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3. An information access system according to claim 1 wherein said terminal further includes recording means for recording the phonetic signal information on a recording medium. | 3. An information access system according to claim 1 wherein said terminal further includes recording means for recording the phonetic signal information on a recording medium. 4. An information access system according to claim 3 wherein said terminal further includes playback means for playing back the phonetic signal information recorded on the recording medium. | 0.88898 |
9. The system of claim 8 , the memory further storing computer executable instructions that when executed by the processor cause the processor to carry out the steps that include: attempting to extend the normalized link text to include the context text from the left side or the right side of the normalized link text when the normalized link text matches the link address; and determining that the link text is safe when there is no additional context text to the left side or the right side of the normalized link text. | 9. The system of claim 8 , the memory further storing computer executable instructions that when executed by the processor cause the processor to carry out the steps that include: attempting to extend the normalized link text to include the context text from the left side or the right side of the normalized link text when the normalized link text matches the link address; and determining that the link text is safe when there is no additional context text to the left side or the right side of the normalized link text. 10. The system of claim 9 , the memory further storing computer executable instructions that when executed by the processor cause the processor to carry out the attempting to extend the normalized link text to include the context text from the left side or the right side of the normalized link text by: determining whether there is additional content text displayed adjacent to the normalized link text; and when there is additional context text displayed adjacent to the normalized link text: extending the normalized link text to include the additional context text, and repeating the steps of generating, determining, and the responsive actions, wherein the normalized text is generated based on the additional context text. | 0.702619 |
6. An image processing method that includes the step (i) of comparing features of an image that are extracted from image data of a document to be matched and features of an image of a reference document that has been stored, so as to determine whether the image of the document to be matched is similar to the image of the reference document, the image processing method comprising the step (ii) of determining whether the document to be matched that is determined in the step (i) as being similar to the reference document has been zoomed with respect to the similar reference document, and when the document to be matched has been zoomed, calculating a conversion coefficient with which the size of the document to be matched is changed to the size of the similar reference document. | 6. An image processing method that includes the step (i) of comparing features of an image that are extracted from image data of a document to be matched and features of an image of a reference document that has been stored, so as to determine whether the image of the document to be matched is similar to the image of the reference document, the image processing method comprising the step (ii) of determining whether the document to be matched that is determined in the step (i) as being similar to the reference document has been zoomed with respect to the similar reference document, and when the document to be matched has been zoomed, calculating a conversion coefficient with which the size of the document to be matched is changed to the size of the similar reference document. 8. The image processing method as set forth in claim 6 , further comprising the step (iv) of adding as associated information the conversion coefficient calculated in the step (ii) to the image data of the document to be matched, so that the size of the document to be matched is changed to the size of the similar reference document. | 0.829256 |
10. A method for managing survey data performed by at least one processor, comprising: collecting, by the at least one processor, surveys of a first survey type and surveys of a second survey type, the first type surveys including survey results having one or more answers to first questions, the second type surveys including survey results having one or more answers to second questions, the second type surveys relating to a different topic than the first type surveys; storing, by the at least one processor, the survey results in a layered database, the layered database having a fist layer storing the first and second questions and question weights for the first and second questions, And a second layer storing the survey results of the first type surveys and the second type surveys, the second layer being linked to the first layer; and generating, by the at least one processor, at least one report providing satisfaction results across the first type surveys and the second type surveys based on the question weights and the survey results of the first and second type surveys. | 10. A method for managing survey data performed by at least one processor, comprising: collecting, by the at least one processor, surveys of a first survey type and surveys of a second survey type, the first type surveys including survey results having one or more answers to first questions, the second type surveys including survey results having one or more answers to second questions, the second type surveys relating to a different topic than the first type surveys; storing, by the at least one processor, the survey results in a layered database, the layered database having a fist layer storing the first and second questions and question weights for the first and second questions, And a second layer storing the survey results of the first type surveys and the second type surveys, the second layer being linked to the first layer; and generating, by the at least one processor, at least one report providing satisfaction results across the first type surveys and the second type surveys based on the question weights and the survey results of the first and second type surveys. 12. The method of claim 10 , further comprising: calculating, by the at least one processor, a first overall satisfaction score for the first type surveys based on the question weights for the first questions and the survey results for the first type surveys, and a second overall satisfaction score for the second type surveys based on the question weights for the second questions and the survey results of the second type surveys. | 0.612181 |
1. A method for providing a workflow management system, said method comprising: maintaining a database configured to store translation segments, said translation segments identifying target language phrases in a target language that corresponds to source language phrases in a source language; identifying translators connected to a network using a translator identity for each of a plurality of different translators; storing translation segments submitted by a plurality of different translators; storing information by the database, the information identifying a translator that has submitted a translation segment of the submitted translation segments, by storing the translation segment in association with the translator identity of the translator that has submitted the translation segment; identifying translation segments for inclusion in at least partially translated content; delivering as part of a translation task said at least partially translated content electronically, said at least partially translated content including segments translated into said target language; and tracking the translator identity associated with a translation segment when the translation segment is selected for use in said at least partially translated content. | 1. A method for providing a workflow management system, said method comprising: maintaining a database configured to store translation segments, said translation segments identifying target language phrases in a target language that corresponds to source language phrases in a source language; identifying translators connected to a network using a translator identity for each of a plurality of different translators; storing translation segments submitted by a plurality of different translators; storing information by the database, the information identifying a translator that has submitted a translation segment of the submitted translation segments, by storing the translation segment in association with the translator identity of the translator that has submitted the translation segment; identifying translation segments for inclusion in at least partially translated content; delivering as part of a translation task said at least partially translated content electronically, said at least partially translated content including segments translated into said target language; and tracking the translator identity associated with a translation segment when the translation segment is selected for use in said at least partially translated content. 15. The method for providing a workflow management system according to claim 1 , further comprising: notifying translators to submit bids; receiving bids from at least one translator; determining a bid award; and sending a bid award notification. | 0.617991 |
6. One or more non-transitory computer-readable media having computer-executable instructions embodied thereon for performing a method of generating an entry in a personal information manager based on information in a textual communication, the method comprising: providing a user interface that allows a user to generate a template that is associated with two event descriptors used to generate a calendar entry, wherein an event descriptor is text describing characteristics of an event, and wherein the event is associated with at least a physical location and a time period; storing the template in a data store configured for storing a plurality of templates; receiving the textual communication; identifying a plurality of event descriptors within the textual communication; displaying the textual communication to a recipient with the plurality of event descriptors displayed as selectable, wherein the plurality of event descriptors appearance is changed to indicate the plurality of event descriptors are capable of selection by the recipient; receiving a first selection of a first event descriptor from the plurality of event descriptors, wherein the first event descriptor describes the physical location associated with the event; receiving a second selection of a second event descriptor from the plurality of event descriptors, wherein the second event descriptor describes the time period associated with the event; determining a time of travel between a default location and the physical location; generating directions from the default location to the physical location; generating a suggested calendar entry that includes the time of travel and the directions; and displaying, to the recipient, the suggested calendar entry based on the first selection and the second selection. | 6. One or more non-transitory computer-readable media having computer-executable instructions embodied thereon for performing a method of generating an entry in a personal information manager based on information in a textual communication, the method comprising: providing a user interface that allows a user to generate a template that is associated with two event descriptors used to generate a calendar entry, wherein an event descriptor is text describing characteristics of an event, and wherein the event is associated with at least a physical location and a time period; storing the template in a data store configured for storing a plurality of templates; receiving the textual communication; identifying a plurality of event descriptors within the textual communication; displaying the textual communication to a recipient with the plurality of event descriptors displayed as selectable, wherein the plurality of event descriptors appearance is changed to indicate the plurality of event descriptors are capable of selection by the recipient; receiving a first selection of a first event descriptor from the plurality of event descriptors, wherein the first event descriptor describes the physical location associated with the event; receiving a second selection of a second event descriptor from the plurality of event descriptors, wherein the second event descriptor describes the time period associated with the event; determining a time of travel between a default location and the physical location; generating directions from the default location to the physical location; generating a suggested calendar entry that includes the time of travel and the directions; and displaying, to the recipient, the suggested calendar entry based on the first selection and the second selection. 7. The media of claim 6 , wherein the method further comprises: displaying, to the recipient, one or more event types that correlate with the first selection and the second selection; receiving a selection of a first event type from the user; and wherein the suggested calendar entry is also based on the first event type. | 0.513784 |
1. A method for unsupervised learning of a grammatical parser and the use thereof, wherein the method comprises: providing a processor on a computer, wherein the processor runs a content acquisition system to obtain a corpus of text documents over a computer network; storing the corpus of text documents from the content acquisition system on a storage device; providing a processor on the computer which runs a text analytics engine, wherein the text analytics engine comprise a core algorithm, and a factorization algorithm; using the core algorithm to: divide the corpus of text documents into a plurality of sentences; divide the sentences from the plurality of sentences into a plurality of text units; join the text units from the plurality of text units into a plurality of grammatical links; and using the factorization algorithm to factorize a matrix or a tensor for each of the grammatical links of the plurality of grammatical links to respectively generate a plurality of factorized matrices or a plurality of factorized tensors; and additionally using the core algorithm to: generate parses from a corpus of a novel document, comprising: divide the corpus from the novel document into a plurality of sentences; divide the sentences from the plurality of sentences from the novel document into a plurality of text units; identify a subset of all possible grammatical links from the plurality of text units from the novel document; and determine the relative likelihood of the grammatical links in the corpus of the novel document by using the factorized matrices or the factorized tensors to compute a score representing the likelihood of the grammatical links. | 1. A method for unsupervised learning of a grammatical parser and the use thereof, wherein the method comprises: providing a processor on a computer, wherein the processor runs a content acquisition system to obtain a corpus of text documents over a computer network; storing the corpus of text documents from the content acquisition system on a storage device; providing a processor on the computer which runs a text analytics engine, wherein the text analytics engine comprise a core algorithm, and a factorization algorithm; using the core algorithm to: divide the corpus of text documents into a plurality of sentences; divide the sentences from the plurality of sentences into a plurality of text units; join the text units from the plurality of text units into a plurality of grammatical links; and using the factorization algorithm to factorize a matrix or a tensor for each of the grammatical links of the plurality of grammatical links to respectively generate a plurality of factorized matrices or a plurality of factorized tensors; and additionally using the core algorithm to: generate parses from a corpus of a novel document, comprising: divide the corpus from the novel document into a plurality of sentences; divide the sentences from the plurality of sentences from the novel document into a plurality of text units; identify a subset of all possible grammatical links from the plurality of text units from the novel document; and determine the relative likelihood of the grammatical links in the corpus of the novel document by using the factorized matrices or the factorized tensors to compute a score representing the likelihood of the grammatical links. 9. The method of claim 1 , further comprising providing a cutoff, wherein scores above the cutoff are used to determine the relative likelihood of a grammatical link. | 0.569274 |
1. A method for performing runtime checking operations in a compiled programming development environment, comprising the steps of: a) compiling a source code file into executable object code comprising machine language instructions, wherein said source code file includes aggregate data items and pointers and also includes expressions which manipulate said aggregate data items and pointers, wherein said step of compiling comprises: creating data structures for aggregate data items and pointers in the source code file; and inserting calls to runtime checking functions for one or more expressions in the source code file which manipulate said aggregate data items and pointers; and b) executing the executable object code, wherein said step of executing comprises: executing one or more of said runtime checking functions to determine if invalid operations occur in said expressions which manipulate said aggregate data items and pointers; and reporting an error to the user if an invalid operation is found to occur after said step of executing one or more of said runtime checking functions. | 1. A method for performing runtime checking operations in a compiled programming development environment, comprising the steps of: a) compiling a source code file into executable object code comprising machine language instructions, wherein said source code file includes aggregate data items and pointers and also includes expressions which manipulate said aggregate data items and pointers, wherein said step of compiling comprises: creating data structures for aggregate data items and pointers in the source code file; and inserting calls to runtime checking functions for one or more expressions in the source code file which manipulate said aggregate data items and pointers; and b) executing the executable object code, wherein said step of executing comprises: executing one or more of said runtime checking functions to determine if invalid operations occur in said expressions which manipulate said aggregate data items and pointers; and reporting an error to the user if an invalid operation is found to occur after said step of executing one or more of said runtime checking functions. 25. The method of claim 1, wherein said step of executing the executable object code comprises: accessing one or more data structures for pointers and aggregate data items in arguments being passed from a caller function to a callee function; placing said one or more data structures into a current runtime information data structure; beginning execution of said callee function; and accessing said one or more data structures from said current runtime information data structure inside said callee function to perform runtime checking operations on expressions inside said callee function. | 0.633172 |
1. A computer system for facilitating sales of a product to a user, the computer system comprising: a user interface configured to query the user regarding product interests of the user; a selection device operatively connected to the user interface, and configured to present a customized proposal to the user based on the user's product interests; an active database operatively connected to the selection device, and configured to store the user's product interests; a report database operatively connected to the selection device, and configured to store a plurality of page layouts; a static database operatively connected to the selection device, and configured to store product information; a difference database operatively connected to the static database, wherein the difference database stores update information configured for transmittal to the static database; and a report generator operatively connected to the active database, the report database, the selection device, and the static database, and configured to link page layout identifiers with particular data that appear in the customized proposal, wherein the customized proposal includes at least one item based upon the user's product interests, and wherein the at least one item includes at least one of: a product picture, an environment picture, and a text portion. | 1. A computer system for facilitating sales of a product to a user, the computer system comprising: a user interface configured to query the user regarding product interests of the user; a selection device operatively connected to the user interface, and configured to present a customized proposal to the user based on the user's product interests; an active database operatively connected to the selection device, and configured to store the user's product interests; a report database operatively connected to the selection device, and configured to store a plurality of page layouts; a static database operatively connected to the selection device, and configured to store product information; a difference database operatively connected to the static database, wherein the difference database stores update information configured for transmittal to the static database; and a report generator operatively connected to the active database, the report database, the selection device, and the static database, and configured to link page layout identifiers with particular data that appear in the customized proposal, wherein the customized proposal includes at least one item based upon the user's product interests, and wherein the at least one item includes at least one of: a product picture, an environment picture, and a text portion. 10. The computer system of claim 1 , wherein the static database stores a plurality of product pictures, a plurality of environment pictures, and a plurality of text portions, wherein each text portion is associated with at least one of a product and a environment. | 0.644272 |
1. A method for creating or updating parallel corpus in a machine translation system, comprising the steps of: preparing a test set, E, to be updated; translating the test set E from a first language to a second language using a translation method other than parallel corpus, so as to create set F in the second language; translating set F back to the first language using a translation method other than parallel corpus so as to create set E′ in the first language; computing confidence scores for the translation of each item in the set based on the similarity of E and E′; creating a subset, H, of the highest confidence scores; and adding the translations in subset H directly to the parallel corpus without first presenting the translations to a human translator for correction, wherein the parallel corpus is stored in memory on the machine translation system. | 1. A method for creating or updating parallel corpus in a machine translation system, comprising the steps of: preparing a test set, E, to be updated; translating the test set E from a first language to a second language using a translation method other than parallel corpus, so as to create set F in the second language; translating set F back to the first language using a translation method other than parallel corpus so as to create set E′ in the first language; computing confidence scores for the translation of each item in the set based on the similarity of E and E′; creating a subset, H, of the highest confidence scores; and adding the translations in subset H directly to the parallel corpus without first presenting the translations to a human translator for correction, wherein the parallel corpus is stored in memory on the machine translation system. 2. The method of claim 1 further comprising the steps of: creating a subset, L, of lowest confidence scores; presenting subset L to human translators for correction; and adding the human corrections to the parallel corpus. | 0.697188 |
19. A computer readable storage medium as recited in claim 18 , wherein the contextual date information of the date request includes one or more word (s) arranged in a natural language. | 19. A computer readable storage medium as recited in claim 18 , wherein the contextual date information of the date request includes one or more word (s) arranged in a natural language. 20. A computer readable storage medium as recited in claim 19 , wherein the contextual date information specifies a holiday. | 0.916925 |
1. A computer-implemented method comprising: identifying, by one or more computing devices and from a plurality of images, one or more images that depict an entity; determining, by the one or more computing devices, location information associated with the one or more images that depict the entity; identifying, by the one or more computing devices and based at least in part on the location information associated with the one or more images that depict the entity, one or more candidate entity profiles from an entity directory; providing, by the one or more computing devices, the one or more images that depict the entity and the one or more candidate entity profiles as input to a machine learning model comprising a neural network and at least one recurrent neural network, the neural network comprising a deep convolutional neural network (CNN), the at least one recurrent neural network comprising a long short-term memory network (LSTM), the CNN being configured to receive data indicative of the one or more images that depict the entity, extract features from the one or more images that depict the entity, and provide data indicative of the extracted features to the LSTM, the LSTM being configured to receive data indicative of the one or more candidate entity profiles, obtain text-related information from the one or more candidate entity profiles, and model at least a portion of structured information from a candidate entity profile as a sequence of characters, such that a match score between the extracted features and data from the candidate entity profile can be determined; generating, by the one or more computing devices, one or more outputs of the machine learning model, each output comprising a match score associated with at least one candidate entity profile and an image that depicts the entity; and updating, by the one or more computing devices, the entity directory based at least in part on the one or more generated outputs of the machine learning model. | 1. A computer-implemented method comprising: identifying, by one or more computing devices and from a plurality of images, one or more images that depict an entity; determining, by the one or more computing devices, location information associated with the one or more images that depict the entity; identifying, by the one or more computing devices and based at least in part on the location information associated with the one or more images that depict the entity, one or more candidate entity profiles from an entity directory; providing, by the one or more computing devices, the one or more images that depict the entity and the one or more candidate entity profiles as input to a machine learning model comprising a neural network and at least one recurrent neural network, the neural network comprising a deep convolutional neural network (CNN), the at least one recurrent neural network comprising a long short-term memory network (LSTM), the CNN being configured to receive data indicative of the one or more images that depict the entity, extract features from the one or more images that depict the entity, and provide data indicative of the extracted features to the LSTM, the LSTM being configured to receive data indicative of the one or more candidate entity profiles, obtain text-related information from the one or more candidate entity profiles, and model at least a portion of structured information from a candidate entity profile as a sequence of characters, such that a match score between the extracted features and data from the candidate entity profile can be determined; generating, by the one or more computing devices, one or more outputs of the machine learning model, each output comprising a match score associated with at least one candidate entity profile and an image that depicts the entity; and updating, by the one or more computing devices, the entity directory based at least in part on the one or more generated outputs of the machine learning model. 4. The computer-implemented method of claim 1 , wherein each match score provides a degree of confidence that an entity depicted in an image corresponds to a candidate entity profile. | 0.568024 |
8. A computerized method for providing relevant paid content, the method comprising: receiving a search request; determining a plurality of contextual uses associated with the search request, wherein contextual uses comprise majority and minority contextual uses associated with the search request; determining type of content suitable to represent each of the determined contextual uses; and identifying at least one paid content relevant for each of the determined contextual uses. | 8. A computerized method for providing relevant paid content, the method comprising: receiving a search request; determining a plurality of contextual uses associated with the search request, wherein contextual uses comprise majority and minority contextual uses associated with the search request; determining type of content suitable to represent each of the determined contextual uses; and identifying at least one paid content relevant for each of the determined contextual uses. 21. The method of claim 8 , further comprising: displaying indicia representative of each of the determined contextual uses on the same page, wherein the indicia for each of the determined contextual uses includes the identified paid content for the respective determined contextual uses. | 0.726492 |
