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19. The media of claim 17 , wherein a reliability-value of a first translation of the one or more translations is based on a credibility-score of a first user who submitted an input associated with the first translation.
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19. The media of claim 17 , wherein a reliability-value of a first translation of the one or more translations is based on a credibility-score of a first user who submitted an input associated with the first translation. 20. The media of claim 19 , wherein the credibility-score of the user who submitted an input associated with the first translation is based on a number of inputs by the first user that match respective correct translations for one or more respective control strings.
| 0.935608 |
11. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, by a set of one or more first servers, a query from a client device; in response to receiving the query, identifying, by one or more of the first servers, at least one index entry that is associated with a first document that (i) is responsive to the query, and (ii) is hosted by one or more second servers, wherein the index entry includes (i) an indication of a graphical user interface that is based on a document annotation associated with the first document and (ii) a static metric that is indicative of the quality of the first document, wherein the graphical user interface facilitates access to functionality provided by one or more functions within the first document; generating, by one or more of the first servers, a response to the query that includes multiple search results, wherein at least one particular search result of the multiple search results is a reference to the first document that is associated with the identified index entry; determining, by the one or more first servers, whether the graphical user interface should be associated with the reference to the first document in a search results document based on (i) the document annotation and (ii) the static metric stored in the index entry; in response to determining that the graphical user interface should be associated with the reference to the first document in a search results document based on (i) the document annotation and (ii) the static metric stored in the index entry, obtaining, by one or more of the first servers, information relating to the graphical user interface from the index entry; and providing, by one or more of the first servers, a search results document that includes at least (i) the reference to the first document that is associated with the identified index entry, and (ii) the graphical user interface that facilitates access to functionality provided by one or more functions within the first document.
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11. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, by a set of one or more first servers, a query from a client device; in response to receiving the query, identifying, by one or more of the first servers, at least one index entry that is associated with a first document that (i) is responsive to the query, and (ii) is hosted by one or more second servers, wherein the index entry includes (i) an indication of a graphical user interface that is based on a document annotation associated with the first document and (ii) a static metric that is indicative of the quality of the first document, wherein the graphical user interface facilitates access to functionality provided by one or more functions within the first document; generating, by one or more of the first servers, a response to the query that includes multiple search results, wherein at least one particular search result of the multiple search results is a reference to the first document that is associated with the identified index entry; determining, by the one or more first servers, whether the graphical user interface should be associated with the reference to the first document in a search results document based on (i) the document annotation and (ii) the static metric stored in the index entry; in response to determining that the graphical user interface should be associated with the reference to the first document in a search results document based on (i) the document annotation and (ii) the static metric stored in the index entry, obtaining, by one or more of the first servers, information relating to the graphical user interface from the index entry; and providing, by one or more of the first servers, a search results document that includes at least (i) the reference to the first document that is associated with the identified index entry, and (ii) the graphical user interface that facilitates access to functionality provided by one or more functions within the first document. 13. The computer-readable medium of claim 11 , wherein determining whether the graphical user interface should be associated with the reference to the first document in a search results document based on (i) the document annotation and (ii) the static metric stored in the index entry comprises: identifying a static metric that is associated with the first document; determining whether the static metric exceeds a predetermined threshold; and in response to determining that the static metric does not exceed the predetermined threshold, determining not to provide a graphical user interface that is associated with the first document in the search results document.
| 0.565035 |
27. A video conversational communication network in accordance with claim 23 wherein said one message switching interface means comprises at least one host computer network control means and a plurality of keystation terminal controller interface means operatively connected between said keystation and said one host computer network control means with at least one keystation being operatively connected to one keystation terminal controller interface means for each of said plurality of keystation terminal controller interface means, said host computer network control means comprising said message routing logic means and said storage means operatively connected thereto, each of said keystation terminal controller interface means comprising said display control logic means and said local video display storage means for locally storing video conversational textual data for providing a video display thereof to at least one of said keystations connected to said keystation terminal controller interface means, said keyboard means providing said unique calling signals to said keystation terminal controller interface means, said keystation terminal controller interface means comprising means for providing said calling signals to said one host computer network control means and for receiving said calling signals therefrom for completing a call to said one connected keystation.
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27. A video conversational communication network in accordance with claim 23 wherein said one message switching interface means comprises at least one host computer network control means and a plurality of keystation terminal controller interface means operatively connected between said keystation and said one host computer network control means with at least one keystation being operatively connected to one keystation terminal controller interface means for each of said plurality of keystation terminal controller interface means, said host computer network control means comprising said message routing logic means and said storage means operatively connected thereto, each of said keystation terminal controller interface means comprising said display control logic means and said local video display storage means for locally storing video conversational textual data for providing a video display thereof to at least one of said keystations connected to said keystation terminal controller interface means, said keyboard means providing said unique calling signals to said keystation terminal controller interface means, said keystation terminal controller interface means comprising means for providing said calling signals to said one host computer network control means and for receiving said calling signals therefrom for completing a call to said one connected keystation. 33. A video conversational communication network in accordance with claim 27 wherein said local storage means comprises means for retrievably storing a subscriber created page of textual data, said keyboard means comprising means for providing a unique contact list page calling signal to said message routing logic means corresponding to a designated retrievably stored contact list, said message routing logic means being responsive to said unique contact list page calling signal for simultaneously transmitting said subscriber created page to all of said keystations on said contact list, whereby a subscriber may simultaneously transmit a message to a plurality of predesignated subscribers in the network in single call.
| 0.83436 |
9. A method implemented by a provider in a broadcasting system for managing metadata for multimedia program content scheduled for broadcast in the broadcasting system, the method comprising: receiving by the provider from a client device in the broadcasting system a request for updating a lower fragment containing metadata related to the scheduled multimedia program content, the client device storing the lower fragment in a previously received electronic document, wherein the electronic document has a hierarchical structure based on a prescribed syntax and the hierarchical structure includes an upper fragment located above the lower fragment which is identified by a fragment identification; and in response to the request, sending from the provider to the client device an update document having a structure based on the prescribed syntax, the update document including the upper fragment and an invalid element, wherein the invalid element specifies that information in the lower fragment is invalid.
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9. A method implemented by a provider in a broadcasting system for managing metadata for multimedia program content scheduled for broadcast in the broadcasting system, the method comprising: receiving by the provider from a client device in the broadcasting system a request for updating a lower fragment containing metadata related to the scheduled multimedia program content, the client device storing the lower fragment in a previously received electronic document, wherein the electronic document has a hierarchical structure based on a prescribed syntax and the hierarchical structure includes an upper fragment located above the lower fragment which is identified by a fragment identification; and in response to the request, sending from the provider to the client device an update document having a structure based on the prescribed syntax, the update document including the upper fragment and an invalid element, wherein the invalid element specifies that information in the lower fragment is invalid. 10. The method of claim 9 wherein the lower fragment stored in the client device is deleted in response to the invalid element.
| 0.616444 |
14. A computer program product including a computer-readable storage medium having instructions stored thereon for processing data information, such that the instructions, when carried out by a processing device, enable the processing device to perform the operations of: providing a first visual indication on a display screen to indicate a selection of content; detecting that the selection of tagged content includes part of a grouping of related tagged content; and providing a second visual indication on the display screen to indicate a portion of the grouping of related tagged content not included in the selection of content; displaying a first type of command that can be performed on the selection of tagged content as identified by the first visual indication; and displaying a second type of command that can be performed on the portion the grouping of related tagged content as particularly identified by the second visual indication.
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14. A computer program product including a computer-readable storage medium having instructions stored thereon for processing data information, such that the instructions, when carried out by a processing device, enable the processing device to perform the operations of: providing a first visual indication on a display screen to indicate a selection of content; detecting that the selection of tagged content includes part of a grouping of related tagged content; and providing a second visual indication on the display screen to indicate a portion of the grouping of related tagged content not included in the selection of content; displaying a first type of command that can be performed on the selection of tagged content as identified by the first visual indication; and displaying a second type of command that can be performed on the portion the grouping of related tagged content as particularly identified by the second visual indication. 18. A computer program product as in claim 14 , wherein displaying the first type of command includes displaying at least one text editor command enabling a user to perform at least one respective text editing function associated with the selection of content identified by the first visual indication; and wherein displaying the second type of command includes displaying at least one tag command enabling the user to perform at least one respective tag operation on the grouping of related content, the at least one respective tag operation enabling the user to select how to a format associated with the grouping of related content.
| 0.648898 |
8. A method comprising: by a computing system comprising a hardware computer processor and non-transitory storage medium storing software instructions, receive a user input indicative of an entity and a search query; identify a statistical model associated with the entity, wherein the statistical model is determined based on a first plurality of documents associated with the entity, the statistical model indicative at least of frequencies of one or more words within the first plurality of documents; identify a second plurality of documents, at least partially different than the first plurality of documents, corresponding to the search query and the indicated entity; identify, for each of the second plurality of documents, one or more segments; apply the identified statistical model to each of the identified segments to determine, for each of the second plurality of documents, a statistical significance of segments identified in the documents, the statistical significance indicative of frequencies of the one or more words in the segment compared to the frequencies of the one or more words indicated in the statistical model; and provide for display at least a representative segment having a highest statistical significance and a link to the document containing the representative segment.
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8. A method comprising: by a computing system comprising a hardware computer processor and non-transitory storage medium storing software instructions, receive a user input indicative of an entity and a search query; identify a statistical model associated with the entity, wherein the statistical model is determined based on a first plurality of documents associated with the entity, the statistical model indicative at least of frequencies of one or more words within the first plurality of documents; identify a second plurality of documents, at least partially different than the first plurality of documents, corresponding to the search query and the indicated entity; identify, for each of the second plurality of documents, one or more segments; apply the identified statistical model to each of the identified segments to determine, for each of the second plurality of documents, a statistical significance of segments identified in the documents, the statistical significance indicative of frequencies of the one or more words in the segment compared to the frequencies of the one or more words indicated in the statistical model; and provide for display at least a representative segment having a highest statistical significance and a link to the document containing the representative segment. 12. The method of claim 8 , wherein statistical significance of segments is further based on comparing the statistical model and content of the second plurality of documents.
| 0.826389 |
13. A system for phonetic decision tree testing, the system comprising: at least one recording device to store processor-executable instructions; and at least one processor coupled to the at least one recording device and programmed by the processor-executable instructions to act as: a training engine configured to evaluate a phonetic decision tree, created using a first data set of terms of a training data set, using a second set of terms from the training data set and a set of standard pronunciations, the second set of terms comprising terms for evaluating the phonetic decision tree and including at least one second term not in the first data set, wherein the training engine categorizes a result of the evaluation into a set of correctly phonetized terms and a set of incorrectly phonetized terms, wherein the phonetic tree generation engine is configured to create an exception-limited phonetic decision tree from the set of correctly phonetized terms.
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13. A system for phonetic decision tree testing, the system comprising: at least one recording device to store processor-executable instructions; and at least one processor coupled to the at least one recording device and programmed by the processor-executable instructions to act as: a training engine configured to evaluate a phonetic decision tree, created using a first data set of terms of a training data set, using a second set of terms from the training data set and a set of standard pronunciations, the second set of terms comprising terms for evaluating the phonetic decision tree and including at least one second term not in the first data set, wherein the training engine categorizes a result of the evaluation into a set of correctly phonetized terms and a set of incorrectly phonetized terms, wherein the phonetic tree generation engine is configured to create an exception-limited phonetic decision tree from the set of correctly phonetized terms. 16. The system of claim 13 , wherein the phonetic tree generation engine is configured to create an exception-limited phonetic decision tree by: following the evaluation and the categorizing by the training engine, determining if one or more termination conditions are met by the phonetic decision tree; and when the one or more termination conditions are met, adopting the phonetic decision tree as the exception-limited phonetic decision tree.
| 0.602324 |
38. The computer-program product of claim 22 , the method comprising determining, via the determined KPIs, that the transformed human-capital information should be placed into one of the plurality of job-species nodes.
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38. The computer-program product of claim 22 , the method comprising determining, via the determined KPIs, that the transformed human-capital information should be placed into one of the plurality of job-species nodes. 40. The computer-program product of claim 38 , the method comprising: responsive to the determination that the transformed human-capital information should be placed into one of the plurality of job-species node comprises, classifying the transformed human-capital information into a selected job-species node from the plurality of job-species nodes.
| 0.893068 |
7. The method of claim 1 , wherein the qualitative analysis comprises a collective qualitative analysis of a subset of the impressions related to the comment.
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7. The method of claim 1 , wherein the qualitative analysis comprises a collective qualitative analysis of a subset of the impressions related to the comment. 12. The method of claim 7 , wherein the subset comprises one or more of the impressions for which both the historical user and the target user have been invited to an event, are identified as participants in an event, are verified as having attended an event, or have indicated interest in an event.
| 0.910767 |
21. The computing device of claim 19 , wherein the probabilistic model comprises a language model that predicts words based on at least the sequence of contacts and a spatial model that predicts a character for the third contact based on the information about the spatial location of the third contact.
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21. The computing device of claim 19 , wherein the probabilistic model comprises a language model that predicts words based on at least the sequence of contacts and a spatial model that predicts a character for the third contact based on the information about the spatial location of the third contact. 22. The computing device of claim 21 , wherein the probabilistic model estimates a probability of selection of the predicted word having a same number of characters as the number of contacts in the sequence of contacts separately from estimating the probability of selection of the predicted word having a greater number of characters than the number of contacts in the sequence of contacts.
| 0.858444 |
15. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: identify a shared visual concept in two or more visual-media items, wherein each visual-media item comprises one or more images, each image comprising one or more visual features, and wherein each visual-media item comprises one or more visual concepts, the shared visual concept being identified based on one or more shared visual features in the respective images of the visual-media items; extract, for each of the visual-media items, one or more n-grams from one or more communications associated with the visual-media item; generate, in a d-dimensional space, an embedding for each of the visual-media items, wherein a location of the embedding for the visual-media item is based on the one or more visual concepts included in the visual-media item; generate, in the d-dimensional space, an embedding for each of the extracted n-grams, wherein a location of the embedding for the n-gram is based on a frequency of occurrence of the n-gram in the communications associated with the visual-media items; associate, with the shared visual concept, one or more of the extracted n-grams that have embeddings within a threshold area of the embeddings for the identified visual-media items; populate a visual-concept index that indexes visual concepts with their respective associated n-grams; receive, from a client system of a user, a search query comprising one or more n-grams; determine, based on the visual-concept index, one or more visual concepts associated with the n-grams of the search query; and send, to the client system of the user, one or more search results comprising visual-media items in which the determined visual concepts are identified.
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15. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: identify a shared visual concept in two or more visual-media items, wherein each visual-media item comprises one or more images, each image comprising one or more visual features, and wherein each visual-media item comprises one or more visual concepts, the shared visual concept being identified based on one or more shared visual features in the respective images of the visual-media items; extract, for each of the visual-media items, one or more n-grams from one or more communications associated with the visual-media item; generate, in a d-dimensional space, an embedding for each of the visual-media items, wherein a location of the embedding for the visual-media item is based on the one or more visual concepts included in the visual-media item; generate, in the d-dimensional space, an embedding for each of the extracted n-grams, wherein a location of the embedding for the n-gram is based on a frequency of occurrence of the n-gram in the communications associated with the visual-media items; associate, with the shared visual concept, one or more of the extracted n-grams that have embeddings within a threshold area of the embeddings for the identified visual-media items; populate a visual-concept index that indexes visual concepts with their respective associated n-grams; receive, from a client system of a user, a search query comprising one or more n-grams; determine, based on the visual-concept index, one or more visual concepts associated with the n-grams of the search query; and send, to the client system of the user, one or more search results comprising visual-media items in which the determined visual concepts are identified. 20. The media of claim 15 , wherein the location of the embedding for each of one or more extracted n-grams is further based on a topic associated with the n-gram, the topic being determined based on a topic index that indexes n-grams by topic.
| 0.612439 |
1. A computer-implemented method for selectively providing Notice To Airmen (NOTAM) notifications to a crew of an aircraft, the computer-implemented method comprising: receiving, by a processor, a plurality of NOTAMs; determining a target phase of flight associated with the aircraft, from a plurality of predefined phases of flight; determining a relevance for each of the plurality of NOTAMs, according to the target phase of flight, based on a plurality of relevance rules, each of the plurality of relevance rules assigning relevance based, at least in part, on the plurality of predefined phases of flight; providing, by the processor, a notification of one or more NOTAMs according to the relevance for the target phase of flight; and assigning a relevance code to a plurality of NOTAM subject codes for each of a plurality of phases of flight, wherein the relevance for each of the plurality of NOTAMs corresponds to the relevance code associated with a NOTAM subject code of each of the plurality of NOTAMs; wherein each relevance code comprises the relevance of the NOTAM subject code to a plurality of flight segments of a planned flight route such that determining the relevance for each of the plurality of NOTAMs according to the target phase of flight comprises retrieving the relevance code corresponding to the target phase of flight and determining the relevance for each of the plurality of NOTAMs according to the corresponding relevance code, and wherein providing the notification of one or more NOTAMs according to the relevance for the target phase of flight comprises determining one or more types of notifications to provide according to each relevance code and providing the one or more types of notifications; wherein the relevance code comprises a multi-letter code, the multi-letter code including a plurality of letters, each of the plurality of letters associated with one or more flight segments, of the plurality of flight segments, of the planned flight route, and each of the plurality of letters comprising an indication of relevance of the NOTAM subject code to the corresponding flight segment of the planned flight route for the target phase of flight.
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1. A computer-implemented method for selectively providing Notice To Airmen (NOTAM) notifications to a crew of an aircraft, the computer-implemented method comprising: receiving, by a processor, a plurality of NOTAMs; determining a target phase of flight associated with the aircraft, from a plurality of predefined phases of flight; determining a relevance for each of the plurality of NOTAMs, according to the target phase of flight, based on a plurality of relevance rules, each of the plurality of relevance rules assigning relevance based, at least in part, on the plurality of predefined phases of flight; providing, by the processor, a notification of one or more NOTAMs according to the relevance for the target phase of flight; and assigning a relevance code to a plurality of NOTAM subject codes for each of a plurality of phases of flight, wherein the relevance for each of the plurality of NOTAMs corresponds to the relevance code associated with a NOTAM subject code of each of the plurality of NOTAMs; wherein each relevance code comprises the relevance of the NOTAM subject code to a plurality of flight segments of a planned flight route such that determining the relevance for each of the plurality of NOTAMs according to the target phase of flight comprises retrieving the relevance code corresponding to the target phase of flight and determining the relevance for each of the plurality of NOTAMs according to the corresponding relevance code, and wherein providing the notification of one or more NOTAMs according to the relevance for the target phase of flight comprises determining one or more types of notifications to provide according to each relevance code and providing the one or more types of notifications; wherein the relevance code comprises a multi-letter code, the multi-letter code including a plurality of letters, each of the plurality of letters associated with one or more flight segments, of the plurality of flight segments, of the planned flight route, and each of the plurality of letters comprising an indication of relevance of the NOTAM subject code to the corresponding flight segment of the planned flight route for the target phase of flight. 6. The computer-implemented method of claim 1 , wherein the computer-implemented method completes each operation at least once during each phase of flight of the aircraft such that the crew of the aircraft is provided with applicable NOTAMs during each phase of flight according to relevance to the phase of flight.
| 0.530131 |
1. A recommendation system for generating recommendations of alternative unique items, the recommendation system comprising: an items information database configured to store data relating to unique items; a penalty computation engine configured to calculate a dissimilarity penalty, the dissimilarity penalty at least partially generated based on a magnitude of dissimilarity between a selected item and an alternative item, the penalty computation engine comprising: a customizations filter configured to calculate a customization score, the customization score representing an estimated preference impact of a difference between at least one customization attribute of the selected item and at least one customization attribute of the alternative item; a condition filter configured to calculate a condition score, the condition score representing an estimated preference impact of a difference between at least one condition attribute of the selected item and at least one condition attribute of the alternative item; wherein data representing the at least one customization attribute and the at least one condition attribute of the alternative item is configured to be stored in the items information database; and a dissimilarity penalty calculator configured to generate the dissimilarity penalty by combining at least the customization score and the condition score; a recommendation compilation engine configured to generate a recommendation of alternative unique items, wherein the recommendation compilation engine is configured to electronically communicate with the penalty computation engine to calculate dissimilarity penalties for each of a plurality of alternative unique items, the recommendation of alternative unique items comprising a ranking of at least a portion of the plurality of alternative unique items, the ranking based at least partially on the calculated dissimilarity penalties; and one or more computers configured to operate the recommendation compilation engine, wherein the one or more computers comprises a computer processor and an electronic storage medium.
