sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
0.99
|
|---|---|---|
10. The keyboard of claim 9 , wherein there are five rows and three columns of keys. | 10. The keyboard of claim 9 , wherein there are five rows and three columns of keys. 11. The keyboard of claim 10 , wherein the letters P and Q are located on a single key. | 0.966644 |
23. A management system as recited in claim 22 , wherein the different products send resource information to the interference engine to process rules that depend on at least one fact representing the resource information. | 23. A management system as recited in claim 22 , wherein the different products send resource information to the interference engine to process rules that depend on at least one fact representing the resource information. 24. A management system as recited in claim 23 , wherein the action includes a debug data acquisition. | 0.927498 |
1. A processor implemented method for generating color information for at least one object in a spreadsheet document described in a markup language, the method comprising: parsing the spreadsheet document to generate at least one display list associated with the at least one object by: obtaining distinct color values from a plurality of spreadsheet color table objects, wherein color values in the plurality of spreadsheet color table objects are referenced by the at least one object in the spreadsheet by using a plurality of indexes of the color table objects; storing the distinct color values in a color palette table object, wherein color values in the color palette table object are accessed using a plurality of color palette indexes; and generating a mapping between each index in each of the plurality of color table objects and one of the plurality of color palette indexes that points to a same color value; and rasterizing the at least one object in a frame buffer by processing the display list using the mapping generated during parsing. | 1. A processor implemented method for generating color information for at least one object in a spreadsheet document described in a markup language, the method comprising: parsing the spreadsheet document to generate at least one display list associated with the at least one object by: obtaining distinct color values from a plurality of spreadsheet color table objects, wherein color values in the plurality of spreadsheet color table objects are referenced by the at least one object in the spreadsheet by using a plurality of indexes of the color table objects; storing the distinct color values in a color palette table object, wherein color values in the color palette table object are accessed using a plurality of color palette indexes; and generating a mapping between each index in each of the plurality of color table objects and one of the plurality of color palette indexes that points to a same color value; and rasterizing the at least one object in a frame buffer by processing the display list using the mapping generated during parsing. 9. The processor implemented method of claim 1 , wherein the plurality of color table objects comprise at least one of an indexed color table. object, a theme color object, and a color table object. | 0.816421 |
8. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for building a small business social graph, the method comprising: receiving a collection of data from a first business; and building a social graph that adheres to a Resource Description Framework Schema (RDFS) by: determining an ontology for businesses in the social graph; determining if a first node for the first business exists in the social graph, wherein the social graph is a graph-based data model that indicates relationships among various businesses; if not, adding the first node for the first business to the social graph according to the ontology; analyzing the collection of data to identify a second business; determining if a second node for the second business exists in the social graph; if not, adding the second node for the second business to the social graph according to the ontology; adding a relationship between the first node and the second node to the social graph, according to the ontology, to indicate the relationship between the first business and the second business, analyzing the collection of data to identify a first person; determining if a third node for the first person exists in the social graph; if not, adding the third node for the first person to the social graph according to the ontology; determining that the second node and the third node share a unique identifier; and relating the second business and the first person as a same entity. | 8. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for building a small business social graph, the method comprising: receiving a collection of data from a first business; and building a social graph that adheres to a Resource Description Framework Schema (RDFS) by: determining an ontology for businesses in the social graph; determining if a first node for the first business exists in the social graph, wherein the social graph is a graph-based data model that indicates relationships among various businesses; if not, adding the first node for the first business to the social graph according to the ontology; analyzing the collection of data to identify a second business; determining if a second node for the second business exists in the social graph; if not, adding the second node for the second business to the social graph according to the ontology; adding a relationship between the first node and the second node to the social graph, according to the ontology, to indicate the relationship between the first business and the second business, analyzing the collection of data to identify a first person; determining if a third node for the first person exists in the social graph; if not, adding the third node for the first person to the social graph according to the ontology; determining that the second node and the third node share a unique identifier; and relating the second business and the first person as a same entity. 14. The non-transitory computer-readable storage medium of claim 8 , wherein the collection of data can include: accounting data; financial data; social-network data; and personal information from a Personal Information Manager (PIM). | 0.640833 |
49. A system comprising: one or more computers; and a computer-readable storage device storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: determining a partial similarity score for a vector x in a set of vectors and each other vector in the set of vectors, each partial similarity score representing a degree of similarity between features of the vector x and corresponding features of other vectors in the set of vectors; determining an upper bound, the upper bound being an estimate of the maximum similarity between non-processed features of the vector x and non-processed features of the other vectors, the non-processed features being features that have not been used to calculate the partial similarity scores; as long as the upper bound is greater than or equal to the similarity threshold, adding vectors to a candidate set of vectors and repeating the operations of determining a partial similarity score and determining an upper bound; when the upper bound is lower than the similarity threshold, determining partial similarity scores only for vectors in the candidate set of vectors; and identifying x and a vector y in the candidate set of vectors as similar vectors using the partial similarity score between x and y. | 49. A system comprising: one or more computers; and a computer-readable storage device storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: determining a partial similarity score for a vector x in a set of vectors and each other vector in the set of vectors, each partial similarity score representing a degree of similarity between features of the vector x and corresponding features of other vectors in the set of vectors; determining an upper bound, the upper bound being an estimate of the maximum similarity between non-processed features of the vector x and non-processed features of the other vectors, the non-processed features being features that have not been used to calculate the partial similarity scores; as long as the upper bound is greater than or equal to the similarity threshold, adding vectors to a candidate set of vectors and repeating the operations of determining a partial similarity score and determining an upper bound; when the upper bound is lower than the similarity threshold, determining partial similarity scores only for vectors in the candidate set of vectors; and identifying x and a vector y in the candidate set of vectors as similar vectors using the partial similarity score between x and y. 101. The system of claim 49 , in which each vector in the set of vectors represents a corresponding query, and each feature of each vector represents a relevance of a corresponding document to the query. | 0.571384 |
6. The method of claim 1 , wherein each of the first and second plurality of text messages is associated with at least one topic and each of the first and second plurality of text messages is indexed in the database according to the at least one topic. | 6. The method of claim 1 , wherein each of the first and second plurality of text messages is associated with at least one topic and each of the first and second plurality of text messages is indexed in the database according to the at least one topic. 9. The method of claim 6 , wherein the user identifies the topic. | 0.91634 |
5. The automated computer based method as recited in claim 4 wherein a tabular display compares each word or character element of the writing sample submitted to each corresponding word or character element of the master file with resultant non-matches noted and highlighted in the color-codes corresponding to the category based analysis. | 5. The automated computer based method as recited in claim 4 wherein a tabular display compares each word or character element of the writing sample submitted to each corresponding word or character element of the master file with resultant non-matches noted and highlighted in the color-codes corresponding to the category based analysis. 6. The automated computer based method as recited in claim 5 wherein a graphical user interface is included to allow the user to move from each identified error to a corresponding error line of the tabular display. | 0.934009 |
10. A method for providing textual information, comprising: detecting auditory information with an audio sensor; transmitting a first signal containing said auditory information to a loudspeaker and a voice to text server; converting said audio information to textual information with said voice to text server; preparing a message containing at least a portion of said textual information with said voice to text server; and transmitting a second signal containing a first copy of said message from said voice to text server to all addresses over a Wi-Fi network, the Wi-Fi network configured to connect to a plurality of mobile computing devices; and in response to a request from at least one of said plurality of mobile computing devices, to transmit a third signal containing second copy of said message to the at least one mobile computing device that issued the request. | 10. A method for providing textual information, comprising: detecting auditory information with an audio sensor; transmitting a first signal containing said auditory information to a loudspeaker and a voice to text server; converting said audio information to textual information with said voice to text server; preparing a message containing at least a portion of said textual information with said voice to text server; and transmitting a second signal containing a first copy of said message from said voice to text server to all addresses over a Wi-Fi network, the Wi-Fi network configured to connect to a plurality of mobile computing devices; and in response to a request from at least one of said plurality of mobile computing devices, to transmit a third signal containing second copy of said message to the at least one mobile computing device that issued the request. 13. The method of claim 10 , wherein said textual information is first textual information and the method further comprises translating said first textual information into second textual information, the second textual information being different than said first textual information. | 0.648371 |
