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5. The method of claim 1 , further comprising: obtaining a traffic rate of the comparable text item; identifying a modified traffic text item comprising a modified traffic rate that exceeds the traffic rate; generating a traffic improved website comprising the modified traffic text item, wherein the modified traffic text item is text; receiving, from the user, a second approval of the traffic improved website; and generating, based on the second approval, the website comprising the modified traffic text item based on the traffic improved website.
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5. The method of claim 1 , further comprising: obtaining a traffic rate of the comparable text item; identifying a modified traffic text item comprising a modified traffic rate that exceeds the traffic rate; generating a traffic improved website comprising the modified traffic text item, wherein the modified traffic text item is text; receiving, from the user, a second approval of the traffic improved website; and generating, based on the second approval, the website comprising the modified traffic text item based on the traffic improved website. 8. The method of claim 5 , further comprising: modifying the comparable text item by adding text to the comparable text item to generate the modified traffic text item.
| 0.957559 |
12. A system, comprising: a data processing apparatus; a memory storage apparatus in data communication with the data processing apparatus and storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: for each of one or more textual advertisements of a sponsor of the textual advertisements, each of the advertisements including a link to a corresponding landing page that causes a user device to request the landing page in response to the advertisement being selected when the advertisement is displayed on the user device: identifying landing page images in the landing page to which the textual advertisement links; for each landing page image identified in the landing page, determining a relevance measure that measures the relevance of the landing page image to the content of the landing page; selecting, by the data processing apparatus, one or more of the landing page images for concurrent display with the textual advertisement based on the relevance measures of the landing page images; and storing, in a data storage system, data associating the selected landing page images with the textual advertisements.
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12. A system, comprising: a data processing apparatus; a memory storage apparatus in data communication with the data processing apparatus and storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: for each of one or more textual advertisements of a sponsor of the textual advertisements, each of the advertisements including a link to a corresponding landing page that causes a user device to request the landing page in response to the advertisement being selected when the advertisement is displayed on the user device: identifying landing page images in the landing page to which the textual advertisement links; for each landing page image identified in the landing page, determining a relevance measure that measures the relevance of the landing page image to the content of the landing page; selecting, by the data processing apparatus, one or more of the landing page images for concurrent display with the textual advertisement based on the relevance measures of the landing page images; and storing, in a data storage system, data associating the selected landing page images with the textual advertisements. 19. The system of claim 12 , further comprising for each of a plurality of textual advertisements that an advertiser has not specified an image to be displayed with the textual advertisement: determining an advertising entity for the textual advertisement; identifying one or more entity images based on the advertising entity; storing, in the data storage system, data associating the entity images with the textual advertisement; determining a vertical for the textual advertisement; selecting one or more vertical images based on the vertical of the textual advertisement; and storing, in the data storage system, data associating the vertical images with the textual advertisement.
| 0.5 |
6. A program for controlling messaging outputs in a messaging session, residing on a computer usable medium having computer readable program code means, said program comprising: means for receiving a plurality of message entries each associated with a particular topic from among a plurality of topics within a particular channel of a messaging session; and means for controlling output of said plurality of message entries according to output attributes assigned to said plurality of message entries for a particular user to distinguish according to a receiving user's preferences between said plurality of topics, such that output of said plurality of message entries according to topic is distinguished according to a user receiving said plurality of message entries.
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6. A program for controlling messaging outputs in a messaging session, residing on a computer usable medium having computer readable program code means, said program comprising: means for receiving a plurality of message entries each associated with a particular topic from among a plurality of topics within a particular channel of a messaging session; and means for controlling output of said plurality of message entries according to output attributes assigned to said plurality of message entries for a particular user to distinguish according to a receiving user's preferences between said plurality of topics, such that output of said plurality of message entries according to topic is distinguished according to a user receiving said plurality of message entries. 9. The program for controlling messaging outputs in a messaging session according to claim 6 , said program further comprising: means for controlling output of said plurality of message entries to distinguish between said plurality of users.
| 0.691327 |
15. One or more machine-readable storage devices having stored therein a program product, which, when executed by a set of one or more processors, causes the set of one or more processors to perform a method comprising: for an expected input string comprising a plurality of expected string segments comprising a first expected string segment and a second expected string segment, receiving a first speech segment for the first expected string segment and a second speech segment for the second expected string segment, wherein the first speech segment is different from the second speech segment; performing speech recognition separately on the first speech segment and the second speech segment, wherein said performing speech recognition comprises generating a first segment n-best list and a second segment n-best list, the first segment n-best list comprising n highest confidence score results of said speech recognition on the first speech segment, and the second segment n-best list comprising n highest confidence score results of said speech recognition on the second speech segment, where n comprises at least one integer; generating a global n-best list corresponding to said expected input string, wherein the global n-best list comprises a plurality of results each generated at least in part by combining a result from said first segment n-best list with a result from said second segment n-best list; and determining a final global speech recognition result corresponding to said expected input string, wherein said determining said final global speech recognition result comprises pruning results of said global n-best list utilizing a pruning criterion.
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15. One or more machine-readable storage devices having stored therein a program product, which, when executed by a set of one or more processors, causes the set of one or more processors to perform a method comprising: for an expected input string comprising a plurality of expected string segments comprising a first expected string segment and a second expected string segment, receiving a first speech segment for the first expected string segment and a second speech segment for the second expected string segment, wherein the first speech segment is different from the second speech segment; performing speech recognition separately on the first speech segment and the second speech segment, wherein said performing speech recognition comprises generating a first segment n-best list and a second segment n-best list, the first segment n-best list comprising n highest confidence score results of said speech recognition on the first speech segment, and the second segment n-best list comprising n highest confidence score results of said speech recognition on the second speech segment, where n comprises at least one integer; generating a global n-best list corresponding to said expected input string, wherein the global n-best list comprises a plurality of results each generated at least in part by combining a result from said first segment n-best list with a result from said second segment n-best list; and determining a final global speech recognition result corresponding to said expected input string, wherein said determining said final global speech recognition result comprises pruning results of said global n-best list utilizing a pruning criterion. 17. The one or more machine-readable storage devices according to claim 15 , wherein the first segment n-best list comprises a first number of results and the second segment n-best list comprises a second number of results, and the first number is different from the second number.
| 0.548458 |
1. A method, comprising: receiving, by a computing device, a set of information descriptive of a user; receiving, by the computing device, narrative information associated with the user; and validating, by the computing device, at least one item in the set of information based on an analysis of the narrative information.
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1. A method, comprising: receiving, by a computing device, a set of information descriptive of a user; receiving, by the computing device, narrative information associated with the user; and validating, by the computing device, at least one item in the set of information based on an analysis of the narrative information. 2. The method of claim 1 , wherein the narrative information comprises audio information.
| 0.808889 |
26. The computer-readable medium of claim 25 , wherein generating the first dominant query includes: receiving a group of queries including one or more query suggestions for the first text input; determining a popularity value for each query in the group of queries, the popularity value for each query being derived from a number of times one or more users submitted the query suggestion; and identifying a selected query from the one or more queries as the first dominant query, the selected query having a popularity value that exceeds a threshold.
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26. The computer-readable medium of claim 25 , wherein generating the first dominant query includes: receiving a group of queries including one or more query suggestions for the first text input; determining a popularity value for each query in the group of queries, the popularity value for each query being derived from a number of times one or more users submitted the query suggestion; and identifying a selected query from the one or more queries as the first dominant query, the selected query having a popularity value that exceeds a threshold. 29. The computer-readable medium of claim 26 , wherein the popularity value for each query is the number of times one or more users submitted a search for the query suggestion divided by the total number of times the one or more users submitted a search for queries beginning with text matching the first text input.
| 0.825692 |
6. The method of claim 1 , applying the first set of rules resulting in assigning respective scores to respective name segments, the computer determining whether the on-line bank account is utilized for business purposes based at least in part upon the respective scores for respective name segments.
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6. The method of claim 1 , applying the first set of rules resulting in assigning respective scores to respective name segments, the computer determining whether the on-line bank account is utilized for business purposes based at least in part upon the respective scores for respective name segments. 7. The method of claim 6 , the first set of rules comprising multiple rules that are applied to at least one name segment such that multiple scores are assigned to the at least one name segment.
| 0.851736 |
19. The method of claim 1 , further comprising weighting the learned microgenre preferences of the user according to at least one of a measure of recency of selection of the content item having the analyzed microgenre metadata, number of selections of the content item having the analyzed microgenre metadata, and time of use of the content item having the analyzed microgenre metadata, wherein the act of selecting and ordering the collection of content items is further based on the weighted learned microgenre preferences so that content items containing microgenre metadata comparable to the learned microgenre preferences having relatively higher weights are ranked relatively more highly.
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19. The method of claim 1 , further comprising weighting the learned microgenre preferences of the user according to at least one of a measure of recency of selection of the content item having the analyzed microgenre metadata, number of selections of the content item having the analyzed microgenre metadata, and time of use of the content item having the analyzed microgenre metadata, wherein the act of selecting and ordering the collection of content items is further based on the weighted learned microgenre preferences so that content items containing microgenre metadata comparable to the learned microgenre preferences having relatively higher weights are ranked relatively more highly. 20. The method of claim 19 , wherein the weights of the learned microgenre preferences are decayed as time passes from the act of learning the microgenre preferences of the user.
| 0.884842 |
12. The system of claim 9 , wherein the server device is configured to: obtain an automatic speech recognition (ASR) model using the noise parameter; and perform ASR processing using the obtained ASR model and the noise-reduced signal to generate ASR results.
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12. The system of claim 9 , wherein the server device is configured to: obtain an automatic speech recognition (ASR) model using the noise parameter; and perform ASR processing using the obtained ASR model and the noise-reduced signal to generate ASR results. 13. The system of claim 12 , wherein the server device is further configured to obtain an ASR model by selecting an ASR model from a plurality of ASR models.
| 0.913377 |
7. A learning aid as set forth in claim 6, wherein said visual display means and said digital logic means are responsive to the absence of said difference signal from said comparator means indicative of a correct choice of a letter contained within said selected word as an operator input received by said keyboard to display said letter in its appropriate position in said selected word on said visual display means, and said visual display means and said digital logic means are responsive to the presence of said difference signal from said comparator means indicative of an incorrect choice of a letter contained within said selected word as an operator input received by said keyboard to record an incorrect choice decreasing the remaining number of individual inputs permitted to an operator via said keyboard by one.
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7. A learning aid as set forth in claim 6, wherein said visual display means and said digital logic means are responsive to the absence of said difference signal from said comparator means indicative of a correct choice of a letter contained within said selected word as an operator input received by said keyboard to display said letter in its appropriate position in said selected word on said visual display means, and said visual display means and said digital logic means are responsive to the presence of said difference signal from said comparator means indicative of an incorrect choice of a letter contained within said selected word as an operator input received by said keyboard to record an incorrect choice decreasing the remaining number of individual inputs permitted to an operator via said keyboard by one. 8. A learning aid as set forth in claim 7, wherein said visual display means includes a plurality of character positions, said digital logic means being responsive to the selection of said selected word as randomly chosen by said random access generating means or the word represented by the digital data stored in said memory means depending upon which one of said random access generating means and said memory means is enabled for causing said visual display means to display an appropriate number of blank spaces in respective character positions thereof, said blank spaces being no greater in number than said plurality of character positions and corresponding to the number of letters contained in said selected word; and the correct choice of a letter contained within said selected word as an operator input actuating an individual key of said keyboard being operable to display said letter in place of the corresponding blank space of said visual display means appropriately locating the displayed letter in its position in said selected word.
| 0.840599 |
5. The method of claim 1 , further comprising selecting the second semantic descriptor based in part on syntactic-lexical constraints.
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5. The method of claim 1 , further comprising selecting the second semantic descriptor based in part on syntactic-lexical constraints. 6. The method of claim 5 , wherein at least one syntactic-lexical constraint requires that the clause contains a certain kind of lexical particle.
| 0.924615 |
7. An information gathering system for optimizing searching as in claim 6 wherein the search handler identifies the website content through a search engine.
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7. An information gathering system for optimizing searching as in claim 6 wherein the search handler identifies the website content through a search engine. 8. An information gathering system for optimizing searching as in claim 7 wherein the data extraction tool extracts the website content from indexed data provided by the search engine.
| 0.962152 |
6. A system for making unstructured data available to structured data tools comprising: a core server computer executing at least one software module comprising: code to access a source of unstructured data; code to read the unstructured data from the source of unstructured data; code to write a copy of the unstructured data to a capture schema, wherein the capture schema comprises a set of tables to store the copy of the unstructured data and attributes of the unstructured data; code to send the copy of the unstructured data to one or more transformation tools; code to parse, via a natural language processing transformation tool, the copy of the unstructured data to extract sentences from the copy of the unstructured data and then further extract from the extracted sentences sentence-level natural-language processed entities, wherein the sentence-level natural-language processed entities are at least noun phrases; extracting, via a linguistic processing transformation tool, sentence-level linguistically-processed relationships, wherein the sentence-level linguistically-processed relationships comprise associations between the sentence-level natural-language processed entities; code to send the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships from the one or more transformation tools to a categorization tool; code to determine, via the categorization tool, categorization data elements present in each extracted sentence, wherein the categorization data elements based on to the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships, and are placed within predetermined categories, and a confidence level for each categorization data element, wherein the confidence level for each categorization data element combines one or more data points linked to the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships to create a statistically-oriented calculation of confidence assigned to the categorization data element; code to write the categorization data elements from the categorization tool and the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships from the one or more transformation tools in a structured database schema; code to output the confidence level for at least one of the categorization data elements for use in structured data tools; and wherein the one or more data points are selected from the group consisting of: confidence score of value provided by the one or more transformation tools, number of relationships found in the source of unstructured data compared to the size of the source of unstructured data, average number of relationships per kilobyte for relationships of the same type as a selected relationship, number of entities found to be associated with a relationship compared to an average number of entities for relationships in a same hierarchy, number of times similar relationships have been found in the past, number of entities that are grouped together to form a master entity, a number of times an entity occurred in the source of unstructured data compared to the average number of occurrences for entities in the same hierarchy, weighted confidences based on hierarchy of a relationship or entity, measures of data extraction confidence integrated with the system via an analysis schema, measures based on a fullness of a relationship's attributes, measures based on the confluence of a same finding by multiple transformation tools, measures based on the source of the unstructured data, and combinations thereof.
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6. A system for making unstructured data available to structured data tools comprising: a core server computer executing at least one software module comprising: code to access a source of unstructured data; code to read the unstructured data from the source of unstructured data; code to write a copy of the unstructured data to a capture schema, wherein the capture schema comprises a set of tables to store the copy of the unstructured data and attributes of the unstructured data; code to send the copy of the unstructured data to one or more transformation tools; code to parse, via a natural language processing transformation tool, the copy of the unstructured data to extract sentences from the copy of the unstructured data and then further extract from the extracted sentences sentence-level natural-language processed entities, wherein the sentence-level natural-language processed entities are at least noun phrases; extracting, via a linguistic processing transformation tool, sentence-level linguistically-processed relationships, wherein the sentence-level linguistically-processed relationships comprise associations between the sentence-level natural-language processed entities; code to send the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships from the one or more transformation tools to a categorization tool; code to determine, via the categorization tool, categorization data elements present in each extracted sentence, wherein the categorization data elements based on to the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships, and are placed within predetermined categories, and a confidence level for each categorization data element, wherein the confidence level for each categorization data element combines one or more data points linked to the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships to create a statistically-oriented calculation of confidence assigned to the categorization data element; code to write the categorization data elements from the categorization tool and the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships from the one or more transformation tools in a structured database schema; code to output the confidence level for at least one of the categorization data elements for use in structured data tools; and wherein the one or more data points are selected from the group consisting of: confidence score of value provided by the one or more transformation tools, number of relationships found in the source of unstructured data compared to the size of the source of unstructured data, average number of relationships per kilobyte for relationships of the same type as a selected relationship, number of entities found to be associated with a relationship compared to an average number of entities for relationships in a same hierarchy, number of times similar relationships have been found in the past, number of entities that are grouped together to form a master entity, a number of times an entity occurred in the source of unstructured data compared to the average number of occurrences for entities in the same hierarchy, weighted confidences based on hierarchy of a relationship or entity, measures of data extraction confidence integrated with the system via an analysis schema, measures based on a fullness of a relationship's attributes, measures based on the confluence of a same finding by multiple transformation tools, measures based on the source of the unstructured data, and combinations thereof. 7. The system of claim 6 , further comprising code to determine a topic of a section of text, extracting a section of text from a whole document, matching names, or matching addresses.
| 0.583021 |
1. A method performed by one or more computing devices, the method comprising: obtaining, by at least one of the one or more computing devices, a search query; obtaining, by at least one of the one or more computing devices, product search results based on the search query and a products search index that includes information regarding documents associated with products; determining, by at least one of the one or more computing devices, a category associated with a set of results of the product search results; identifying, by at least one of the one or more computing devices, candidate queries for the search query; determining, by at least one of the one or more computing devices, whether the category matches one of the candidate queries; determining, by at least one of the one or more computing devices, a first ratio based on a first quantity of times that the search query is submitted to a web search engine interface; determining, by at least one of the one or more computing devices, a second ratio based on a second quantity of times that the search query is submitted to a specialized search engine interface that is used to search for information associated with a type of media or to search for information associated with news; identifying, by at least one of the one or more computing devices and based on the first ratio and the second ratio, that the search query is associated with the type of media identified by the category when the category matches one of the candidate queries; and providing, by at least one of the one or more computing devices and based on identifying that the search query is associated with the type of media, a result document based on the type of media.