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1. A recommendation system for generating recommendations of alternative unique items, the recommendation system comprising: an items information database configured to store data relating to unique items; a penalty computation engine configured to calculate a dissimilarity penalty, the dissimilarity penalty at least partially generated based on a magnitude of dissimilarity between a selected item and an alternative item, the penalty computation engine comprising: a customizations filter configured to calculate a customization score, the customization score representing an estimated preference impact of a difference between at least one customization attribute of the selected item and at least one customization attribute of the alternative item; a condition filter configured to calculate a condition score, the condition score representing an estimated preference impact of a difference between at least one condition attribute of the selected item and at least one condition attribute of the alternative item; wherein data representing the at least one customization attribute and the at least one condition attribute of the alternative item is configured to be stored in the items information database; and a dissimilarity penalty calculator configured to generate the dissimilarity penalty by combining at least the customization score and the condition score; a recommendation compilation engine configured to generate a recommendation of alternative unique items, wherein the recommendation compilation engine is configured to electronically communicate with the penalty computation engine to calculate dissimilarity penalties for each of a plurality of alternative unique items, the recommendation of alternative unique items comprising a ranking of at least a portion of the plurality of alternative unique items, the ranking based at least partially on the calculated dissimilarity penalties; and one or more computers configured to operate the recommendation compilation engine, wherein the one or more computers comprises a computer processor and an electronic storage medium. 3. The recommendation system of claim 1 , wherein the recommendation compilation engine is further configured to receive selected item data, the selected item data being related to a plurality of attributes of the selected item, the plurality of attributes comprising at least the at least one customization attribute of the selected item and the at least one condition attribute of the selected item.
| 0.525253 |
8. The method of claim 4 , further comprising: receiving a token into the scanner from the reader buffer based on an indication that the token is to be overwritten in the reader buffer, wherein the scanner is configured to receive the token into the scanner.
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8. The method of claim 4 , further comprising: receiving a token into the scanner from the reader buffer based on an indication that the token is to be overwritten in the reader buffer, wherein the scanner is configured to receive the token into the scanner. 9. The method of claim 8 , further comprising: maintaining pointers from the scanner to the tokens in the reader buffer.
| 0.935668 |
5. The method as recited in claim 1 , wherein deriving the supplemental content item further comprises creating the supplemental content item in an annotatable format.
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5. The method as recited in claim 1 , wherein deriving the supplemental content item further comprises creating the supplemental content item in an annotatable format. 6. The method as recited in claim 5 , wherein the annotatable format is different from a format of the selected original content item.
| 0.955352 |
1. A method comprising: defining a set of objects to be included in a menu theme template for producing a multimedia menu comprising a plurality of user-selectable menu controls for navigating a multimedia presentation, said set of objects comprising a drop zone area object for receiving and displaying content selected by a user while the multimedia menu is being authored, wherein said defining comprises defining properties for the set of objects in a menu theme description file; defining a set of modules for rendering the set of objects, each module providing a particular functionality for rendering a particular object in the set of objects; defining a set of paths to said set of modules; and defining a rendering engine for compositing a user-editable version of the menu theme template based on the properties defined in the menu theme description file and the set of objects rendered according to the set of modules, said rendering engine using the set of paths to identify the set of modules, said menu theme template for allowing the user to author the multimedia menu.
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1. A method comprising: defining a set of objects to be included in a menu theme template for producing a multimedia menu comprising a plurality of user-selectable menu controls for navigating a multimedia presentation, said set of objects comprising a drop zone area object for receiving and displaying content selected by a user while the multimedia menu is being authored, wherein said defining comprises defining properties for the set of objects in a menu theme description file; defining a set of modules for rendering the set of objects, each module providing a particular functionality for rendering a particular object in the set of objects; defining a set of paths to said set of modules; and defining a rendering engine for compositing a user-editable version of the menu theme template based on the properties defined in the menu theme description file and the set of objects rendered according to the set of modules, said rendering engine using the set of paths to identify the set of modules, said menu theme template for allowing the user to author the multimedia menu. 7. The method of claim 1 further comprising: storing the menu theme description file in a menu theme bundle; and storing one or more content files in the menu theme bundle.
| 0.660648 |
4. The word alignment apparatus according to claim 1 , wherein the optimization portion optimizes the alignment by performing a weighted two-part graph matching with a value of at least one of the similarity degree and the association degree that have been calculated by the alignment calculator.
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4. The word alignment apparatus according to claim 1 , wherein the optimization portion optimizes the alignment by performing a weighted two-part graph matching with a value of at least one of the similarity degree and the association degree that have been calculated by the alignment calculator. 5. The word alignment apparatus according to claim 4 , wherein the optimization portion optimizes the alignment by performing a maximum and minimum weight matching on bipartite graph.
| 0.899453 |
12. The computer program product of claim 11 , where receiving a plurality of images includes receiving images having features associated with text and features associated with non-text image content.
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12. The computer program product of claim 11 , where receiving a plurality of images includes receiving images having features associated with text and features associated with non-text image content. 13. The computer program product of claim 12 , further comprising: receiving ranging data associated with the received image; generating a planar map of the received image using the ranging data; comparing the identified candidate text region with the planar map; and eliminating the identified candidate text region if the candidate text region is not located on a single plane.
| 0.706152 |
1. A remote system administration method, comprising: receiving an editor input form at a forms-enabled and script-enabled web browser through a network from a server in response to a request from a client, the web browser resident on the client; sending a server path input to the server from the web browser; receiving a file selection form from the server, the file selection form including filenames identifying files included in a server path defined by the server path input; sending a file selection from the web browser to the server, the file selection identifying one of the files; receiving a copy of the one of the files from the server; editing the copy of the one of the files using the web browser without the use of a plug-in to the web browser to produce an updated file; and sending the updated file to the server for storage.
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1. A remote system administration method, comprising: receiving an editor input form at a forms-enabled and script-enabled web browser through a network from a server in response to a request from a client, the web browser resident on the client; sending a server path input to the server from the web browser; receiving a file selection form from the server, the file selection form including filenames identifying files included in a server path defined by the server path input; sending a file selection from the web browser to the server, the file selection identifying one of the files; receiving a copy of the one of the files from the server; editing the copy of the one of the files using the web browser without the use of a plug-in to the web browser to produce an updated file; and sending the updated file to the server for storage. 5. The method of claim 1, further comprising receiving an indication at the client that selected text is present in the one of the files.
| 0.869565 |
27. The apparatus of claim 24 , wherein the query is to include device descriptive information, application descriptive information and identity information.
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27. The apparatus of claim 24 , wherein the query is to include device descriptive information, application descriptive information and identity information. 28. The apparatus of claim 27 , wherein the application descriptive information comprises a signature of an application executing on the device.
| 0.928214 |
7. The device of claim 3 , wherein the processor is programmed to extract the information from the translation of the recognized speech by the second speaker translated to the first language by detecting one or more keywords in the translation.
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7. The device of claim 3 , wherein the processor is programmed to extract the information from the translation of the recognized speech by the second speaker translated to the first language by detecting one or more keywords in the translation. 8. The device of claim 7 , wherein the processor is further programmed to retrieve one or more documents related to the extract information from a remote database.
| 0.952255 |
11. The method of claim 10 , wherein the method further comprises embedding the created file into another file that is of a type compatible with the external application.
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11. The method of claim 10 , wherein the method further comprises embedding the created file into another file that is of a type compatible with the external application. 13. The method of claim 11 , wherein the external application is a PDF player and the created file is embedded into a PDF file.
| 0.942878 |
14. A method of searching a plurality of documents, the method comprising: receiving a request to search the plurality of documents stored on a device, wherein the request includes query criteria; identifying a subset of the plurality of documents based on the query criteria; identifying, for each of the subset of documents, a plurality of blocks by visually segmenting the document; expanding, based on the content of the plurality of blocks, the query criteria; and identifying a second subset of the plurality of documents based on the expanded query criteria; and ranking the blocks according to the location of query criteria in the block and how frequently the query criteria occur in the block.
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14. A method of searching a plurality of documents, the method comprising: receiving a request to search the plurality of documents stored on a device, wherein the request includes query criteria; identifying a subset of the plurality of documents based on the query criteria; identifying, for each of the subset of documents, a plurality of blocks by visually segmenting the document; expanding, based on the content of the plurality of blocks, the query criteria; and identifying a second subset of the plurality of documents based on the expanded query criteria; and ranking the blocks according to the location of query criteria in the block and how frequently the query criteria occur in the block. 17. A method as recited in claim 14 , wherein the visually segmenting the document comprises: identifying a plurality of visual blocks in the document; detecting one or more separators between the visual blocks of the plurality of visual blocks; and constructing, based at least in part on the plurality of visual blocks and the one or more separators, a content structure for the document, wherein the content structure identifies the different visual blocks as different portions of semantic content of the document, and wherein the different visual blocks are the plurality of blocks for the document.
| 0.639351 |
15. A method of reproducing a text subtitle stream recorded on an optical disc, the method comprising: reading a first segment included in the text subtitle stream, the first segment including first style information, the first style information including at least one of composition information and rendering information for a region including text subtitle data; reading a second segment included in the text subtitle stream, the second segment including the text subtitle data and second style information, wherein the second segment is linked to the first segment, the second style information includes font information for the text subtitle data, wherein the font information is declared at a beginning of at least a portion of the text subtitle data being affected by the font information, wherein the second segment includes a length indicator indicating a length of the at least the portion of the text subtitle data, and wherein each of the first segment and the second segment includes a segment identifier identifying the first segment and the second segment, respectively; and reproducing the text subtitle data using the first and second style information.
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15. A method of reproducing a text subtitle stream recorded on an optical disc, the method comprising: reading a first segment included in the text subtitle stream, the first segment including first style information, the first style information including at least one of composition information and rendering information for a region including text subtitle data; reading a second segment included in the text subtitle stream, the second segment including the text subtitle data and second style information, wherein the second segment is linked to the first segment, the second style information includes font information for the text subtitle data, wherein the font information is declared at a beginning of at least a portion of the text subtitle data being affected by the font information, wherein the second segment includes a length indicator indicating a length of the at least the portion of the text subtitle data, and wherein each of the first segment and the second segment includes a segment identifier identifying the first segment and the second segment, respectively; and reproducing the text subtitle data using the first and second style information. 16. The method of claim 15 , wherein the composition information includes position information for positioning a text subtitle represented by the text subtitle data on a display.
| 0.669673 |
1. A text processing system operable in two modes, in a first mode audio commentary is recorded and associated with selected portions of displayed text, in a second mode the commentary is played back while the text to which it pertains is recalled to a display, said system comprising: (a) a word processor including: (i) a display unit (DU) on which the text is displayed, (ii) addressable means for storing data including said text, (iii) input means for selecting the mode of operation, (iv) a processing unit responsive to said input means for communicating data, including text, between said storage means, the DU and said input means, said processing unit generating digital address information corresponding to the locations in said storing means where said selected text is located, said processing unit including bus means by which the display unit, storing means and interface means can communicate with the processing unit; (b) recorder means capable of recording and playing back address information and commentary; (c) means for interfacing said processing unit with the recorder means to permit the processing unit to control recording and playback and to store and retrieve said address information from the recording means such that: (i) during the first mode the processing unit generates address information to be recorded along with the audio commentary and (ii) during the second mode the processing unit causes the recorder to play back the recorded address information and commentary, said processing unit retrieving said address information via said interfacing means and utilizing it to display the text to which the commentary pertains; whereby a first user can select text displayed on the DU and record commentary relating thereto and, when desired, the same or a second user can listen to the recorded commentary while having the text to which it pertains displayed on the DU.
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1. A text processing system operable in two modes, in a first mode audio commentary is recorded and associated with selected portions of displayed text, in a second mode the commentary is played back while the text to which it pertains is recalled to a display, said system comprising: (a) a word processor including: (i) a display unit (DU) on which the text is displayed, (ii) addressable means for storing data including said text, (iii) input means for selecting the mode of operation, (iv) a processing unit responsive to said input means for communicating data, including text, between said storage means, the DU and said input means, said processing unit generating digital address information corresponding to the locations in said storing means where said selected text is located, said processing unit including bus means by which the display unit, storing means and interface means can communicate with the processing unit; (b) recorder means capable of recording and playing back address information and commentary; (c) means for interfacing said processing unit with the recorder means to permit the processing unit to control recording and playback and to store and retrieve said address information from the recording means such that: (i) during the first mode the processing unit generates address information to be recorded along with the audio commentary and (ii) during the second mode the processing unit causes the recorder to play back the recorded address information and commentary, said processing unit retrieving said address information via said interfacing means and utilizing it to display the text to which the commentary pertains; whereby a first user can select text displayed on the DU and record commentary relating thereto and, when desired, the same or a second user can listen to the recorded commentary while having the text to which it pertains displayed on the DU. 5. The system according to claim 1 wherein said word processor includes means for permitting the user to designate portions of the text displayed on said DU as the selected portions of text to which the commentary pertains.
| 0.529134 |
10. An electronic device, comprising: a controller that: identifies a device context corresponding to the electronic device; processes the device context in real time to identify a potential user intent and to determine a probability that the potential user intent corresponds to an actual user intent; selects a user input sensitivity parameter based on the potential user intent and the determined probability; and adapts the sensitivity of the at least one user interface component to correspond to the user input sensitivity parameter.
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10. An electronic device, comprising: a controller that: identifies a device context corresponding to the electronic device; processes the device context in real time to identify a potential user intent and to determine a probability that the potential user intent corresponds to an actual user intent; selects a user input sensitivity parameter based on the potential user intent and the determined probability; and adapts the sensitivity of the at least one user interface component to correspond to the user input sensitivity parameter. 11. The electronic device of claim 10 , wherein: when the probability that the potential user intent corresponds to the actual user intent is below or above a threshold, the controller solicits at least one user input prior to adapting the sensitivity of the at least one user interface component.
| 0.695503 |
1. A method for generating test data, the method comprising: obtaining, by a processor, at least one rule based on a requirement specification, wherein the requirement specification is obtained from a user and is based on business and functional requirements, and wherein the at least one rule indicates a format of at least one of valid test data and invalid test data for testing of at least one parameter of a program code, and wherein the at least one rule is obtained independent of analyzing the program code; determining, by the processor, at least one relational expression corresponding to the at least one parameter of the program code based on the at least one rule; tokenizing, by the processor, the at least one relational expression into a plurality of tokens, and parsing the plurality of tokens to identify and then assign one or more valid upper and lower boundary values and one or more invalid upper and lower boundary values for each token, of the at least one parameter of the program code; generating, by the processor, one or more valid test data based on the assigned one or more valid upper and lower boundary values for each token of the at least one parameter of the program code, wherein the generating one or more valid test data comprises solving the at least one relational expression based on the one or more valid upper and lower boundary values; generating, by the processor, one or more invalid test data based on the assigned one or more invalid upper and lower boundary values for each token of the plurality of tokens of the at least one parameter of the program code, wherein the generating one or more invalid test data comprises solving the at least one relational expression based on the one or more invalid upper and lower boundary values; and wherein the one or more valid test data is a first range of values limited by the one or more valid upper and lower boundary values and the one or more invalid test data is a second range of values lying outside the first range of values and limited by the one or more invalid upper and lower boundary values.
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1. A method for generating test data, the method comprising: obtaining, by a processor, at least one rule based on a requirement specification, wherein the requirement specification is obtained from a user and is based on business and functional requirements, and wherein the at least one rule indicates a format of at least one of valid test data and invalid test data for testing of at least one parameter of a program code, and wherein the at least one rule is obtained independent of analyzing the program code; determining, by the processor, at least one relational expression corresponding to the at least one parameter of the program code based on the at least one rule; tokenizing, by the processor, the at least one relational expression into a plurality of tokens, and parsing the plurality of tokens to identify and then assign one or more valid upper and lower boundary values and one or more invalid upper and lower boundary values for each token, of the at least one parameter of the program code; generating, by the processor, one or more valid test data based on the assigned one or more valid upper and lower boundary values for each token of the at least one parameter of the program code, wherein the generating one or more valid test data comprises solving the at least one relational expression based on the one or more valid upper and lower boundary values; generating, by the processor, one or more invalid test data based on the assigned one or more invalid upper and lower boundary values for each token of the plurality of tokens of the at least one parameter of the program code, wherein the generating one or more invalid test data comprises solving the at least one relational expression based on the one or more invalid upper and lower boundary values; and wherein the one or more valid test data is a first range of values limited by the one or more valid upper and lower boundary values and the one or more invalid test data is a second range of values lying outside the first range of values and limited by the one or more invalid upper and lower boundary values. 4. The method as claimed in claim 1 , wherein the generated one or more test data is provided to the program code as input for testing the program code against the one or more test data.
| 0.847471 |
39. An audio processing system, comprising: a rendering engine operable to sequentially render audio summaries and transition audio segments with at least one transition audio segment rendered between each pair of sequential audio summaries, wherein each of the audio summaries comprises digital content summarizing at least a portion of a respective associated audio piece and, in response to receipt of a user request to browse the audio summaries, the rendering engine is operable to order ones of the audio summaries into a sequence in order of audio feature vector closeness to a given one of the audio summaries being rendered when the user request was received and to render the sequence.
