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1. A method comprising generating a compact language model, including: receiving, at a computing system including one or more processors, a collection of n-grams, each n-gram having one or more associated parameter values; determining, at the computing system, a fingerprint for each n-gram of the collection of n-grams; identifying, at the computing system, locations in an array for each n-gram using a plurality of hash functions; and encoding, at the computing system, the one or more parameter values associated with each n-gram in the identified array locations as a function of corresponding array values and the fingerprint for the n-gram, where identifying locations in the array further comprises: building an array having a specified number of locations; identifying a plurality of locations corresponding to each n-gram in the collection; identifying a first n-gram-location pair corresponding to a first n-gram associated with a first location of degree one, where the first location is of degree one when no other n-gram of the collection of n-grams is associated with the first location; and removing the first n-gram-location pair such that the n-gram no longer corresponds to any other locations in the array such that one or more other locations in the array are of degree one.
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1. A method comprising generating a compact language model, including: receiving, at a computing system including one or more processors, a collection of n-grams, each n-gram having one or more associated parameter values; determining, at the computing system, a fingerprint for each n-gram of the collection of n-grams; identifying, at the computing system, locations in an array for each n-gram using a plurality of hash functions; and encoding, at the computing system, the one or more parameter values associated with each n-gram in the identified array locations as a function of corresponding array values and the fingerprint for the n-gram, where identifying locations in the array further comprises: building an array having a specified number of locations; identifying a plurality of locations corresponding to each n-gram in the collection; identifying a first n-gram-location pair corresponding to a first n-gram associated with a first location of degree one, where the first location is of degree one when no other n-gram of the collection of n-grams is associated with the first location; and removing the first n-gram-location pair such that the n-gram no longer corresponds to any other locations in the array such that one or more other locations in the array are of degree one. 2. The method of claim 1 , further comprising: sequentially identifying additional locations of degree one and removing the corresponding n-gram-location pairs until each n-gram of the collection is matched with a unique location in the array.
| 0.514915 |
12. The method of claim 1 , further comprising dividing the text content into the plurality of text parts such that the number of text parts is as small as possible without reducing the portion of the text content covered by the text parts.
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12. The method of claim 1 , further comprising dividing the text content into the plurality of text parts such that the number of text parts is as small as possible without reducing the portion of the text content covered by the text parts. 13. The method of claim 12 , wherein the number of text parts that start or end with numeric, neutral or whitespace characters and have a mismatch between the intrinsic text direction and the declared text direction is as small as possible without reducing the portion of the text content covered by the plurality of text parts.
| 0.877881 |
1. A method comprising, by one or more processors associated with one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the plurality of nodes corresponding to a plurality of users associated with an online social network, respectively; identifying a plurality of non-overlapping clusters in the social graph using graph clustering, each cluster comprising a discrete set of nodes from the plurality of nodes; providing a treatment to at least a first set of users and a second set of users, the first and second sets of users corresponding to a first set of clusters and a second set of clusters of the plurality of clusters, respectively, the first set of clusters being discrete from the second set of clusters; and determining, for each of at least the first and second sets of users, a treatment effect of the treatment on the users of the set of users based on a network exposure to the treatment for each user, wherein, for each respective cluster, the network exposure of the nodes in the cluster is absolute k-neighborhood exposure, absolute k-core exposure, fractional q-neighborhood exposure, or fractional q-core exposure.
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1. A method comprising, by one or more processors associated with one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the plurality of nodes corresponding to a plurality of users associated with an online social network, respectively; identifying a plurality of non-overlapping clusters in the social graph using graph clustering, each cluster comprising a discrete set of nodes from the plurality of nodes; providing a treatment to at least a first set of users and a second set of users, the first and second sets of users corresponding to a first set of clusters and a second set of clusters of the plurality of clusters, respectively, the first set of clusters being discrete from the second set of clusters; and determining, for each of at least the first and second sets of users, a treatment effect of the treatment on the users of the set of users based on a network exposure to the treatment for each user, wherein, for each respective cluster, the network exposure of the nodes in the cluster is absolute k-neighborhood exposure, absolute k-core exposure, fractional q-neighborhood exposure, or fractional q-core exposure. 13. The method of claim 1 , wherein the treatment is a particular product or feature of the online social network.
| 0.72357 |
2. The method as in claim 1 wherein the command input which causes the turning on of large vocabulary speech recognition is a non-acoustic input.
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2. The method as in claim 1 wherein the command input which causes the turning on of large vocabulary speech recognition is a non-acoustic input. 14. The method as in claim 2 wherein: said method provides a user interface having a plurality of speech mode selection buttons, which are either hardware or software buttons, each for selecting a respective one from a plurality of different speech recognition modes, which are distinguished from one another by characteristics other than recognition duration and which are all available for selection by the user at one time; and the non-acoustic input which causes the turning on of the large vocabulary speech recognition is the pressing of one of said buttons; and the method responds to the pressing of a given speech mode button by turning on the large vocabulary speech recognition in the given button's associated mode and then subsequently automatically turning off said recognition in said mode.
| 0.72953 |
1. A method for performing a search of target documents based on a reference document received as input, the method comprising: executing a reference search, based on the reference document received as input, using search criteria to select and score a set of target documents against the reference document, each target document given a reference score representing similarity between the target document and the reference document, the set of target documents with the reference scores representing a reference search result set; executing a reverse search, based on the target documents in the reference search result set as input, using search criteria to select and score the reference document against each of the target documents in the reference search result set, each target document given a reverse score representing similarity between the reference document and the target document, the set of target documents with the reverse scores representing a reverse search result set; and combining the reference score and reverse score for respective ones of the target documents using a secondary combining function, each target document given a secondary combined score based on the combining that is a function of the reference score and the reverse score, the set of target documents with the secondary combined scores representing a secondary result set.
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1. A method for performing a search of target documents based on a reference document received as input, the method comprising: executing a reference search, based on the reference document received as input, using search criteria to select and score a set of target documents against the reference document, each target document given a reference score representing similarity between the target document and the reference document, the set of target documents with the reference scores representing a reference search result set; executing a reverse search, based on the target documents in the reference search result set as input, using search criteria to select and score the reference document against each of the target documents in the reference search result set, each target document given a reverse score representing similarity between the reference document and the target document, the set of target documents with the reverse scores representing a reverse search result set; and combining the reference score and reverse score for respective ones of the target documents using a secondary combining function, each target document given a secondary combined score based on the combining that is a function of the reference score and the reverse score, the set of target documents with the secondary combined scores representing a secondary result set. 20. The method of claim 1 , wherein the search performed is a job or job candidate search.
| 0.742967 |
15. A non-transitory computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: identifying, in a domain-independent manner, a dialog act for an independent clause of a speech recognizer output; identifying, in a domain-dependent manner, an object within the independent clause; and recursively generating, for each sub-independent clause within the independent clause, a semantic representation using the dialog act and the object of the independent clause.
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15. A non-transitory computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: identifying, in a domain-independent manner, a dialog act for an independent clause of a speech recognizer output; identifying, in a domain-dependent manner, an object within the independent clause; and recursively generating, for each sub-independent clause within the independent clause, a semantic representation using the dialog act and the object of the independent clause. 17. The non-transitory computer-readable storage device of claim 15 , the computer-readable storage device having additional instructions stored which result in the operations further comprising: identifying, in the domain-dependent manner, an action within the independent clause, wherein recursively generating the semantic representation further comprises using the action.
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42. An apparatus according to claim 41, wherein the utility functions include a function to set a trigger event.
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42. An apparatus according to claim 41, wherein the utility functions include a function to set a trigger event. 44. An apparatus according to claim 42, wherein the utility functions include a function to determine whether an event is set.
| 0.956913 |
1. A computer-readable storage medium having computer-executable instructions for causing a computer to perform steps comprising: providing an object model for transactional memory, wherein transactional memory is a concurrency control for controlling access to shared memory in concurrent computing, the object model allowing transaction syntax to be separated from program flow; and allowing memory transaction objects created using the object model to live beyond an instantiating execution scope, thereby allowing additional properties about the memory transaction to be manipulated.
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1. A computer-readable storage medium having computer-executable instructions for causing a computer to perform steps comprising: providing an object model for transactional memory, wherein transactional memory is a concurrency control for controlling access to shared memory in concurrent computing, the object model allowing transaction syntax to be separated from program flow; and allowing memory transaction objects created using the object model to live beyond an instantiating execution scope, thereby allowing additional properties about the memory transaction to be manipulated. 5. The computer-readable storage medium of claim 1 , wherein the object model provides a constructor for creating a top level transaction.
| 0.548387 |
1. A method of generating topic words from at least one seed word and a collection of electronic documents comprising the steps of: a. identifying keywords in each document that are indicative of the topic of the document; b. evaluating the relevance of each of the documents to the at least one seed word; c. identifying at least one key topic document that is relevant to the at least one seed word; d. selecting a subset of the documents, referred to as topic documents, by an iterative process starting with the selection of the at least one key topic document and then selecting other documents if their keywords are sufficiently similar to the keywords contained in the previously selected topic documents; and e. extracting a set of topic words from the topic documents, wherein the steps of the method are performed by a computer processor running software.
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1. A method of generating topic words from at least one seed word and a collection of electronic documents comprising the steps of: a. identifying keywords in each document that are indicative of the topic of the document; b. evaluating the relevance of each of the documents to the at least one seed word; c. identifying at least one key topic document that is relevant to the at least one seed word; d. selecting a subset of the documents, referred to as topic documents, by an iterative process starting with the selection of the at least one key topic document and then selecting other documents if their keywords are sufficiently similar to the keywords contained in the previously selected topic documents; and e. extracting a set of topic words from the topic documents, wherein the steps of the method are performed by a computer processor running software. 9. The method of claim 1 wherein the topic documents include the at least one key topic document and the other topic documents are selected by an algorithm that considers each document, one at a time, in declining order of relevance to the at least one seed word, and selects a document as a topic document if it contains at least a predefined percentage of keywords that occur as keywords of the previously selected topic documents.
| 0.604252 |
1. An apparatus for scanning an executable script object comprising: a digital dictionary configured to store tokens each comprising a possible piece of a uniform resource locator (URL); a script parser configured to: receive an executable script object comprising text, parse the text of the executable script object to find an instance of one of the tokens in the text, continue to parse the text of the executable script object adjacent to the instance of the token to find a syntax element, and construct a candidate URL from the instance of the token and the syntax element; a URL rules detector configured to: store rules for validating URLs, and utilize the stored rules to determine whether the candidate URL is a valid URL.
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1. An apparatus for scanning an executable script object comprising: a digital dictionary configured to store tokens each comprising a possible piece of a uniform resource locator (URL); a script parser configured to: receive an executable script object comprising text, parse the text of the executable script object to find an instance of one of the tokens in the text, continue to parse the text of the executable script object adjacent to the instance of the token to find a syntax element, and construct a candidate URL from the instance of the token and the syntax element; a URL rules detector configured to: store rules for validating URLs, and utilize the stored rules to determine whether the candidate URL is a valid URL. 16. The apparatus of claim 1 , wherein the URL rules detector is further configured to send an object retrieval request to a Website associated with the candidate URL if the candidate URL is a valid URL.
| 0.53203 |
1. A content item retrieval method, the method comprising: determining multiple base locations, wherein determining each base location is based on GPS information or user entry, each base location being a location from which to apply a corresponding criterion distance-determined granularity thresholding for setting a threshold for location similarity in selecting or rejecting target items for content item retrieval, wherein criterion distance-determined granularity thresholding is applied for each base location of the multiple base locations separately based on differences in distance between farther locations being less important than between equally distant closer locations, further wherein the farther in distance moved from a corresponding base location of the multiple base locations, the less important, in terms of determining similarity, are differences in distance between locations of different content items at the corresponding further distances from the corresponding base location; extracting, as a first anchor item location, location data for a first identified anchor content item, the first identified anchor content item for designating which candidate content items for which a content type is not known or specified by a user are to be retrieved; setting a first threshold based on a criterion distance that candidate content items must meet to be selected, wherein the first threshold comprises an assigned value on a scale of 1 to 10, where a value of 1 indicates a very small distance between a corresponding base location and candidate content item and a value of 10 indicates a great distance between the corresponding base location and candidate content item, and wherein the criterion distance is determined, using criterion distance-determined granularity thresholding, as a distance between the corresponding base location of the multiple base locations and the first anchor item location, further wherein the distance from the corresponding base location is ranked on the scale and as the distance from the corresponding base location increases, then longer distances are encompassed by fewer gradations of the scale, such that distance granularity on the scale is higher for locations geographically closer to the corresponding base location than for locations further away from the corresponding base location; extracting, as a first candidate location, the location data for a first candidate content item, and determining, as a first candidate distance, the distance between the corresponding base location of the multiple base locations and the first candidate location; selecting the first candidate content item as similar for content item retrieval based on (i) the first candidate distance that corresponds to the distance between the corresponding base location of the multiple base locations and the first candidate location and (ii) the first threshold that is based upon the criterion distance, wherein the first candidate content item is selected as being similar to the first identified content item in response to the determined first candidate distance, when compared to the first threshold, being within or with the first threshold; and outputting a selection signal for indicating retrieval of the first candidate content item when the first candidate location of the candidate content item is selected as being similar to the first identified content item for content item retrieval.
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1. A content item retrieval method, the method comprising: determining multiple base locations, wherein determining each base location is based on GPS information or user entry, each base location being a location from which to apply a corresponding criterion distance-determined granularity thresholding for setting a threshold for location similarity in selecting or rejecting target items for content item retrieval, wherein criterion distance-determined granularity thresholding is applied for each base location of the multiple base locations separately based on differences in distance between farther locations being less important than between equally distant closer locations, further wherein the farther in distance moved from a corresponding base location of the multiple base locations, the less important, in terms of determining similarity, are differences in distance between locations of different content items at the corresponding further distances from the corresponding base location; extracting, as a first anchor item location, location data for a first identified anchor content item, the first identified anchor content item for designating which candidate content items for which a content type is not known or specified by a user are to be retrieved; setting a first threshold based on a criterion distance that candidate content items must meet to be selected, wherein the first threshold comprises an assigned value on a scale of 1 to 10, where a value of 1 indicates a very small distance between a corresponding base location and candidate content item and a value of 10 indicates a great distance between the corresponding base location and candidate content item, and wherein the criterion distance is determined, using criterion distance-determined granularity thresholding, as a distance between the corresponding base location of the multiple base locations and the first anchor item location, further wherein the distance from the corresponding base location is ranked on the scale and as the distance from the corresponding base location increases, then longer distances are encompassed by fewer gradations of the scale, such that distance granularity on the scale is higher for locations geographically closer to the corresponding base location than for locations further away from the corresponding base location; extracting, as a first candidate location, the location data for a first candidate content item, and determining, as a first candidate distance, the distance between the corresponding base location of the multiple base locations and the first candidate location; selecting the first candidate content item as similar for content item retrieval based on (i) the first candidate distance that corresponds to the distance between the corresponding base location of the multiple base locations and the first candidate location and (ii) the first threshold that is based upon the criterion distance, wherein the first candidate content item is selected as being similar to the first identified content item in response to the determined first candidate distance, when compared to the first threshold, being within or with the first threshold; and outputting a selection signal for indicating retrieval of the first candidate content item when the first candidate location of the candidate content item is selected as being similar to the first identified content item for content item retrieval. 8. The method of claim 1 , further comprising: extracting, as a second location, location data for a second identified content item, the second identified content item for designating which additional candidate content items are to be retrieved; and setting the first threshold based on the first criterion distance and also on a second criterion distance, wherein the second criterion distance is determined as a distance between the base location and the second location.
| 0.849332 |
14. One or more computer readable media storing computer executable instructions to perform a method for constructing multi-dimensional vector representations for each document of a set of documents, the method comprising: determining each predicate structure of one or more predicate structures M in each document of the set of documents, said M predicate structures including a predicate and at least one argument; identifying the predicate and the at least one argument in each of said M predicate structures by a predicate key that is an integer representation; determining a fixed number of arguments q for vector construction; constructing an N-dimensional vector representation of each document based upon the predicate and q arguments; and outputting at least one document of the set of documents based upon the constructed N-dimensional vector representation of the at least one document, wherein any predicate structure of said M predicate structures that includes less than q arguments fills unfilled argument positions with a numerical zero.
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14. One or more computer readable media storing computer executable instructions to perform a method for constructing multi-dimensional vector representations for each document of a set of documents, the method comprising: determining each predicate structure of one or more predicate structures M in each document of the set of documents, said M predicate structures including a predicate and at least one argument; identifying the predicate and the at least one argument in each of said M predicate structures by a predicate key that is an integer representation; determining a fixed number of arguments q for vector construction; constructing an N-dimensional vector representation of each document based upon the predicate and q arguments; and outputting at least one document of the set of documents based upon the constructed N-dimensional vector representation of the at least one document, wherein any predicate structure of said M predicate structures that includes less than q arguments fills unfilled argument positions with a numerical zero. 19. The computer readable media of claim 14 , the method further comprising normalizing said N-dimensional vector representations.
| 0.534468 |
14. The method of claim 12 wherein at least one of said special symbols represents N-or-more concatenate symbol paterns for comparison with a plurality of adjacent bytes, N being preselected as any integer.
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14. The method of claim 12 wherein at least one of said special symbols represents N-or-more concatenate symbol paterns for comparison with a plurality of adjacent bytes, N being preselected as any integer. 19. The method of claim 14, wherein each said concatenate symbol pattern comprises at least one further special symbol.
| 0.96257 |
1. A system for obtaining solution suggestions for problems, the system comprising: at least one processor and at least one storage medium including an electronic model of a system or process, wherein the electronic model includes components of the system or process and relationships between the components; a problem analysis tool that analyzes the components and the relationships between the components of the electronic model to identify a problem to be solved, generates a problem statement representing the problem, and generates a machine representation of a problem statement; a query formatter that reformulates the machine representation into a natural language query or Boolean query and automatically submits the query to at least one knowledge base; and the at least one knowledge base comprising at least one database comprising problem solutions and returning a set of solution suggestions responsive to the query.