1. In a computing environment, a method comprising: processing a search log, including determining which queries from the search log correspond to information that is safe to publish; and for each of the queries having information that is safe to publish, publishing the information as output data, wherein determining which queries from the search log correspond to information that is safe to publish comprises limiting how many queries in the search log each user can contribute to a set of queries for processing, wherein publishing the information as output data comprises outputting a query-action graph having nodes representing queries and nodes representing actions taken, with each edge between a query node and an action node having a weight that indicates how many times that action was taken following that query, wherein the weight has zero noise, a negative noise or a positive noise added thereto, or outputting a query-inaction graph having nodes representing queries and nodes representing actions skipped, with each edge between a query node and an inaction node having a weight that indicates how many times that action was not taken following that query, and wherein the weight has zero noise, a negative noise or a positive noise added thereto. | 1. In a computing environment, a method comprising: processing a search log, including determining which queries from the search log correspond to information that is safe to publish; and for each of the queries having information that is safe to publish, publishing the information as output data, wherein determining which queries from the search log correspond to information that is safe to publish comprises limiting how many queries in the search log each user can contribute to a set of queries for processing, wherein publishing the information as output data comprises outputting a query-action graph having nodes representing queries and nodes representing actions taken, with each edge between a query node and an action node having a weight that indicates how many times that action was taken following that query, wherein the weight has zero noise, a negative noise or a positive noise added thereto, or outputting a query-inaction graph having nodes representing queries and nodes representing actions skipped, with each edge between a query node and an inaction node having a weight that indicates how many times that action was not taken following that query, and wherein the weight has zero noise, a negative noise or a positive noise added thereto. 5. The method of claim 1 wherein publishing the information as output data comprises outputting a count value for each query that is safe to publish, where this count value corresponds to an approximate number of times that the query appears in the search log or a subset of queries for processing, plus a noise value. | 0.614339 |
10. A document presentation system, the document presentation system comprising: one or more processors; system memory; a document database; a search database; a document collection system, the document collection system configured to: collect documents from one or more data sources; tag documents, including for each collected document: tagging items in the document for which the document can be searched; and tagging portions of the document as eligible for alteration, based on classification of the portions, when presented to a user that does not have access to the entire document contents; store the tagged documents in a search database for use in generating search results that match received search requests; and store copies of collected documents in the document database for use in building altered representations of a collected document for a user that does not have access to the entire document contents; and a presentation engine, presentation engine configured to: determine how to alter search results that include tagged portions of a document tagged as eligible for alteration when a user does not have access to the tagged portions of the document based on an access policy; and build an altered representation of the document by replacing the tagged portions of the document with other data in accordance with the determination. | 10. A document presentation system, the document presentation system comprising: one or more processors; system memory; a document database; a search database; a document collection system, the document collection system configured to: collect documents from one or more data sources; tag documents, including for each collected document: tagging items in the document for which the document can be searched; and tagging portions of the document as eligible for alteration, based on classification of the portions, when presented to a user that does not have access to the entire document contents; store the tagged documents in a search database for use in generating search results that match received search requests; and store copies of collected documents in the document database for use in building altered representations of a collected document for a user that does not have access to the entire document contents; and a presentation engine, presentation engine configured to: determine how to alter search results that include tagged portions of a document tagged as eligible for alteration when a user does not have access to the tagged portions of the document based on an access policy; and build an altered representation of the document by replacing the tagged portions of the document with other data in accordance with the determination. 12. The system of claim 10 , the presentation engine further configured to: receive credentials from the user; present the credentials to a data source; and receive the access policy from the data source. | 0.626545 |
6. A client device of a user associated with a user node in a social graph of a social-networking system, the client device comprising: one or more processors; and one or more computer-readable non-transitory storage media coupled to the processors and embodying software that is operable when executed by the processors to: access a tag that encodes information regarding a concept node in the social graph, the concept node representing a concept of the social-networking system; determine based at least in part on the tag and a node type of the concept node one or more social actions to take on the social graph with respect to the user node and the concept node, wherein a list of default social actions based on the node type of the concept node as determined by the social-networking system is accessed to select a plurality of social actions related to the information of the tag regarding the concept node to determine the one or more social actions to take on the social graph; display an interactive list comprising the one or more social actions determined based at least in part on the tag that encodes information regarding the concept node to the user for selection of a social action from the one or more social actions; receive user input comprising the selected social action from the interactive list; and transmit, to one or more computer systems of a social-networking system maintaining at least a portion of the social graph, a message configured to effect the selected social action on the social graph with respect to the user node and the concept node, wherein the selected social action is determined based on the user input and on the tad, and wherein the selected social action comprises at least one of an action performed by the user on the concept or a relationship established between the user and the concept. | 6. A client device of a user associated with a user node in a social graph of a social-networking system, the client device comprising: one or more processors; and one or more computer-readable non-transitory storage media coupled to the processors and embodying software that is operable when executed by the processors to: access a tag that encodes information regarding a concept node in the social graph, the concept node representing a concept of the social-networking system; determine based at least in part on the tag and a node type of the concept node one or more social actions to take on the social graph with respect to the user node and the concept node, wherein a list of default social actions based on the node type of the concept node as determined by the social-networking system is accessed to select a plurality of social actions related to the information of the tag regarding the concept node to determine the one or more social actions to take on the social graph; display an interactive list comprising the one or more social actions determined based at least in part on the tag that encodes information regarding the concept node to the user for selection of a social action from the one or more social actions; receive user input comprising the selected social action from the interactive list; and transmit, to one or more computer systems of a social-networking system maintaining at least a portion of the social graph, a message configured to effect the selected social action on the social graph with respect to the user node and the concept node, wherein the selected social action is determined based on the user input and on the tad, and wherein the selected social action comprises at least one of an action performed by the user on the concept or a relationship established between the user and the concept. 8. The client device of claim 6 , wherein the selected social action is determined based on the user input and on the tag. | 0.703608 |
1. A method comprising: providing a computing device; receiving, by the computing device, medical status data generated by a monitoring device, the medical status data representing a physiological characteristic of a patient; generating, by the computing device, a script file by applying a transformation to the medical status data, the transformation specified by an Extensible Stylesheet Language Transformation (XSLT) document; executing, by the computing device, the script file; receiving responses from a plurality of receiver systems, each of the responses indicating whether each of the receiver systems successfully received data sent by the computing device; determining whether one or more of the receiver systems is an authority, wherein one receiver system is an authority when operation of the monitoring device is effected by whether the one receiver system successfully received the data; disregarding one or more of the responses when one or more of the receiver systems is not an authority; setting, when one response is a first response received from receiver systems to which the computing device has sent data and the one receiver system is an authority, an overall response to the response; setting, when the one response is not the first response received from the receiver systems to which the computing device sent data and the one receiver system is an authority, the overall response to a result of performing a logical “and” operation on the response and the overall response; and sending the overall response to the monitoring device when the computing device has received responses from each of the receiver systems to which the computing device sent data. | 1. A method comprising: providing a computing device; receiving, by the computing device, medical status data generated by a monitoring device, the medical status data representing a physiological characteristic of a patient; generating, by the computing device, a script file by applying a transformation to the medical status data, the transformation specified by an Extensible Stylesheet Language Transformation (XSLT) document; executing, by the computing device, the script file; receiving responses from a plurality of receiver systems, each of the responses indicating whether each of the receiver systems successfully received data sent by the computing device; determining whether one or more of the receiver systems is an authority, wherein one receiver system is an authority when operation of the monitoring device is effected by whether the one receiver system successfully received the data; disregarding one or more of the responses when one or more of the receiver systems is not an authority; setting, when one response is a first response received from receiver systems to which the computing device has sent data and the one receiver system is an authority, an overall response to the response; setting, when the one response is not the first response received from the receiver systems to which the computing device sent data and the one receiver system is an authority, the overall response to a result of performing a logical “and” operation on the response and the overall response; and sending the overall response to the monitoring device when the computing device has received responses from each of the receiver systems to which the computing device sent data. 6. The method of claim 1 , wherein executing the script file comprises: generating result data; and providing the result data to one of the receiver systems. | 0.568647 |
1. A method comprising: retrieving profile information related to the user, the profile information including the user's tag affinities; selecting questions based on tags related to the user's tag affinities; for each of the questions, determining a score for the question by combining the user's tag affinities for the tags; for each of the questions, adjusting the score for the question based on a duration of time elapsed since the user last interacted with one or more questions associated with the tags; sorting the questions based on the adjusted scores for the questions; and providing the highest sorted question in the interface for display to the user. | 1. A method comprising: retrieving profile information related to the user, the profile information including the user's tag affinities; selecting questions based on tags related to the user's tag affinities; for each of the questions, determining a score for the question by combining the user's tag affinities for the tags; for each of the questions, adjusting the score for the question based on a duration of time elapsed since the user last interacted with one or more questions associated with the tags; sorting the questions based on the adjusted scores for the questions; and providing the highest sorted question in the interface for display to the user. 9. The method of claim 1 , wherein providing the highest sorted question in the interface for display to the user further comprises: embedding the interface in a third party application associated with the social networking system; and providing the question in the embedded interface with selectable links to direct the user to the social networking system. | 0.726272 |