12. A non-transitory computer-readable storage medium storing a set of instructions that, when executed by a processor, cause the processor to perform operations, comprising: receiving a stream of data from a log of browsing activity of a user account; organizing the stream of data in a sequential and nested data structure; defining a relational and a sequential operator that both operate in parallel on the sequential and nested data structure; receiving a query related to the stream of data; splitting a collection of tuples from the stream of data into a plurality of substream of data without splitting the individual tuples; and processing, using a hardware processor of a machine, the query on the plurality of substreams across a plurality of nodes of the collection of tuples by operating the relational operator on the nested data structure of a tuple from the collection of tuples in parallel with operating the sequential operator on the sequential data structure of the tuple from the collection of tuples, wherein each respective individual tuple comprises an instance of one of: a search activity by the user account, a bid activity by the user account and a view item activity by the user account, the operators comprising an input operator, an output operator, a relational operator, and a pattern query, the input operator configured to load session logs corresponding to a date range, the output operator configured to save session logs in a storage device, the relational operator configured to operate on the sequential and nested data structure based on relation conditions and extract sub-sequences, the pattern query configured to operate on the sequential and nested data structure to identify sub-sequences that match an event pattern, the event pattern modeled as tuples and defined as a template that matches a set of contiguous events, the event pattern comprising respective instances of search activity that generated no results, the template describing order dependencies in the event pattern, data parameter conditions defining selection criteria for events, and context conditions identifying how events from a start of an event pattern and an end of an event pattern are broken into each pattern part. | 12. A non-transitory computer-readable storage medium storing a set of instructions that, when executed by a processor, cause the processor to perform operations, comprising: receiving a stream of data from a log of browsing activity of a user account; organizing the stream of data in a sequential and nested data structure; defining a relational and a sequential operator that both operate in parallel on the sequential and nested data structure; receiving a query related to the stream of data; splitting a collection of tuples from the stream of data into a plurality of substream of data without splitting the individual tuples; and processing, using a hardware processor of a machine, the query on the plurality of substreams across a plurality of nodes of the collection of tuples by operating the relational operator on the nested data structure of a tuple from the collection of tuples in parallel with operating the sequential operator on the sequential data structure of the tuple from the collection of tuples, wherein each respective individual tuple comprises an instance of one of: a search activity by the user account, a bid activity by the user account and a view item activity by the user account, the operators comprising an input operator, an output operator, a relational operator, and a pattern query, the input operator configured to load session logs corresponding to a date range, the output operator configured to save session logs in a storage device, the relational operator configured to operate on the sequential and nested data structure based on relation conditions and extract sub-sequences, the pattern query configured to operate on the sequential and nested data structure to identify sub-sequences that match an event pattern, the event pattern modeled as tuples and defined as a template that matches a set of contiguous events, the event pattern comprising respective instances of search activity that generated no results, the template describing order dependencies in the event pattern, data parameter conditions defining selection criteria for events, and context conditions identifying how events from a start of an event pattern and an end of an event pattern are broken into each pattern part. 13. The non-transitory computer-readable storage medium of claim 12 wherein the nested data structure comprises an atom, a tuple, a map, and a bag, wherein the atom includes a single value, wherein the tuple includes a sequence of atoms, wherein the map includes a collection of key and value pairs, wherein the bag includes the collection of tuples. | 0.535409 |
1. A method of delivering support services related to a chemical processing unit or units to a customer, wherein the chemical processing unit or units comprise a portion of at least one of a petroleum refinery, a petrochemical production plant, a chemicals purification plant, a natural gas processing unit, a gas separations unit, a refinery product blending unit, a bio-chemical production unit, a bio-fuel production unit, a fine chemicals production unit, an oil and gas production unit, and a pharmaceuticals production unit, the method comprising: providing interactive, computer-implemented support services to the customer during at least a portion of a lifespan of the unit or units, comprising: receiving a query related to at least one aspect associated with the unit or units from a requester; prompting the requester for information related to the query by presenting questions related to the query; receiving the information relating to the query from the requester by receiving responses to the questions, the responses comprising one of (i) yes; (ii) no; or (iii) uncertain; providing a diagram or illustration of the unit or units and prompting the requestor to select an element or component of the one or more units; receiving the selection of the element or component of the diagram or illustration; identifying one or more possible answers to the query based upon the query, the responses to the questions, and the selection of the element or component of the diagram or illustration; and providing the one or more possible answers to the requester. | 1. A method of delivering support services related to a chemical processing unit or units to a customer, wherein the chemical processing unit or units comprise a portion of at least one of a petroleum refinery, a petrochemical production plant, a chemicals purification plant, a natural gas processing unit, a gas separations unit, a refinery product blending unit, a bio-chemical production unit, a bio-fuel production unit, a fine chemicals production unit, an oil and gas production unit, and a pharmaceuticals production unit, the method comprising: providing interactive, computer-implemented support services to the customer during at least a portion of a lifespan of the unit or units, comprising: receiving a query related to at least one aspect associated with the unit or units from a requester; prompting the requester for information related to the query by presenting questions related to the query; receiving the information relating to the query from the requester by receiving responses to the questions, the responses comprising one of (i) yes; (ii) no; or (iii) uncertain; providing a diagram or illustration of the unit or units and prompting the requestor to select an element or component of the one or more units; receiving the selection of the element or component of the diagram or illustration; identifying one or more possible answers to the query based upon the query, the responses to the questions, and the selection of the element or component of the diagram or illustration; and providing the one or more possible answers to the requester. 2. The method of claim 1 , wherein providing interactive, computer-implemented support services to the customer comprises electronically providing support services to the customer through a remotely-accessible internet website. | 0.507038 |
10. A method implemented at least in part by a computing device, the method comprising: providing a typographically erroneous domain name; tracing the domain name wherein the tracing comprises entering the domain name as part of a URL and recording one or more subsequent URLs; identifying a domain parking service for the domain name based at least in part on information in one of the recorded URLs; determining client identification information in at least one of the recorded URLs wherein the client identification information identifies a customer of the domain parking service, wherein the client identification information is a particular client identifier extracted from a Client ID (cid) field of the final destination URL; and blocking one or more domain names based at least in part on the client identification information. | 10. A method implemented at least in part by a computing device, the method comprising: providing a typographically erroneous domain name; tracing the domain name wherein the tracing comprises entering the domain name as part of a URL and recording one or more subsequent URLs; identifying a domain parking service for the domain name based at least in part on information in one of the recorded URLs; determining client identification information in at least one of the recorded URLs wherein the client identification information identifies a customer of the domain parking service, wherein the client identification information is a particular client identifier extracted from a Client ID (cid) field of the final destination URL; and blocking one or more domain names based at least in part on the client identification information. 15. A computer-readable storage medium comprising processor-executable instructions for performing the method of claim 10 . | 0.589268 |
1. A computer-implemented method to halt execution of queries containing entity resolution (ER) candidate-building keys unsuitable for generating a restricted set of candidate entities against which to match a received identity record, the method comprising: receiving an identity record; determining a plurality of ER candidate-building keys for the received identity record; generating a query from one or more of the plurality of ER candidate-building keys to retrieve entities matching any of the one or more ER candidate-building keys, wherein the one or more ER candidate-building keys are derived from at least a field of the received identity record; and upon determining, during execution of the query and by operation of one or more computer processors, that at least a first ER candidate-building key of the one or more ER candidate-building keys is unsuitable for generating a restricted set of candidate entities against which to match the received identity record, aborting executing the query, wherein the restricted set of candidate entities is selected from a plurality of available entities greater in number than the restricted set of candidate entities. | 1. A computer-implemented method to halt execution of queries containing entity resolution (ER) candidate-building keys unsuitable for generating a restricted set of candidate entities against which to match a received identity record, the method comprising: receiving an identity record; determining a plurality of ER candidate-building keys for the received identity record; generating a query from one or more of the plurality of ER candidate-building keys to retrieve entities matching any of the one or more ER candidate-building keys, wherein the one or more ER candidate-building keys are derived from at least a field of the received identity record; and upon determining, during execution of the query and by operation of one or more computer processors, that at least a first ER candidate-building key of the one or more ER candidate-building keys is unsuitable for generating a restricted set of candidate entities against which to match the received identity record, aborting executing the query, wherein the restricted set of candidate entities is selected from a plurality of available entities greater in number than the restricted set of candidate entities. 3. The computer-implemented method of claim 1 , wherein the unsuitable ER candidate-building key comprises a ER candidate-building key that has retrieved a count of entities beyond a predefined threshold count. | 0.654225 |
1. A non-transitory computer readable medium having an executable data structure for managing reproduction of text subtitle data by a reproducing apparatus, comprising: an area storing at least one main AV data and a plurality of subtitle information segments, each one of the subtitle information segments being represented by a single PES packet of transport packets which includes a packet identifier for identifying a type of packet, wherein each one of the subtitle information segments includes a segment identifier identifying the subtitle information segment as one of text data and graphic data, wherein one of the subtitle information segments identified as the text data includes at most two text subtitle regions, and each text subtitle region is linked to at least one style information defined in another one of the subtitle information segments identified as the text data using an identifier, wherein the other one of the subtitle information segments identified as the graphic data is multiplexed with the main AV data into a file. | 1. A non-transitory computer readable medium having an executable data structure for managing reproduction of text subtitle data by a reproducing apparatus, comprising: an area storing at least one main AV data and a plurality of subtitle information segments, each one of the subtitle information segments being represented by a single PES packet of transport packets which includes a packet identifier for identifying a type of packet, wherein each one of the subtitle information segments includes a segment identifier identifying the subtitle information segment as one of text data and graphic data, wherein one of the subtitle information segments identified as the text data includes at most two text subtitle regions, and each text subtitle region is linked to at least one style information defined in another one of the subtitle information segments identified as the text data using an identifier, wherein the other one of the subtitle information segments identified as the graphic data is multiplexed with the main AV data into a file. 2. The non-transitory computer readable medium of claim 1 , wherein a first subtitle information segment among the plurality of subtitle information segments identified as the text data includes a palette identifier identifying palette information for controlling color attributes of the subtitle area. | 0.535503 |
1. A method of propagating annotations among related data objects present in discrete data sources available on an enterprise network running an annotation system, comprising: receiving a request to find annotations related to data objects in a first data source; identifying a plurality of candidate data objects contained in the first data source; identifying a set of annotations created for the candidate data objects in other data sources; providing an indication of which candidate data objects have annotations that have been created in other data sources; displaying, to a user, at least one annotation from the identified set of annotations created for a first data object contained in the first data source and a data object related to the first data object; and providing the user with an option to associate the at least one annotation with the first data object. | 1. A method of propagating annotations among related data objects present in discrete data sources available on an enterprise network running an annotation system, comprising: receiving a request to find annotations related to data objects in a first data source; identifying a plurality of candidate data objects contained in the first data source; identifying a set of annotations created for the candidate data objects in other data sources; providing an indication of which candidate data objects have annotations that have been created in other data sources; displaying, to a user, at least one annotation from the identified set of annotations created for a first data object contained in the first data source and a data object related to the first data object; and providing the user with an option to associate the at least one annotation with the first data object. 5. The method of claim 1 , wherein identifying a plurality of candidate data objects comprises parsing the first data source to identify key terms present in the first data source that are likely to be annotated in other data sources available on the network. | 0.543951 |
11. The method of claim 10, further comprising the step of: providing a recorded script which is associated with said figure. | 11. The method of claim 10, further comprising the step of: providing a recorded script which is associated with said figure. 13. The method of claim 11, wherein the step of providing said recorded script comprises: providing a written script which is associated with said figure; and dictating said written script into a recording apparatus so as to form said recorded script. | 0.855835 |
4. The method of claim 1 , further comprising calculating a transcription quality score from the at least one conformity ratio. | 4. The method of claim 1 , further comprising calculating a transcription quality score from the at least one conformity ratio. 6. The method of claim 4 , further comprising producing an indication of the of the transcription quality score. | 0.955921 |
43. A system comprising: a server 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: receiving, first endorsement information characterizing a first member's rating of a first local product or service provider, wherein the first member is in a member network and is provided with a financial incentive to endorse the first local product or service provider; receiving, from a second member in the member network, a local search query comprising information identifying one or more items to be found and a geographic locale to be searched; identifying, using a member network engine available to the server, that there is an association between the first member and the second member, wherein the association comprises an explicit relationship between the first member and the second member or a common membership of the first member and the second member in a community of the member network, wherein the first member is explicitly related to at least one other member in the member network; ranking items responsive to the local search query based on a type of the association between the second member and the first member in the member network; and responding, to the local search query with information describing a result set responsive to the local search query, the response set including the ranked items. | 43. A system comprising: a server 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: receiving, first endorsement information characterizing a first member's rating of a first local product or service provider, wherein the first member is in a member network and is provided with a financial incentive to endorse the first local product or service provider; receiving, from a second member in the member network, a local search query comprising information identifying one or more items to be found and a geographic locale to be searched; identifying, using a member network engine available to the server, that there is an association between the first member and the second member, wherein the association comprises an explicit relationship between the first member and the second member or a common membership of the first member and the second member in a community of the member network, wherein the first member is explicitly related to at least one other member in the member network; ranking items responsive to the local search query based on a type of the association between the second member and the first member in the member network; and responding, to the local search query with information describing a result set responsive to the local search query, the response set including the ranked items. 47. The system of claim 43 , wherein the first endorsement information comprises: a category suited for classifying local search queries; an identifier of the first local product or service provider in the category; and a rating of the first local product or service provider. | 0.768732 |
1. A computer-implemented method comprising: obtaining a candidate transcription that an automated speech recognizer generates for an utterance; determining a particular context associated with the utterance; obtaining a context profile associated with the particular context, wherein the context profile specifies (i) one or more n-grams, and, (ii) for each of the one more n-grams, a value that reflects an extent to which the candidate transcription includes the n-gram specified in the context profile; determining that a particular n-gram that is included in the candidate transcription is included among a set of undesirable n-grams that is associated with the context; adjusting a speech recognition confidence score associated with the transcription based on determining that the particular n-gram that is included in the candidate transcription is included among the set of undesirable n-grams that is associated with the context, wherein adjusting the speech recognition confidence score associated with the transcription comprises multiplying a value representing the speech recognition confidence score and the value that reflects an extent to which the candidate transcription includes the n-gram specified in the context profile; and determining whether to provide the candidate transcription for output based at least on the adjusted speech recognition confidence score. | 1. A computer-implemented method comprising: obtaining a candidate transcription that an automated speech recognizer generates for an utterance; determining a particular context associated with the utterance; obtaining a context profile associated with the particular context, wherein the context profile specifies (i) one or more n-grams, and, (ii) for each of the one more n-grams, a value that reflects an extent to which the candidate transcription includes the n-gram specified in the context profile; determining that a particular n-gram that is included in the candidate transcription is included among a set of undesirable n-grams that is associated with the context; adjusting a speech recognition confidence score associated with the transcription based on determining that the particular n-gram that is included in the candidate transcription is included among the set of undesirable n-grams that is associated with the context, wherein adjusting the speech recognition confidence score associated with the transcription comprises multiplying a value representing the speech recognition confidence score and the value that reflects an extent to which the candidate transcription includes the n-gram specified in the context profile; and determining whether to provide the candidate transcription for output based at least on the adjusted speech recognition confidence score. 2. The method of claim 1 , wherein the set of undesirable n-grams includes common incorrect phrases associated with the particular context associated with the utterance. | 0.942334 |
13. At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform a method comprising acts of: (A) obtaining language data comprising training data and associated values for one or more metadata attributes, the language data comprising a plurality of instances of language data, an instance of language data comprising an instance of training data and one or more metadata attribute values associated with the instance of training data; (B) identifying, by processing the language data, a set of one or more of the metadata attributes to use for clustering the instances of training data, the set of metadata attributes comprising a first set of metadata attributes and a second set of metadata attributes; (C) clustering, using an automated clustering technique, the training data instances based on their respective values for the first set of metadata attributes into a first plurality of clusters; (D) generating a basis language model for each of the first plurality of clusters to obtain a plurality of basis language models and storing the plurality of basis language models in at least one computer hardware memory; (E) clustering the training data instances based on their respective values for the second set of metadata attributes into a second plurality of clusters different from the first plurality of clusters, the second plurality of clusters comprising a first cluster of training data instances and a second cluster of training data instances; (F) generating a language model for each of the second plurality of clusters as a respective mixture of the plurality of basis language models at least in part by: generating a first language model for the first cluster of training data instances as a first mixture of basis language models in the plurality of basis language models, the first mixture of basis language models comprising at least a first basis language model weighted by a first mixture weight and a second basis language model weighted by a second mixture weight, wherein generating the first language model comprises using an expectation-maximization technique to estimate the first mixture weight and the second mixture weight using data in the first cluster of training data instances; and generating a second language model for the second cluster of training data instances as a second mixture of basis language models in the plurality of basis language models by estimating mixture weights of basis language models in the second mixture using data in the second cluster of training data instances; and (G) receiving a voice utterance and recognizing the voice utterance using the generated first language model to obtain text corresponding to the voice utterance. | 13. At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform a method comprising acts of: (A) obtaining language data comprising training data and associated values for one or more metadata attributes, the language data comprising a plurality of instances of language data, an instance of language data comprising an instance of training data and one or more metadata attribute values associated with the instance of training data; (B) identifying, by processing the language data, a set of one or more of the metadata attributes to use for clustering the instances of training data, the set of metadata attributes comprising a first set of metadata attributes and a second set of metadata attributes; (C) clustering, using an automated clustering technique, the training data instances based on their respective values for the first set of metadata attributes into a first plurality of clusters; (D) generating a basis language model for each of the first plurality of clusters to obtain a plurality of basis language models and storing the plurality of basis language models in at least one computer hardware memory; (E) clustering the training data instances based on their respective values for the second set of metadata attributes into a second plurality of clusters different from the first plurality of clusters, the second plurality of clusters comprising a first cluster of training data instances and a second cluster of training data instances; (F) generating a language model for each of the second plurality of clusters as a respective mixture of the plurality of basis language models at least in part by: generating a first language model for the first cluster of training data instances as a first mixture of basis language models in the plurality of basis language models, the first mixture of basis language models comprising at least a first basis language model weighted by a first mixture weight and a second basis language model weighted by a second mixture weight, wherein generating the first language model comprises using an expectation-maximization technique to estimate the first mixture weight and the second mixture weight using data in the first cluster of training data instances; and generating a second language model for the second cluster of training data instances as a second mixture of basis language models in the plurality of basis language models by estimating mixture weights of basis language models in the second mixture using data in the second cluster of training data instances; and (G) receiving a voice utterance and recognizing the voice utterance using the generated first language model to obtain text corresponding to the voice utterance. 14. The at least one non-transitory computer-readable storage medium of claim 13 , wherein the one or more metadata attributes comprise a plurality of metadata attributes, wherein the act (B) comprises: automatically evaluating multiple of the plurality of metadata attributes, the automatically evaluating a first of the multiple metadata attributes comprising generating at least one language model for at least one group of training data instances obtained by dividing the training data instances based on their respective values for the first metadata attribute; and identifying the set of metadata attributes based on results of the evaluation. | 0.5 |
6. The Boolean search formula generation apparatus according to claim 1 , wherein the search result acquisition unit acquires a weighting factor of each document in the search results searched using the search products as a search condition, and the Boolean search formula generation unit uses the weighting factor to calculate at least one of the recall and the precision. | 6. The Boolean search formula generation apparatus according to claim 1 , wherein the search result acquisition unit acquires a weighting factor of each document in the search results searched using the search products as a search condition, and the Boolean search formula generation unit uses the weighting factor to calculate at least one of the recall and the precision. 7. The Boolean search formula generation apparatus according to claim 6 , wherein the Boolean search formula generation unit treats a minimum weighting factor among the weighting factors of the documents included in the base set as a weighting factor of document not included in the base set to approximate the precision of the search products. | 0.911617 |
6. The computer-implemented method of claim 5 further comprising generating the probability score for each of the plurality of alignments using a translation corpus and a machine learning routine. | 6. The computer-implemented method of claim 5 further comprising generating the probability score for each of the plurality of alignments using a translation corpus and a machine learning routine. 7. The computer-implemented method of claim 6 further comprising selecting the one of the plurality of alignments as the selected alignment based on the plurality of probability scores. | 0.938632 |
69. A method comprising the steps of: a) generating a display including a display portion with a view of a scanned document within a browser of a client device based on document data derived from a scan of a document in print form; b) inputting predetermined index data into at least one field of an index field portion of the display within the browser of the client device, the index field portion defined in the display within the browser separately from the display portion; c) generating a send data signal from within the browser of the client device using a control element of a control portion defined separately from the index field portion and the display portion in the display within the browser; d) transmitting the document data and index data from the client device to the server over an internetwork with the control element of the control portion using a destination address of a server identified in an address field of the browser in response to the send data signal generated in said step (c); e) receiving the document data and index data at the server; and f) storing the document data in association with the index data received from the server in a database of a data storage unit separate from the server. | 69. A method comprising the steps of: a) generating a display including a display portion with a view of a scanned document within a browser of a client device based on document data derived from a scan of a document in print form; b) inputting predetermined index data into at least one field of an index field portion of the display within the browser of the client device, the index field portion defined in the display within the browser separately from the display portion; c) generating a send data signal from within the browser of the client device using a control element of a control portion defined separately from the index field portion and the display portion in the display within the browser; d) transmitting the document data and index data from the client device to the server over an internetwork with the control element of the control portion using a destination address of a server identified in an address field of the browser in response to the send data signal generated in said step (c); e) receiving the document data and index data at the server; and f) storing the document data in association with the index data received from the server in a database of a data storage unit separate from the server. 70. A method as claimed in claim 69 wherein the display of the scanned document is included in a hypertext mark-up language (HTML) document displayed by the browser of the client device's user interface. | 0.710526 |