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1. A system for obtaining solution suggestions for problems, the system comprising: at least one processor and at least one storage medium including an electronic model of a system or process, wherein the electronic model includes components of the system or process and relationships between the components; a problem analysis tool that analyzes the components and the relationships between the components of the electronic model to identify a problem to be solved, generates a problem statement representing the problem, and generates a machine representation of a problem statement; a query formatter that reformulates the machine representation into a natural language query or Boolean query and automatically submits the query to at least one knowledge base; and the at least one knowledge base comprising at least one database comprising problem solutions and returning a set of solution suggestions responsive to the query. 7. The system of claim 1 , wherein the at least one knowledge base is remotely accessed.
| 0.660387 |
1. A method for a computer system to interpret an input from a user and generate a response, comprising: receiving a user input; converting the user input into an input array comprising rows and columns having a plurality of concepts; determining if any of the plurality of concepts in the input array is derived from a root concept; if any of the plurality of concepts is derived from a root concept, replacing each such derived concept with the corresponding root concept, identifying one or more related concepts that relate to the root concept, and generating a multi-dimensional array based on the input array that includes the one or more related concepts; generating one or more additional multi-dimensional arrays, based on the input, containing any composite concepts, each derived from two or more concepts contained in the original array; marking one or more concepts in the multi-dimensional arrays as essential based on application-specific criteria; correlating a plurality of concepts in the multi-dimensional array to a plurality of first elements in a database by comparing a plurality of linear arrays derived from the multidimensional array to the plurality of elements in the database, wherein the first elements in the database includes a link to a second element in the database do not comprise possible responses; determining a plurality of possible responses to the user input based on the correlation of the multi-dimensional array and the plurality of elements in the database; and generating a response to the user input.
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1. A method for a computer system to interpret an input from a user and generate a response, comprising: receiving a user input; converting the user input into an input array comprising rows and columns having a plurality of concepts; determining if any of the plurality of concepts in the input array is derived from a root concept; if any of the plurality of concepts is derived from a root concept, replacing each such derived concept with the corresponding root concept, identifying one or more related concepts that relate to the root concept, and generating a multi-dimensional array based on the input array that includes the one or more related concepts; generating one or more additional multi-dimensional arrays, based on the input, containing any composite concepts, each derived from two or more concepts contained in the original array; marking one or more concepts in the multi-dimensional arrays as essential based on application-specific criteria; correlating a plurality of concepts in the multi-dimensional array to a plurality of first elements in a database by comparing a plurality of linear arrays derived from the multidimensional array to the plurality of elements in the database, wherein the first elements in the database includes a link to a second element in the database do not comprise possible responses; determining a plurality of possible responses to the user input based on the correlation of the multi-dimensional array and the plurality of elements in the database; and generating a response to the user input. 7. The method of claim 1 , wherein the multi-dimensional array comprises a plurality of tokens and wherein each token corresponds to a concept.
| 0.548802 |
2. The machine-readable medium of claim 1 , further comprising instructions to: detect actuation of a pagination navigation control of the web browser; and transmit a request for a different subset of the plurality of item listings based on the actuation and based on the pagination navigation information.
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2. The machine-readable medium of claim 1 , further comprising instructions to: detect actuation of a pagination navigation control of the web browser; and transmit a request for a different subset of the plurality of item listings based on the actuation and based on the pagination navigation information. 5. The machine-readable medium of claim 2 , wherein detecting actuation of the pagination navigation control includes detecting a touch gesture on a display.
| 0.925703 |
17. A system for converting digital source content into a structured document, the system comprising: an interface for receiving digital source content, the digital source content comprising source data elements where each source data element includes one or more attributes; a processor; and a memory for storing executable instructions that comprise: a parsing module that determines the one or more attributes for each of the source data elements; an assignment module that: compares an attribute and value for the source data elements to expected values for an identifier and tags each of the source data elements with the identifier based upon their one or more attributes, the identifier defining a function for a particular source data element with a structured document; determines, for data elements of the digital source content, a semantic naming convention, a structure, a granularity, an order, and a styling by comparing the data elements of the digital source content to classified data elements of previously generated structured documents; identifies data elements of the digital source content that match classified data elements of previously analyzed structured documents; and assigns any of the semantic naming convention, the structure, the granularity, the order, and the styling of the classified data elements of previously generated structured documents to the matching data elements; and a document generator module that generates the structured document from the tagged source data elements.
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17. A system for converting digital source content into a structured document, the system comprising: an interface for receiving digital source content, the digital source content comprising source data elements where each source data element includes one or more attributes; a processor; and a memory for storing executable instructions that comprise: a parsing module that determines the one or more attributes for each of the source data elements; an assignment module that: compares an attribute and value for the source data elements to expected values for an identifier and tags each of the source data elements with the identifier based upon their one or more attributes, the identifier defining a function for a particular source data element with a structured document; determines, for data elements of the digital source content, a semantic naming convention, a structure, a granularity, an order, and a styling by comparing the data elements of the digital source content to classified data elements of previously generated structured documents; identifies data elements of the digital source content that match classified data elements of previously analyzed structured documents; and assigns any of the semantic naming convention, the structure, the granularity, the order, and the styling of the classified data elements of previously generated structured documents to the matching data elements; and a document generator module that generates the structured document from the tagged source data elements. 26. The system according to claim 17 , wherein any of the digital source content or the structured document comprises any format selected from ePub, HTML, JavaScript, Cascading Style Sheets, Extensible Markup Language, plain text, and Comma Separated Value, and images.
| 0.569248 |
48. The apparatus of claim 47 , wherein the file is in accordance with International Organization for Standardization (ISO) base media file format.
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48. The apparatus of claim 47 , wherein the file is in accordance with International Organization for Standardization (ISO) base media file format. 51. The apparatus of claim 48 , wherein the at least one group is indicated in a sample group description box.
| 0.941316 |
1. A method of obtaining enhanced answers to a plurality of questions comprising: accessing features comprising any one or more of: at least one feature for each of a plurality of judges, and at least one feature for each of the questions; accessing at least one answer for each question given by one of the judges and, for a plurality of the questions, more than one answer given by different ones of the judges; using a probabilistic learning system to learn an expertise of each judge using the features, the probabilistic learning system using at least a first question for which an answer is known as ground truth and a second question for which a ground truth answer is unknown, true answers to at least some of the questions being unknown to the probabilistic learning system and true expertise of the judges for the questions being unknown to the probabilistic learning system, an enhanced answer to a question being more likely to be accurate than a corresponding answer before application of the probabilistic learning system; and using the probabilistic learning system to determine enhanced answers to the questions by aggregating the answers in a manner which takes into account the identified expertise of the judges by weighting answers of the judges based on the identified expertise of the judges.
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1. A method of obtaining enhanced answers to a plurality of questions comprising: accessing features comprising any one or more of: at least one feature for each of a plurality of judges, and at least one feature for each of the questions; accessing at least one answer for each question given by one of the judges and, for a plurality of the questions, more than one answer given by different ones of the judges; using a probabilistic learning system to learn an expertise of each judge using the features, the probabilistic learning system using at least a first question for which an answer is known as ground truth and a second question for which a ground truth answer is unknown, true answers to at least some of the questions being unknown to the probabilistic learning system and true expertise of the judges for the questions being unknown to the probabilistic learning system, an enhanced answer to a question being more likely to be accurate than a corresponding answer before application of the probabilistic learning system; and using the probabilistic learning system to determine enhanced answers to the questions by aggregating the answers in a manner which takes into account the identified expertise of the judges by weighting answers of the judges based on the identified expertise of the judges. 8. A method as claimed in claim 1 wherein using the probabilistic learning system to determine enhanced answers to the questions comprises propagating answers made by the judges through nodes in a logical component of the probabilistic learning system according to logical relations between the questions.
| 0.646505 |
3. A computer-implemented method for assessing compliance with the HIPAA, in a context management system, the method comprising: (A) collecting context data from a plurality of applications that use the context management system; (B) storing data corresponding to the collected context data on a centralized storage location; and (C) extracting audit information by processing at least a subset of the data stored on the centralized storage location, the audit information suitable for making an assessment of compliance with a provision of the HIPAA; wherein any of the plurality of applications supports the CCOW standard set.
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3. A computer-implemented method for assessing compliance with the HIPAA, in a context management system, the method comprising: (A) collecting context data from a plurality of applications that use the context management system; (B) storing data corresponding to the collected context data on a centralized storage location; and (C) extracting audit information by processing at least a subset of the data stored on the centralized storage location, the audit information suitable for making an assessment of compliance with a provision of the HIPAA; wherein any of the plurality of applications supports the CCOW standard set. 17. The method of claim 3 , wherein (B) comprises: (i) storing the context data onto an intermediate collection platform, disposed between the context management system and the centralized storage location; and (ii) sending the context data from the intermediate collection platform to the centralized storage location.
| 0.604962 |
1. A method comprising: storing a plurality of parser definitions, wherein each parser definition is associated with an object type, wherein a particular parser definition of the one or more parser definitions comprises two or more parser sub-definitions, wherein a first parser sub-definition of the two or more parser sub-definitions is associated with a first property type, and wherein a second parser sub-definition of the two or more parser sub-definitions is associated with a second property type, wherein at least the first property type is a composite type that includes two or more of a string component, a date component, or a number component, by: displaying, on a computer display device using a user interface screen display, a text box that can receive a user entry of regular expression pattern text; creating and storing a plurality of property type component mappings that associate sub-definitions of the regular expression pattern text with property type components by selecting from a combo box in the user interface screen display, wherein the two or more parser sub-definitions comprise the sub-definitions of the regular expression pattern text; determining whether input data matches the particular parser definition; based at least in part on determining that the input data matches the particular parser definition: creating at least a first property instance of the first property type and a second property instance of the second property type; storing first data corresponding to a first portion of the input data in the first property instance, wherein the first portion of the input data and the corresponding first data each include two or more of string data, date data, or number data; storing second data based on a second portion of the input data in the second property instance; wherein the method is performed by one or more computing devices.
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1. A method comprising: storing a plurality of parser definitions, wherein each parser definition is associated with an object type, wherein a particular parser definition of the one or more parser definitions comprises two or more parser sub-definitions, wherein a first parser sub-definition of the two or more parser sub-definitions is associated with a first property type, and wherein a second parser sub-definition of the two or more parser sub-definitions is associated with a second property type, wherein at least the first property type is a composite type that includes two or more of a string component, a date component, or a number component, by: displaying, on a computer display device using a user interface screen display, a text box that can receive a user entry of regular expression pattern text; creating and storing a plurality of property type component mappings that associate sub-definitions of the regular expression pattern text with property type components by selecting from a combo box in the user interface screen display, wherein the two or more parser sub-definitions comprise the sub-definitions of the regular expression pattern text; determining whether input data matches the particular parser definition; based at least in part on determining that the input data matches the particular parser definition: creating at least a first property instance of the first property type and a second property instance of the second property type; storing first data corresponding to a first portion of the input data in the first property instance, wherein the first portion of the input data and the corresponding first data each include two or more of string data, date data, or number data; storing second data based on a second portion of the input data in the second property instance; wherein the method is performed by one or more computing devices. 6. The method of claim 1 , wherein the composite type consists of a string component and a number component, and wherein the first portion of the input data and the corresponding first data each consist of string data and number data.
| 0.569538 |
3. A method according to claim 2 , wherein said making the temporally ordered posting list a total order includes: assigning, to documents in the content store, unique timestamps as document identifiers; wherein each posting record identifies a document in the content store by using the unique timestamp assigned to the document as a document identifier.
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3. A method according to claim 2 , wherein said making the temporally ordered posting list a total order includes: assigning, to documents in the content store, unique timestamps as document identifiers; wherein each posting record identifies a document in the content store by using the unique timestamp assigned to the document as a document identifier. 4. A method according to claim 3 , wherein said making the temporally ordered posting list a total order includes applying a Bloom filter to a plurality of existing timestamps assigned to documents in the content store as document identifiers.
| 0.914881 |
1. A system, which includes a processor operatively coupled to computer storage media, for providing online advertising, the system comprising: a reception module that intercepts a search query bound for a search engine, wherein the search query includes a keyword, and wherein the reception module determines whether the search query includes a designated format; a reference module that accesses a one-to-one mapping stored on the computer storage media that associates the keyword with an Internet protocol (IP) address of an advertisement provider, wherein the search query is routed to the reference module when the search query is deemed to include the designated format, wherein the reference module identifies the IP address by leveraging the processor to reference the keyword in the one-to-one mapping; a direction module in communication with the reference module that sends an advertisement request to the IP address of the advertisement provider when the reference module identifies the IP address; and a search engine that receives the search query from the reception module when the search query is deemed to not include the designated format.
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1. A system, which includes a processor operatively coupled to computer storage media, for providing online advertising, the system comprising: a reception module that intercepts a search query bound for a search engine, wherein the search query includes a keyword, and wherein the reception module determines whether the search query includes a designated format; a reference module that accesses a one-to-one mapping stored on the computer storage media that associates the keyword with an Internet protocol (IP) address of an advertisement provider, wherein the search query is routed to the reference module when the search query is deemed to include the designated format, wherein the reference module identifies the IP address by leveraging the processor to reference the keyword in the one-to-one mapping; a direction module in communication with the reference module that sends an advertisement request to the IP address of the advertisement provider when the reference module identifies the IP address; and a search engine that receives the search query from the reception module when the search query is deemed to not include the designated format. 2. The system of claim 1 , wherein the keyword is a brand name and wherein the advertisement provider is a business entity that owns the brand name.
| 0.5 |
1. A test-to-speed synthesis system for converting printed data as represented by digital characters into audible synthesized speech, said system comprising: allophone rule means having a plurality of allophonic code signals corresponding to the digital characters which are representative of the printed data, wherein the allophonic code signals are determinative of the respective allophone subset variants of each of the recognized phonemes in a given spoken language as modified by the speech environment in which the particular phoneme occurs; allophone rules processor means having an input for receiving the digital characters representative of printed data and operably coupled to said allophone rule means for searching the allophone rule means to provide an allophonic code signal output corresponding to the digital characters received by sid allophone rules processor means from the allophonic code signals of said allophone rule means; and synthesized speech producing means operably coupled to said allophone rules processor means for receiving said allophonic code signal output therefrom to produce an audible synthesized speech-like sound in response to said allophonic code signal output from said allophone rules processor means.
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1. A test-to-speed synthesis system for converting printed data as represented by digital characters into audible synthesized speech, said system comprising: allophone rule means having a plurality of allophonic code signals corresponding to the digital characters which are representative of the printed data, wherein the allophonic code signals are determinative of the respective allophone subset variants of each of the recognized phonemes in a given spoken language as modified by the speech environment in which the particular phoneme occurs; allophone rules processor means having an input for receiving the digital characters representative of printed data and operably coupled to said allophone rule means for searching the allophone rule means to provide an allophonic code signal output corresponding to the digital characters received by sid allophone rules processor means from the allophonic code signals of said allophone rule means; and synthesized speech producing means operably coupled to said allophone rules processor means for receiving said allophonic code signal output therefrom to produce an audible synthesized speech-like sound in response to said allophonic code signal output from said allophone rules processor means. 2. The system of claim 1 wherein said allophone rule means comprises digital storage means in which said allophonic code signals are stored.
| 0.704142 |
1. A method comprising: receiving, by a processor, a request from a user to discuss content with a recipient user in a social network, wherein the recipient user is associated with a group comprising a plurality of the recipient users in the social network; creating, by the processor, a temporary placeholder account for the user; creating, by the processor, a first group for the user and the recipient user in the social network in view of the temporary placeholder account, wherein the first group is different from the group; initiating, by the processor, a live discussion between the user and the recipient user about the content in the first group; converting, by the processor, the temporary placeholder account to a permanent placeholder account for the user in view of a condition, wherein the converting comprises allowing the user to join the group in the social network; and sending, by the processor, a notification of the user joining the group to the plurality of the recipient users.
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1. A method comprising: receiving, by a processor, a request from a user to discuss content with a recipient user in a social network, wherein the recipient user is associated with a group comprising a plurality of the recipient users in the social network; creating, by the processor, a temporary placeholder account for the user; creating, by the processor, a first group for the user and the recipient user in the social network in view of the temporary placeholder account, wherein the first group is different from the group; initiating, by the processor, a live discussion between the user and the recipient user about the content in the first group; converting, by the processor, the temporary placeholder account to a permanent placeholder account for the user in view of a condition, wherein the converting comprises allowing the user to join the group in the social network; and sending, by the processor, a notification of the user joining the group to the plurality of the recipient users. 9. The method of claim 1 wherein the condition comprises one of an identity of the user, a relationship between the user and the recipient user and a trial period.
| 0.632705 |
17. A system for annotating an essay, comprising: a data processor; computer readable memory encoded with instructions which, when executed, cause the data processor to execute steps comprising: identifying a sentence of the essay; identifying a plurality of features associated with said sentence; determining a probability of said sentence being a discourse element by a statistical evaluation that includes mapping the plurality of features to a model, said model having been generated by a machine learning application trained based on at least one annotated essay, wherein said mapping comprises extracting a pattern from the sentence based on the plurality of features and based on the training of the machine learning application; and annotating said essay based on said probability, wherein said discourse element is at least one of: a title, a background, a thesis statement, a main point, support and conclusion.
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17. A system for annotating an essay, comprising: a data processor; computer readable memory encoded with instructions which, when executed, cause the data processor to execute steps comprising: identifying a sentence of the essay; identifying a plurality of features associated with said sentence; determining a probability of said sentence being a discourse element by a statistical evaluation that includes mapping the plurality of features to a model, said model having been generated by a machine learning application trained based on at least one annotated essay, wherein said mapping comprises extracting a pattern from the sentence based on the plurality of features and based on the training of the machine learning application; and annotating said essay based on said probability, wherein said discourse element is at least one of: a title, a background, a thesis statement, a main point, support and conclusion. 26. The system of claim 17 , wherein the plurality of features includes a punctuation within the identified sentence.
| 0.663842 |
18. The computer storage medium of claim 12 , further comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations including applying a darkening offset to the received hinted glyph outline including increasing the outline for the entire glyph.