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1. A method performed by one or more computing devices, the method comprising: obtaining, by at least one of the one or more computing devices, a search query; obtaining, by at least one of the one or more computing devices, product search results based on the search query and a products search index that includes information regarding documents associated with products; determining, by at least one of the one or more computing devices, a category associated with a set of results of the product search results; identifying, by at least one of the one or more computing devices, candidate queries for the search query; determining, by at least one of the one or more computing devices, whether the category matches one of the candidate queries; determining, by at least one of the one or more computing devices, a first ratio based on a first quantity of times that the search query is submitted to a web search engine interface; determining, by at least one of the one or more computing devices, a second ratio based on a second quantity of times that the search query is submitted to a specialized search engine interface that is used to search for information associated with a type of media or to search for information associated with news; identifying, by at least one of the one or more computing devices and based on the first ratio and the second ratio, that the search query is associated with the type of media identified by the category when the category matches one of the candidate queries; and providing, by at least one of the one or more computing devices and based on identifying that the search query is associated with the type of media, a result document based on the type of media. 2. The method of claim 1 , where providing the result document based on the type of media includes: identifying one or more products based on the type of media, generating the result document based on the identified one or more products, and providing the result document.
| 0.55656 |
4. The method of claim 3 , further comprising: ranking the subset prior to the providing.
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4. The method of claim 3 , further comprising: ranking the subset prior to the providing. 5. The method of claim 4 , wherein the ranking comprises: applying at least one objective criterion.
| 0.968018 |
31. A method as claimed in claim 30 wherein the step of executing knowledge sources includes the step of updating object values.
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31. A method as claimed in claim 30 wherein the step of executing knowledge sources includes the step of updating object values. 42. A method as claimed in claim 31 further including the steps of communicating messages through communication links between modules in the form of request-response pairs.
| 0.95675 |
1. A method for providing voice commerce, the method being implemented on a computer system having one or more physical processors programmed with computer program instructions which, when executed, perform the method, the method comprising: receiving, by the computer system, a user input comprising a natural language utterance; providing, by the computer system, the natural language utterance as an input to a speech recognition engine; obtaining, by the computer system, one or more words or phrases recognized from the natural language utterance as an output of the speech recognition engine; determining, by the computer system, a context based at least on the one or more words or phrases; identifying, by the computer system, without further user input after the receipt of the user input, a product or service to be purchased on behalf of a user based at least on the determined context; obtaining, by the computer system, payment information with which to pay for the product or service; obtaining, by the computer system, without further user input after the receipt of the user input, shipping information with which to deliver the product or service, wherein the shipping information specifies a name or address of a recipient to which the product or service is to be delivered after the product or service is purchased; and completing, by the computer system, without further user input after the receipt of the user input, a purchase transaction for the product or service based on the payment information and shipping information.
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1. A method for providing voice commerce, the method being implemented on a computer system having one or more physical processors programmed with computer program instructions which, when executed, perform the method, the method comprising: receiving, by the computer system, a user input comprising a natural language utterance; providing, by the computer system, the natural language utterance as an input to a speech recognition engine; obtaining, by the computer system, one or more words or phrases recognized from the natural language utterance as an output of the speech recognition engine; determining, by the computer system, a context based at least on the one or more words or phrases; identifying, by the computer system, without further user input after the receipt of the user input, a product or service to be purchased on behalf of a user based at least on the determined context; obtaining, by the computer system, payment information with which to pay for the product or service; obtaining, by the computer system, without further user input after the receipt of the user input, shipping information with which to deliver the product or service, wherein the shipping information specifies a name or address of a recipient to which the product or service is to be delivered after the product or service is purchased; and completing, by the computer system, without further user input after the receipt of the user input, a purchase transaction for the product or service based on the payment information and shipping information. 7. The method of claim 1 , further comprising: obtaining, by the computer system, user profile information associated with the user, wherein the user profile information comprises at least one of default payment information that is to be used to pay for products or services on behalf of the user or default shipping information that is to be used to delivery products or services on behalf of the user, wherein at least one of: (i) obtaining the payment information comprises selecting the default payment information to pay for the product or service; or (ii) obtaining the shipping information comprises selecting the default shipping information to deliver the product or service, and wherein completing the purchase transaction comprises completing, without further user input after the receipt of the user input, the purchase transaction based on at least one of the default payment information or the default shipping information.
| 0.5 |
8. A computer readable storage device, tangibly embodying a program of instructions executable by a computer for translating content, wherein the content has an author who is part of a social network, the program of instructions, when executing, performing the following steps: receiving the content; retrieving from the social network contextual information associated with the content; retrieving from the social network author information associated with the author; creating a content-specific dictionary based upon the retrieved contextual information and the retrieved author information; creating a translation profile based upon the retrieved contextual information, the retrieved author information and the created content-specific dictionary; determining one of a plurality of generic dictionaries to use for the translating, wherein the determination of the one of the plurality of generic dictionaries to use is based upon the translation profile; and translating the received content using the content-specific dictionary and the determined one of the plurality of generic dictionaries to use.
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8. A computer readable storage device, tangibly embodying a program of instructions executable by a computer for translating content, wherein the content has an author who is part of a social network, the program of instructions, when executing, performing the following steps: receiving the content; retrieving from the social network contextual information associated with the content; retrieving from the social network author information associated with the author; creating a content-specific dictionary based upon the retrieved contextual information and the retrieved author information; creating a translation profile based upon the retrieved contextual information, the retrieved author information and the created content-specific dictionary; determining one of a plurality of generic dictionaries to use for the translating, wherein the determination of the one of the plurality of generic dictionaries to use is based upon the translation profile; and translating the received content using the content-specific dictionary and the determined one of the plurality of generic dictionaries to use. 9. The computer readable storage device of claim 8 , wherein the content comprises a social network post by the author.
| 0.603197 |
3. The method of claim 2 , wherein the locating comprises locating in a respective one of the tree structures a graphic assembly comprising at least two constituent graphic elements.
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3. The method of claim 2 , wherein the locating comprises locating in a respective one of the tree structures a graphic assembly comprising at least two constituent graphic elements. 4. The method of claim 3 , wherein the locating of the graphic assembly comprises identifying a respective tree structure for each of multiple presentations of the graphic assembly corresponding to different respective arrangements of the constituent graphic elements.
| 0.815145 |
1. A method of selecting a profile model for use in examining a structure formed on a semiconductor wafer using optical metrology, the method comprising: a) obtaining an initial profile model having a set of profile parameters that characterize the structure to be examined; b) training a machine learning system using the initial profile model; c) generating a simulated diffraction signal for an optimized profile model using the trained machine learning system, wherein the optimized profile model has a set of profile parameters with the same or fewer profile parameters than the initial profile model; and d) modifying the optimized profile model by eliminating at least one profile parameter or fixing to a value at least one profile parameter and iterating steps c) and d) using the modified optimized profile model and the same trained machine learning system until one or more termination criteria are met.
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1. A method of selecting a profile model for use in examining a structure formed on a semiconductor wafer using optical metrology, the method comprising: a) obtaining an initial profile model having a set of profile parameters that characterize the structure to be examined; b) training a machine learning system using the initial profile model; c) generating a simulated diffraction signal for an optimized profile model using the trained machine learning system, wherein the optimized profile model has a set of profile parameters with the same or fewer profile parameters than the initial profile model; and d) modifying the optimized profile model by eliminating at least one profile parameter or fixing to a value at least one profile parameter and iterating steps c) and d) using the modified optimized profile model and the same trained machine learning system until one or more termination criteria are met. 8. The method of claim 1 , wherein step b) comprises: training a first machine learning system using a set of training input data and a set of training output data, wherein each of the training input data is a profile model having a set of profile parameters with the same profile parameters as the initial profile model, and wherein each of the training output data is a diffraction signal.
| 0.557808 |
7. The non-transitory storage medium of claim 1 , further comprising instructions for causing said computer to implement: deploying process software for providing said search and reference functions for a messaging system, said deploying process software further comprising: installing said process software on at least one server; identifying server addresses for users accessing said process software on said at least one server; installing a proxy server if needed; sending said process software to said at least one server and copying said process software to a file system of said at least one server; sending the process software to at least a first client computer; and executing said process software on said first client computer.
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7. The non-transitory storage medium of claim 1 , further comprising instructions for causing said computer to implement: deploying process software for providing said search and reference functions for a messaging system, said deploying process software further comprising: installing said process software on at least one server; identifying server addresses for users accessing said process software on said at least one server; installing a proxy server if needed; sending said process software to said at least one server and copying said process software to a file system of said at least one server; sending the process software to at least a first client computer; and executing said process software on said first client computer. 10. The non-transitory storage medium of claim 7 , wherein said sending said process software to said first client computer further comprises identifying a user and an address of said first client computer.
| 0.886152 |
14. A computer executable program stored on a computer-readable storage medium and configured to make a computer manage electronically recorded document files, the program comprising instructions for performing the steps of: a step for inputting information by an operator; a step for editing a virtual combination object based on the information inputted in said input step, the virtual combination object denoting an object that has a first data region and virtually combining document files, wherein the first data region includes information for managing the document files to be virtually combined, including an order relation between the document files, and a setting position of the index object to be set immediately before or immediately after the virtually combined document file, or immediately before or immediately after a page constituting the document file; a step for editing an index object based on the information inputted in said input step, the index object denoting an object that has a second data region and manages at least one or more document files included in the document files virtually combined by the virtual combination object or one or more pages constituting the document file, a s a subgroup in the virtual combination object, wherein the second data region includes information on setting for processing the subgroup and a parameter according to the process setting; and a step for managing and processing the document files based on the information recorded in the virtual combination object and the index object.
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14. A computer executable program stored on a computer-readable storage medium and configured to make a computer manage electronically recorded document files, the program comprising instructions for performing the steps of: a step for inputting information by an operator; a step for editing a virtual combination object based on the information inputted in said input step, the virtual combination object denoting an object that has a first data region and virtually combining document files, wherein the first data region includes information for managing the document files to be virtually combined, including an order relation between the document files, and a setting position of the index object to be set immediately before or immediately after the virtually combined document file, or immediately before or immediately after a page constituting the document file; a step for editing an index object based on the information inputted in said input step, the index object denoting an object that has a second data region and manages at least one or more document files included in the document files virtually combined by the virtual combination object or one or more pages constituting the document file, a s a subgroup in the virtual combination object, wherein the second data region includes information on setting for processing the subgroup and a parameter according to the process setting; and a step for managing and processing the document files based on the information recorded in the virtual combination object and the index object. 24. The computer executable program according to claim 14 , wherein the index object has the form of index paper with the tab part, when displayed on a display device in said display step, and, using a pointing device to serve as an input device, a part except for the tab part of the index object, displayed on the display device, is dragged and then dropped in the outside of the virtual combination object displayed on the display device, whereby said virtual combination editing step deletes the dragged and dropped index object.
| 0.618884 |
11. Apparatus, comprising: a memory, which is configured to hold a list of target users of a communication network and respective speech phrases that are characteristic of the target users; and a processor, which is configured to maintain the list in the memory, to select a plurality of candidate communication terminals from among multiple communication terminals in the communication network based on a selection criterion, to analyze speech that is communicated via the candidate communication terminals so as to identify one or more of the speech phrases in the speech, and to correlate one of the candidate communication terminals with a target user who is associated in the list with the identified speech phrases.
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11. Apparatus, comprising: a memory, which is configured to hold a list of target users of a communication network and respective speech phrases that are characteristic of the target users; and a processor, which is configured to maintain the list in the memory, to select a plurality of candidate communication terminals from among multiple communication terminals in the communication network based on a selection criterion, to analyze speech that is communicated via the candidate communication terminals so as to identify one or more of the speech phrases in the speech, and to correlate one of the candidate communication terminals with a target user who is associated in the list with the identified speech phrases. 12. The apparatus according to claim 11 , wherein the processor is configured to select the candidate communication terminals using the selection criterion by choosing one or more communication terminals that were not used previously in the communication network.
| 0.510246 |
10. The method of claim 1 , further comprising: ranking each document in the cluster.
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10. The method of claim 1 , further comprising: ranking each document in the cluster. 11. The method of claim 10 , wherein the documents are ranked based on a predetermined source score which is associated with the source that the document came from.
| 0.964994 |
6. The method of claim 1 , wherein receiving the source text portion comprises: utilizing multiple input filters that convert input information from a non-textual format to a textual format and remove non-translatable formatting from the source text portion.
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6. The method of claim 1 , wherein receiving the source text portion comprises: utilizing multiple input filters that convert input information from a non-textual format to a textual format and remove non-translatable formatting from the source text portion. 7. The method of claim 6 , wherein the multiple input filters includes one or more of a filter that performs optical character recognition on graphics to generate text and a filter that performs voice-to-text conversion on audio to generate text.
| 0.935057 |
12. The system of claim 11 , further comprising selecting an action to be executed from a plurality of actions activated by the application of the Rete algorithm.
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12. The system of claim 11 , further comprising selecting an action to be executed from a plurality of actions activated by the application of the Rete algorithm. 13. The system of claim 12 , further comprising imposing an ordering of execution of the plurality of activated actions using a conflict resolution strategy.
| 0.928082 |
1. A method comprising: initiating a test sequence against a production database within a system of a host organization, the system having a processor and memory therein, wherein the test sequence specifies (i) new data for insertion into the production database during the test sequence and (ii) one or more test queries against the production database during the test sequence; performing a database transaction to insert the new data into the production database without committing the new data to the production database; recording names of one or more objects corresponding to the inserted new data, the one or more objects created as part of the transaction to insert the new data into the production database within a transaction entity object map, wherein recording the names of the one or more objects corresponding to the inserted new data comprises recording the names of the one or more objects created within the transaction entity object map during the performing of the database transaction to insert the new data into the production database in which the transaction entity object map is used for transaction management operations, including: (i) checking locks on objects stored within the production database, (ii) protecting against deadlock by queries executed against the production database, (iii) determining a failure occurs during transactions with the production database, (iv) determining a rollback is required for transactions with the production database, (v) determining any new changes to data have occurred before committing transactions to the production database affected by the new changes to data, and (vi) determining a commit operation is permissible for transactions with the production database; the method further comprising: modifying the one or more test queries specified by the test sequence to no longer query against the production database by substituting the one or more test queries with references to the names of the one or more objects in operating memory separate from information stored within the production database; and executing the one or more modified test queries.
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1. A method comprising: initiating a test sequence against a production database within a system of a host organization, the system having a processor and memory therein, wherein the test sequence specifies (i) new data for insertion into the production database during the test sequence and (ii) one or more test queries against the production database during the test sequence; performing a database transaction to insert the new data into the production database without committing the new data to the production database; recording names of one or more objects corresponding to the inserted new data, the one or more objects created as part of the transaction to insert the new data into the production database within a transaction entity object map, wherein recording the names of the one or more objects corresponding to the inserted new data comprises recording the names of the one or more objects created within the transaction entity object map during the performing of the database transaction to insert the new data into the production database in which the transaction entity object map is used for transaction management operations, including: (i) checking locks on objects stored within the production database, (ii) protecting against deadlock by queries executed against the production database, (iii) determining a failure occurs during transactions with the production database, (iv) determining a rollback is required for transactions with the production database, (v) determining any new changes to data have occurred before committing transactions to the production database affected by the new changes to data, and (vi) determining a commit operation is permissible for transactions with the production database; the method further comprising: modifying the one or more test queries specified by the test sequence to no longer query against the production database by substituting the one or more test queries with references to the names of the one or more objects in operating memory separate from information stored within the production database; and executing the one or more modified test queries. 2. The method of claim 1 , wherein the transaction entity object map is used to track objects created as part of a transaction with the production database.
| 0.653289 |
1. A method comprising: receiving, by a computing device, an input natural language text including an input word; searching a semantic register to identify a matching word corresponding to the input word, wherein the semantic register comprises a plurality of records, each record associating a word with a concept of a semantic class; responsive to successfully identifying the matching word, identifying a first plurality of concepts associated with the matching word by the semantic register; ranking a plurality of semantic classes associated with the identified first plurality of concepts according to a probability of the input word being associated with a respective semantic class; selecting a pre-defined number of semantic classes having highest probabilities of the input word being associated with a respective semantic class; iterating through a second plurality of concepts associated, by the semantic register, with the pre-defined number of semantic classes, to identify a concept corresponding to the input word; and responsive to successfully identifying the concept, associating the identified concept with the input word.
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1. A method comprising: receiving, by a computing device, an input natural language text including an input word; searching a semantic register to identify a matching word corresponding to the input word, wherein the semantic register comprises a plurality of records, each record associating a word with a concept of a semantic class; responsive to successfully identifying the matching word, identifying a first plurality of concepts associated with the matching word by the semantic register; ranking a plurality of semantic classes associated with the identified first plurality of concepts according to a probability of the input word being associated with a respective semantic class; selecting a pre-defined number of semantic classes having highest probabilities of the input word being associated with a respective semantic class; iterating through a second plurality of concepts associated, by the semantic register, with the pre-defined number of semantic classes, to identify a concept corresponding to the input word; and responsive to successfully identifying the concept, associating the identified concept with the input word. 7. The method of claim 1 , wherein identifying the concept corresponding to the input word further comprises: identifying, in a parallel natural language text corresponding to the input natural language text, a parallel word corresponding to the input word; and comparing a first context associated the input word to a second context associated with the parallel word in the parallel natural language text.
| 0.5796 |
32. The computer program product of claim 29 , wherein characteristics of the taxonomic nouns include at least one of a term type, a flag, a document count, and an occurrence count.
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32. The computer program product of claim 29 , wherein characteristics of the taxonomic nouns include at least one of a term type, a flag, a document count, and an occurrence count. 40. The computer program product of claim 32 , wherein the term type includes a topic name, the topic name including a single term that represents a cluster of related terms.
| 0.945108 |
51. A system for synthesizing signals from compressed information signals having the form of an inverse transformation of a partially symmetric phase adjusted transform of the original signals, said compressed information signals being devoid of selected portions corresponding to a fraction of the partially symmetric portions of said phase adjusted transform, and instruction signals identifying the selected portions, said system comprising: means for reproducing said compressed information signals; means coupled to said reproducing means for expanding the reproduced signals to supply said fractional portions in accordance with said instruction signals; and means for converting the expanded reproduced signals to audible form.