1. A method for aspect categorization comprising: receiving an input text sequence; providing for identifying aspect terms in the input text sequence; providing for identifying sentiment phrases in the input text sequence; for an identified aspect term: providing for identifying sentiment dependencies in which the aspect term is in a syntactic dependency with one of the identified sentiment phrases, and from a dependency graph of the input text sequence, the dependency graph comprising a sequence of nodes, providing for identifying pseudo-dependencies in which a node representing the aspect term precedes or follows a node representing a semantic anchor in the dependency graph without an intervening other aspect term; extracting features from at least one of identified sentiment dependencies and identified pseudo-dependencies; with a classifier trained to output at least one of category labels and polarity labels for aspect terms, classifying the identified aspect term based on the extracted features; and outputting information based on the classification. | 1. A method for aspect categorization comprising: receiving an input text sequence; providing for identifying aspect terms in the input text sequence; providing for identifying sentiment phrases in the input text sequence; for an identified aspect term: providing for identifying sentiment dependencies in which the aspect term is in a syntactic dependency with one of the identified sentiment phrases, and from a dependency graph of the input text sequence, the dependency graph comprising a sequence of nodes, providing for identifying pseudo-dependencies in which a node representing the aspect term precedes or follows a node representing a semantic anchor in the dependency graph without an intervening other aspect term; extracting features from at least one of identified sentiment dependencies and identified pseudo-dependencies; with a classifier trained to output at least one of category labels and polarity labels for aspect terms, classifying the identified aspect term based on the extracted features; and outputting information based on the classification. 17. A system comprising memory which stores instructions for performing the method of claim 1 and a processor in communication with the memory which executes the instructions. | 0.568013 |
15. A computer storage medium encoded with instructions that, when executed by a user device, cause the user device to perform operations comprising: receiving a plurality of unstructured textual datasets that each include information about a respective potential security threat; determining that a first subset of the plurality of unstructured textual datasets and a second, different subset of the plurality of unstructured textual datasets both comprise information about a particular threat, the second, different subset being a different subset than the first subset; discarding the first subset in response to determining that the first subset of the plurality of unstructured textual datasets and the second, different subset of the plurality of unstructured textual datasets both comprise information about the particular threat; for each respective subset in the plurality of unstructured textual datasets that has not been discarded: identifying one or more keywords in the respective subset; determining one or more patterns included in the respective subset using the identified one or more keywords; identifying one or more intelligence types that correspond with the respective subset using the one or more patterns; and associating, for each respective intelligence type of the identified one or more intelligence types, the respective subset from the plurality of unstructured textual datasets with the respective intelligence type; determining a rule for a third party that indicates that the third party should receive data associated with a particular intelligence type of the one or more intelligence types; determining that the second subset of the plurality of unstructured textual datasets is associated with the particular intelligence type; and providing the second subset of the plurality of unstructured textual datasets that is associated with the particular intelligence type to the third party. | 15. A computer storage medium encoded with instructions that, when executed by a user device, cause the user device to perform operations comprising: receiving a plurality of unstructured textual datasets that each include information about a respective potential security threat; determining that a first subset of the plurality of unstructured textual datasets and a second, different subset of the plurality of unstructured textual datasets both comprise information about a particular threat, the second, different subset being a different subset than the first subset; discarding the first subset in response to determining that the first subset of the plurality of unstructured textual datasets and the second, different subset of the plurality of unstructured textual datasets both comprise information about the particular threat; for each respective subset in the plurality of unstructured textual datasets that has not been discarded: identifying one or more keywords in the respective subset; determining one or more patterns included in the respective subset using the identified one or more keywords; identifying one or more intelligence types that correspond with the respective subset using the one or more patterns; and associating, for each respective intelligence type of the identified one or more intelligence types, the respective subset from the plurality of unstructured textual datasets with the respective intelligence type; determining a rule for a third party that indicates that the third party should receive data associated with a particular intelligence type of the one or more intelligence types; determining that the second subset of the plurality of unstructured textual datasets is associated with the particular intelligence type; and providing the second subset of the plurality of unstructured textual datasets that is associated with the particular intelligence type to the third party. 19. The computer storage medium of claim 15 , wherein identifying the one or more intelligence types that correspond with the respective subset using the one or more patterns comprises: determining one or more rules using the one or more patterns; and identifying the one or more intelligence types that correspond with the respective subset using the one or more rules. | 0.637428 |
1. An artificial intelligence system comprising: a storage device comprising a terminology database that stores (i) a plurality of terms utilized in a previous communication by a human user requesting a product and/or a service in a first spoken language, (ii) a plurality of responses in a second spoken language to the previous communication, and (iii) a plurality of outcomes that indicate accuracy of a correspondence between the plurality of responses in the second spoken language and the plurality of terms in the first spoken language, the second spoken language being distinct from the first spoken language; and a processor that (i) learns to generate responses associated with corresponding terms in a request based upon a statistical probability analysis of the plurality of outcomes from the terminology database, (ii) receives a request for a product and/or service in the first spoken language in a current communication in which a human language interpreter is not available, (iii) selects a phrase in the first spoken language from the terminology database based on an occurrence of a term in the first spoken language in the request and a substantial probability of the phrase provided in the first spoken language in conjunction with the term in the first spoken language eliciting particular follow-up data from the human user, (iv) provides the phrase in the second spoken language to an entity representative that participates in the current communication, (v) generates a response to the human user in the first spoken language to obtain the particular follow-up data from the human user in the first spoken language to facilitate ordering the product and/or service, (vi) provides the particular follow-up data received from the user in the second spoken language to the entity representative for the entity representative to order the product and/or service, and (vii) auto-populates at least one question for a requestor of the product and/or the service in the first spoken language and sends the at least one question to the requestor. | 1. An artificial intelligence system comprising: a storage device comprising a terminology database that stores (i) a plurality of terms utilized in a previous communication by a human user requesting a product and/or a service in a first spoken language, (ii) a plurality of responses in a second spoken language to the previous communication, and (iii) a plurality of outcomes that indicate accuracy of a correspondence between the plurality of responses in the second spoken language and the plurality of terms in the first spoken language, the second spoken language being distinct from the first spoken language; and a processor that (i) learns to generate responses associated with corresponding terms in a request based upon a statistical probability analysis of the plurality of outcomes from the terminology database, (ii) receives a request for a product and/or service in the first spoken language in a current communication in which a human language interpreter is not available, (iii) selects a phrase in the first spoken language from the terminology database based on an occurrence of a term in the first spoken language in the request and a substantial probability of the phrase provided in the first spoken language in conjunction with the term in the first spoken language eliciting particular follow-up data from the human user, (iv) provides the phrase in the second spoken language to an entity representative that participates in the current communication, (v) generates a response to the human user in the first spoken language to obtain the particular follow-up data from the human user in the first spoken language to facilitate ordering the product and/or service, (vi) provides the particular follow-up data received from the user in the second spoken language to the entity representative for the entity representative to order the product and/or service, and (vii) auto-populates at least one question for a requestor of the product and/or the service in the first spoken language and sends the at least one question to the requestor. 6. The artificial intelligence system of claim 1 , wherein the product and/or the service are associated with an emergency response system. | 0.57384 |
1. A non-transitory computer-readable medium comprising program code to be executed by a processor, the program code comprising: program code for receiving a first display element, the first display element defined at least in part according to a first style attribute defined in a style sheet language; program code for receiving a second display element, the second display element defined at least in part according to a second style attribute defined in the style sheet language; program code for receiving a first relationship between the first display element and the second display element; program code for automatically generating a modified second style attribute in the style sheet language, the modified second style sheet attribute based on the first style attribute and the first relationship; program code for storing the modified second style attribute in the style sheet language document; program code for receiving a third display element, the third display element defined at least in part according to a third style attribute defined in a style sheet language; program code for receiving a second relationship between the first display element and the third display element; program code for automatically generating a modified third style attribute in the style sheet language, the modified third style sheet attribute based on the first style attribute and the second; and program code for storing the modified third style attribute in the style sheet language document, wherein at least one of the first or the second relationship comprises a spatial relationship or a size relationship, and wherein at least one of the first or the second relationship is dynamic. | 1. A non-transitory computer-readable medium comprising program code to be executed by a processor, the program code comprising: program code for receiving a first display element, the first display element defined at least in part according to a first style attribute defined in a style sheet language; program code for receiving a second display element, the second display element defined at least in part according to a second style attribute defined in the style sheet language; program code for receiving a first relationship between the first display element and the second display element; program code for automatically generating a modified second style attribute in the style sheet language, the modified second style sheet attribute based on the first style attribute and the first relationship; program code for storing the modified second style attribute in the style sheet language document; program code for receiving a third display element, the third display element defined at least in part according to a third style attribute defined in a style sheet language; program code for receiving a second relationship between the first display element and the third display element; program code for automatically generating a modified third style attribute in the style sheet language, the modified third style sheet attribute based on the first style attribute and the second; and program code for storing the modified third style attribute in the style sheet language document, wherein at least one of the first or the second relationship comprises a spatial relationship or a size relationship, and wherein at least one of the first or the second relationship is dynamic. 4. The non-transitory computer-readable medium of claim 1 , further comprising program code for storing the relationship in the style sheet language document. | 0.683993 |
2. The method of claim 1 , further comprising outputting a set of selectable multiple choice answers selectable for responding to the output question. | 2. The method of claim 1 , further comprising outputting a set of selectable multiple choice answers selectable for responding to the output question. 3. The method of claim 2 , wherein the set of multiple choice answers is a set of text strings, each including one or more words, which are alternatively selectable by the user for answering the generated question. | 0.875253 |
26. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps for verifying a user identity, the method steps comprising: receiving multi-modal inputs from a user interacting with a conversational system during a user session and transforming the received multi-modal inputs into formal commands executable by the machine; extracting features from the multi-modal inputs and formal commands, wherein the extracted features include a combination of input modalities representative of the user's current interaction behavior for performing a task during the user session; and comparing the combination of input modalities representative of the user's current interaction behavior for performing the task to a behavior model representative of the user's past interaction behavior comprising a known combination of input modalities for performing the task used by the user during one or more previous user sessions to determine the identity of the user. | 26. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps for verifying a user identity, the method steps comprising: receiving multi-modal inputs from a user interacting with a conversational system during a user session and transforming the received multi-modal inputs into formal commands executable by the machine; extracting features from the multi-modal inputs and formal commands, wherein the extracted features include a combination of input modalities representative of the user's current interaction behavior for performing a task during the user session; and comparing the combination of input modalities representative of the user's current interaction behavior for performing the task to a behavior model representative of the user's past interaction behavior comprising a known combination of input modalities for performing the task used by the user during one or more previous user sessions to determine the identity of the user. 37. The program storage device as recited in claim 26 , wherein the extracted features include features representative of a dialog state between the user and the system. | 0.572785 |
27. A non-transitory computer-readable medium comprising computer program instructions executable by a computer processor to perform a method, the method comprising: (A) converting a plurality of atomic tuples, representing a plurality of cells stored in a grid, into a plurality of schema tuples, the method comprising: (A) (1) assigning a plurality of logical types to theplurality of atomic tuples; (A) (2) assigning a role of locator to a first subset of the plurality of cells based on the plurality of logical types; (A) (3) extracting from the plurality of atomic tuples a locator tuple slice, wherein the locator tuple slice comprises a plurality of locator tuples corresponding to a plurality of contiguous cells, from the plurality of cells, having the role of locator and forming a 1XN shape within the grid; (A) (4) determining, based on values of at least some of the plurality of contiguous cells, whether any empty cells in the plurality of contiguous cells implicitly contain missing values; (A) (5) if any of the empty cells are determined to implicitly contain missing values, then storing the missing values of the locator tuples of the locator tuple slice corresponding to the cells which are determined to implicitly contain missing values; and (A) (6) converting the plurality of locator tuples into a plurality of logical schema tuples corresponding to the plurality of locator tuples, wherein each of the plurality of logical schema tuples comprises a type of the corresponding locator tuple and a value of the corresponding locator tuple. | 27. A non-transitory computer-readable medium comprising computer program instructions executable by a computer processor to perform a method, the method comprising: (A) converting a plurality of atomic tuples, representing a plurality of cells stored in a grid, into a plurality of schema tuples, the method comprising: (A) (1) assigning a plurality of logical types to theplurality of atomic tuples; (A) (2) assigning a role of locator to a first subset of the plurality of cells based on the plurality of logical types; (A) (3) extracting from the plurality of atomic tuples a locator tuple slice, wherein the locator tuple slice comprises a plurality of locator tuples corresponding to a plurality of contiguous cells, from the plurality of cells, having the role of locator and forming a 1XN shape within the grid; (A) (4) determining, based on values of at least some of the plurality of contiguous cells, whether any empty cells in the plurality of contiguous cells implicitly contain missing values; (A) (5) if any of the empty cells are determined to implicitly contain missing values, then storing the missing values of the locator tuples of the locator tuple slice corresponding to the cells which are determined to implicitly contain missing values; and (A) (6) converting the plurality of locator tuples into a plurality of logical schema tuples corresponding to the plurality of locator tuples, wherein each of the plurality of logical schema tuples comprises a type of the corresponding locator tuple and a value of the corresponding locator tuple. 33. The computer-readable medium of claim 27 , wherein the method further comprises: (B) identifying a second subset of the plurality of cells, wherein the second subset contains a plurality of values of a plurality of logical types; (C) identifying a third subset of the plurality of cells, wherein the third subset contains a plurality of names of the plurality of values in the second subset, wherein the third subset and the second subset are disjoint. | 0.503561 |
25. A method comprising: matching primary data generated from fingerprint data from at least one of a television and a mobile device with targeted data based on a relevancy factor using a relevancy-matching server in accordance with looking in a data repository for at least one of a matching item and a related item, the relevancy factor comprising at least one of a category of the primary data, a behavioral history of a user, a category of a sandboxed application of the mobile device, and other information associated with the user; looking in the data repository for at least one of the targeted data, a reference to the targeted data and a metadata of the targeted data using the relevancy-matching server; generating the fingerprint data from characteristic features of media data on the television, wherein the primary data is any one of a content identification data and a content identification history; associating the mobile device with the television based on: executing a sandbox-reachable service on the television; automatically announcing, through the television, the sandbox-reachable service to a discovery module executing at least one of: on a pairing server external to the mobile device and as part of an extension of a security sandbox executing on the mobile device, the security sandbox constraining an executable environment for the sandboxed application therein; identifying the sandbox-reachable service offered through the television based on receiving, through the discovery module, the automatic announcement to enable the sandboxed application of the mobile device reach the sandbox-reachable service by communicating an identification data of the television via the sandbox-reachable service when a shared computer network is determined to be commonly associated with the mobile device and the television; and establishing bidirectional communication between the mobile device and the television based on the sandboxed application reaching the sandbox-reachable service to render the primary data available across the sandbox-reachable service and the sandboxed application; processing the fingerprint data through a content identification server; and communicating the primary data from the fingerprint data to any of a number of devices with an access to at least one of: the identification data of the television and an identification data of an automatic content identification service of the television through the content identification server. | 25. A method comprising: matching primary data generated from fingerprint data from at least one of a television and a mobile device with targeted data based on a relevancy factor using a relevancy-matching server in accordance with looking in a data repository for at least one of a matching item and a related item, the relevancy factor comprising at least one of a category of the primary data, a behavioral history of a user, a category of a sandboxed application of the mobile device, and other information associated with the user; looking in the data repository for at least one of the targeted data, a reference to the targeted data and a metadata of the targeted data using the relevancy-matching server; generating the fingerprint data from characteristic features of media data on the television, wherein the primary data is any one of a content identification data and a content identification history; associating the mobile device with the television based on: executing a sandbox-reachable service on the television; automatically announcing, through the television, the sandbox-reachable service to a discovery module executing at least one of: on a pairing server external to the mobile device and as part of an extension of a security sandbox executing on the mobile device, the security sandbox constraining an executable environment for the sandboxed application therein; identifying the sandbox-reachable service offered through the television based on receiving, through the discovery module, the automatic announcement to enable the sandboxed application of the mobile device reach the sandbox-reachable service by communicating an identification data of the television via the sandbox-reachable service when a shared computer network is determined to be commonly associated with the mobile device and the television; and establishing bidirectional communication between the mobile device and the television based on the sandboxed application reaching the sandbox-reachable service to render the primary data available across the sandbox-reachable service and the sandboxed application; processing the fingerprint data through a content identification server; and communicating the primary data from the fingerprint data to any of a number of devices with an access to at least one of: the identification data of the television and an identification data of an automatic content identification service of the television through the content identification server. 26. The method of claim 25 , further comprising: processing, through the sandboxed application of the mobile device an embedded object comprising at least one of a script, an image, a player, an iframe, and other external media included in the sandboxed application. | 0.580857 |
6. A method according to claim 1 , wherein the method further comprises: analyzing the entries in the first metadata object to derive attributes relevant for search, wherein identifying the matching documents comprises: using the attributes to identify the matching documents, and wherein said analyzing of the entries in the first metadata object comprises: analyzing free text and explicit attributes of the first metadata object to derive the attributes. | 6. A method according to claim 1 , wherein the method further comprises: analyzing the entries in the first metadata object to derive attributes relevant for search, wherein identifying the matching documents comprises: using the attributes to identify the matching documents, and wherein said analyzing of the entries in the first metadata object comprises: analyzing free text and explicit attributes of the first metadata object to derive the attributes. 7. A method according to claim 6 , further comprising: ranking the matching documents responsive to the metadata in metadata objects associated with the matching documents, wherein the ranking of the given document is boosted based on an amount of viewing and editing activity in the first metadata object, a number of recent entries in the first metadata object, a number of explicit positive endorsements of the given document, or a sentiment score for the given document, wherein the sentiment score for the given document is derived from the free text of the first metadata object. | 0.811828 |
15. A non-transitory computer-readable medium for customizing content, the non-transitory computer-readable medium having a computer-executable component configured to: receive a request from a computing device including a processor to customize an original narration; select a narration settings file from an electronic data store configured to store a plurality of narration settings files, wherein the narration settings file comprises at least one narration parameter; receive at least one modification to the at least one narration parameter, wherein the at least one modification is specified through a user interface displayed on the computing device; from an updated narration settings file comprising at least one modified narration parameter, wherein the at least one modified narration parameter comprises the at least one narration parameter as modified in accordance with the at least one modification; modify the original narration in accordance with the updated narration settings file in order to form a modified narration for the item of content; and store the updated narration settings file to the electronic data store. | 15. A non-transitory computer-readable medium for customizing content, the non-transitory computer-readable medium having a computer-executable component configured to: receive a request from a computing device including a processor to customize an original narration; select a narration settings file from an electronic data store configured to store a plurality of narration settings files, wherein the narration settings file comprises at least one narration parameter; receive at least one modification to the at least one narration parameter, wherein the at least one modification is specified through a user interface displayed on the computing device; from an updated narration settings file comprising at least one modified narration parameter, wherein the at least one modified narration parameter comprises the at least one narration parameter as modified in accordance with the at least one modification; modify the original narration in accordance with the updated narration settings file in order to form a modified narration for the item of content; and store the updated narration settings file to the electronic data store. 20. The non-transitory computer-readable medium of claim 15 , wherein the computer-executable component is further configured to select the narration settings file from the electronic data store based at least in part on user input made through the computing device. | 0.714051 |