17. A processor-based system for classifying an object in an image, the system comprising: one or more processors; and a non-transitory computer-readable medium or media comprising one or more sequences of instructions which, when executed by the one or more processors, causes steps to be performed comprising: for each local window of a set of local windows from the image: [a] computing a set of image features; [b] applying one or more pre-trained classifiers to the set of image features to obtain a set of classifier response values; [c] generating a classification context for the local window using the set of classifier response values of the local window and the sets of classifier response values of local windows that are within a neighborhood of the local window; and [d] constructing an augmented feature set comprising the classification context and the set of image features for the local window; [e] applying a pre-trained contextual boost classifier to the augmented feature set to obtain a set of contextual boost classifier response values; [f] responsive to a stop condition not being reached: adjusting the classification context for the local window using the set of contextual boost classifier response values; adjusting the augmented feature set for the local window using the classification context and a prior augmented feature set for the local window; and returning to [e]. | 17. A processor-based system for classifying an object in an image, the system comprising: one or more processors; and a non-transitory computer-readable medium or media comprising one or more sequences of instructions which, when executed by the one or more processors, causes steps to be performed comprising: for each local window of a set of local windows from the image: [a] computing a set of image features; [b] applying one or more pre-trained classifiers to the set of image features to obtain a set of classifier response values; [c] generating a classification context for the local window using the set of classifier response values of the local window and the sets of classifier response values of local windows that are within a neighborhood of the local window; and [d] constructing an augmented feature set comprising the classification context and the set of image features for the local window; [e] applying a pre-trained contextual boost classifier to the augmented feature set to obtain a set of contextual boost classifier response values; [f] responsive to a stop condition not being reached: adjusting the classification context for the local window using the set of contextual boost classifier response values; adjusting the augmented feature set for the local window using the classification context and a prior augmented feature set for the local window; and returning to [e]. 18. The processor-based system for classifying an object in an image of claim 17 wherein the step of computing a set of image features comprises: generating a context region for the local window comprising at least a portion of the image and formed by selecting a portion or portions of the image that are within a context region area defined relative to the local window; computing a local difference pattern feature by performing the steps comprising: partitioning the context region and the local window into blocks; calculating a brightness value for a reference block; calculating a brightness value for at least some of the blocks; computing a difference value between the brightness of the reference block and the brightness of at least some of the blocks; and forming the difference values into the local difference pattern feature; and constructing a multi-scale feature comprising: a high-scale feature comprising one or more features extracted from the local window at a high-resolution size; a mid-scale feature comprising a combination of one or more features extracted from the local window at a mid-resolution and one or more features extracted from a set of one or more regions at the mid-resolution, the set of one or more regions being formed from the context region; and a low-scale feature comprising one or more features extracted from a combined local window at a low-resolution size, the combined local window comprising the local window and the context region for the local window. | 0.5 |
10. An apparatus in a group manager of a central service node for enabling services or media in a communication network, comprising: a monitoring unit adapted to detect activities and conditions of communication devices in the network, a context collecting unit adapted to, for each of a plurality of entities, collect individual context data relating to the entity, the individual context data comprising a first data value corresponding to a first behavioral context parameter, and a second data value corresponding to a first environmental context parameter, wherein first behavioral context parameter is separate and distinct from the first environmental context parameter, a context vector unit adapted to, for each of the plurality of said entities, create an individual context vector for said entity from said collected individual context data related to said entity wherein each of said plurality of context vectors identifies a point in a logical, as opposed to a physical, N-dimensional space, where N is greater than or equal to two, the context vector unit further adapted to create a master context vector comprising a third data value corresponding to the first behavioral context parameter, and a fourth data value corresponding to the first environmental context parameter, wherein the master context vector identifies a centroid point in the logical N-dimensional space, a distance calculating unit adapted to determine, for each of the plurality of said individual context vectors, the distance between the centroid point and the point identified by said individual context vector, and a group defining unit adapted to define a group of correlated entities that are found to be correlated or similar with respect to one or more features or characteristics based on the collected individual context data by including an entity in the group in response to determining that the distance between the centroid point and the point identified by said individual context vector corresponding to said entity is less than a threshold. | 10. An apparatus in a group manager of a central service node for enabling services or media in a communication network, comprising: a monitoring unit adapted to detect activities and conditions of communication devices in the network, a context collecting unit adapted to, for each of a plurality of entities, collect individual context data relating to the entity, the individual context data comprising a first data value corresponding to a first behavioral context parameter, and a second data value corresponding to a first environmental context parameter, wherein first behavioral context parameter is separate and distinct from the first environmental context parameter, a context vector unit adapted to, for each of the plurality of said entities, create an individual context vector for said entity from said collected individual context data related to said entity wherein each of said plurality of context vectors identifies a point in a logical, as opposed to a physical, N-dimensional space, where N is greater than or equal to two, the context vector unit further adapted to create a master context vector comprising a third data value corresponding to the first behavioral context parameter, and a fourth data value corresponding to the first environmental context parameter, wherein the master context vector identifies a centroid point in the logical N-dimensional space, a distance calculating unit adapted to determine, for each of the plurality of said individual context vectors, the distance between the centroid point and the point identified by said individual context vector, and a group defining unit adapted to define a group of correlated entities that are found to be correlated or similar with respect to one or more features or characteristics based on the collected individual context data by including an entity in the group in response to determining that the distance between the centroid point and the point identified by said individual context vector corresponding to said entity is less than a threshold. 13. The apparatus according to claim 10 , wherein updating the group includes changing the context parameters of relevance and/or the membership conditions. | 0.720405 |
5. The method of claim 1 , wherein the plurality of MLA classifiers includes: the first MLA classifier; the second MLA classifier; a third MLA classifier, and a fourth MLA classifier. | 5. The method of claim 1 , wherein the plurality of MLA classifiers includes: the first MLA classifier; the second MLA classifier; a third MLA classifier, and a fourth MLA classifier. 9. The method of claim 5 , wherein the third MLA classifier is a rule-based classifier. | 0.955748 |
54. Apparatus for use with a network, the apparatus comprising: an interface; and a processor, which is configured to cause a web browser to display (a) a first content item in a first content area displayed on a webpage, and (b) a second content item in a second content area displayed separately from the first content area on the webpage; cause the web browser to display, in the second content area, at least a portion of a set of one or more third content items related to the first content item, if the processor receives, from the web browser via the interface over the network, an indication of dragging, by a user of the web browser, of a first element displayed in the first content area, and dropping, by the user, of the first element into the second content area; and cause the web browser to display, in the first content area, at least a portion of a set of one or more fourth content items related to the second content item, if the processor receives, from the web browser via the interface over the network, an indication of dragging, by the user, of a second element displayed in the second content area, and dropping, by the user, of the second element into the first content area, wherein the first element is selected from the group consisting of: the first content item, and a first graphical element displayed in association with the first content item, and wherein the second element is selected from the group consisting of: the second content item, and a second graphical element displayed in association with the second content item. | 54. Apparatus for use with a network, the apparatus comprising: an interface; and a processor, which is configured to cause a web browser to display (a) a first content item in a first content area displayed on a webpage, and (b) a second content item in a second content area displayed separately from the first content area on the webpage; cause the web browser to display, in the second content area, at least a portion of a set of one or more third content items related to the first content item, if the processor receives, from the web browser via the interface over the network, an indication of dragging, by a user of the web browser, of a first element displayed in the first content area, and dropping, by the user, of the first element into the second content area; and cause the web browser to display, in the first content area, at least a portion of a set of one or more fourth content items related to the second content item, if the processor receives, from the web browser via the interface over the network, an indication of dragging, by the user, of a second element displayed in the second content area, and dropping, by the user, of the second element into the first content area, wherein the first element is selected from the group consisting of: the first content item, and a first graphical element displayed in association with the first content item, and wherein the second element is selected from the group consisting of: the second content item, and a second graphical element displayed in association with the second content item. 55. The apparatus according to claim 54 , wherein the first content item is of a first content category, and wherein the second content item is of a second content category different from the first content category. | 0.587634 |
8. The information handling system of claim 7 wherein the actions further comprise: identifying a term in a first passage of the selected document; detecting that an anaphor in a subsequent passage of the selected document references the identified term; and resolving the anaphor found in the subsequent passage with the identified term. | 8. The information handling system of claim 7 wherein the actions further comprise: identifying a term in a first passage of the selected document; detecting that an anaphor in a subsequent passage of the selected document references the identified term; and resolving the anaphor found in the subsequent passage with the identified term. 9. The information handling system of claim 8 wherein the identified term relates to the identified correction. | 0.939406 |
15. The method of claim 14 , further comprising: informing the user by the voice portal server of an incorrect usage if each determined confidence level is less than each associated acceptance limit for any slot. | 15. The method of claim 14 , further comprising: informing the user by the voice portal server of an incorrect usage if each determined confidence level is less than each associated acceptance limit for any slot. 17. The method of claim 15 , further comprising: informing the user by the voice portal server of the at least one uttered phrase associated with the at least one corresponding slot for which each determined confidence level is less than each associated acceptance limit. | 0.876861 |