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51. A system for synthesizing signals from compressed information signals having the form of an inverse transformation of a partially symmetric phase adjusted transform of the original signals, said compressed information signals being devoid of selected portions corresponding to a fraction of the partially symmetric portions of said phase adjusted transform, and instruction signals identifying the selected portions, said system comprising: means for reproducing said compressed information signals; means coupled to said reproducing means for expanding the reproduced signals to supply said fractional portions in accordance with said instruction signals; and means for converting the expanded reproduced signals to audible form. 52. The combination of claim 51 further including memory means for storing said compressed signals and wherein said reproducing means includes means for reading said compressed signals from said memory means.
| 0.928446 |
1. A method for establishing with a computer system an audio conference between two or more communication devices each associated with one of a plurality of different languages, wherein one of said different languages represents a main language, said method comprising the steps of: providing a computer system connecting each of one or more of said communication devices associated with a different one of said languages than said main language with a communication device of an interpreter for interpreting between said different one of said languages and said main language to enable the communication device of the interpreter to receive voice communication from each of the one or more of said communication devices associated with said different one of said languages, and connecting the communication device of the interpreter associated with each one of said different languages than said main language with one or more of said communication devices in the main language to enable the communication device of the interpreter to receive voice communication from said one or more communication devices associated with the main language; and controlling the communication device of the interpreter associated with each one of said different languages than the main language during oral translation by the interpreter between said one of said different languages and said main language as to which one of (i) one or more of said communication devices associated with the main language is connected to the communication device of the interpreter, or (ii) one or more of said communication devices associated with said one of said different languages is connected to the communication device of the interpreter, to receive voice communication of the interpreter in one of said main language or said one of said different languages, respectively, in which said controlling step is carried out by said computer system responsive to the interpreter at the communication device of the interpreter for at least one of the one or more different languages than the main language over a single voice communication line between the communication device of the interpreter and said computer system.
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1. A method for establishing with a computer system an audio conference between two or more communication devices each associated with one of a plurality of different languages, wherein one of said different languages represents a main language, said method comprising the steps of: providing a computer system connecting each of one or more of said communication devices associated with a different one of said languages than said main language with a communication device of an interpreter for interpreting between said different one of said languages and said main language to enable the communication device of the interpreter to receive voice communication from each of the one or more of said communication devices associated with said different one of said languages, and connecting the communication device of the interpreter associated with each one of said different languages than said main language with one or more of said communication devices in the main language to enable the communication device of the interpreter to receive voice communication from said one or more communication devices associated with the main language; and controlling the communication device of the interpreter associated with each one of said different languages than the main language during oral translation by the interpreter between said one of said different languages and said main language as to which one of (i) one or more of said communication devices associated with the main language is connected to the communication device of the interpreter, or (ii) one or more of said communication devices associated with said one of said different languages is connected to the communication device of the interpreter, to receive voice communication of the interpreter in one of said main language or said one of said different languages, respectively, in which said controlling step is carried out by said computer system responsive to the interpreter at the communication device of the interpreter for at least one of the one or more different languages than the main language over a single voice communication line between the communication device of the interpreter and said computer system. 5. The method according to claim 1 further comprising the step of providing by said computer system for at least one of the one or more said communication devices associated with one of the different languages than the main language with a one-way receive only connection with the audio conference in said main language to enable hearing the audio conference in said main language at an adjustable volume level at the communication device.
| 0.635818 |
10. A method of executing operations sets on data sets accessible according to a protocol on a host having a processor and a memory, comprising: executing on the processor instructions configured to: upon receiving a request to associate, with a data set and a verb of the protocol that is associated with an action, an operations set other than the action of the verb: store the operations set in the memory, and associate the operations set with the verb of the protocol and the data set; and upon receiving a protocol request specifying a verb of the protocol and a data set: execute the action associated with the verb of the protocol to fulfill the protocol request; and additionally execute at least one operations set associated with the verb and the data set.
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10. A method of executing operations sets on data sets accessible according to a protocol on a host having a processor and a memory, comprising: executing on the processor instructions configured to: upon receiving a request to associate, with a data set and a verb of the protocol that is associated with an action, an operations set other than the action of the verb: store the operations set in the memory, and associate the operations set with the verb of the protocol and the data set; and upon receiving a protocol request specifying a verb of the protocol and a data set: execute the action associated with the verb of the protocol to fulfill the protocol request; and additionally execute at least one operations set associated with the verb and the data set. 12. The method of claim 10 : the operations set comprising a predicate condition of the verb, and the executing comprising: executing the operations set before executing the protocol request, and conditioning executing the protocol request on a fulfilling of the predicate condition of the operations set.
| 0.548571 |
14. A method of testing an electronic document page, the method comprising: creating an intermediate representation of an electronic document page, the page being defined by a page description implemented in a markup language, the page description referring to data accessible via a data model, the intermediate representation including at least a portion of the data accessible via the data model, the intermediate representation being renderable to create a rendered page, the rendered page being displayable on a display device; initiating an action in the intermediate representation, the action simulating user input that can be provided via a rendered representation of the page, the action capable of causing a change in the portion of the data accessible via the data model; determining an expected value for the portion of the data model based on the initiated action in the intermediate representation; identifying an actual value for the portion of the data model; determining whether the actual value matches the expected value; and when the actual value does not match the expected value, storing an indication of an error.
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14. A method of testing an electronic document page, the method comprising: creating an intermediate representation of an electronic document page, the page being defined by a page description implemented in a markup language, the page description referring to data accessible via a data model, the intermediate representation including at least a portion of the data accessible via the data model, the intermediate representation being renderable to create a rendered page, the rendered page being displayable on a display device; initiating an action in the intermediate representation, the action simulating user input that can be provided via a rendered representation of the page, the action capable of causing a change in the portion of the data accessible via the data model; determining an expected value for the portion of the data model based on the initiated action in the intermediate representation; identifying an actual value for the portion of the data model; determining whether the actual value matches the expected value; and when the actual value does not match the expected value, storing an indication of an error. 18. The method recited in claim 14 , wherein the one or more operations for creating the page include at least one operation for defining at least a portion of the data model.
| 0.627223 |
19. A computer-implemented method of facilitating comparisons of information item attributes based on queries of a topic-based-source-specific search system, the system being configured to collect information from predefined sources relating to a content topic prior to the queries, the method being implemented by the system that includes one or more processors executing one or more computer program modules which, when executed, perform the method, the method comprising: storing, by an indexing module, metadata in association with information items of the predefined sources, wherein the metadata indicate a first attribute relating to first ones of the information items and a second attribute relating to second ones of the information items; receiving, by a query input module, an input relating to a query; and determining, by an information retrieval module, a subset of the information items that relates to the received input; providing, by a user interface module, a display of a user interface that presents a comparison between the first attribute and the second attribute based on one or more first information items of the determined subset that relate to the first attribute and one or more second information items of the determined subset that relate to the second attribute; determining, by a suggestion module, suggested ones of the predefined sources and suggested ones of the information items of the predefined sources based on the received input; providing, by the user interface module, a set of suggestions including a group of suggestions relating to the suggested sources and a group of suggestions relating to the suggested information items for presentation on the user interface; providing, by the user interface module, a query input component on the display of the user interface, wherein the query input component is configured to receive the input; receiving, by the query input module, a second input relating to the query responsive to providing the set of suggestions; and determining, by an information retrieval module, a subset of the information items that relates to the received second input; determining, by the information retrieval module, one or more sources associated with the determined subset of the information items; and providing, by the user interface module, one or more representations of the determined subset of the information items and one or more representations of the determined sources on the display of the user interface simultaneously with the query input component.
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19. A computer-implemented method of facilitating comparisons of information item attributes based on queries of a topic-based-source-specific search system, the system being configured to collect information from predefined sources relating to a content topic prior to the queries, the method being implemented by the system that includes one or more processors executing one or more computer program modules which, when executed, perform the method, the method comprising: storing, by an indexing module, metadata in association with information items of the predefined sources, wherein the metadata indicate a first attribute relating to first ones of the information items and a second attribute relating to second ones of the information items; receiving, by a query input module, an input relating to a query; and determining, by an information retrieval module, a subset of the information items that relates to the received input; providing, by a user interface module, a display of a user interface that presents a comparison between the first attribute and the second attribute based on one or more first information items of the determined subset that relate to the first attribute and one or more second information items of the determined subset that relate to the second attribute; determining, by a suggestion module, suggested ones of the predefined sources and suggested ones of the information items of the predefined sources based on the received input; providing, by the user interface module, a set of suggestions including a group of suggestions relating to the suggested sources and a group of suggestions relating to the suggested information items for presentation on the user interface; providing, by the user interface module, a query input component on the display of the user interface, wherein the query input component is configured to receive the input; receiving, by the query input module, a second input relating to the query responsive to providing the set of suggestions; and determining, by an information retrieval module, a subset of the information items that relates to the received second input; determining, by the information retrieval module, one or more sources associated with the determined subset of the information items; and providing, by the user interface module, one or more representations of the determined subset of the information items and one or more representations of the determined sources on the display of the user interface simultaneously with the query input component. 20. The method of claim 19 , wherein the first attribute corresponds to a first political or government entity, and wherein the second attribute corresponds to a second political or government entity.
| 0.575535 |
1. A method comprising: receiving, by a server device comprising a processor, a noise-reduced audio signal and a noise parameter from a user device, wherein the noise parameter provides information relating to how noise was reduced in the noise-reduced audio signal; selecting, by the server device, a first automatic speech recognition (ASR) model from a plurality of ASR models wherein: each ASR model of the plurality of ASR models is associated with a respective noise parameter model, and the first ASR model is selected based at least in part on a comparison between the noise parameter and the noise parameter model associated with the first ASR model; and performing, by the server device, ASR processing on the noise-reduced audio signal using the first ASR model to generate ASR results.
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1. A method comprising: receiving, by a server device comprising a processor, a noise-reduced audio signal and a noise parameter from a user device, wherein the noise parameter provides information relating to how noise was reduced in the noise-reduced audio signal; selecting, by the server device, a first automatic speech recognition (ASR) model from a plurality of ASR models wherein: each ASR model of the plurality of ASR models is associated with a respective noise parameter model, and the first ASR model is selected based at least in part on a comparison between the noise parameter and the noise parameter model associated with the first ASR model; and performing, by the server device, ASR processing on the noise-reduced audio signal using the first ASR model to generate ASR results. 8. The method of claim 1 , further comprising transmitting the ASR results to the user device.
| 0.652961 |
1. One or more non-transitory computer-readable media storing computer-executable instructions for comparing two structured documents that, when executed by one or more processors, configure the one or more processors to perform operations comprising: identifying, by performing a traversal of a first structure in a first document and a second structure in a second document, one or more potential matches between elements in the first and second documents; obtaining, from a user, specified custom rules defining expected differences between the first and second documents, the expected differences indicating a positional change between at least one actual element positioned within a first hierarchical arrangement of the first document and at least one expected element positioned within a second hierarchical arrangement of the second document; determining when differences between the identified potential matches are significant based at least in part on the custom rules, wherein significant differences are determined to be significant as a result of being differences, other than expected differences, that vary from the expected differences; and effecting data storage for the at least one difference that is determined to be significant.
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1. One or more non-transitory computer-readable media storing computer-executable instructions for comparing two structured documents that, when executed by one or more processors, configure the one or more processors to perform operations comprising: identifying, by performing a traversal of a first structure in a first document and a second structure in a second document, one or more potential matches between elements in the first and second documents; obtaining, from a user, specified custom rules defining expected differences between the first and second documents, the expected differences indicating a positional change between at least one actual element positioned within a first hierarchical arrangement of the first document and at least one expected element positioned within a second hierarchical arrangement of the second document; determining when differences between the identified potential matches are significant based at least in part on the custom rules, wherein significant differences are determined to be significant as a result of being differences, other than expected differences, that vary from the expected differences; and effecting data storage for the at least one difference that is determined to be significant. 7. The one or more computer-readable media of claim 1 , wherein the instructions, when executed, further configure the one or more processors to perform operations comprising filtering out differences determined to be statistically insignificant.
| 0.687283 |
46. The system of claim 39 , wherein the search engine generates subplans structured as left deep operator subtrees for obtaining data requested by the query.
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46. The system of claim 39 , wherein the search engine generates subplans structured as left deep operator subtrees for obtaining data requested by the query. 47. The system of claim 46 , wherein the search engine groups said subplans into classes based on tables covered by each subplan.
| 0.908243 |
17. A computer-readable storage medium comprising instructions for performing a method for providing an efficient M-out-of-N partial matching search, the method comprising: initializing a global location space (GLS) by assigning respective occurrences of words to continuous locations of a one-dimensional array comprised within the GLS, wherein the words are from one or more documents indexed for searching, the one or more documents delineated within the GLS using end of document (EOD) words, an EOD word comprising a designator marking a boundary between two documents; separating words of a received query having an integer value N words into an active set and a non-active set, the active set comprising an integer value M words of the received query that are left-most occurring with the GLS, the integer value M being less than the integer value N; and traversing the GLS by applying geometric constraints to the active set to determine if M words of the received query are comprised within one or more documents, at least one of the traversal comprising: detecting an occurrence of a right EOD word of a current document occurring within the GLS before a location of a right-most word of the active set within the GLS, and determining the current document fails a geometric constraint based upon the occurrence, and for respective current words of the active set occurring before the right EOD word: incrementing a current location of a current word to a next occurring location of the current word within the GLS after the right EOD word based upon the next occurring location occurring before a left-most word of the non-active set within the GLS, otherwise substituting the current word with the left-most word within the non-active set.
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17. A computer-readable storage medium comprising instructions for performing a method for providing an efficient M-out-of-N partial matching search, the method comprising: initializing a global location space (GLS) by assigning respective occurrences of words to continuous locations of a one-dimensional array comprised within the GLS, wherein the words are from one or more documents indexed for searching, the one or more documents delineated within the GLS using end of document (EOD) words, an EOD word comprising a designator marking a boundary between two documents; separating words of a received query having an integer value N words into an active set and a non-active set, the active set comprising an integer value M words of the received query that are left-most occurring with the GLS, the integer value M being less than the integer value N; and traversing the GLS by applying geometric constraints to the active set to determine if M words of the received query are comprised within one or more documents, at least one of the traversal comprising: detecting an occurrence of a right EOD word of a current document occurring within the GLS before a location of a right-most word of the active set within the GLS, and determining the current document fails a geometric constraint based upon the occurrence, and for respective current words of the active set occurring before the right EOD word: incrementing a current location of a current word to a next occurring location of the current word within the GLS after the right EOD word based upon the next occurring location occurring before a left-most word of the non-active set within the GLS, otherwise substituting the current word with the left-most word within the non-active set. 20. The computer-readable storage medium of claim 17 , comprising: identifying one or more documents comprising M words within the active set based upon traversing the GLS.
| 0.524832 |
18. A method of providing a hybrid system-modified user annotation during a presentation of a content item where the hybrid system-modified user annotation is based on (i) a user annotation that comprises a reference associated with a corresponding products or service appearing in the content item and (ii) system identification of the product-or-service reference in the user annotation, the method being implemented by a computer system that includes one or more physical processors executing one or more computer program instructions which, when executed, perform the method, the method comprising: receiving, by the computer system, a first annotation provided by a first user during a presentation of a first content item, wherein the first annotation corresponds to a reference time at which a product or service appears in the first content item, and wherein the first annotation is provided by the first user via a user device different from the computer system; identifying, by the computer system, in the first annotation, a reference referring to the product or service; modifying, by the computer system, the first annotation to include a mechanism that enables a transaction related to the product or service, wherein the first annotation is modified to include the mechanism based on the identification of the reference; and providing, by the computer system, a presentation of the modified first annotation during one or more presentations of the first content item to other users such that the mechanism is available for use by the other users via the modified first annotation during the one or more presentations of the first content item.
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18. A method of providing a hybrid system-modified user annotation during a presentation of a content item where the hybrid system-modified user annotation is based on (i) a user annotation that comprises a reference associated with a corresponding products or service appearing in the content item and (ii) system identification of the product-or-service reference in the user annotation, the method being implemented by a computer system that includes one or more physical processors executing one or more computer program instructions which, when executed, perform the method, the method comprising: receiving, by the computer system, a first annotation provided by a first user during a presentation of a first content item, wherein the first annotation corresponds to a reference time at which a product or service appears in the first content item, and wherein the first annotation is provided by the first user via a user device different from the computer system; identifying, by the computer system, in the first annotation, a reference referring to the product or service; modifying, by the computer system, the first annotation to include a mechanism that enables a transaction related to the product or service, wherein the first annotation is modified to include the mechanism based on the identification of the reference; and providing, by the computer system, a presentation of the modified first annotation during one or more presentations of the first content item to other users such that the mechanism is available for use by the other users via the modified first annotation during the one or more presentations of the first content item. 19. The method of claim 18 , wherein providing the presentation of the modified first annotation comprises providing, based on the corresponding reference time, the presentation of the modified first annotation at a time at which the corresponding reference time is reached during the one or more presentations of the first content item.
| 0.6122 |
2. The system claimed in claim 1 , further comprising: a database to store: teaching experiences related to graduate attributes and learning outcomes; student feedback related to courses, or course units; a processor to: map changes to teaching and assessment methods, both formative and summative, related to information in the database.
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2. The system claimed in claim 1 , further comprising: a database to store: teaching experiences related to graduate attributes and learning outcomes; student feedback related to courses, or course units; a processor to: map changes to teaching and assessment methods, both formative and summative, related to information in the database. 3. The system claimed in claim 2 , further comprising: an interface for teachers to: set up assessment items, which contain information such as the title, due date, maximum marks, list of questions, answer guide and grading system; map assessment items to relevant graduate attributes and learning outcomes; input definitions of assessment rubrics, assessment criteria highlighter and XML markup editor to be used for commenting and grading assessment items; and, allocate and track assessment items, or a group of questions within the assessment items, to one or more markers.
| 0.791991 |
1. A computer-implemented method for use in natural language translation, said method comprising performing in software processes, the steps of: receiving source material segments being authored by a user in a first natural language; comparing, utilizing a module stored in memory and communicatively coupled with a processor, the received source material segments with stored material segments in the first natural language, said stored material segments having previously been translated from said first natural language to target segments in a second natural language; identifying a plurality of source material segments that are similar to stored material segments using a fuzzy match level; outputting the plurality of identified source material segments and respective similar stored material segments in a form suitable for review by a user; replacing identified source material segments with respective similar stored material segments to assist full translation of source material from said first natural language to at least said second natural language, wherein the replacing is carried out in response to input from a user and wherein the user chooses to amend the source material they are currently authoring according to stored material; and translating the authored source material using machine translation to: reuse similar stored material segments replaced from translation memory and respective stored target segments stored in translation memory, and translate the source material segments not replaced from translation memory.