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18. The computer storage medium of claim 12 , further comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations including applying a darkening offset to the received hinted glyph outline including increasing the outline for the entire glyph. 19. The computer storage medium of claim 18 , further comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations including: identifying a baseline associated with the glyph; and identifying an origin point of the modified hinted glyph outline relative to the baseline, when the position of the origin relative to the baseline has changed for the modified hinted glyph outline due to the applied darkening offset, translating the modified hinted glyph outline to maintain the origin point relative to the baseline.
| 0.694836 |
15. A terminal that displays an available character capacity in a character entry window, comprising: an input unit for entering characters; a display that displays the character entry window; a controller that calculates the available character capacity and available character capacity percentage based on characters entered by a user, controls the display to display the entered characters in the character entry window, and controls the display to display an indication of the available character capacity at a position in the character entry window adjacent to a last character entered by the user when the available character capacity percentage is between a first value and a second value, and to automatically change the position of the displayed indication of the available character capacity to a new corresponding position for each of a plurality of additional characters entered by the user, wherein the controller changes the color of the indication of the available character capacity when the available character capacity percentage is between the second value and a third value, wherein the second value is less than the first value and the second value is greater than the third value, and the controller changes a display type of the indication of the available character capacity from a number to a text when the available character capacity percentage is zero.
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15. A terminal that displays an available character capacity in a character entry window, comprising: an input unit for entering characters; a display that displays the character entry window; a controller that calculates the available character capacity and available character capacity percentage based on characters entered by a user, controls the display to display the entered characters in the character entry window, and controls the display to display an indication of the available character capacity at a position in the character entry window adjacent to a last character entered by the user when the available character capacity percentage is between a first value and a second value, and to automatically change the position of the displayed indication of the available character capacity to a new corresponding position for each of a plurality of additional characters entered by the user, wherein the controller changes the color of the indication of the available character capacity when the available character capacity percentage is between the second value and a third value, wherein the second value is less than the first value and the second value is greater than the third value, and the controller changes a display type of the indication of the available character capacity from a number to a text when the available character capacity percentage is zero. 19. The terminal according to claim 15 , wherein the controller changes the color of the indication by changing the color of the indication when the available character capacity percentage is between the second value and the third value.
| 0.508503 |
12. A method for correcting errors in an audio transcription comprising: recording an analog audio transmission with an analog audio recorder; converting the analog format to a digital format with a transcription generator including an analog-to-digital audio converter; generating a transcription of said audio transmission; storing said audio recording; generating a collection of link data; storing the text of said transcription; playing the recorded audio transmission; cross linking said stored text with said recorded audio transmission; editing said text using a cursor; dragging a slider on a playback controller located on the text editor screen to jump to any part of the recording; and jumping the text cursor to a corresponding playback position by a first button, disabling a text tracking function of the audio transcription by a second button, and optionally controlling speed of a playback by a third button.
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12. A method for correcting errors in an audio transcription comprising: recording an analog audio transmission with an analog audio recorder; converting the analog format to a digital format with a transcription generator including an analog-to-digital audio converter; generating a transcription of said audio transmission; storing said audio recording; generating a collection of link data; storing the text of said transcription; playing the recorded audio transmission; cross linking said stored text with said recorded audio transmission; editing said text using a cursor; dragging a slider on a playback controller located on the text editor screen to jump to any part of the recording; and jumping the text cursor to a corresponding playback position by a first button, disabling a text tracking function of the audio transcription by a second button, and optionally controlling speed of a playback by a third button. 17. The method for correcting errors in an audio transcription of claim 12 , further comprising: providing feedback from the step of editing to the step of generating a transcription.
| 0.534205 |
1. A computer implemented method, comprising: identifying a message of a user, wherein the message includes a plurality of terms and is an electronic communication sent or received by the user; determining an event based on the message, wherein the event includes one or more event properties that are determined based on one or more of the terms; determining an event confidence level based on the event properties; determining an effect on dissemination of information related to the event, wherein the effect is determined based on the event confidence level, wherein the dissemination of information includes a first dissemination of information that is related to a first computer application and a second dissemination of information that is related to a second computer application and that is unique from the first dissemination of information, and wherein the determining the effect on the dissemination of information comprises: determining, based on the event confidence level, to influence the first dissemination of information based on the event and to not influence the second dissemination of information based on the event, the influence of the first dissemination of information being reflected in output provided to the user via the first computer application; identifying additional data associated with the user and the event; determining a new event confidence level based on the additional data; and adjusting the effect on the dissemination of information related to the event based on the new event confidence level, wherein the adjusting the effect on the dissemination of information comprises determining, based on the new event confidence level, to influence both the first dissemination of information and the second dissemination of information based on the event, the influence of the second dissemination of information being reflected in additional output provided to the user via the second computer application.
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1. A computer implemented method, comprising: identifying a message of a user, wherein the message includes a plurality of terms and is an electronic communication sent or received by the user; determining an event based on the message, wherein the event includes one or more event properties that are determined based on one or more of the terms; determining an event confidence level based on the event properties; determining an effect on dissemination of information related to the event, wherein the effect is determined based on the event confidence level, wherein the dissemination of information includes a first dissemination of information that is related to a first computer application and a second dissemination of information that is related to a second computer application and that is unique from the first dissemination of information, and wherein the determining the effect on the dissemination of information comprises: determining, based on the event confidence level, to influence the first dissemination of information based on the event and to not influence the second dissemination of information based on the event, the influence of the first dissemination of information being reflected in output provided to the user via the first computer application; identifying additional data associated with the user and the event; determining a new event confidence level based on the additional data; and adjusting the effect on the dissemination of information related to the event based on the new event confidence level, wherein the adjusting the effect on the dissemination of information comprises determining, based on the new event confidence level, to influence both the first dissemination of information and the second dissemination of information based on the event, the influence of the second dissemination of information being reflected in additional output provided to the user via the second computer application. 8. The method of claim 1 , wherein the first dissemination of information includes providing one or more query suggestions to the user and wherein the determining to influence the first dissemination of information in the adjusting the effect on the dissemination of information related to the event includes adjusting, based on the new event confidence level, a degree of influence of the event in ranking the query suggestions.
| 0.579705 |
15. A processing system comprising: a network interface through which to receive a search query from a user via a network; and a processor configured to control the processing system to perform operations including inputting a plurality of digital catalogs of products or services; extracting content from the plurality of digital catalogs; storing the extracted content in a database so that the extracted content is searchable, wherein said storing includes generating and storing a hierarchy of unique objects to represent each of the plurality of digital catalogs, and wherein said generating includes defining, for each catalog of the plurality of digital catalogs, a parent object to store a front page of the catalog, related catalog data and a pointer to each child object of the parent object, and a child object of the parent object to represent an internal page of the catalog, the child object including content of the internal page, a page number of the internal page, and a pointer to the parent object;; uploading a user-provided logo at a computer system; associating the logo with at least one catalog of the plurality of digital catalogs at the computer system, in such a manner that when a user views a result set corresponding to a search, the logo will be superimposed on an image associated with the at least one catalog in the result set; receiving at the computer system a search query from a user; and in response to the search query, identifying, by the computer system, content extracted from one of the digital catalogs and stored in the database, which satisfies the search query; and causing the result set to be output to the user, the result set including, in association with each other, the identified content extracted from said one of the digital catalogs and stored in the database, which satisfies the search query, and an image of a particular page of said one of the digital catalogs from which the identified content was extracted.
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15. A processing system comprising: a network interface through which to receive a search query from a user via a network; and a processor configured to control the processing system to perform operations including inputting a plurality of digital catalogs of products or services; extracting content from the plurality of digital catalogs; storing the extracted content in a database so that the extracted content is searchable, wherein said storing includes generating and storing a hierarchy of unique objects to represent each of the plurality of digital catalogs, and wherein said generating includes defining, for each catalog of the plurality of digital catalogs, a parent object to store a front page of the catalog, related catalog data and a pointer to each child object of the parent object, and a child object of the parent object to represent an internal page of the catalog, the child object including content of the internal page, a page number of the internal page, and a pointer to the parent object;; uploading a user-provided logo at a computer system; associating the logo with at least one catalog of the plurality of digital catalogs at the computer system, in such a manner that when a user views a result set corresponding to a search, the logo will be superimposed on an image associated with the at least one catalog in the result set; receiving at the computer system a search query from a user; and in response to the search query, identifying, by the computer system, content extracted from one of the digital catalogs and stored in the database, which satisfies the search query; and causing the result set to be output to the user, the result set including, in association with each other, the identified content extracted from said one of the digital catalogs and stored in the database, which satisfies the search query, and an image of a particular page of said one of the digital catalogs from which the identified content was extracted. 23. The processing system of claim 15 , wherein the operations further comprise: Enabling the user to page through a digital copy of said one of the digital catalogs from which the identified content was extracted.
| 0.569967 |
18. The computer implemented method of claim 16 , wherein the first group further comprises recipients who are members of the same domain as the user.
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18. The computer implemented method of claim 16 , wherein the first group further comprises recipients who are members of the same domain as the user. 19. The computer implemented method of claim 18 , further comprising: receiving an email from a second recipient who is not listed in the contact folder of the user and who is not a member of the same domain as the user; and not sending the out of office message.
| 0.881188 |
11. A computer-readable storage memory storing computer executable instructions executed by one or more processors of a computer implementing a method comprising: receiving criteria for implementing a query for documents; performing the query; receiving a set of documents resulting from the query; selecting a subset of the documents resulting from the query; generating an absolute relevance score for each document of the subset of the documents, the absolute relevance score being a function of human-generated labels and extrinsic data, the extrinsic data including a measure of query-independent popularity of a document of the set of documents, the popularity being determined based on a sum of clicks on the document; sorting the subset of the documents according to the absolute relevance score; selecting one or more related refinements based on characteristics of those documents of the subset of the documents with absolute relevance scores above a threshold value; displaying on the computer the one or more related refinements; presenting a list of related categories; ordering the list of related categories with respect to an average absolute relevance that is calculated by taking an average absolute relevance of documents in each respective related category; and displaying on the computer those documents of the subset of the documents having respective absolute relevance scores above the threshold value, wherein recent clicks are given more weight than older clicks.
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11. A computer-readable storage memory storing computer executable instructions executed by one or more processors of a computer implementing a method comprising: receiving criteria for implementing a query for documents; performing the query; receiving a set of documents resulting from the query; selecting a subset of the documents resulting from the query; generating an absolute relevance score for each document of the subset of the documents, the absolute relevance score being a function of human-generated labels and extrinsic data, the extrinsic data including a measure of query-independent popularity of a document of the set of documents, the popularity being determined based on a sum of clicks on the document; sorting the subset of the documents according to the absolute relevance score; selecting one or more related refinements based on characteristics of those documents of the subset of the documents with absolute relevance scores above a threshold value; displaying on the computer the one or more related refinements; presenting a list of related categories; ordering the list of related categories with respect to an average absolute relevance that is calculated by taking an average absolute relevance of documents in each respective related category; and displaying on the computer those documents of the subset of the documents having respective absolute relevance scores above the threshold value, wherein recent clicks are given more weight than older clicks. 15. The computer-readable storage memory of claim 11 , wherein the extrinsic data includes a count of a number of phrases in a document of the set of documents that exactly match the query and a comparison of a category of the query to a category of the document.
| 0.585347 |
1. A speech coding system responsive to an input speech signal provided by a system user, the system comprising: a first speech transcribing means comprising a speech recognition means having a word vocabulary associated therewith, the speech recognition means recognizing words in the input speech signal in accordance with the vocabulary and generating at least one phonetic token representative of the input speech signal; a second speech transcribing means for generating at least one phonetic token representative of a word in the input speech signal which is not in the word vocabulary; channel means, responsive to at least one of the phonetic tokens, for handling at least one of the phonetic tokens in accordance with an application of the speech coding system; and speech synthesizing means, responsive to the channel means, for generating a synthesized speech signal using at least one of a plurality of pre-enrolled phonetic tokens that substantially matches at least one of the phonetic tokens which is representative of the input speech signal provided by the system user.
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1. A speech coding system responsive to an input speech signal provided by a system user, the system comprising: a first speech transcribing means comprising a speech recognition means having a word vocabulary associated therewith, the speech recognition means recognizing words in the input speech signal in accordance with the vocabulary and generating at least one phonetic token representative of the input speech signal; a second speech transcribing means for generating at least one phonetic token representative of a word in the input speech signal which is not in the word vocabulary; channel means, responsive to at least one of the phonetic tokens, for handling at least one of the phonetic tokens in accordance with an application of the speech coding system; and speech synthesizing means, responsive to the channel means, for generating a synthesized speech signal using at least one of a plurality of pre-enrolled phonetic tokens that substantially matches at least one of the phonetic tokens which is representative of the input speech signal provided by the system user. 6. The speech coding system of claim 1, wherein the at least one phonetic token generated by the speech recognition means and the at least one phonetic token generated by the second speech transcribing means have a measure associated therewith, respectively, indicative of the similarity of the phonetic token to the input speech.
| 0.563268 |
1. A method for a database system, comprising: establishing a column-oriented in-memory database structure including a main store and a dictionary compressed delta store, wherein the delta store comprises a value identifier vector that includes each value of a record stored in a same row of a column of the database and a delta dictionary associated with the column of the database; receiving a transaction associated with the column; recording the transaction within the delta store; adding an entry associated with the transaction to a value log of the value identifier vector, the value log comprising a transaction identifier and a row identifier indicating a row in the value identifier vector; and adding an entry associated with the transaction to a dictionary log of the delta dictionary.
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1. A method for a database system, comprising: establishing a column-oriented in-memory database structure including a main store and a dictionary compressed delta store, wherein the delta store comprises a value identifier vector that includes each value of a record stored in a same row of a column of the database and a delta dictionary associated with the column of the database; receiving a transaction associated with the column; recording the transaction within the delta store; adding an entry associated with the transaction to a value log of the value identifier vector, the value log comprising a transaction identifier and a row identifier indicating a row in the value identifier vector; and adding an entry associated with the transaction to a dictionary log of the delta dictionary. 3. The method of claim 1 , wherein the received transaction comprises one of an insert transaction, an update transaction, or a delete operation.
| 0.69926 |
2. The method according to claim 1 , further comprising: verifying at least partially structured data is tagged correctly; and releasing at least partially structured data, such that the at least partially structured data may be incorporated into the main application.
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2. The method according to claim 1 , further comprising: verifying at least partially structured data is tagged correctly; and releasing at least partially structured data, such that the at least partially structured data may be incorporated into the main application. 3. The method according to claim 2 , wherein verifying at least partially structured data comprises examining one or more identification tags in the at least partially structured data.
| 0.973204 |
22. The computer program product of claim 21 , wherein the computer code is further configured for: determining a weight for each received vote, the weight indicating the vote's relative contribution to the quality score.
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22. The computer program product of claim 21 , wherein the computer code is further configured for: determining a weight for each received vote, the weight indicating the vote's relative contribution to the quality score. 23. The computer program product of claim 22 , wherein the weight of a vote submitted by a voting member is based on the perceived quality among members of translations previously submitted by the voting member.
| 0.897347 |
82. The computer program product of claim 29 , wherein the computer program product is configured for identifying taxonomy software elements in connection with at least one source data document.
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82. The computer program product of claim 29 , wherein the computer program product is configured for identifying taxonomy software elements in connection with at least one source data document. 86. The computer program product of claim 82 , wherein the computer program product provides for modification of one or more parameters associated with the taxonomy software elements.
| 0.980061 |
27. A tangible non-transitory computer-readable medium having stored thereon computer-executable instructions, execution of which, by a computing device, cause the computing device to perform operations comprising: receiving an input from a media communications server via a session brokered based on a distribution of processing load; interpreting a request for information in the input; communicating the request for information to a communication interface; and receiving information from the communication interface responsive to the request for information.
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27. A tangible non-transitory computer-readable medium having stored thereon computer-executable instructions, execution of which, by a computing device, cause the computing device to perform operations comprising: receiving an input from a media communications server via a session brokered based on a distribution of processing load; interpreting a request for information in the input; communicating the request for information to a communication interface; and receiving information from the communication interface responsive to the request for information. 38. The computer-readable medium of claim 27 , the method further comprising: receiving, at the media communications server, a dialog input from a communications subsystem; requesting, at the media communications server, a dialog engine from a broker operable to distribute a processing load across a plurality of dialog engines; sending, from the media communications server, the request for information to the dialog engine based on the dialog input; and receiving, at the media communications server, the information from the dialog engine.
| 0.5 |
1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: a. providing a set of content items, each content item having at least one associated descriptive term to describe the content item; b. receiving incremental input entered by the user for incrementally identifying desired content items; c. in response to the incremental input entered by the user, presenting a subset of content items; d. receiving selection actions of content items of the subset from the user; e. analyzing the descriptive terms associated with the selected content items to learn the preferred descriptive terms of the user; f. expressing the learned preferred descriptive terms as a segmented measurement collection having at least one fine grain segment, wherein the segmented measurement collection is a segmented probability distribution function that associates probability weights with the preferred descriptive terms, and wherein the fine grain segment has relatively fine grain differentiation of measurements associated with preferred descriptive terms within the segment, and further wherein the segmented measurement collection further includes an overflow segment, such that the measurements within the overflow segment are not differentiated from other measurements within the overflow segment, and wherein measurements within the overflow segment are differentiated from the measurements within the fine grain segment; and g. in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented measurement collection; h. wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device.