1. A conference system, comprising: a recognition section for recognizing speech in a first language; a translation section for translating a recognition result recognized by the recognition section into a second language different from the first language; a generation section for generating a translation subtitle for displaying a translation result translated by the translation section and the recognition result corresponding to the translation result in parallel, and a recognition result subtitle for displaying the recognition result that has not been translated by the translation section; and a display section for displaying the translation subtitle and the recognition result subtitle generated by the generation section, wherein the recognition section recognizes the speech in the first language at least twice, the conference system further comprising: a recognition determination section for determining whether or not a recognition result obtained in the first recognition by the recognition section should be replaced with a recognition result obtained in the second or later recognition; and an area determination section for determining, when it is determined by the recognition determination section that the recognition result obtained in the first recognition should be replaced, whether or not a displayable area capable of displaying a replace portion of the recognition result obtained in the second or later recognition is generated in the translation subtitle by erasing a replaced portion of the recognition result obtained in the first recognition in the translation subtitle displayed in the display section, wherein the generation section corrects, when it is determined by the recognition determination section that the recognition result obtained in the first recognition should be replaced, the translation subtitle to a translation subtitle in which the recognition result obtained in the second or later recognition and a translation result translated from the recognition result obtained in the second or later recognition by the translation section are displayed, wherein the display section includes: an erase section for erasing the replaced portion when it is determined by the recognition determination section that the recognition result obtained in the first recognition should be replaced; a scroll display section for scrolling, when it is determined by the area determination section that a displayable area is not generated, a portion of the translation subtitle following the replaced portion in a direction toward an end for providing the displayable area; and a replace portion display section for displaying the replace portion in the displayable area. | 1. A conference system, comprising: a recognition section for recognizing speech in a first language; a translation section for translating a recognition result recognized by the recognition section into a second language different from the first language; a generation section for generating a translation subtitle for displaying a translation result translated by the translation section and the recognition result corresponding to the translation result in parallel, and a recognition result subtitle for displaying the recognition result that has not been translated by the translation section; and a display section for displaying the translation subtitle and the recognition result subtitle generated by the generation section, wherein the recognition section recognizes the speech in the first language at least twice, the conference system further comprising: a recognition determination section for determining whether or not a recognition result obtained in the first recognition by the recognition section should be replaced with a recognition result obtained in the second or later recognition; and an area determination section for determining, when it is determined by the recognition determination section that the recognition result obtained in the first recognition should be replaced, whether or not a displayable area capable of displaying a replace portion of the recognition result obtained in the second or later recognition is generated in the translation subtitle by erasing a replaced portion of the recognition result obtained in the first recognition in the translation subtitle displayed in the display section, wherein the generation section corrects, when it is determined by the recognition determination section that the recognition result obtained in the first recognition should be replaced, the translation subtitle to a translation subtitle in which the recognition result obtained in the second or later recognition and a translation result translated from the recognition result obtained in the second or later recognition by the translation section are displayed, wherein the display section includes: an erase section for erasing the replaced portion when it is determined by the recognition determination section that the recognition result obtained in the first recognition should be replaced; a scroll display section for scrolling, when it is determined by the area determination section that a displayable area is not generated, a portion of the translation subtitle following the replaced portion in a direction toward an end for providing the displayable area; and a replace portion display section for displaying the replace portion in the displayable area. 2. The conference system according to claim 1 , wherein each word or each phrase included in the recognition result is displayed in the translation subtitle in parallel to an expression included in the translation result and corresponding to the word or the phrase. | 0.810271 |
1. A computer-implemented method for generating a search term comprising: in a computer system: a. defining a profile based on a selection made by a user; b. getting a text object, wherein the text object contains a plurality of text items, at least one of the plurality of text items comprising a text item pointed to by a Universal Resource Locator (URL); c. selecting at least one, but not all of the text items based on the profile; d. parsing only the selected text items to generate the search term; and e. creating a search based on the search term and a selection of a search engine made by the user. | 1. A computer-implemented method for generating a search term comprising: in a computer system: a. defining a profile based on a selection made by a user; b. getting a text object, wherein the text object contains a plurality of text items, at least one of the plurality of text items comprising a text item pointed to by a Universal Resource Locator (URL); c. selecting at least one, but not all of the text items based on the profile; d. parsing only the selected text items to generate the search term; and e. creating a search based on the search term and a selection of a search engine made by the user. 4. The method of claim 1 , wherein at least one of the plurality of text items is selected from the group comprising: changed text, text changed by a specific person, and only unchanged text. | 0.680412 |
8. A system for managing data, comprising: a network computer, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: instantiating an attributes engine to perform further actions, including: analyzing one or more characteristics of one or more model object features of a plurality of model objects; classifying the one or more model object features based on the one or more characteristics, wherein the one or more characteristics include a data type and one or more values of the one or more model object features; and associating one or more similarity tasks with the one or more model object features based on their classification; and instantiating a similarity engine to perform further actions, including: providing a similarity model that includes the one or more similarity tasks; employing the similarity model to provide one or more candidate similarity scores based on one or more exemplar model objects that are labeled as being similar, wherein the one or more exemplar model objects are provided by a similarity client application; modifying the similarity model based on the one or more exemplar model objects and the one or more candidate similarity scores; employing the modified similarity model to provide similarity scores for one or more model objects, wherein providing the similarity scores is based on execution of the one or more similarity tasks that are associated with the one or more model object features of the one or more model objects scores; and identifying two or more similar model objects based on the similarity; and a client computer, comprising: a client computer transceiver that communicates over the network; a client computer memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: employing the similarity client application engine to provide the one or more exemplar model objects in a visual presentation in a display to a user, wherein one or more features of the visual presentation are modified based on geo-location information of the user provided by a global positioning system (GPS) device, and wherein the one or more modified features include one or more of a time zone, language, currency, or calendar format. | 8. A system for managing data, comprising: a network computer, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: instantiating an attributes engine to perform further actions, including: analyzing one or more characteristics of one or more model object features of a plurality of model objects; classifying the one or more model object features based on the one or more characteristics, wherein the one or more characteristics include a data type and one or more values of the one or more model object features; and associating one or more similarity tasks with the one or more model object features based on their classification; and instantiating a similarity engine to perform further actions, including: providing a similarity model that includes the one or more similarity tasks; employing the similarity model to provide one or more candidate similarity scores based on one or more exemplar model objects that are labeled as being similar, wherein the one or more exemplar model objects are provided by a similarity client application; modifying the similarity model based on the one or more exemplar model objects and the one or more candidate similarity scores; employing the modified similarity model to provide similarity scores for one or more model objects, wherein providing the similarity scores is based on execution of the one or more similarity tasks that are associated with the one or more model object features of the one or more model objects scores; and identifying two or more similar model objects based on the similarity; and a client computer, comprising: a client computer transceiver that communicates over the network; a client computer memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: employing the similarity client application engine to provide the one or more exemplar model objects in a visual presentation in a display to a user, wherein one or more features of the visual presentation are modified based on geo-location information of the user provided by a global positioning system (GPS) device, and wherein the one or more modified features include one or more of a time zone, language, currency, or calendar format. 14. The system of claim 8 , wherein the similarity engine performs further actions comprising: associating the modified similarity model with one or more of a user, an organization, or a client; and differently modifying different instances of the similarity model associated with different users, different organizations, or different clients. | 0.599903 |
19. A computer programmed to convert assembly language instructions into object code, the computer comprising: means for receiving invocation of a first macro and a variable as an argument for the first macro; means, coupled to said means for receiving, for automatically identifying a second macro to be invoked to perform, on said variable, an operation identified by the first macro; wherein the first macro and the second macro have different names; and wherein the second macro is defined within said computer to comprise first assembler instructions for use with at least variables of an element type identical to a corresponding type of the variable; means for automatically expanding the second macro, using at least said first assembler instructions to generate second assembler instructions in an assembly language; and means for using an assembler for said assembly language to generate object code, based at least on the second assembler instructions; wherein the second assembler instructions comprise at least one opcode which depends at least on said corresponding type of the variable. | 19. A computer programmed to convert assembly language instructions into object code, the computer comprising: means for receiving invocation of a first macro and a variable as an argument for the first macro; means, coupled to said means for receiving, for automatically identifying a second macro to be invoked to perform, on said variable, an operation identified by the first macro; wherein the first macro and the second macro have different names; and wherein the second macro is defined within said computer to comprise first assembler instructions for use with at least variables of an element type identical to a corresponding type of the variable; means for automatically expanding the second macro, using at least said first assembler instructions to generate second assembler instructions in an assembly language; and means for using an assembler for said assembly language to generate object code, based at least on the second assembler instructions; wherein the second assembler instructions comprise at least one opcode which depends at least on said corresponding type of the variable. 22. The computer of claim 19 further comprising: means for determining a class type of the variable based on said corresponding type; and means for saving the class type. | 0.627158 |
3. The apparatus of claim 2 , wherein the clustering module determines a number of steps between a sequence of hierarchy locations based on a number of symbols between the sequence of hierarchy locations. | 3. The apparatus of claim 2 , wherein the clustering module determines a number of steps between a sequence of hierarchy locations based on a number of symbols between the sequence of hierarchy locations. 4. The apparatus of claim 3 , wherein upon search results belonging to more than one hierarchy location in the hierarchy data structure, the search result with more than one hierarchy location is added to a group having a least number of steps. | 0.923535 |
1. A method in a computerized healthcare system for populating an electronic clinical document, the method comprising: providing an electronic clinical document for a particular patient, the electronic clinical document being capable of receiving dictation audio input, structured user input, free-text input, and system-generated input; receiving dictation audio input into the electronic clinical document, wherein the dictation audio input is audio data; receiving at least one of structured user input, free-text input, and system-generated input into the electronic clinical document; embedding the dictation audio input directly into the electronic clinical document; presenting graphical representations indicative of the embedded dictation audio input in the electronic clinical document; and assigning a dictation audio identifier to each of the graphical representations, wherein the dictation audio identifier associates the dictation audio input with the particular patient, the electronic clinical document, and a location of the dictation audio input within the electronic clinical document. | 1. A method in a computerized healthcare system for populating an electronic clinical document, the method comprising: providing an electronic clinical document for a particular patient, the electronic clinical document being capable of receiving dictation audio input, structured user input, free-text input, and system-generated input; receiving dictation audio input into the electronic clinical document, wherein the dictation audio input is audio data; receiving at least one of structured user input, free-text input, and system-generated input into the electronic clinical document; embedding the dictation audio input directly into the electronic clinical document; presenting graphical representations indicative of the embedded dictation audio input in the electronic clinical document; and assigning a dictation audio identifier to each of the graphical representations, wherein the dictation audio identifier associates the dictation audio input with the particular patient, the electronic clinical document, and a location of the dictation audio input within the electronic clinical document. 8. The method of claim 1 , further comprising receiving a transcribed body of text associated with the dictation audio input. | 0.551628 |
2. The method of claim 1 , further comprising creating a display graph that is a hierarchical representation of the runtime graph. | 2. The method of claim 1 , further comprising creating a display graph that is a hierarchical representation of the runtime graph. 13. The method of claim 2 , wherein the display graph is a depth-limited projection of the runtime graph. | 0.956175 |
1. A computer-implemented method for training acoustic models in an automatic speech recognition system through the selection of acoustic data comprising the steps of: a. training a first acoustic model in the automatic speech recognition system using a training-data corpus comprising a plurality of speech audio files and a respective plurality of transcriptions for the plurality of speech audio files; b. performing a forced Viterbi alignment of the plurality of speech audio files using the trained first acoustic model in the automatic speech recognition system and determining an average frame likelihood score β r for each of the plurality of speech audio files; c. calculating a global frame likelihood score δ for the plurality of speech audio files, wherein the global frame likelihood score δ comprises an average of frame likelihoods over the entire corpus; d. performing a phoneme recognition of the plurality of speech audio files using the trained first acoustic model and the plurality of transcriptions in the automatic speech recognition system; e. calculating a phoneme recognition accuracy γ for each of the plurality of speech audio files and a global phoneme recognition accuracy v for the plurality of speech audio files; f. creating a subset training-data corpus comprising audio files retained from the plurality of speech audio files which meet at least one predetermined criterion indicating that an audio file has good audio quality, the at least one predetermined criterion comprising at least one criterion selected from the group comprising: a first criterion based on the average frame likelihood score β of the retained speech audio file and the global frame likelihood score δ; and a second criterion based on the phoneme recognition accuracy γ of the retained speech audio file and the global phoneme recognition accuracy v; and g. training a second acoustic model in the automatic speech recognition system using the subset training-data corpus. | 1. A computer-implemented method for training acoustic models in an automatic speech recognition system through the selection of acoustic data comprising the steps of: a. training a first acoustic model in the automatic speech recognition system using a training-data corpus comprising a plurality of speech audio files and a respective plurality of transcriptions for the plurality of speech audio files; b. performing a forced Viterbi alignment of the plurality of speech audio files using the trained first acoustic model in the automatic speech recognition system and determining an average frame likelihood score β r for each of the plurality of speech audio files; c. calculating a global frame likelihood score δ for the plurality of speech audio files, wherein the global frame likelihood score δ comprises an average of frame likelihoods over the entire corpus; d. performing a phoneme recognition of the plurality of speech audio files using the trained first acoustic model and the plurality of transcriptions in the automatic speech recognition system; e. calculating a phoneme recognition accuracy γ for each of the plurality of speech audio files and a global phoneme recognition accuracy v for the plurality of speech audio files; f. creating a subset training-data corpus comprising audio files retained from the plurality of speech audio files which meet at least one predetermined criterion indicating that an audio file has good audio quality, the at least one predetermined criterion comprising at least one criterion selected from the group comprising: a first criterion based on the average frame likelihood score β of the retained speech audio file and the global frame likelihood score δ; and a second criterion based on the phoneme recognition accuracy γ of the retained speech audio file and the global phoneme recognition accuracy v; and g. training a second acoustic model in the automatic speech recognition system using the subset training-data corpus. 4. The method of claim 1 , wherein step (b) further comprises: obtaining a total likelihood score α r for each of the plurality of speech audio files. | 0.586614 |
12. The method of claim 10 , wherein said translator classes comprise executable code for performing conversions between XML data and object model data. | 12. The method of claim 10 , wherein said translator classes comprise executable code for performing conversions between XML data and object model data. 13. The method of claim 12 , wherein said translator classes include: a generic translator class, using said mapping information and one or more predetermined default processes to perform said conversions; and a custom translator class, using customized executable code to perform said conversions. | 0.842014 |
14. A computer-readable storage containing instructions for causing a computing device to carry out a method of building a language model, comprising: providing a first language model derived from a first corpus comprising a first set of data files, wherein each of the first set of data files is associated with a different set of text elements; providing a second language model derived from a second corpus different from the first corpus comprising a second set of data files, wherein i) each of the second set of data files is associated with a different set of text elements, ii) each of the data files in the first set of data files corresponds to a respective data file in the second set of data files, and iii) a data file in the first set of data files corresponds to a data file in the second set of data files if the data file in the first set of data files is associated with a similar set of text elements as is associated with the data file in the second set of data files; and merging, in parallel, respective data files in the first set of data files with corresponding data files in the second set of data files, thereby generating a combined language model by merging the first language model with the second language model. | 14. A computer-readable storage containing instructions for causing a computing device to carry out a method of building a language model, comprising: providing a first language model derived from a first corpus comprising a first set of data files, wherein each of the first set of data files is associated with a different set of text elements; providing a second language model derived from a second corpus different from the first corpus comprising a second set of data files, wherein i) each of the second set of data files is associated with a different set of text elements, ii) each of the data files in the first set of data files corresponds to a respective data file in the second set of data files, and iii) a data file in the first set of data files corresponds to a data file in the second set of data files if the data file in the first set of data files is associated with a similar set of text elements as is associated with the data file in the second set of data files; and merging, in parallel, respective data files in the first set of data files with corresponding data files in the second set of data files, thereby generating a combined language model by merging the first language model with the second language model. 15. The computer-readable storage of claim 14 , wherein each of the first set of data files is associated with a set of text elements, and each of the corresponding second set of data files is associated with the same set of text elements. | 0.602732 |
1. A method for activating a cellular phone account utilizing automated speech recognition, comprising: receiving a plurality of user supplied information over a network utilizing automated speech recognition; storing the information in a memory database; and determining if the stored information is sufficient for cellular phone activation, wherein if sufficient, automatically activating the cellular phone account based on the information received utilizing the automated speech recognition, and wherein, if not sufficient, continuing to store the information in the memory database without activating the cellular phone and allowing the user to resume an interrupted activation session without repeating the previously stored information. | 1. A method for activating a cellular phone account utilizing automated speech recognition, comprising: receiving a plurality of user supplied information over a network utilizing automated speech recognition; storing the information in a memory database; and determining if the stored information is sufficient for cellular phone activation, wherein if sufficient, automatically activating the cellular phone account based on the information received utilizing the automated speech recognition, and wherein, if not sufficient, continuing to store the information in the memory database without activating the cellular phone and allowing the user to resume an interrupted activation session without repeating the previously stored information. 20. The method as recited in claim 1 , wherein audible confirmations are conditionally transmitted to the user over the network, based on a confidence score associated with the information received from the user. | 0.840676 |
1. A method of processing a query, comprising: providing a pre-defined logical schema to a user of a database system, wherein the pre-defined logical schema is mapped to at least two relational database entities of different databases storing data therein; receiving a logical query for data stored in the databases from the user, wherein the logical query is written in an object-oriented query language utilizing the pre-defined logical schema, and comprises two or more predicates and an operator specifying an action to take with one or more of the predicates; in response to receiving the logical query, interpreting the logical query using the pre-defined logical schema to determine which of the relational database entities is a subject of the logical query, and which of the relational database entities is associated with each predicate; requesting the database of each determined relational database entity of the logical query to: translate each of the associated predicates of that database in the logical query into a query language specific to that database, wherein at least two different databases translate an associated predicate; and apply an authorization rule with each of the associated predicates of that database in the logical query, wherein the authorization rule identifies unauthorized data: receiving a translated predicate query for each determined predicate of the logical query from its associated database of the relational database entity, wherein each translated predicate query is written in a relational query language specific to the associated database and is a translation of one of the object-oriented predicates in the logical query; combining each translated predicate query received from the databases of the determined relational database entities into a master query using the operator; executing the master query against the databases of the relational database entities that are subjects of the logical query; in response to executing the master query, receiving a query result set from the databases of the relational database entities that are subjects of the logical query; and providing the query result set to the user, wherein the query result set lacks the unauthorized data. | 1. A method of processing a query, comprising: providing a pre-defined logical schema to a user of a database system, wherein the pre-defined logical schema is mapped to at least two relational database entities of different databases storing data therein; receiving a logical query for data stored in the databases from the user, wherein the logical query is written in an object-oriented query language utilizing the pre-defined logical schema, and comprises two or more predicates and an operator specifying an action to take with one or more of the predicates; in response to receiving the logical query, interpreting the logical query using the pre-defined logical schema to determine which of the relational database entities is a subject of the logical query, and which of the relational database entities is associated with each predicate; requesting the database of each determined relational database entity of the logical query to: translate each of the associated predicates of that database in the logical query into a query language specific to that database, wherein at least two different databases translate an associated predicate; and apply an authorization rule with each of the associated predicates of that database in the logical query, wherein the authorization rule identifies unauthorized data: receiving a translated predicate query for each determined predicate of the logical query from its associated database of the relational database entity, wherein each translated predicate query is written in a relational query language specific to the associated database and is a translation of one of the object-oriented predicates in the logical query; combining each translated predicate query received from the databases of the determined relational database entities into a master query using the operator; executing the master query against the databases of the relational database entities that are subjects of the logical query; in response to executing the master query, receiving a query result set from the databases of the relational database entities that are subjects of the logical query; and providing the query result set to the user, wherein the query result set lacks the unauthorized data. 5. The method according to claim 1 , further comprising: saving the logical query in the database system. | 0.937352 |
1. A device comprising: memory for storing data for providing services based upon identification of decision makers associated with communication services, the data comprising a user profile and default template identifying a default decision maker for a service; and a controller for: analyzing policy rules and the stored data; identifying a new decision maker for a particular service based on the analysis of the policy rules and the stored data; providing the services to the identified new decision maker; and determining an order of ownership model for the services selected from a group comprising a single owner, multiple owners with order of priority possibly including veto power for at least some issues, and multiple owners that agree at least on some specified issues. | 1. A device comprising: memory for storing data for providing services based upon identification of decision makers associated with communication services, the data comprising a user profile and default template identifying a default decision maker for a service; and a controller for: analyzing policy rules and the stored data; identifying a new decision maker for a particular service based on the analysis of the policy rules and the stored data; providing the services to the identified new decision maker; and determining an order of ownership model for the services selected from a group comprising a single owner, multiple owners with order of priority possibly including veto power for at least some issues, and multiple owners that agree at least on some specified issues. 6. The device of claim 1 , wherein the controller publishes the new decision maker for the particular service identified by the controller. | 0.876511 |
1. A computer-implemented system for populating clusters of documents, comprising: a presentation module to place a set of clusters in a display in relation to a common origin; a document selection module to select one of a plurality of unclustered documents in the display and to determine an angle θ of the document from the common origin; a cluster placement module to compute for each cluster, an angle σ of the cluster relative to the common origin; a placement calculation module to determine a difference between the document angle θ and one such cluster angle σ; a predetermined variance applied to the difference; and a clustering module to place the document into the cluster when the difference is less than the variance. | 1. A computer-implemented system for populating clusters of documents, comprising: a presentation module to place a set of clusters in a display in relation to a common origin; a document selection module to select one of a plurality of unclustered documents in the display and to determine an angle θ of the document from the common origin; a cluster placement module to compute for each cluster, an angle σ of the cluster relative to the common origin; a placement calculation module to determine a difference between the document angle θ and one such cluster angle σ; a predetermined variance applied to the difference; and a clustering module to place the document into the cluster when the difference is less than the variance. 9. A system according to claim 1 , wherein the clusters each comprise one of a circular and a non-circular shape within the display. | 0.672752 |