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39. An audio processing system, comprising: a rendering engine operable to sequentially render audio summaries and transition audio segments with at least one transition audio segment rendered between each pair of sequential audio summaries, wherein each of the audio summaries comprises digital content summarizing at least a portion of a respective associated audio piece and, in response to receipt of a user request to browse the audio summaries, the rendering engine is operable to order ones of the audio summaries into a sequence in order of audio feature vector closeness to a given one of the audio summaries being rendered when the user request was received and to render the sequence. 40. The system of claim 39 , wherein the rendering engine is operable to render the audio summaries in accordance with the ordered sequence.
| 0.725633 |
1. A computer implemented natural language processing method for resolving partial matches, comprising: receiving, using a computer processor, a natural language input query that does not fully specify an entity; tokenizing, using the computer processor, the input query into a constituent set of query tokens; searching, using the computer processor, an entity index by comparing the query tokens to contents of the index, the contents representing a plurality of entities, each of which is tokenized into a constituent set of entity tokens associated with the tokenized entity; identifying, using the computer processor, a plurality of partial match query tokens from the set of query tokens, each partial match query token matching at least one entity token in the index; determining, using the computer processor, whether a sequential break exists in the input query between the partial match query tokens; for each partial match query token, determining, using the computer processor, the entity corresponding to each partial match query token by identifying the entity associated with each entity token in the index that matches the partial match query token; determining, using the computer processor, whether there is an intersection between the identified entities corresponding to the partial match query tokens; and when a sequential break exists in the input query between the partial match query tokens and there is no intersection between the identified entities corresponding to the partial match query tokens determining, using the computer processor, that the input query relates to a plurality of entities, and presenting a response to the received natural language input query to a user based upon the identified entities.
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1. A computer implemented natural language processing method for resolving partial matches, comprising: receiving, using a computer processor, a natural language input query that does not fully specify an entity; tokenizing, using the computer processor, the input query into a constituent set of query tokens; searching, using the computer processor, an entity index by comparing the query tokens to contents of the index, the contents representing a plurality of entities, each of which is tokenized into a constituent set of entity tokens associated with the tokenized entity; identifying, using the computer processor, a plurality of partial match query tokens from the set of query tokens, each partial match query token matching at least one entity token in the index; determining, using the computer processor, whether a sequential break exists in the input query between the partial match query tokens; for each partial match query token, determining, using the computer processor, the entity corresponding to each partial match query token by identifying the entity associated with each entity token in the index that matches the partial match query token; determining, using the computer processor, whether there is an intersection between the identified entities corresponding to the partial match query tokens; and when a sequential break exists in the input query between the partial match query tokens and there is no intersection between the identified entities corresponding to the partial match query tokens determining, using the computer processor, that the input query relates to a plurality of entities, and presenting a response to the received natural language input query to a user based upon the identified entities. 3. The computer-implemented method according to claim 1 , wherein the constituent set of entity tokens associated with the tokenized entity in the index are derived by the processor using a combination of language modeling principles of high-frequency products, n-gram modeling and TF-IDF tokenization techniques.
| 0.540459 |
12. A method comprising: generating a preview document of a native document comprising a preview code including table elements corresponding to fields in the native document, the native document stored on a client device, the generating comprising: generating field dimensions for the fields in the native document; generating a field mapping of fields in the native document to table elements in the preview code; generating a formula listing designating, for each formula of a set of formulas in the native document, one or more fields associated with the formula in the native document; and displaying the preview document on a display by executing the preview code; generating an updated preview document in response to a change to the native document; swapping the updated preview document with the displayed preview document; and applying a current user interaction context to the swapped updated preview document.
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12. A method comprising: generating a preview document of a native document comprising a preview code including table elements corresponding to fields in the native document, the native document stored on a client device, the generating comprising: generating field dimensions for the fields in the native document; generating a field mapping of fields in the native document to table elements in the preview code; generating a formula listing designating, for each formula of a set of formulas in the native document, one or more fields associated with the formula in the native document; and displaying the preview document on a display by executing the preview code; generating an updated preview document in response to a change to the native document; swapping the updated preview document with the displayed preview document; and applying a current user interaction context to the swapped updated preview document. 14. The method of claim 12 , further comprising: receiving a modification of a table element from the user; determining a target field associated with the modification using the field mapping; modifying the target field in the native document with the modification.
| 0.669486 |
1. A computer-implemented method of providing promotional content related to one or more natural language utterances and/or responses, 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, at the one or more physical processors, a first natural language utterance; providing, by the one or more physical processors, a response to the first natural language utterance; receiving, at the one or more physical processors, a second natural language utterance relating to the first natural language utterance; performing, by the one or more physical processors, speech recognition to recognize one or more words of the second natural language utterance; determining, by the one or more physical processors, domain information for the one or more recognized words based on the first natural language utterance; processing, by the one or more physical processors, based on the domain information, the one or more recognized words to determine an interpretation of the second natural language utterance, wherein processing the one or more recognized words comprises: providing the one or more recognized words to a first domain agent associated with a first domain and a second domain agent associated with a second domain; obtaining a first interpretation of the second natural language utterance from the first domain agent; obtaining a second interpretation of the second natural language utterance from the second domain agent; and determining the interpretation based on one or more of the first interpretation or the second interpretation; determining, by the one or more physical processors, promotional content based on the interpretation; and presenting, by the one or more physical processors, the promotional content to a user.
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1. A computer-implemented method of providing promotional content related to one or more natural language utterances and/or responses, 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, at the one or more physical processors, a first natural language utterance; providing, by the one or more physical processors, a response to the first natural language utterance; receiving, at the one or more physical processors, a second natural language utterance relating to the first natural language utterance; performing, by the one or more physical processors, speech recognition to recognize one or more words of the second natural language utterance; determining, by the one or more physical processors, domain information for the one or more recognized words based on the first natural language utterance; processing, by the one or more physical processors, based on the domain information, the one or more recognized words to determine an interpretation of the second natural language utterance, wherein processing the one or more recognized words comprises: providing the one or more recognized words to a first domain agent associated with a first domain and a second domain agent associated with a second domain; obtaining a first interpretation of the second natural language utterance from the first domain agent; obtaining a second interpretation of the second natural language utterance from the second domain agent; and determining the interpretation based on one or more of the first interpretation or the second interpretation; determining, by the one or more physical processors, promotional content based on the interpretation; and presenting, by the one or more physical processors, the promotional content to a user. 31. The method of claim 1 , further comprising: obtaining, by the one or more physical processors, user profile information associated with the user, wherein the user profile information specifies prior user interactions with items; identifying, by the one or more physical processors, one or more requests associated with the first natural language utterance or the second natural language utterance; determining, by the one or more physical processors, one or more applications for processing the one or more requests; and identifying, by the one or more physical processors, categories of items based on the prior user interactions specified by the user profile information, wherein the categories relate to the one or more applications, wherein determining the promotional content comprises determining a promotional item associated with one of the categories.
| 0.5 |
11. A computer-implemented method comprising: generating, based at least in part on a co-occurrence analysis of search histories associated with an electronic catalog, a cluster of item descriptors describing types of items in the electronic catalog that tend to be searched for in the electronic catalog in combination, the cluster of item descriptors including at least a first item descriptor representing a first item type and a second item descriptor representing a second item type; generating, based at least in part on the cluster of item descriptors, a plurality of item clusters, each item cluster including a plurality of items in the electronic catalog and including at least a first item of the first item type and a second item of the second item type; and providing a catalog item recommendation based at least in part on the plurality of item clusters, said method performed by an electronic catalog system comprising one or more computing devices.
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11. A computer-implemented method comprising: generating, based at least in part on a co-occurrence analysis of search histories associated with an electronic catalog, a cluster of item descriptors describing types of items in the electronic catalog that tend to be searched for in the electronic catalog in combination, the cluster of item descriptors including at least a first item descriptor representing a first item type and a second item descriptor representing a second item type; generating, based at least in part on the cluster of item descriptors, a plurality of item clusters, each item cluster including a plurality of items in the electronic catalog and including at least a first item of the first item type and a second item of the second item type; and providing a catalog item recommendation based at least in part on the plurality of item clusters, said method performed by an electronic catalog system comprising one or more computing devices. 12. The computer-implemented method of claim 11 , wherein the catalog item recommendation is provided in a search results page that is generated in response to receiving a current search request.
| 0.917578 |
13. The method of claim 8 further comprising modifying said request based on said rules.
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13. The method of claim 8 further comprising modifying said request based on said rules. 14. The method of claim 13 further comprising restricting the at least one of the type and amount of the content requested.
| 0.948397 |
1. A system comprising: memory; one or more processors; and a segmentation component stored on the memory and executable by the one or more processors, the segmentation component comprising: a configuration element that: displays a plurality of search types, displays, for a given search type of the plurality of search types, one or more representations of search engines to enable selection of a respective search engine from among a plurality of search engines, and receives one or more user selections associating respective search engines of the plurality of search engines with respective search types of the plurality of search types; and a routing element that: receives a search query, compares the search query to a set of search terms to determine a search type for the search query from among the plurality of search types, and determines, based at least partly on the user selections and the search type of the search query, a search engine from among the plurality of search engines.
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1. A system comprising: memory; one or more processors; and a segmentation component stored on the memory and executable by the one or more processors, the segmentation component comprising: a configuration element that: displays a plurality of search types, displays, for a given search type of the plurality of search types, one or more representations of search engines to enable selection of a respective search engine from among a plurality of search engines, and receives one or more user selections associating respective search engines of the plurality of search engines with respective search types of the plurality of search types; and a routing element that: receives a search query, compares the search query to a set of search terms to determine a search type for the search query from among the plurality of search types, and determines, based at least partly on the user selections and the search type of the search query, a search engine from among the plurality of search engines. 11. The system of claim 1 , wherein the plurality of search types include a consumer search, an image search, an entertainment search, a news search, a default search, and a local default search.
| 0.598479 |
4. The method of claim 1 , wherein the expression of the rule returns a predicted user life span based on the one or more calculated health attribute values.
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4. The method of claim 1 , wherein the expression of the rule returns a predicted user life span based on the one or more calculated health attribute values. 5. The method claim 4 , wherein the first action includes reporting the predicted user life span.
| 0.976984 |
2. The apparatus of claim 1 , wherein, in the segmentation of the one or more faces from the captured visual data, the processor is further configured to use at least one face finding algorithm to find one or more likely humans in the vicinity.
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2. The apparatus of claim 1 , wherein, in the segmentation of the one or more faces from the captured visual data, the processor is further configured to use at least one face finding algorithm to find one or more likely humans in the vicinity. 3. The apparatus of claim 2 , wherein the at least one face finding algorithm comprises a Jones-Viola object detection framework.
| 0.969296 |
1. A method comprising: instantiating a virtual service from a service model, wherein the virtual service is operable to receive requests intended for a particular one of a plurality of software components in a system and generate simulated responses of the particular software component based on a service model modeling responses of the particular software component, wherein the service model is based on monitored requests of the particular software component and monitored responses of the particular software component to the monitored requests; identifying a particular request from another software component intended for the particular software component, wherein the particular request is redirected to the virtual service; generating content of a simulated response to the particular request using the virtual service, wherein the content of the simulated response is in a first language based on the service model, the service model models responses of the particular software component in only a particular set of languages, and the particular set of languages comprises the first language; determining, based on the request, a second language to be applied to the simulated response, wherein the second language is outside the particular set of languages; determining, using a data processing apparatus, a translation of the content from the first language into the second language; and sending a modified version of the simulated response comprising the content in the second language to the other software component in response to the particular request.
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1. A method comprising: instantiating a virtual service from a service model, wherein the virtual service is operable to receive requests intended for a particular one of a plurality of software components in a system and generate simulated responses of the particular software component based on a service model modeling responses of the particular software component, wherein the service model is based on monitored requests of the particular software component and monitored responses of the particular software component to the monitored requests; identifying a particular request from another software component intended for the particular software component, wherein the particular request is redirected to the virtual service; generating content of a simulated response to the particular request using the virtual service, wherein the content of the simulated response is in a first language based on the service model, the service model models responses of the particular software component in only a particular set of languages, and the particular set of languages comprises the first language; determining, based on the request, a second language to be applied to the simulated response, wherein the second language is outside the particular set of languages; determining, using a data processing apparatus, a translation of the content from the first language into the second language; and sending a modified version of the simulated response comprising the content in the second language to the other software component in response to the particular request. 13. The method of claim 1 , wherein the second language is determined from content of the particular request.
| 0.521037 |
1. A computer-implemented method comprising: receiving, by a computer system comprising one or more servers from particular members of a member network, machine-readable endorsement information that characterizes the particular members' ratings of various articles; receiving member profile information specifying that one or more members of the member network are experts in one or more respective fields; receiving, by the computer system, a first search query from a first user in the member network; determining, by the computer system, that the first search query relates to a particular field; identifying, from an article index by the computer system, a first plurality of articles that are responsive to the first search query; identifying, by the computer system from profile information of the members of the member network, one or more experts in the member network that are each an expert in the particular field to which the computer system determined the first search query relates; identifying, from a repository of member network data for the member network, a second plurality of articles that are responsive to the first search query and that have been endorsed by particular members in the member network, wherein the repository of member network data is different from the article index; determining that a first article in the second plurality of articles has been endorsed by an expert in the one or more experts in the member network who are each an expert in the particular field to which the computer system determined the first search query relates; generating, by the computer system, a plurality of article identifiers for articles that include articles from the first and second pluralities of articles; ranking, by the computer system, using the endorsements for articles in the second plurality of articles, the first article that has been endorsed by the expert in the particular field to which the first search query relates with a higher ranking than a second article that was not endorsed by an expert in the particular field to which the first search query relates; and responding, by the computer system, to the first search query with the plurality of article identifiers according to the ranking including a first article identifier for the first article and a second article identifier for the second article.
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1. A computer-implemented method comprising: receiving, by a computer system comprising one or more servers from particular members of a member network, machine-readable endorsement information that characterizes the particular members' ratings of various articles; receiving member profile information specifying that one or more members of the member network are experts in one or more respective fields; receiving, by the computer system, a first search query from a first user in the member network; determining, by the computer system, that the first search query relates to a particular field; identifying, from an article index by the computer system, a first plurality of articles that are responsive to the first search query; identifying, by the computer system from profile information of the members of the member network, one or more experts in the member network that are each an expert in the particular field to which the computer system determined the first search query relates; identifying, from a repository of member network data for the member network, a second plurality of articles that are responsive to the first search query and that have been endorsed by particular members in the member network, wherein the repository of member network data is different from the article index; determining that a first article in the second plurality of articles has been endorsed by an expert in the one or more experts in the member network who are each an expert in the particular field to which the computer system determined the first search query relates; generating, by the computer system, a plurality of article identifiers for articles that include articles from the first and second pluralities of articles; ranking, by the computer system, using the endorsements for articles in the second plurality of articles, the first article that has been endorsed by the expert in the particular field to which the first search query relates with a higher ranking than a second article that was not endorsed by an expert in the particular field to which the first search query relates; and responding, by the computer system, to the first search query with the plurality of article identifiers according to the ranking including a first article identifier for the first article and a second article identifier for the second article. 19. The method of claim 1 , wherein identifying the one or more experts in the member network that are each an expert in the particular field to which the computer system determined the first search query relates comprises determining that at least one of the one or more experts in the member network is an expert in the particular field using corresponding professional information or corresponding educational information in the profile information for the corresponding expert.
| 0.588756 |
3. A non-transitory computer-readable medium having stored thereon computer-readable instructions that when executed by a computing device cause the computing device to: define an active topic as a first topic in response to execution of an application by the computing device, wherein the first topic includes first text defining a plurality of phrases, a probability of occurrence associated with each of the plurality of phrases based on the first topic, and a response associated with each of the plurality of phrases; receive speech text recognized from a recorded audio signal, wherein recognition of the speech text is based at least partially on the probability of occurrence associated with each of the plurality of phrases of the first topic; identify a phrase of the plurality of phrases associated with the received speech text; perform the response associated with the identified phrase, wherein the response includes instructions defining an action triggered by occurrence of the received speech text, and further wherein the action includes defining the active topic as a second topic, wherein the second topic includes second text defining a second plurality of phrases, a second probability of occurrence associated with each of the second plurality of phrases, and a second response associated with each of the second plurality of phrases; receive an indicator of an interaction with the application by a user; in response to receipt of the indicator, determine if the active topic is a correct topic based on the interaction with the application; if the active topic is determined to be the correct topic based on the interaction with the application, increase the probability of occurrence associated with the identified phrase; and if the active topic is determined to not be the correct topic based on the interaction with the application, decrease the probability of occurrence associated with the identified phrase.
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3. A non-transitory computer-readable medium having stored thereon computer-readable instructions that when executed by a computing device cause the computing device to: define an active topic as a first topic in response to execution of an application by the computing device, wherein the first topic includes first text defining a plurality of phrases, a probability of occurrence associated with each of the plurality of phrases based on the first topic, and a response associated with each of the plurality of phrases; receive speech text recognized from a recorded audio signal, wherein recognition of the speech text is based at least partially on the probability of occurrence associated with each of the plurality of phrases of the first topic; identify a phrase of the plurality of phrases associated with the received speech text; perform the response associated with the identified phrase, wherein the response includes instructions defining an action triggered by occurrence of the received speech text, and further wherein the action includes defining the active topic as a second topic, wherein the second topic includes second text defining a second plurality of phrases, a second probability of occurrence associated with each of the second plurality of phrases, and a second response associated with each of the second plurality of phrases; receive an indicator of an interaction with the application by a user; in response to receipt of the indicator, determine if the active topic is a correct topic based on the interaction with the application; if the active topic is determined to be the correct topic based on the interaction with the application, increase the probability of occurrence associated with the identified phrase; and if the active topic is determined to not be the correct topic based on the interaction with the application, decrease the probability of occurrence associated with the identified phrase. 4. The non-transitory computer-readable medium of claim 3 , wherein the application includes input controls for accessing a plurality of user interface windows and for entering information in a database.
| 0.509082 |
1. A method for merging information of high semantic level representing complex situations comprising several items of information or data originating from several sensors, said method being executed on a processor and comprising: acquiring the several items of information or data arising from at least two sensors in raw form and transforming the several items of information or data using said processor to cast the several items of information or data into a form of conceptual graphs, a conceptual graph representing several concepts and relations which exist between the several concepts, a conceptual graph comprising several entity nodes and relation nodes, with a set of concept nodes E defined on a support S, two conceptual graphs G 1 and G 2 defined on the support S, and the two conceptual graphs G 1 and G 2 being stored in a database; defining a knowledge base containing information or data specific to a sector of an application of data merging and rules applied in said sector of the application, and transforming said information or data specific to the sector of the application using the processor to present said information or data specific to the sector of the application in a form of conceptual graphs; determining a merging strategy denoted strategy merge as follows: strategy merge =f merge ◯f comp :E×E→E∪{E×E}, where f merge :{true, false}×E×E→E∪{E×E} is a merge function for merging concept nodes of graphs, and f comp : E×E→{true, false}×E×E is a function for testing compatibility between two concept nodes of the graphs; applying the merging strategy to the information or data arising from the knowledge base and from an observation base taking the form of graphs to produce merged data; and sending the merged data to a decision making system, wherein: the two conceptual graphs G 1 and G 2 have a common generalization H, and projections P 1 :H→G 1 and P 2 :H→G 2 , P 1 and P 2 are compatible according to the function f comp if, for each concept c of the graph H, the following conditions are complied with: P 1 (c) and P 2 (c) have a common sub-type different from an absurd type, referents or components of P 1 (c) and P 2 (c) conform to their most general common sub-type, and the referents of P 1 (c) and P 2 (c) are either equal, or one of the two is undefined, or f comp (P 1 (c), P 2 (c))=(true, P 1 (c), P 2 (c)).