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1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: a. providing a set of content items, each content item having at least one associated descriptive term to describe the content item; b. receiving incremental input entered by the user for incrementally identifying desired content items; c. in response to the incremental input entered by the user, presenting a subset of content items; d. receiving selection actions of content items of the subset from the user; e. analyzing the descriptive terms associated with the selected content items to learn the preferred descriptive terms of the user; f. expressing the learned preferred descriptive terms as a segmented measurement collection having at least one fine grain segment, wherein the segmented measurement collection is a segmented probability distribution function that associates probability weights with the preferred descriptive terms, and wherein the fine grain segment has relatively fine grain differentiation of measurements associated with preferred descriptive terms within the segment, and further wherein the segmented measurement collection further includes an overflow segment, such that the measurements within the overflow segment are not differentiated from other measurements within the overflow segment, and wherein measurements within the overflow segment are differentiated from the measurements within the fine grain segment; and g. in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented measurement collection; h. wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device. 21. The method of claim 1 , further comprising: organizing the content items of the set of content items into groupings based on the informational content of the content items; determining a context in which the user performed the selection actions, the context including at least one of geographic location of the user, day, date, time, and the group into which the selected content items are organized; and associating the contexts of the user selection actions with the preferred descriptive terms learned from the corresponding user selections; wherein only preferred descriptive terms associated with the context in which the user entered the subsequent incremental input are used in the selecting and ordering of the collection of content items.
| 0.53764 |
1. A method for comparing a text image and a character string comprising: embedding a character string into a vectorial space, comprising extracting a set of features from the character string and generating a character string representation based on the extracted character string features; embedding a text image into a vectorial space, comprising extracting a set of features from the text image and generating a text image representation based on the extracted text image features; and computing a compatibility between the text image representation and character string representation comprising computing a function of the text image representation and character string representation, the function including an embedding parameter w which is a DE-dimensional vector or a D×E matrix W which embeds the text image representation and character string representation into a new space, where D is the dimensionality of the text image representation and E is the dimensionality of the character string representation, wherein at least one of the embedding and the computing of the compatibility is performed with a processor.
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1. A method for comparing a text image and a character string comprising: embedding a character string into a vectorial space, comprising extracting a set of features from the character string and generating a character string representation based on the extracted character string features; embedding a text image into a vectorial space, comprising extracting a set of features from the text image and generating a text image representation based on the extracted text image features; and computing a compatibility between the text image representation and character string representation comprising computing a function of the text image representation and character string representation, the function including an embedding parameter w which is a DE-dimensional vector or a D×E matrix W which embeds the text image representation and character string representation into a new space, where D is the dimensionality of the text image representation and E is the dimensionality of the character string representation, wherein at least one of the embedding and the computing of the compatibility is performed with a processor. 9. The method of claim 1 , wherein the character string embedding comprises extraction of a spatial pyramid bag-of-characters.
| 0.580311 |
16. A method for processing an output of a speech recognizer, comprising: (a) storing a representation of the output of the speech recognizer as a representation of the speech input in a memory; (b) determining if at least one command is present in the stored representation; (c) if at least one command is present in the stored representation, determining a context of the speech input; (d) if the speech input is not in context of a command, at least one of notifying a user, prompting the user for input, and passing a data input representing the stored representation to a contextually appropriate data sink; (e) if the determined context of the speech input is in a command context, then for each command present in the speech input: i) determining the elements required for processing each respective command; and ii) determining if the stored representation comprises all the elements required for executing the command, and if so executing the command; Otherwise: iii) prompting the user for further input and receiving and processing subsequent input from the user until aborted or the received and processed information renders the command sufficiently complete for execution; and iv) if a command becomes sufficiently complete for execution, executing the command in an appropriate application or process.
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16. A method for processing an output of a speech recognizer, comprising: (a) storing a representation of the output of the speech recognizer as a representation of the speech input in a memory; (b) determining if at least one command is present in the stored representation; (c) if at least one command is present in the stored representation, determining a context of the speech input; (d) if the speech input is not in context of a command, at least one of notifying a user, prompting the user for input, and passing a data input representing the stored representation to a contextually appropriate data sink; (e) if the determined context of the speech input is in a command context, then for each command present in the speech input: i) determining the elements required for processing each respective command; and ii) determining if the stored representation comprises all the elements required for executing the command, and if so executing the command; Otherwise: iii) prompting the user for further input and receiving and processing subsequent input from the user until aborted or the received and processed information renders the command sufficiently complete for execution; and iv) if a command becomes sufficiently complete for execution, executing the command in an appropriate application or process. 19. The method according to claim 16 , wherein said representation of a speech input is at least one of a set of potentially recognized words, a data matrix, a context based data construct, a command structure and a textual representation of the speech input.
| 0.588502 |
13. A non-transitory computer readable medium encoded with a computer program, wherein the computer program, when executed by one or more computer processors, causes the one or more computer processors to execute a method for assessing an identifier, the method comprising: receiving a string of characters making up the identifier; determining a keyboard type for a keyboard; determining a finger positioning corresponding to a position of a typer's fingers on the keyboard; and calculating a typeability score for the identifier based on the string of characters and the keyboard type, wherein the typeability score signifies a difficulty of typing the identifier on the keyboard type wherein the typeability score is further based on the finger positioning, and wherein the finger positioning is based on the typer's typing habits.
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13. A non-transitory computer readable medium encoded with a computer program, wherein the computer program, when executed by one or more computer processors, causes the one or more computer processors to execute a method for assessing an identifier, the method comprising: receiving a string of characters making up the identifier; determining a keyboard type for a keyboard; determining a finger positioning corresponding to a position of a typer's fingers on the keyboard; and calculating a typeability score for the identifier based on the string of characters and the keyboard type, wherein the typeability score signifies a difficulty of typing the identifier on the keyboard type wherein the typeability score is further based on the finger positioning, and wherein the finger positioning is based on the typer's typing habits. 18. The non-transitory computer readable medium of claim 13 , wherein the method further comprises assessing, based on the typeability score, whether the identifier is generated by an automated process.
| 0.635904 |
6. A method of searching for web content on a mobile communication facility comprising: capturing, by the mobile communication facility, having one or more processors, speech presented by a user using a resident capture facility on the mobile communication facility; transmitting, by the mobile communication facility, a communications header to a speech recognition facility from the mobile communication facility through a wireless communications facility, wherein the communications header includes metadata with at least one of device name, a network type, an audio source, display parameters for the wireless communications facility, a geographic location, or phone number information; transmitting, by the mobile communication facility, at least a portion of the captured speech as data through the wireless communication facility to a speech recognition facility; receiving, by the mobile communication facility, text from the speech recognition facility from speech-to-text results generated by the speech recognition facility based at least in part on information relating to the captured speech and the communications header, the text including information configured to enable a user to conduct a search on the mobile communication facility, wherein the speech-to-text results are generated using at least one statistical language model selected from a set of language models based at least in part on the information relating to the captured speech and the communications header, wherein the received text includes URL usage information configured to enable the user to conduct the search on the mobile communication facility; and loading the text into a search application resident on the mobile communications facility to search for the web content.
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6. A method of searching for web content on a mobile communication facility comprising: capturing, by the mobile communication facility, having one or more processors, speech presented by a user using a resident capture facility on the mobile communication facility; transmitting, by the mobile communication facility, a communications header to a speech recognition facility from the mobile communication facility through a wireless communications facility, wherein the communications header includes metadata with at least one of device name, a network type, an audio source, display parameters for the wireless communications facility, a geographic location, or phone number information; transmitting, by the mobile communication facility, at least a portion of the captured speech as data through the wireless communication facility to a speech recognition facility; receiving, by the mobile communication facility, text from the speech recognition facility from speech-to-text results generated by the speech recognition facility based at least in part on information relating to the captured speech and the communications header, the text including information configured to enable a user to conduct a search on the mobile communication facility, wherein the speech-to-text results are generated using at least one statistical language model selected from a set of language models based at least in part on the information relating to the captured speech and the communications header, wherein the received text includes URL usage information configured to enable the user to conduct the search on the mobile communication facility; and loading the text into a search application resident on the mobile communications facility to search for the web content. 7. The method of claim 6 , wherein the speech-to-text results are generated using client state information relating to the captured speech.
| 0.570803 |
1. A method, comprising: controlling an automated album scoring process to acquire static information for a set of albums and to acquire dynamic information for the set of albums; controlling the automated album scoring process to select a genre for which an album recommendation is to be made, to select a region for which the album recommendation is to be made, and to select a demographic for which the album recommendation is to be made; controlling the automated album scoring process to produce a raw score for a member of the set of albums as a function of the static information, the dynamic information, the genre, the region, and the demographic; controlling an automated recommendation process to acquire a set of thresholds associated with recommendations in the music marketplace, and to acquire a set of time constraints associated with recommendations in the music marketplace, where the set of ratios, set of thresholds, and set of time constraints control, at least in part, whether an album will be recommended in the music marketplace; controlling the automated recommendation process to acquire a set of weights that control, at least in part, the relative importance to a recommendation score of the genre, the region, the demographic, members of the set of thresholds, or members of the set of time constraints; controlling the automated recommendation process to produce the recommendation score for the member of the set of albums as a function of the raw score, the set of thresholds, the set of time constraints, and the set of weights; selecting the member of the set of albums as a recommended album based, at least in part, on the recommendation score, and automatically generating editorial content for the music marketplace for the recommended album.
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1. A method, comprising: controlling an automated album scoring process to acquire static information for a set of albums and to acquire dynamic information for the set of albums; controlling the automated album scoring process to select a genre for which an album recommendation is to be made, to select a region for which the album recommendation is to be made, and to select a demographic for which the album recommendation is to be made; controlling the automated album scoring process to produce a raw score for a member of the set of albums as a function of the static information, the dynamic information, the genre, the region, and the demographic; controlling an automated recommendation process to acquire a set of thresholds associated with recommendations in the music marketplace, and to acquire a set of time constraints associated with recommendations in the music marketplace, where the set of ratios, set of thresholds, and set of time constraints control, at least in part, whether an album will be recommended in the music marketplace; controlling the automated recommendation process to acquire a set of weights that control, at least in part, the relative importance to a recommendation score of the genre, the region, the demographic, members of the set of thresholds, or members of the set of time constraints; controlling the automated recommendation process to produce the recommendation score for the member of the set of albums as a function of the raw score, the set of thresholds, the set of time constraints, and the set of weights; selecting the member of the set of albums as a recommended album based, at least in part, on the recommendation score, and automatically generating editorial content for the music marketplace for the recommended album. 3. The method of claim 1 , where the dynamic information includes a consumption data for an album, a review for an album, a ranking for an album, a search-based popularity indicia for an album, a web-site traffic-based popularity indicia for an album, a social media-based popularity indicia for an album, a previous popularity score for an album, or information provided by a distributor of an album.
| 0.5 |
9. A method of sharing queries in a hub processing unit coupled to a plurality of client information processing units over a network, the method on the hub processing unit comprising the steps of: receiving a query selected for sharing by a first user of a client information processing system; storing the query; storing information in an accounting database for awarding the first user for submitting the query for sharing; receiving from a second user a selection of the query shared by the first user; performing the further sub-steps of: activating a hyperlink to request a search result set based upon the second user's selection of the hyperlink; and displaying the search result set for the second user.
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9. A method of sharing queries in a hub processing unit coupled to a plurality of client information processing units over a network, the method on the hub processing unit comprising the steps of: receiving a query selected for sharing by a first user of a client information processing system; storing the query; storing information in an accounting database for awarding the first user for submitting the query for sharing; receiving from a second user a selection of the query shared by the first user; performing the further sub-steps of: activating a hyperlink to request a search result set based upon the second user's selection of the hyperlink; and displaying the search result set for the second user. 12. The method as defined in claim 9 , wherein the receiving step further includes a step of awarding at least one of a reward and points for at least one query submission by a user.
| 0.564103 |
19. The computer system of claim 18 , wherein the program instructions to cause the display of the probability that the event corresponding to the event identified in the query input will affect the mapped at least one asset display the probability based on where the probability falls within a range of probabilities that the event corresponding to the event identified in the query input will affect the mapped at least one asset.
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19. The computer system of claim 18 , wherein the program instructions to cause the display of the probability that the event corresponding to the event identified in the query input will affect the mapped at least one asset display the probability based on where the probability falls within a range of probabilities that the event corresponding to the event identified in the query input will affect the mapped at least one asset. 20. The computer system of claim 19 , wherein the range of probabilities are displayed through different colors.
| 0.935478 |
1. A method for improving the operation of a computer system, the method comprising: creating a data record having data that can be accessed by credentialed users of a multi-tenant computing system; establishing restricted access for the created record and storing the restricted-access record in a tenant data store in the multi-tenant computing system such that a first subset of the credentialed users of the multi-tenant computing system may access the restricted-access record; accessing the restricted-access record stored in the tenant data store using access credentials of a user in the first subset of users; generating a note associated with the record, the note having restricted access that is different from the restricted access of the record that corresponds to a second subset of the credentialed users of the multi-tenant computing system; accessing the restricted-access record using access credentials of a user in the second subset; and displaying the record on the display with the note displayed over the record if the access credentials allow for access to both the restricted-access record and the note.
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1. A method for improving the operation of a computer system, the method comprising: creating a data record having data that can be accessed by credentialed users of a multi-tenant computing system; establishing restricted access for the created record and storing the restricted-access record in a tenant data store in the multi-tenant computing system such that a first subset of the credentialed users of the multi-tenant computing system may access the restricted-access record; accessing the restricted-access record stored in the tenant data store using access credentials of a user in the first subset of users; generating a note associated with the record, the note having restricted access that is different from the restricted access of the record that corresponds to a second subset of the credentialed users of the multi-tenant computing system; accessing the restricted-access record using access credentials of a user in the second subset; and displaying the record on the display with the note displayed over the record if the access credentials allow for access to both the restricted-access record and the note. 2. The method of claim 1 , wherein the restricted access of the record comprises a restriction of access to users of the tenant data store who have the access credentials corresponding to the record.
| 0.667508 |
2. The method of claim 1 , wherein the field comprises a plurality of fields.
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2. The method of claim 1 , wherein the field comprises a plurality of fields. 3. The method of claim 2 , wherein the plurality of fields comprises a first field of the form and a second field of the form; and wherein filling in the field of the form with the text further comprises: placing a first portion of the text into the first field of the form; and placing a second portion of the text into the second field of the form.
| 0.787015 |
12. A tangible computer-readable medium encoded with instructions that, in response to execution by a computing device, cause the computing device to perform operations comprising: receiving one or more natural language queries from a user; determining whether servicing a given natural language query needs data stored in a relational data store or a multi-dimensional data store, wherein the relational data store stores fact data and the multi-dimensional data store data store stores aggregated fact data, formed via a segmented aggregation process involving aggregation along multiple dimensions in a determined sequence, in a multi-dimensional data structure, and wherein the multi-dimensional data store is configured to communicate bi-directionally with the relational data store; in response to determining that servicing the given natural language query needs data stored in the relational data store, automatically routing the given natural language query to the relational data store, so that data is accessed from the relational data store and forwarded to the user; and in response to determining that servicing the given natural language query needs data stored in the multi-dimensional data store formed via the segmented aggregation process, automatically routing the given natural language query to the multi-dimensional data store, so that aggregated fact data can be accessed and forwarded to the user.
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12. A tangible computer-readable medium encoded with instructions that, in response to execution by a computing device, cause the computing device to perform operations comprising: receiving one or more natural language queries from a user; determining whether servicing a given natural language query needs data stored in a relational data store or a multi-dimensional data store, wherein the relational data store stores fact data and the multi-dimensional data store data store stores aggregated fact data, formed via a segmented aggregation process involving aggregation along multiple dimensions in a determined sequence, in a multi-dimensional data structure, and wherein the multi-dimensional data store is configured to communicate bi-directionally with the relational data store; in response to determining that servicing the given natural language query needs data stored in the relational data store, automatically routing the given natural language query to the relational data store, so that data is accessed from the relational data store and forwarded to the user; and in response to determining that servicing the given natural language query needs data stored in the multi-dimensional data store formed via the segmented aggregation process, automatically routing the given natural language query to the multi-dimensional data store, so that aggregated fact data can be accessed and forwarded to the user. 14. The tangible computer-readable medium of claim 12 , wherein the multi-dimensional data store is generated by calculating aggregated fact data from the fact data according to a multi-dimensional data aggregation process, and storing the aggregated fact data in the multi-dimensional data store.
| 0.634809 |
15. The method of claim 1 , wherein the visual characteristic comprises a text formatting characteristic.
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15. The method of claim 1 , wherein the visual characteristic comprises a text formatting characteristic. 16. The method of claim 15 , wherein the visual characteristic comprises boldface.
| 0.966137 |
34. A system for providing audio-based guidance in a media guide, the system comprising control circuitry configured to: receive a plurality of listings, wherein each of the plurality of listings is associated with a respective media item of a plurality of media items, the plurality of media items including a first media item having audio-friendly characteristics that make media content desirable to users who have difficulties viewing or understanding a visual portion of the content, the plurality of media items including a second media item not having the audio-friendly characteristics; generate for display the plurality of listings; receive a first user command to navigate to a listing associated with the first media item; receive a second user command to obtain additional information associated with the first media item; automatically determine that the first media item has the audio-friendly characteristics; and in response to receiving the second user command, play an audio notification when the first media item is determined to have the audio-friendly characteristics.
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34. A system for providing audio-based guidance in a media guide, the system comprising control circuitry configured to: receive a plurality of listings, wherein each of the plurality of listings is associated with a respective media item of a plurality of media items, the plurality of media items including a first media item having audio-friendly characteristics that make media content desirable to users who have difficulties viewing or understanding a visual portion of the content, the plurality of media items including a second media item not having the audio-friendly characteristics; generate for display the plurality of listings; receive a first user command to navigate to a listing associated with the first media item; receive a second user command to obtain additional information associated with the first media item; automatically determine that the first media item has the audio-friendly characteristics; and in response to receiving the second user command, play an audio notification when the first media item is determined to have the audio-friendly characteristics. 43. The system of claim 34 , wherein the control circuitry is further configured to: receive a third user command to access the first media item; and access the first media item in response to the third user command to access the first media item.
| 0.545356 |
19. A computer program product for editing text, the computer program product comprising a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising computer readable program code configured to: in response to an instruction to apply editing to at least one sentence within a document that is displayed on a display screen, changing a first word or phrase in the at least one sentence for a second word or phrase while maintaining semantic content of the first word or phrase and such that the at least one sentence falls within a predetermined range, wherein the changing the first word or phrase comprises one of: in response to the second word or phrase having more characters or words than the first word or phrase, changing a third word or phrase within the at least one sentence including the second word or phrase for a fourth word or phrase, such that the at least one sentence including the second word or phrase falls within the predetermined range; and in response the second word or phrase having fewer characters or words than the first word or phrase, changing a fifth word or phrase within the at least one sentence including the second word or phrase for a sixth word or phrase, such that the at least one sentence including the second word or phrase falls within the predetermined range; and displaying the at least one sentence including the second word or phrase, and one of the fourth word or phrase and the sixth word or phrase, on the display screen.