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1. A computer-implemented method for use in natural language translation, said method comprising performing in software processes, the steps of: receiving source material segments being authored by a user in a first natural language; comparing, utilizing a module stored in memory and communicatively coupled with a processor, the received source material segments with stored material segments in the first natural language, said stored material segments having previously been translated from said first natural language to target segments in a second natural language; identifying a plurality of source material segments that are similar to stored material segments using a fuzzy match level; outputting the plurality of identified source material segments and respective similar stored material segments in a form suitable for review by a user; replacing identified source material segments with respective similar stored material segments to assist full translation of source material from said first natural language to at least said second natural language, wherein the replacing is carried out in response to input from a user and wherein the user chooses to amend the source material they are currently authoring according to stored material; and translating the authored source material using machine translation to: reuse similar stored material segments replaced from translation memory and respective stored target segments stored in translation memory, and translate the source material segments not replaced from translation memory. 26. The method according to claim 1 , wherein said outputting further comprises outputting data associated with said identifying of the plurality of source material segments that are similar to stored material segments using the fuzzy match level.
| 0.520656 |
3. The method of claim 1 wherein the plurality of objects further comprise a number of candidates, and further comprising: making a determination that at least a portion of a particular candidate matches the at least portion of the string of reference characters; and responsive to the making of the determination, storing the at least portion of the string of reference characters as at least a portion of a segment.
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3. The method of claim 1 wherein the plurality of objects further comprise a number of candidates, and further comprising: making a determination that at least a portion of a particular candidate matches the at least portion of the string of reference characters; and responsive to the making of the determination, storing the at least portion of the string of reference characters as at least a portion of a segment. 4. The method of claim 3 , further comprising deleting the particular candidate.
| 0.967678 |
8. The computer-implemented method of claim 1 further comprising, extracting the plurality of relational tables from the corpus, and processing the plurality of relational tables into a graph using a model by using a feature set comprising one or more features corresponding to context associated with each relational table of the plurality of relational tables.
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8. The computer-implemented method of claim 1 further comprising, extracting the plurality of relational tables from the corpus, and processing the plurality of relational tables into a graph using a model by using a feature set comprising one or more features corresponding to context associated with each relational table of the plurality of relational tables. 10. The computer-implemented method of claim 8 further comprising, automatically generating labeled training data, and training the model based at least in part on the automatically generated labeled training data.
| 0.930013 |
4. A computer-readable storage medium storing program code, the program code comprising: code to call a constructor to register an interface to a description of a persistent class; code to access the registered interface to determine an internal structure of the persistent class; code to process an instance of the persistent class based on the determined internal structure, wherein the instance of the persistent class is a persistent database object; code to determine, based on the determined internal structure, members of the persistent database object that are filled with default values; code to store the persistent database object in a database; code to reduce storage demands on the database by removing the default values from the persistent database object before the storing of the persistent database object in the database; code to read the persistent database object from the database after the storing of the persistent database object in the database; code to populate the determined members of the persistent database object with the default values after the reading of the persistent database object from the database; code to define an index associated with one or more members of the instance based on the determined internal structure; and code to verify referential integrity of the instance.
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4. A computer-readable storage medium storing program code, the program code comprising: code to call a constructor to register an interface to a description of a persistent class; code to access the registered interface to determine an internal structure of the persistent class; code to process an instance of the persistent class based on the determined internal structure, wherein the instance of the persistent class is a persistent database object; code to determine, based on the determined internal structure, members of the persistent database object that are filled with default values; code to store the persistent database object in a database; code to reduce storage demands on the database by removing the default values from the persistent database object before the storing of the persistent database object in the database; code to read the persistent database object from the database after the storing of the persistent database object in the database; code to populate the determined members of the persistent database object with the default values after the reading of the persistent database object from the database; code to define an index associated with one or more members of the instance based on the determined internal structure; and code to verify referential integrity of the instance. 5. The medium according to claim 4 , the program code further comprising: code to register the persistent class in an object management system, and wherein the interface is registered in the object management system.
| 0.574789 |
14. A system comprising: a processing device storing; an input module configured to receive a matrix for a set of documents, each row of the matrix corresponding to each document of the set of documents and each column of the matrix corresponding to a text segment that is in at least one document of the set of documents, each cell of the matrix including a frequency value indicating a number of instances of a corresponding text segment in a corresponding document; a smoothing module configured to receive an indication of a relationship between two text segments, each of the two text segments associated with a first column and a second column, respectively, of the matrix and to adjust, for each document, a frequency value of the second column based on a frequency value of the first column; and an analysis module configured to project each frequency value of the matrix into a reference space to generate a set of projection values in the reference space, to identify a plurality of subsets of the reference space, at least some of the plurality of subsets including at least some of the projection values of the set of projection values in the reference space, to cluster, for each subset of the plurality of subsets, at least some documents of the set of documents that correspond to a subset of the set of projection values to generate clusters of one or more documents, and to generate a graph of nodes, each of the nodes identifying one or more of the documents corresponding to each cluster.
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14. A system comprising: a processing device storing; an input module configured to receive a matrix for a set of documents, each row of the matrix corresponding to each document of the set of documents and each column of the matrix corresponding to a text segment that is in at least one document of the set of documents, each cell of the matrix including a frequency value indicating a number of instances of a corresponding text segment in a corresponding document; a smoothing module configured to receive an indication of a relationship between two text segments, each of the two text segments associated with a first column and a second column, respectively, of the matrix and to adjust, for each document, a frequency value of the second column based on a frequency value of the first column; and an analysis module configured to project each frequency value of the matrix into a reference space to generate a set of projection values in the reference space, to identify a plurality of subsets of the reference space, at least some of the plurality of subsets including at least some of the projection values of the set of projection values in the reference space, to cluster, for each subset of the plurality of subsets, at least some documents of the set of documents that correspond to a subset of the set of projection values to generate clusters of one or more documents, and to generate a graph of nodes, each of the nodes identifying one or more of the documents corresponding to each cluster. 16. The system of claim 14 , further comprising a visualization module configured to generate a graphical representation of the graph of nodes.
| 0.610835 |
1. A taxonomy control for an appliance having a software component configured to perform a cycle of operation on a physical article and for a controlling device for the appliance, the taxonomy control comprising: a dataset, stored in a medium, and describing attributes that contain a plurality of child values which represent valid values of the attributes, and derived from operational capabilities of the appliance for at least one state of the appliance, and a taxonomy operator in a processor to operate on the dataset, wherein the dataset is generated by the appliance in the at least one state, limited to the at least one state, and sent to the controlling device, whereby the controlling device can create well formed commands from the dataset as operated on by the taxonomy operator that can be executed by the appliance in the at least one state without need for a variant of the software component in the controlling device.
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1. A taxonomy control for an appliance having a software component configured to perform a cycle of operation on a physical article and for a controlling device for the appliance, the taxonomy control comprising: a dataset, stored in a medium, and describing attributes that contain a plurality of child values which represent valid values of the attributes, and derived from operational capabilities of the appliance for at least one state of the appliance, and a taxonomy operator in a processor to operate on the dataset, wherein the dataset is generated by the appliance in the at least one state, limited to the at least one state, and sent to the controlling device, whereby the controlling device can create well formed commands from the dataset as operated on by the taxonomy operator that can be executed by the appliance in the at least one state without need for a variant of the software component in the controlling device. 7. The taxonomy control of claim 1 wherein the taxonomy operator is one of a selection builder, a status interpreter, and a command generator.
| 0.605136 |
9. A computer program product for selecting a recommended investment portfolio based in part on investment factor considerations, the computer program product comprising computer-readable media encoded with non-transitory tangible instructions for execution by a processor to perform a method comprising: (a) providing a portfolio of securities identified for potential inclusion in the recommended investment portfolio; (b) providing investment factor scores for the identified securities; (c) ranking the identified securities relative to each other based on their investment factor scores in a computerized ranking engine; (d) entering into a processor: (i) initial weightings for each of the identified securities, or data by which initial weightings for each of the identified securities is objectively calculated, the initial weightings or the data being unadjusted by investment factor considerations, (ii) the ranking of the identified securities based on their investment factor scores, and (iii) an investment factor multiplier algorithm that is correlated with the relative ranking; (e) calculating via the processor using a weighting engine, adjusted weightings for the portfolio of securities using at least the entered items (i)-(iii), wherein securities having higher ranked investment factor scores relative to other securities receive greater weightings, and the weightings include non-binary weightings; (f) outputting via the processor, the adjusted weightings for the portfolio of securities; and (g) selecting the recommended investment portfolio based in part on investment factor considerations using the adjusted weightings.
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9. A computer program product for selecting a recommended investment portfolio based in part on investment factor considerations, the computer program product comprising computer-readable media encoded with non-transitory tangible instructions for execution by a processor to perform a method comprising: (a) providing a portfolio of securities identified for potential inclusion in the recommended investment portfolio; (b) providing investment factor scores for the identified securities; (c) ranking the identified securities relative to each other based on their investment factor scores in a computerized ranking engine; (d) entering into a processor: (i) initial weightings for each of the identified securities, or data by which initial weightings for each of the identified securities is objectively calculated, the initial weightings or the data being unadjusted by investment factor considerations, (ii) the ranking of the identified securities based on their investment factor scores, and (iii) an investment factor multiplier algorithm that is correlated with the relative ranking; (e) calculating via the processor using a weighting engine, adjusted weightings for the portfolio of securities using at least the entered items (i)-(iii), wherein securities having higher ranked investment factor scores relative to other securities receive greater weightings, and the weightings include non-binary weightings; (f) outputting via the processor, the adjusted weightings for the portfolio of securities; and (g) selecting the recommended investment portfolio based in part on investment factor considerations using the adjusted weightings. 15. The computer program product of claim 9 wherein step (c) further comprises the computerized ranking engine receiving the investment factor scores from a database of such scores.
| 0.588409 |
15. A computer-implemented method comprising: identifying, by a data processing apparatus, a test object having a corresponding set of object attribute values; identifying, by the data processing apparatus, sets of training candidates, each candidate in each of the sets of training candidates having a corresponding set of training candidate attribute values; and for each set of training candidates: identifying a set of training candidate/object feature value pairs, each training candidate/object feature value pair being an object attribute value and a matching training candidate attribute value, providing, by the data processing apparatus, the set of training candidate/object feature value pairs to a plurality of models; training each model to predict a likelihood that a candidate matches the test object, the training comprising, for each model: identifying K training candidates for the model; and adjusting one or more model coefficients of the model based on the object attributes and the training candidates specified by the set of training candidate/object feature value pairs that correspond to the identified K training candidates for the model; wherein the value of K is different for each model.
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15. A computer-implemented method comprising: identifying, by a data processing apparatus, a test object having a corresponding set of object attribute values; identifying, by the data processing apparatus, sets of training candidates, each candidate in each of the sets of training candidates having a corresponding set of training candidate attribute values; and for each set of training candidates: identifying a set of training candidate/object feature value pairs, each training candidate/object feature value pair being an object attribute value and a matching training candidate attribute value, providing, by the data processing apparatus, the set of training candidate/object feature value pairs to a plurality of models; training each model to predict a likelihood that a candidate matches the test object, the training comprising, for each model: identifying K training candidates for the model; and adjusting one or more model coefficients of the model based on the object attributes and the training candidates specified by the set of training candidate/object feature value pairs that correspond to the identified K training candidates for the model; wherein the value of K is different for each model. 17. The method of claim 15 , wherein each of the sets of training candidates include a positive candidate that matches the test object and a plurality of negative candidates that do not match the test object.
| 0.856938 |
19. A computer server-implemented method for personalization of network search results and search result rankings, the computer server comprising a network input and output interface, at least one data storage device, and one or more processors coupled to the at least one data storage device and network input and output interface, the method comprising: using the network input and output interface, receiving at least one query from a respondent or co-respondent via the network; in response to the at least one query, using the one or more processors, accessing at least one data storage device and selecting a plurality of return queries; using the network input and output interface, transmitting the plurality of return queries to the respondent or co-respondent via the network; using the network input and output interface, receiving a plurality of responses to the return queries from the respondent or co-respondent via the network; using the one or more processors, generating a digital filter from each plurality of responses to the return queries to form a plurality of digital filters; using the one or more processors, searching the at least one data storage device for corresponding pluralities of responses to the return queries from one or more co-respondents or respondents, respectively; using the one or more processors, comparatively pair-wise scoring the plurality of responses to the return queries against the corresponding pluralities of responses to the return queries by using the plurality of digital filters to provide a two-stage filtering of the search results through both a respondent digital filter of a selected respondent and a co-respondent digital filter of a selected co-respondent, of the plurality of digital filters, to form a plurality of pair-wise alignment scores for a plurality of respondent and co-respondent combinations; using the one or more processors, sorting and ranking the plurality of respondent and co-respondent combinations according to the plurality of pair-wise alignment scores; and using the one or more processors, outputting a listing of the sorted and ranked respondents or co-respondents to form the personalized network search results and search result rankings.
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19. A computer server-implemented method for personalization of network search results and search result rankings, the computer server comprising a network input and output interface, at least one data storage device, and one or more processors coupled to the at least one data storage device and network input and output interface, the method comprising: using the network input and output interface, receiving at least one query from a respondent or co-respondent via the network; in response to the at least one query, using the one or more processors, accessing at least one data storage device and selecting a plurality of return queries; using the network input and output interface, transmitting the plurality of return queries to the respondent or co-respondent via the network; using the network input and output interface, receiving a plurality of responses to the return queries from the respondent or co-respondent via the network; using the one or more processors, generating a digital filter from each plurality of responses to the return queries to form a plurality of digital filters; using the one or more processors, searching the at least one data storage device for corresponding pluralities of responses to the return queries from one or more co-respondents or respondents, respectively; using the one or more processors, comparatively pair-wise scoring the plurality of responses to the return queries against the corresponding pluralities of responses to the return queries by using the plurality of digital filters to provide a two-stage filtering of the search results through both a respondent digital filter of a selected respondent and a co-respondent digital filter of a selected co-respondent, of the plurality of digital filters, to form a plurality of pair-wise alignment scores for a plurality of respondent and co-respondent combinations; using the one or more processors, sorting and ranking the plurality of respondent and co-respondent combinations according to the plurality of pair-wise alignment scores; and using the one or more processors, outputting a listing of the sorted and ranked respondents or co-respondents to form the personalized network search results and search result rankings. 26. The computer server-implemented method of claim 19 , further comprising: using the one or more processors, providing the two-stage filtering by comparing a selected combination of respondent and co-respondent digital filters, of the plurality of digital filters, to generate the pair-wise alignment score for the selected respondent and co-respondent combination.
| 0.548465 |
1. A method of synchronizing bookmarks comprising: receiving a request to save a first bookmark identifying a first web document in a first mode, the first bookmark received from a first browser executing in the first mode, the first mode being one of a visual mode and a voice mode; receiving, from the first browser, the first bookmark comprising data indicative of the first web document; storing the first bookmark in a bookmark repository on a multimodal platform, the bookmark repository operable for storing one or more bookmarks in a multimodal format and accessible to a plurality of browsers regardless of whether the browsers are executing in the visual or voice mode; receiving, from a second browser executing in a second mode, the second mode being one of the visual or voice mode, a request to access the first bookmark; linking the first bookmark with a second web document in the second mode containing substantially equivalent content of the first web document, the second web document compatible with the second browser based on a relationship between the first web document and the second web document; and sending a second bookmark identifying the second web document to the second browser, wherein the second browser executing in the second mode is operable to navigate to the second web document using the second bookmark.
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1. A method of synchronizing bookmarks comprising: receiving a request to save a first bookmark identifying a first web document in a first mode, the first bookmark received from a first browser executing in the first mode, the first mode being one of a visual mode and a voice mode; receiving, from the first browser, the first bookmark comprising data indicative of the first web document; storing the first bookmark in a bookmark repository on a multimodal platform, the bookmark repository operable for storing one or more bookmarks in a multimodal format and accessible to a plurality of browsers regardless of whether the browsers are executing in the visual or voice mode; receiving, from a second browser executing in a second mode, the second mode being one of the visual or voice mode, a request to access the first bookmark; linking the first bookmark with a second web document in the second mode containing substantially equivalent content of the first web document, the second web document compatible with the second browser based on a relationship between the first web document and the second web document; and sending a second bookmark identifying the second web document to the second browser, wherein the second browser executing in the second mode is operable to navigate to the second web document using the second bookmark. 7. The method of claim 1 , wherein the first bookmark specifies a preferred mode for interacting with the second web document, further comprising, upon re-directing and the second browser is directed to the second web document operating in the mode specified in the first bookmark.
| 0.5 |
7. The system of claim 1 , further comprising: one or more status data structures defining a status change of one or more of the nodes, wherein the one or more status data structures define one or more configuration changes that are implemented to change the service offering provided from a first offering to a second offering; and one or more status processes that comprise steps that are performed to change the configuration defined in the respective status data structure to implement the change from the first offering to the second offering for a user.
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7. The system of claim 1 , further comprising: one or more status data structures defining a status change of one or more of the nodes, wherein the one or more status data structures define one or more configuration changes that are implemented to change the service offering provided from a first offering to a second offering; and one or more status processes that comprise steps that are performed to change the configuration defined in the respective status data structure to implement the change from the first offering to the second offering for a user. 9. The system of claim 7 , wherein the status change is a resource change, wherein the status data structure defines physical network assets to be changed for providing the service defined by second service offering node; and a status process configured to perform one or more functions to implement the changes to the respective physical network resources that are provisioned.
| 0.944347 |
9. The method of claim 1 , wherein generating the first voice activity indicator value includes normalizing a function of the difference between the first value and the second value.
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9. The method of claim 1 , wherein generating the first voice activity indicator value includes normalizing a function of the difference between the first value and the second value. 10. The method of claim 9 , wherein normalizing the difference between the first value and the second value comprises one of: dividing the difference by a function of the sum of the first value and the second value; dividing the difference by a function of an integral value of the spectrum amplitude of the audible signal over a first frequency range that includes the candidate pitch.
| 0.873939 |
1. A method for supporting input of one or more execution parameters of predetermined software in an input field, comprising: receiving input of a text character string including one or more execution parameters in the input field displayed on a display device; determining a selection type in response to a user selection of a part of the text character string; displaying on the display device one or more execution options of the execution parameters depending on the determined selection type, where a user can select one of the one or more execution options in response to a selection of a part of said text character string by the user, said one or more execution options displayed varying according to the type of selection of the part of said text character string; and in response to the user selection of a desired execution option, transforming said text character string to include the desired execution option selected and displaying the transformed text character string on the display device, wherein said predetermined software is a search engine, said text character string represents a search condition, and said execution options are search options for said search engine and wherein said search options include search field specification, wild card, fuzzy search, proximity search, range search, search term boosting, Boolean operator, grouping and field grouping.