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1. A method for merging information of high semantic level representing complex situations comprising several items of information or data originating from several sensors, said method being executed on a processor and comprising: acquiring the several items of information or data arising from at least two sensors in raw form and transforming the several items of information or data using said processor to cast the several items of information or data into a form of conceptual graphs, a conceptual graph representing several concepts and relations which exist between the several concepts, a conceptual graph comprising several entity nodes and relation nodes, with a set of concept nodes E defined on a support S, two conceptual graphs G 1 and G 2 defined on the support S, and the two conceptual graphs G 1 and G 2 being stored in a database; defining a knowledge base containing information or data specific to a sector of an application of data merging and rules applied in said sector of the application, and transforming said information or data specific to the sector of the application using the processor to present said information or data specific to the sector of the application in a form of conceptual graphs; determining a merging strategy denoted strategy merge as follows: strategy merge =f merge ◯f comp :E×E→E∪{E×E}, where f merge :{true, false}×E×E→E∪{E×E} is a merge function for merging concept nodes of graphs, and f comp : E×E→{true, false}×E×E is a function for testing compatibility between two concept nodes of the graphs; applying the merging strategy to the information or data arising from the knowledge base and from an observation base taking the form of graphs to produce merged data; and sending the merged data to a decision making system, wherein: the two conceptual graphs G 1 and G 2 have a common generalization H, and projections P 1 :H→G 1 and P 2 :H→G 2 , P 1 and P 2 are compatible according to the function f comp if, for each concept c of the graph H, the following conditions are complied with: P 1 (c) and P 2 (c) have a common sub-type different from an absurd type, referents or components of P 1 (c) and P 2 (c) conform to their most general common sub-type, and the referents of P 1 (c) and P 2 (c) are either equal, or one of the two is undefined, or f comp (P 1 (c), P 2 (c))=(true, P 1 (c), P 2 (c)). 7. The method according to claim 1 , wherein: { f merge ( true , c 1 , c 2 ) = f mer ( c 1 , c 2 ) = c f false ( true , c 1 , c 2 ) = Id ( c 1 , c 2 ) = ( c 1 , c 2 ) , where f mer : E×E→E is a function defined by an expert in the sector of application, cεE is the concept resulting from merging of c 1 and c 2 , and Id is an identity function defined on E ×E.
| 0.587762 |
16. A document separation system comprising: a processor; and a memory coupled to the processor, the memory storing processor executable instructions which, when executed by the processor cause the processor to: determine quality scores for a plurality of the documents in the set of related documents based on comparisons with a predetermined value; obtain a similarity score for a plurality of pairs of documents in the set of related document; and obtain a first subset of related documents which solves an optimization problem, the first subset of related documents being a subset of the set of related documents, the optimization problem being a function of one or more quality scores of the documents assigned to the first subset of related documents and one or more similarity scores of pairs of documents assigned to the first subset of related documents, wherein the optimization problem maximizes an evaluation function and wherein the evaluation function is: f ( A ) = ∑ v ∈ V u v ( v , A ( v ) ) + ∑ v 1 , v 2 ∈ E u E ( v 1 , v 2 , A ( v 1 ) , A ( v 2 ) ) where v is a document, A(v) is a labelling function which assigns a document, v, to either the first subset of related documents or a second subset of related documents, V is the set of related documents, u v (v,A(v)) is a function of the quality score of a document v, E is a set of all pairs of documents and u E (v 1 ,v 1 ,A(v 1 ),A(v 2 )) is a function of the similarly score between document v 1 and v 2 .
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16. A document separation system comprising: a processor; and a memory coupled to the processor, the memory storing processor executable instructions which, when executed by the processor cause the processor to: determine quality scores for a plurality of the documents in the set of related documents based on comparisons with a predetermined value; obtain a similarity score for a plurality of pairs of documents in the set of related document; and obtain a first subset of related documents which solves an optimization problem, the first subset of related documents being a subset of the set of related documents, the optimization problem being a function of one or more quality scores of the documents assigned to the first subset of related documents and one or more similarity scores of pairs of documents assigned to the first subset of related documents, wherein the optimization problem maximizes an evaluation function and wherein the evaluation function is: f ( A ) = ∑ v ∈ V u v ( v , A ( v ) ) + ∑ v 1 , v 2 ∈ E u E ( v 1 , v 2 , A ( v 1 ) , A ( v 2 ) ) where v is a document, A(v) is a labelling function which assigns a document, v, to either the first subset of related documents or a second subset of related documents, V is the set of related documents, u v (v,A(v)) is a function of the quality score of a document v, E is a set of all pairs of documents and u E (v 1 ,v 1 ,A(v 1 ),A(v 2 )) is a function of the similarly score between document v 1 and v 2 . 18. The document separation system of claim 16 , wherein the processor executable instructions, when executed, cause the processor to determine the quality score for a document based on the number of words or characters in that document.
| 0.71265 |
18. The medium of claim 17 , wherein the one or more existing gesture descriptors are determined to match the gesture descriptor based on a closeness tolerance between each of the one or more existing gesture descriptors and the gesture descriptor.
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18. The medium of claim 17 , wherein the one or more existing gesture descriptors are determined to match the gesture descriptor based on a closeness tolerance between each of the one or more existing gesture descriptors and the gesture descriptor. 20. The medium of claim 18 , wherein said returning comprises returning a plurality of identifiers; wherein a plurality of existing gesture descriptors corresponding to the plurality of identifiers are determined to be the plurality of existing gesture descriptors most closely matching the gesture descriptor based on a closeness tolerance between each of the plurality of existing gesture descriptors and the gesture descriptor; and wherein the software application accesses data associating identifiers with commands to determine a plurality of commands based on the plurality of returned identifiers and selects a command based on current contextual information associated with the software application.
| 0.754879 |
25. A method of restructuring a relational database having at least one relation, each said relation having a plurality of tuples, a set of attributes, a set of candidate keys and a set of non-key attributes; wherein each tuple is managed as a two-dimensional relation for each attribute and each relation has a candidate key serving as a set of attributes which can uniquely identify one of said tuples, comprising the steps of: a) checking, with reference to values of tuples which are present in the relations, whether a first set of attributes is functionally dependent on a second set of attributes; b) dividing a first relation into a second and a third relation by a projecting operation for a designated attribute set; c) performing said steps a) and b) in order to determine from attribute sets A and B which are included in said relation and are mutually primary, when said attribute set A is a proper subset of said set of candidate keys and when said attribute set B is a subset of a non-key attribute set serving as a subset of the candidate key; and d) performing said steps a) and b) when said attribute sets A and B are proper subsets of said non-key attribute set in said attribute sets A and B which are mutually primary and included in a relation.
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25. A method of restructuring a relational database having at least one relation, each said relation having a plurality of tuples, a set of attributes, a set of candidate keys and a set of non-key attributes; wherein each tuple is managed as a two-dimensional relation for each attribute and each relation has a candidate key serving as a set of attributes which can uniquely identify one of said tuples, comprising the steps of: a) checking, with reference to values of tuples which are present in the relations, whether a first set of attributes is functionally dependent on a second set of attributes; b) dividing a first relation into a second and a third relation by a projecting operation for a designated attribute set; c) performing said steps a) and b) in order to determine from attribute sets A and B which are included in said relation and are mutually primary, when said attribute set A is a proper subset of said set of candidate keys and when said attribute set B is a subset of a non-key attribute set serving as a subset of the candidate key; and d) performing said steps a) and b) when said attribute sets A and B are proper subsets of said non-key attribute set in said attribute sets A and B which are mutually primary and included in a relation. 28. A method according to claim 25, further comprising a step for detecting a predetermined character of attributes of said relation of said relational database,.. a step for informing a terminal of said detection results, a step for inputting an instruction from said terminal, a, step for converting, when a relation to be restructured of said relational database has a non-normal form, said non-normal form into a first normal form in accordance with the instruction.
| 0.660454 |
1. A computer-implemented method performed at a server system having one or more processors and memory, the method comprising: receiving a search query from a user; identifying search results associated with the search query; identifying a set of user-preferred search results that includes search results in a search history of the user, wherein each of the user-preferred search results has been previously selected by the user for at least a predefined minimum number of times; identifying in the search results, one or more search results, each of which is associated with a respective user-preferred search result; ordering the search results based at least in part on a popularity metric associated with each of the identified search results, wherein the popularity metric is a function of one or more parameters including at least one parameter that is a time span period from the user's most remote selection of the respective user-preferred search result to the user's most recent selection of the respective user-preferred search result; and providing the ordered search results to the user.
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1. A computer-implemented method performed at a server system having one or more processors and memory, the method comprising: receiving a search query from a user; identifying search results associated with the search query; identifying a set of user-preferred search results that includes search results in a search history of the user, wherein each of the user-preferred search results has been previously selected by the user for at least a predefined minimum number of times; identifying in the search results, one or more search results, each of which is associated with a respective user-preferred search result; ordering the search results based at least in part on a popularity metric associated with each of the identified search results, wherein the popularity metric is a function of one or more parameters including at least one parameter that is a time span period from the user's most remote selection of the respective user-preferred search result to the user's most recent selection of the respective user-preferred search result; and providing the ordered search results to the user. 5. The method of claim 1 , further comprising receiving the search history of the user from one or more client devices associated with the user.
| 0.717868 |
1. A computer-implemented method comprising: receiving a communication from a communicating user via an interface of a social networking system for communicating to social networking system users via the social networking system; identifying an anchor term in the communication, the anchor term having multiple meanings and identified based on a set of dictionary nodes each associated with a potential meaning of the anchor term, the set of dictionary nodes identified by querying a dictionary with the anchor term; identifying a set of candidate nodes based on the set of dictionary nodes from a dictionary that comprises a set of dictionary nodes, each dictionary node representing a topic, wherein each identified candidate node comprises a dictionary node that is a candidate for representing one of the multiple meanings of the anchor term; after identifying the anchor term, determining a score for each of one or more of the candidate nodes representative of a likelihood that the candidate node represents one of the multiple meanings of the anchor term based at least in part on terms other than the anchor term in communications that include the anchor term made by other users who are connected to the communicating user in the social networking system within a pre-determined interval of time immediately preceding identifying the anchor term; presenting one or more of the candidate nodes to the communicating user based on the determined scores; prompting the communicating user to select one of the presented candidate nodes to represent one of the multiple meanings of the anchor term; and responsive to receiving a candidate node selection from the communicating user, generating a post within a newsfeed including the received communication, the post associated with an object maintained by the social networking system representing the selected candidate node, the post including the anchor term in hyperlink text that, when selected, directs a user to a web page of the social networking system associated with the object.
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1. A computer-implemented method comprising: receiving a communication from a communicating user via an interface of a social networking system for communicating to social networking system users via the social networking system; identifying an anchor term in the communication, the anchor term having multiple meanings and identified based on a set of dictionary nodes each associated with a potential meaning of the anchor term, the set of dictionary nodes identified by querying a dictionary with the anchor term; identifying a set of candidate nodes based on the set of dictionary nodes from a dictionary that comprises a set of dictionary nodes, each dictionary node representing a topic, wherein each identified candidate node comprises a dictionary node that is a candidate for representing one of the multiple meanings of the anchor term; after identifying the anchor term, determining a score for each of one or more of the candidate nodes representative of a likelihood that the candidate node represents one of the multiple meanings of the anchor term based at least in part on terms other than the anchor term in communications that include the anchor term made by other users who are connected to the communicating user in the social networking system within a pre-determined interval of time immediately preceding identifying the anchor term; presenting one or more of the candidate nodes to the communicating user based on the determined scores; prompting the communicating user to select one of the presented candidate nodes to represent one of the multiple meanings of the anchor term; and responsive to receiving a candidate node selection from the communicating user, generating a post within a newsfeed including the received communication, the post associated with an object maintained by the social networking system representing the selected candidate node, the post including the anchor term in hyperlink text that, when selected, directs a user to a web page of the social networking system associated with the object. 10. The computer-implemented method of claim 1 , wherein identifying an anchor term in the communication comprises: parsing the communication into one or more terms, wherein each term comprises a set of alpha-numeric characters; and selecting one of the one or more parsed terms for use as the anchor term.
| 0.524558 |
14. A system for supporting migration of unstructured data stored in enterprise content management systems, comprising: memory operable to store unstructured data; and at least one hardware processor interoperably coupled to the memory and operable to: generate a search for the unstructured data matching at least one content search rule, the unstructured data comprising information that does not have a predefined data model, the at least one content search rule comprising an enterprise identifier and a document identifier and the at least one content search rule being retrieved from a migration engine server configured to provide support for migration of the unstructured data and structured data stored in an enterprise resource planning system; receive a list of matched documents, wherein each document in the list of matched documents comprises at least a portion of the unstructured data and is associated with at least a source repository identifier and a unique document identifier; calculate a target repository identifier and at least one metadata change instruction for each unique document identifier using at least one migration rule defining how the unstructured data is to be migrated to maintain an integrity of the unstructured data, the at least one migration rule being compliant with international regulations; and modify metadata for the document associated with the document identifier using the calculated at least one metadata change instruction to generate a modified copy of the document, the at least one metadata change instruction specifying that any matched content with a particular source repository identifier is to be modified to reflect a particular target repository identifier, the particular target repository identifier comprising at least one of a prefix and a suffix different from the particular source repository identifier and the at least one metadata change instruction specifying deletion of the metadata matching the particular source repository identifier from a source repository associated with the particular source repository identifier upon migration to a target repository associated with the particular target repository identifier.
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14. A system for supporting migration of unstructured data stored in enterprise content management systems, comprising: memory operable to store unstructured data; and at least one hardware processor interoperably coupled to the memory and operable to: generate a search for the unstructured data matching at least one content search rule, the unstructured data comprising information that does not have a predefined data model, the at least one content search rule comprising an enterprise identifier and a document identifier and the at least one content search rule being retrieved from a migration engine server configured to provide support for migration of the unstructured data and structured data stored in an enterprise resource planning system; receive a list of matched documents, wherein each document in the list of matched documents comprises at least a portion of the unstructured data and is associated with at least a source repository identifier and a unique document identifier; calculate a target repository identifier and at least one metadata change instruction for each unique document identifier using at least one migration rule defining how the unstructured data is to be migrated to maintain an integrity of the unstructured data, the at least one migration rule being compliant with international regulations; and modify metadata for the document associated with the document identifier using the calculated at least one metadata change instruction to generate a modified copy of the document, the at least one metadata change instruction specifying that any matched content with a particular source repository identifier is to be modified to reflect a particular target repository identifier, the particular target repository identifier comprising at least one of a prefix and a suffix different from the particular source repository identifier and the at least one metadata change instruction specifying deletion of the metadata matching the particular source repository identifier from a source repository associated with the particular source repository identifier upon migration to a target repository associated with the particular target repository identifier. 16. The system of claim 14 , the at least one hardware processor further operable to delete the modified metadata for the document from the source repository associated with the source repository identifier if the target repository identifier is different than the source repository identifier.
| 0.509838 |
1. A method of collecting information from users and aggregating it into a useful format, the method comprising: through a computer device and server computer in communication with each other: a. presenting a question to a subject user at the computer device; b. electronically recording, by the server computer, the subject user's free text response to the question; c. calculating a list of one or more prior free text responses from other subject users which may be equivalent to response of the subject user; d. presenting the calculated list of potentially-equivalent free text responses from other subject users to the subject user at the computer device; e. the subject user selecting if one or more prior responses on the list are equivalent to the subject user's response or if none on the list is equivalent; f. electronically recording, by the server computer, the subject user's selection of an equivalent response; g. calculating a selected list of responses to the question; h. re-presenting the question and the selected list of responses to the subject user at the computer device; i. electronically recording, by the server computer which response on the selected list the subject user selects as the best response to the question; such that responses from the subject user are collected and aggregated into the responses from other subject users in a manner resulting in information enhancing knowledge retention and learning.
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1. A method of collecting information from users and aggregating it into a useful format, the method comprising: through a computer device and server computer in communication with each other: a. presenting a question to a subject user at the computer device; b. electronically recording, by the server computer, the subject user's free text response to the question; c. calculating a list of one or more prior free text responses from other subject users which may be equivalent to response of the subject user; d. presenting the calculated list of potentially-equivalent free text responses from other subject users to the subject user at the computer device; e. the subject user selecting if one or more prior responses on the list are equivalent to the subject user's response or if none on the list is equivalent; f. electronically recording, by the server computer, the subject user's selection of an equivalent response; g. calculating a selected list of responses to the question; h. re-presenting the question and the selected list of responses to the subject user at the computer device; i. electronically recording, by the server computer which response on the selected list the subject user selects as the best response to the question; such that responses from the subject user are collected and aggregated into the responses from other subject users in a manner resulting in information enhancing knowledge retention and learning. 21. The method of claim 1 , wherein the correctness of the answer and its components is determined by one or more persons.
| 0.546845 |
21. A method performed by one or more server devices, the method comprising: identifying, by at least one of the one or more server devices, a blog document that is responsive to a search query; generating, by at least one of the one or more server devices, a first score for the blog document based on a relevance of the blog document to the search query; generating, by at least one of the one or more server devices, a second score for the blog document based on a quality of the blog document independent of the search query, where the second score is based on: a first indication of whether ads appear in a blogroll associated with the blog document or blog metadata associated with the blog document, and a second indication of whether ads appear in blog posts in the blog document; generating, by at least one of the one or more server devices, a third score based on the first and second scores; and providing, by at least one of the one or more server devices, information relating to the blog document based on the third score.
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21. A method performed by one or more server devices, the method comprising: identifying, by at least one of the one or more server devices, a blog document that is responsive to a search query; generating, by at least one of the one or more server devices, a first score for the blog document based on a relevance of the blog document to the search query; generating, by at least one of the one or more server devices, a second score for the blog document based on a quality of the blog document independent of the search query, where the second score is based on: a first indication of whether ads appear in a blogroll associated with the blog document or blog metadata associated with the blog document, and a second indication of whether ads appear in blog posts in the blog document; generating, by at least one of the one or more server devices, a third score based on the first and second scores; and providing, by at least one of the one or more server devices, information relating to the blog document based on the third score. 23. The method of claim 21 , where providing the information relating to the blog document includes: presenting information regarding the blog document and at least one other document in a first order that is based on the third score, where the first order is different from a second order that is solely based on the first score.
| 0.709139 |
15. A mobile device, comprising: a processor; and a computer readable memory in communication with the processor, the memory storing statements and instructions for execution by the processor to perform a method of converting a Shockwave Flash (SWF) shape definition, including a first plurality of directed edges having a first path style in common, into a first vector graphics path definition corresponding to the first path style, the method including: i) creating a first path style graph representation corresponding to the first path style, based on mapping the first plurality of directed edges of the SWF shape definition having the first path style in common to a first plurality of vertices and undirected edges, and generating and storing connectivity information relating to the first plurality of vertices and undirected edges such that each of the undirected edges is connected to at least two of the first plurality of vertices and such that each of the first plurality of vertices is connected to two of the undirected edges, the first path style graph representation including first path style information and a first graph representation; ii) creating a first vector graphics path by traversing undirected edges of a graph represented by the first graph representation and by removing an undirected edge, after the undirected edge has been traversed, from each edge set to which the traversed edge belongs; and iii) creating the first vector graphics path definition including the first vector graphics path and the first path style information.