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19. A computer program product for editing text, the computer program product comprising a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising computer readable program code configured to: in response to an instruction to apply editing to at least one sentence within a document that is displayed on a display screen, changing a first word or phrase in the at least one sentence for a second word or phrase while maintaining semantic content of the first word or phrase and such that the at least one sentence falls within a predetermined range, wherein the changing the first word or phrase comprises one of: in response to the second word or phrase having more characters or words than the first word or phrase, changing a third word or phrase within the at least one sentence including the second word or phrase for a fourth word or phrase, such that the at least one sentence including the second word or phrase falls within the predetermined range; and in response the second word or phrase having fewer characters or words than the first word or phrase, changing a fifth word or phrase within the at least one sentence including the second word or phrase for a sixth word or phrase, such that the at least one sentence including the second word or phrase falls within the predetermined range; and displaying the at least one sentence including the second word or phrase, and one of the fourth word or phrase and the sixth word or phrase, on the display screen. 20. The computer program product according to claim 19 , wherein displaying the at least one sentence including the second word or phrase on the display screen comprises displaying at least one of the second word or phrase, the fourth word or phrase, and the sixth word or phrase to a user; the method further comprising: in response to at least one of the second word or phrase, the fourth word or phrase and the sixth word or phrase being selected by the user, displaying on the display screen a conversion list indicating at least one conversion candidate that maintains the semantic content of the selected word or phrase; and in response to a conversion candidate on the conversion list being selected by the user, replacing the selected word or phrase with the conversion candidate selected by the user.
| 0.60969 |
2. The method of claim 1 , further comprising communicating the offline grammar model to the resource-constrained offline device for storage by the resource-constrained offline device and for use by an offline semantic processor of the resource-constrained offline device, the offline semantic processor using the offline grammar model to map text, outputted by a voice to text module, to a corresponding action of the offline grammar model, and to identify one or more attributes, for the corresponding action, that constrain the corresponding action based on the corresponding parameters.
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2. The method of claim 1 , further comprising communicating the offline grammar model to the resource-constrained offline device for storage by the resource-constrained offline device and for use by an offline semantic processor of the resource-constrained offline device, the offline semantic processor using the offline grammar model to map text, outputted by a voice to text module, to a corresponding action of the offline grammar model, and to identify one or more attributes, for the corresponding action, that constrain the corresponding action based on the corresponding parameters. 3. The method of claim 2 , wherein communicating the offline grammar model to the resource-constrained offline device dynamically updates the offline grammar model stored in the resource-constrained offline device.
| 0.798896 |
13. The speech recognition apparatus according to claim 11, wherein, when the membership degree vector corresponding to a frame t of the input pattern is defined as a.sub.t =(a.sub.t1, . . . ,a.sub.tM), the membership degree vector corresponding to a frame j of the reference pattern is defined as b.sub.j =(b.sub.j1, . . . ,b.sub.jM), a k-th (t,j) coordinate on the matching path is defined as x(k)=(t(k),j(k)) and a weighting coefficient at x(k) is defined as w(x(k)), the similarity degree of a.sub.t(k) and b.sub.j(k) is specified as below, ##EQU79## and an accumulated similarity degree along the path of vector series a.sub.t(1), . . . ,a.sub.t(K) and b.sub.j(1), . . . ,b.sub.j(K) is specified as below, ##EQU80## wherein for 1.ltoreq.n.ltoreq.k-1, if t(k)-t(k-n)=1, w(x(k-n+1))+ . . .+w(x(k))=1.
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13. The speech recognition apparatus according to claim 11, wherein, when the membership degree vector corresponding to a frame t of the input pattern is defined as a.sub.t =(a.sub.t1, . . . ,a.sub.tM), the membership degree vector corresponding to a frame j of the reference pattern is defined as b.sub.j =(b.sub.j1, . . . ,b.sub.jM), a k-th (t,j) coordinate on the matching path is defined as x(k)=(t(k),j(k)) and a weighting coefficient at x(k) is defined as w(x(k)), the similarity degree of a.sub.t(k) and b.sub.j(k) is specified as below, ##EQU79## and an accumulated similarity degree along the path of vector series a.sub.t(1), . . . ,a.sub.t(K) and b.sub.j(1), . . . ,b.sub.j(K) is specified as below, ##EQU80## wherein for 1.ltoreq.n.ltoreq.k-1, if t(k)-t(k-n)=1, w(x(k-n+1))+ . . .+w(x(k))=1. 15. The speech recognition apparatus according to claim 13, wherein for x(k)=(t,j),k-1.gtoreq.n.gtoreq.1, the matching path includes either of (1) x(k-1)=(t-1,j-n) or x(k-1)=(t-1,j), (2) x(k-1)=(t-1,j-1) or x(k-1)=(t-1,j), x(k-m)=(t-1,j-m) for m=2, . . . ,n, (3) x(k-m)=(t,j-m), x(k-n)=(t-1,j-n) for m=1, . . . ,n-1, (4) x(k-m)=(t,j-m), x(k-n)=(t-1,j-n) for m=1, . . . ,n-1 and (5) x(k-1)=(t-1,j-1) or x(k-1)=(t-1,j), x(k-m)=(t-1,j-m) for m=2, . . . ,n and w(x(k))=1 for the path(1), w(x(k))=1,w(x(k-m+1))=0 for the path(2), w(x(K-m+1))=0, w(x(k-n+1))=1 for the path(3) and w(x(k-m+1))=1/n for the paths (4) and (5).
| 0.765439 |
26. A method, comprising: receiving message data at a server from a first remote device, the message data associated with a message and the message including text of one or more words, one or more characters, one or more symbols, or any combination thereof; determining, at the server, an intended recipient of the message; identifying one or more characteristics of the intended recipient, wherein the one or more identified characteristics include at least a geographical location of the intended recipient and a climatic condition associated with the geographical location of the intended recipient; parsing the message data to identify text, symbols, or any combination thereof, that match criteria associated with an advertisement campaign, wherein the advertisement campaign identifies a number of potential customers to receive at least one advertisement associated with the advertisement campaign; composing an advertisement based on an advertisement message associated with the advertisement campaign and based on at least one of the one or more identified characteristics of the intended recipient and the text, symbols, or any combination thereof, that match the criteria associated with the advertisement campaign, wherein the advertisement message includes a graphical image that corresponds to a pre-recorded audio message; determining whether a second word is more effective for marketing purposes at the identified geographical location of the intended recipient than a first word included in the advertisement; replacing the first word with the second word to produce a modified advertisement in response to determining that the second word is more effective for marketing purposes than the first word at the identified geographical location of the intended recipient; creating, at the server, an audio file based on the message data and the modified advertisement, wherein the pre-recorded audio message is integrated into the audio file before sending the audio file to a second remote device associated with the intended recipient; creating, at the server, a text file that includes a first portion corresponding to the message data and indicating a first display color and a second portion corresponding to the modified advertisement and indicating a second display color; and sending the text file and the audio file from the server to the second remote device.
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26. A method, comprising: receiving message data at a server from a first remote device, the message data associated with a message and the message including text of one or more words, one or more characters, one or more symbols, or any combination thereof; determining, at the server, an intended recipient of the message; identifying one or more characteristics of the intended recipient, wherein the one or more identified characteristics include at least a geographical location of the intended recipient and a climatic condition associated with the geographical location of the intended recipient; parsing the message data to identify text, symbols, or any combination thereof, that match criteria associated with an advertisement campaign, wherein the advertisement campaign identifies a number of potential customers to receive at least one advertisement associated with the advertisement campaign; composing an advertisement based on an advertisement message associated with the advertisement campaign and based on at least one of the one or more identified characteristics of the intended recipient and the text, symbols, or any combination thereof, that match the criteria associated with the advertisement campaign, wherein the advertisement message includes a graphical image that corresponds to a pre-recorded audio message; determining whether a second word is more effective for marketing purposes at the identified geographical location of the intended recipient than a first word included in the advertisement; replacing the first word with the second word to produce a modified advertisement in response to determining that the second word is more effective for marketing purposes than the first word at the identified geographical location of the intended recipient; creating, at the server, an audio file based on the message data and the modified advertisement, wherein the pre-recorded audio message is integrated into the audio file before sending the audio file to a second remote device associated with the intended recipient; creating, at the server, a text file that includes a first portion corresponding to the message data and indicating a first display color and a second portion corresponding to the modified advertisement and indicating a second display color; and sending the text file and the audio file from the server to the second remote device. 27. The method of claim 26 , wherein the text file is sent from the server to the second remote device via a short message service (SMS) message.
| 0.675 |
1. In a computerized search system which queries are submitted by users who receive, in response, a list of documents selected from a corpus of documents wherein the list comprises documents deemed responsive to a user's query, a method of preprocessing the query comprising: obtaining a base query from a user, wherein the base query comprises a plurality of words; determining a base distribution of nodes of a taxonomy that have non-zero probabilities of being relevant to the base query, wherein the taxonomy is a taxonomy of topics into which documents of the corpus of documents might be assigned; modifying the base query to form a truncated query when it is determined that the base query will return no results, wherein modifying the base query to form the truncated query comprises: identifying word pairs in the base query, determining pair distributions for word pairs over the taxonomy, selecting a desired word pair based in part on the pair distributions, generating a first query by omitting from the base query a first word of the desired word pair, generating a second query by omitting from the base query a second word from the desired word pair, determining a first count of documents corresponding to the first query, determining a second count of documents corresponding to the second query, and determining at least one word to remove from the base query based on the first and second counts such that the truncated query comprises a portion of the base query from which the at least one word is removed; running the truncated query against the corpus of documents to obtain a results list of one or more documents in the document corpus deemed responsive to the truncated query; and outputting the results list as the list comprising documents deemed responsive to the user's query.
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1. In a computerized search system which queries are submitted by users who receive, in response, a list of documents selected from a corpus of documents wherein the list comprises documents deemed responsive to a user's query, a method of preprocessing the query comprising: obtaining a base query from a user, wherein the base query comprises a plurality of words; determining a base distribution of nodes of a taxonomy that have non-zero probabilities of being relevant to the base query, wherein the taxonomy is a taxonomy of topics into which documents of the corpus of documents might be assigned; modifying the base query to form a truncated query when it is determined that the base query will return no results, wherein modifying the base query to form the truncated query comprises: identifying word pairs in the base query, determining pair distributions for word pairs over the taxonomy, selecting a desired word pair based in part on the pair distributions, generating a first query by omitting from the base query a first word of the desired word pair, generating a second query by omitting from the base query a second word from the desired word pair, determining a first count of documents corresponding to the first query, determining a second count of documents corresponding to the second query, and determining at least one word to remove from the base query based on the first and second counts such that the truncated query comprises a portion of the base query from which the at least one word is removed; running the truncated query against the corpus of documents to obtain a results list of one or more documents in the document corpus deemed responsive to the truncated query; and outputting the results list as the list comprising documents deemed responsive to the user's query. 3. The method of claim 1 , wherein the corpus of documents comprises web pages and the list of documents comprises at least a list of URLs.
| 0.79351 |
1. A method of adjusting model parameters in a speech recognition system comprising: in a speech recognition system executed by computer system that combines recognition outputs from a plurality of parallel speech recognition processes that operate on a given speech input word sequence and produce different competing recognition outputs which are then combined to determine a final recognition output; wherein the speech recognition processes are complementary so as to produce different recognition errors on a given same speech input; performing a discriminative adjustment process including: i. selecting at least one acoustic model of the system, and ii. adjusting a plurality of model parameters of the selected acoustic model based on a joint discriminative criterion over a plurality of complementary acoustic models to lower combined recognition WER in the system over only independently discriminatively trained recognition systems.
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1. A method of adjusting model parameters in a speech recognition system comprising: in a speech recognition system executed by computer system that combines recognition outputs from a plurality of parallel speech recognition processes that operate on a given speech input word sequence and produce different competing recognition outputs which are then combined to determine a final recognition output; wherein the speech recognition processes are complementary so as to produce different recognition errors on a given same speech input; performing a discriminative adjustment process including: i. selecting at least one acoustic model of the system, and ii. adjusting a plurality of model parameters of the selected acoustic model based on a joint discriminative criterion over a plurality of complementary acoustic models to lower combined recognition WER in the system over only independently discriminatively trained recognition systems. 11. A method according to claim 1 , wherein discriminative adjusting a plurality of model parameters includes performing parameter adaptation using at least one non-linear transformation.
| 0.5 |
6. A method of extracting universal scene descriptors (USDs) from a scene, comprising: providing a sequence of one or more unsegmented images of a scene; unsupervised decomposition of the scene captured in each said image into at least one region of interest (ROI), the scene in at least one said image decomposed into a plurality of ROIs; extracting multiple classes of biologically-inspired visual features from the scene captured in each image for each ROI; assembling the visual features from the plurality of classes into a universal feature vector for each said ROI, each said universal feature vector providing a USD for the scene; presenting the universal feature vector for each ROI in each image to a plurality of classifiers that extract semantic information from the universal feature vector for the scene at different levels of a complex scene understanding hierarchy and output multiple scene semantic descriptors at multiple semantic levels; assembling the scene semantic descriptors into a metadata vector for each said ROI; converting the metadata vector into a structured description for each said ROI; assembling the structured descriptions for all ROI in a scene into a single structured description; and storing the structured description as metadata for the sequence of images.
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6. A method of extracting universal scene descriptors (USDs) from a scene, comprising: providing a sequence of one or more unsegmented images of a scene; unsupervised decomposition of the scene captured in each said image into at least one region of interest (ROI), the scene in at least one said image decomposed into a plurality of ROIs; extracting multiple classes of biologically-inspired visual features from the scene captured in each image for each ROI; assembling the visual features from the plurality of classes into a universal feature vector for each said ROI, each said universal feature vector providing a USD for the scene; presenting the universal feature vector for each ROI in each image to a plurality of classifiers that extract semantic information from the universal feature vector for the scene at different levels of a complex scene understanding hierarchy and output multiple scene semantic descriptors at multiple semantic levels; assembling the scene semantic descriptors into a metadata vector for each said ROI; converting the metadata vector into a structured description for each said ROI; assembling the structured descriptions for all ROI in a scene into a single structured description; and storing the structured description as metadata for the sequence of images. 7. The method of claim 6 , wherein the visual features are assembled into the universal feature vector by, normalizing all features to a fixed range; and concatenating all visual features into a fixed length universal feature vector.
| 0.597107 |
1. A method for providing a video in response to a query, the method comprising using at least one hardware processor for: receiving a multiplicity of videos from a source; for each video: receiving meta data related to the video; extracting from the video a video frame containing computer code; identifying a region of interest (ROI) within the video frame; performing optical character recognition (OCR) of the ROI to extract a code segment; analyzing the code segment, said analyzing comprising: (a) semantically analyzing the code segment to obtain a first rank, (b) structurally analyzing the code segment to obtain a second rank, and (c) analyzing the meta data to obtain a third rank; and combining the first rank, second rank and third rank into a total rank associated with the code segment; receiving a query; matching the query to each code segment to identify matching code segments and associated videos; and providing the associated videos in accordance with total ranks associated with the matching code segments.
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1. A method for providing a video in response to a query, the method comprising using at least one hardware processor for: receiving a multiplicity of videos from a source; for each video: receiving meta data related to the video; extracting from the video a video frame containing computer code; identifying a region of interest (ROI) within the video frame; performing optical character recognition (OCR) of the ROI to extract a code segment; analyzing the code segment, said analyzing comprising: (a) semantically analyzing the code segment to obtain a first rank, (b) structurally analyzing the code segment to obtain a second rank, and (c) analyzing the meta data to obtain a third rank; and combining the first rank, second rank and third rank into a total rank associated with the code segment; receiving a query; matching the query to each code segment to identify matching code segments and associated videos; and providing the associated videos in accordance with total ranks associated with the matching code segments. 2. The method according to claim 1 , further comprising displaying to a user a list of videos from which code segments being associated with highest ranks have been extracted.
| 0.637483 |
2. The apparatus according to claim 1 , further comprising a document obtaining unit that obtains the second document data identified by the identifying unit.
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2. The apparatus according to claim 1 , further comprising a document obtaining unit that obtains the second document data identified by the identifying unit. 4. The apparatus according to claim 2 , further comprising: a type determining unit that determines a type of the text document data, and embeds the type in the text document data; and a display unit that displays the second document data obtained by the document obtaining unit while classifying in units of types embedded in the text document data.
| 0.910714 |
2. The system of claim 1 , wherein the software component is a software stub.
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2. The system of claim 1 , wherein the software component is a software stub. 3. The system of claim 2 ,further comprising: a linkage interface class defined in an Interface Description Language, said linkage interface class defining a template for the stub and a template for a skeleton, wherein the first linkage section is included within an instance of the stub, and wherein the second linkage section is included within an instance of the skeleton.
| 0.937229 |
13. A system comprising: a translation server operable to perform machine translation obtaining translation model data from a translation model for translation between a source language and a target language and language model data from a language model for the target language, the translation server further operable to translate text in the source language into the target language using the obtained translation model data and language model data, the translation server comprising: a request queue operable to store requests for language model data to be obtained for translating a segment in the source language, a segment translation server cache operable to store language model data obtained by the requests by the translation server; and a second segment translation server cache storing a selected portion of the language model, wherein the translation server is operable to: periodically delete data in the segment translation server cache, process the translation of the segment using language model data from a second language model for the target language to produce an initial translation of the segment before the requests for the language data in the language model in the request queue are sent out, update the requests for the language model data of the language model in the request queue based on the initial translation, send out the updated requests in the request queue to obtain language model data from the language model for processing the initial translation, and after the updated requests are served and the data for the updated requests are stored in the segment translation server cache, process the initial translation with the data for the updated requests to produce a final translation.
