medium storing a program having instructions which when executed by a processor will cause the processor to: access a selected data source including data to be inserted into a plurality of files generated using a template and a data source; receive user input identifying template elements that act as location placeholders within an electronic document for data from the data source; generate a template from the electronic document using the identified template elements; generate a preview of a file generated using the template and the data source, the preview visible on the display device; receive selection of an output destination for the plurality of files generated using the template and the data source; generate the plurality of files using the template and the data source; and send the plurality of files to the output destination. | 15. Apparatus comprising a storage medium storing a program having instructions which when executed by a processor will cause the processor to: access a selected data source including data to be inserted into a plurality of files generated using a template and a data source; receive user input identifying template elements that act as location placeholders within an electronic document for data from the data source; generate a template from the electronic document using the identified template elements; generate a preview of a file generated using the template and the data source, the preview visible on the display device; receive selection of an output destination for the plurality of files generated using the template and the data source; generate the plurality of files using the template and the data source; and send the plurality of files to the output destination. 16. The apparatus of claim 15 wherein in the instructions will further cause the processor to save the template for later use after generating the template. | 0.746753 |
8,726,395 | 1 | 6 | 1. A system comprising: a memory device that stores instructions; and a hardware processor that executes the instructions to create an adaptation engine for partial encryption of a document, the adaptation engine comprising: a paginator, the paginator paginating the document into at least one sub-page according to characteristics of a specific device class; and an encryptor, the encryptor separately encrypting a to-be-encrypted element of the at least one sub-page using a partial encryption mechanism known by a client device and based on the characteristics of the specific device class, wherein when the to-be-encrypted element of the at least one sub-page comprises the entire sub-page, the encryptor encrypts the entire sub-page, and when the to-be-encrypted element of the at least one sub-page comprises less than all elements of the entire sub-page, the encryptor encrypts only the to-be-encrypted element, and further wherein the adaptation engine surrounds the to-be-encrypted element of the at least one sub-page with a corresponding encryption tag. | 1. A system comprising: a memory device that stores instructions; and a hardware processor that executes the instructions to create an adaptation engine for partial encryption of a document, the adaptation engine comprising: a paginator, the paginator paginating the document into at least one sub-page according to characteristics of a specific device class; and an encryptor, the encryptor separately encrypting a to-be-encrypted element of the at least one sub-page using a partial encryption mechanism known by a client device and based on the characteristics of the specific device class, wherein when the to-be-encrypted element of the at least one sub-page comprises the entire sub-page, the encryptor encrypts the entire sub-page, and when the to-be-encrypted element of the at least one sub-page comprises less than all elements of the entire sub-page, the encryptor encrypts only the to-be-encrypted element, and further wherein the adaptation engine surrounds the to-be-encrypted element of the at least one sub-page with a corresponding encryption tag. 6. The system of claim 1 , wherein the encryptor bases the partial encryption mechanism on jCETaglib. | 0.878019 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.