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15. A mobile device, comprising: a processor; and a computer readable memory in communication with the processor, the memory storing statements and instructions for execution by the processor to perform a method of converting a Shockwave Flash (SWF) shape definition, including a first plurality of directed edges having a first path style in common, into a first vector graphics path definition corresponding to the first path style, the method including: i) creating a first path style graph representation corresponding to the first path style, based on mapping the first plurality of directed edges of the SWF shape definition having the first path style in common to a first plurality of vertices and undirected edges, and generating and storing connectivity information relating to the first plurality of vertices and undirected edges such that each of the undirected edges is connected to at least two of the first plurality of vertices and such that each of the first plurality of vertices is connected to two of the undirected edges, the first path style graph representation including first path style information and a first graph representation; ii) creating a first vector graphics path by traversing undirected edges of a graph represented by the first graph representation and by removing an undirected edge, after the undirected edge has been traversed, from each edge set to which the traversed edge belongs; and iii) creating the first vector graphics path definition including the first vector graphics path and the first path style information. 20. The mobile device of claim 15 wherein each edge set for a respective vertex is implemented as a linked list of edges connected to that vertex.
| 0.709276 |
12. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for selecting links while updating a probabilistic generative model for textual documents, the method comprising: receiving a current model, which contains terminal nodes representing words and cluster nodes representing clusters of conceptually related words, wherein nodes in the current model are coupled together by weighted links, wherein if a node fires, a link from the node to another node is activated and causes the other node to fire with a probability proportionate to the weight of the link; applying a set of training documents containing words to the current model to produce a new model, and while doing so, determining expected counts for activations of links and prospective links, determining link-ratings for the links and the prospective links based on the expected counts, and selecting links to be included in the new model based on the determined link-ratings; and making the new model the current model.
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12. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for selecting links while updating a probabilistic generative model for textual documents, the method comprising: receiving a current model, which contains terminal nodes representing words and cluster nodes representing clusters of conceptually related words, wherein nodes in the current model are coupled together by weighted links, wherein if a node fires, a link from the node to another node is activated and causes the other node to fire with a probability proportionate to the weight of the link; applying a set of training documents containing words to the current model to produce a new model, and while doing so, determining expected counts for activations of links and prospective links, determining link-ratings for the links and the prospective links based on the expected counts, and selecting links to be included in the new model based on the determined link-ratings; and making the new model the current model. 21. The computer-readable storage medium of claim 12 , wherein producing the new model additionally involves selectively deleting nodes from the new model.
| 0.641878 |
4. A system for generating a reference set for use during document review, comprising: a collection of unclassified documents; a clustering module to identify one or more features within each of the unclassified documents, to generate clusters of the features, and to select at least one feature from one or more of the clusters as reference set candidates; a classification module to assign a classification code to each reference set candidate; an identification module to refine the reference set candidates by grouping the reference set candidates into further clusters, selecting at least one of the reference set candidates in one or more of the further clusters, and assigning a classification code to the further reference set candidates; a data module to form a reference set from the unclassified documents associated with the further classified reference set candidates; and a processor to execute the modules.
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4. A system for generating a reference set for use during document review, comprising: a collection of unclassified documents; a clustering module to identify one or more features within each of the unclassified documents, to generate clusters of the features, and to select at least one feature from one or more of the clusters as reference set candidates; a classification module to assign a classification code to each reference set candidate; an identification module to refine the reference set candidates by grouping the reference set candidates into further clusters, selecting at least one of the reference set candidates in one or more of the further clusters, and assigning a classification code to the further reference set candidates; a data module to form a reference set from the unclassified documents associated with the further classified reference set candidates; and a processor to execute the modules. 5. A system according to claim 4 , further comprising: a refinement module to refine the reference set by reducing a number of reference set candidates included in the reference set.
| 0.589686 |
10. The mobile device of claim 7 , wherein the third switch provides a tactile response when any portion of the toggle key is pressed.
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10. The mobile device of claim 7 , wherein the third switch provides a tactile response when any portion of the toggle key is pressed. 11. The mobile device of claim 10 , wherein when the mobile device is in the telephony mode, the telephony character is input by engaging either the first switch or the second switch.
| 0.956868 |
30. The hardware computer readable storage media of claim 25 wherein rendering information comprises rendering an audible prompt to the user.
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30. The hardware computer readable storage media of claim 25 wherein rendering information comprises rendering an audible prompt to the user. 31. The hardware computer readable storage media of claim 30 wherein rendering information comprises rendering visual indications to the user.
| 0.951055 |
33. The apparatus of claim 31 , further comprising: a text-to-speech engine to play the emphasis-adjusted audio stream.
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33. The apparatus of claim 31 , further comprising: a text-to-speech engine to play the emphasis-adjusted audio stream. 34. The apparatus of claim 33 , wherein the method further comprises: (E) correcting errors in the document based on the emphasis-adjusted audio stream.
| 0.959194 |
7. The method of claim 5 , wherein said step of inserting or modifying statements further comprises the step of: inserting at least one of said statements at a subset of locations associated with an insecure variable.
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7. The method of claim 5 , wherein said step of inserting or modifying statements further comprises the step of: inserting at least one of said statements at a subset of locations associated with an insecure variable. 8. The method of claim 7 , wherein said subset of locations is determined by: determining a minimum fixing set associated with vulnerabilities identified by said verifying step.
| 0.896617 |
15. A system comprising: a processor; and a memory storing instructions that, when executed, cause the system to: receiving an image as a search query, the image being a first event; identifying search parameters in the search query that include first event attributes associated with the first event; identify a second event and second event attributes for the second event; and identify contextual information associated with a single activity; associate the first event and the second event as being associated with the single activity based on contextual information describing relatedness of the first and second event attributes; generate a task associated with completing the single activity for a user; and update the single activity based on a status change of the task.
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15. A system comprising: a processor; and a memory storing instructions that, when executed, cause the system to: receiving an image as a search query, the image being a first event; identifying search parameters in the search query that include first event attributes associated with the first event; identify a second event and second event attributes for the second event; and identify contextual information associated with a single activity; associate the first event and the second event as being associated with the single activity based on contextual information describing relatedness of the first and second event attributes; generate a task associated with completing the single activity for a user; and update the single activity based on a status change of the task. 20. The system of claim 15 wherein the memory also stores instructions that, when executed, cause the system to: identify a phone call, the phone call have a date and a time; and associate first event attributes with the phone call based in part on temporal locality of the date and time of the phone call and first event attributes.
| 0.581006 |
17. The system of claim 11 , wherein each word image is assigned to a word cluster based on its feature vector, by: calculating a distance between each one of the multiple word images and every other one of the multiple word images, based on feature vectors associated with those word images; selecting, from among the multiple word images, two of the word images that are closest in distance to each other; and assigning the two of the word images to the word cluster.
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17. The system of claim 11 , wherein each word image is assigned to a word cluster based on its feature vector, by: calculating a distance between each one of the multiple word images and every other one of the multiple word images, based on feature vectors associated with those word images; selecting, from among the multiple word images, two of the word images that are closest in distance to each other; and assigning the two of the word images to the word cluster. 18. The system of claim 17 , wherein the stored instructions further configure the system to: select, from among the multiple word images other than the assigned word images, an additional one of the multiple word images that is closest to the representative word image; assign the additional one of the word images to the word cluster; and repeat the foregoing elements until a predetermined number of the multiple word images have been assigned to the word cluster.
| 0.762104 |
2. The method of claim 1 , wherein determining the number of links pointing to the text file comprises: determining whether two links are pointing to the text file.
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2. The method of claim 1 , wherein determining the number of links pointing to the text file comprises: determining whether two links are pointing to the text file. 3. The method of claim 2 , wherein locking the data structure based on the number of links pointing to the text file comprises: locking the data structure in response to determining the number of links pointing to the text file is two.
| 0.955179 |
6. The method as claimed in claim 1 , including: receiving a query and processing the query to divide it into terms, including numerical terms; processing a numerical term of the query to a stem, the stem being in the form of a number, and a distance measurement of the numerical term to the stem, wherein a numerical term is a string of characters identified as a number by a numeric parser; and retrieving document results for the stem from an index.
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6. The method as claimed in claim 1 , including: receiving a query and processing the query to divide it into terms, including numerical terms; processing a numerical term of the query to a stem, the stem being in the form of a number, and a distance measurement of the numerical term to the stem, wherein a numerical term is a string of characters identified as a number by a numeric parser; and retrieving document results for the stem from an index. 8. The method as claimed in claim 6 , including scoring results by comparing the distance measurements of the query terms and the document results for the stem.
| 0.815948 |
1. A processor-based method for producing supplemental information for audio signature data, the method comprising: obtaining, by executing instructions with a processor, the audio signature data of a first time period, the audio signature data including data relating to at least one of time or frequency components representing a first characteristic of media; obtaining, by executing instructions with the processor, first semantic audio signature data for the first time period, the first semantic audio signature data being a measure of generalized information representing characteristics of the media; and storing, in a memory, the audio signature data of the first time period in association with a second time period when the processor determines, by executing instructions with the processor, that second semantic audio signature data for the second time period substantially matches the first semantic audio signature data for the first time period.
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1. A processor-based method for producing supplemental information for audio signature data, the method comprising: obtaining, by executing instructions with a processor, the audio signature data of a first time period, the audio signature data including data relating to at least one of time or frequency components representing a first characteristic of media; obtaining, by executing instructions with the processor, first semantic audio signature data for the first time period, the first semantic audio signature data being a measure of generalized information representing characteristics of the media; and storing, in a memory, the audio signature data of the first time period in association with a second time period when the processor determines, by executing instructions with the processor, that second semantic audio signature data for the second time period substantially matches the first semantic audio signature data for the first time period. 7. The method of claim 1 , wherein the first semantic audio signature data is generated by transforming an audio signal of the media from a time domain to a frequency domain.
| 0.713775 |
9. An apparatus for printing documents, comprising: an obtaining module configured to obtain a name of a color document; a retrieving module configured to retrieve printing step information for the color document according to the name of the color document, and configured to determine whether the printing step information for the color document is complete, wherein the printing step information comprises information on processes of rasterization, halftoning, and realization of the halftone dots that applied to the color document; and a printing module configured to print the color document according to the printing step information in the case that the printing step information for the color document is complete.
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9. An apparatus for printing documents, comprising: an obtaining module configured to obtain a name of a color document; a retrieving module configured to retrieve printing step information for the color document according to the name of the color document, and configured to determine whether the printing step information for the color document is complete, wherein the printing step information comprises information on processes of rasterization, halftoning, and realization of the halftone dots that applied to the color document; and a printing module configured to print the color document according to the printing step information in the case that the printing step information for the color document is complete. 10. The apparatus for printing documents according to claim 9 , further comprising: a processing module configured to process the color document to obtain printing step information in the case that the printing step information for the color document is not complete.
| 0.5 |
1. A computer-implemented method comprising: retrieving a markup language document including server side script code specified using personalme page (PHP) syntax, wherein the server side script code is for execution on a server in response to a request for the markup language document; generating C++ code from the server side script code, wherein the generated C++ code comprises: one or more C++ classes comprising code corresponding to the server side script code, one or more C++ header files storing information describing structures of the C++ classes, and code for memory allocation of objects instantiated from the C++ classes; and compiling the generated C++ code to object code, wherein the object code is invoked for processing the markup language document.
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1. A computer-implemented method comprising: retrieving a markup language document including server side script code specified using personalme page (PHP) syntax, wherein the server side script code is for execution on a server in response to a request for the markup language document; generating C++ code from the server side script code, wherein the generated C++ code comprises: one or more C++ classes comprising code corresponding to the server side script code, one or more C++ header files storing information describing structures of the C++ classes, and code for memory allocation of objects instantiated from the C++ classes; and compiling the generated C++ code to object code, wherein the object code is invoked for processing the markup language document. 9. The computer-implemented method of claim 1 , wherein the code for memory allocation allocates a set of multiple objects of the same size.
| 0.819693 |
8. An information handling device, comprising: a processor; a display device operatively coupled to the processor; a memory device that stores instructions executable by the processor to: receive a plurality of handwriting ink strokes, wherein the plurality of handwriting ink strokes comprise a first subset of ink strokes and a second subset of ink strokes; determine at least one grouping of the plurality of handwriting ink strokes, wherein the at least one grouping is determined using spacing associated with the plurality of handwriting ink strokes and comparing at least one attribute associated with at least one portion of the first subset of ink strokes to at least one attribute associated with at least one portion of the second subset of ink strokes; wherein, if the at least one attribute associated with at least one portion of the first subset of ink strokes is similar to the at least one attribute associated with at least one portion of the second subset of ink strokes, the at least one grouping comprises the first subset of ink strokes and the second subset of ink strokes; wherein, if the at least one attribute associated with at least one portion of the first subset of ink strokes is different than the at least one attribute associated with at least one portion of the second subset of ink strokes, the at least one grouping comprises a subset of ink strokes selected from the group consisting of: the first subset of ink strokes and the second subset of ink strokes; send the at least one grouping to a recognition engine; receive machine input from the recognition engine; and display, on the display device, the machine input.
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8. An information handling device, comprising: a processor; a display device operatively coupled to the processor; a memory device that stores instructions executable by the processor to: receive a plurality of handwriting ink strokes, wherein the plurality of handwriting ink strokes comprise a first subset of ink strokes and a second subset of ink strokes; determine at least one grouping of the plurality of handwriting ink strokes, wherein the at least one grouping is determined using spacing associated with the plurality of handwriting ink strokes and comparing at least one attribute associated with at least one portion of the first subset of ink strokes to at least one attribute associated with at least one portion of the second subset of ink strokes; wherein, if the at least one attribute associated with at least one portion of the first subset of ink strokes is similar to the at least one attribute associated with at least one portion of the second subset of ink strokes, the at least one grouping comprises the first subset of ink strokes and the second subset of ink strokes; wherein, if the at least one attribute associated with at least one portion of the first subset of ink strokes is different than the at least one attribute associated with at least one portion of the second subset of ink strokes, the at least one grouping comprises a subset of ink strokes selected from the group consisting of: the first subset of ink strokes and the second subset of ink strokes; send the at least one grouping to a recognition engine; receive machine input from the recognition engine; and display, on the display device, the machine input. 11. The information handling device of claim 8 , wherein the instructions are further executable by the processor to receive at least one handwriting ink stroke adjacent to a machine input.
| 0.531978 |
10. A non-transitory, machine-readable medium that stores instructions, which, when performed by a machine, cause the machine to perform operations comprising: retrieving data definitions defining types of a plurality of business objects stored in enterprise data, the data definitions specify one or more attributes for each of the types of the plurality of business objects; generating, based at least in part on the data definitions, a meta-model of the enterprise data, the meta-model provides semantic information characterizing conceptual meaning to the one or more attributes; using the meta-model of the enterprise data to generate a rule definition that maps the enterprise data to the semantic information; using the rule definition to generate at least one semantic object and at least one semantic relation from the plurality of business objects stored in the enterprise data; and storing the at least one semantic object and the at least one semantic relation in a meta-model semantic network, the meta-model semantic network associating a term to the at least one semantic object.
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10. A non-transitory, machine-readable medium that stores instructions, which, when performed by a machine, cause the machine to perform operations comprising: retrieving data definitions defining types of a plurality of business objects stored in enterprise data, the data definitions specify one or more attributes for each of the types of the plurality of business objects; generating, based at least in part on the data definitions, a meta-model of the enterprise data, the meta-model provides semantic information characterizing conceptual meaning to the one or more attributes; using the meta-model of the enterprise data to generate a rule definition that maps the enterprise data to the semantic information; using the rule definition to generate at least one semantic object and at least one semantic relation from the plurality of business objects stored in the enterprise data; and storing the at least one semantic object and the at least one semantic relation in a meta-model semantic network, the meta-model semantic network associating a term to the at least one semantic object. 13. The non-transitory, machine-readable medium of claim 10 , further comprising: receiving a message with a search query; identifying a relevant term in the search query; identifying that the at least one semantic relation is associated with the search query; searching the meta-model semantic network for semantic objects linked to the relevant term according to the at least one semantic relation; and communicating the semantic objects in a search result.
| 0.509009 |
1. An aid for teaching word pronunciation comprising: a set of alphabetical letters in material form, said letters being arrangeable to form words; at least one of said letters having a structural distinction from other letters in said set, in addition to conventional differences of alphabetic configuration; said structural distinction selected from a group of at least three structural distinctions, each distinction denoting a particular pronunciation of said letter in the formed word; one of said distinctions being that the letter is transparent, to denote that the letter is silent in the formed word; another of said distinctions being that the letter is of a greater height than the other letters, to denote that the letter is to be pronounced with a long vowel sound; still another of said distinctions being that the letter is in the shape of an object, to denote that the letter is to be pronounced as in the word for the depicted object.
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1. An aid for teaching word pronunciation comprising: a set of alphabetical letters in material form, said letters being arrangeable to form words; at least one of said letters having a structural distinction from other letters in said set, in addition to conventional differences of alphabetic configuration; said structural distinction selected from a group of at least three structural distinctions, each distinction denoting a particular pronunciation of said letter in the formed word; one of said distinctions being that the letter is transparent, to denote that the letter is silent in the formed word; another of said distinctions being that the letter is of a greater height than the other letters, to denote that the letter is to be pronounced with a long vowel sound; still another of said distinctions being that the letter is in the shape of an object, to denote that the letter is to be pronounced as in the word for the depicted object. 11. A teaching aid in accordance with claim 1 wherein said set of alphabetical letters includes the letter O of annular structure defining a central opening bridged by a vertical bar and bearing indicia representation of the numeral one in conjunction with the periphery of said vertical bar to denote its pronunciation as being that of the letter O in the word ONCE.
| 0.5 |
1. A computer-implemented method comprising steps of: from a workload set, automatically selecting a plurality of database query language statements for automatic tuning, wherein the workload set comprises multiple database query language statements and performance data for the multiple database query language statements; automatically tuning the plurality of database query language statements until one or more time periods are reached or exceeded, thereby generating a plurality of tuning recommendations for a subset of database query language statements of said plurality of database query language statements, each tuning recommendation of said plurality of tuning recommendations being a tuning recommendation for a database query language statement of said subset of database query language statements; automatically testing the plurality of tuning recommendations against a database, wherein testing the plurality of tuning recommendations comprises, for one or more tuning recommendations of said plurality of tuning recommendations, automatically executing a particular database query language statement from said subset of database query language statements with said one or more tuning recommendations enabled thereby automatically generating an execution plan for the particular database query language statement based on said one or more tuning recommendations enabled for testing and automatically testing said execution plan against one or more other alternative execution plans for the particular database query language statement generated based on enabling, for testing, one or more other tuning recommendations from the plurality of tuning recommendations; based at least in part on automatically testing the plurality of tuning recommendations against the database, automatically implementing at least one tuning recommendation of said plurality of tuning recommendations and not implementing at least another tuning recommendation of said plurality of tuning recommendations; and wherein the steps are performed by one or more computing devices.