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13. A system comprising: a translation server operable to perform machine translation obtaining translation model data from a translation model for translation between a source language and a target language and language model data from a language model for the target language, the translation server further operable to translate text in the source language into the target language using the obtained translation model data and language model data, the translation server comprising: a request queue operable to store requests for language model data to be obtained for translating a segment in the source language, a segment translation server cache operable to store language model data obtained by the requests by the translation server; and a second segment translation server cache storing a selected portion of the language model, wherein the translation server is operable to: periodically delete data in the segment translation server cache, process the translation of the segment using language model data from a second language model for the target language to produce an initial translation of the segment before the requests for the language data in the language model in the request queue are sent out, update the requests for the language model data of the language model in the request queue based on the initial translation, send out the updated requests in the request queue to obtain language model data from the language model for processing the initial translation, and after the updated requests are served and the data for the updated requests are stored in the segment translation server cache, process the initial translation with the data for the updated requests to produce a final translation. 17. The system of claim 13 , wherein the translation server is further operable to: obtain the translation model data from the translation model based on the segment; translate the segment into a set of possible translations based on the translation model data; obtain the language model data from the language model based on the set of possible translations, the language model data matching at least one token in at least one possible translation of the set of possible translations; and determine a translation of the segment based on the obtained language model data and the set of possible translations.
| 0.573513 |
12. The system of claim 11 , wherein the retrieved information describing media is a list of actors, directors, composers, titles, and locations.
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12. The system of claim 11 , wherein the retrieved information describing media is a list of actors, directors, composers, titles, and locations. 15. The system of claim 12 , wherein the graph further models relative popularity of each piece of information in the list.
| 0.92007 |
13. The system of claim 9 , wherein the rule includes a condition clause that is utilized to identify the first candidate value in the first query and a predicate clause that includes the aspect- value pair.
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13. The system of claim 9 , wherein the rule includes a condition clause that is utilized to identify the first candidate value in the first query and a predicate clause that includes the aspect- value pair. 14. The system of claim 13 , wherein the rule includes a condition clause that is utilized to identify the first candidate value in the first data item and a condition clause that includes the aspect-value pair.
| 0.957211 |
8. A computer-implemented method for document authentication and identification, comprising: receiving a digitized document; comparing the digitized document to a set of markers to determine whether the digitized document is an encoded document with one or more text characters replaced, wherein the one or more text characters replaced includes at least one letter, number, symbol or space changed to another letter, number, or symbol; in response to determining that the digitized document is an encoded document with one or more characters replaced, extracting information from the set of markers using a decoder according to an encoding strategy; and comparing the extracted information and the set of markers with data stored in an encoding history to authenticate and identify the received digitized document.
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8. A computer-implemented method for document authentication and identification, comprising: receiving a digitized document; comparing the digitized document to a set of markers to determine whether the digitized document is an encoded document with one or more text characters replaced, wherein the one or more text characters replaced includes at least one letter, number, symbol or space changed to another letter, number, or symbol; in response to determining that the digitized document is an encoded document with one or more characters replaced, extracting information from the set of markers using a decoder according to an encoding strategy; and comparing the extracted information and the set of markers with data stored in an encoding history to authenticate and identify the received digitized document. 10. The method of claim 8 wherein the decoder determines that the set of markers comprise at least one of: an inserted signature quote with information encoded in characters of the signature quote, and a modified sentence syntax with the information encoded in a modified location.
| 0.923161 |
17. The computer program product of claim 16 , the operations further comprising: receiving a query; and retrieving information from the second ontology based on the query, the retrieving comprising combining contributions of pertinence, with respect to the query, from the machine-learned new features and the symbolic knowledge.
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17. The computer program product of claim 16 , the operations further comprising: receiving a query; and retrieving information from the second ontology based on the query, the retrieving comprising combining contributions of pertinence, with respect to the query, from the machine-learned new features and the symbolic knowledge. 36. The computer program product of claim 17 , wherein the query comprises a search string, and the retrieving comprises: identifying a document related to the search string; and obtaining information associated with the identified document.
| 0.926594 |
24. The method of claim 1 , wherein the at least one action comprises transmitting the at least one document to a destination, the method further comprising determining a destination.
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24. The method of claim 1 , wherein the at least one action comprises transmitting the at least one document to a destination, the method further comprising determining a destination. 26. The method of claim 24 , wherein determining a destination comprises reading an indicator of a destination from the image.
| 0.945085 |
1. A teaching material generation method for languages, comprising: providing, in a storage module, a plurality of social circumstances and a plurality of contextual situations, wherein the contextual situations comprise people, event, time, location, objects, or expressions, and wherein the social circumstances comprise greetings, requests, descriptions, praising, apologizing, invitations, responses, promising, declining, or farewell; receiving, by a user interface, a selection corresponding to at least one of the social circumstances; receiving, by the user interface, a selection corresponding to at least two of the contextual situations; and generating, by a processing module, teaching material, according to the selected social circumstance and the selected contextual situations.
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1. A teaching material generation method for languages, comprising: providing, in a storage module, a plurality of social circumstances and a plurality of contextual situations, wherein the contextual situations comprise people, event, time, location, objects, or expressions, and wherein the social circumstances comprise greetings, requests, descriptions, praising, apologizing, invitations, responses, promising, declining, or farewell; receiving, by a user interface, a selection corresponding to at least one of the social circumstances; receiving, by the user interface, a selection corresponding to at least two of the contextual situations; and generating, by a processing module, teaching material, according to the selected social circumstance and the selected contextual situations. 22. The method of claim 1 , wherein the user interface allows the simultaneous selection of multiple contextual situations and multiple social circumstances, and the processing module generates teaching material according to the multiple selected social circumstances and contextual situations.
| 0.620579 |
18. The method of claim 17 , wherein calculating a pricing structure comprises co-multiplying a weight factor for the selected geo-targeted area(s), a factor for the selected platform(s), a number of times the browser plug-in has been downloaded within a given time period and a leased term popularity factor.
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18. The method of claim 17 , wherein calculating a pricing structure comprises co-multiplying a weight factor for the selected geo-targeted area(s), a factor for the selected platform(s), a number of times the browser plug-in has been downloaded within a given time period and a leased term popularity factor. 19. The method of claim 18 , wherein the geo-targeted area(s) comprises at least one of national, regional, state and/or zip code level geo-targeting.
| 0.937057 |
31. An apparatus comprising: a processor; memory in electronic communication with the processor; and instructions stored in the memory, the instructions being executable by the processor to: receive a portion of an audio signal at a first classifier in a digital audio device; classify, by the digital audio device, the portion of the audio signal at the first classifier as speech or as music; and process the portion of the audio signal, wherein processing the portion of the audio signal comprises: if the portion is classified by the first classifier as speech, then encode, by the digital audio device, the speech using a first coding mode; or if the portion is classified by the first classifier as music, then: provide the portion to a second classifier in the digital audio device; classify, by the digital audio device, the portion at the second classifier as speech or as music; and encode the portion of the audio signal, wherein encoding the portion of the audio signal comprises: if the portion is classified at the second classifier as speech, then encode, by the digital audio device, the portion using a second coding mode; or if the portion is classified at the second classifier as music, then encode, by the digital audio device, the portion using a third coding mode.
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31. An apparatus comprising: a processor; memory in electronic communication with the processor; and instructions stored in the memory, the instructions being executable by the processor to: receive a portion of an audio signal at a first classifier in a digital audio device; classify, by the digital audio device, the portion of the audio signal at the first classifier as speech or as music; and process the portion of the audio signal, wherein processing the portion of the audio signal comprises: if the portion is classified by the first classifier as speech, then encode, by the digital audio device, the speech using a first coding mode; or if the portion is classified by the first classifier as music, then: provide the portion to a second classifier in the digital audio device; classify, by the digital audio device, the portion at the second classifier as speech or as music; and encode the portion of the audio signal, wherein encoding the portion of the audio signal comprises: if the portion is classified at the second classifier as speech, then encode, by the digital audio device, the portion using a second coding mode; or if the portion is classified at the second classifier as music, then encode, by the digital audio device, the portion using a third coding mode. 35. The processor of claim 31 , wherein the instructions are also executable to determine if the second classifier is enabled prior to providing the portion to the second classifier, and if the second classifier is not enabled, then encode the portion with the third coding mode.
| 0.543883 |
1. A computer device including a processor, a memory coupled to the processor, and a program stored in the memory, wherein the computer is configured to execute the program and perform the steps of: providing a collection of documents, wherein said collection includes at least one document; receiving a word or word string query to be analyzed; searching by a processor, said collection of documents for the query to be analyzed and returning documents containing the query to be analyzed; determining a user-defined amount of words or word strings or both to the left of said query to be analyzed in said returned documents based on their frequency and creating a Left Signature List comprising each of said words and word strings to the left of said query to be analyzed in said returned documents; searching said collection of documents for the words and word strings on the Left Signature List and returning second documents containing said words and word strings on the Left Signature List; determining a user-defined amount of words or word strings or both to the right of each of said words and word strings comprising said Left Signature List in said second returned documents and creating Left Anchor Lists comprising each of said words and word strings to the right of each of said words and word strings on the Left Signature List based on their frequency in said second returned documents; determining a user-defined number of words or word strings or both to the right of said query to be analyzed in said returned documents and creating a Right Signature List comprising each of said words and word strings to the right of said query to be analyzed in said returned documents based on their frequency; searching said collection of documents for each of said words and word strings on the Right Signature List and returning third documents containing said words and word strings on the Right Signature List; determining a user-defined number of words or word strings or both to the left of each of said words and word strings comprising said Right Signature List in said third returned documents and creating Right Anchor Lists comprising each of said words and word strings to the left of each of said words and word strings on the Right Signature List based on their frequency in said third returned documents; and ranking results based on the number of different Anchor Lists on which the result appears so long as the result appears on at least one Left Anchor List and one Right Anchor List.
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1. A computer device including a processor, a memory coupled to the processor, and a program stored in the memory, wherein the computer is configured to execute the program and perform the steps of: providing a collection of documents, wherein said collection includes at least one document; receiving a word or word string query to be analyzed; searching by a processor, said collection of documents for the query to be analyzed and returning documents containing the query to be analyzed; determining a user-defined amount of words or word strings or both to the left of said query to be analyzed in said returned documents based on their frequency and creating a Left Signature List comprising each of said words and word strings to the left of said query to be analyzed in said returned documents; searching said collection of documents for the words and word strings on the Left Signature List and returning second documents containing said words and word strings on the Left Signature List; determining a user-defined amount of words or word strings or both to the right of each of said words and word strings comprising said Left Signature List in said second returned documents and creating Left Anchor Lists comprising each of said words and word strings to the right of each of said words and word strings on the Left Signature List based on their frequency in said second returned documents; determining a user-defined number of words or word strings or both to the right of said query to be analyzed in said returned documents and creating a Right Signature List comprising each of said words and word strings to the right of said query to be analyzed in said returned documents based on their frequency; searching said collection of documents for each of said words and word strings on the Right Signature List and returning third documents containing said words and word strings on the Right Signature List; determining a user-defined number of words or word strings or both to the left of each of said words and word strings comprising said Right Signature List in said third returned documents and creating Right Anchor Lists comprising each of said words and word strings to the left of each of said words and word strings on the Right Signature List based on their frequency in said third returned documents; and ranking results based on the number of different Anchor Lists on which the result appears so long as the result appears on at least one Left Anchor List and one Right Anchor List. 3. The computer device of claim 1 , wherein said ranking results includes adding a total frequency of each word or word string occurring in said Left Anchor Lists to a total frequency of said word or word string occurring in said Right Anchor Lists, for each word or word string occurring in at least one Left Anchor List and one Right Anchor List.
| 0.5 |
1. A computing system for providing textual output of an input method editor to an application, the computing system comprising: a first memory region that stores a first version of a body of text to which textual output of the input method editor is applied; a second memory region that stores a second version of a body of text to which text modifications performed by the application are applied; and a reconciliation subsystem configured to reconcile the contents of the first and second memory regions in a manner that favors the contents of the second memory region, including: reversing edits made by the input method editor to text stored in the first memory region; and applying text modifications performed by the application to the text stored in the first memory region.
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1. A computing system for providing textual output of an input method editor to an application, the computing system comprising: a first memory region that stores a first version of a body of text to which textual output of the input method editor is applied; a second memory region that stores a second version of a body of text to which text modifications performed by the application are applied; and a reconciliation subsystem configured to reconcile the contents of the first and second memory regions in a manner that favors the contents of the second memory region, including: reversing edits made by the input method editor to text stored in the first memory region; and applying text modifications performed by the application to the text stored in the first memory region. 8. The computing system of claim 1 , wherein reconciling the contents of the first and second memory regions in a manner that favors the contents of the second memory region includes changing content of the first memory to contain content in the first memory.
| 0.74622 |
24. A computer program product, encoded on a computer readable medium, operable to cause a data processing apparatus to perform operations comprising: selecting a candidate query in a query sequence stored in a query log, the query sequence including an initial query and one or more revised queries and defining an order in which the queries were submitted for a search session; selecting a revised query subsequent to the candidate query in the order; determining a quality score for the revised query; determining a navigation score for the revised query; and determining that the quality score for the revised query is greater than a quality score threshold and that the navigation score for the revised query is greater than a navigation score threshold, and in response: identifying a navigational resource for the revised query; and associating the navigational resource with the candidate query, the association specifying the navigational resource as being relevant to the candidate query in a search operation.
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24. A computer program product, encoded on a computer readable medium, operable to cause a data processing apparatus to perform operations comprising: selecting a candidate query in a query sequence stored in a query log, the query sequence including an initial query and one or more revised queries and defining an order in which the queries were submitted for a search session; selecting a revised query subsequent to the candidate query in the order; determining a quality score for the revised query; determining a navigation score for the revised query; and determining that the quality score for the revised query is greater than a quality score threshold and that the navigation score for the revised query is greater than a navigation score threshold, and in response: identifying a navigational resource for the revised query; and associating the navigational resource with the candidate query, the association specifying the navigational resource as being relevant to the candidate query in a search operation. 61. The computer program product of claim 24 , wherein determining a quality score for the revised query comprises determining a quality score for the revised query relative to the candidate query.
| 0.796169 |
13. An information handling system, comprising: at least one processor, wherein the at least one processor is operable to perform a method comprising: receiving a request for data visualization; wherein the request specifies input data, at least one user query, and a data-visualization type; inferring, without user-modification of the request, at least one additional query not specified by the at least one user query based on a user-interface (UI) range of freedom associated with the request, wherein the UI range of freedom encompasses a plurality of modifications collectively enabled by a plurality of UI controls of a visualization interface on which the requested visualization will be served; causing a map-reduce framework to process the input data according to the at least one user query and the at least one additional query, the causing yielding resultant data; storing in a cache a portion of the resultant data that relates to the at least one additional query; generating the requested data visualization based on a portion of the resultant data that relates to the at least one user query; and serving the requested visualization on the visualization interface.
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13. An information handling system, comprising: at least one processor, wherein the at least one processor is operable to perform a method comprising: receiving a request for data visualization; wherein the request specifies input data, at least one user query, and a data-visualization type; inferring, without user-modification of the request, at least one additional query not specified by the at least one user query based on a user-interface (UI) range of freedom associated with the request, wherein the UI range of freedom encompasses a plurality of modifications collectively enabled by a plurality of UI controls of a visualization interface on which the requested visualization will be served; causing a map-reduce framework to process the input data according to the at least one user query and the at least one additional query, the causing yielding resultant data; storing in a cache a portion of the resultant data that relates to the at least one additional query; generating the requested data visualization based on a portion of the resultant data that relates to the at least one user query; and serving the requested visualization on the visualization interface. 15. The information handling system of claim 13 , wherein the method comprises, as a modification to the request is received via the visualization interface: determining whether the cache fulfills at least one new user query specified by the modification; and responsive to a determination that the cache fulfills the at least one new user query: retrieving data from the cache that fulfills the at least one new user query; generating an updated data visualization based on the retrieved data; and serving the updated data visualization on the visualization interface.
| 0.5 |
1. A computer-implemented method for real-time document sharing and editing, comprising: recording a count of one or more tags being traversed to reach a position of a cursor of a user editing a copy of a document; recording a position of the cursor; receiving an update to the copy of the document from a server; generating an updated copy of the document; using the position of the cursor and the count of the one or more tags to determine an updated position of the cursor in the updated copy of the document; recording one or more types of the one or more tags being traversed to reach the position of the cursor; and displaying to the user the updated copy of the document with the cursor displayed at the updated position.
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1. A computer-implemented method for real-time document sharing and editing, comprising: recording a count of one or more tags being traversed to reach a position of a cursor of a user editing a copy of a document; recording a position of the cursor; receiving an update to the copy of the document from a server; generating an updated copy of the document; using the position of the cursor and the count of the one or more tags to determine an updated position of the cursor in the updated copy of the document; recording one or more types of the one or more tags being traversed to reach the position of the cursor; and displaying to the user the updated copy of the document with the cursor displayed at the updated position. 2. The computer-implemented method of claim 1 , wherein the position of the cursor is saved in a form of navigation directions from a beginning of the copy of the document and from an end of the copy of the document.
| 0.68732 |
1. A method for providing an interactive knowledge based community solution, the community comprising multiple users, each of the multiple users belonging to a user type, the user types comprising participant, mentor, and subject matter expert, the method comprising the steps of: (a) associating a user profile with at least one of the multiple users; (b) matching a participant user with a mentor user based on user profiles of the participant user and the mentor user; (c) matching a participant user with at least one subject matter expert user based on the user profile of the participant user including at least one of an industry identifier and an occupation identifier, and based on the user profile of the at least one subject matter expert user including at least one of an industry identifier and an occupation identifier; and (d) providing a computerized terminal interface for allowing at least one user to interact with at least one other user; wherein the computerized terminal interface displays personalized content to each participant user, and the displayed personalized content is selected on the basis of at least one of (i) a match between the participant user and a mentor user, and (ii) a match between the participant user and at least one subject matter expert user; and wherein each mentor user and subject matter expert user differs from one another.