7. The method of claim 1 further comprising: determining a plurality of collections of entities based at least in part on the one or more terms or phrases; and selecting one of the plurality of collections of entities as the first collection of entities based at least in part on a predetermined selection criteria. | 7. The method of claim 1 further comprising: determining a plurality of collections of entities based at least in part on the one or more terms or phrases; and selecting one of the plurality of collections of entities as the first collection of entities based at least in part on a predetermined selection criteria. 8. The method of claim 7 wherein the predetermined selection criteria is selected from the group comprising a most popular collection, a most likely collection or a most relevant collection. | 0.963042 |
1. A method of editing a first file, comprising: reading the first file; reading at least one second file comprising at least one behavior describing changes that may be made to the first file, wherein the at least one behavior includes at least one participant designated by an expert for use in editing the first file; providing for display a menu of identifiers comprising an identifier for the at least one behavior referenced in the at least one second file; receiving a selection of the identifier, by an operator, for the at least one behavior from the menu of identifiers provided, wherein the operator is different from the expert; and responsive to the selection of the identifier for the at least one behavior: determining a location in the first file, the location corresponding to the at least one participant; and editing the first file at the location corresponding to the at least one participant, wherein the editing is performed in accordance with the changes described by the at least one behavior corresponding to the selected identifier. | 1. A method of editing a first file, comprising: reading the first file; reading at least one second file comprising at least one behavior describing changes that may be made to the first file, wherein the at least one behavior includes at least one participant designated by an expert for use in editing the first file; providing for display a menu of identifiers comprising an identifier for the at least one behavior referenced in the at least one second file; receiving a selection of the identifier, by an operator, for the at least one behavior from the menu of identifiers provided, wherein the operator is different from the expert; and responsive to the selection of the identifier for the at least one behavior: determining a location in the first file, the location corresponding to the at least one participant; and editing the first file at the location corresponding to the at least one participant, wherein the editing is performed in accordance with the changes described by the at least one behavior corresponding to the selected identifier. 6. The method of claim 1 wherein the location comprises a selection made by the operator. | 0.646409 |
10. A system of creating a structural document, the system comprising: a computing device; and a non-transitory computer-readable storage medium in communication with the computing device, wherein the computer-readable storage medium comprises one or more programming instructions that, when executed, cause the computing device to: receive content information pertaining to one or more contents that are to be encased by a structural document, determine a shape of a structural document based at least in part on the received content information, determine a plurality of dimensions of the structural document based at least in part on the received content information, receive content item information associated with one or more content items, wherein the content item information comprises at least one brand identifier associated with a provider of the one or more contents, cause a three-dimensional graphical representation of the structural document to be displayed at a user computing device, wherein a shape of the three-dimensional graphical representation corresponds to the determined shape, wherein a plurality of dimensions of the three-dimensional graphical representation correspond to the determined plurality of dimensions, wherein the three-dimensional graphical representation comprises at least a portion of the received content items; receive an indication that a user is finished creating the structural document, generate a print document comprising an encoded data mark, and provide the print document to one or more print-related devices. | 10. A system of creating a structural document, the system comprising: a computing device; and a non-transitory computer-readable storage medium in communication with the computing device, wherein the computer-readable storage medium comprises one or more programming instructions that, when executed, cause the computing device to: receive content information pertaining to one or more contents that are to be encased by a structural document, determine a shape of a structural document based at least in part on the received content information, determine a plurality of dimensions of the structural document based at least in part on the received content information, receive content item information associated with one or more content items, wherein the content item information comprises at least one brand identifier associated with a provider of the one or more contents, cause a three-dimensional graphical representation of the structural document to be displayed at a user computing device, wherein a shape of the three-dimensional graphical representation corresponds to the determined shape, wherein a plurality of dimensions of the three-dimensional graphical representation correspond to the determined plurality of dimensions, wherein the three-dimensional graphical representation comprises at least a portion of the received content items; receive an indication that a user is finished creating the structural document, generate a print document comprising an encoded data mark, and provide the print document to one or more print-related devices. 12. The system of claim 10 , wherein: the one or more programming instructions that, when executed, cause the computing device to receive content information comprises one or more programming instructions that, when executed, cause the computing device to receive one or more of the following: one or more dimensions associated with the one or more contents, a shape associated with the one or more contents, a weight associated with the one or more contents, and an image of the one or more contents; and the one or more programming instructions that, when executed, cause the computing device to determine a shape of the structural document comprise one or more programming instructions that, when executed, cause the computing device to automatically determine a shape of the structural document based on the received content information. | 0.508079 |
12. A non-transitory storage medium comprising instructions stored thereon executable by a processor to perform a method, comprising: identifying a log file of importance; centralizing a storage of the identified log file of importance for storing the identified log file in the storage; generating a social profile of the stored log file of importance; setting an access privilege associated with the generated social profile of the stored log file of importance; permitting a user to access the generated social profile of the stored log file of importance based on the set access privilege; and processing, using a processor and a memory, at least one of a comment and an annotation in the accessed social profile of the stored log file of importance, wherein the processed at least one of a command and an annotation is from the user; assigning, by the user, a tag to the generated social profile, wherein the assigned tag is a term that attaches to the generated social profile, as meta-data to enable a faster relevant search based on the term; receiving a search request for a software code that relates to the stored log file of importance; and retrieving the software code, in response to the received search request, based on the assigned tag. | 12. A non-transitory storage medium comprising instructions stored thereon executable by a processor to perform a method, comprising: identifying a log file of importance; centralizing a storage of the identified log file of importance for storing the identified log file in the storage; generating a social profile of the stored log file of importance; setting an access privilege associated with the generated social profile of the stored log file of importance; permitting a user to access the generated social profile of the stored log file of importance based on the set access privilege; and processing, using a processor and a memory, at least one of a comment and an annotation in the accessed social profile of the stored log file of importance, wherein the processed at least one of a command and an annotation is from the user; assigning, by the user, a tag to the generated social profile, wherein the assigned tag is a term that attaches to the generated social profile, as meta-data to enable a faster relevant search based on the term; receiving a search request for a software code that relates to the stored log file of importance; and retrieving the software code, in response to the received search request, based on the assigned tag. 14. The non-transitory storage medium of claim 12 further comprising instructions for: permitting annotation of information in the generated social profile; determining that the stored log file of importance is associated with a debug condition that has been resolved; and closing future comments to the stored log file of importance when the debug condition is resolved. | 0.580531 |
2. The method of claim 1 where returning the top-t records in R Q for a given value t, ranked by their relevancy to the query comprises finding a trie node corresponding to a keyword in a trie with inverted lists on leaf nodes by traversing the trie from the root; locating leaf descendants of the trie node corresponding to the keyword, and retrieving the corresponding predicted words and the predicted records on inverted lists. | 2. The method of claim 1 where returning the top-t records in R Q for a given value t, ranked by their relevancy to the query comprises finding a trie node corresponding to a keyword in a trie with inverted lists on leaf nodes by traversing the trie from the root; locating leaf descendants of the trie node corresponding to the keyword, and retrieving the corresponding predicted words and the predicted records on inverted lists. 5. The method of claim 2 where returning the top-t records in R Q for a given value t, ranked by their relevancy to the query comprises among the union lists ∪ 1 , ∪ 2 , . . . , ∪ t , of the leaf nodes of each prefix node identifying the shortest union list, verifying each record ID on the shortest list by checking if it exists on all the other union lists by maintaining a forward list maintained for each record r, which is a sorted list of IDs of keywords in r, denoted as F r , so that each prefix p i has a range of keyword IDs [MinId i , MaxId i ], verifying whether r appears on a union list ∪ k of a query prefix p k for a record r on the shortest union list by testing if p k appears in the forward list F r as a prefix by performing a binary search for MinId k on the forward list F r to get a lower bound Id lb , and check if Id lb is no larger than MaxId k , where the probing succeeds if the condition holds, and fails otherwise. | 0.762295 |
14. For a signal processing application, a computer-implemented method of detecting a data pattern from a plurality of received signals, the method comprising the steps of: (a) the computer providing a sequence of scan values derived from a sequence of count values, each scan value selecting one of a set of candidates in a varying pattern, wherein step (a) includes the step of generating the sequence of scan values so as to select each of the set of candidates in a periodic scan pattern; (b) the computer generating, for each of the sequence of count values, a difference term between a current metric value and a previous metric value based on a set of coefficients for a received symbol; (c) the computer combining, for each of a sequence of count values, the difference term with one or more previous difference terms to provide one of a set of metric values; and (d) the computer generating, based on the set of metric values corresponding to the sequence of scan values, soft-output values corresponding to the data pattern; wherein, for step (a), the received symbol is represented by symbol values in two or more dimensions, and step (a) includes the step of the computer generating the sequence of scan values so as to select each of the set of candidates in a scan pattern in each dimension, the scan pattern of each dimension varying in frequency with the scan pattern of at least one other dimension. | 14. For a signal processing application, a computer-implemented method of detecting a data pattern from a plurality of received signals, the method comprising the steps of: (a) the computer providing a sequence of scan values derived from a sequence of count values, each scan value selecting one of a set of candidates in a varying pattern, wherein step (a) includes the step of generating the sequence of scan values so as to select each of the set of candidates in a periodic scan pattern; (b) the computer generating, for each of the sequence of count values, a difference term between a current metric value and a previous metric value based on a set of coefficients for a received symbol; (c) the computer combining, for each of a sequence of count values, the difference term with one or more previous difference terms to provide one of a set of metric values; and (d) the computer generating, based on the set of metric values corresponding to the sequence of scan values, soft-output values corresponding to the data pattern; wherein, for step (a), the received symbol is represented by symbol values in two or more dimensions, and step (a) includes the step of the computer generating the sequence of scan values so as to select each of the set of candidates in a scan pattern in each dimension, the scan pattern of each dimension varying in frequency with the scan pattern of at least one other dimension. 15. The invention as recited in claim 14 , further comprising the step of (e) providing the set of coefficients for each received symbol. | 0.527415 |
8. A system for supplementing product information, the system comprising one or more processors and one or more memory devices operably coupled to the one or more processors, the one or more memory devices storing executable and operational data effective to cause the one or more processors to: receive a plurality of keywords; for each keyword of at least a portion of the plurality of keywords, obtain a result set for the each keyword by searching a product taxonomy; obtain a filtered set of keywords from the at least the portion of the plurality of keywords by filtering a set of keywords according to categories of result sets for the set of keywords, wherein the executable and operational data are further effective to cause the one or more processors to obtain the filtered set of keywords from the at least the portion of the plurality of keywords by filtering the set of keywords according to categories of the result sets for the set of keywords by, for each keyword of the at least the portion of the plurality of keywords and the result set for the each keyword performing: evaluating categorical similarity among products of the result set for the each keyword, wherein the executable and operational data are further effective to cause the one or more processors to evaluate the categorical similarity among products of the result set for the each keyword by calculating category consistency of the result set for the each keyword and wherein the executable and operational data are further effective to cause the one or more processors to calculate the category consistency of the result set for the each keyword by calculating the category consistency as n/(N−n), where n is a number of products in the result set for the each keyword and belonging to a most common category in categories represented in the result set for the each keyword and where N is a total number of products in the result set for the each keyword; assigning a score to the each keyword according to the categorical similarity; and filtering the at least the portion of the plurality of keywords according to the scores assigned thereto to obtain the filtered set of keywords; and define product groups for at least a portion of the filtered set of keywords, each product group having associated therewith a keyword from the filtered set of keywords and one or more products from the result set for the each keyword from the filtered set of keywords. | 8. A system for supplementing product information, the system comprising one or more processors and one or more memory devices operably coupled to the one or more processors, the one or more memory devices storing executable and operational data effective to cause the one or more processors to: receive a plurality of keywords; for each keyword of at least a portion of the plurality of keywords, obtain a result set for the each keyword by searching a product taxonomy; obtain a filtered set of keywords from the at least the portion of the plurality of keywords by filtering a set of keywords according to categories of result sets for the set of keywords, wherein the executable and operational data are further effective to cause the one or more processors to obtain the filtered set of keywords from the at least the portion of the plurality of keywords by filtering the set of keywords according to categories of the result sets for the set of keywords by, for each keyword of the at least the portion of the plurality of keywords and the result set for the each keyword performing: evaluating categorical similarity among products of the result set for the each keyword, wherein the executable and operational data are further effective to cause the one or more processors to evaluate the categorical similarity among products of the result set for the each keyword by calculating category consistency of the result set for the each keyword and wherein the executable and operational data are further effective to cause the one or more processors to calculate the category consistency of the result set for the each keyword by calculating the category consistency as n/(N−n), where n is a number of products in the result set for the each keyword and belonging to a most common category in categories represented in the result set for the each keyword and where N is a total number of products in the result set for the each keyword; assigning a score to the each keyword according to the categorical similarity; and filtering the at least the portion of the plurality of keywords according to the scores assigned thereto to obtain the filtered set of keywords; and define product groups for at least a portion of the filtered set of keywords, each product group having associated therewith a keyword from the filtered set of keywords and one or more products from the result set for the each keyword from the filtered set of keywords. 11. The system of claim 8 , wherein the executable and operational data are further effective to cause the one or more processors to evaluate categorical similarity among products of the result set for the each keyword by determining a distance in the product taxonomy from a root node in the product taxonomy of a most common category of the product taxonomy represented in the result set for the each keyword. | 0.503344 |
1. A method comprising: at a server device that hosts a fitness management application, receiving text information that describes a food recipe; at the server, parsing the text information to identify a first text portion that corresponds to one or more food ingredients and a second text portion that corresponds to a quantity corresponding to each of the one or more food ingredients; at the server, matching the one or more food ingredients in the first text portion with respective ones of known food ingredients in a database of known food ingredients; at the server, converting the quantity corresponding to each of the one or more food ingredients in the second text portion from a first quantity unit to a second quantity unit, the second quantity unit being selected based at least in part on a unit associated to nutrition information for the one or more food ingredients; at the server, calculating one or more nutrient content values of the food recipe using the nutritional information for the one or more food ingredients and the second quantity unit; and entering at least a portion of the calculated one or more nutrient content values into a nutrition log upon user selection thereof. | 1. A method comprising: at a server device that hosts a fitness management application, receiving text information that describes a food recipe; at the server, parsing the text information to identify a first text portion that corresponds to one or more food ingredients and a second text portion that corresponds to a quantity corresponding to each of the one or more food ingredients; at the server, matching the one or more food ingredients in the first text portion with respective ones of known food ingredients in a database of known food ingredients; at the server, converting the quantity corresponding to each of the one or more food ingredients in the second text portion from a first quantity unit to a second quantity unit, the second quantity unit being selected based at least in part on a unit associated to nutrition information for the one or more food ingredients; at the server, calculating one or more nutrient content values of the food recipe using the nutritional information for the one or more food ingredients and the second quantity unit; and entering at least a portion of the calculated one or more nutrient content values into a nutrition log upon user selection thereof. 6. The method of claim 1 , further comprising: sending the one or more nutrient content values to a client device; receiving corrective instructions from the client device, wherein the corrective instructions include instructions to modify particular ones of the one or more nutrient content values; and modifying particular ones of the one or more nutrient content values based on the corrective instructions. | 0.625133 |
14. The method of claim 11 , wherein loading system-specific meta data comprises scanning the databases and application systems. | 14. The method of claim 11 , wherein loading system-specific meta data comprises scanning the databases and application systems. 15. The method of claim 14 , wherein scanning comprises scanning at least one of a DBMS catalog, a COBOL copybook, a system logical data model, a system physical data model, a data dictionary, ETL meta data, source code, a database, a file system, and a BI tool. | 0.923753 |
20. A computer system comprising: a computer having at least one computer processor, wherein the computer is configured to at least: cause a display of at least a portion of a body of text of an electronic document within a first user interface on a display associated with the computer; receive a selection of at least one external resource; receive a selection of at least a portion of the body of text within the first user interface; identify at least two established facts within the selected portion of the body of text using the at least one computer processor; identify a contradiction between the at least two established facts within the body of text using the at least one computer processor; determine whether the at least one external resource comprises information regarding the contradiction; in response to determining that the at least one external resource comprises information regarding the contradiction, generate information regarding a first change to the electronic document based at least in part on the information regarding the contradiction; and cause a display of at least a second user interface on the display, wherein the second user interface is superimposed over at least a portion of the first user interface, and wherein the second user interface comprises at least some of the information regarding the first change to the electronic document to address the contradiction; and receive a first instruction to implement the first change to the electronic document via the second user interface. | 20. A computer system comprising: a computer having at least one computer processor, wherein the computer is configured to at least: cause a display of at least a portion of a body of text of an electronic document within a first user interface on a display associated with the computer; receive a selection of at least one external resource; receive a selection of at least a portion of the body of text within the first user interface; identify at least two established facts within the selected portion of the body of text using the at least one computer processor; identify a contradiction between the at least two established facts within the body of text using the at least one computer processor; determine whether the at least one external resource comprises information regarding the contradiction; in response to determining that the at least one external resource comprises information regarding the contradiction, generate information regarding a first change to the electronic document based at least in part on the information regarding the contradiction; and cause a display of at least a second user interface on the display, wherein the second user interface is superimposed over at least a portion of the first user interface, and wherein the second user interface comprises at least some of the information regarding the first change to the electronic document to address the contradiction; and receive a first instruction to implement the first change to the electronic document via the second user interface. 21. The computer system of claim 20 , wherein the computer is further configured to at least: calculate a confidence level of the contradiction according to a formula, wherein the formula comprises at least one of: a factor relating to a location of at least one of the at least two established facts within the electronic document, a factor relating to a proximity of the at least two established facts within the electronic document, or a factor relating to a context of at least one of the at least two established facts within the electronic document, and wherein whether the at least one external resource comprises information regarding the contradiction is determined based at least in part on the confidence level of the contradiction. | 0.500244 |
1. A mobile system responsive to a user generated natural language speech utterance, comprising: a speech unit connected to a computer device on a vehicle, wherein the speech unit receives a natural language speech utterance from a user and converts the received natural language speech utterance into an electronic signal; and a natural language speech processing system connected to the computer device on the vehicle, wherein the natural language speech processing system receives, processes, and responds to the electronic signal using data received from a plurality of domain agents, wherein the natural language speech processing system includes: a speech recognition engine that recognizes at least one of words or phrases from the electronic signal using at least the data received from the plurality of domain agents, wherein the data used by the speech recognition engine includes a plurality of dictionary and phrase entries that are dynamically updated based on at least a history of a current dialog and one or more prior dialogs associated with the user; a parser that interprets the recognized words or phrases, wherein the parser uses at least the data received from the plurality of domain agents to interpret the recognized words or phrases, wherein the parser interprets the recognized words or phrases by: determining a context for the natural language speech utterance; selecting at least one of the plurality of domain agents based on the determined context; and transforming the recognized words or phrases into at least one of a question or a command, wherein the at least one question or command is formulated in a grammar that the selected domain agent uses to process the formulated question or command; and an agent architecture that communicatively couples services of each of an agent manager, a system agent, the plurality of domain agents, and an agent library that includes one or more utilities that can be used by the system agent and the plurality of domain agents, wherein the selected domain agent uses the communicatively coupled services to create a response to the formulated question or command and format the response for presentation to the user. | 1. A mobile system responsive to a user generated natural language speech utterance, comprising: a speech unit connected to a computer device on a vehicle, wherein the speech unit receives a natural language speech utterance from a user and converts the received natural language speech utterance into an electronic signal; and a natural language speech processing system connected to the computer device on the vehicle, wherein the natural language speech processing system receives, processes, and responds to the electronic signal using data received from a plurality of domain agents, wherein the natural language speech processing system includes: a speech recognition engine that recognizes at least one of words or phrases from the electronic signal using at least the data received from the plurality of domain agents, wherein the data used by the speech recognition engine includes a plurality of dictionary and phrase entries that are dynamically updated based on at least a history of a current dialog and one or more prior dialogs associated with the user; a parser that interprets the recognized words or phrases, wherein the parser uses at least the data received from the plurality of domain agents to interpret the recognized words or phrases, wherein the parser interprets the recognized words or phrases by: determining a context for the natural language speech utterance; selecting at least one of the plurality of domain agents based on the determined context; and transforming the recognized words or phrases into at least one of a question or a command, wherein the at least one question or command is formulated in a grammar that the selected domain agent uses to process the formulated question or command; and an agent architecture that communicatively couples services of each of an agent manager, a system agent, the plurality of domain agents, and an agent library that includes one or more utilities that can be used by the system agent and the plurality of domain agents, wherein the selected domain agent uses the communicatively coupled services to create a response to the formulated question or command and format the response for presentation to the user. 6. The mobile system according to claim 1 , wherein the selected domain agent includes data for communicating with one or more devices. | 0.594932 |