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1. A computer-implemented method comprising steps of: from a workload set, automatically selecting a plurality of database query language statements for automatic tuning, wherein the workload set comprises multiple database query language statements and performance data for the multiple database query language statements; automatically tuning the plurality of database query language statements until one or more time periods are reached or exceeded, thereby generating a plurality of tuning recommendations for a subset of database query language statements of said plurality of database query language statements, each tuning recommendation of said plurality of tuning recommendations being a tuning recommendation for a database query language statement of said subset of database query language statements; automatically testing the plurality of tuning recommendations against a database, wherein testing the plurality of tuning recommendations comprises, for one or more tuning recommendations of said plurality of tuning recommendations, automatically executing a particular database query language statement from said subset of database query language statements with said one or more tuning recommendations enabled thereby automatically generating an execution plan for the particular database query language statement based on said one or more tuning recommendations enabled for testing and automatically testing said execution plan against one or more other alternative execution plans for the particular database query language statement generated based on enabling, for testing, one or more other tuning recommendations from the plurality of tuning recommendations; based at least in part on automatically testing the plurality of tuning recommendations against the database, automatically implementing at least one tuning recommendation of said plurality of tuning recommendations and not implementing at least another tuning recommendation of said plurality of tuning recommendations; and wherein the steps are performed by one or more computing devices. 12. The computer-implemented method of claim 1 , wherein said automatically selecting the plurality of database query language statements for automatic tuning, said automatically tuning the plurality of database query language statements, and said automatically testing the plurality of tuning recommendations against the database are performed until a certain time period, of the one or more time periods, is reached.
| 0.570466 |
1. A word processor device on which a page of a textual document can be composed and edited, and in which textual data representing said page can be temporarily stored and the stored textual data transferred to and from magnetic tape wound on a tape cassette, the word processor device being a unitary and integral device and comprising: keyboard means integrally formed with said word processor device for manually entering said textual data and for entering word processing commands; information buffer means integrally formed with said word processor device and connected to said keyboard means for temporarily storing one page of said textual data; character display means integrally formed with said word processor device for visually displaying at least a portion of the page of textual data stored in said information buffer means; cassette recorder apparatus integrally formed with said word processor device for transferring said one page of said textual data between said information buffer means and the magnetic tape of said tape cassette, the latter containing any such pages of transferred textual data in sequential order; and signal processing means for controlling the operation of said information buffer means and said cassette recorder apparatus for transferring said page of textual data to said magnetic tape in response to a word processing command entered on said keyboard means, and also transferring a stored page of said textual data from said magnetic tape to said information buffer means in response to another command entered on said keyboard means; said keyboard means, said information buffer means, said cassette recorder apparatus, said signal processing means, and said character display means integrally forming said word processor device being arranged in a size, shape and weight that is personally portable.
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1. A word processor device on which a page of a textual document can be composed and edited, and in which textual data representing said page can be temporarily stored and the stored textual data transferred to and from magnetic tape wound on a tape cassette, the word processor device being a unitary and integral device and comprising: keyboard means integrally formed with said word processor device for manually entering said textual data and for entering word processing commands; information buffer means integrally formed with said word processor device and connected to said keyboard means for temporarily storing one page of said textual data; character display means integrally formed with said word processor device for visually displaying at least a portion of the page of textual data stored in said information buffer means; cassette recorder apparatus integrally formed with said word processor device for transferring said one page of said textual data between said information buffer means and the magnetic tape of said tape cassette, the latter containing any such pages of transferred textual data in sequential order; and signal processing means for controlling the operation of said information buffer means and said cassette recorder apparatus for transferring said page of textual data to said magnetic tape in response to a word processing command entered on said keyboard means, and also transferring a stored page of said textual data from said magnetic tape to said information buffer means in response to another command entered on said keyboard means; said keyboard means, said information buffer means, said cassette recorder apparatus, said signal processing means, and said character display means integrally forming said word processor device being arranged in a size, shape and weight that is personally portable. 2. A word processor device according to claim 1, wherein said signal processing means includes a microprocessor including a permanent storage device containing steps for controlling the transfer of said textual data, a control unit for controlling the transfer of said data in response to said stored program steps, keyboard interface means coupled to said keyboard means to process data and commands entered on said keyboard; recorder interface means coupled to said cassette recorder apparatus to control operation thereof and to receive data for transfer to and from said magnetic tape; and data bus means linking said permanent storage device, said control unit, said keyboard interface means, said recorder interface means, and said information buffer means.
| 0.5 |
13. A computer readable non-transitory storage medium embodying instructions executed by a plurality of processors for updating a probabilistic process model (PPM) of a semi-structured business process, the method comprising: receiving the PPM and at least one probability distribution corresponding to a decision node of the PPM, wherein the received PPM includes all possible execution sequences of the semi-structured business process, wherein the received PPM is generated from a process model (PM) and a probabilistic graph including a probability, at each and every task of the semi-structured business process, for advancing to each of the other tasks of the semi-structured business process, and wherein the PM is derived from execution traces generated by one or more computer system elements generated during execution of a plurality of tasks of a semi-structured business process; receiving a status and content of an executing case instance of the business process; and updating at least one probability of the PPM using the probability distribution and the received status and content of said executing case instance of the business process.
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13. A computer readable non-transitory storage medium embodying instructions executed by a plurality of processors for updating a probabilistic process model (PPM) of a semi-structured business process, the method comprising: receiving the PPM and at least one probability distribution corresponding to a decision node of the PPM, wherein the received PPM includes all possible execution sequences of the semi-structured business process, wherein the received PPM is generated from a process model (PM) and a probabilistic graph including a probability, at each and every task of the semi-structured business process, for advancing to each of the other tasks of the semi-structured business process, and wherein the PM is derived from execution traces generated by one or more computer system elements generated during execution of a plurality of tasks of a semi-structured business process; receiving a status and content of an executing case instance of the business process; and updating at least one probability of the PPM using the probability distribution and the received status and content of said executing case instance of the business process. 14. The computer readable storage medium of claim 13 , wherein updating further comprises mapping the PPM to an extended probabilistic process model with additional nodes representing states achievable through parallel paths in the PPM.
| 0.764733 |
11. A computer readable medium storing computer instructions that are executable by a processor to: create one or more new target database images for each of a group of backup datasets, wherein the backup datasets include data from one or more source databases associated with an application server operating on a first host, wherein at least one of the one or more source databases is hosted on a remote source host separate from the first host; register a client with the application server, wherein the client is installed on a backup host and is configured to: store a seed document in each of the one or more new target database images, wherein said seed documents are Lotus® replication notes and said replication request is a Lotus® replication request; and modify each seed document to specify which portions of a backup dataset in said group are to be stored in each corresponding new target database image; receive a backup request; in response to determining the backup request corresponds to an incremental backup request: sending a replication request to said client, the replication request including a formula that indicates which data should be replicated; the client activating each seed document in said one or more new target database images, wherein said activating comprises conveying a filter to each said seed document; each said seed document sending a selective replication request based upon parameters of the filter to a given server responsive to the seed document being activated; and the given server replicating a filtered portion of each database for which a replication request is received, thereby updating said one or more new target database images, wherein archive logging is not used for replication.
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11. A computer readable medium storing computer instructions that are executable by a processor to: create one or more new target database images for each of a group of backup datasets, wherein the backup datasets include data from one or more source databases associated with an application server operating on a first host, wherein at least one of the one or more source databases is hosted on a remote source host separate from the first host; register a client with the application server, wherein the client is installed on a backup host and is configured to: store a seed document in each of the one or more new target database images, wherein said seed documents are Lotus® replication notes and said replication request is a Lotus® replication request; and modify each seed document to specify which portions of a backup dataset in said group are to be stored in each corresponding new target database image; receive a backup request; in response to determining the backup request corresponds to an incremental backup request: sending a replication request to said client, the replication request including a formula that indicates which data should be replicated; the client activating each seed document in said one or more new target database images, wherein said activating comprises conveying a filter to each said seed document; each said seed document sending a selective replication request based upon parameters of the filter to a given server responsive to the seed document being activated; and the given server replicating a filtered portion of each database for which a replication request is received, thereby updating said one or more new target database images, wherein archive logging is not used for replication. 14. The computer readable medium of claim 11 , wherein to update each new target database image, the instructions are further executable by a processor to synchronize the new target database images with data from the source databases excluding at least a portion of the data specified in the information used to modify the seed document.
| 0.61435 |
2. The medium as in claim 1 , wherein the grouping of resources is a grouping of documents, the instructions, when executed by the processing device, further enabling the processing device to perform operations of: calculating a first ranking of terms for the first set of resources, the first ranking indicating a relative importance of distinctive terms contained in each document in the first set of resources; and calculating a second ranking of terms for the second set of resources, the second ranking indicating a relative importance of distinctive terms contained in each document in the second set of resources.
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2. The medium as in claim 1 , wherein the grouping of resources is a grouping of documents, the instructions, when executed by the processing device, further enabling the processing device to perform operations of: calculating a first ranking of terms for the first set of resources, the first ranking indicating a relative importance of distinctive terms contained in each document in the first set of resources; and calculating a second ranking of terms for the second set of resources, the second ranking indicating a relative importance of distinctive terms contained in each document in the second set of resources. 3. The medium as in claim 2 , the instructions, when executed by the processing device, further enabling the processing device to perform the operations of: comparing terms in the first ranking with the terms in the second ranking; and in response to the comparing, determining a similarity value indicative of a relative similarity among the terms in the first ranking and the terms in the second ranking.
| 0.898605 |
1. A method for selective decryption within an encrypted document, said method comprising: detecting an encrypted portion of a document, said encrypted portion having been selected and marked for decryption, said encrypted portion being an encryption of a text portion of the document, said text portion comprising a known character string that had been added to the text portion prior to the text portion being encrypted; receiving a selection of a valid key configured to decrypt the encrypted portion; ascertaining that an attempt to convert the encrypted portion into a decrypted portion of the document by decrypting the encrypted portion using the valid key was successful, said ascertaining comprising determining that the decrypted portion includes the known character string; in response to said ascertaining, removing the known character string from the decrypted portion; and after said removing the known character string, displaying the encrypted portion.
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1. A method for selective decryption within an encrypted document, said method comprising: detecting an encrypted portion of a document, said encrypted portion having been selected and marked for decryption, said encrypted portion being an encryption of a text portion of the document, said text portion comprising a known character string that had been added to the text portion prior to the text portion being encrypted; receiving a selection of a valid key configured to decrypt the encrypted portion; ascertaining that an attempt to convert the encrypted portion into a decrypted portion of the document by decrypting the encrypted portion using the valid key was successful, said ascertaining comprising determining that the decrypted portion includes the known character string; in response to said ascertaining, removing the known character string from the decrypted portion; and after said removing the known character string, displaying the encrypted portion. 6. The method of claim 1 , wherein said receiving the selection of a valid key comprises: presenting to a user an identification of a plurality of keys previously entered to open a corresponding plurality of documents; and receiving from the user the selection of the valid key from the plurality of keys.
| 0.81432 |
1. A method performed by a device to filter objectionable material, from a multimedia program including plural segments, on a segment-by-segment basis responsive to a filter criteria, comprising: providing a learning module to generate the filter criteria learned based on user instructions by examples of objectionable content; splitting the multimedia program into plural components; extracting audio, video, and transcript features from segments within the plural components; processing each segment amongst the segments, according to the learned filter criteria generated by the learning module and the extracted features, and generating a numeric ranking corresponding to the filter criteria learned based on the user instructions by examples of objectionable content and applied to the segment; and when the respective numeric ranking for the segment exceeds a threshold, processing the segment to thereby eliminate material corresponding to the learned filter criteria.
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1. A method performed by a device to filter objectionable material, from a multimedia program including plural segments, on a segment-by-segment basis responsive to a filter criteria, comprising: providing a learning module to generate the filter criteria learned based on user instructions by examples of objectionable content; splitting the multimedia program into plural components; extracting audio, video, and transcript features from segments within the plural components; processing each segment amongst the segments, according to the learned filter criteria generated by the learning module and the extracted features, and generating a numeric ranking corresponding to the filter criteria learned based on the user instructions by examples of objectionable content and applied to the segment; and when the respective numeric ranking for the segment exceeds a threshold, processing the segment to thereby eliminate material corresponding to the learned filter criteria. 4. The method as recited in claim 1 , wherein: the filter criteria corresponds to an image included in the segment being processed; and the entire segment is skipped during the processing step.
| 0.671856 |
2. The method of claim 1 , wherein the method further comprises: identifying a set of source sentences in each of the documents; and constructing a language-independent semantic structure (LISS) for each source sentence of the identified set of source sentences, wherein said estimating the similarity value between the first and the second documents includes a comparison of the LISS's of the first document with the LISS's of the second document.
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2. The method of claim 1 , wherein the method further comprises: identifying a set of source sentences in each of the documents; and constructing a language-independent semantic structure (LISS) for each source sentence of the identified set of source sentences, wherein said estimating the similarity value between the first and the second documents includes a comparison of the LISS's of the first document with the LISS's of the second document. 4. The method of claim 2 , wherein the method further comprises: displaying through a user interface a portion of the first document and a portion of the second document; identifying fragments of the first and the second documents that are related to said similarity value; and aligning in the user interface the identified fragments with respect to each other and with respect to the user interface.
| 0.720155 |
23. A method by which a physical-document monitoring device facilitates management of a physical document, the method comprising: sensing a state of the physical document, with a sensor coupled to a document coupling device; generating a signal representing the document state with the sensor; determining the document state based on the signal with a computer coupled to the sensor and the document coupling device; and generating a wireless signal to send a representation of the document state to a remote device.
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23. A method by which a physical-document monitoring device facilitates management of a physical document, the method comprising: sensing a state of the physical document, with a sensor coupled to a document coupling device; generating a signal representing the document state with the sensor; determining the document state based on the signal with a computer coupled to the sensor and the document coupling device; and generating a wireless signal to send a representation of the document state to a remote device. 28. The method of claim 23 , wherein the document state comprises the location of the document.
| 0.617391 |
1. A method for selecting at least one product record for embedding into a document and display with the document in a user interface, the method comprising: analyzing, with a computing device, at least a portion of the document, the analysis including at least a frequency of words in the document; constructing, with a computing device, a keyword query search string based on the analysis of the document, the keyword query search string at least partially based on words of the document having the highest frequencies; applying, with a computing device, the keyword query search string to a products database, the products database including a plurality of product records which include information regarding products, to identify at least one product record in the products database that satisfies the keyword query search string; selecting, with a computing device, at least one of the identified product records for embedding into the document and display in the user interface, and embedding, with a computing device, at least one of the selected product records into the document for display in the user interface, wherein the document is not stored within the products database.
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1. A method for selecting at least one product record for embedding into a document and display with the document in a user interface, the method comprising: analyzing, with a computing device, at least a portion of the document, the analysis including at least a frequency of words in the document; constructing, with a computing device, a keyword query search string based on the analysis of the document, the keyword query search string at least partially based on words of the document having the highest frequencies; applying, with a computing device, the keyword query search string to a products database, the products database including a plurality of product records which include information regarding products, to identify at least one product record in the products database that satisfies the keyword query search string; selecting, with a computing device, at least one of the identified product records for embedding into the document and display in the user interface, and embedding, with a computing device, at least one of the selected product records into the document for display in the user interface, wherein the document is not stored within the products database. 12. The method of claim 1 , wherein said selected product records are displayed in the user interface.
| 0.532651 |
1. A system for providing continuous automated verification of user identity and intent, comprising: at least one server for communicating with a network; at least one network interface card associated with the at least one server for providing access to data flow through the network; a processor within each of the at least one server, the processor implementing a first processing node and a second processing node for: monitoring, prior to granting at least one user access to the network, at the first processing node associated with the network, a mirrored live-data flow of a live-data flow passing through the first processing node in a non-intrusive manner that does not affect the live-data flow passing through the first processing node, wherein the live-data flow comprises data that is in active transmission between endpoints in the network and prior to storage of the data within the live-data flow in a database; detecting relevant network access and activity in the mirrored live data flow; dynamically generating a first set of verification criteria at the second processing node based on live data inputs from the mirrored live-data flow and external data sources to verify an identify and an activity of the at least one user attempting to access the network prior to access and performing an activity on the network, wherein the first set of verification criteria comprise a first set of dynamically generated dialogue of questions with associated answers to be provided by the at least one user; dynamically generating a second set of verification criteria at the second processing node based on the responses provided by the at least one user to the first set of dynamically generated dialogue of questions to verify the identity and the activity of the at least one user attempting to access the network, wherein the second set of verification criteria comprise a second set of dynamically generated dialogue of questions with associated answers to be provided by the at least one user; dynamically adjusting a required threshold level at which the first and second verification criteria must be met by the at least one user attempting the network access in order to allow or deny the network access and activity by the at least one user; denying the relevant network access and activity if the verification criteria are not met at the required threshold level, to preempt unverified and unwanted access to and activity on the network by the at least one user; allowing the relevant network access and activity if the verification criteria are met at the required threshold level; and continuing to monitor and verify the user identity and the user activity for a dynamic time period after access and activity on the network is granted, to ensure continued user identity and activity fidelity.
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1. A system for providing continuous automated verification of user identity and intent, comprising: at least one server for communicating with a network; at least one network interface card associated with the at least one server for providing access to data flow through the network; a processor within each of the at least one server, the processor implementing a first processing node and a second processing node for: monitoring, prior to granting at least one user access to the network, at the first processing node associated with the network, a mirrored live-data flow of a live-data flow passing through the first processing node in a non-intrusive manner that does not affect the live-data flow passing through the first processing node, wherein the live-data flow comprises data that is in active transmission between endpoints in the network and prior to storage of the data within the live-data flow in a database; detecting relevant network access and activity in the mirrored live data flow; dynamically generating a first set of verification criteria at the second processing node based on live data inputs from the mirrored live-data flow and external data sources to verify an identify and an activity of the at least one user attempting to access the network prior to access and performing an activity on the network, wherein the first set of verification criteria comprise a first set of dynamically generated dialogue of questions with associated answers to be provided by the at least one user; dynamically generating a second set of verification criteria at the second processing node based on the responses provided by the at least one user to the first set of dynamically generated dialogue of questions to verify the identity and the activity of the at least one user attempting to access the network, wherein the second set of verification criteria comprise a second set of dynamically generated dialogue of questions with associated answers to be provided by the at least one user; dynamically adjusting a required threshold level at which the first and second verification criteria must be met by the at least one user attempting the network access in order to allow or deny the network access and activity by the at least one user; denying the relevant network access and activity if the verification criteria are not met at the required threshold level, to preempt unverified and unwanted access to and activity on the network by the at least one user; allowing the relevant network access and activity if the verification criteria are met at the required threshold level; and continuing to monitor and verify the user identity and the user activity for a dynamic time period after access and activity on the network is granted, to ensure continued user identity and activity fidelity. 26. The system of claim 1 , wherein the processor implements the first processing node and the second processing node for dynamically adjusting by correlating live-data network inputs at the first processing node with network and external data sources at the second processing node, the live-data network inputs including but not limited to keywords in network transmissions, volume and patterns in network activity and mobile money transfers, patterns in transmissions to and from users and to and from locations and endpoints.
| 0.522828 |
1. A method for extensibility of binding definitions for a user interface application comprising: executing a program by a computer system that transforms the computer system into a machine that performs: obtaining an extensible markup language (XML) framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to bind a user interface object to an underlying object, wherein the application is incompatible with the first grammar level; performing a first extensible style sheet (XSL) transformation of the framework to generate the first set of rules for interpretation of the binding specifications in the first grammar level; performing a second XSL transformation of the framework to generate a first presentation style for the first grammar level; obtaining the binding specification in the first grammar level, the binding specification conforming to the first set of rules; and applying the first set of rules and the first presentation style to the binding specification to generate output binding specifications in a second grammar level compatible with the application.