17. A method for selecting advertising for display with a web page requested by a user comprising: receiving, as input, a plurality of documents and a plurality of key terms; analyzing content of the plurality of documents; automatically generating a key term feature vector for each key term based on the content of the plurality of documents, each key term feature vector comprising elements comprising a plurality of words or phrases that are related to the corresponding key term; analyzing at least one of a Universal Resource Locator (“URL”) of said web page and a content of said web page; automatically generating a document feature vector based on the URL or the content of the web page, the document feature vector comprising elements comprising a plurality of words or phrases that are contained in the URL or content of the web page; comparing the key term feature vector and the document feature vector; generating a relevance factor based on the similarity of the elements of the key term feature vector and the document feature vector; and providing a relevant advertisement for display by said web browser with said web page according to the determined relevance factor. | 17. A method for selecting advertising for display with a web page requested by a user comprising: receiving, as input, a plurality of documents and a plurality of key terms; analyzing content of the plurality of documents; automatically generating a key term feature vector for each key term based on the content of the plurality of documents, each key term feature vector comprising elements comprising a plurality of words or phrases that are related to the corresponding key term; analyzing at least one of a Universal Resource Locator (“URL”) of said web page and a content of said web page; automatically generating a document feature vector based on the URL or the content of the web page, the document feature vector comprising elements comprising a plurality of words or phrases that are contained in the URL or content of the web page; comparing the key term feature vector and the document feature vector; generating a relevance factor based on the similarity of the elements of the key term feature vector and the document feature vector; and providing a relevant advertisement for display by said web browser with said web page according to the determined relevance factor. 19. The method of claim 17 , wherein said providing an advertisement for display comprises providing the advertisement for display within the web page. | 0.588106 |
15. A method, comprising: receiving, via at least one of one or more computing devices, a test document associated with a workflow definition, the test document comprising a programmatic input source configured to provide an input for an action of the workflow definition and an expected state for the workflow definition based at least in part on the input; delivering, via at least one of the one or more computing devices, the input from the programmatic input source for the action of a workflow instance, the workflow instance being a first instance of the workflow definition executed by a workflow engine, and the action determined based at least in part upon a present state of the workflow instance, the input being determined upon execution of the action of the workflow instance; receiving, via at least one of the one or more computing devices, a next state of the workflow instance, the next state being determined by the workflow engine based at least in part upon the present state, the action, and the input; comparing, via at least one of the one or more computing devices, the next state of the workflow instance to the expected state specified by the test document; and restarting, via at least one of the one or more computing devices, the workflow instance at a beginning of the workflow instance in response to detecting a discrepancy between the next state of the workflow instance and the expected state specified by the test document in response to comparing the next state of the workflow instance to the expected state specified by the test document. | 15. A method, comprising: receiving, via at least one of one or more computing devices, a test document associated with a workflow definition, the test document comprising a programmatic input source configured to provide an input for an action of the workflow definition and an expected state for the workflow definition based at least in part on the input; delivering, via at least one of the one or more computing devices, the input from the programmatic input source for the action of a workflow instance, the workflow instance being a first instance of the workflow definition executed by a workflow engine, and the action determined based at least in part upon a present state of the workflow instance, the input being determined upon execution of the action of the workflow instance; receiving, via at least one of the one or more computing devices, a next state of the workflow instance, the next state being determined by the workflow engine based at least in part upon the present state, the action, and the input; comparing, via at least one of the one or more computing devices, the next state of the workflow instance to the expected state specified by the test document; and restarting, via at least one of the one or more computing devices, the workflow instance at a beginning of the workflow instance in response to detecting a discrepancy between the next state of the workflow instance and the expected state specified by the test document in response to comparing the next state of the workflow instance to the expected state specified by the test document. 21. The method of claim 15 , further comprising initiating, via at least one of the one or more computing devices, the workflow instance based at least in part upon the workflow definition specified by the test document. | 0.638037 |
34. At least one tangible computer-readable medium encoded with instructions that, when executed by at least one hardware computer processor, perform a method of performing a search for content on the Internet, the method comprising: receiving voice input provided from a user; and generating at least one text search query for a plurality of Internet-accessible search engines that search for content on the Internet, wherein the at least one text search query is generated, at least in part, by performing speech recognition on the voice input; wherein the at least one text search query comprises at least two text search queries; wherein the act of generating further comprises: generating a first of the at least two text search queries, at least in part by performing speech recognition on the voice input using a first language model associated with a first of the plurality of search engines; and generating a second of the at least two text search queries, at least in part by performing speech recognition on the voice input using a second language model, different from the first language model, associated with a second of the plurality of search engines; wherein the first language model is one that was trained on content indexed by the first of the plurality of search engines; wherein the first of the plurality of search engines is a site-specific search engine; and wherein the second of the plurality of search engines is a general search engine. | 34. At least one tangible computer-readable medium encoded with instructions that, when executed by at least one hardware computer processor, perform a method of performing a search for content on the Internet, the method comprising: receiving voice input provided from a user; and generating at least one text search query for a plurality of Internet-accessible search engines that search for content on the Internet, wherein the at least one text search query is generated, at least in part, by performing speech recognition on the voice input; wherein the at least one text search query comprises at least two text search queries; wherein the act of generating further comprises: generating a first of the at least two text search queries, at least in part by performing speech recognition on the voice input using a first language model associated with a first of the plurality of search engines; and generating a second of the at least two text search queries, at least in part by performing speech recognition on the voice input using a second language model, different from the first language model, associated with a second of the plurality of search engines; wherein the first language model is one that was trained on content indexed by the first of the plurality of search engines; wherein the first of the plurality of search engines is a site-specific search engine; and wherein the second of the plurality of search engines is a general search engine. 37. The at least one tangible computer-readable medium of claim 34 , wherein the act of generating further comprises: selecting one of a plurality of available language models to be used in performing automatic speech recognition on the voice input; and performing automatic speech recognition on the voice input using the selected one of the plurality of language models. | 0.626905 |
21. The method of claim 1 , further comprising: automatically identifying key organization entities in a subject area using an online bibliographic database. | 21. The method of claim 1 , further comprising: automatically identifying key organization entities in a subject area using an online bibliographic database. 22. The method of claim 21 , wherein the online bibliographic database is MEDLINE. | 0.976696 |
13. The computer program product as claimed in claim 9 wherein the element diagram definition includes a linking relationship between nodes in the internally constructed custom tree. | 13. The computer program product as claimed in claim 9 wherein the element diagram definition includes a linking relationship between nodes in the internally constructed custom tree. 14. The computer program product as claimed in claim 13 wherein the method further comprises completing the inheritance hierarchy based on the linking relationship between the nodes in the internally constructed custom tree. | 0.922945 |
11. A method comprising: determining, by a system including a processor, a first language of an intended recipient of user input based on a first identity of the intended recipient; determining, by the system, a second language of another intended recipient of the user input based on a second identity of the other intended recipient translating, by the system, the user input into a first translated message of the first language using a multi-lingual library, wherein the user input was inputted into a first accessory operably coupled with a first computing device, wherein the first computing device is programmed to present a video game; providing, by the system, the first translated message to a second accessory for presentation to the intended recipient; translating, by the system, the user input into a second translated message of the second language using the multi-lingual library; and providing, by the system, the second translated message to a third accessory for presentation to the other intended recipient. | 11. A method comprising: determining, by a system including a processor, a first language of an intended recipient of user input based on a first identity of the intended recipient; determining, by the system, a second language of another intended recipient of the user input based on a second identity of the other intended recipient translating, by the system, the user input into a first translated message of the first language using a multi-lingual library, wherein the user input was inputted into a first accessory operably coupled with a first computing device, wherein the first computing device is programmed to present a video game; providing, by the system, the first translated message to a second accessory for presentation to the intended recipient; translating, by the system, the user input into a second translated message of the second language using the multi-lingual library; and providing, by the system, the second translated message to a third accessory for presentation to the other intended recipient. 13. The method of claim 11 , wherein the first translated message is presented at the second accessory as synthesized voice content. | 0.597473 |
1. A computer system configured to validate CAPTCHAs, the computer system comprising: one or more hardware processors programmed, via executable code instructions, to implement: a CAPTCHA generator module configured to: determine a phrase containing a first combination of one or more words that, when perceived together, sounds like a different second combination of one or more words; and generate CAPTCHA user interface depicting: the phrase of words including the first combination of one or more words, and at least two options, at least one of which makes sense within the context of the phrase; a human validator module configured to: receive a selection of at least one of the options associated with the CAPTCHA user interface; determine whether the selection makes sense within the context of the phrase; and transmit whether the selection makes sense within the context of the phrase. | 1. A computer system configured to validate CAPTCHAs, the computer system comprising: one or more hardware processors programmed, via executable code instructions, to implement: a CAPTCHA generator module configured to: determine a phrase containing a first combination of one or more words that, when perceived together, sounds like a different second combination of one or more words; and generate CAPTCHA user interface depicting: the phrase of words including the first combination of one or more words, and at least two options, at least one of which makes sense within the context of the phrase; a human validator module configured to: receive a selection of at least one of the options associated with the CAPTCHA user interface; determine whether the selection makes sense within the context of the phrase; and transmit whether the selection makes sense within the context of the phrase. 8. The computer system of claim 1 , wherein the determination of whether the at least two options associated with the CAPTCHA user interface make sense within the context of the phrase is based, at least in part, on data gathered from human corrections made to computerized voice-to-text transcriptions. | 0.5 |
8. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: access a first feature vector representing a video-content object corresponding to a node in a social graph of a social-networking system, wherein: the video-content object comprises frames and audio and is associated with text; the first feature vector is based on one or more of the frames of the video-content object; and the social graph comprises a plurality of nodes and edges connecting the nodes; access a second feature vector representing the video-content object, wherein the second feature vector is based on at least some of the text; access a third feature vector representing the video-content object, wherein the third feature vector is based on one or more portions of the audio; determine a fourth feature vector representing the video-content object, wherein the fourth feature vector is based on a combination of the first, second, and third feature vectors; and determine a context of the video-content object based on the fourth feature vector and social-graph information based at least in part on one or more nodes or edges connected to the node corresponding to the video-content object. | 8. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: access a first feature vector representing a video-content object corresponding to a node in a social graph of a social-networking system, wherein: the video-content object comprises frames and audio and is associated with text; the first feature vector is based on one or more of the frames of the video-content object; and the social graph comprises a plurality of nodes and edges connecting the nodes; access a second feature vector representing the video-content object, wherein the second feature vector is based on at least some of the text; access a third feature vector representing the video-content object, wherein the third feature vector is based on one or more portions of the audio; determine a fourth feature vector representing the video-content object, wherein the fourth feature vector is based on a combination of the first, second, and third feature vectors; and determine a context of the video-content object based on the fourth feature vector and social-graph information based at least in part on one or more nodes or edges connected to the node corresponding to the video-content object. 12. The media of claim 8 , wherein the software is further operable when executed to remove a second video-content object based on determining that the video-content object and the second video-content object are similar based on the feature vector for the video-content object and a feature vector for the second video-content object, wherein determining the context of the video-content object comprises determining that the video-content object is inappropriate. | 0.770895 |
20. The method of claim 9 , wherein step (a) comprises: determining whether each candidate codevector belongs to an illegal space representing illegal candidate codevectors, wherein the illegal space is defined by the one ore more illegal space definitions; and declaring as a legal candidate codevector each candidate codevector that does not belong to the illegal space. | 20. The method of claim 9 , wherein step (a) comprises: determining whether each candidate codevector belongs to an illegal space representing illegal candidate codevectors, wherein the illegal space is defined by the one ore more illegal space definitions; and declaring as a legal candidate codevector each candidate codevector that does not belong to the illegal space. 22. The method of claim 20 , wherein the illegal space is represented as an illegal criterion for LSF vectors, and the illegal criterion for LSF vectors includes first and second successive LSFs in a pair of LSFs being closer to each other than a minimum separation distance. | 0.86262 |
13. Training apparatus for helping a user improve his or her use of a word recognition system, which recognition system scores matches of signal models for each of a plurality of words against each of a succession of user generated signals; which recognition system produces a succession of outputs corresponding to the succession of user generated signals, each such output representing as the recognized word the word whose signal model scored best against the corresponding one of said user generated signal, with such an output being considered a mis-recognition when that output represents as the recognized word a word other than that actually represented by the output's corresponding user generated signal and which recognition system responds to the receipt of a correction command from a user when a mis-recognition has occurred by correcting that mis-recognition, that is, by changing the mis-recognition's output to remove the representation as the recognized word of a word other than that actually represented by that output's corresponding user generated signal; said training apparatus comprising: means for instructing the user to generate a user generated signal for each of a corresponding succession of expected words; training output means for responding to the user's successive generation of said user generated signals by producing a corresponding succession of outputs, some of which represent as the recognized word the expected word corresponding to the output's user generated signal, and some of which represent a simulated mis-recognition of that expected word by representing as the recognized word for the output's user generated signal a word other than that signal's corresponding expected word; means for receiving a correction command from a user indicating that the user desires to correct such a simulated mis-recognition when that mis-recognition has occurred and for responding to the receipt of such a correction command by changing the mis-recognition's output by removing that output's representation as the recognized word of a word other than the output's corresponding expected word; and correction monitoring means for monitoring whether or not the user responds to a simulated mis-recognition by entering a correction command to correct that mis-recognition and for providing an output to the user to notify him or her when he or she fails to correct such a simulated mis-recognition. | 13. Training apparatus for helping a user improve his or her use of a word recognition system, which recognition system scores matches of signal models for each of a plurality of words against each of a succession of user generated signals; which recognition system produces a succession of outputs corresponding to the succession of user generated signals, each such output representing as the recognized word the word whose signal model scored best against the corresponding one of said user generated signal, with such an output being considered a mis-recognition when that output represents as the recognized word a word other than that actually represented by the output's corresponding user generated signal and which recognition system responds to the receipt of a correction command from a user when a mis-recognition has occurred by correcting that mis-recognition, that is, by changing the mis-recognition's output to remove the representation as the recognized word of a word other than that actually represented by that output's corresponding user generated signal; said training apparatus comprising: means for instructing the user to generate a user generated signal for each of a corresponding succession of expected words; training output means for responding to the user's successive generation of said user generated signals by producing a corresponding succession of outputs, some of which represent as the recognized word the expected word corresponding to the output's user generated signal, and some of which represent a simulated mis-recognition of that expected word by representing as the recognized word for the output's user generated signal a word other than that signal's corresponding expected word; means for receiving a correction command from a user indicating that the user desires to correct such a simulated mis-recognition when that mis-recognition has occurred and for responding to the receipt of such a correction command by changing the mis-recognition's output by removing that output's representation as the recognized word of a word other than the output's corresponding expected word; and correction monitoring means for monitoring whether or not the user responds to a simulated mis-recognition by entering a correction command to correct that mis-recognition and for providing an output to the user to notify him or her when he or she fails to correct such a simulated mis-recognition. 14. Training apparatus as in claim 13, wherein: said word recognition system which the apparatus helps a user improve his or her use of is a speech recognition system; and the user generated signals which the means for instructing instructs the user to generate for each expected word are spoken utterances of that word. | 0.683147 |
17. A method, comprising: receiving, from an imaging device of an electronic device, a first image of a target object; analyzing, by one or more processors using an image recognition application, the first image to identify a first feature of the target object; accessing, by one or more of the processors, a model database to identify one or more models of objects that include the first feature; in response to identifying more than one model: identifying, by one or more of the processors, that one of the identified models includes a distinguishing point, determining, by one or more of the processors by analyzing a second image of the target object, that the target object comprises the distinguishing point, wherein determining that the target object comprises the distinguishing point comprises: identifying a location on the target object where the distinguishing point may appear; displaying the target object on a display of the electronic device; when an area that contains the location appears on the display, causing the display to indicate the location by displaying one or more boundary indicators; receiving the second image; and analyzing the second image to determine whether the second image includes the distinguishing point, and in response to determining that the target object comprises the distinguishing point, retrieving one or more document files that correspond to the identified model that contains the distinguishing point. | 17. A method, comprising: receiving, from an imaging device of an electronic device, a first image of a target object; analyzing, by one or more processors using an image recognition application, the first image to identify a first feature of the target object; accessing, by one or more of the processors, a model database to identify one or more models of objects that include the first feature; in response to identifying more than one model: identifying, by one or more of the processors, that one of the identified models includes a distinguishing point, determining, by one or more of the processors by analyzing a second image of the target object, that the target object comprises the distinguishing point, wherein determining that the target object comprises the distinguishing point comprises: identifying a location on the target object where the distinguishing point may appear; displaying the target object on a display of the electronic device; when an area that contains the location appears on the display, causing the display to indicate the location by displaying one or more boundary indicators; receiving the second image; and analyzing the second image to determine whether the second image includes the distinguishing point, and in response to determining that the target object comprises the distinguishing point, retrieving one or more document files that correspond to the identified model that contains the distinguishing point. 19. The method of claim 17 , wherein each model in the database is an appliance model. | 0.707615 |