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1. A method for supporting input of one or more execution parameters of predetermined software in an input field, comprising: receiving input of a text character string including one or more execution parameters in the input field displayed on a display device; determining a selection type in response to a user selection of a part of the text character string; displaying on the display device one or more execution options of the execution parameters depending on the determined selection type, where a user can select one of the one or more execution options in response to a selection of a part of said text character string by the user, said one or more execution options displayed varying according to the type of selection of the part of said text character string; and in response to the user selection of a desired execution option, transforming said text character string to include the desired execution option selected and displaying the transformed text character string on the display device, wherein said predetermined software is a search engine, said text character string represents a search condition, and said execution options are search options for said search engine and wherein said search options include search field specification, wild card, fuzzy search, proximity search, range search, search term boosting, Boolean operator, grouping and field grouping. 3. The method according to claim 1 , further comprising: transmitting the one or more parameters and execution options included in said transformed text character string to a server that executes said predetermined software.
| 0.532367 |
9. An article of manufacture including a non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by a computing device, cause the computing device to perform operations comprising: determining a reference transcription of a reference utterance, wherein the reference transcription is derived using a strong acoustic model, a language model and a weight vector, and wherein the reference transcription has a confidence level of at least 70%; based on the reference transcription having the confidence level of at least 70%, determining a secondary transcription of the reference utterance, wherein the secondary transcription is derived using a weak acoustic model, the language model and the weight vector, wherein the secondary transcription has a secondary confidence level, wherein the weak acoustic model has a higher error rate than the strong acoustic model, and wherein the secondary transcription is different from the reference transcription; and based on the secondary transcription being different from the reference transcription, updating the weight vector so that transcribing the reference utterance using the weak acoustic model, the language model and the updated weight vector results in a tertiary transcription with a tertiary confidence level that is greater than the secondary confidence level.
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9. An article of manufacture including a non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by a computing device, cause the computing device to perform operations comprising: determining a reference transcription of a reference utterance, wherein the reference transcription is derived using a strong acoustic model, a language model and a weight vector, and wherein the reference transcription has a confidence level of at least 70%; based on the reference transcription having the confidence level of at least 70%, determining a secondary transcription of the reference utterance, wherein the secondary transcription is derived using a weak acoustic model, the language model and the weight vector, wherein the secondary transcription has a secondary confidence level, wherein the weak acoustic model has a higher error rate than the strong acoustic model, and wherein the secondary transcription is different from the reference transcription; and based on the secondary transcription being different from the reference transcription, updating the weight vector so that transcribing the reference utterance using the weak acoustic model, the language model and the updated weight vector results in a tertiary transcription with a tertiary confidence level that is greater than the secondary confidence level. 14. The article of manufacture of claim 9 , wherein a first feature vector characterizes the reference transcription, wherein a second feature vector characterizes the secondary transcription, and wherein updating the weight vector comprises adding the first feature vector to the weight vector and subtracting the second feature vector from the weight vector.
| 0.612239 |
1. A method for semantic attribution of a request, said method implemented by a processor of a computer system, said method comprising: said processor receiving source data statements for the request; said processor receiving a selection of a domain for the received source data statements; said processor semantically analyzing the received source data statements, said semantically analyzing comprising matching elements in the received source data statements to respective one or more entries in an ontology associated with the selected domain, wherein the ontology comprises items and relationships that define the selected domain, and wherein each element in the received source data statements is a word or a phrase; after said matching is performed for one matched element of the matched elements, said processor determining whether completeness is indicated for the one matched element; responsive to determining that completeness is indicated for the one matched element, said processor fulfilling completeness for the one matched element; said processor assigning the one or more entries to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries; said processor saving the annotated elements with the respective annotations; and said processor using the annotations to generate a search query for the request.
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1. A method for semantic attribution of a request, said method implemented by a processor of a computer system, said method comprising: said processor receiving source data statements for the request; said processor receiving a selection of a domain for the received source data statements; said processor semantically analyzing the received source data statements, said semantically analyzing comprising matching elements in the received source data statements to respective one or more entries in an ontology associated with the selected domain, wherein the ontology comprises items and relationships that define the selected domain, and wherein each element in the received source data statements is a word or a phrase; after said matching is performed for one matched element of the matched elements, said processor determining whether completeness is indicated for the one matched element; responsive to determining that completeness is indicated for the one matched element, said processor fulfilling completeness for the one matched element; said processor assigning the one or more entries to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries; said processor saving the annotated elements with the respective annotations; and said processor using the annotations to generate a search query for the request. 5. The method of claim 1 , wherein the one or more entries of the annotation that annotates one matched element of the matched elements consists of a plurality of entries.
| 0.570864 |
1. A method for providing information associated with documents, comprising: receiving the documents, wherein the documents include images; determining a first set of editing instructions and classification information associated with the documents using data-processing software, wherein the data-processing software determines the first set of editing instructions and classification information using at least one of a spatial filter or a frequency filter, and wherein the classification information includes attributes associated with at least some of the documents; providing the images and the first set of editing instructions and classification information to a group of individuals; receiving a second set of editing instructions and classification information associated with the documents, wherein the second set of editing instructions and classification information are generated by the group of individuals and include modifications and additions to the first set of editing instructions and classification information, and wherein the second set of editing instructions and classification information include subjective comments about content in the document; storing the documents and the second set of editing instructions and the classification information in a non-transitory computer-readable medium, wherein the second set of editing instructions and the classification information facilitate searches for the content in the stored documents; receiving a request for information that is associated with a time-varying subjective value; identifying the information by searching through the stored documents using the second set of editing instructions and the classification information; and providing the information in response to the request, wherein the information includes multiple versions of at least one of the documents, and wherein the multiple versions are, at least in part, based on different editing instructions and classification information in the second set of editing instructions and classification information from different individuals in the group of individuals, which include different identified subjective content, thereby providing different images that reflect the time-varying subjective value.
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1. A method for providing information associated with documents, comprising: receiving the documents, wherein the documents include images; determining a first set of editing instructions and classification information associated with the documents using data-processing software, wherein the data-processing software determines the first set of editing instructions and classification information using at least one of a spatial filter or a frequency filter, and wherein the classification information includes attributes associated with at least some of the documents; providing the images and the first set of editing instructions and classification information to a group of individuals; receiving a second set of editing instructions and classification information associated with the documents, wherein the second set of editing instructions and classification information are generated by the group of individuals and include modifications and additions to the first set of editing instructions and classification information, and wherein the second set of editing instructions and classification information include subjective comments about content in the document; storing the documents and the second set of editing instructions and the classification information in a non-transitory computer-readable medium, wherein the second set of editing instructions and the classification information facilitate searches for the content in the stored documents; receiving a request for information that is associated with a time-varying subjective value; identifying the information by searching through the stored documents using the second set of editing instructions and the classification information; and providing the information in response to the request, wherein the information includes multiple versions of at least one of the documents, and wherein the multiple versions are, at least in part, based on different editing instructions and classification information in the second set of editing instructions and classification information from different individuals in the group of individuals, which include different identified subjective content, thereby providing different images that reflect the time-varying subjective value. 3. The method of claim 1 , wherein the group of individuals has a professional relationship with an organization that provides a system that receives the documents and determines the first set of editing instructions and classification information.
| 0.573667 |
9. The dialog system of claim 4 , wherein the plan script defines activities via tags that include an element for selecting between various activities depending on a newest node included in the dialog move tree.
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9. The dialog system of claim 4 , wherein the plan script defines activities via tags that include an element for selecting between various activities depending on a newest node included in the dialog move tree. 10. The dialog system of claim 9 , wherein the tags are XML tags that hierarchically define the activities.
| 0.937651 |
9. A computer readable storage device comprising computer executable instructions that when executed by one or more processors cause one or more computing devices to perform a method comprising: compiling visual information and textual information from a plurality of images; extracting the visual information from the plurality of images by using a gray block methodology; reducing the visual information by employing a projection matrix; hashing the reduced visual information; clustering the plurality of images based at least in part on a hash value to create image clusters; building one or more statistical language models based at least in part on the image clusters; and annotating a personal image by selecting words with a maximum joint probability with the personal image.
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9. A computer readable storage device comprising computer executable instructions that when executed by one or more processors cause one or more computing devices to perform a method comprising: compiling visual information and textual information from a plurality of images; extracting the visual information from the plurality of images by using a gray block methodology; reducing the visual information by employing a projection matrix; hashing the reduced visual information; clustering the plurality of images based at least in part on a hash value to create image clusters; building one or more statistical language models based at least in part on the image clusters; and annotating a personal image by selecting words with a maximum joint probability with the personal image. 13. A computer readable storage device as recited in claim 9 , wherein the one or more statistical language models is a unigram model that calculates a probability that a word is associated with the personal image based at least in part on a visual similarity between the personal image and the image clusters and a prior probability of the image clusters.
| 0.5 |
21. A system for coreference resolution comprising: memory which stores a set of document clusters, each cluster in the set comprising a set of text documents; an entity extractor which is configured for identifying instances of each of a set of candidate named entities in the document clusters, the instances of a respective candidate named entity being text elements; a socio-temporal features extractor which is configured for computing at least one socio-temporal feature for each of a set of pairs of the candidate named entities, based on event profiles for the candidate named entities in each pair, the event profiles each comprising an optionally normalized vector of size k, where k is the number of document clusters in the set, in which each index of the vector is based on the occurrences of the identified instances of the candidate named entity in a respective one of the k clusters; a prediction component which is configured for outputting a similarity score for each pair of the candidate named entities based on the at least one socio-temporal feature; a merging component which is configured for merging the candidate named entities of each pair into a common real named entity, when the computed similarity score meets a predetermined threshold; and a processor which implements at least one of the socio-temporal features extractor and the prediction component.
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21. A system for coreference resolution comprising: memory which stores a set of document clusters, each cluster in the set comprising a set of text documents; an entity extractor which is configured for identifying instances of each of a set of candidate named entities in the document clusters, the instances of a respective candidate named entity being text elements; a socio-temporal features extractor which is configured for computing at least one socio-temporal feature for each of a set of pairs of the candidate named entities, based on event profiles for the candidate named entities in each pair, the event profiles each comprising an optionally normalized vector of size k, where k is the number of document clusters in the set, in which each index of the vector is based on the occurrences of the identified instances of the candidate named entity in a respective one of the k clusters; a prediction component which is configured for outputting a similarity score for each pair of the candidate named entities based on the at least one socio-temporal feature; a merging component which is configured for merging the candidate named entities of each pair into a common real named entity, when the computed similarity score meets a predetermined threshold; and a processor which implements at least one of the socio-temporal features extractor and the prediction component. 22. The system of claim 21 , wherein the prediction component is configured for inputting the at least one socio-temporal feature to a classifier which has been trained to output a similarity score for a pair of candidate named entities based on the socio-temporal feature.
| 0.528037 |
1. A system responsive to a user generated natural language speech utterance, comprising: an agent architecture that includes a plurality of domain agents, each of the plurality of domain agents being an autonomous executable configured to receive, process, and respond to requests associated with a respective context; a parser configured to determine a context for one or more keywords contained in the utterance and to determine a meaning of the utterance based on the determined context, wherein the parser selects at least one of the plurality of domain agents based on the determined meaning, wherein the selected domain agent is configured to receive, process, and respond to requests associated with the determined context; an event manager configured to coordinate interaction between the parser and the agent architecture; and an update manager that enables the user to purchase one or more domain agents from a third party on a one-time or subscription basis.
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1. A system responsive to a user generated natural language speech utterance, comprising: an agent architecture that includes a plurality of domain agents, each of the plurality of domain agents being an autonomous executable configured to receive, process, and respond to requests associated with a respective context; a parser configured to determine a context for one or more keywords contained in the utterance and to determine a meaning of the utterance based on the determined context, wherein the parser selects at least one of the plurality of domain agents based on the determined meaning, wherein the selected domain agent is configured to receive, process, and respond to requests associated with the determined context; an event manager configured to coordinate interaction between the parser and the agent architecture; and an update manager that enables the user to purchase one or more domain agents from a third party on a one-time or subscription basis. 31. The system according to claim 1 , further comprising a speech recognition engine that recognizes words and phrases contained in the received user utterance using information in one or more dictionary and phrase tables, wherein the parser examines the recognized words and phrases to identify the one or more keywords.
| 0.504202 |
16. The command processing system of claim 14 , wherein the first set of verbal commands comprise a command for identifying or setting the point-of-interest for the navigation operations.
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16. The command processing system of claim 14 , wherein the first set of verbal commands comprise a command for identifying or setting the point-of-interest for the navigation operations. 17. The command processing system of claim 16 , wherein the second set of verbal commands is associated with operating an entertainment system, a climate control system or a diagnostic system.
| 0.938442 |
8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a query; obtaining search results including publication search results responsive to the query, wherein each publication search result refers to a respective book; determining that a score for a highest-ranked publication search result satisfies a threshold relative to respective scores of one or more other publication search results to be provided in response to the query, wherein the highest-ranked publication search result refers to a book; in response to determining that the score for the highest-ranked publication search result satisfies the threshold relative to respective scores of the other publication search results, wherein the score for the highest ranked publication search result satisfies the threshold if the score is at least a threshold multiple of a second score for a second publication search result ranked second in a ranked order of the publication search results, generating a rich result for the highest-ranked publication search result, wherein the rich result for the highest-ranked publication search result comprises more elements of data than any of the other publication search results to be provided in response to the query, wherein the rich result for the highest-ranked publication search result comprises data from one or more web resources that refer to the book, and wherein the elements of data for the rich result comprise a title of the book, an author of the book, and a link to a website related to the book; and providing the rich result and the one or more other publication search results in response to the query.
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8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a query; obtaining search results including publication search results responsive to the query, wherein each publication search result refers to a respective book; determining that a score for a highest-ranked publication search result satisfies a threshold relative to respective scores of one or more other publication search results to be provided in response to the query, wherein the highest-ranked publication search result refers to a book; in response to determining that the score for the highest-ranked publication search result satisfies the threshold relative to respective scores of the other publication search results, wherein the score for the highest ranked publication search result satisfies the threshold if the score is at least a threshold multiple of a second score for a second publication search result ranked second in a ranked order of the publication search results, generating a rich result for the highest-ranked publication search result, wherein the rich result for the highest-ranked publication search result comprises more elements of data than any of the other publication search results to be provided in response to the query, wherein the rich result for the highest-ranked publication search result comprises data from one or more web resources that refer to the book, and wherein the elements of data for the rich result comprise a title of the book, an author of the book, and a link to a website related to the book; and providing the rich result and the one or more other publication search results in response to the query. 15. The system of claim 8 , wherein the elements of data for the rich result comprise a snippet of the book or a summary of the book.
| 0.591183 |
1. A method of analyzing a network data stream comprising: capturing frames from a network data stream; parsing said captured frames using a protocol parser having a data structure, stored on a computer-readable medium, that includes a data type that identifies the protocol to generate parsed frames, wherein the protocol parser is created by interpreting a script that describes the format of the protocol and that is written in a language describing network protocols; organizing said parsed frames into conversations; and substituting a data structure size in said protocol parser for a selected data structure.
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1. A method of analyzing a network data stream comprising: capturing frames from a network data stream; parsing said captured frames using a protocol parser having a data structure, stored on a computer-readable medium, that includes a data type that identifies the protocol to generate parsed frames, wherein the protocol parser is created by interpreting a script that describes the format of the protocol and that is written in a language describing network protocols; organizing said parsed frames into conversations; and substituting a data structure size in said protocol parser for a selected data structure. 4. The method of analyzing a network data stream claimed in claim 1 including debugging said interpreted script to determine if said script has errors.
| 0.689504 |
8. The method of claim 1 , further comprising: receiving a portion of the search request as an unstructured input; comparing the portion of the search request with the tokens; and suggesting some of the tokens for replacing the portion of the search request.
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8. The method of claim 1 , further comprising: receiving a portion of the search request as an unstructured input; comparing the portion of the search request with the tokens; and suggesting some of the tokens for replacing the portion of the search request. 9. The method of claim 8 , further comprising: detecting selection of one of the tokens; replacing the portion of the search request with the selected one of the tokens; and generating the structured query based on the selected one of the tokens.
| 0.870291 |
6. A memory device having instructions stored thereon that, in response to execution by a processing device, cause the processing device to perform operations comprising: identifying a first plurality of text strings of a first data source of a first web server; combining the text strings of the first plurality into a first entity comprising first attributes each of which corresponds to a respective one of the text strings of the first plurality; identifying a second plurality of text strings of a second data source of a second web server that is different than the first web server; combining the text strings of the second plurality into a second entity that is different than the first entity, the second entity comprising second attributes each of which corresponds to a respective one of the text strings of the second plurality; generating a database that includes the first and second entities; responsive to receiving a query comprising a combination of attribute selections, performing a search using the generated database that includes the first and second entities to select a subset of the first and second entities that corresponds to the combination of attribute selections; and causing the entity of the selected subset to be presented on a user terminal from which the query originated.
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6. A memory device having instructions stored thereon that, in response to execution by a processing device, cause the processing device to perform operations comprising: identifying a first plurality of text strings of a first data source of a first web server; combining the text strings of the first plurality into a first entity comprising first attributes each of which corresponds to a respective one of the text strings of the first plurality; identifying a second plurality of text strings of a second data source of a second web server that is different than the first web server; combining the text strings of the second plurality into a second entity that is different than the first entity, the second entity comprising second attributes each of which corresponds to a respective one of the text strings of the second plurality; generating a database that includes the first and second entities; responsive to receiving a query comprising a combination of attribute selections, performing a search using the generated database that includes the first and second entities to select a subset of the first and second entities that corresponds to the combination of attribute selections; and causing the entity of the selected subset to be presented on a user terminal from which the query originated. 7. The memory device of claim 6 , wherein at least one of the first attributes is different than at least one of the second attributes.
| 0.565633 |
15. The method of claim 1, further comprising: creating an association ween said front panel object and said configured graphical code portion; locking said association between said front panel object and said configured graphical code portion, wherein said locking prevents user editing of said configured graphical code portion.