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1. A method for extensibility of binding definitions for a user interface application comprising: executing a program by a computer system that transforms the computer system into a machine that performs: obtaining an extensible markup language (XML) framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to bind a user interface object to an underlying object, wherein the application is incompatible with the first grammar level; performing a first extensible style sheet (XSL) transformation of the framework to generate the first set of rules for interpretation of the binding specifications in the first grammar level; performing a second XSL transformation of the framework to generate a first presentation style for the first grammar level; obtaining the binding specification in the first grammar level, the binding specification conforming to the first set of rules; and applying the first set of rules and the first presentation style to the binding specification to generate output binding specifications in a second grammar level compatible with the application. 3. The method of claim 1 , wherein the first transformation is in accordance with a third presentation style.
| 0.874142 |
1. One or more computer-readable media usable to determine a password, the computer-readable media comprising instructions, executable by a processor, for: generating words, one after another, the words each having at least one character position, each word being generated by selecting characters, one after another, for each character position of the word from a character string for the respective character position, each character string: being stored in memory; comprising a plurality of permissible characters that may be used in the password, the order of the characters in the character string being individually selected for each character position of the word based on a frequency that each character occurs at the respective character position in words in a database, such that the characters in each character string are ordered from most frequent occurrence at the respective character position to least frequent occurrence at the respective character position and each character string begins with a permissible character most frequently used in the words in the database at the respective position and ends with a permissible character least frequently used in the words in the database at the respective position; and entering each generated word, one after another and based on an order in which the words are generated, until the password is determined.
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1. One or more computer-readable media usable to determine a password, the computer-readable media comprising instructions, executable by a processor, for: generating words, one after another, the words each having at least one character position, each word being generated by selecting characters, one after another, for each character position of the word from a character string for the respective character position, each character string: being stored in memory; comprising a plurality of permissible characters that may be used in the password, the order of the characters in the character string being individually selected for each character position of the word based on a frequency that each character occurs at the respective character position in words in a database, such that the characters in each character string are ordered from most frequent occurrence at the respective character position to least frequent occurrence at the respective character position and each character string begins with a permissible character most frequently used in the words in the database at the respective position and ends with a permissible character least frequently used in the words in the database at the respective position; and entering each generated word, one after another and based on an order in which the words are generated, until the password is determined. 7. The one or more computer-readable media of claim 1 , wherein each character string comprises at least two of lower-case letters, capital letters, numbers, spaces, and symbols.
| 0.563009 |
5. The database system of claim 1 , wherein the at least one processor is further operable to cause: when the state of the post is editable: processing an edit request indicating at least one requested edit to the post; and editing the post to reflect the at least one requested edit, the edited post configured to be shared in at least one feed of the social networking system.
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5. The database system of claim 1 , wherein the at least one processor is further operable to cause: when the state of the post is editable: processing an edit request indicating at least one requested edit to the post; and editing the post to reflect the at least one requested edit, the edited post configured to be shared in at least one feed of the social networking system. 6. The database system of claim 5 , wherein the at least one requested edit comprises at least one of: a change to content of the post, a change to a header of the post, a change to data associated with and apart from the post, an association of a link with the post, an association of a file with the post, or a change to a file associated with the post.
| 0.890259 |
6. A computer-implemented method to expand a set of seeds while applying a dynamic threshold of relatedness, the method comprising: receiving from a web query log a set of terms with contexts and one or more identified seeds, wherein the seeds are terms that are related to a concept for which to identify additional related terms from the set of terms; modeling the received terms and seeds as a bipartite graph with candidate terms being nodes on one side and identified context nodes on the other side by dividing each query into a context of a fixed number of tokens of prefix or suffix and a remaining term; determining a relevance score for each term based on the identified seeds; ranking the received set of terms by the determined relevance score; selecting an initial threshold ranking value for separating terms in the set related to the seeds from terms not related to the seeds; picking a top ranked number of terms above a threshold from the ranked set of terms based on the selected initial threshold to form a new set; determining a quality measurement that identifies how well each term relates to the picked threshold number of terms in the new set; ranking the terms in the new set based on the determined quality measurement; selecting a next threshold to use to separate terms in the new set related to the seeds from terms not related to the seeds; using the selected next threshold to select a threshold number of terms from the ranked new set; repeating the steps of determining the quality measurement, ranking the terms, and selecting a threshold number of terms for a determined number of iterations; and reporting the resulting expanded seed set that includes the terms in the received set that are the highest quality matches to the received seeds, wherein the preceding steps are performed by at least one processor.
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6. A computer-implemented method to expand a set of seeds while applying a dynamic threshold of relatedness, the method comprising: receiving from a web query log a set of terms with contexts and one or more identified seeds, wherein the seeds are terms that are related to a concept for which to identify additional related terms from the set of terms; modeling the received terms and seeds as a bipartite graph with candidate terms being nodes on one side and identified context nodes on the other side by dividing each query into a context of a fixed number of tokens of prefix or suffix and a remaining term; determining a relevance score for each term based on the identified seeds; ranking the received set of terms by the determined relevance score; selecting an initial threshold ranking value for separating terms in the set related to the seeds from terms not related to the seeds; picking a top ranked number of terms above a threshold from the ranked set of terms based on the selected initial threshold to form a new set; determining a quality measurement that identifies how well each term relates to the picked threshold number of terms in the new set; ranking the terms in the new set based on the determined quality measurement; selecting a next threshold to use to separate terms in the new set related to the seeds from terms not related to the seeds; using the selected next threshold to select a threshold number of terms from the ranked new set; repeating the steps of determining the quality measurement, ranking the terms, and selecting a threshold number of terms for a determined number of iterations; and reporting the resulting expanded seed set that includes the terms in the received set that are the highest quality matches to the received seeds, wherein the preceding steps are performed by at least one processor. 11. The method of claim 6 wherein ranking the received terms comprises invoking a sorting function that orders the terms by the determined relevance scores.
| 0.657423 |
1. A computer-implemented method of analyzing a clinical decision support (CDS) document and improving content analyzer system accuracy, the method comprising: improving content analyzer system accuracy in identifying CDS document deficiencies and consistencies with respect to reference content, the reference content comprising clinical guidelines, by repeatedly training a machine learning module, hosted by a content analyzer system, based on new incoming data, wherein the machine learning module is configured to automatically determine which content features are to be used to determine whether content is to be designated as relevant and matching to the reference content and which content is to be designated as non-relevant and to construct or modify an electronic model accordingly, wherein the features comprise one or more of text length, presence of a medication term, medical intervention language, use of a negation, or context, wherein improving content analyzer system accuracy by training the machine learning module comprises repeatedly: collecting positive and negative cases from CDS documents, training the electronic model using the collected positive and negative cases from CDS documents, taking as input a text segment extracted from a CDS document and returning a likelihood that the text segment matches a reference checklist item, and wherein the new incoming data indicates whether the likelihood that the text segment matches a reference checklist item is correct or incorrect; receiving at a computer system, including hardware and comprising an analytics engine, a clinical decision support document from a medical service provider system; accessing over a network from a remote system, by the computer system, reference content corresponding at least in part to the clinical decision support document, the reference content comprising clinical guidelines; using, by the computer system, the electronic model to identify and extract medical intervention content from the clinical decision support document; using feedback with respect to the identification of the medical intervention content to refine the electronic model; segmenting, by the computer system, at least a portion of the extracted medical intervention content into a first plurality of segments including: at least a first segment, comprising a first set of text, and a second segment comprising a second set of text, wherein a given segment in the first plurality of segments is evaluated to identify a core concept, wherein identifying the core concept further comprises determining whether a given segment includes a plurality of medications, and determining which of the plurality of medications are part of the core concept and which of the plurality of medications are not part of the core concept, and if the core concept of the given segment comprises at least one a medical intervention, determining whether a negation is associated with the at least one medical intervention; determining, by the trained machine learning engine, if the first segment corresponds to at least a first item included in the reference content, the first item comprising a third set of text comprising terminology not present in the first and second sets of text; at least partly in response to determining that the first segment, comprising the first set of text, corresponds to the first item included in the reference content, the first item comprising the third set of text, causing a version of the clinical decision support document to be generated to include a visual indication that the first segment corresponds to the first item included in the reference content; determining, by the trained machine learning engine, if a second item included in the reference content corresponds to at least one of the first plurality of segments; at least partly in response to determining that the second item included in the reference content does not correspond to at least one of the first plurality of segments, causing the version of the clinical decision support document to be generated to include a visual indication that the first plurality of segments fails to include at least one segment that corresponds to the second item included in the reference content; and at least partly in response to determining that the second item included in the reference content does correspond to at least one of the first plurality of segments, causing the version of the clinical decision support document to include a visual indication that the second item corresponds to at least one segment in the first plurality of segments.
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1. A computer-implemented method of analyzing a clinical decision support (CDS) document and improving content analyzer system accuracy, the method comprising: improving content analyzer system accuracy in identifying CDS document deficiencies and consistencies with respect to reference content, the reference content comprising clinical guidelines, by repeatedly training a machine learning module, hosted by a content analyzer system, based on new incoming data, wherein the machine learning module is configured to automatically determine which content features are to be used to determine whether content is to be designated as relevant and matching to the reference content and which content is to be designated as non-relevant and to construct or modify an electronic model accordingly, wherein the features comprise one or more of text length, presence of a medication term, medical intervention language, use of a negation, or context, wherein improving content analyzer system accuracy by training the machine learning module comprises repeatedly: collecting positive and negative cases from CDS documents, training the electronic model using the collected positive and negative cases from CDS documents, taking as input a text segment extracted from a CDS document and returning a likelihood that the text segment matches a reference checklist item, and wherein the new incoming data indicates whether the likelihood that the text segment matches a reference checklist item is correct or incorrect; receiving at a computer system, including hardware and comprising an analytics engine, a clinical decision support document from a medical service provider system; accessing over a network from a remote system, by the computer system, reference content corresponding at least in part to the clinical decision support document, the reference content comprising clinical guidelines; using, by the computer system, the electronic model to identify and extract medical intervention content from the clinical decision support document; using feedback with respect to the identification of the medical intervention content to refine the electronic model; segmenting, by the computer system, at least a portion of the extracted medical intervention content into a first plurality of segments including: at least a first segment, comprising a first set of text, and a second segment comprising a second set of text, wherein a given segment in the first plurality of segments is evaluated to identify a core concept, wherein identifying the core concept further comprises determining whether a given segment includes a plurality of medications, and determining which of the plurality of medications are part of the core concept and which of the plurality of medications are not part of the core concept, and if the core concept of the given segment comprises at least one a medical intervention, determining whether a negation is associated with the at least one medical intervention; determining, by the trained machine learning engine, if the first segment corresponds to at least a first item included in the reference content, the first item comprising a third set of text comprising terminology not present in the first and second sets of text; at least partly in response to determining that the first segment, comprising the first set of text, corresponds to the first item included in the reference content, the first item comprising the third set of text, causing a version of the clinical decision support document to be generated to include a visual indication that the first segment corresponds to the first item included in the reference content; determining, by the trained machine learning engine, if a second item included in the reference content corresponds to at least one of the first plurality of segments; at least partly in response to determining that the second item included in the reference content does not correspond to at least one of the first plurality of segments, causing the version of the clinical decision support document to be generated to include a visual indication that the first plurality of segments fails to include at least one segment that corresponds to the second item included in the reference content; and at least partly in response to determining that the second item included in the reference content does correspond to at least one of the first plurality of segments, causing the version of the clinical decision support document to include a visual indication that the second item corresponds to at least one segment in the first plurality of segments. 13. The method as defined in claim 1 , the method further comprising using a pattern matching engine and/or a machine learning engine to identify content that is to be included in the first plurality of segments.
| 0.743568 |
1. A method comprising: identifying, by one or more processors, one or more particular terms, of a plurality of terms, in a search query; forming, by the one or more processors and based on identifying the one or more particular terms, another search query; obtaining, by the one or more processors, first context data that includes a first set of documents returned for the search query and second context data that includes a second set of documents returned for the other search query; comparing, by the one or more processors, information associated with the first set of documents returned for the search query and information associated with the second set of documents returned for the other search query; determining, by the one or more processors and based on the comparing, that the first context data and the second context data are different; and storing, by the one or more processors and based on the determining, information indicating that the search query and the other search query are associated with different context data.
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1. A method comprising: identifying, by one or more processors, one or more particular terms, of a plurality of terms, in a search query; forming, by the one or more processors and based on identifying the one or more particular terms, another search query; obtaining, by the one or more processors, first context data that includes a first set of documents returned for the search query and second context data that includes a second set of documents returned for the other search query; comparing, by the one or more processors, information associated with the first set of documents returned for the search query and information associated with the second set of documents returned for the other search query; determining, by the one or more processors and based on the comparing, that the first context data and the second context data are different; and storing, by the one or more processors and based on the determining, information indicating that the search query and the other search query are associated with different context data. 3. The method of claim 1 , where, when forming the other search query, the method includes: forming a plurality of other queries, each query, of the plurality of other queries, including a respective combination of the plurality of terms, and each query, of the plurality of other queries, including a respective set of the one or more particular terms, each respective set being different.
| 0.518487 |
18. A computer-readable storage medium containing instructions for controlling a computer system to receive, determine, and display an airport taxi route for a vehicle, by a method comprising: receiving an input text string representing at least a portion of the airport taxi route from a text input component on board the vehicle, the input text string having multiple text characters; parsing a first substring and a second substring from the input text string, the first substring and the second substring each having at least one text character; determining a first matching route component corresponding to the first substring; determining a second matching route component corresponding to the second substring; adding the first matching route component and the second matching route component to the airport taxi route; and displaying the airport taxi route on a display device on board the vehicle.
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18. A computer-readable storage medium containing instructions for controlling a computer system to receive, determine, and display an airport taxi route for a vehicle, by a method comprising: receiving an input text string representing at least a portion of the airport taxi route from a text input component on board the vehicle, the input text string having multiple text characters; parsing a first substring and a second substring from the input text string, the first substring and the second substring each having at least one text character; determining a first matching route component corresponding to the first substring; determining a second matching route component corresponding to the second substring; adding the first matching route component and the second matching route component to the airport taxi route; and displaying the airport taxi route on a display device on board the vehicle. 25. The computer-readable storage medium of claim 18 , the method further comprising determining at least one of a starting point, an intermediate point, or an ending point for the airport taxi route using aircraft position, navigation information, system information, or ATC clearance information.
| 0.767496 |
1. A method comprising, by a computing device: receiving, from a client system of a first user, a text query inputted by the first user at a query field of a currently accessed interface of an online social network; generating a plurality of structured queries based on the text query, each structured query comprising one or more query tokens, wherein one or more of the query tokens are unique query tokens comprising references to one or more unique objects associated with the online social network, respectively; generating one or more search results corresponding to at least one of the structured queries; and sending, to the client system responsive to receiving the text query, instructions for displaying one or more suggested queries on the interface, wherein the one or more suggested queries correspond to one or more structured queries, respectively, at least one of the suggested queries being displayed with a preview of one or more search results matching the structured query corresponding to the suggested query, and wherein each suggested query that is displayed is selectable by the first user to retrieve search results matching the structured query corresponding to the selected suggested query.
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1. A method comprising, by a computing device: receiving, from a client system of a first user, a text query inputted by the first user at a query field of a currently accessed interface of an online social network; generating a plurality of structured queries based on the text query, each structured query comprising one or more query tokens, wherein one or more of the query tokens are unique query tokens comprising references to one or more unique objects associated with the online social network, respectively; generating one or more search results corresponding to at least one of the structured queries; and sending, to the client system responsive to receiving the text query, instructions for displaying one or more suggested queries on the interface, wherein the one or more suggested queries correspond to one or more structured queries, respectively, at least one of the suggested queries being displayed with a preview of one or more search results matching the structured query corresponding to the suggested query, and wherein each suggested query that is displayed is selectable by the first user to retrieve search results matching the structured query corresponding to the selected suggested query. 7. The method of claim 1 , further comprising: receiving from the first user a selection of one of the structured queries, wherein search results are generated for at least the selected structured query, and wherein the preview of the search results is displayed with the selected structured query.
| 0.548464 |
3. The computer-implemented system of claim 2 , further comprising means for selecting one or more of grouped predicates for ungrouping.
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3. The computer-implemented system of claim 2 , further comprising means for selecting one or more of grouped predicates for ungrouping. 4. The computer-implemented system of claim 3 , further comprising means, responsive to grouped predicate selection, for removing the indications of grouping from the first display area.
| 0.933681 |
15. A system for layout decomposition, comprising: a coloring graph generation unit configured to derive data of a coloring graph from layout data for a layout design, the layout design corresponding to at least a portion of an integrated circuit, the layout data comprising mask assignment information for some layout features, the coloring graph comprising vertices representing layout features in the layout design and edges between some pairs of vertices indicating the mask assignment information; a graph reduction unit configured to perform performing a graph reduction process, wherein the graph reduction process comprises collapsing diamond graphs; a graph partitioning unit configured to perform a graph partitioning process; a layout decomposition unit configured to decompose the layout design based on a simplified coloring graph generated by the graph reduction unit and/or the graph partitioning unit to generate decomposition information; and storing the decomposition information.
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15. A system for layout decomposition, comprising: a coloring graph generation unit configured to derive data of a coloring graph from layout data for a layout design, the layout design corresponding to at least a portion of an integrated circuit, the layout data comprising mask assignment information for some layout features, the coloring graph comprising vertices representing layout features in the layout design and edges between some pairs of vertices indicating the mask assignment information; a graph reduction unit configured to perform performing a graph reduction process, wherein the graph reduction process comprises collapsing diamond graphs; a graph partitioning unit configured to perform a graph partitioning process; a layout decomposition unit configured to decompose the layout design based on a simplified coloring graph generated by the graph reduction unit and/or the graph partitioning unit to generate decomposition information; and storing the decomposition information. 17. The system recited in claim 15 , wherein the graph partitioning process comprises: separating subgraphs connected by one or two edges, separating biconnected components, or both.
| 0.711368 |
34. A system comprising: one or more processors; memory; one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving a text input, the text input associated with an input context; determining, using a first language model, a first frequency of occurrence of an m-gram with respect to a first subset of a corpus, wherein the first subset is associated with a first context, and wherein the m-gram includes at least one word in the text input; determining, based on a degree of similarity between the input context and the first context, a first weighting factor, wherein a weighted first frequency of occurrence of the m-gram is obtained by applying the first weighting factor to the first frequency of occurrence of the m-gram; determining, using the first language model, a second frequency of occurrence of the m-gram with respect to a second subset of the corpus, wherein the second subset is associated with a second context; and determining, based on a degree of similarity between the input context and the second context, a second weighting factor, wherein a weighted second frequency of occurrence of the m-gram is obtained by applying the second weighting factor to the second frequency of occurrence of the m-gram; determining, based on the weighted first frequency of occurrence of the m-gram and the weighted second frequency of occurrence of the m-gram, a first weighted probability of a first predicted text given the text input, wherein the m-gram includes at least one word in the first predicted text.