7. A method for decompressing a spinal canal, comprising: moving a posterior element of a vertebra that is separated from a first portion of a lateral mass of the vertebra away from the first portion of the lateral mass to expand a spinal canal disposed between the posterior element and the first portion of the lateral mass; implanting a first bone anchor into the first portion of the lateral mass; coupling a first end of a first connecting plate to the first bone anchor; and coupling a second end of the first connecting plate to the posterior element to maintain the posterior element in a fixed position with respect to the first portion of the lateral mass, wherein the second end of the first connecting plate comprises a buttress formed on an inferior, vertebra-facing surface of the first connecting plate, and first sidewall of the buttress contacts the posterior element when the second end of the first connecting plate is coupled to the posterior element while a second side-wall that is opposed to the first sidewall is a distance apart from the first portion of the lateral mass. | 7. A method for decompressing a spinal canal, comprising: moving a posterior element of a vertebra that is separated from a first portion of a lateral mass of the vertebra away from the first portion of the lateral mass to expand a spinal canal disposed between the posterior element and the first portion of the lateral mass; implanting a first bone anchor into the first portion of the lateral mass; coupling a first end of a first connecting plate to the first bone anchor; and coupling a second end of the first connecting plate to the posterior element to maintain the posterior element in a fixed position with respect to the first portion of the lateral mass, wherein the second end of the first connecting plate comprises a buttress formed on an inferior, vertebra-facing surface of the first connecting plate, and first sidewall of the buttress contacts the posterior element when the second end of the first connecting plate is coupled to the posterior element while a second side-wall that is opposed to the first sidewall is a distance apart from the first portion of the lateral mass. 17. The method of claim 7 , wherein the posterior element comprises either a portion of a lamina of the vertebra or a spinous process of the vertebra, and the lateral mass comprises a pedicle of the vertebra. | 0.69409 |
3. The document processing apparatus according to claim 1 , further comprising means for outputting said electronic document stored in the storage device to the composite device, with which the document processing apparatus is in communication, in a case wherein said print item selection information indicates only an original document as a printing object. | 3. The document processing apparatus according to claim 1 , further comprising means for outputting said electronic document stored in the storage device to the composite device, with which the document processing apparatus is in communication, in a case wherein said print item selection information indicates only an original document as a printing object. 6. The document processing apparatus according to claim 3 , wherein said print item selection information further includes print-form selection information wherein said means for generating a print document of a new type, when generating a print document of an output type including said extracted written-in information, includes means for selectively laying out either image data of said written-in information or test in a print document based on said print-form selection information. | 0.889034 |
1. A method for rendering arranged content search results, the method comprising: causing via a processor of a user device, at least in part, a rendering of a plurality of result objects in a single view in a user interface of the user device, the rendering of the plurality of result objects comprising: causing, at least in part, tracking of access events associated with a plurality of the result objects, wherein the plurality of the result objects are from a plurality of search domains, wherein the tracking of access events comprises tracking a number of times that one or more of the plurality of result objects has been accessed to develop a tracking history for the one or more of the plurality of result objects, wherein the tracking of access events further comprises tracking a number of times that the one or more of the plurality of result objects has been accessed from a first domain of local content stored on the user device and/or from a second domain of remote content accessible via a network; causing, at least in part, determining a context of the user device during the tracking of the access events; causing, at least in part, mapping of the determined context of the user device associated with the tracked access events; causing, at least in part, determining a rank value for the respective result objects based, at least in part, on the mapping and the tracking history of the respective result objects; causing, at least in part, a sorting of the ranked result objects according to the determined rank value; and rendering, at least in part, the sorted ranked result objects in the single view in the user interface of the user device. | 1. A method for rendering arranged content search results, the method comprising: causing via a processor of a user device, at least in part, a rendering of a plurality of result objects in a single view in a user interface of the user device, the rendering of the plurality of result objects comprising: causing, at least in part, tracking of access events associated with a plurality of the result objects, wherein the plurality of the result objects are from a plurality of search domains, wherein the tracking of access events comprises tracking a number of times that one or more of the plurality of result objects has been accessed to develop a tracking history for the one or more of the plurality of result objects, wherein the tracking of access events further comprises tracking a number of times that the one or more of the plurality of result objects has been accessed from a first domain of local content stored on the user device and/or from a second domain of remote content accessible via a network; causing, at least in part, determining a context of the user device during the tracking of the access events; causing, at least in part, mapping of the determined context of the user device associated with the tracked access events; causing, at least in part, determining a rank value for the respective result objects based, at least in part, on the mapping and the tracking history of the respective result objects; causing, at least in part, a sorting of the ranked result objects according to the determined rank value; and rendering, at least in part, the sorted ranked result objects in the single view in the user interface of the user device. 4. The method of claim 1 , wherein the determined rank value of a result object is based, at least in part, on one or more of at least one rank metric, group information, a view/result access algorithm, or a combination thereof associated with the result object. | 0.56525 |
1. A method comprising: classifying a reference set of visual patterns that belong to a parent class into mutually exclusive child classes that include first and second child classes, a visual pattern from the reference set being classified into the first child class instead of the second child class; modifying a weight vector that corresponds to the parent class, the modified weight vector altering a first probability that the visual pattern belongs to the first child class and a second probability that the visual pattern belongs to the second child class; based on the altered first and second probabilities, removing mutual exclusivity from the first and second child classes by adding the visual pattern to the second child class; and using a processor, generating a hierarchy of classes of visual patterns, the hierarchy including the parent class and the mutually nonexclusive first and second child classes that each include the visual pattern. | 1. A method comprising: classifying a reference set of visual patterns that belong to a parent class into mutually exclusive child classes that include first and second child classes, a visual pattern from the reference set being classified into the first child class instead of the second child class; modifying a weight vector that corresponds to the parent class, the modified weight vector altering a first probability that the visual pattern belongs to the first child class and a second probability that the visual pattern belongs to the second child class; based on the altered first and second probabilities, removing mutual exclusivity from the first and second child classes by adding the visual pattern to the second child class; and using a processor, generating a hierarchy of classes of visual patterns, the hierarchy including the parent class and the mutually nonexclusive first and second child classes that each include the visual pattern. 8. The method of claim 1 , wherein: the classifying of the reference set of visual patterns is based on the weight vector prior to the modifying of the weight vector. | 0.637295 |
8. A system for filtering content based on acquiring data associated with language identification, comprising: a computing device having a processor and a memory including instructions, which when executed by the processor, provides: a language preference model for acquiring data associated with language identification from a plurality of sources associated with the content of an interactive program guide, performing an analysis of the acquired data associated with language identification to determine which source of the plurality of sources associated with the content of an interactive program guide has a highest priority, and in response to performing the analysis, processing the acquired data to utilize the source with the highest priority to identify a preferred language of the interactive program guide based on the analysis of the acquired data associated with language identification; and a recommendation engine, in response to performing the analysis, receiving the identified preferred language from the language preference model and filtering content presented in the interactive program guide based on the identified preferred language, wherein filtering content presented in the interactive program guide based on a preferred language identified comprises the computing device filtering data based on a parameter associated with and obtained from a user device or based on the user's use of the user device. | 8. A system for filtering content based on acquiring data associated with language identification, comprising: a computing device having a processor and a memory including instructions, which when executed by the processor, provides: a language preference model for acquiring data associated with language identification from a plurality of sources associated with the content of an interactive program guide, performing an analysis of the acquired data associated with language identification to determine which source of the plurality of sources associated with the content of an interactive program guide has a highest priority, and in response to performing the analysis, processing the acquired data to utilize the source with the highest priority to identify a preferred language of the interactive program guide based on the analysis of the acquired data associated with language identification; and a recommendation engine, in response to performing the analysis, receiving the identified preferred language from the language preference model and filtering content presented in the interactive program guide based on the identified preferred language, wherein filtering content presented in the interactive program guide based on a preferred language identified comprises the computing device filtering data based on a parameter associated with and obtained from a user device or based on the user's use of the user device. 11. The system of claim 8 , wherein the language preference model applies business rules to determine a source having a highest priority. | 0.666149 |
1. One or more computer-readable storage devices having computer-executable instructions embodied thereon that when executed provide a method for facilitating decision support by determining nomenclature linkages between variables in databases that have different ontologies, the method comprising: identifying a first set of documents from a first record system having a first ontology; identifying a second set of documents from a second record system having a second ontology that is different than the first ontology; determining a use-case present in the first and second sets of documents; determining a set of variables relevant to the use-case; receiving from the first set of documents, a first document containing at least one first-document variable from the set of variables; wherein each first-document variable has a first-document value associated with it; receiving from the second set of documents, a second document containing at least one second-document variable from the set of variables; (1) wherein the second-document variable has a second-document value associated with it, and (2) wherein the second-document variable is also contained in the first document; based on the determined use-case and set of variables, generating a classifier; for each first-document variable contained in the first document, applying the classifier to transform the first-document value associated with the first-document variable to a categorical datatype; for each second-document variable contained in the second document, applying the classifier to transform the second-document value associated with the second-document variable to a categorical datatype; based on the categorical datatypes of the first document and the categorical datatypes of the second document, generating a set of textmatrices; applying latent semantic analysis to the set of textmatrices to determine a latent semantic space associated with the at least one first-document variable and the at least one second document variable; specifying a threshold of similarity; for a first comparison-variable, from the at least one first-document variables associated with the latent semantic space: determining a measure of similarity to a second-comparison variable from the at least one second-document variables associated with the latent semantic space: performing a comparison of the measure similarity to the threshold; and based on the comparison, determining that the measure similarity satisfies the threshold, associating the first comparison variable with the second comparison variable, and designating the association as a synonymy, wherein the threshold is satisfied if the measure of similarity is greater than the threshold. | 1. One or more computer-readable storage devices having computer-executable instructions embodied thereon that when executed provide a method for facilitating decision support by determining nomenclature linkages between variables in databases that have different ontologies, the method comprising: identifying a first set of documents from a first record system having a first ontology; identifying a second set of documents from a second record system having a second ontology that is different than the first ontology; determining a use-case present in the first and second sets of documents; determining a set of variables relevant to the use-case; receiving from the first set of documents, a first document containing at least one first-document variable from the set of variables; wherein each first-document variable has a first-document value associated with it; receiving from the second set of documents, a second document containing at least one second-document variable from the set of variables; (1) wherein the second-document variable has a second-document value associated with it, and (2) wherein the second-document variable is also contained in the first document; based on the determined use-case and set of variables, generating a classifier; for each first-document variable contained in the first document, applying the classifier to transform the first-document value associated with the first-document variable to a categorical datatype; for each second-document variable contained in the second document, applying the classifier to transform the second-document value associated with the second-document variable to a categorical datatype; based on the categorical datatypes of the first document and the categorical datatypes of the second document, generating a set of textmatrices; applying latent semantic analysis to the set of textmatrices to determine a latent semantic space associated with the at least one first-document variable and the at least one second document variable; specifying a threshold of similarity; for a first comparison-variable, from the at least one first-document variables associated with the latent semantic space: determining a measure of similarity to a second-comparison variable from the at least one second-document variables associated with the latent semantic space: performing a comparison of the measure similarity to the threshold; and based on the comparison, determining that the measure similarity satisfies the threshold, associating the first comparison variable with the second comparison variable, and designating the association as a synonymy, wherein the threshold is satisfied if the measure of similarity is greater than the threshold. 10. The one or more computer-readable storage devices of claim 1 , further comprising displaying to a user the first comparison variable and the second comparison variable as a designated synonymy. | 0.511793 |
3. The method of claim 1 , further comprising: providing a first display area or a first visual format; providing a second display area or a second visual format; and displaying the electronic objects or links to the electronic objects in the first display area or in the first visual format if the importance measure is above a threshold. | 3. The method of claim 1 , further comprising: providing a first display area or a first visual format; providing a second display area or a second visual format; and displaying the electronic objects or links to the electronic objects in the first display area or in the first visual format if the importance measure is above a threshold. 4. The method of claim 3 , wherein the first display area or the second display area is associated with a text label representing the meaning of a high importance or a low importance. | 0.88908 |
9. A system for using educational contexts for learners to adjust processing of search queries in a learner-specific manner, the system comprising: one or more processors; a context engine that accesses an educational-context data store that identifies, for each learner of a set of learners, a course that the learner is enrolled in, the course being associated with a syllabus; a query engine that, using the one or more processors: receives a search query entered by a learner of the set of learners via an interface at an input time, the search query including a query term; determines a weight for a concept for the query; identifies a content object in a set of content objects based on the determined weight for the concept; and determines a query result that identifies the content object as being responsive to the query; and a schedule engine that: identifies the syllabus associated with the course that the learner is enrolled in; and identifies a portion of the syllabus corresponding to the input time, wherein the query engine determines the weight for the concept based on: the query term; the course that the learner is identified as being enrolled in; and the portion of the syllabus. | 9. A system for using educational contexts for learners to adjust processing of search queries in a learner-specific manner, the system comprising: one or more processors; a context engine that accesses an educational-context data store that identifies, for each learner of a set of learners, a course that the learner is enrolled in, the course being associated with a syllabus; a query engine that, using the one or more processors: receives a search query entered by a learner of the set of learners via an interface at an input time, the search query including a query term; determines a weight for a concept for the query; identifies a content object in a set of content objects based on the determined weight for the concept; and determines a query result that identifies the content object as being responsive to the query; and a schedule engine that: identifies the syllabus associated with the course that the learner is enrolled in; and identifies a portion of the syllabus corresponding to the input time, wherein the query engine determines the weight for the concept based on: the query term; the course that the learner is identified as being enrolled in; and the portion of the syllabus. 14. The system for using educational contexts for learners to adjust processing of search queries in the learner-specific manner as recited in claim 9 , wherein the query engine further determines an order for plurality of content objects in the set of content objects based on the weight for the concept, the plurality of content objects including the content object, wherein the query result identifies at least some of the plurality of content objects in the determined order. | 0.632164 |
4. The method of claim 1 , wherein the first plurality of offensive words is provided by a first source and the second plurality of offensive words is provided by a second source, wherein the first source is different than the second source. | 4. The method of claim 1 , wherein the first plurality of offensive words is provided by a first source and the second plurality of offensive words is provided by a second source, wherein the first source is different than the second source. 5. The method of claim 4 , wherein the first source or the second source comprises a user, a service administrator, a third party, a government institution having jurisdictional authority for a user, a non-governmental institution with which the user is associated or any combination thereof. | 0.902153 |
1. A system for providing education-related alerts in an online learning environment, comprising: a watcher module to monitor an online learning environment comprising a plurality of users participating in online educational activities; an online database comprising a performance threshold and a time threshold for the online educational activities; an event module to receive a score for an assignment completed by one or more students in the online learning environment during a first time, to receive a further score for the same assignment completed by the student during a second time, to determine a score difference between the score and the further score, to determine a time difference between the first score and the second score, to apply the performance threshold to the score difference, to apply the time threshold to the time difference, and to determine an occurrence of suspected cheating when the score difference fails to satisfy the performance threshold and the time difference fails to satisfy the time threshold; an alert module to generate an alert for the suspected cheating occurrence, comprising: a template module to select a template for the suspected cheating occurrence; a data entry module to populate the template with notification of the suspected cheating occurrence as the alert, wherein the template comprises a predetermined format with at least one of text, fillable fields, and a blank text box that are filled by the data entry module; and an interactive element module to provide to recipients of the alert, suggested response actions comprising at least one of producing additional information, initiating a communication, and sending additional alerts, wherein the suggested response actions are each displayed in the alert by an interactive response action element comprising at least one of response buttons, text recommendations, images, sound, and hyperlinks that allows the recipients of the alert to perform an action; a delivery module to provide the alert to one or more of the users as the recipients; and a processor to execute each of the modules, which are stored on a non-transitory computer-readable storage medium. | 1. A system for providing education-related alerts in an online learning environment, comprising: a watcher module to monitor an online learning environment comprising a plurality of users participating in online educational activities; an online database comprising a performance threshold and a time threshold for the online educational activities; an event module to receive a score for an assignment completed by one or more students in the online learning environment during a first time, to receive a further score for the same assignment completed by the student during a second time, to determine a score difference between the score and the further score, to determine a time difference between the first score and the second score, to apply the performance threshold to the score difference, to apply the time threshold to the time difference, and to determine an occurrence of suspected cheating when the score difference fails to satisfy the performance threshold and the time difference fails to satisfy the time threshold; an alert module to generate an alert for the suspected cheating occurrence, comprising: a template module to select a template for the suspected cheating occurrence; a data entry module to populate the template with notification of the suspected cheating occurrence as the alert, wherein the template comprises a predetermined format with at least one of text, fillable fields, and a blank text box that are filled by the data entry module; and an interactive element module to provide to recipients of the alert, suggested response actions comprising at least one of producing additional information, initiating a communication, and sending additional alerts, wherein the suggested response actions are each displayed in the alert by an interactive response action element comprising at least one of response buttons, text recommendations, images, sound, and hyperlinks that allows the recipients of the alert to perform an action; a delivery module to provide the alert to one or more of the users as the recipients; and a processor to execute each of the modules, which are stored on a non-transitory computer-readable storage medium. 3. A system according to claim 1 , further comprising: a request module to receive a request for performance of an action from at least one of the users in response to the alert; and a processor to process the request, comprising one or more of: a response module to generate a response alert; and a change module to initiate a change to the education-related information. | 0.5 |
1. A talking electronic apparatus comprising: memory means for storing digital speech data and digital control data from which a plurality of requests in synthesized human speech for respective operator responses and appropriate operator responses corresponding to said plurality of requests may be respectively derived, speech synthesizer means operably associated with said memory means for converting said digital speech data into audible human speech, means for randomly accessing a portion of said digital speech data stored in said memory means from which a request for an operator response may be derived, means for transferring said randomly accessed portion of said digital speech data from said memory means to said speech synthesizer means to produce a randomly selected audible request in human speech, operator input means for receiving an operator response to said randomly selected audible request, and means responsive to said digital control data and said operator response to said randomly selected audible request for responding in a manner producing an output indicative of the appropriateness of said operator response with respect to the appropriate operator response corresponding to said randomly selected audible request. | 1. A talking electronic apparatus comprising: memory means for storing digital speech data and digital control data from which a plurality of requests in synthesized human speech for respective operator responses and appropriate operator responses corresponding to said plurality of requests may be respectively derived, speech synthesizer means operably associated with said memory means for converting said digital speech data into audible human speech, means for randomly accessing a portion of said digital speech data stored in said memory means from which a request for an operator response may be derived, means for transferring said randomly accessed portion of said digital speech data from said memory means to said speech synthesizer means to produce a randomly selected audible request in human speech, operator input means for receiving an operator response to said randomly selected audible request, and means responsive to said digital control data and said operator response to said randomly selected audible request for responding in a manner producing an output indicative of the appropriateness of said operator response with respect to the appropriate operator response corresponding to said randomly selected audible request. 4. A talking electronic apparatus according to claim 1, wherein said means responsive to said digital control data and said operator response includes visual presentation means for informing said operator if said operator response is appropriate. | 0.733376 |
1. A computer-implemented method for organizing a collection of files from an Internet search, the method comprising: by at least one computer: assigning a score to each file based on at least the following factors: recency, editorial popularity, clickthru popularity, favorites metadata, and favorites collaborative filtering; organizing the files based on the assigned scores; and displaying the files as organized; wherein the clickthru popularity for each file is based on an aggregation of at least: a first clicks-per-minute value for each file; a second clicks-per-hour value for each file; and a third clicks-per-day value for each file. | 1. A computer-implemented method for organizing a collection of files from an Internet search, the method comprising: by at least one computer: assigning a score to each file based on at least the following factors: recency, editorial popularity, clickthru popularity, favorites metadata, and favorites collaborative filtering; organizing the files based on the assigned scores; and displaying the files as organized; wherein the clickthru popularity for each file is based on an aggregation of at least: a first clicks-per-minute value for each file; a second clicks-per-hour value for each file; and a third clicks-per-day value for each file. 6. The method of claim 1 wherein weighting of collaborative filtering favorites metadata is R cf
R cf,l =W sim ( S max,l )+(1− W sim ) P 1 , where: W sim = similarity weighting factor = C ma x sim ( 1 - 1 1 + n i ) , where: 0≦C max sim ≦1. | 0.702578 |
12. The method of claim 1 , further comprising: passively monitoring the plurality of messages exchanged between the two or more participants. | 12. The method of claim 1 , further comprising: passively monitoring the plurality of messages exchanged between the two or more participants. 14. The method of claim 12 , wherein said testing conformance is performed after runtime. | 0.978843 |