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15. The method of claim 1, further comprising: creating an association ween said front panel object and said configured graphical code portion; locking said association between said front panel object and said configured graphical code portion, wherein said locking prevents user editing of said configured graphical code portion. 16. The method of claim 15, further comprising: unlocking said association between said front panel object and said configured graphical code portion in response to user input after said locking, wherein said unlocking removes said association between said front panel object and said configured graphical code portion; directly changing said configured graphical code portion in response to user input after said unlocking.
| 0.864706 |
20. The computing device of claim 19 , further comprising a document analysis module that parses documents within the collection and generates tokens.
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20. The computing device of claim 19 , further comprising a document analysis module that parses documents within the collection and generates tokens. 21. The computing device of claim 20 , further comprising an entity recognition module that identifies attributes from the generated tokens and provides the unique identifiers for each of the identified attributes.
| 0.921014 |
1. A computer system, the computer system comprising: one or more hardware processors; system memory coupled to the one or more hardware processors, the system memory storing instructions that are executable by the one or more hardware processors; and the one or more hardware processors executing the instructions stored in the system memory to optimize a query, including the following: access a query plan search space for a query of a distributed database, the query plan search space including a hierarchical structure of a root group of logical operators, one or more intermediate groups of logical operators, and one or more leaf groups of logical operators; and formulate an annotated query plan search space for the query, including: identify a distribution property for a child group of at least one other group, the at least one other group selected from among: the root group and the one or more intermediate groups, the distribution property indicating type of distribution relevant to the child group, the distribution property identifying a column that data for a parent group is distributed on, the parent group being above the child group in the hierarchical structure; and annotate the child group with the type of distribution by attaching an indication of the identified column to the child group to propagate the identified type of distribution to the child group for use in query plan pruning.
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1. A computer system, the computer system comprising: one or more hardware processors; system memory coupled to the one or more hardware processors, the system memory storing instructions that are executable by the one or more hardware processors; and the one or more hardware processors executing the instructions stored in the system memory to optimize a query, including the following: access a query plan search space for a query of a distributed database, the query plan search space including a hierarchical structure of a root group of logical operators, one or more intermediate groups of logical operators, and one or more leaf groups of logical operators; and formulate an annotated query plan search space for the query, including: identify a distribution property for a child group of at least one other group, the at least one other group selected from among: the root group and the one or more intermediate groups, the distribution property indicating type of distribution relevant to the child group, the distribution property identifying a column that data for a parent group is distributed on, the parent group being above the child group in the hierarchical structure; and annotate the child group with the type of distribution by attaching an indication of the identified column to the child group to propagate the identified type of distribution to the child group for use in query plan pruning. 3. The computer system of claim 1 , wherein the one or more hardware processors executing the instructions to identify a distribution property comprises the one or more hardware processors executing the instructions to identify a distribution property that indicates a type of distribution for a top operator.
| 0.592113 |
1. A computer implemented method of automatically generating a radiation treatment plan for a patient, said method comprising: accessing patient information pertaining to planning a radiation treatment for said patient; automatically selecting one or more predictive models based on said patient information in accordance with a hierarchical model comprising a plurality of predictive models arranged in a hierarchy, wherein a respective predictive model of said plurality of predictive models is established based on training data and operable to generate a radiation treatment prediction, wherein said hierarchical model is automatically generated through a machine training process, and wherein said respective predictive model represents a correlation between a set of input variables representing patient information features and a set of output variables; processing said patient information in accordance with said one or more predictive models; and outputting one or more radiation treatment predictions.
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1. A computer implemented method of automatically generating a radiation treatment plan for a patient, said method comprising: accessing patient information pertaining to planning a radiation treatment for said patient; automatically selecting one or more predictive models based on said patient information in accordance with a hierarchical model comprising a plurality of predictive models arranged in a hierarchy, wherein a respective predictive model of said plurality of predictive models is established based on training data and operable to generate a radiation treatment prediction, wherein said hierarchical model is automatically generated through a machine training process, and wherein said respective predictive model represents a correlation between a set of input variables representing patient information features and a set of output variables; processing said patient information in accordance with said one or more predictive models; and outputting one or more radiation treatment predictions. 9. The computer implemented method of claim 1 , wherein each of said one or more radiation treatment predictions comprises a predicted achievable dose distribution.
| 0.711382 |
9. A non-transitory computer-readable storage medium comprising instructions that, when executed by a processor, perform a method for generating roles for a platform, the method comprising: identifying, by a computer system, a set of first user roles that are used to control access to a set of first application programs, wherein: (i) the first application programs are implemented on a first computer platform in which user access to the first application programs is provided through a laptop or personal computer, and (ii) each user role in the set of first user roles is assigned (a) multiple respective users, and (b) one or more of the first application programs to which the multiple respective users have access due to their user role assignment; generating, by the computer system, a set of second user roles that are to be used to control access to a set of second application programs, by generating a corresponding second user role for each user role in the set of first user roles, wherein: (i) the second application programs are implemented on a second computer platform that is a mobile device platform in which user access to the second application programs is provided through use of a particular type of mobile device, and the second application programs are each a mobile application for the mobile device platform, (ii) each user role in the set of second user roles will be assigned multiple respective users, and (iii) each user role in the set of second user roles corresponds to a corresponding user role in the set of first user roles, wherein when the set of second user roles are generated, assignments do not exist between the set of second user roles and the second application programs; accessing, by the computer system, first metadata that is assigned to the set of first user roles; accessing, by the computer system, second metadata that is assigned to the second application programs; comparing, by the computer system, the first metadata that is assigned to the set of first user roles to the second metadata that is assigned to the second application programs to identify a matching portion of the first metadata that matches a matching portion of the second metadata; assigning, by the computer system, a second matching application program from the set of second application programs to a second matching user role from the set of second user roles, due to the computer system having identified that: (a) the matching portion of the first metadata matches the matching portion of the second metadata, (b) the matching portion of the first metadata is assigned to a first matching user role from among the set of first user roles, (c) the first matching user role corresponds to the second matching user role, and (d) the matching portion of the second metadata is assigned to the second matching application program.
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9. A non-transitory computer-readable storage medium comprising instructions that, when executed by a processor, perform a method for generating roles for a platform, the method comprising: identifying, by a computer system, a set of first user roles that are used to control access to a set of first application programs, wherein: (i) the first application programs are implemented on a first computer platform in which user access to the first application programs is provided through a laptop or personal computer, and (ii) each user role in the set of first user roles is assigned (a) multiple respective users, and (b) one or more of the first application programs to which the multiple respective users have access due to their user role assignment; generating, by the computer system, a set of second user roles that are to be used to control access to a set of second application programs, by generating a corresponding second user role for each user role in the set of first user roles, wherein: (i) the second application programs are implemented on a second computer platform that is a mobile device platform in which user access to the second application programs is provided through use of a particular type of mobile device, and the second application programs are each a mobile application for the mobile device platform, (ii) each user role in the set of second user roles will be assigned multiple respective users, and (iii) each user role in the set of second user roles corresponds to a corresponding user role in the set of first user roles, wherein when the set of second user roles are generated, assignments do not exist between the set of second user roles and the second application programs; accessing, by the computer system, first metadata that is assigned to the set of first user roles; accessing, by the computer system, second metadata that is assigned to the second application programs; comparing, by the computer system, the first metadata that is assigned to the set of first user roles to the second metadata that is assigned to the second application programs to identify a matching portion of the first metadata that matches a matching portion of the second metadata; assigning, by the computer system, a second matching application program from the set of second application programs to a second matching user role from the set of second user roles, due to the computer system having identified that: (a) the matching portion of the first metadata matches the matching portion of the second metadata, (b) the matching portion of the first metadata is assigned to a first matching user role from among the set of first user roles, (c) the first matching user role corresponds to the second matching user role, and (d) the matching portion of the second metadata is assigned to the second matching application program. 13. The non-transitory computer-readable storage medium of claim 9 , wherein the method further comprises automatically detecting, by the computer system, the first metadata from documents assigned to the set of first user roles, and as a result assigning, by the computer system, the first metadata to the set of first user roles.
| 0.521858 |
9. The computer program product of claim 8 , wherein the overlay index includes a posting list for each term in the specified context, wherein the posting list specifies: (i) each occurrence of the specified context and (ii) the position of the respective occurrence of the specified context, in the plurality of documents.
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9. The computer program product of claim 8 , wherein the overlay index includes a posting list for each term in the specified context, wherein the posting list specifies: (i) each occurrence of the specified context and (ii) the position of the respective occurrence of the specified context, in the plurality of documents. 10. The computer program product of claim 9 , wherein the term index includes a posting list for each term used in the plurality of documents, wherein the plurality of documents further includes: (i) a first document having, inside the specified context, an occurrence of the first search term and no occurrences of the second search term and, outside the specified context, an occurrence of the second search term and no occurrences of the first search term (ii) a second document having, inside the specified context, respective occurrences of the first and second search terms and, outside the specified context, no occurrences of any of the first and second search terms.
| 0.835137 |
1. A method performed by one or more processors associated with one or more server devices, the method comprising: receiving, at the one or more server devices, a local search request that includes one or more query terms and a geographic identification; identifying, by one or more processors associated with the one or more server devices, a local search listing based on the local search request; identifying, by one or more processors associated with the one or more server devices, a title associated with the identified local search listing; assigning, by by one or more processors associated with the one or more server devices, a webscore for the identified local search listing, where the webscore is determined from a number of search results returned by querying a search engine with the title when a size of the title is greater than a threshold, and the webscore is determined from the number of search results returned by querying the search engine with the title and the geographic identification when the size of the title is less than the threshold; ranking, by one or more processors associated with the one or more server devices, the identified local search listing based on the assigned webscore; and providing, by the one or more server devices, the ranked identified local search listing.
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1. A method performed by one or more processors associated with one or more server devices, the method comprising: receiving, at the one or more server devices, a local search request that includes one or more query terms and a geographic identification; identifying, by one or more processors associated with the one or more server devices, a local search listing based on the local search request; identifying, by one or more processors associated with the one or more server devices, a title associated with the identified local search listing; assigning, by by one or more processors associated with the one or more server devices, a webscore for the identified local search listing, where the webscore is determined from a number of search results returned by querying a search engine with the title when a size of the title is greater than a threshold, and the webscore is determined from the number of search results returned by querying the search engine with the title and the geographic identification when the size of the title is less than the threshold; ranking, by one or more processors associated with the one or more server devices, the identified local search listing based on the assigned webscore; and providing, by the one or more server devices, the ranked identified local search listing. 2. The method of claim 1 , further comprising scaling the webscore for the identified local search listing.
| 0.693619 |
15. An article comprising one or more computer-readable data storage media storing program code operable to cause one or more machines to perform operations, the operations comprising: identifying, in a machine-readable index, a first sentence fragment and a second sentence fragment that are both associated with a same first information item, wherein the first information item is an entity name, wherein the machine-readable index comprises a plurality of information items and sentence fragments associated with respective of the information items; in response to identifying that the first sentence fragment and the second sentence fragment are both associated with the same first information item, identifying a paraphrase pair in the first and second sentence fragments; repeating the identifying of the first sentence fragment and the second sentence fragment and the identifying of the paraphrase pair to identify a plurality of paraphrase pairs; and determining a frequency of occurrence value for each of the paraphrase pairs in the plurality of paraphrase pairs, wherein the frequency of occurrence value embodies the frequency at which each paraphrase pair appears in the plurality of paraphrase pairs, wherein the paraphrase pair comprises a first paraphrase and a second paraphrase, the first paraphrase comprises a proper subset of the words in the first sentence fragment, the second paraphrase comprises a proper subset of the words in the second sentence fragment, and the first paraphrase and the second paraphrase are in a same language, have a same or a similar meaning, and are not identical.
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15. An article comprising one or more computer-readable data storage media storing program code operable to cause one or more machines to perform operations, the operations comprising: identifying, in a machine-readable index, a first sentence fragment and a second sentence fragment that are both associated with a same first information item, wherein the first information item is an entity name, wherein the machine-readable index comprises a plurality of information items and sentence fragments associated with respective of the information items; in response to identifying that the first sentence fragment and the second sentence fragment are both associated with the same first information item, identifying a paraphrase pair in the first and second sentence fragments; repeating the identifying of the first sentence fragment and the second sentence fragment and the identifying of the paraphrase pair to identify a plurality of paraphrase pairs; and determining a frequency of occurrence value for each of the paraphrase pairs in the plurality of paraphrase pairs, wherein the frequency of occurrence value embodies the frequency at which each paraphrase pair appears in the plurality of paraphrase pairs, wherein the paraphrase pair comprises a first paraphrase and a second paraphrase, the first paraphrase comprises a proper subset of the words in the first sentence fragment, the second paraphrase comprises a proper subset of the words in the second sentence fragment, and the first paraphrase and the second paraphrase are in a same language, have a same or a similar meaning, and are not identical. 18. The article of claim 15 , wherein the operations further comprise: identifying a subset of the plurality of paraphrase pairs having a frequency of occurrence value above a threshold; and adding the subset of the plurality of paraphrase pairs to a machine-readable data collection.
| 0.568311 |
1. An input recognition system comprising: a keypad comprising a set of keys that includes a predefined hotkey; a hotkey detection component that identifies a single actuation of the predefined hotkey as indicating the start of a first sequence of key activations corresponding to a first pattern that is being input into the keypad for recognizing a first character, and two actuations of the predefined hotkey as indicating an end of the first sequence of key activations; a timer configured to cooperate with the hotkey detection component for detecting a pattern boundary that distinguishes the first sequence of key activations corresponding to the first pattern from a second sequence of key activations corresponding to a second pattern when a user fails to indicate a completion of the first sequence of key activations; an input component that acquires input data corresponding to said first sequence of key activations; and an analysis component that receives the input data from the input component and recognizes the first character based on interpreting said first pattern as corresponding to a visual representation of the first character superimposed over the set of keys.
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1. An input recognition system comprising: a keypad comprising a set of keys that includes a predefined hotkey; a hotkey detection component that identifies a single actuation of the predefined hotkey as indicating the start of a first sequence of key activations corresponding to a first pattern that is being input into the keypad for recognizing a first character, and two actuations of the predefined hotkey as indicating an end of the first sequence of key activations; a timer configured to cooperate with the hotkey detection component for detecting a pattern boundary that distinguishes the first sequence of key activations corresponding to the first pattern from a second sequence of key activations corresponding to a second pattern when a user fails to indicate a completion of the first sequence of key activations; an input component that acquires input data corresponding to said first sequence of key activations; and an analysis component that receives the input data from the input component and recognizes the first character based on interpreting said first pattern as corresponding to a visual representation of the first character superimposed over the set of keys. 10. The system of claim 1 , wherein the analysis component includes a prognostic component that predicts said pattern boundary based at least in part on historical information, and wherein the prognostic component interacts with the timer component to learn user input habits to facilitate identification of said first and second sequences.
| 0.5 |
15. One or more non-transitory computer-readable media storing instructions which, when executed by at least one processor, instructing the at least one processor for performing actions comprising: accessing a data structure that includes at least one data element having information entropy equal to at least a threshold information entropy detected in at least one document associated with a software module; during execution of the software module, providing the at least one data element for requesting access to one or more secure features of the software module; determining that the providing of the at least one data element enables the access to the one or more secure features; and designating the at least one data element as sensitive information written into the at least one document.
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15. One or more non-transitory computer-readable media storing instructions which, when executed by at least one processor, instructing the at least one processor for performing actions comprising: accessing a data structure that includes at least one data element having information entropy equal to at least a threshold information entropy detected in at least one document associated with a software module; during execution of the software module, providing the at least one data element for requesting access to one or more secure features of the software module; determining that the providing of the at least one data element enables the access to the one or more secure features; and designating the at least one data element as sensitive information written into the at least one document. 19. The one or more non-transitory computer-readable media of claim 15 , the actions further comprising: modifying the at least one document, including one or more of: deleting the at least one data element from the at least one document; or altering the at least one data element in the at least one document.
| 0.784469 |
1. A method for processing and analyzing content from at least one Website on a communication network, the method comprising steps for: receiving instructions, via a graphical user interface (GUI) executed by a server, to conduct a search for at least one keyword on the communication network; launching a Web crawler, by the server, to search a plurality of Websites for at least one Website having content that includes said at least one keyword; identifying Websites comprising at least one comment container, wherein said comment container includes at least one conversation; creating a unique xpath, by the server, to said at least one comment container of each identified Website of said Websites, wherein the unique xpath comprises an extraction string dynamically generated to identify at least one of how to find comments, the date of a post on the Website, IP address, user name, and location; saving, in a database, the unique xpath created for said at least one comment container of said each identified Website; detecting using the unique xpath at least one conversation that includes the at least one keyword from search of a content of said comment container of said each Website accessible only by said unique xpath; saving only a portion of the content of said comment container from said each Website that includes the at least one keyword along with information associated to each conversation of said identified conversation; assigning, via a server, a categorical topic for said each conversation; assigning, via a server, a sentiment for said each conversation; and generating at least one report, by the server, providing selected information related to said each conversation, along with categorical topic and sentiment for said each conversation, wherein the method is computer implemented, and wherein said assigning the sentiment comprises assigning a positive or negative value along a range, based on the words comprised in the content of the Website.
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1. A method for processing and analyzing content from at least one Website on a communication network, the method comprising steps for: receiving instructions, via a graphical user interface (GUI) executed by a server, to conduct a search for at least one keyword on the communication network; launching a Web crawler, by the server, to search a plurality of Websites for at least one Website having content that includes said at least one keyword; identifying Websites comprising at least one comment container, wherein said comment container includes at least one conversation; creating a unique xpath, by the server, to said at least one comment container of each identified Website of said Websites, wherein the unique xpath comprises an extraction string dynamically generated to identify at least one of how to find comments, the date of a post on the Website, IP address, user name, and location; saving, in a database, the unique xpath created for said at least one comment container of said each identified Website; detecting using the unique xpath at least one conversation that includes the at least one keyword from search of a content of said comment container of said each Website accessible only by said unique xpath; saving only a portion of the content of said comment container from said each Website that includes the at least one keyword along with information associated to each conversation of said identified conversation; assigning, via a server, a categorical topic for said each conversation; assigning, via a server, a sentiment for said each conversation; and generating at least one report, by the server, providing selected information related to said each conversation, along with categorical topic and sentiment for said each conversation, wherein the method is computer implemented, and wherein said assigning the sentiment comprises assigning a positive or negative value along a range, based on the words comprised in the content of the Website. 8. The method of claim 1 , wherein the at least one report comprises a geo-location relating to the origin of the conversations.
| 0.539286 |
5. The method of claim 1 , wherein determining that social annotations are to be displayed in the search results page comprises determining that a knowledge panel is to be displayed in the search results page, the knowledge panel being associated with the at least one topic, the knowledge panel being annotated with the at least one social annotation in the enhanced search results page.