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34. A system comprising: one or more processors; memory; one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving a text input, the text input associated with an input context; determining, using a first language model, a first frequency of occurrence of an m-gram with respect to a first subset of a corpus, wherein the first subset is associated with a first context, and wherein the m-gram includes at least one word in the text input; determining, based on a degree of similarity between the input context and the first context, a first weighting factor, wherein a weighted first frequency of occurrence of the m-gram is obtained by applying the first weighting factor to the first frequency of occurrence of the m-gram; determining, using the first language model, a second frequency of occurrence of the m-gram with respect to a second subset of the corpus, wherein the second subset is associated with a second context; and determining, based on a degree of similarity between the input context and the second context, a second weighting factor, wherein a weighted second frequency of occurrence of the m-gram is obtained by applying the second weighting factor to the second frequency of occurrence of the m-gram; determining, based on the weighted first frequency of occurrence of the m-gram and the weighted second frequency of occurrence of the m-gram, a first weighted probability of a first predicted text given the text input, wherein the m-gram includes at least one word in the first predicted text. 37. The system of claim 34 , wherein the first language model includes a plurality of sub-models arranged in a hierarchical context tree, and wherein each sub-model is associated with a specific context.
| 0.571072 |
1. A computer-implemented method comprising: using a geoparser engine to identify one or more potential geographic references within a document, and to generate respective geotags associated with the identified geographic references; determining to display on a visual display device a visual representation of the geotags along with the associated geographic references; providing a user interface that facilitates one or more of a change of at least one of the displayed geotags, and a specification of one or more additional geographic references within the document and of additional respective geotags associated with the additional geographic references; and determining to send the one or more of the change(s) to the displayed geotags, and the specification of additional geographic references and additional respective geotags to the geoparser engine for one or more of display on the visual display device within the visual representation and future use by the geoparser engine; wherein each of the geotags includes a relevance, parameter for assessing a pertinence of the geotag with respect to the document, or a confidence parameter for assessing a relevance of the geotag with respect to the associated geographic reference, or a combination thereof.
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1. A computer-implemented method comprising: using a geoparser engine to identify one or more potential geographic references within a document, and to generate respective geotags associated with the identified geographic references; determining to display on a visual display device a visual representation of the geotags along with the associated geographic references; providing a user interface that facilitates one or more of a change of at least one of the displayed geotags, and a specification of one or more additional geographic references within the document and of additional respective geotags associated with the additional geographic references; and determining to send the one or more of the change(s) to the displayed geotags, and the specification of additional geographic references and additional respective geotags to the geoparser engine for one or more of display on the visual display device within the visual representation and future use by the geoparser engine; wherein each of the geotags includes a relevance, parameter for assessing a pertinence of the geotag with respect to the document, or a confidence parameter for assessing a relevance of the geotag with respect to the associated geographic reference, or a combination thereof. 5. The method of claim 1 , wherein an enabled change includes changing a location to which the geotag refers.
| 0.895833 |
5. The method according to claim 3 , wherein determining that the HTML tag matches a tag ruler element in the tag ruler comprises: acquiring a tag ruler element in the tag ruler according to the sequence of the tag ruler elements in the tag ruler; searching for an HTML tag identical with the tag ruler element in the HTML text; saving the location of the HTML tag in the HTML text; and determining that the latter HTML tag of identical HTML tags is matched when information between the adjacent locations of the identical HTML tags does not comprise a tag ruler element in the tag ruler.
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5. The method according to claim 3 , wherein determining that the HTML tag matches a tag ruler element in the tag ruler comprises: acquiring a tag ruler element in the tag ruler according to the sequence of the tag ruler elements in the tag ruler; searching for an HTML tag identical with the tag ruler element in the HTML text; saving the location of the HTML tag in the HTML text; and determining that the latter HTML tag of identical HTML tags is matched when information between the adjacent locations of the identical HTML tags does not comprise a tag ruler element in the tag ruler. 6. The method according to claim 5 , wherein saving the web information segments and the location information of the HTML tags enclosing the web information segments in the HTML text comprises: saving the web information segments and the location information of the HTML tags enclosing the web information segments in the HTML text in a stack; and the method further comprises: popping out all information in the stack when an HTML tag is unmatched.
| 0.776396 |
1. A method, comprising: (a) receiving a digital image of a document associated with a document type, the digital image including a plurality of black and white pixels arranged in rows; (b) locating at least two predefined portions of the digital image; (c) calculating an area confidence level for each of the predefined portions of the digital image as a function of a total number of black pixels located in the predefined portion relative to an expected number of black pixels for the predefined portion; (d) calculating a text confidence level as a function of a total number of pixel groups relative to a total number of characters, wherein each pixel group comprises a set of touching black pixels and each character comprises one or more pixel groups, wherein calculating the text confidence level comprises: subtracting the total number of characters from the total number of pixel groups to produce a first quantity, dividing the first quantity by the total number characters to produce a second quantity, and subtracting the second quantity from 1 to produce the text confidence level, and if the text confidence level is negative, setting the text confidence level equal to 0; (e) calculating an image profile confidence level as a function of a black pixel distribution and a black pixel density; (f) calculating an overall image confidence level as a function of the area confidence level, the text confidence level, and the image profile confidence level; and (g) storing the digital image as a result of determining that the overall image confidence level is greater than or equal to a threshold value associated with the document type of the image.
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1. A method, comprising: (a) receiving a digital image of a document associated with a document type, the digital image including a plurality of black and white pixels arranged in rows; (b) locating at least two predefined portions of the digital image; (c) calculating an area confidence level for each of the predefined portions of the digital image as a function of a total number of black pixels located in the predefined portion relative to an expected number of black pixels for the predefined portion; (d) calculating a text confidence level as a function of a total number of pixel groups relative to a total number of characters, wherein each pixel group comprises a set of touching black pixels and each character comprises one or more pixel groups, wherein calculating the text confidence level comprises: subtracting the total number of characters from the total number of pixel groups to produce a first quantity, dividing the first quantity by the total number characters to produce a second quantity, and subtracting the second quantity from 1 to produce the text confidence level, and if the text confidence level is negative, setting the text confidence level equal to 0; (e) calculating an image profile confidence level as a function of a black pixel distribution and a black pixel density; (f) calculating an overall image confidence level as a function of the area confidence level, the text confidence level, and the image profile confidence level; and (g) storing the digital image as a result of determining that the overall image confidence level is greater than or equal to a threshold value associated with the document type of the image. 6. The method of claim 1 , wherein calculating the image profile confidence level comprises: calculating a standard deviation of the black pixel distribution in each row; calculating the black pixel density as a ratio of a total number of black pixels in an image area to a total number of pixels in the image area; and setting the image profile confidence level equal to the smaller of (i) a function of the standard deviation and (ii) a function of the black pixel density.
| 0.534637 |
3. The system of claim 2 , wherein the web server is configured to receive the query and a setting mode from the web browser, to transfer the query and the setting mode to the query autocompletion server, to receive the at least one autocomplete recommended word according to the query and the setting mode from the query autocompletion server, and to transmit the at least one autocomplete recommended word to the web browser.
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3. The system of claim 2 , wherein the web server is configured to receive the query and a setting mode from the web browser, to transfer the query and the setting mode to the query autocompletion server, to receive the at least one autocomplete recommended word according to the query and the setting mode from the query autocompletion server, and to transmit the at least one autocomplete recommended word to the web browser. 4. The system of claim 3 , wherein the setting mode comprises selection information about at least one of a prefix index of the consonant/vowel unit, a prefix index of the syllable unit, and a suffix index of the syllable unit, and wherein the query autocompletion server is configured to determine the at least one autocomplete recommended word from the recommended word index database using the selected index.
| 0.844299 |
1. A computer-implemented method for restricting access to a telephone call management system, said method comprising the steps of: during a registration process by a user of said telephone call management system: prompting the user to speak one or more predetermined keywords; receiving a first speech sample from said user; verifying said first speech sample is indicative of said one or more predetermined keywords using speaker independent voice recognition; and associating said verified first speech sample with said user and storing said verified first speech sample in a database; and during each subsequent access attempt by said user to said telephone call management system to place a telephone: prompting said user for a second speech sample; determining whether a voice characteristic of said second speech sample matches a voice characteristic of said verified first speech sample; allowing said telephone call to be completed when the voice characteristic of said second speech sample matches the voice characteristic of said verified first speech sample; and after the allowing said telephone call to be completed, sampling voice data from said telephone call to detect if an unauthorized person has spoken based on the voice characteristic of the verified first speech sample.
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1. A computer-implemented method for restricting access to a telephone call management system, said method comprising the steps of: during a registration process by a user of said telephone call management system: prompting the user to speak one or more predetermined keywords; receiving a first speech sample from said user; verifying said first speech sample is indicative of said one or more predetermined keywords using speaker independent voice recognition; and associating said verified first speech sample with said user and storing said verified first speech sample in a database; and during each subsequent access attempt by said user to said telephone call management system to place a telephone: prompting said user for a second speech sample; determining whether a voice characteristic of said second speech sample matches a voice characteristic of said verified first speech sample; allowing said telephone call to be completed when the voice characteristic of said second speech sample matches the voice characteristic of said verified first speech sample; and after the allowing said telephone call to be completed, sampling voice data from said telephone call to detect if an unauthorized person has spoken based on the voice characteristic of the verified first speech sample. 2. A method according to claim 1 , further comprising: during the registration process by said user of said telephone call management system: assigning an identification to said user; associating said identification with said first speech sample in said database; during the each subsequent access attempt by said user to said telephone call management system to place said telephone call: receiving said identification from said user; and locating said first speech sample in said database using said identification.
| 0.502345 |
12. A method in accordance with claim 1 , wherein: the psychological state of the person is at least one of anger, anxiety, depression, emotional withdrawal, lack of flexibility, impulsiveness and emotional instability.
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12. A method in accordance with claim 1 , wherein: the psychological state of the person is at least one of anger, anxiety, depression, emotional withdrawal, lack of flexibility, impulsiveness and emotional instability. 16. A method in accordance with claim 12 , wherein the computer analysis is of only a single computer communication of the person.
| 0.960467 |
21. The apparatus of claim 20 , where the text window is associated with an application that differs from at least one of the first and the second applications.
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21. The apparatus of claim 20 , where the text window is associated with an application that differs from at least one of the first and the second applications. 23. The apparatus of claim 21 , where the text window is associated with a handwriting recognition function.
| 0.940994 |
15. An apparatus comprising: one or more processors and a memory; input means for receiving, from a user interface, an annotation associated with a background image; control means for adding the annotation to a queue of pending annotations; output means for transmitting the annotation from the apparatus to a server; wherein the control means removes the annotation from the queue of pending annotations, and adds the annotation to a list of acknowledged annotations, when an acknowledgment of the annotation is received by the apparatus from the server; wherein the output means generates a display image comprising the background image, annotations in the list of acknowledged annotations, and annotations in the queue of pending annotations; and wherein the one or more processors and the memory cooperate to implement at least in part the input, output and control means.
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15. An apparatus comprising: one or more processors and a memory; input means for receiving, from a user interface, an annotation associated with a background image; control means for adding the annotation to a queue of pending annotations; output means for transmitting the annotation from the apparatus to a server; wherein the control means removes the annotation from the queue of pending annotations, and adds the annotation to a list of acknowledged annotations, when an acknowledgment of the annotation is received by the apparatus from the server; wherein the output means generates a display image comprising the background image, annotations in the list of acknowledged annotations, and annotations in the queue of pending annotations; and wherein the one or more processors and the memory cooperate to implement at least in part the input, output and control means. 21. The apparatus of claim 15 : wherein the output means generates an acknowledged annotation image comprising the background image, and the annotations in the list of acknowledged annotations; and wherein the output means generates the display image based on the acknowledged annotation image and the annotations in the queue of pending annotations.
| 0.522998 |
11. A system for optimizing a query in a multi-tenant database system, the system comprising: a processor; and one or more stored sequences of instructions which, when executed by the processor, cause the processor to: receiving a query request with a query predicate to filter data returned in response to the query request, wherein the query predicate comprises a formula; generating an index corresponding to one tenant of the multi-tenant database system; preprocessing the formula in the query predicate based upon the generated index for the tenant to create a transformed query request, wherein the preprocessing includes: applying the generated index to a database field referenced in the formula, replacing at least one reference to a database field within the formula with a reference to a second database field based upon the generated index; and optimizing the query request using the transformed query request, receiving a query request with a reference to a first database field in the query predicate, wherein the first database field comprises the formula in the query predicate, wherein the formula comprises a reference to a second database field; and transforming the query request to a transformed query request by replacing the reference to the first database field within the query request with at least one reference to the second database field.
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11. A system for optimizing a query in a multi-tenant database system, the system comprising: a processor; and one or more stored sequences of instructions which, when executed by the processor, cause the processor to: receiving a query request with a query predicate to filter data returned in response to the query request, wherein the query predicate comprises a formula; generating an index corresponding to one tenant of the multi-tenant database system; preprocessing the formula in the query predicate based upon the generated index for the tenant to create a transformed query request, wherein the preprocessing includes: applying the generated index to a database field referenced in the formula, replacing at least one reference to a database field within the formula with a reference to a second database field based upon the generated index; and optimizing the query request using the transformed query request, receiving a query request with a reference to a first database field in the query predicate, wherein the first database field comprises the formula in the query predicate, wherein the formula comprises a reference to a second database field; and transforming the query request to a transformed query request by replacing the reference to the first database field within the query request with at least one reference to the second database field. 12. The system for optimizing a query in a database system of claim 11 , wherein the one or more stored sequences of instructions which, when executed by the processor, cause the processor to further carry out: preprocessing the formula by performing an inverse function on a function within the formula.
| 0.5 |
8. The method of claim 1 , wherein calculating a score for each transfer mapping in the set of transfer mappings that describe a select node of the input semantic structure comprises: computing separate scores for a plurality of models; and combining the separate scores to determine the score for each transfer mapping that describe a select node of the input semantic structure.
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8. The method of claim 1 , wherein calculating a score for each transfer mapping in the set of transfer mappings that describe a select node of the input semantic structure comprises: computing separate scores for a plurality of models; and combining the separate scores to determine the score for each transfer mapping that describe a select node of the input semantic structure. 13. The method of claim 8 and further comprising: computing a rank score for each transfer mapping that describe a select node of the input semantic structure, the rank score based on a number of matching binary features in the input semantic structure and the input semantic side of each transfer mapping; and combining the rank score with the separate scores for the plurality of models to determine the score for each transfer mapping that describe a select node of the input semantic structure.
| 0.755548 |
1. A system for processing natural language utterances, comprising: a computing device having access to a plurality of domain agents associated with a plurality of different domains, and programmed to execute one or more computer program instructions which, when executed, cause the computing device to: receive a first natural language utterance; determine that the first natural language utterance contains one or more words that were unrecognized or incorrectly recognized in response to a recognition associated with the first natural language utterance having a confidence level below a predetermined value; obtain a phonetic alphabet spelling associated with the one or more unrecognized or incorrectly recognized words in response to the determination; look up the one or more unrecognized or incorrectly recognized words in one or more dictionary and phrase tables based on the phonetic alphabet spelling; update the one or more dictionary and phrase tables based on a pronunciation associated with the one or more unrecognized or incorrectly recognized words; receive a second natural language utterance that comprises a question; generate a digitized speech signal from the second natural language utterance; recognize one or more words in the second natural language utterance based on a pronunciation associated with the one or more words using the one or more dictionary and phrase tables; tag the one or more words in the second natural language utterance with a user identity determined from voice characteristics associated with the digitized speech signal and one or more user profiles; determine a context of the question in the second natural language utterance; select one of the plurality of domain agents based on the context of the question; generate a request associated with the second natural language utterance based on the one or more words in the second natural language utterance and a grammar used by the selected domain agent, wherein the request includes the question; invoke the selected domain agent to cause the selected domain agent to process the request; and receive a response to the request from the selected domain agent.
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1. A system for processing natural language utterances, comprising: a computing device having access to a plurality of domain agents associated with a plurality of different domains, and programmed to execute one or more computer program instructions which, when executed, cause the computing device to: receive a first natural language utterance; determine that the first natural language utterance contains one or more words that were unrecognized or incorrectly recognized in response to a recognition associated with the first natural language utterance having a confidence level below a predetermined value; obtain a phonetic alphabet spelling associated with the one or more unrecognized or incorrectly recognized words in response to the determination; look up the one or more unrecognized or incorrectly recognized words in one or more dictionary and phrase tables based on the phonetic alphabet spelling; update the one or more dictionary and phrase tables based on a pronunciation associated with the one or more unrecognized or incorrectly recognized words; receive a second natural language utterance that comprises a question; generate a digitized speech signal from the second natural language utterance; recognize one or more words in the second natural language utterance based on a pronunciation associated with the one or more words using the one or more dictionary and phrase tables; tag the one or more words in the second natural language utterance with a user identity determined from voice characteristics associated with the digitized speech signal and one or more user profiles; determine a context of the question in the second natural language utterance; select one of the plurality of domain agents based on the context of the question; generate a request associated with the second natural language utterance based on the one or more words in the second natural language utterance and a grammar used by the selected domain agent, wherein the request includes the question; invoke the selected domain agent to cause the selected domain agent to process the request; and receive a response to the request from the selected domain agent. 8. The system according to claim 1 , wherein to process the request, the plurality of domain agents are each configured to: query one or more local or remote information sources in response to determining that the request includes the question.
| 0.563282 |
1. A method for representing user interaction with a web service comprising: acquiring a representation of actions of a user performing multiple iterations of a task with the web service; analyzing the acquired actions to determine semantics and a plurality of variables describing the user actions, each variable being an input to the web service that the web service requests the user to enter during the multiple iterations of the task, the variables comprising free variables and bound variables, where which of the variables are the free variables and which of the variables are the bound variables is determined automatically without prompting the user, by analyzing differences in the actions of the user across the multiple iterations of the task; representing the semantics and the variables in at least one script file, the at least one script file supporting performance of user interaction with the web service based on the semantics and values provided for the variables, where each bound variable has a constant value over multiple executions of the at least one script file, and each free variable has a value that is changeable over the multiple executions of the at least one script file; and associating the at least one script file with a unique uniform resource locator (URL) address that is selectable to initiate performance of user interaction with the web service, wherein the unique URL address is selectable by different user devices to invoke and execute the user interaction.
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1. A method for representing user interaction with a web service comprising: acquiring a representation of actions of a user performing multiple iterations of a task with the web service; analyzing the acquired actions to determine semantics and a plurality of variables describing the user actions, each variable being an input to the web service that the web service requests the user to enter during the multiple iterations of the task, the variables comprising free variables and bound variables, where which of the variables are the free variables and which of the variables are the bound variables is determined automatically without prompting the user, by analyzing differences in the actions of the user across the multiple iterations of the task; representing the semantics and the variables in at least one script file, the at least one script file supporting performance of user interaction with the web service based on the semantics and values provided for the variables, where each bound variable has a constant value over multiple executions of the at least one script file, and each free variable has a value that is changeable over the multiple executions of the at least one script file; and associating the at least one script file with a unique uniform resource locator (URL) address that is selectable to initiate performance of user interaction with the web service, wherein the unique URL address is selectable by different user devices to invoke and execute the user interaction. 2. The method of claim 1 , wherein analyzing further comprises determining potential values of the variables, and wherein representing further comprises representing the potential values in a file.
| 0.607055 |
4. The method according to claim 1 , further comprising defining each of the plurality of multiword expressions using a sequence of symbols.
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4. The method according to claim 1 , further comprising defining each of the plurality of multiword expressions using a sequence of symbols. 5. The method according to claim 4 , wherein symbols in the sequence of symbols are one of alphanumeric characters, music notes, chemical formulations, biological formulations, and kanji characters.
| 0.939477 |
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