1. A system, comprising: a processor configured to: determine a topic based on a user demand, wherein the determining of the topic comprises: determine frequencies of phrases based on an analysis of a search query log from a web site, a search query log from a search engine, or a combination thereof; compare the frequencies of the phrases to a predetermined threshold; determine at least one theme based on phrases having frequencies exceeding the predetermined threshold; sort the at least one theme based on common words in the phrases; cluster the at least one theme based on a clustering technique, the clustering technique being a min hash clustering or a n-squared clustering based on bi-grams; and determine the topic based on the clustered at least one theme; automatically generate content for the topic; and select the content that is contextually relevant for display within a corpus of content, wherein the content is optimized for the topic; wherein the corpus of content includes a web site, a user's social networking web page, content customized for mobile devices, content customized based on location awareness, or an electronic mail message; and wherein: in the event that the corpus of content includes the web site, content of the web site is different from other web pages of the website; in the event that the corpus of content includes a user's social networking web page, content of the user's social networking web page is different from another user's social networking web page; in the event that the corpus of content includes content customized for mobile devices, content of a mobile device is different from another mobile device; in the event that the corpus of content includes content customized based on location awareness, content of a location is different from another location; and in the event that the corpus of content includes the electronic mail message, the electronic mail message is different from another electronic mail message; and a memory coupled to the processor and configured to provide the processor with instructions. | 1. A system, comprising: a processor configured to: determine a topic based on a user demand, wherein the determining of the topic comprises: determine frequencies of phrases based on an analysis of a search query log from a web site, a search query log from a search engine, or a combination thereof; compare the frequencies of the phrases to a predetermined threshold; determine at least one theme based on phrases having frequencies exceeding the predetermined threshold; sort the at least one theme based on common words in the phrases; cluster the at least one theme based on a clustering technique, the clustering technique being a min hash clustering or a n-squared clustering based on bi-grams; and determine the topic based on the clustered at least one theme; automatically generate content for the topic; and select the content that is contextually relevant for display within a corpus of content, wherein the content is optimized for the topic; wherein the corpus of content includes a web site, a user's social networking web page, content customized for mobile devices, content customized based on location awareness, or an electronic mail message; and wherein: in the event that the corpus of content includes the web site, content of the web site is different from other web pages of the website; in the event that the corpus of content includes a user's social networking web page, content of the user's social networking web page is different from another user's social networking web page; in the event that the corpus of content includes content customized for mobile devices, content of a mobile device is different from another mobile device; in the event that the corpus of content includes content customized based on location awareness, content of a location is different from another location; and in the event that the corpus of content includes the electronic mail message, the electronic mail message is different from another electronic mail message; and a memory coupled to the processor and configured to provide the processor with instructions. 10. The system recited in claim 1 , wherein the content is selected for display in a plurality of modules, and wherein the processor is further configured to: determine performance metrics associated with the plurality of modules; and determine a charge for using each of the plurality of modules based on the performance metrics associated with each of the plurality of modules. | 0.63035 |
2. The invention of claim 1 further comprising: ranking at least some of the suppliers of the search result sets compared to other suppliers using relationship based criteria not limited to current bids; and requesting search result sets related to the keyword from the suppliers in accordance with the ranking of the suppliers. | 2. The invention of claim 1 further comprising: ranking at least some of the suppliers of the search result sets compared to other suppliers using relationship based criteria not limited to current bids; and requesting search result sets related to the keyword from the suppliers in accordance with the ranking of the suppliers. 4. The invention of claim 2 wherein the suppliers are ranked in accordance with a response time for providing prior search result sets provided by each supplier in response to prior requests for search result sets. | 0.745714 |
1. A method of teaching the pronounciation and spelling and distinguishing between the written and spoken form of any language, the method comprising: A. utilizing three sets of tiles which consist essentially of: (1) a first set denoting alphabet letters, (2) a second set denoting phonetic vowels, (3) a third set denoting phonetic consonants, said first set comprising all geometrically uniform tiles, each said geometrically uniform tile having an alphabet letter on one surface thereof in black or white and a background of opposite white or black colour to the letter colours, there being a separate tile for each upper case alphabet letter and a separate tile for each lower case alphabet letter, said second set of tiles comprising geometrically uniform tiles wherein one surface of each tile is blank and is individually and distinctively coloured to represent a phonetic vowel spelling where there are differences in spelling the same vowel sound, while the other surface of each tile contains a phonetic symbol to represent the vowel sound of said one surface, the said third set of tiles comprising single letter consonants and two-letter digraph combinations of consonants having a single phonetic sound: B. selecting the first, second and third sets to be distinct, and C. teaching the pronounciation and spelling of words of said any language by interposing said alphabet tiles and said phonetic tiles. | 1. A method of teaching the pronounciation and spelling and distinguishing between the written and spoken form of any language, the method comprising: A. utilizing three sets of tiles which consist essentially of: (1) a first set denoting alphabet letters, (2) a second set denoting phonetic vowels, (3) a third set denoting phonetic consonants, said first set comprising all geometrically uniform tiles, each said geometrically uniform tile having an alphabet letter on one surface thereof in black or white and a background of opposite white or black colour to the letter colours, there being a separate tile for each upper case alphabet letter and a separate tile for each lower case alphabet letter, said second set of tiles comprising geometrically uniform tiles wherein one surface of each tile is blank and is individually and distinctively coloured to represent a phonetic vowel spelling where there are differences in spelling the same vowel sound, while the other surface of each tile contains a phonetic symbol to represent the vowel sound of said one surface, the said third set of tiles comprising single letter consonants and two-letter digraph combinations of consonants having a single phonetic sound: B. selecting the first, second and third sets to be distinct, and C. teaching the pronounciation and spelling of words of said any language by interposing said alphabet tiles and said phonetic tiles. 2. The method of claim 1, wherein said third set of tiles includes tiles which are individually formed into different geometric shapes to represent indicia selected from specific phonetic consonants and digraphs of said any language. | 0.576248 |
1. A client system, comprising: a processor; and a memory containing a program that, when executed on the processor, performs an operation, comprising: receiving, over a data communication network, an electronic document comprising a request to retrieve a plurality of advertisement creatives, wherein the request specifies an advertisement management system and a single identification tag identifying a plurality of advertisement types to be inserted within the electronic document, wherein the plurality of advertisement types comprises all advertisement types to appear within the electronic document, and wherein each of the plurality of advertisement creatives comprises computer program code configured to request a respective advertisement of a type selected from one of the plurality of advertisement types; responsive to transmitting the request specified within the received electronic document to the advertisement management system, receiving, over the data communication network from the advertisement management system, a single software object, wherein the advertisement management system is configured to select the plurality of advertisement creatives based on the plurality of advertisement types identified by the single identification tag specified within the transmitted request, and wherein the single software object comprises a JavaScript object notation (JSON) object that defines all of the plurality of advertisement creatives and identifies how the advertisement creatives will be displayed by the browser: extracting, without requiring user interaction, all of the plurality of advertisement creatives from the single software object by referencing a library configured to interpret the single software object; inserting, without requiring user interaction, each of the plurality of advertisement creatives into the electronic document, prior to rendering the electronic document; and rendering the electronic document together with the plurality of advertisement creatives. | 1. A client system, comprising: a processor; and a memory containing a program that, when executed on the processor, performs an operation, comprising: receiving, over a data communication network, an electronic document comprising a request to retrieve a plurality of advertisement creatives, wherein the request specifies an advertisement management system and a single identification tag identifying a plurality of advertisement types to be inserted within the electronic document, wherein the plurality of advertisement types comprises all advertisement types to appear within the electronic document, and wherein each of the plurality of advertisement creatives comprises computer program code configured to request a respective advertisement of a type selected from one of the plurality of advertisement types; responsive to transmitting the request specified within the received electronic document to the advertisement management system, receiving, over the data communication network from the advertisement management system, a single software object, wherein the advertisement management system is configured to select the plurality of advertisement creatives based on the plurality of advertisement types identified by the single identification tag specified within the transmitted request, and wherein the single software object comprises a JavaScript object notation (JSON) object that defines all of the plurality of advertisement creatives and identifies how the advertisement creatives will be displayed by the browser: extracting, without requiring user interaction, all of the plurality of advertisement creatives from the single software object by referencing a library configured to interpret the single software object; inserting, without requiring user interaction, each of the plurality of advertisement creatives into the electronic document, prior to rendering the electronic document; and rendering the electronic document together with the plurality of advertisement creatives. 10. The system of claim 1 , wherein the electronic document further comprises a second request to retrieve the library configured to interpret the single software object, and the operation further comprises sending the second request to the library to interpret the single software object. | 0.67418 |
12. Software for retrieving multimedia information, the software embodied on a computer-readable storage medium and, when executed by a computer, operable to: provide the multimedia information from independently accessible retrieval paths, the paths including: a textual search entry path configured to enable entry of one or more terms to search for in at least a portion of textual information stored on a computer-readable storage medium, wherein the textual search entry path is operable to access a stem index including a plurality of stems that are each associated with textual information and one or more related stems, the stems being concatenated in order to map each stem to other stems and to textual information that express a similar idea, and search the textual information using the stem index for textual information that closely resembles a search inquiry comprising one or more terms entered in the textual search entry path. | 12. Software for retrieving multimedia information, the software embodied on a computer-readable storage medium and, when executed by a computer, operable to: provide the multimedia information from independently accessible retrieval paths, the paths including: a textual search entry path configured to enable entry of one or more terms to search for in at least a portion of textual information stored on a computer-readable storage medium, wherein the textual search entry path is operable to access a stem index including a plurality of stems that are each associated with textual information and one or more related stems, the stems being concatenated in order to map each stem to other stems and to textual information that express a similar idea, and search the textual information using the stem index for textual information that closely resembles a search inquiry comprising one or more terms entered in the textual search entry path. 14. The software of claim 12 , wherein the textual search entry path is further operable to eliminate one or more stop terms in a search inquiry by comparing terms in the search inquiry to terms stored in a stop term list and by eliminating any terms in the search inquiry that match terms stored in the stop term list. | 0.5 |
2. The method of claim 1 , further comprising: attempting to fetch a document by crawling the web crawl space; determining that the document has been moved; and performing redirect processing by: identifying a new seed name that represents a new location of the document; and generating one or more additional allow rules on the new seed name to enlarge the web crawl space. | 2. The method of claim 1 , further comprising: attempting to fetch a document by crawling the web crawl space; determining that the document has been moved; and performing redirect processing by: identifying a new seed name that represents a new location of the document; and generating one or more additional allow rules on the new seed name to enlarge the web crawl space. 3. The method of claim 2 , further comprising: adding the one or more additional allow rules to the set of allow rules; and crawling the web crawl space defined by the set of allow rules. | 0.934813 |
9. A system for automated document recognition, identification and data extraction, the system comprising: a processor; a memory coupled to the processor, the memory storing instructions, the instructions being executable by the processor to perform a method, the method comprising: receiving a video stream associated with a document associated with a user, detecting an image of the document in the video stream, the detecting including recognizing a shape corresponding to the identification document overall, improving the detected image of the document in the video stream by adjusting colors, adjusting brightness, and removing blurring, extracting the detected image of the document from the video stream, the image being a still image, analyzing the extracted image using optical character recognition to produce image data, the image data including text zones, each of the text zones being associated with one or more distances to other text zones and one or more borders of the document, the one or more distances being determined using coordinates, comparing the extracted image to one or more document templates using the image data, determining a document template having a highest degree of coincidence with the extracted image using the comparison, matching the text zones of the image with text zones of the document template to determine a type of data in each text zone, and structuring the data into a standard format to obtain structured data; and a database communicatively coupled to the processor, the database storing the one or more document templates. | 9. A system for automated document recognition, identification and data extraction, the system comprising: a processor; a memory coupled to the processor, the memory storing instructions, the instructions being executable by the processor to perform a method, the method comprising: receiving a video stream associated with a document associated with a user, detecting an image of the document in the video stream, the detecting including recognizing a shape corresponding to the identification document overall, improving the detected image of the document in the video stream by adjusting colors, adjusting brightness, and removing blurring, extracting the detected image of the document from the video stream, the image being a still image, analyzing the extracted image using optical character recognition to produce image data, the image data including text zones, each of the text zones being associated with one or more distances to other text zones and one or more borders of the document, the one or more distances being determined using coordinates, comparing the extracted image to one or more document templates using the image data, determining a document template having a highest degree of coincidence with the extracted image using the comparison, matching the text zones of the image with text zones of the document template to determine a type of data in each text zone, and structuring the data into a standard format to obtain structured data; and a database communicatively coupled to the processor, the database storing the one or more document templates. 11. The system of claim 9 , wherein the matching is based on the coordinates of the text zones. | 0.668251 |
9. A structured data storage device comprising: a storage means for storing a structured data file having structured data into a storage medium to be removably attached to the structured data storage device, and store an index file having index information for use to search the structured data into the storage medium; a detecting means for detecting whether or not the stored structured data file has been updated by an external device; and an index information generating means for analyzing, when the detecting means detects that the stored structured data file has been updated, the updated structured data file, generate new index information relating to the structured data included in the updated structured data file, and update the stored index file using the new index information, wherein the structured data has a plurality of data units identically configured with hierarchically structured elements, each data unit comprises a reference element positioned at the top of the respective data units, and one or more search elements positioned below the reference element, the index information comprises a first index component and a second index component, the first index component links together information which identifies the reference element, information which identifies the structured data file having the structured data comprising the identified reference element, information which identifies the position of the identified reference element in the structured data included in the identified structured data file, information which identifies respective search elements positioned below the identified reference element, and content information of the respective search elements, the second index component links together information which identifies respective search elements, content information of the respective search elements, and information which identifies a reference element having the respective search elements, the index information generating means detects a reference element included in the structured data in the updated structured data file, analyzes the updated structured data file by detecting a search element positioned below the detected reference element, and generates the new index information comprising a new first index component and a new second index component, the index information generating means links together, as the new first index component, information which identifies uniquely discriminates the detected reference element, information which identifies the updated structured data file having the structured data comprising the identified reference element, information which identifies the position of the identified reference element in the structured data included in the identified structured data file, information which identifies the detected search element positioned below the identified reference element, and content information of the detected search element, and the index information generating means links together, as the new second index component, information which identifies the detected search element, content information of the respective search elements, and information which identifies the detected reference element having the respective search elements. | 9. A structured data storage device comprising: a storage means for storing a structured data file having structured data into a storage medium to be removably attached to the structured data storage device, and store an index file having index information for use to search the structured data into the storage medium; a detecting means for detecting whether or not the stored structured data file has been updated by an external device; and an index information generating means for analyzing, when the detecting means detects that the stored structured data file has been updated, the updated structured data file, generate new index information relating to the structured data included in the updated structured data file, and update the stored index file using the new index information, wherein the structured data has a plurality of data units identically configured with hierarchically structured elements, each data unit comprises a reference element positioned at the top of the respective data units, and one or more search elements positioned below the reference element, the index information comprises a first index component and a second index component, the first index component links together information which identifies the reference element, information which identifies the structured data file having the structured data comprising the identified reference element, information which identifies the position of the identified reference element in the structured data included in the identified structured data file, information which identifies respective search elements positioned below the identified reference element, and content information of the respective search elements, the second index component links together information which identifies respective search elements, content information of the respective search elements, and information which identifies a reference element having the respective search elements, the index information generating means detects a reference element included in the structured data in the updated structured data file, analyzes the updated structured data file by detecting a search element positioned below the detected reference element, and generates the new index information comprising a new first index component and a new second index component, the index information generating means links together, as the new first index component, information which identifies uniquely discriminates the detected reference element, information which identifies the updated structured data file having the structured data comprising the identified reference element, information which identifies the position of the identified reference element in the structured data included in the identified structured data file, information which identifies the detected search element positioned below the identified reference element, and content information of the detected search element, and the index information generating means links together, as the new second index component, information which identifies the detected search element, content information of the respective search elements, and information which identifies the detected reference element having the respective search elements. 12. The structured data storage device according to claim 9 , further comprising an update means for updating elements of the structured data, in accordance with externally specified update information, wherein the update means: specifies a search element of a candidate to be updated, content information of the search element of the candidate to be updated, element selection condition which specifies the search element of the candidate to be updated, in accordance with the externally specified update information; extracts, from the second index component, a pair of information which identifies the specified search element and content information of the specified search element; extracts, from the second index component, information which is associated with the extracted pair and identifies the reference element; extracts, from the first index component, information which identifies the structured data file, the information being associated with the information which identifies the extracted reference element, and information which identifies the position of the reference element; reads the reference element from the structured data file identified by the information which identifies the extracted structured data file and the information which identifies the position of the extracted reference element; replaces the content of the element which is positioned below the read reference element and satisfies the element selection condition, in accordance with the contents to be updated; and causes the storage means to store again the structured data file with the elements already updated, into the storage medium, and causes the index information generating means to analyze the structured data file with the elements already updated to update the index information. | 0.528978 |
19. A system for compiling a unique sample code, comprising at least one sample code template generator for defining at least one sample code template comprising multiple sample code segments to be used for building a sample code for specific web content, said sample code segments at least comprising a sample owner identifying code segment, and a sample identifying code segment; at least one sample code segment specification module connected to said template generator for specifying the content of the sample code segments defined by means of the code template generator, wherein the sample owner identifying code segment is specified by an Internet address, in particular an IP address and/or a domain name, of an owner of the specific web content; at least one code generator connected to said template generator and said specification module for stringing the specified sample code segments to form the sample code; and at least one database for storing at least one cross-reference between a generated sample code and a digital path to a digital location via which access can be gained to the specific web content and providing the generated sample code with a time stamp indicating a time dependency of the specific web content, wherein the generated sample code and the digital path are mutually distinctive. | 19. A system for compiling a unique sample code, comprising at least one sample code template generator for defining at least one sample code template comprising multiple sample code segments to be used for building a sample code for specific web content, said sample code segments at least comprising a sample owner identifying code segment, and a sample identifying code segment; at least one sample code segment specification module connected to said template generator for specifying the content of the sample code segments defined by means of the code template generator, wherein the sample owner identifying code segment is specified by an Internet address, in particular an IP address and/or a domain name, of an owner of the specific web content; at least one code generator connected to said template generator and said specification module for stringing the specified sample code segments to form the sample code; and at least one database for storing at least one cross-reference between a generated sample code and a digital path to a digital location via which access can be gained to the specific web content and providing the generated sample code with a time stamp indicating a time dependency of the specific web content, wherein the generated sample code and the digital path are mutually distinctive. 21. The system according to claim 19 , wherein the system further comprises at least one service module for administering the system for issuing a code. | 0.525239 |
1. A computer-implemented method comprising: providing a plurality of transcribed words from a word lattice for display on a computing device; in response to receiving an indication that a particular transcribed word has been selected, providing for display on the computing device a particular alternate phrase from the word lattice, wherein the particular alternate phrase includes alternate words that correspond to (i) the particular transcribed word and (ii) at least one transcribed word preceding the particular transcribed word; and in response to receiving an indication that the particular alternate phrase has been selected, replacing, with the particular transcribed phrase, (i) the particular transcribed word and (ii) the at least one transcribed word preceding the particular transcribed word. | 1. A computer-implemented method comprising: providing a plurality of transcribed words from a word lattice for display on a computing device; in response to receiving an indication that a particular transcribed word has been selected, providing for display on the computing device a particular alternate phrase from the word lattice, wherein the particular alternate phrase includes alternate words that correspond to (i) the particular transcribed word and (ii) at least one transcribed word preceding the particular transcribed word; and in response to receiving an indication that the particular alternate phrase has been selected, replacing, with the particular transcribed phrase, (i) the particular transcribed word and (ii) the at least one transcribed word preceding the particular transcribed word. 7. The method of claim 1 , wherein the word lattice is one of: a hierarchical word lattice, or a finite state transducer word lattice. | 0.743189 |