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5. The method of claim 1 , wherein determining that social annotations are to be displayed in the search results page comprises determining that a knowledge panel is to be displayed in the search results page, the knowledge panel being associated with the at least one topic, the knowledge panel being annotated with the at least one social annotation in the enhanced search results page. 6. The method of claim 5 , wherein determining that a knowledge panel is to be displayed comprises identifying content for display in the knowledge panel for a factual entity associated with the knowledge panel, the knowledge panel presenting the identified content in a knowledge panel area alongside at least a portion of the search results.
| 0.861942 |
6. A machine-implemented method for providing a graphical user interface (GUI) for a research system, the method comprising: providing a selectable list of user objectives for a recurring search that identifies documents, from a particular recurring time period, classified as relevant to a set of categories by the research system, wherein a selected user objective comprises a purpose for which the user plans to use the identified documents; providing a categories display area for displaying a set of recommended categories to include in the recurring search based on the selected user objective and an initial set of categories, wherein the set of recommended categories comprises a subset of pre-selected categories most related to the initial set of categories and further categories for selection by the user; after a set of additional categories for the recurring search are selected by the user, providing a filters display area for displaying a set of recommended filters for removing specific types of documents from the recurring search that are otherwise relevant to the selected categories for the recurring search, wherein a first set of selected additional categories results in displaying a first set of recommended filters and a second set of selected additional categories results in displaying a second, different set of recommended filters; and providing a plurality of selectable user interface controls for modifying delivery parameters for the recurring search, wherein a set of the plurality of selectable user interface controls are automatically pre-selected for the user based on an analysis of a plurality of user profile information and user behavior information, wherein email is pre-selected as a medium through which reports are delivered to the user if the user does not log-in to the research system on a recurring basis over a specified time period.
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6. A machine-implemented method for providing a graphical user interface (GUI) for a research system, the method comprising: providing a selectable list of user objectives for a recurring search that identifies documents, from a particular recurring time period, classified as relevant to a set of categories by the research system, wherein a selected user objective comprises a purpose for which the user plans to use the identified documents; providing a categories display area for displaying a set of recommended categories to include in the recurring search based on the selected user objective and an initial set of categories, wherein the set of recommended categories comprises a subset of pre-selected categories most related to the initial set of categories and further categories for selection by the user; after a set of additional categories for the recurring search are selected by the user, providing a filters display area for displaying a set of recommended filters for removing specific types of documents from the recurring search that are otherwise relevant to the selected categories for the recurring search, wherein a first set of selected additional categories results in displaying a first set of recommended filters and a second set of selected additional categories results in displaying a second, different set of recommended filters; and providing a plurality of selectable user interface controls for modifying delivery parameters for the recurring search, wherein a set of the plurality of selectable user interface controls are automatically pre-selected for the user based on an analysis of a plurality of user profile information and user behavior information, wherein email is pre-selected as a medium through which reports are delivered to the user if the user does not log-in to the research system on a recurring basis over a specified time period. 7. The method of claim 6 , wherein at least one of the initial set of categories is one of a company, an industry, a person, and a topic.
| 0.570597 |
34. A computer implemented method for adding a script to a hypertext page using a proxy, comprising: intercepting a resource request from a client machine at said proxy, said resource request identifying a resource; extracting, at the proxy, a resource request identifier from the resource request and storing the resource request identifier in computer readable memory, the resource request identifier associated with the resource; forwarding the resource request to a network and thereafter locating the resource; returning the resource to the proxy in a response to the forwarded resource request; matching the received resource with the previously stored resource request identifier from a the resource request; analyzing a plurality of templates using at least the previously stored resource request identifier to obtain a template associated with the resource; locating a template from the plurality of templates that corresponds to the received resource identified by the matching previously stored resource request identifier; embedding at least one script into the response using the located template; and sending the response to the client machine.
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34. A computer implemented method for adding a script to a hypertext page using a proxy, comprising: intercepting a resource request from a client machine at said proxy, said resource request identifying a resource; extracting, at the proxy, a resource request identifier from the resource request and storing the resource request identifier in computer readable memory, the resource request identifier associated with the resource; forwarding the resource request to a network and thereafter locating the resource; returning the resource to the proxy in a response to the forwarded resource request; matching the received resource with the previously stored resource request identifier from a the resource request; analyzing a plurality of templates using at least the previously stored resource request identifier to obtain a template associated with the resource; locating a template from the plurality of templates that corresponds to the received resource identified by the matching previously stored resource request identifier; embedding at least one script into the response using the located template; and sending the response to the client machine. 36. The method of claim 34 wherein said network is the Internet.
| 0.641245 |
2. The method of claim 1 further comprises defining a set of core attributes which may be associated with data items, where the attributes are selected from a group comprised of length of data item, minimum length of data item, maximum length of data item, list of values for the data item, pattern of characters which comprise a data item, case-sensitivity of characters which comprise a data item and a reference to a layout.
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2. The method of claim 1 further comprises defining a set of core attributes which may be associated with data items, where the attributes are selected from a group comprised of length of data item, minimum length of data item, maximum length of data item, list of values for the data item, pattern of characters which comprise a data item, case-sensitivity of characters which comprise a data item and a reference to a layout. 4. The method of claim 2 further comprises assigning a search direction in a search domain for a given data item in the layout, where the search direction is assigned in accordance with placement of the given data item in the layout.
| 0.89807 |
1. A method of rendering a virtual environment, said virtual environment having a virtual model, comprising: identifying a user entering the virtual environment and user context in the virtual model; rendering an output of the virtual model using objects in the virtual model; locating, in associated user memory, previous versions of the objects in the virtual model; identifying differences between the objects in the virtual model and the previous versions of the objects located in the user memory; and rendering a layer of the identified differences on the rendered output of the virtual model by modifying the objects in the virtual model based on user preference, wherein an identified difference is rendered differently than another identified difference according to the user preference and according to type of object.
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1. A method of rendering a virtual environment, said virtual environment having a virtual model, comprising: identifying a user entering the virtual environment and user context in the virtual model; rendering an output of the virtual model using objects in the virtual model; locating, in associated user memory, previous versions of the objects in the virtual model; identifying differences between the objects in the virtual model and the previous versions of the objects located in the user memory; and rendering a layer of the identified differences on the rendered output of the virtual model by modifying the objects in the virtual model based on user preference, wherein an identified difference is rendered differently than another identified difference according to the user preference and according to type of object. 4. A method according to claim 1 wherein the identified difference is defined according to at least one of: the type of object, difference, or magnitude of difference.
| 0.663282 |
31. A non-transitory computer readable storage medium as defined in claim 15 , including an input interface for communicating with a message service that includes the inbox to gather the size information.
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31. A non-transitory computer readable storage medium as defined in claim 15 , including an input interface for communicating with a message service that includes the inbox to gather the size information. 35. A non-transitory computer readable storage medium as defined in claim 31 , wherein the input interface receives the size information pushed from the message service.
| 0.91857 |
24. The method of claim 2 , further comprising: each item having at least one publisher identifier: in the aggregating step, aggregating the annotations for each publisher identifier such that the keywords and the user identifiers associated with the publisher identifier are aggregated from all the annotations corresponding to the publisher identifier; searching based on at least one keyword; determining publisher identifiers that match the at least one searched keyword from the aggregated annotations corresponding to the publisher identifier; and ranking the determined publisher identifiers.
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24. The method of claim 2 , further comprising: each item having at least one publisher identifier: in the aggregating step, aggregating the annotations for each publisher identifier such that the keywords and the user identifiers associated with the publisher identifier are aggregated from all the annotations corresponding to the publisher identifier; searching based on at least one keyword; determining publisher identifiers that match the at least one searched keyword from the aggregated annotations corresponding to the publisher identifier; and ranking the determined publisher identifiers. 25. The method according to claim 24 , wherein the ranking of publisher identifiers is done using an information retrieval ranking algorithm.
| 0.934461 |
17. A data processing system comprising: a display device; a processor system coupled to the display device; and a memory coupled to the processor system, wherein the processor system is configured to display, on the display device, a text input field which, through input to the text input field itself, can select between at least a first operation and a second operation, wherein the text input field includes a first portion and a second portion, and wherein the first operation is different than the second operation; receive a first input to the text input field to select the first operation, wherein the first input comprises receiving a user input in the first portion of the text input field, and the first operation is selected in response to the first input being positioned in the first portion when the first input is received; receive a first text input in the text input field, the first text input being displayable in the text input field; perform the selected first operation on all text within the text input field; receive a second input to the text input field to select the second operation, wherein the second input comprises receiving a user input in the second portion of the text input field, and the second operation is selected in response to the second input being positioned in the second portion when the second input is received; receive a second text input in the text input field, the second text input being displayable in the text input field; and perform the selected second operation on all text within the text input field.
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17. A data processing system comprising: a display device; a processor system coupled to the display device; and a memory coupled to the processor system, wherein the processor system is configured to display, on the display device, a text input field which, through input to the text input field itself, can select between at least a first operation and a second operation, wherein the text input field includes a first portion and a second portion, and wherein the first operation is different than the second operation; receive a first input to the text input field to select the first operation, wherein the first input comprises receiving a user input in the first portion of the text input field, and the first operation is selected in response to the first input being positioned in the first portion when the first input is received; receive a first text input in the text input field, the first text input being displayable in the text input field; perform the selected first operation on all text within the text input field; receive a second input to the text input field to select the second operation, wherein the second input comprises receiving a user input in the second portion of the text input field, and the second operation is selected in response to the second input being positioned in the second portion when the second input is received; receive a second text input in the text input field, the second text input being displayable in the text input field; and perform the selected second operation on all text within the text input field. 21. A data processing system as in claim 17 wherein an animation is displayed within the text input field after receiving the first input and wherein the first input can select from among more than two operations, including the first operation and the second operation.
| 0.661937 |
14. A method, comprising: identifying, in at least one computing device, a plurality of categories in a taxonomy of a collection of items by matching at least one term in a user-provided unstructured search query with metadata associated with respective categories in the taxonomy; identifying, in the at least one computing device, a refinement in the user-provided unstructured search query that is associated with at least one of the plurality of categories by translating at least one keyword from the user-provided unstructured search query into at least one criterion for selecting items from the at least one of the plurality of categories, wherein the translation is configured to translate a plurality of synonyms into the at least one criterion; generating, in the at least one computing device, a confidence score for individual categories of the plurality of categories based at least in part on a matching of at least a portion of the user-provided unstructured search query with data associated with the individual categories of the plurality of categories, individual confidence scores being generated using a weighted combination of a plurality of factors, a first factor of the plurality of factors comprising a quality of text match of items in a respective category with the user-provided unstructured search query and a second factor of the plurality of factors comprising a number of refinements identified in the user-provided unstructured search query that are associated with the respective category, and the data associated with the respective category comprising a description of the respective category, and the quality of text match being based at least in part on a frequency that the at least a portion of the user-provided unstructured search query occurs within the description; selecting, in the at least one computing device, a first pool of items from the one of the plurality of categories when the respective confidence score meets a threshold; selecting, in the at least one computing device, a second pool of items from the collection of items when no confidence score meets the threshold; and generating, in the at least one computing device, a network page listing at least a portion of the first pool of items or the second pool of items that has been selected, the network page including a disambiguation tool when no confidence score meets the threshold, and the disambiguation tool providing a user interface for selecting one category from the plurality of categories.
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14. A method, comprising: identifying, in at least one computing device, a plurality of categories in a taxonomy of a collection of items by matching at least one term in a user-provided unstructured search query with metadata associated with respective categories in the taxonomy; identifying, in the at least one computing device, a refinement in the user-provided unstructured search query that is associated with at least one of the plurality of categories by translating at least one keyword from the user-provided unstructured search query into at least one criterion for selecting items from the at least one of the plurality of categories, wherein the translation is configured to translate a plurality of synonyms into the at least one criterion; generating, in the at least one computing device, a confidence score for individual categories of the plurality of categories based at least in part on a matching of at least a portion of the user-provided unstructured search query with data associated with the individual categories of the plurality of categories, individual confidence scores being generated using a weighted combination of a plurality of factors, a first factor of the plurality of factors comprising a quality of text match of items in a respective category with the user-provided unstructured search query and a second factor of the plurality of factors comprising a number of refinements identified in the user-provided unstructured search query that are associated with the respective category, and the data associated with the respective category comprising a description of the respective category, and the quality of text match being based at least in part on a frequency that the at least a portion of the user-provided unstructured search query occurs within the description; selecting, in the at least one computing device, a first pool of items from the one of the plurality of categories when the respective confidence score meets a threshold; selecting, in the at least one computing device, a second pool of items from the collection of items when no confidence score meets the threshold; and generating, in the at least one computing device, a network page listing at least a portion of the first pool of items or the second pool of items that has been selected, the network page including a disambiguation tool when no confidence score meets the threshold, and the disambiguation tool providing a user interface for selecting one category from the plurality of categories. 18. The method of claim 14 , wherein the respective confidence score is generated based at least in part on whether the refinement is associated with the respective category.
| 0.551967 |
1. A method, comprising: identifying a plurality of refinements R(q) of a first search query q, each refinement rεR(q) being a search query that follows the first query q in a session of queries submitted to a search system; identifying a document set D(r) of each of the refinements r, the document set of a refinement being the documents d that have been presented as search results in response to the refinement by the search system and that have received user selections while being presented as the search results; building a representation of a graph G for the first search query q, wherein the graph G has a node for the first search query q, a node for each of the refinements r, a node for each document d in the document sets of the refinements, and an off-topic node for an off-topic state f and wherein the graph G has edges from the first search query node q to each of the refinement nodes r, edges from the first search query node q to each document node of the respective document set D(q) of the first search query q, edges from each refinement node to each document node in the respective document set D(r) of the refinement, and edges from each refinement node to each node for a co-occurring query Q(r) of the refinement and to the off-topic node; building a transition probability matrix P for the graph G that includes first probabilities for each edge (r i , d), second probabilities for each edge (r i , f) and third probabilities for each edge (r i , r j ); calculating a visit probability vector for each refinement in the plurality of refinements R(q) from the transition probability matrix P, where each vector has elements representing a probability for each document in the document set D(q) and the document sets of the refinements R(q); clustering the refinements into refinement clusters by partitioning the visit probability vectors into proper subsets; and deriving search suggestion for the first search query based on the refinement clusters and providing, to a user device, data that causes the user device to display the search suggestions as search suggestions for the first query.
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1. A method, comprising: identifying a plurality of refinements R(q) of a first search query q, each refinement rεR(q) being a search query that follows the first query q in a session of queries submitted to a search system; identifying a document set D(r) of each of the refinements r, the document set of a refinement being the documents d that have been presented as search results in response to the refinement by the search system and that have received user selections while being presented as the search results; building a representation of a graph G for the first search query q, wherein the graph G has a node for the first search query q, a node for each of the refinements r, a node for each document d in the document sets of the refinements, and an off-topic node for an off-topic state f and wherein the graph G has edges from the first search query node q to each of the refinement nodes r, edges from the first search query node q to each document node of the respective document set D(q) of the first search query q, edges from each refinement node to each document node in the respective document set D(r) of the refinement, and edges from each refinement node to each node for a co-occurring query Q(r) of the refinement and to the off-topic node; building a transition probability matrix P for the graph G that includes first probabilities for each edge (r i , d), second probabilities for each edge (r i , f) and third probabilities for each edge (r i , r j ); calculating a visit probability vector for each refinement in the plurality of refinements R(q) from the transition probability matrix P, where each vector has elements representing a probability for each document in the document set D(q) and the document sets of the refinements R(q); clustering the refinements into refinement clusters by partitioning the visit probability vectors into proper subsets; and deriving search suggestion for the first search query based on the refinement clusters and providing, to a user device, data that causes the user device to display the search suggestions as search suggestions for the first query. 3. The method of claim 1 , wherein for each edge (r 1 , f): P [ r i , f ] = ( 1 - ɛ ) × ∑ q ′ ∈ ( Q ( r i ) - R ( q ) ) n s ( r i , q ′ ) ∑ q ′ ∈ Q ( r i ) n s ( r i , q ′ ) .
| 0.807466 |
1. A computer implemented method for classifying a document using a plurality of confidence grades, comprising: providing a training engine and a classification engine employing a computer system for classifying said document using said plurality of confidence grades, wherein said computer system further comprises a processor, a memory unit for storing programs and data, an input/output (I/O) controller, a network interface, and a data bus; training a classifier by said training engine using a plurality of training documents, wherein training said classifier comprises: obtaining a list of first words from said training documents, wherein each of said training documents is classified into one of a plurality of classes; for each class belonging to said classes: determining a prior probability of said class, wherein said prior probability is probability of occurrence of said training documents in said class given said training documents in said classes; calculating conditional probabilities for said list of first words; calculating a minimum posterior probability and a maximum posterior probability for said class; defining multiple threshold constants by evaluating empirically said calculated minimum and maximum posterior probabilities across a number of experimentations; determining a plurality of confidence thresholds using said list of first words, said prior probability of said class, and one of said multiple threshold constants; and defining said confidence grades using said determined confidence thresholds; classifying said document by said classification engine using said trained classifier, wherein classifying said document comprises: obtaining a list of second words from said document, wherein said second words are commonly present in said list of first words; determining conditional probabilities for said list of second words for each of said classes from said calculated conditional probabilities for said list of first words; calculating a posterior probability for each of said classes using said prior probability and said determined conditional probabilities; comparing said calculated posterior probability with said determined confidence thresholds for each of said classes; assigning each of said classes to one of said defined confidence grades based on said comparison of said calculated posterior probability with said determined confidence thresholds; and assigning said document to one of said classes based on said calculated posterior probability and said assigned confidence grades for each of said classes; whereby said document is classified into one of said classes using said confidence grades.