7. A system for determining a common sequence of ordered statements comprising: a memory; and a processor device communicatively coupled to the memory, wherein the memory is encoded with instructions for determining a common sequence of statements from one or more sets of ordered statements, and wherein the processor device is configured to: create a global list comprising a first set of links generated from a first sequence of statements of a first script, wherein a link in the first set of links indicates an ordered mapping between a source statement and a destination statement selected from the first sequence of statements, and an ordered mapping indicates that a source statement is executed before a destination statement is executed; add, to the global list, a second set of links generated from a second sequence of statements of a second script, wherein a link in the second set of links indicates an ordered mapping between a source statement and a destination statement selected from the second sequence of statements; determine, from the global list, two or more links having equivalent source statements and equivalent destination statements; add at least one of the two or more links to a first group of common sequences; and store the first group of common sequences in a database. | 7. A system for determining a common sequence of ordered statements comprising: a memory; and a processor device communicatively coupled to the memory, wherein the memory is encoded with instructions for determining a common sequence of statements from one or more sets of ordered statements, and wherein the processor device is configured to: create a global list comprising a first set of links generated from a first sequence of statements of a first script, wherein a link in the first set of links indicates an ordered mapping between a source statement and a destination statement selected from the first sequence of statements, and an ordered mapping indicates that a source statement is executed before a destination statement is executed; add, to the global list, a second set of links generated from a second sequence of statements of a second script, wherein a link in the second set of links indicates an ordered mapping between a source statement and a destination statement selected from the second sequence of statements; determine, from the global list, two or more links having equivalent source statements and equivalent destination statements; add at least one of the two or more links to a first group of common sequences; and store the first group of common sequences in a database. 10. The system of claim 7 , wherein the processor device is further configured to add source statements and destination statements of one or more links between a first source statement of a first link and a first destination statement of the first link until the first destination statement is not equivalent to a source statement of another link. | 0.666667 |
24. One or more machine-readable tangible and non-transitory media having information for ranking a search result, wherein the information, when read by at least one machine, causes the at least one machine to: access a set of recency ranking data comprising one or more past search queries, one or more past search results, and one or more recency features, wherein the recency features comprise: a time-sensitive feature representing a particular time period that was determined based on content of at least some of the past search queries, wherein the at least some of the past search queries were sensitive to the particular time period, and a query timestamp feature representing the time at which the past search queries were received at a search engine; train a first ranking model via machine learning based on the recency features; and determine when recency is to be utilized for ranking a search result based on the ranking model. | 24. One or more machine-readable tangible and non-transitory media having information for ranking a search result, wherein the information, when read by at least one machine, causes the at least one machine to: access a set of recency ranking data comprising one or more past search queries, one or more past search results, and one or more recency features, wherein the recency features comprise: a time-sensitive feature representing a particular time period that was determined based on content of at least some of the past search queries, wherein the at least some of the past search queries were sensitive to the particular time period, and a query timestamp feature representing the time at which the past search queries were received at a search engine; train a first ranking model via machine learning based on the recency features; and determine when recency is to be utilized for ranking a search result based on the ranking model. 27. The media of claim 24 , wherein the recency features comprise: one or more resource timestamp features each of which representing a timestamp extracted from one of the recency network resources; one or more resource age features each of which representing, for one of the recency query-resource pairs, a difference between the query timestamp of the recency query and the resource timestamp of the recency resource; one or more resource link-time features each of which representing a time when a link to one of the recency network resources is discovered; one or more web-buzz features each of which representing one of the recency network resources that is popular during one particular time period; and one or more click-buzz features each of which representing one of the recency network resources that receives a higher amount of clicks during one particular time period. | 0.5841 |
15. A system for data cleansing using rule based formatting, comprising: a hardware server that implements the system; a tokenizing module, implemented by the hardware server, that tokenizes a first input data according to a data dictionary, and tokenizes a second input data according to said data dictionary; a rule-based parsing module, implemented by the hardware server, that parses said first input data and said second tokenized input data using a predefined parsing rule including an option operator, wherein the option operator indicates that a particular index defined in the predefined parsing rule is optional; a formatting module, implemented by the hardware server, that receives the said first tokenized input data and said second tokenized input data, wherein a first token is included in a first output data if a first formatting rule component in a formatting rule is a first valid index to said first tokenized input data, wherein said first token is associated with said first valid index, wherein a first string literal is included in said first output data if said first formatting rule component in the formatting rule is a string literal, and wherein said formatting rule includes an immediate at least one conditional format operator, wherein the at least one conditional format operator indicates whether to include a particular string literal in an output data based on the existence of a particular token, wherein a second token is included in a second output data if said first formatting rule component in the formatting rule is a second valid index to said second tokenized input data, wherein said second token is associated with said second valid index, wherein a second string literal is included in said second output data if said first formatting rule component in the formatting rule is a string literal, and wherein said first output data and said second output data are formatted according to the formatting rule; a first data source that stores said first input data; a second data source that stores said second input data; and a third data source that stores said first output data and said second output data. | 15. A system for data cleansing using rule based formatting, comprising: a hardware server that implements the system; a tokenizing module, implemented by the hardware server, that tokenizes a first input data according to a data dictionary, and tokenizes a second input data according to said data dictionary; a rule-based parsing module, implemented by the hardware server, that parses said first input data and said second tokenized input data using a predefined parsing rule including an option operator, wherein the option operator indicates that a particular index defined in the predefined parsing rule is optional; a formatting module, implemented by the hardware server, that receives the said first tokenized input data and said second tokenized input data, wherein a first token is included in a first output data if a first formatting rule component in a formatting rule is a first valid index to said first tokenized input data, wherein said first token is associated with said first valid index, wherein a first string literal is included in said first output data if said first formatting rule component in the formatting rule is a string literal, and wherein said formatting rule includes an immediate at least one conditional format operator, wherein the at least one conditional format operator indicates whether to include a particular string literal in an output data based on the existence of a particular token, wherein a second token is included in a second output data if said first formatting rule component in the formatting rule is a second valid index to said second tokenized input data, wherein said second token is associated with said second valid index, wherein a second string literal is included in said second output data if said first formatting rule component in the formatting rule is a string literal, and wherein said first output data and said second output data are formatted according to the formatting rule; a first data source that stores said first input data; a second data source that stores said second input data; and a third data source that stores said first output data and said second output data. 18. The system of claim 15 further comprising a data dictionary repository that stores said data dictionary. | 0.505109 |
1. A computer-implemented method for training video location classifiers, the method comprising: storing a set of locations, each location uniquely corresponding to a geographic area having a unique geographic placement; providing a user interface for uploading a video, the user interface comprising a user interface element for specifying locations from the stored set of locations; receiving, from users via the user interface, a set of uploaded videos, each uploaded video labeled with a location from the stored set of locations, the location specified using the user interface; selecting, for each of a plurality of the locations, a location training set comprising ones of the uploaded videos that are labeled with the location; for each of a plurality of video location classifiers, each video location classifier associated with one of the locations: for each uploaded video of the location training set for the associated location, deriving a set of features associated with the uploaded video, the set of features comprising: audiovisual features extracted from content of the uploaded video; upload location information derived from an internet protocol (IP) address from which the uploaded video was uploaded; landmark scores indicating whether the uploaded video contains landmark features, the landmark scores being produced by applying trained landmark classifiers to the uploaded video; category scores indicating whether the uploaded video represents predetermined categories, the category scores produced by category classifiers that are trained based at least in part on a set of videos considered to represent the categories; and textual features derived from metadata of the uploaded video; training the video location classifier based at least in part on the features derived from the uploaded videos in the location training set; for an unlabeled video not labeled with a location from the stored set of locations, and for a first one of the trained video location classifiers: deriving a set of features comprising audiovisual features extracted from content of the unlabeled video, upload location information derived from the IP address from which the video was uploaded, landmark scores indicating whether the unlabeled video contains landmark features, category scores indicating whether the unlabeled video represents predetermined categories, and textual features derived from metadata of the unlabeled video; applying the first one of the trained video location classifiers to the set of features derived for the unlabeled video, thereby producing a location score indicating how strongly the unlabeled video represents the location associated with the first one of the trained video location classifiers; predicting based on the location score, that the unlabeled video represents the location associated with the first one of the trained video location classifiers; and providing, to a user, a visual representation of a map, the map including a visual indication of the unlabeled video on a portion of the map corresponding to the location associated with the first one of the trained video location classifiers. | 1. A computer-implemented method for training video location classifiers, the method comprising: storing a set of locations, each location uniquely corresponding to a geographic area having a unique geographic placement; providing a user interface for uploading a video, the user interface comprising a user interface element for specifying locations from the stored set of locations; receiving, from users via the user interface, a set of uploaded videos, each uploaded video labeled with a location from the stored set of locations, the location specified using the user interface; selecting, for each of a plurality of the locations, a location training set comprising ones of the uploaded videos that are labeled with the location; for each of a plurality of video location classifiers, each video location classifier associated with one of the locations: for each uploaded video of the location training set for the associated location, deriving a set of features associated with the uploaded video, the set of features comprising: audiovisual features extracted from content of the uploaded video; upload location information derived from an internet protocol (IP) address from which the uploaded video was uploaded; landmark scores indicating whether the uploaded video contains landmark features, the landmark scores being produced by applying trained landmark classifiers to the uploaded video; category scores indicating whether the uploaded video represents predetermined categories, the category scores produced by category classifiers that are trained based at least in part on a set of videos considered to represent the categories; and textual features derived from metadata of the uploaded video; training the video location classifier based at least in part on the features derived from the uploaded videos in the location training set; for an unlabeled video not labeled with a location from the stored set of locations, and for a first one of the trained video location classifiers: deriving a set of features comprising audiovisual features extracted from content of the unlabeled video, upload location information derived from the IP address from which the video was uploaded, landmark scores indicating whether the unlabeled video contains landmark features, category scores indicating whether the unlabeled video represents predetermined categories, and textual features derived from metadata of the unlabeled video; applying the first one of the trained video location classifiers to the set of features derived for the unlabeled video, thereby producing a location score indicating how strongly the unlabeled video represents the location associated with the first one of the trained video location classifiers; predicting based on the location score, that the unlabeled video represents the location associated with the first one of the trained video location classifiers; and providing, to a user, a visual representation of a map, the map including a visual indication of the unlabeled video on a portion of the map corresponding to the location associated with the first one of the trained video location classifiers. 