8. A computer-implemented method of aligning fragments of a first text in a first language with corresponding fragments of a second text, which is a translation of the first text into a second language, comprising: preliminarily dividing the first and second texts into fragments; generating a hypothesis about correspondence between at least first fragment in the first text and at least second fragment in the second text; performing a lexico-morphological analysis of the first and the second fragments using linguistic descriptions; performing a syntactic analysis of the first and the second fragments using linguistic descriptions and generating a syntactic structure for the first fragment and a syntactic structure for the second fragment; generating a semantic structure for the first fragment and a semantic structure for the second fragment, wherein the semantic structures are directional acyclic graphs with nodes that are assigned elements of semantic hierarchy; estimating the degree of correspondence between the semantic structure for the first fragment and the semantic structure for the second fragment, wherein estimating the degree of correspondence between the semantic structures includes identifying correspondence of tree structure, deep slots, non-tree links, and semantic classes; and if the degree of correspondence between the semantic structure for the first fragment and the semantic structure for the second fragment satisfies a predetermined threshold, saving the generated syntactic and semantic structures for the first fragment in connection with the first fragment; and saving the generated syntactic and semantic structures for the second fragment in connection with the second fragment. | 8. A computer-implemented method of aligning fragments of a first text in a first language with corresponding fragments of a second text, which is a translation of the first text into a second language, comprising: preliminarily dividing the first and second texts into fragments; generating a hypothesis about correspondence between at least first fragment in the first text and at least second fragment in the second text; performing a lexico-morphological analysis of the first and the second fragments using linguistic descriptions; performing a syntactic analysis of the first and the second fragments using linguistic descriptions and generating a syntactic structure for the first fragment and a syntactic structure for the second fragment; generating a semantic structure for the first fragment and a semantic structure for the second fragment, wherein the semantic structures are directional acyclic graphs with nodes that are assigned elements of semantic hierarchy; estimating the degree of correspondence between the semantic structure for the first fragment and the semantic structure for the second fragment, wherein estimating the degree of correspondence between the semantic structures includes identifying correspondence of tree structure, deep slots, non-tree links, and semantic classes; and if the degree of correspondence between the semantic structure for the first fragment and the semantic structure for the second fragment satisfies a predetermined threshold, saving the generated syntactic and semantic structures for the first fragment in connection with the first fragment; and saving the generated syntactic and semantic structures for the second fragment in connection with the second fragment. 13. The method of claim 8 further comprising indexing fragments of the first text and indexing fragments of the second text in accordance with determined correspondence of the fragments of the first and the second texts. | 0.535828 |
1. A method of preprocessing an image for optical character recognition (OCR), wherein the image comprises a plurality of columns, each column of the plurality of columns comprising at least one of Arabic text and non-text items, the method comprising: determining a plurality of components associated with at least one of the Arabic text and the non-text items of the plurality of columns, wherein a component comprises a series of connected pixels; calculating a line height and a column spacing associated with the plurality of components; associating at least one component of the plurality of components with a column of the plurality of columns based on at least one of the line height and the column spacing; calculating a first set of characteristic parameters for each column of the plurality of columns; and merging the plurality of components of each column of the plurality of columns based on the first set of characteristic parameters to form at least one of at least one Arabic sub-word and at least one Arabic word, wherein the first set of characteristic parameters is at least one of a line height associated with each column, a word spacing associated with each column, a line spacing associated with each column, a number of pixels corresponding to each component, a width of each component, a height of each component, coordinates of each component, density of each component, and aspect ratio of each component and wherein calculating the line spacing associated with each column comprises: creating a histogram of a plurality of horizontal projections of the plurality of components associated with each column, wherein a horizontal projection of the plurality of horizontal projections indicates a number of pixels associated with the plurality of components corresponding to each sweep of the raster scan; calculating an average distance between two consecutive maximum horizontal projections; and computing the line spacing based on the average distance. | 1. A method of preprocessing an image for optical character recognition (OCR), wherein the image comprises a plurality of columns, each column of the plurality of columns comprising at least one of Arabic text and non-text items, the method comprising: determining a plurality of components associated with at least one of the Arabic text and the non-text items of the plurality of columns, wherein a component comprises a series of connected pixels; calculating a line height and a column spacing associated with the plurality of components; associating at least one component of the plurality of components with a column of the plurality of columns based on at least one of the line height and the column spacing; calculating a first set of characteristic parameters for each column of the plurality of columns; and merging the plurality of components of each column of the plurality of columns based on the first set of characteristic parameters to form at least one of at least one Arabic sub-word and at least one Arabic word, wherein the first set of characteristic parameters is at least one of a line height associated with each column, a word spacing associated with each column, a line spacing associated with each column, a number of pixels corresponding to each component, a width of each component, a height of each component, coordinates of each component, density of each component, and aspect ratio of each component and wherein calculating the line spacing associated with each column comprises: creating a histogram of a plurality of horizontal projections of the plurality of components associated with each column, wherein a horizontal projection of the plurality of horizontal projections indicates a number of pixels associated with the plurality of components corresponding to each sweep of the raster scan; calculating an average distance between two consecutive maximum horizontal projections; and computing the line spacing based on the average distance. 3. The method of claim 1 , wherein the image is obtained by filtering salt and pepper noise. | 0.6335 |
19. The system of claim 14 , wherein the user group configuration settings specify an authentication method to authenticate the users in the user group. | 19. The system of claim 14 , wherein the user group configuration settings specify an authentication method to authenticate the users in the user group. 20. The method of claim 19 , wherein sending the user group container document over a public network to each of a plurality of client devices comprises authenticating users of the client devices according to the authentication method. | 0.949185 |
1. A computer implemented method for identifying a sketching matrix used by a linear sketch comprising: receiving, by a processor, an initial output of the linear sketch; generating, by the processor, a query vector; inputting, by the processor, the query vector into the linear sketch; receiving, by the processor, an revised output of the linear sketch based on inputting the query vector; iteratively repeating the steps of generating the query vector, inputting the query vector into the linear sketch, and receiving an revised output of the linear sketch based on inputting the query vector until the sketching matrix used by the linear sketch can be identified. | 1. A computer implemented method for identifying a sketching matrix used by a linear sketch comprising: receiving, by a processor, an initial output of the linear sketch; generating, by the processor, a query vector; inputting, by the processor, the query vector into the linear sketch; receiving, by the processor, an revised output of the linear sketch based on inputting the query vector; iteratively repeating the steps of generating the query vector, inputting the query vector into the linear sketch, and receiving an revised output of the linear sketch based on inputting the query vector until the sketching matrix used by the linear sketch can be identified. 7. The method of claim 1 , wherein the query vector is selected from a multivariate normal distribution N(0,τI n ), where τI n is a covariance matrix, which is a scalar τtimes the identity matrix I n . | 0.562081 |
4. The storage medium of claim 3 , wherein determining that a term of the query phrase is a lexical synonym of a corresponding term of the synonym phrase or shares meaning with the corresponding term of the synonym phrase includes determining that the query term and the term of the synonym phrase share a common stem. | 4. The storage medium of claim 3 , wherein determining that a term of the query phrase is a lexical synonym of a corresponding term of the synonym phrase or shares meaning with the corresponding term of the synonym phrase includes determining that the query term and the term of the synonym phrase share a common stem. 5. The storage medium of claim 4 , wherein lexically comparing the term of the query phrase and the term of the synonym phrase includes one or more of the following: removing punctuation and/or spacing from a term; using an edit-distance technique to determine whether a substantial number of characters match between the term of the query phrase and the term of the synonym phrase; removing diacritical marks from a term; using a pseudostem technique to determine whether the term of the query phrase and the term of the synonym phrase share a common prefix; using language-specific linguistic rules to facilitate detecting gender and/or number stemming across the term of the query phrase and the term of the synonym phrase; identifying an abbreviation for a term; stripping vowels from a term; or identifying non-lexical synonyms for the term of the query phrase or the term of the synonym phrase. | 0.573958 |
14. A non-transitory computer readable medium having stored thereon instructions for translating user keywords into semantic queries the instructions comprising executable code which, when executed by at least one processor, causes the processor to: receive keywords; search the conceptual model to identify one or more concepts relevant to the keywords; transform at least a portion of the conceptual model into a connected graph; generate at least one path through the connected graph, the at least one path connecting the one or more concepts; identify and rank facets that support incremental user navigation from nodes of convergence in the at least one path, wherein the facets are generated at least in part by indexing a number of distinct values for attributes of the one or more concepts; generate at least one structured semantic query from the at least one path with the identified and ranked facets; and execute the at least one structure semantic query on a semantic repository. | 14. A non-transitory computer readable medium having stored thereon instructions for translating user keywords into semantic queries the instructions comprising executable code which, when executed by at least one processor, causes the processor to: receive keywords; search the conceptual model to identify one or more concepts relevant to the keywords; transform at least a portion of the conceptual model into a connected graph; generate at least one path through the connected graph, the at least one path connecting the one or more concepts; identify and rank facets that support incremental user navigation from nodes of convergence in the at least one path, wherein the facets are generated at least in part by indexing a number of distinct values for attributes of the one or more concepts; generate at least one structured semantic query from the at least one path with the identified and ranked facets; and execute the at least one structure semantic query on a semantic repository. 19. The non-transitory computer readable medium of claim 14 , wherein the at least one path expansion rule is a self-loop, a path-loop, or a subsumed-loop or requires applying cardinalities to relations between concepts. | 0.87181 |
17. A system for processing natural language text using at least one computer, the system Comprising a run time engine in a first instance, comprising a conversion module, data-driven and rule-based annotators, a set of standard components, ontologies, tokenizers, structure recolgnition components, and developer created processing scripts; a development environment element having a development management system, a document management system, a development executive component, at least one annotation interface, a document structure system, an ontology management system, a development scripting language interpreter, where the development scripting language interpreter implements a first set developer created processing scripts and workflows, and a semantic exploration component; and a feedback module with at least one client component in communication with the runtime engine in the first instance and a first logging component for collecting user feedback for all applications in communication with the development environment. | 17. A system for processing natural language text using at least one computer, the system Comprising a run time engine in a first instance, comprising a conversion module, data-driven and rule-based annotators, a set of standard components, ontologies, tokenizers, structure recolgnition components, and developer created processing scripts; a development environment element having a development management system, a document management system, a development executive component, at least one annotation interface, a document structure system, an ontology management system, a development scripting language interpreter, where the development scripting language interpreter implements a first set developer created processing scripts and workflows, and a semantic exploration component; and a feedback module with at least one client component in communication with the runtime engine in the first instance and a first logging component for collecting user feedback for all applications in communication with the development environment. 20. The system according to claim 17 where the development executive component comprises the runtime engine in a second instance. | 0.584687 |
1. A method programmed in a non-transitory memory of a device comprising: a. automatically fact checking target information by comparing the target information with source information to generate a result, wherein the target information comprises web page information or social networking information, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and b. automatically affecting the target information and presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein searching for the exact match begins searching the source information located on a fastest access time hardware device and continues to slower access time hardware devices; wherein utilizing pattern matching begins utilizing the source information located on the fastest access time hardware device and continues to the slower access time hardware devices; and wherein the natural language search begins searching the source information located on the fastest access time hardware device and continues to the slower access time hardware devices, wherein searching for the exact match begins searching the source information classified by a plurality of keywords found in the target information, then using the source information classified by a single keyword found in the target information, and then using the source information classified by keywords related to the keywords found in the target information; wherein utilizing pattern matching begins utilizing the source information classified by the plurality of keywords found in the target information, then using the source information classified by the single keyword found in the target information, and then using the source information classified by the keywords related to the keywords found in the target information; and wherein the natural language search begins searching the source information classified by the plurality of keywords found in the target information, then using the source information classified by the single keyword found in the target information, and then using the source information classified by the keywords related to the keywords found in the target information. | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically fact checking target information by comparing the target information with source information to generate a result, wherein the target information comprises web page information or social networking information, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and b. automatically affecting the target information and presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein searching for the exact match begins searching the source information located on a fastest access time hardware device and continues to slower access time hardware devices; wherein utilizing pattern matching begins utilizing the source information located on the fastest access time hardware device and continues to the slower access time hardware devices; and wherein the natural language search begins searching the source information located on the fastest access time hardware device and continues to the slower access time hardware devices, wherein searching for the exact match begins searching the source information classified by a plurality of keywords found in the target information, then using the source information classified by a single keyword found in the target information, and then using the source information classified by keywords related to the keywords found in the target information; wherein utilizing pattern matching begins utilizing the source information classified by the plurality of keywords found in the target information, then using the source information classified by the single keyword found in the target information, and then using the source information classified by the keywords related to the keywords found in the target information; and wherein the natural language search begins searching the source information classified by the plurality of keywords found in the target information, then using the source information classified by the single keyword found in the target information, and then using the source information classified by the keywords related to the keywords found in the target information. 11. The method of claim 1 further comprising utilizing a plurality of fact checking implementations initially, wherein each fact checking implementation utilizes a different set of source information, and comparing results of each fact checking implementation, and iteratively eliminating a fact checking implementation of the plurality of fact checking implementations with a lowest confidence score until a single fact checking implementation remains. | 0.582583 |
13. A system for updating a summary page of a text file, comprising: a computer system having a memory, wherein the text file is loaded in the memory in accordance with a software application of a client device, wherein the software application is at least one member of a group comprising: a word processing application and a notes application; and a summary page update module loaded in the memory in accordance with the software application of the client device, wherein the summary page update module is arranged to: receive a query on the software application of the client device for accessing categories of data of the text file stored in accordance with the software application of the client device; identify categories of data in the text file, wherein the categories of data are identified by analyzing metadata stored with the text file, wherein the categories of data are determined by the received query, wherein the identified categories of data are stored in a dynamic content container stored with the text file, wherein the dynamic container causes a continuous synchronous relationship between the text file and the summary page; display the identified categories of data on the summary page, wherein modification to the query of the text file results in new identified categories of data being displayed on the summary page, wherein the summary page includes a plurality of links, wherein each link indicates a portion of the text file that is displayed on the summary page, wherein selection of one of the links causes navigation to the portion of the text file that is displayed on the summary page and is indicate by the selected link; and upon receiving a user input that modifies the text file in relation to one of the categories identified in the summary page, automatically updating the dynamic container with the modification to cause the dynamic container to automatically update the summary page with the modification. | 13. A system for updating a summary page of a text file, comprising: a computer system having a memory, wherein the text file is loaded in the memory in accordance with a software application of a client device, wherein the software application is at least one member of a group comprising: a word processing application and a notes application; and a summary page update module loaded in the memory in accordance with the software application of the client device, wherein the summary page update module is arranged to: receive a query on the software application of the client device for accessing categories of data of the text file stored in accordance with the software application of the client device; identify categories of data in the text file, wherein the categories of data are identified by analyzing metadata stored with the text file, wherein the categories of data are determined by the received query, wherein the identified categories of data are stored in a dynamic content container stored with the text file, wherein the dynamic container causes a continuous synchronous relationship between the text file and the summary page; display the identified categories of data on the summary page, wherein modification to the query of the text file results in new identified categories of data being displayed on the summary page, wherein the summary page includes a plurality of links, wherein each link indicates a portion of the text file that is displayed on the summary page, wherein selection of one of the links causes navigation to the portion of the text file that is displayed on the summary page and is indicate by the selected link; and upon receiving a user input that modifies the text file in relation to one of the categories identified in the summary page, automatically updating the dynamic container with the modification to cause the dynamic container to automatically update the summary page with the modification. 14. The system of claim 13 , wherein the metadata is embedded in the text file. | 0.528056 |
17. The non-transitory computer-readable medium of claim 11 , further including instructions that when executed by the processing unit, cause the processing unit to display the merged context-based search results by displaying a context-specific augmentation that relates the merged context-based search results to a current context associated with the application program. | 17. The non-transitory computer-readable medium of claim 11 , further including instructions that when executed by the processing unit, cause the processing unit to display the merged context-based search results by displaying a context-specific augmentation that relates the merged context-based search results to a current context associated with the application program. 18. The computer-readable medium of claim 17 , wherein the context-specific augmentation comprises icons associated with tools that are specific to the application program and appear within resources listed in the merged context-based search results. | 0.812113 |
1. A computer-implemented method comprising: processing a query to identify item listings that satisfy the query, each item listing comprising data representing one or more attributes of a product or service offered for sale; assigning a ranking score to each item listing that satisfies the query, the ranking score derived as the product of two or more component scores including a first component score representing a measure of relevance between search terms in a search query and the item listing, the second component score being independent of the query and representing a measure of quality for the item listing, the measure of quality being based at least in part on at least one of (i) an attribute of the item listing determinable at a time of listing, or (ii) an observed sales performance of the item listing or an item listing similar thereto; and presenting the item listings that satisfy the query in a search results page, the item listings positioned in the search results page based on the ranking score assigned to each item listing. | 1. A computer-implemented method comprising: processing a query to identify item listings that satisfy the query, each item listing comprising data representing one or more attributes of a product or service offered for sale; assigning a ranking score to each item listing that satisfies the query, the ranking score derived as the product of two or more component scores including a first component score representing a measure of relevance between search terms in a search query and the item listing, the second component score being independent of the query and representing a measure of quality for the item listing, the measure of quality being based at least in part on at least one of (i) an attribute of the item listing determinable at a time of listing, or (ii) an observed sales performance of the item listing or an item listing similar thereto; and presenting the item listings that satisfy the query in a search results page, the item listings positioned in the search results page based on the ranking score assigned to each item listing. 11. The computer-implemented method of claim 1 , wherein, in addition to the first and second component scores, the ranking score is derived as the product of a third component score representing a business rules score, the business rules score i) derived by evaluating one or more business rules, and ii) resulting in a promotion or demotion of an item listing. | 0.579639 |
7. A data gathering system in accordance with claim 2 and further including means for operating said computer system to remove any of said definitions from said computer system when supplied with the designator that accompanied the definition into the system, said removal means using the directory to locate the portion of said definition connected within a linkage, said removal means including means for re-establishing the linkage from which said definition is removed, and said removal means including means for removing the designator for a variable from the directory. | 7. A data gathering system in accordance with claim 2 and further including means for operating said computer system to remove any of said definitions from said computer system when supplied with the designator that accompanied the definition into the system, said removal means using the directory to locate the portion of said definition connected within a linkage, said removal means including means for re-establishing the linkage from which said definition is removed, and said removal means including means for removing the designator for a variable from the directory. 8. A data gathering system in accordance with claim 7 and further including means for operating said computer system to maintain a record of all locations previously occupied by definitions which have been removed, said record maintaining means cooperating with said acceptance and storing means to reassign previously occupied locations to definitions newly entered into the computer system. | 0.829492 |
1. A method of sequence recognition, comprising the steps of: receiving an input sequence; converting the input sequence to an input sequence SSM Sequence Model (SSM) Matrix; comparing the input sequence SSM Matrix to a plurality of known SSM Matrices representing a plurality of known sequences; matching the input sequence to the known sequence based on the step of comparing. | 1. A method of sequence recognition, comprising the steps of: receiving an input sequence; converting the input sequence to an input sequence SSM Sequence Model (SSM) Matrix; comparing the input sequence SSM Matrix to a plurality of known SSM Matrices representing a plurality of known sequences; matching the input sequence to the known sequence based on the step of comparing. 31. The method of claim 1 adapted for spell checking, wherein the step of receiving the input sequence comprises the step of receiving a misspelled textual sequence, and wherein the step of comparing the input sequence SSM Matrix to a plurality of known SSM Matrices representing a plurality of known sequences comprises the step of comparing the input sequence SSM Matrix to a plurality of known SSM Matrices representing a plurality of known sequences for correctly spelled textual sequences. | 0.755212 |
19. The system of claim 18 , wherein the processing unit is further operative to, in response to pasting the spreadsheet element in the target document, display a recovery action user interface having at least one selectable recovery action. | 19. The system of claim 18 , wherein the processing unit is further operative to, in response to pasting the spreadsheet element in the target document, display a recovery action user interface having at least one selectable recovery action. 20. The system of claim 19 , wherein the processing unit is further operative to, in response to receiving a recovery action selection from the recovery action user interface: remove the spreadsheet element from the target document, and paste the spreadsheet element as a table with a third set of formatting properties corresponding to the target document applied thereto. | 0.885241 |
10. An intra-sentence boundary extracting system according to claim 8, wherein said boundary position data output means comprises: a maximum value extracting unit, operatively connected to said neural network, for extracting a maximum value of the boundary position data output by the output layer of said neural network; and an input pattern generating unit, operatively connected to said inputted word number retrieving means and said neural network, for generating, in response to operation of said neural network, the input pattern using the word numbers output by said inputted word number retrieving means. | 10. An intra-sentence boundary extracting system according to claim 8, wherein said boundary position data output means comprises: a maximum value extracting unit, operatively connected to said neural network, for extracting a maximum value of the boundary position data output by the output layer of said neural network; and an input pattern generating unit, operatively connected to said inputted word number retrieving means and said neural network, for generating, in response to operation of said neural network, the input pattern using the word numbers output by said inputted word number retrieving means. 11. An intra-sentence boundary extracting system according to claim 10, wherein said input pattern generating unit comprises: a word sequence generating unit, operatively connected to said inputted word classifying means, for generating as a word-sequence the n preceding words, the target word and the m succeeding words; and an input control unit, operatively connected to said word sequence generating unit and said neural network, for outputting the input pattern to said neural network using the word-sequence output by said word sequence generating unit. | 0.774783 |
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