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1. A computer implemented method for classifying a document using a plurality of confidence grades, comprising: providing a training engine and a classification engine employing a computer system for classifying said document using said plurality of confidence grades, wherein said computer system further comprises a processor, a memory unit for storing programs and data, an input/output (I/O) controller, a network interface, and a data bus; training a classifier by said training engine using a plurality of training documents, wherein training said classifier comprises: obtaining a list of first words from said training documents, wherein each of said training documents is classified into one of a plurality of classes; for each class belonging to said classes: determining a prior probability of said class, wherein said prior probability is probability of occurrence of said training documents in said class given said training documents in said classes; calculating conditional probabilities for said list of first words; calculating a minimum posterior probability and a maximum posterior probability for said class; defining multiple threshold constants by evaluating empirically said calculated minimum and maximum posterior probabilities across a number of experimentations; determining a plurality of confidence thresholds using said list of first words, said prior probability of said class, and one of said multiple threshold constants; and defining said confidence grades using said determined confidence thresholds; classifying said document by said classification engine using said trained classifier, wherein classifying said document comprises: obtaining a list of second words from said document, wherein said second words are commonly present in said list of first words; determining conditional probabilities for said list of second words for each of said classes from said calculated conditional probabilities for said list of first words; calculating a posterior probability for each of said classes using said prior probability and said determined conditional probabilities; comparing said calculated posterior probability with said determined confidence thresholds for each of said classes; assigning each of said classes to one of said defined confidence grades based on said comparison of said calculated posterior probability with said determined confidence thresholds; and assigning said document to one of said classes based on said calculated posterior probability and said assigned confidence grades for each of said classes; whereby said document is classified into one of said classes using said confidence grades. 5. The computer implemented method of claim 1 , further comprising modifying said list of first words, comprising: removing stop words from said list of first words; removing numeric digits from said list of first words; stemming each of said first words in said list of first words; and determining frequency of occurrence of each of said first words in each of said classes, wherein said first words with said frequency of occurrence less than a predetermined value are removed from said list of first words.
| 0.695471 |
19. The apparatus of claim 15 wherein the story angle data of the angle set data structure further comprises, for each story angle, data representative of an importance value for that story angle.
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19. The apparatus of claim 15 wherein the story angle data of the angle set data structure further comprises, for each story angle, data representative of an importance value for that story angle. 22. The apparatus of claim 19 wherein the processor is further configured to (1) create an archive of data, the data being indicative of at least one member of the group consisting of a plurality of previously generated evaluation indicators, a plurality of previously generated story generation requests, a plurality of story angles previously found to be applicable to previously evaluated data, and a plurality of previously generated narrative stories, (2) adjust the importance value for at least one of the story angles in the angle set data structure based on the content of the archive.
| 0.7375 |
20. A method as recited in claim 1 wherein generating search results comprises generating search results in response to suggestion data.
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20. A method as recited in claim 1 wherein generating search results comprises generating search results in response to suggestion data. 22. A method as recited in claim 20 further comprising communicating the suggestion data to the user device from a head end.
| 0.953326 |
1. A computer-implemented method comprising: generating, by a mobile device, an audio recording of (i) a spoken, natural language question that has been asked about an item of media content and that does not name, or request the name of, the item of media content, and (ii) ambient sounds that are associated with the playback of the item of media content and that are recorded contemporaneously with the question being asked; forwarding the audio recording to a coordination engine server; receiving from the coordination engine server an answer to the question, the answer based on processing of the question by a query processing engine server and on processing of the ambient sounds by a content identification engine server; and in response to the question, providing, by the mobile device, an answer to the question that has been asked about the item of media content.
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1. A computer-implemented method comprising: generating, by a mobile device, an audio recording of (i) a spoken, natural language question that has been asked about an item of media content and that does not name, or request the name of, the item of media content, and (ii) ambient sounds that are associated with the playback of the item of media content and that are recorded contemporaneously with the question being asked; forwarding the audio recording to a coordination engine server; receiving from the coordination engine server an answer to the question, the answer based on processing of the question by a query processing engine server and on processing of the ambient sounds by a content identification engine server; and in response to the question, providing, by the mobile device, an answer to the question that has been asked about the item of media content. 7. The computer-implemented method of claim 1 , further comprising: detecting environmental image data associated with the item of media content, and providing the answer based on the question and the environmental image data.
| 0.60302 |
1. A computer implemented method for storing a hierarchical table as a markup language file, the method comprising: identifying, by a processor of the computer, position of a plurality of cells included in the hierarchical table, the position of one or more cells of the plurality of cells including a first dimension coordinate and a second dimension coordinate; inserting, by the processor of the computer, the first dimension coordinate as a markup tag in the markup language file; inserting, by the processor of the computer, the second dimension coordinate as a markup attribute, corresponding to the markup tag, in the markup language file; identifying, by the processor of the computer, data included in the selected the one or more cells; identifying, by the processor of the computer, hierarchical information associated to the one or more cells; and storing the data included in the one or more cells and the hierarchical information associated to the one or more cells in the markup attribute.
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1. A computer implemented method for storing a hierarchical table as a markup language file, the method comprising: identifying, by a processor of the computer, position of a plurality of cells included in the hierarchical table, the position of one or more cells of the plurality of cells including a first dimension coordinate and a second dimension coordinate; inserting, by the processor of the computer, the first dimension coordinate as a markup tag in the markup language file; inserting, by the processor of the computer, the second dimension coordinate as a markup attribute, corresponding to the markup tag, in the markup language file; identifying, by the processor of the computer, data included in the selected the one or more cells; identifying, by the processor of the computer, hierarchical information associated to the one or more cells; and storing the data included in the one or more cells and the hierarchical information associated to the one or more cells in the markup attribute. 7. The computer implemented method according to claim 1 , wherein storing the hierarchical information includes: storing, in the processor of the computer, a markup attribute name of a markup attribute corresponding to a parent cell, from the one or more cells, in a markup attribute corresponding to a child cell, from the one or more cells.
| 0.670124 |
10. The method according to claim 1 , further comprising: storing information regarding a focus position and a scrolling position in the text browsing mode; and restoring the focus position and the scrolling position, based on the stored information, in a mode in which the definition information is applied.
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10. The method according to claim 1 , further comprising: storing information regarding a focus position and a scrolling position in the text browsing mode; and restoring the focus position and the scrolling position, based on the stored information, in a mode in which the definition information is applied. 13. The method according to claim 10 , wherein the restoring the focus position and the scrolling position is performed so that an item adjacent to the focus position to be restored is used as a focus target in the mode in which the definition information is applied if it is judged that a focus target in the text browsing mode does not exist at a position to be restored in the mode in which the definition information is applied.
| 0.800669 |
15. An apparatus, comprising: a memory element configured to store data; a processor operable to execute instructions associated with the data; a network sensor configured to interface with the memory and the processor, wherein the apparatus is configured for: receiving network traffic associated with a first user and a second user; evaluating keywords in the network traffic in order to identify a topic of discussion involving the first and the second users; determining a first sentiment associated with a first data segment associated with the first user; determining a second sentiment associated with a second data segment associated with the second user; deriving one or more statements from the network traffic; categorizing the one or more derived statements into argument map attributes, wherein the deriving and the categorizing comprise at least one activity selected from a group consisting of speech recognition, sentiment analysis and basic linguistic models; and generating an computer-automated argument map comprising the argument map attributes based on the first data sentiment and the second data sentiment, wherein the automated argument map comprises a visual representation of a structure of an argument in informal logic, wherein the argument map includes components of the argument, comprising main contentions, premises, co-premises, objections, rebuttals, and lemmas.
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15. An apparatus, comprising: a memory element configured to store data; a processor operable to execute instructions associated with the data; a network sensor configured to interface with the memory and the processor, wherein the apparatus is configured for: receiving network traffic associated with a first user and a second user; evaluating keywords in the network traffic in order to identify a topic of discussion involving the first and the second users; determining a first sentiment associated with a first data segment associated with the first user; determining a second sentiment associated with a second data segment associated with the second user; deriving one or more statements from the network traffic; categorizing the one or more derived statements into argument map attributes, wherein the deriving and the categorizing comprise at least one activity selected from a group consisting of speech recognition, sentiment analysis and basic linguistic models; and generating an computer-automated argument map comprising the argument map attributes based on the first data sentiment and the second data sentiment, wherein the automated argument map comprises a visual representation of a structure of an argument in informal logic, wherein the argument map includes components of the argument, comprising main contentions, premises, co-premises, objections, rebuttals, and lemmas. 19. The apparatus of claim 15 , wherein at least a portion of the network traffic includes video data from a video conference that is tagged.
| 0.687773 |
20. The computer storage medium of claim 17 , further comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving one or more string-category associations, where each string is associated with zero or more categories; identifying a category for facts in the collection of facts using the strings of the facts; calculating a category score for facts of the collection of facts having the particular attribute and belonging to the category; and comparing the category score to the global score such that the category is identified as an expected category for the attribute if the comparison satisfies a specified threshold.
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20. The computer storage medium of claim 17 , further comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving one or more string-category associations, where each string is associated with zero or more categories; identifying a category for facts in the collection of facts using the strings of the facts; calculating a category score for facts of the collection of facts having the particular attribute and belonging to the category; and comparing the category score to the global score such that the category is identified as an expected category for the attribute if the comparison satisfies a specified threshold. 21. The computer storage medium of claim 20 , where the comparing includes determining a fraction of the respective category score relative to the global score.
| 0.737374 |
6. A method of associating a search query to a cluster comprising: receiving a Uniform Resource Locator (URL) returned in response to a search based on a search query; extracting a first set of tokens from the URL; determining a similarity between the first set of tokens and each of a multiple set of tokens extracted from multiple other URLs returned in response to other search queries; and associating the search query with a cluster, wherein the associating is based at least in part on the similarities between the first set of tokens and each of the multiple set of tokens extracted from the other URLs.
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6. A method of associating a search query to a cluster comprising: receiving a Uniform Resource Locator (URL) returned in response to a search based on a search query; extracting a first set of tokens from the URL; determining a similarity between the first set of tokens and each of a multiple set of tokens extracted from multiple other URLs returned in response to other search queries; and associating the search query with a cluster, wherein the associating is based at least in part on the similarities between the first set of tokens and each of the multiple set of tokens extracted from the other URLs. 12. The method of claim 6 , wherein the tokens are words extracted from a URL.
| 0.872168 |
5. A system for creating an audio menu describing media content of a media player, the system comprising: a computer processor; a computer memory operatively coupled to the computer processor; the computer memory having disposed within it computer program instructions capable of: retrieving metadata describing the media files managed by the media player, further comprising: retrieving an extensible markup language (‘XML’) metadata file describing the media files managed by the media player; identifying in dependence upon the XML metadata file an organization of the media files managed by the media player; converting at least a portion of the metadata to speech including converting metadata describing a particular media file managed by media player to speech; creating one or more media files for the audio menu; and saving the speech in the audio portion of the one or more media files for the audio menu, further comprising saving the speech according to the organization of the media files managed by the media player.
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5. A system for creating an audio menu describing media content of a media player, the system comprising: a computer processor; a computer memory operatively coupled to the computer processor; the computer memory having disposed within it computer program instructions capable of: retrieving metadata describing the media files managed by the media player, further comprising: retrieving an extensible markup language (‘XML’) metadata file describing the media files managed by the media player; identifying in dependence upon the XML metadata file an organization of the media files managed by the media player; converting at least a portion of the metadata to speech including converting metadata describing a particular media file managed by media player to speech; creating one or more media files for the audio menu; and saving the speech in the audio portion of the one or more media files for the audio menu, further comprising saving the speech according to the organization of the media files managed by the media player. 8. The system of claim 5 wherein the computer memory also has disposed with it computer program instructions capable of creating an audio file organization menu including computer program instructions capable of: identifying an organization of the media files managed by the media player; creating speech describing the organization of the media files managed by the media player; and creating one or more media files; and saving the created speech describing the organization of the media files managed by the media player in the one or more media files.
| 0.633124 |
1. A multi-function machine of the type having the capability of scanning, copying and electronically transmitting documents, the machine comprising: a scanning assembly; a printing assembly; a counting and reporting module configured to generate a summary report corresponding to at least one batch of documents comprising a document set scanned by the scanning assembly, said counting and reporting module further configured to dispatch the summary report to at least one of a printing assembly, a storage device, or a network device; wherein the counting and reporting module is configured to: enable a user to select whether to count the number of documents in the document set and/or whether to count the number of images in the document set; receive at least one input and determining whether the user selected to count the number of documents in the document set and/or whether the user selected to count the number of images in the document set; count the number of documents in the document set scanned during the document scanning procedure if the user selected to count the number of documents in the document set; and count the number of images in the document set scanned during the document scanning procedure if the user selected to count the number of images in the document set; at least one processor configured to sense the completion of a batch scanning procedure by the scanning assembly.
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1. A multi-function machine of the type having the capability of scanning, copying and electronically transmitting documents, the machine comprising: a scanning assembly; a printing assembly; a counting and reporting module configured to generate a summary report corresponding to at least one batch of documents comprising a document set scanned by the scanning assembly, said counting and reporting module further configured to dispatch the summary report to at least one of a printing assembly, a storage device, or a network device; wherein the counting and reporting module is configured to: enable a user to select whether to count the number of documents in the document set and/or whether to count the number of images in the document set; receive at least one input and determining whether the user selected to count the number of documents in the document set and/or whether the user selected to count the number of images in the document set; count the number of documents in the document set scanned during the document scanning procedure if the user selected to count the number of documents in the document set; and count the number of images in the document set scanned during the document scanning procedure if the user selected to count the number of images in the document set; at least one processor configured to sense the completion of a batch scanning procedure by the scanning assembly. 3. The multi-function machine according to claim 1 , wherein the at least one processor senses the completion of the batch scanning procedure by receiving a signal from a document sensor provided in proximity to a document feed assembly of the multi-function machine.
| 0.547703 |
15. A method of controlling a bar code identification system having at least one bar code printer for printing on a web of record members, an input device, a memory and a display, said method comprising: prompting a user to enter information for a job to be printed on said bar code printer, said information representing a layout of a plurality of data fields defining a format and said information including a designation of whether a graphic field of said format includes a fixed graphic or a nonfixed graphic, the location of the graphic on the record member and one or more characteristics or said graphic; storing in a memory at least one bit map representation for a plurality of graphics, each graphic having an associated identification; prompting a user to enter via said input device a graphic identification; determining, in response to said entered graphic identification and from the characteristics of the graphic specified in said format information, whether a bit map of said identified graphic with the designated characteristics is stored in said memory and if it is not stored; translating one bit map representation of said identified graphic into a new bit map representation of said identified graphic with said designated characteristics; and storing said new bit map representation in said memory to update the number of graphic bit map representations stored in said memory.
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15. A method of controlling a bar code identification system having at least one bar code printer for printing on a web of record members, an input device, a memory and a display, said method comprising: prompting a user to enter information for a job to be printed on said bar code printer, said information representing a layout of a plurality of data fields defining a format and said information including a designation of whether a graphic field of said format includes a fixed graphic or a nonfixed graphic, the location of the graphic on the record member and one or more characteristics or said graphic; storing in a memory at least one bit map representation for a plurality of graphics, each graphic having an associated identification; prompting a user to enter via said input device a graphic identification; determining, in response to said entered graphic identification and from the characteristics of the graphic specified in said format information, whether a bit map of said identified graphic with the designated characteristics is stored in said memory and if it is not stored; translating one bit map representation of said identified graphic into a new bit map representation of said identified graphic with said designated characteristics; and storing said new bit map representation in said memory to update the number of graphic bit map representations stored in said memory. 22. A method of controlling a bar code identification system as recited in claim 15 wherein said graphic identification prompting step includes prompting a user to enter a name associated with the graphic.
| 0.533221 |
1. A method for operating a digital assistant, the method comprising: at an electronic device having one or more processors and memory: receiving user speech input; generating a textual representation of the user speech input; parsing the textual representation to determine a primary domain representing a user intent for the textual representation; identifying a first substring from the textual representation that corresponds to a first attribute of the primary domain; parsing the identified first substring to determine a secondary domain representing a user intent for the first sub string; performing a task flow comprising one or more tasks based on the primary domain and the secondary domain; and outputting a response in accordance with the performed task flow.
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1. A method for operating a digital assistant, the method comprising: at an electronic device having one or more processors and memory: receiving user speech input; generating a textual representation of the user speech input; parsing the textual representation to determine a primary domain representing a user intent for the textual representation; identifying a first substring from the textual representation that corresponds to a first attribute of the primary domain; parsing the identified first substring to determine a secondary domain representing a user intent for the first sub string; performing a task flow comprising one or more tasks based on the primary domain and the secondary domain; and outputting a response in accordance with the performed task flow. 18. The method of claim 1 , further comprising: determining a value for the first attribute based on the secondary domain, wherein the task flow is performed using the determined value for the first attribute.
| 0.647511 |
9. A device for adjusting playback progress of a video file, comprising: a receiving component, configured to receive text information to be searched; a searching component, configured to search, in a caption file of the video file, for caption content matching the text information, wherein the caption file is acquired from the video file or generated according to the video file; and an adjusting component, configured to determine playback time point corresponding to the caption content according to the found caption content, and adjust the playback progress of the video file according to the playback time point; wherein the device further comprises: a second judging component, configured to judge whether a language used by the caption file is consistent with the language used by the text information; and a second processing component, configured to regenerate the caption file according to the language used by the text information, when the language used by the caption file is not consistent with the language used by the text information.
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9. A device for adjusting playback progress of a video file, comprising: a receiving component, configured to receive text information to be searched; a searching component, configured to search, in a caption file of the video file, for caption content matching the text information, wherein the caption file is acquired from the video file or generated according to the video file; and an adjusting component, configured to determine playback time point corresponding to the caption content according to the found caption content, and adjust the playback progress of the video file according to the playback time point; wherein the device further comprises: a second judging component, configured to judge whether a language used by the caption file is consistent with the language used by the text information; and a second processing component, configured to regenerate the caption file according to the language used by the text information, when the language used by the caption file is not consistent with the language used by the text information. 16. The device according to claim 9 , wherein the receiving component comprises: a first receiving element, configured to receive input text information; and a second receiving component, configured to receive audio data, and convert the audio data into the text information.
| 0.618234 |
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