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1. A method for providing an interactive knowledge based community solution, the community comprising multiple users, each of the multiple users belonging to a user type, the user types comprising participant, mentor, and subject matter expert, the method comprising the steps of: (a) associating a user profile with at least one of the multiple users; (b) matching a participant user with a mentor user based on user profiles of the participant user and the mentor user; (c) matching a participant user with at least one subject matter expert user based on the user profile of the participant user including at least one of an industry identifier and an occupation identifier, and based on the user profile of the at least one subject matter expert user including at least one of an industry identifier and an occupation identifier; and (d) providing a computerized terminal interface for allowing at least one user to interact with at least one other user; wherein the computerized terminal interface displays personalized content to each participant user, and the displayed personalized content is selected on the basis of at least one of (i) a match between the participant user and a mentor user, and (ii) a match between the participant user and at least one subject matter expert user; and wherein each mentor user and subject matter expert user differs from one another. 3. The method of claim 1 , further comprising the step of recording at least one of any of a status identifier, industry identifier, occupation identifier, and area of interest for each participant user.
| 0.610428 |
1. A method comprising: receiving from a user an utterance in a first language including a first term; by a speech translation system, translating the utterance from the first language into a second language; receiving an indication from the user to initiate a user customization process for customizing one or more modules of the speech translation system to the user; and under the user customization process: receiving an indication from the user to add the first term to one or more modules of the speech translation system; in response to the received indication from the user, determining word class information for the first term; adding, by the speech translation system, the first term, the determined word class information, and at least a portion of the translation of the utterance in the second language to a first machine translation module associated with the first language of the speech translation system; and adding the first term and the at least a portion of the translation of the utterance in the second language to a shared database for a community such that the customization performed by the user is available for use by other users of the community in translations by the speech translation system.
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1. A method comprising: receiving from a user an utterance in a first language including a first term; by a speech translation system, translating the utterance from the first language into a second language; receiving an indication from the user to initiate a user customization process for customizing one or more modules of the speech translation system to the user; and under the user customization process: receiving an indication from the user to add the first term to one or more modules of the speech translation system; in response to the received indication from the user, determining word class information for the first term; adding, by the speech translation system, the first term, the determined word class information, and at least a portion of the translation of the utterance in the second language to a first machine translation module associated with the first language of the speech translation system; and adding the first term and the at least a portion of the translation of the utterance in the second language to a shared database for a community such that the customization performed by the user is available for use by other users of the community in translations by the speech translation system. 2. The method of claim 1 , further comprising: retrieving a second term from the shared database; and adding the second term from the shared database to the first machine translation module.
| 0.623292 |
31. A method of search, the method, comprising: detecting a set of location identifiers of webpages that match a specified pattern that is not a unified resource identifier (URI), the specified pattern being stored in a computer-readable storage medium; wherein, the specified pattern corresponds to a semantic type; identifying a set of search results as having content related to the semantic type; identifying a set of type-determined webpages having the matching location identifiers; data mining the content of each of the set of type-determined web pages to further determine relevancy to the semantic type; identifying a refined set of type-determined web pages from the set of type-determined web pages based on the relevancy to the semantic type determined via the data mining; generating a refined set of search results from the refined set of type-determined web pages; and ranking each of the set of type-determined web pages based on the relevancy determined from the data mining; wherein, the semantic type is associated with multiple attributes that are user-defined; and wherein, the set of search results includes objects associated with the set of location identifiers having the specified pattern.
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31. A method of search, the method, comprising: detecting a set of location identifiers of webpages that match a specified pattern that is not a unified resource identifier (URI), the specified pattern being stored in a computer-readable storage medium; wherein, the specified pattern corresponds to a semantic type; identifying a set of search results as having content related to the semantic type; identifying a set of type-determined webpages having the matching location identifiers; data mining the content of each of the set of type-determined web pages to further determine relevancy to the semantic type; identifying a refined set of type-determined web pages from the set of type-determined web pages based on the relevancy to the semantic type determined via the data mining; generating a refined set of search results from the refined set of type-determined web pages; and ranking each of the set of type-determined web pages based on the relevancy determined from the data mining; wherein, the semantic type is associated with multiple attributes that are user-defined; and wherein, the set of search results includes objects associated with the set of location identifiers having the specified pattern. 34. The method of claim 31 , further comprising, data mining the content of each of the set of search results to further determine relevancy to the semantic type; and identifying a refined set of search results from the set of type-determined web pages based on the relevancy to the semantic type determine via the data mining.
| 0.699626 |
1. A method of managing digital data, the method comprising: searching, by a processor, a plurality of data sets comprising digital data; recording, by the processor, a hit into an index for each occurrence of a unique object in one of the plurality of data sets, wherein each of the plurality of data sets comprises a numbered sequence of objects, wherein said objects are represented by unique machine-readable object values, and wherein said hit comprises an ordinal number of an occurrence of said unique object and at least one of: a value of a previous object that is positioned one unit before said unique object and a value of a next object that is positioned one unit after said unique object; recording hit data into the index, wherein the hit data comprises at least one of: values of additional previous objects with respect to the unique object and values of additional next objects with respect to the unique object, for N objects where N is at least one; restoring at least one of past relationship and future relationship with respect to the unique object based on the recorded hit data; searching for at least two occurrences of the unique object in indexed data set, wherein the searching comprises gathering a value of the unique object, retrieving hits with the occurrence of the unique object in the indexed data set and other data sets from among the data sets; and displaying the retrieved hits as search results, obtained based on the searching or recording the retrieved relationships into the memory available for a processor or an algorithm capable of analyzing the co-occurrence of the unique object with each of the N next or previous objects in the indexed data set or transferring the retrieved relationship to a processor, wherein the search results or the memory records further comprise the restored relationships.
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1. A method of managing digital data, the method comprising: searching, by a processor, a plurality of data sets comprising digital data; recording, by the processor, a hit into an index for each occurrence of a unique object in one of the plurality of data sets, wherein each of the plurality of data sets comprises a numbered sequence of objects, wherein said objects are represented by unique machine-readable object values, and wherein said hit comprises an ordinal number of an occurrence of said unique object and at least one of: a value of a previous object that is positioned one unit before said unique object and a value of a next object that is positioned one unit after said unique object; recording hit data into the index, wherein the hit data comprises at least one of: values of additional previous objects with respect to the unique object and values of additional next objects with respect to the unique object, for N objects where N is at least one; restoring at least one of past relationship and future relationship with respect to the unique object based on the recorded hit data; searching for at least two occurrences of the unique object in indexed data set, wherein the searching comprises gathering a value of the unique object, retrieving hits with the occurrence of the unique object in the indexed data set and other data sets from among the data sets; and displaying the retrieved hits as search results, obtained based on the searching or recording the retrieved relationships into the memory available for a processor or an algorithm capable of analyzing the co-occurrence of the unique object with each of the N next or previous objects in the indexed data set or transferring the retrieved relationship to a processor, wherein the search results or the memory records further comprise the restored relationships. 31. The method of claim 1 , wherein the data sets are numbered sequence of addresses of an itinerary or a map, wherein the sequences of addresses are indexed, and the index is stored on at least one of an information media, a portable memory device, and in the memory of an apparatus.
| 0.670107 |
9. A method of quantizing a vector representative of a portion of a speech or audio signal in an encoder, comprising: (a) determining legal candidate codevectors among a set of candidate codevectors based upon one or more illegal space definitions, the candidate codevectors including line spectral frequencies (LSFs), wherein the one or more illegal space definitions define invalid spacing characteristics of LSFs; (b) deriving a separate error term corresponding to each legal candidate codevector, each error term being a function of the vector and the corresponding legal candidate codevector; (c) determining a best legal candidate codevector among the legal candidate codevectors based on the error terms, whereby the best legal candidate codevector corresponds to a quantization of the vector; and (d) transmitting to a decoder a signal representative of the portion of the speech or audio signal based on the best legal candidate codevector.
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9. A method of quantizing a vector representative of a portion of a speech or audio signal in an encoder, comprising: (a) determining legal candidate codevectors among a set of candidate codevectors based upon one or more illegal space definitions, the candidate codevectors including line spectral frequencies (LSFs), wherein the one or more illegal space definitions define invalid spacing characteristics of LSFs; (b) deriving a separate error term corresponding to each legal candidate codevector, each error term being a function of the vector and the corresponding legal candidate codevector; (c) determining a best legal candidate codevector among the legal candidate codevectors based on the error terms, whereby the best legal candidate codevector corresponds to a quantization of the vector; and (d) transmitting to a decoder a signal representative of the portion of the speech or audio signal based on the best legal candidate codevector. 19. The method of claim 9 , wherein: the vector is an input line spectral frequency (LSF) vector including line spectral frequencies (LSFs); and each candidate codevector is an LSF vector.
| 0.731896 |
18. The system of claim 15 , further comprising predicting a character that is part of the grapheme.
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18. The system of claim 15 , further comprising predicting a character that is part of the grapheme. 19. The system of claim 18 , further comprising predicting any remaining characters in the grapheme.
| 0.97018 |
1. A computer-implemented method comprising: receiving, by at least one processor, an input representative of a temporal constraint for a task of a graph-process model, the temporal constraint defining at least one of a commencement delay, a completion delay, a commencement deadline, and a completion deadline; associating, by the at least one processor, the task with the temporal constraint created based on the received input, the temporal constraint defined to have a placement on the task of the graph-process model based on a type of temporal constraint, wherein the placement of the temporal constraint is based on a graphical element, the graphical element comprising a left border, a right border, a top border and a bottom border, wherein the left border is configured to accept placement of the temporal constraint when the temporal constraint corresponds to the commencement delay, wherein the right border is configured to accept placement of the temporal constraint when the temporal constraint corresponds to the completion delay, wherein the top border is configured to accept placement of the temporal constraint when the temporal constraint corresponds to the commencement deadline, and wherein the bottom border is configured to accept placement of the temporal constraint when the temporal constraint corresponds to the completion deadline; and providing, by the at least one processor, the task and the temporal constraint to configure the graph-process model.
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1. A computer-implemented method comprising: receiving, by at least one processor, an input representative of a temporal constraint for a task of a graph-process model, the temporal constraint defining at least one of a commencement delay, a completion delay, a commencement deadline, and a completion deadline; associating, by the at least one processor, the task with the temporal constraint created based on the received input, the temporal constraint defined to have a placement on the task of the graph-process model based on a type of temporal constraint, wherein the placement of the temporal constraint is based on a graphical element, the graphical element comprising a left border, a right border, a top border and a bottom border, wherein the left border is configured to accept placement of the temporal constraint when the temporal constraint corresponds to the commencement delay, wherein the right border is configured to accept placement of the temporal constraint when the temporal constraint corresponds to the completion delay, wherein the top border is configured to accept placement of the temporal constraint when the temporal constraint corresponds to the commencement deadline, and wherein the bottom border is configured to accept placement of the temporal constraint when the temporal constraint corresponds to the completion deadline; and providing, by the at least one processor, the task and the temporal constraint to configure the graph-process model. 5. The computer-implemented method of claim 1 , wherein associating further comprises: linking a second task to the temporal constraint, the second task being an escalated task.
| 0.532092 |
12. The method according to claim 1 , wherein at least one of the inner portion and the outer portion comprises an animation pattern.
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12. The method according to claim 1 , wherein at least one of the inner portion and the outer portion comprises an animation pattern. 14. The method according to claim 12 , wherein the pattern is varied inversely proportionally to the function of the determined measure.
| 0.914141 |
1. A system for automatically dubbing a video in a first language into a second language, comprising: an audio/video pre-processor constructed and arranged to provide separate original audio and video files of the same media; a text analysis unit constructed and arranged to receive a first text file of the video's subtitles in the first language and a second text file of the video's subtitles in the second language, said text analysis unit further constructed and arranged to re-divide said first and second text files into text sentences; a text-to-speech unit constructed and arranged to receive said text sentences in said first and second languages from said text analysis unit and produce therefrom first and second standard TTS spoken sentences; a prosody unit constructed and arranged to receive said first and second spoken sentences, said separated audio file and timing parameters and produce therefrom dubbing recommendations; and a dubbing unit constructed and arranged to receive said second spoken sentence and said recommendations and produce therefrom an automatically dubbed sentence in said second language.
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1. A system for automatically dubbing a video in a first language into a second language, comprising: an audio/video pre-processor constructed and arranged to provide separate original audio and video files of the same media; a text analysis unit constructed and arranged to receive a first text file of the video's subtitles in the first language and a second text file of the video's subtitles in the second language, said text analysis unit further constructed and arranged to re-divide said first and second text files into text sentences; a text-to-speech unit constructed and arranged to receive said text sentences in said first and second languages from said text analysis unit and produce therefrom first and second standard TTS spoken sentences; a prosody unit constructed and arranged to receive said first and second spoken sentences, said separated audio file and timing parameters and produce therefrom dubbing recommendations; and a dubbing unit constructed and arranged to receive said second spoken sentence and said recommendations and produce therefrom an automatically dubbed sentence in said second language. 3. The system of claim 1 , wherein said producing dubbing recommendations comprises comparing the sentence in said first TTS voice with said sentence in the original audio.
| 0.522071 |
1. A method comprising: selecting a plurality of language models; for each period of a plurality of time periods: identifying a first utterance and a second utterance received during each time period, wherein the first utterance was recognized using a first language model of the plurality of language models and the second utterance was recognized using a second language model of the plurality of language models; identifying distinctions between the first utterance and the second utterance for each of the plurality of time periods; determining when a significant word usage change has occurred within the first language model and the second language model by comparing the distinctions to previously recorded distinctions; and when the significant word usage change is detected: identifying a word corresponding to the significant word usage change; generating, from the utterances, a first cluster of utterances comprising the word; generating, from the utterances, a second cluster of utterances not comprising the word; and updating the plurality of language models using the first cluster of utterances and the second cluster of utterances.
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1. A method comprising: selecting a plurality of language models; for each period of a plurality of time periods: identifying a first utterance and a second utterance received during each time period, wherein the first utterance was recognized using a first language model of the plurality of language models and the second utterance was recognized using a second language model of the plurality of language models; identifying distinctions between the first utterance and the second utterance for each of the plurality of time periods; determining when a significant word usage change has occurred within the first language model and the second language model by comparing the distinctions to previously recorded distinctions; and when the significant word usage change is detected: identifying a word corresponding to the significant word usage change; generating, from the utterances, a first cluster of utterances comprising the word; generating, from the utterances, a second cluster of utterances not comprising the word; and updating the plurality of language models using the first cluster of utterances and the second cluster of utterances. 2. The method of claim 1 , wherein determining when the significant word usage change has occurred further comprises comparing ones of the utterances from a particular group of speakers associated with one of the plurality of time periods with ones of the utterances from the particular group of speakers from another time period of the plurality of time periods.
| 0.701735 |
1. A method for importing a design in hardware description language (HDL) into a system designer, comprising: generating a function operable to specify a number of input and output ports that are in the design in HDL; setting a sample time for sampling signals of a simulation model, wherein the sample time is associated with a clock signal in the design in HDL; generating a simulation model template based on the function and the sample time rendering a plurality of selectable simulation model types; receiving a user selected simulation model type; and generating the simulation model from the simulation model template, wherein the simulation model is operable to be rendered in response to the user selected simulation model type, wherein at least one of the setting, rendering, receiving and generating procedures is performed by a computer.
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1. A method for importing a design in hardware description language (HDL) into a system designer, comprising: generating a function operable to specify a number of input and output ports that are in the design in HDL; setting a sample time for sampling signals of a simulation model, wherein the sample time is associated with a clock signal in the design in HDL; generating a simulation model template based on the function and the sample time rendering a plurality of selectable simulation model types; receiving a user selected simulation model type; and generating the simulation model from the simulation model template, wherein the simulation model is operable to be rendered in response to the user selected simulation model type, wherein at least one of the setting, rendering, receiving and generating procedures is performed by a computer. 3. The method of claim 1 , wherein the clock signal is user identifiable from the design in HDL.
| 0.784444 |
1. A computer-implemented method comprising: receiving a transcription of a first portion of a speech session, wherein the transcription of the first portion of the speech session is generated using a speaker adaptation profile; receiving a stability measure for a segment of the transcription; determining that the stability measure for the segment satisfies a threshold; in response to determining that the stability measure for the segment satisfies the threshold, triggering a real-time update of the speaker adaptation profile using the segment, or using a portion of speech data that corresponds to the segment; receiving a transcription of a second portion of the speech session, wherein the transcription of the second portion of the speech session is generated using the updated speaker adaptation profile; and outputting a set of transcriptions comprising the transcription of the first portion of the speech session and the transcription of the second portion of the speech session.
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1. A computer-implemented method comprising: receiving a transcription of a first portion of a speech session, wherein the transcription of the first portion of the speech session is generated using a speaker adaptation profile; receiving a stability measure for a segment of the transcription; determining that the stability measure for the segment satisfies a threshold; in response to determining that the stability measure for the segment satisfies the threshold, triggering a real-time update of the speaker adaptation profile using the segment, or using a portion of speech data that corresponds to the segment; receiving a transcription of a second portion of the speech session, wherein the transcription of the second portion of the speech session is generated using the updated speaker adaptation profile; and outputting a set of transcriptions comprising the transcription of the first portion of the speech session and the transcription of the second portion of the speech session. 9. The method of claim 1 , further comprising updating the speaker adaptation profile.
| 0.598222 |
15. A system, comprising: a transmitting display device configured to display a first set of content to a user; and a receiving computing device configured for providing related content from text associated with the first set of content, the receiving computing device including: a transceiver component configured to receive, via a Local Area Network (LAN), a stream of text from the transmitting display device, wherein the transmitting display device is remote to the receiving computing device, wherein the stream of text is transmitted to the receiving computing device in response to text data being received by the transmitting display device, wherein the stream of text corresponds to the first set of content, wherein the first set of content includes video, and wherein the stream of text is provided to the receiving computing device independent of the video, and wherein the receiving computing device does not receive the video; a natural language processing component configured to determine terms related to the first set of content from the stream of text using natural language processing, in response to receiving the stream of text from the transmitting display device, the natural language processing performed using scripting commands; a content retrieval component configured to determine a second set of content related to the first set of content, using the terms related to the first set of content, wherein the second set of content is automatically accessed and delivered from the media content source based on pre- established user preferences; and a user interface component configured to provide the second set of content to the user within a user interface, wherein the second set of content is automatically displayed by the receiving computing device concurrently in time with the active display of the first set of content by the transmitting display device, wherein the user interface provides a dynamically generated output to the user using markup language.