8. The computer-implemented method of claim 1 , further comprising: receiving a query from a user for videos, the query comprising text associated with the location; responsive to determining that the unlabeled video represents the location associated with the first one of the video location classifiers, adding the video to a query result set; and providing the query result set to the user. | 0.627599 |
2. The computer program product of claim 1 , wherein identifying the user further comprises authenticating the user. | 2. The computer program product of claim 1 , wherein identifying the user further comprises authenticating the user. 3. The computer program product of claim 2 , wherein the user is authenticated using internet protocol (IP) address tracking or a client-side cookie. | 0.929958 |
1. A method of restating telecommunications data by a batch-driven integrated rules module that receives batched client data, comprising: selecting a set of criteria for restating data from a Graphic User Interface (GUI), the set of criteria includes attributes of a business rule to be applied for restating the data; communicating the set of criteria to the batch-driven integrated rules module wherein the batch-driven integrated rules module comprises a rules database and a script generator; mapping the attributes of the business rule in the communicated set of criteria to rules in the rules database by iteratively utilizing a collection of look-up tables and conditional logic in the rules database; automatically generating a script by the script generator of the batch-driven integrated rules module by communicating with the rules database and compiling the rules in the rules database that were mapped to the attributes of the business rule; extracting data from a data warehouse based on the generated script, the data comprises legacy client data; queuing the legacy client data into a batch; transforming the batched legacy client data based on the generated script; and loading the transformed legacy client data in the data warehouse. | 1. A method of restating telecommunications data by a batch-driven integrated rules module that receives batched client data, comprising: selecting a set of criteria for restating data from a Graphic User Interface (GUI), the set of criteria includes attributes of a business rule to be applied for restating the data; communicating the set of criteria to the batch-driven integrated rules module wherein the batch-driven integrated rules module comprises a rules database and a script generator; mapping the attributes of the business rule in the communicated set of criteria to rules in the rules database by iteratively utilizing a collection of look-up tables and conditional logic in the rules database; automatically generating a script by the script generator of the batch-driven integrated rules module by communicating with the rules database and compiling the rules in the rules database that were mapped to the attributes of the business rule; extracting data from a data warehouse based on the generated script, the data comprises legacy client data; queuing the legacy client data into a batch; transforming the batched legacy client data based on the generated script; and loading the transformed legacy client data in the data warehouse. 5. The method according to claim 1 , wherein the extracted data comprises at least a terabyte of data. | 0.887061 |
1. A system for receiving a retrieval request and generating a recognition result, the system comprising: a processor; a gateway having a plurality of inputs for receiving the retrieval request that includes at least an image portion and contextual information, the gateway processing the retrieval request to generate an image query and a recognition parameter, the gateway having a plurality of outputs for sending recognition results; a matching unit stored on a computer-readable storage medium and executable by the processor, the matching unit coupled to receive the image query and the recognition parameter from the gateway, the matching unit analyzing and comparing the image query and recognition parameter to an index table to generate the recognition result including a page identification number and a location on the recognition result, the matching unit coupled to send the recognition result to the gateway; and a hotspot database coupled to the matching unit, the hotspot database for retrieving hotspot information corresponding to the page and the location identified in the recognition result. | 1. A system for receiving a retrieval request and generating a recognition result, the system comprising: a processor; a gateway having a plurality of inputs for receiving the retrieval request that includes at least an image portion and contextual information, the gateway processing the retrieval request to generate an image query and a recognition parameter, the gateway having a plurality of outputs for sending recognition results; a matching unit stored on a computer-readable storage medium and executable by the processor, the matching unit coupled to receive the image query and the recognition parameter from the gateway, the matching unit analyzing and comparing the image query and recognition parameter to an index table to generate the recognition result including a page identification number and a location on the recognition result, the matching unit coupled to send the recognition result to the gateway; and a hotspot database coupled to the matching unit, the hotspot database for retrieving hotspot information corresponding to the page and the location identified in the recognition result. 5. The system of claim 1 , wherein the hotspot information related to the recognition result also includes links associated with the recognition result. | 0.662153 |
44. A system comprising: one or more computers; one or more data storage devices coupled to the one or more computers and storing instructions, which, when executed by the processor cause the one or more computers cause the one or more computers to perform operations comprising: receiving a current location of a user's electronic device; retrieving data identifying a plurality of points of interest within a predetermined distance to the current location; ranking each point of interest based at least in part on the point of interest's proximity to the current location, wherein for at least one point of interest the ranking is further based on one or more updates associated with the point of interest, where each update comprises data about the point of interest input by an author other than the user into an online social network that includes the user; and providing data identifying one or more of the points of interest to the electronic device for presentation to the user on a display of the electronic device based on the ranking. | 44. A system comprising: one or more computers; one or more data storage devices coupled to the one or more computers and storing instructions, which, when executed by the processor cause the one or more computers cause the one or more computers to perform operations comprising: receiving a current location of a user's electronic device; retrieving data identifying a plurality of points of interest within a predetermined distance to the current location; ranking each point of interest based at least in part on the point of interest's proximity to the current location, wherein for at least one point of interest the ranking is further based on one or more updates associated with the point of interest, where each update comprises data about the point of interest input by an author other than the user into an online social network that includes the user; and providing data identifying one or more of the points of interest to the electronic device for presentation to the user on a display of the electronic device based on the ranking. 47. The system of claim 44 , the operations further comprising: determining the predetermined distance based on a density of points of interest in an area including the current location. | 0.674924 |
1. A method, comprising: storing, in a shared library, device configuration information; providing an application programming interface to allow access of the device configuration information stored in the shared library by a first page description language interpreter and a second page description language interpreter; determining that a first page description language type and a second page description language type are included in a print job; the first page description language interpreter calling the application programming interface to access the device configuration information stored in the shared library to interpret the first page description language type; and the second page description language interpreter calling the application programming interface to access the device configuration information stored in the shared library to interpret the second page description language type. | 1. A method, comprising: storing, in a shared library, device configuration information; providing an application programming interface to allow access of the device configuration information stored in the shared library by a first page description language interpreter and a second page description language interpreter; determining that a first page description language type and a second page description language type are included in a print job; the first page description language interpreter calling the application programming interface to access the device configuration information stored in the shared library to interpret the first page description language type; and the second page description language interpreter calling the application programming interface to access the device configuration information stored in the shared library to interpret the second page description language type. 3. The method of claim 1 , further comprising: adding a new page description language interpreter without changing the shared library, wherein the new page description language interpreter also accesses the device configuration information stored in the shared library by calling the application programming interface. | 0.778472 |
44. The computer-implemented system of claim 39 , wherein the at least one server-side processor is further programmed to: analyze at least one product configuration rule to determine whether at least one product attribute of at least one product record is used in evaluating the at least one product configuration rule; create an attribute binary decision diagram (BDD) structure representative of the at least one product attribute of the least one product record when the at least one processor determines that the at least one product attribute is used in evaluating the at least one product configuration rule; and evaluate the attribute BDD structure to further prepare the customized product record. | 44. The computer-implemented system of claim 39 , wherein the at least one server-side processor is further programmed to: analyze at least one product configuration rule to determine whether at least one product attribute of at least one product record is used in evaluating the at least one product configuration rule; create an attribute binary decision diagram (BDD) structure representative of the at least one product attribute of the least one product record when the at least one processor determines that the at least one product attribute is used in evaluating the at least one product configuration rule; and evaluate the attribute BDD structure to further prepare the customized product record. 45. The computer-implemented system of claim 44 , wherein the attribute BDD structure comprises: an offering attribute node representative of a product attribute value selectable by the user based on evaluating the at least one product configuration rule. | 0.947303 |