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15. A system, comprising: a transmitting display device configured to display a first set of content to a user; and a receiving computing device configured for providing related content from text associated with the first set of content, the receiving computing device including: a transceiver component configured to receive, via a Local Area Network (LAN), a stream of text from the transmitting display device, wherein the transmitting display device is remote to the receiving computing device, wherein the stream of text is transmitted to the receiving computing device in response to text data being received by the transmitting display device, wherein the stream of text corresponds to the first set of content, wherein the first set of content includes video, and wherein the stream of text is provided to the receiving computing device independent of the video, and wherein the receiving computing device does not receive the video; a natural language processing component configured to determine terms related to the first set of content from the stream of text using natural language processing, in response to receiving the stream of text from the transmitting display device, the natural language processing performed using scripting commands; a content retrieval component configured to determine a second set of content related to the first set of content, using the terms related to the first set of content, wherein the second set of content is automatically accessed and delivered from the media content source based on pre- established user preferences; and a user interface component configured to provide the second set of content to the user within a user interface, wherein the second set of content is automatically displayed by the receiving computing device concurrently in time with the active display of the first set of content by the transmitting display device, wherein the user interface provides a dynamically generated output to the user using markup language. 16. The system of claim 15 , further comprising: a first content source providing the first set of content and the text associated with the first set of content; and a second content source providing the second set of content.
| 0.517282 |
6. A non-transitory machine-readable storage medium comprising instructions which, when executed, cause the machine to: access a series of play events comprising real-time media item listening behavior, wherein the play events are associated with a user and a unique sequential identifier, wherein play events comprise instances of media items associated with the user being purchased, played, replayed, tagged, and skipped; compare the play event identifiers to previously retrieved play event identifiers to determine whether the play events are new; store one or more new play events in an event stack wherein the event stack has a predetermine stack limit; arrange real-time media item listening behavior corresponding to the new play events in one or more data structures, wherein the data structures are configured to correlate real-time media item listening behavior and to maintain a temporal context for real-time media item listening behavior; increment counters in the data structure associated with the arranged real-time media item listening behavior upon addition of the real-time media item listening behavior to the data structure, wherein the data structure comprises a plurality of hash tables for identifying and tracking media item attributes including: artist, users, tracks played, user last track played, correlations between different artists with respect to users' listening activity and temporal context of the users' listening activity; display a visualization of the arranged real-time media item listening behavior responsive to the arrangement of the real-time media item listening behavior in the data structure, wherein displaying comprises: adding a plurality of nodes representing artists and a plurality of edges representing consecutive play events of the same artist, each edge connecting a first node of the plurality of nodes to a second node of the plurality of nodes correlated to the first node, each of the plurality of nodes assigned a velocity, a position, a net force, and an identifier associated with one or more media items, and each of the plurality of edges assigned a net spring force; applying a damping factor; and repeatedly updating the position of each of the plurality of nodes based at least on the net force and the velocity assigned to each of the plurality of nodes, the net spring force assigned to each of the plurality of edges, and the damping factor until the position for each of the plurality of nodes reaches an equilibrium; identify and remove an old event from the event stack responsive to the event stack exceeding the predetermined stack limit; decrement counters in the data structure associated with the arranged real-time media item listening behavior upon removal of the old event from the event stack wherein the old event corresponds to the arranged real-time media item listening behavior that is scheduled to be decremented; and update the visualization display responsive to each change in the artists, users, tracks played, user last tracks played, correlations between different artists with respect to users' listening activity and temporal context of the users' listening activity.
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6. A non-transitory machine-readable storage medium comprising instructions which, when executed, cause the machine to: access a series of play events comprising real-time media item listening behavior, wherein the play events are associated with a user and a unique sequential identifier, wherein play events comprise instances of media items associated with the user being purchased, played, replayed, tagged, and skipped; compare the play event identifiers to previously retrieved play event identifiers to determine whether the play events are new; store one or more new play events in an event stack wherein the event stack has a predetermine stack limit; arrange real-time media item listening behavior corresponding to the new play events in one or more data structures, wherein the data structures are configured to correlate real-time media item listening behavior and to maintain a temporal context for real-time media item listening behavior; increment counters in the data structure associated with the arranged real-time media item listening behavior upon addition of the real-time media item listening behavior to the data structure, wherein the data structure comprises a plurality of hash tables for identifying and tracking media item attributes including: artist, users, tracks played, user last track played, correlations between different artists with respect to users' listening activity and temporal context of the users' listening activity; display a visualization of the arranged real-time media item listening behavior responsive to the arrangement of the real-time media item listening behavior in the data structure, wherein displaying comprises: adding a plurality of nodes representing artists and a plurality of edges representing consecutive play events of the same artist, each edge connecting a first node of the plurality of nodes to a second node of the plurality of nodes correlated to the first node, each of the plurality of nodes assigned a velocity, a position, a net force, and an identifier associated with one or more media items, and each of the plurality of edges assigned a net spring force; applying a damping factor; and repeatedly updating the position of each of the plurality of nodes based at least on the net force and the velocity assigned to each of the plurality of nodes, the net spring force assigned to each of the plurality of edges, and the damping factor until the position for each of the plurality of nodes reaches an equilibrium; identify and remove an old event from the event stack responsive to the event stack exceeding the predetermined stack limit; decrement counters in the data structure associated with the arranged real-time media item listening behavior upon removal of the old event from the event stack wherein the old event corresponds to the arranged real-time media item listening behavior that is scheduled to be decremented; and update the visualization display responsive to each change in the artists, users, tracks played, user last tracks played, correlations between different artists with respect to users' listening activity and temporal context of the users' listening activity. 9. The tangible machine-readable storage medium of claim 6 , wherein the data structure correlates arranged real-time media item listening behavior and stores an indication of the correlation as a separate entry in the data structure and wherein the correlation entry is associated with a counters for incrementing and decrementing.
| 0.5 |
1. A method comprising receiving a not-yet-submitted user search query from a client node; wherein the not-yet-submitted user search query is a partial, not completely formed search query; wherein the not-yet-submitted user search query is received after the steps of: prior to the user finalizing and submitting the search query, determining that the not-yet-submitted user search query meets search initiation criteria; in response to receiving the not-yet submitted user search query, generating a set of suggested query candidates; generating a biased parameter, wherein the parameter is associated with a suggested query candidate of the set of suggested query candidates, and the parameter is biased based on an attribute associated with the suggested query candidate; selecting one or more of suggested query candidates of the set of suggested query candidates to be suggested queries for the search query based on the biased parameter associated with the suggested query candidate; determining relevance of at least one of the suggested queries of the one or more suggested query candidates; in response to determining that the relevance of said at least one of the suggested queries meets or exceeds a relevance threshold, providing said at least one of the suggested queries to the client node; receiving, from the client node, a search request including one of the suggested queries as a completely formed query; and in response to receiving the search request including one of the suggested queries as a completely formed query, sending search results back to the client node; wherein search results include a list of links to files or pages.
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1. A method comprising receiving a not-yet-submitted user search query from a client node; wherein the not-yet-submitted user search query is a partial, not completely formed search query; wherein the not-yet-submitted user search query is received after the steps of: prior to the user finalizing and submitting the search query, determining that the not-yet-submitted user search query meets search initiation criteria; in response to receiving the not-yet submitted user search query, generating a set of suggested query candidates; generating a biased parameter, wherein the parameter is associated with a suggested query candidate of the set of suggested query candidates, and the parameter is biased based on an attribute associated with the suggested query candidate; selecting one or more of suggested query candidates of the set of suggested query candidates to be suggested queries for the search query based on the biased parameter associated with the suggested query candidate; determining relevance of at least one of the suggested queries of the one or more suggested query candidates; in response to determining that the relevance of said at least one of the suggested queries meets or exceeds a relevance threshold, providing said at least one of the suggested queries to the client node; receiving, from the client node, a search request including one of the suggested queries as a completely formed query; and in response to receiving the search request including one of the suggested queries as a completely formed query, sending search results back to the client node; wherein search results include a list of links to files or pages. 13. The method of claim 1 , wherein the search initiation criteria is based on how long it has been since the user last entered a character in the not-yet submitted user search query.
| 0.611675 |
3. The method of claim 2 , wherein the variable fields are further parsed to identify a numeric variable field and an alphanumeric variable field.
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3. The method of claim 2 , wherein the variable fields are further parsed to identify a numeric variable field and an alphanumeric variable field. 4. The method of claim 3 , wherein the optimized encoding algorithm for a field is algorithms are identified by employing computing an entropy calculations for the numeric variable field.
| 0.944019 |
15. A computer readable storage medium containing computer readable instructions that when executed by a computer performs the following steps: (a) requesting a user speak a vocabulary word; (b) receiving a first digitized utterance; (c) extracting a plurality of features from the first digitized utterance; (d) determining a signal to noise ratio; (e) when the signal to noise ratio is less than a predetermined signal to noise ratio, returning to step (a); (f) requesting the user speak the vocabulary word; (g) receiving a second digitized utterance of the vocabulary word; (h) extracting the plurality of features from the second digitized utterance; (i) determining a first similarity between the plurality of features from the first digitized utterance and the plurality of features from the second digitized utterance; (j) when the first similarity is less than a predetermined similarity, requesting the user to speak a third utterance of the vocabulary word; (k) extracting the plurality of features from a third digitized utterance; (l) determining a second similarity between the plurality of features from the first digitized utterance and the plurality of features from the third digitized utterance; and (m) when the second similarity is greater than or equal to the predetermined similarity, forming a reference for the vocabulary word.
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15. A computer readable storage medium containing computer readable instructions that when executed by a computer performs the following steps: (a) requesting a user speak a vocabulary word; (b) receiving a first digitized utterance; (c) extracting a plurality of features from the first digitized utterance; (d) determining a signal to noise ratio; (e) when the signal to noise ratio is less than a predetermined signal to noise ratio, returning to step (a); (f) requesting the user speak the vocabulary word; (g) receiving a second digitized utterance of the vocabulary word; (h) extracting the plurality of features from the second digitized utterance; (i) determining a first similarity between the plurality of features from the first digitized utterance and the plurality of features from the second digitized utterance; (j) when the first similarity is less than a predetermined similarity, requesting the user to speak a third utterance of the vocabulary word; (k) extracting the plurality of features from a third digitized utterance; (l) determining a second similarity between the plurality of features from the first digitized utterance and the plurality of features from the third digitized utterance; and (m) when the second similarity is greater than or equal to the predetermined similarity, forming a reference for the vocabulary word. 16. The computer readable storage medium of claim 15, further executing the steps of: (n) when the second similarity is less than the predetermined similarity, determining a third similarity between the plurality of features from the second digitized utterance and the plurality of features from the third digitized utterance; (o) when the third similarity is greater than or equal to the predetermined similarity, forming the reference for the vocabulary word.
| 0.5 |
7. A computer program product stored on a computer readable non-transitory storage medium for implementing a frequency domain based magnetic ink character recognition (MICR) system, comprising: program code configured for generating a set of Fourier components from temporal MICR data for an inputted arbitrary character, wherein the set of Fourier components comprises six components including a fundamental and next five harmonics; program code configured for normalizing the set of Fourier components to generate a normalized set of Fourier components; and program code configured for comparing the normalized set of Fourier components with each of a set of reference waveforms to determine an identity of the inputted arbitrary character, wherein the set of reference waveforms comprises a corresponding six components including a corresponding fundamental and corresponding next five harmonics, and wherein the comparing, comprises: calculating a set of difference value between each component in the normalized set of Fourier components and an associated component in a reference waveform; weighting each difference value such that a difference value calculated for a relatively higher Fourier component receives a relatively lower weight; summing each of the weighted difference values; comparing concavities between the normalized set of Fourier components and each set of reference waveforms; and assigning values based upon a degree of concavity matching.
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7. A computer program product stored on a computer readable non-transitory storage medium for implementing a frequency domain based magnetic ink character recognition (MICR) system, comprising: program code configured for generating a set of Fourier components from temporal MICR data for an inputted arbitrary character, wherein the set of Fourier components comprises six components including a fundamental and next five harmonics; program code configured for normalizing the set of Fourier components to generate a normalized set of Fourier components; and program code configured for comparing the normalized set of Fourier components with each of a set of reference waveforms to determine an identity of the inputted arbitrary character, wherein the set of reference waveforms comprises a corresponding six components including a corresponding fundamental and corresponding next five harmonics, and wherein the comparing, comprises: calculating a set of difference value between each component in the normalized set of Fourier components and an associated component in a reference waveform; weighting each difference value such that a difference value calculated for a relatively higher Fourier component receives a relatively lower weight; summing each of the weighted difference values; comparing concavities between the normalized set of Fourier components and each set of reference waveforms; and assigning values based upon a degree of concavity matching. 8. The computer program product of claim 7 , further comprising program code configured for segmenting inputted MICR data into discrete sets of temporal data for individual characters.
| 0.527864 |
5. The method of claim 1 , wherein accessing a set of training data from a plurality of listings from at least one of supply data or demand data comprises: accessing listing data from a plurality of listings from at least one of supply data or demand data, the supply data generated from seller activity of a plurality of users in a networked system, the demand data generated from buyer activity of the plurality of users in the networked system, each listing including a category from the category structure; and automatically generating a set of training data for the category structure by applying a classifier to the listing data.
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5. The method of claim 1 , wherein accessing a set of training data from a plurality of listings from at least one of supply data or demand data comprises: accessing listing data from a plurality of listings from at least one of supply data or demand data, the supply data generated from seller activity of a plurality of users in a networked system, the demand data generated from buyer activity of the plurality of users in the networked system, each listing including a category from the category structure; and automatically generating a set of training data for the category structure by applying a classifier to the listing data. 7. The method of claim 5 , wherein automatically generating a set of training data comprises: automatically generating a set of training data by applying a classifier to at least one of a title and title relevant information within a description of the plurality of listings.
| 0.828344 |
14. The method of claim 13 , wherein the word element is a phoneme; and wherein said presenting the stimulus word comprises graphically presenting the stimulus word from the stimulus word set to the student.
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14. The method of claim 13 , wherein the word element is a phoneme; and wherein said presenting the stimulus word comprises graphically presenting the stimulus word from the stimulus word set to the student. 15. The method of claim 14 , wherein said displaying a plurality of bins comprises: graphically displaying a phonetic symbol for the respective phoneme of each bin; and aurally presenting a description of the respective phoneme of each bin.
| 0.934038 |
1. A system for search with autosuggest, comprising: a processor configured to: determine a plurality of potential query suggestions for a partially entered query string; automatically suggest a plurality of queries based on a query count for each of the queries, comprising to: determine a weight for each of the plurality of potential search query suggestions, comprising to: determine a first weight of a first potential search query suggestion based on a first query count; determine a first position weight based on a position of a first matching word in the first potential search query suggestion; adjust the first weight of the first potential search query suggestion based on the first position weight to obtain a first adjusted weight for the first potential search query suggestion, comprising to: determine whether a portion of the query string matches a field in a document associated with the first potential search query suggestion; and in the event that the portion of the query string matches the field in the document: adjust the first adjusted weight by a first value in the event that the field corresponds to a first type; and adjust the first adjusted weight by a second value in the event that the field corresponds to a second type, the first value being different from the second value; and a memory coupled to the processor and configured to provide the processor with instructions.
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1. A system for search with autosuggest, comprising: a processor configured to: determine a plurality of potential query suggestions for a partially entered query string; automatically suggest a plurality of queries based on a query count for each of the queries, comprising to: determine a weight for each of the plurality of potential search query suggestions, comprising to: determine a first weight of a first potential search query suggestion based on a first query count; determine a first position weight based on a position of a first matching word in the first potential search query suggestion; adjust the first weight of the first potential search query suggestion based on the first position weight to obtain a first adjusted weight for the first potential search query suggestion, comprising to: determine whether a portion of the query string matches a field in a document associated with the first potential search query suggestion; and in the event that the portion of the query string matches the field in the document: adjust the first adjusted weight by a first value in the event that the field corresponds to a first type; and adjust the first adjusted weight by a second value in the event that the field corresponds to a second type, the first value being different from the second value; and a memory coupled to the processor and configured to provide the processor with instructions. 6. The system recited in claim 1 , wherein the processor is further configured to: determine that the partially entered query string is associated with product or category of a merchant web site.
| 0.608527 |
10. The system of claim 6 , wherein the physical computer system is further programmed to: identify one or more data stores to answer the search query; retrieve the search results from the one or more data stores; retrieve performance data from the one or more data stores; evaluate the performance data retrieved from the one or more data stores; and categorize one or more of the data stores as specialized data stores, based at least in part on the performance evaluation.
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10. The system of claim 6 , wherein the physical computer system is further programmed to: identify one or more data stores to answer the search query; retrieve the search results from the one or more data stores; retrieve performance data from the one or more data stores; evaluate the performance data retrieved from the one or more data stores; and categorize one or more of the data stores as specialized data stores, based at least in part on the performance evaluation. 11. The system of claim 10 , wherein the one or more data stores answer queries of one or more query classes.
| 0.94013 |
11. The computer-implemented method of claim 10 , wherein identifying the keyword comprises at least one of: identifying a spec resource keyword that establishes the identity of the resource; identifying a resource keyword that specifies attributes for processing the resource according to one of a default state and an alternative state.
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11. The computer-implemented method of claim 10 , wherein identifying the keyword comprises at least one of: identifying a spec resource keyword that establishes the identity of the resource; identifying a resource keyword that specifies attributes for processing the resource according to one of a default state and an alternative state. 12. The computer-implemented method of claim 11 , wherein: identifying the resource keyword comprises identifying the spec resource keyword; identifying the flag as corresponding to the spec resource keyword functions as a sufficient trigger to classify the application package as repackaged.
| 0.797276 |
20. The method of claim 19 , wherein the part of a particular completion candidate in the list of completion candidates that matches the partial text entry is represented for display in a manner different from the remaining part of the particular completion candidate.
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20. The method of claim 19 , wherein the part of a particular completion candidate in the list of completion candidates that matches the partial text entry is represented for display in a manner different from the remaining part of the particular completion candidate. 21. A computer-readable medium having stored instructions for directing a processor unit to execute the method of claim 20 .
| 0.933572 |
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