1. A computer-implemented method for determining whether a mismatch is present between a description and content associated with a literary work, the method comprising: separately receiving, by a computer system from a publisher system, a title, a description, and a content associated with a literary work; identifying, by the computer system, a first plurality of words included in the description; identifying, by the computer system, a second plurality words that is included in the content; computing, by the computer system, a matching score based on initializing the matching score to zero, incrementing the matching score for each word in the first plurality of description words that matches at least one word in the second plurality of content words, and decrementing the matching score for each word in the first plurality of words that does not match any words in the second plurality of content words; determining, by the computer system, whether the title is verbatim included in the content; and notifying, by the computer system, the publisher system that the description does not match the content associated with the literary work where the computed matching score is less than zero, thereby indicating that the description does not match the content associated with the literary work, and the title is determined not to be verbatim included in the content. | 1. A computer-implemented method for determining whether a mismatch is present between a description and content associated with a literary work, the method comprising: separately receiving, by a computer system from a publisher system, a title, a description, and a content associated with a literary work; identifying, by the computer system, a first plurality of words included in the description; identifying, by the computer system, a second plurality words that is included in the content; computing, by the computer system, a matching score based on initializing the matching score to zero, incrementing the matching score for each word in the first plurality of description words that matches at least one word in the second plurality of content words, and decrementing the matching score for each word in the first plurality of words that does not match any words in the second plurality of content words; determining, by the computer system, whether the title is verbatim included in the content; and notifying, by the computer system, the publisher system that the description does not match the content associated with the literary work where the computed matching score is less than zero, thereby indicating that the description does not match the content associated with the literary work, and the title is determined not to be verbatim included in the content. 4. The computer-implemented method of claim 1 , wherein the identifying the first plurality of words included in the description and the identifying the second plurality of words included in the content comprises: identifying description stems included in the description, each description stem to correspond to a word included in the description; and identifying content stems included in the content, each content stem to correspond to a word included in the content. | 0.608051 |
10. The method of claim 8 comprising the further step of: (m) determining the likelihood of the correct word model producing the generated outputs; (n) determining the likelihood of the selected incorrect word model producing the generated outputs; (p) comparing the likelihoods determined in steps (m) and (n); and (q) conditioning the defining of an adjusted count value on whether the correct word likelihood fails to exceed the incorrect word likelihood by a prescribed increment. | 10. The method of claim 8 comprising the further step of: (m) determining the likelihood of the correct word model producing the generated outputs; (n) determining the likelihood of the selected incorrect word model producing the generated outputs; (p) comparing the likelihoods determined in steps (m) and (n); and (q) conditioning the defining of an adjusted count value on whether the correct word likelihood fails to exceed the incorrect word likelihood by a prescribed increment. 11. The method of claim 10 wherein determining the minus count value for a subject count includes the step of: (r) determining a minus cumulative count value for each probability item in the incorrect word baseform, the minus cumulative count value being based on the outputs generated in response to the utterance of the known subject word and corresponding to a specific transition .tau..sub.i being taken from a specific state S.sub.j at all label interval times t in the word model of the selected incorrect word, where the probability items have previously defined values. | 0.842846 |
24. A method for application-layer monitoring of communication between one or more database clients and one or more database servers, the method comprising: at a decoding layer above a network layer on a database device at a first network location between one or more database clients residing at one or more second network locations distinct from the first network location and one or more database servers residing at one or more third network locations distinct from both the first network location and the one or more second network locations: using one or more decoders on the database device for receiving database messages communicated over the network from any of the database clients residing at the one or more second network locations and intended for the database servers at the one or more third network locations and database messages communicated from the database servers and intended for the database clients; decoding the database messages, wherein decoding the database messages comprises decoding a protocol generated as an output of a database connectivity driver in response to an input by a database application residing at an application layer, wherein decoding the database messages comprises decoding database messages of database implementations different from each other and, wherein the database connectivity driver is utilized by the one or more database clients to communicate with the database serve; and extracting query-language statements from the database messages, wherein the query-language statements are created by the database application at one or more of the database clients and provided as input to the database connectivity driver and the database connectivity driver generate the database message as an output based on the query-language statement; and at an application layer above the decoding layer at the first network location, using a monitoring application on the database device for receiving query-language statements extracted at the decoders and recording observations on the database messages based at least in part on the query-language statements extracted at the decoding layer. | 24. A method for application-layer monitoring of communication between one or more database clients and one or more database servers, the method comprising: at a decoding layer above a network layer on a database device at a first network location between one or more database clients residing at one or more second network locations distinct from the first network location and one or more database servers residing at one or more third network locations distinct from both the first network location and the one or more second network locations: using one or more decoders on the database device for receiving database messages communicated over the network from any of the database clients residing at the one or more second network locations and intended for the database servers at the one or more third network locations and database messages communicated from the database servers and intended for the database clients; decoding the database messages, wherein decoding the database messages comprises decoding a protocol generated as an output of a database connectivity driver in response to an input by a database application residing at an application layer, wherein decoding the database messages comprises decoding database messages of database implementations different from each other and, wherein the database connectivity driver is utilized by the one or more database clients to communicate with the database serve; and extracting query-language statements from the database messages, wherein the query-language statements are created by the database application at one or more of the database clients and provided as input to the database connectivity driver and the database connectivity driver generate the database message as an output based on the query-language statement; and at an application layer above the decoding layer at the first network location, using a monitoring application on the database device for receiving query-language statements extracted at the decoders and recording observations on the database messages based at least in part on the query-language statements extracted at the decoding layer. 44. The method of claim 24 , further comprising, at the application layer, communicating observations on the database messages to a computer system at a fourth network location for reporting to one or more users. | 0.700412 |
19. An electronic device comprising: a communicator; a display configured to display a user interface (UI); a touch sensitive unit configured to receive a user's touch input; and at least one processor configured to: collate usage information of at least one data source associated with a user in the electronic device, wherein each data source is at least one item used in the electronic device or any application running on the electronic device, categorize the collated usage information into at least one knowledge cluster, wherein the categorizing includes extracting semantic content from the usage information and mapping the extracted semantic content to categorize the collated usage information into the at least one knowledge cluster using an incremental model, store a knowledge graph including the at least one knowledge cluster in a form of at least one knowledge node in the knowledge graph and at least one link among the at least one knowledge node, and dynamically modify at least one element of the UI based on the knowledge graph, wherein the dynamically modifying includes identifying the at least one knowledge cluster from the knowledge graph and displaying the at least one identified knowledge cluster as the at least one element of the UI. | 19. An electronic device comprising: a communicator; a display configured to display a user interface (UI); a touch sensitive unit configured to receive a user's touch input; and at least one processor configured to: collate usage information of at least one data source associated with a user in the electronic device, wherein each data source is at least one item used in the electronic device or any application running on the electronic device, categorize the collated usage information into at least one knowledge cluster, wherein the categorizing includes extracting semantic content from the usage information and mapping the extracted semantic content to categorize the collated usage information into the at least one knowledge cluster using an incremental model, store a knowledge graph including the at least one knowledge cluster in a form of at least one knowledge node in the knowledge graph and at least one link among the at least one knowledge node, and dynamically modify at least one element of the UI based on the knowledge graph, wherein the dynamically modifying includes identifying the at least one knowledge cluster from the knowledge graph and displaying the at least one identified knowledge cluster as the at least one element of the UI. 24. The electronic device of claim 19 , wherein the at least one processor is further configured to: monitor the usage information of the at least one data source in the electronic device, and update the at least one knowledge cluster based on the monitoring using an incremental model. | 0.584856 |
13. A system of providing speech recognition to a user on a mobile device, the system comprising: a hearing assistance application on a mobile device, the mobile device having a display screen, the hearing assistance application configured to receive audio data and transmit the audio data; a hearing assistance processor configured for real-time data exchange with the hearing assistance application, at least one voice processor and at least one recognition processor, the hearing assistance processor configured to receive the audio data from the hearing assistance application and transmit the audio data to the at least one recognition processor to convert the audio data into corresponding text data, receive the text data from the at least one recognition processor, and transmit the text data to the hearing assistance application; the hearing assistance application configured to display at least a portion of the text data on the display screen of the mobile device and receive confirmation to transmit the audio data, the text data or additional audio data derived from the text data to the telephony device, and transmit the confirmation to the hearing assistance processor; and the hearing assistance processor is configured to, in response to receiving the confirmation, transmit the audio data, the text data, or the additional audio data derived from the text data to the telephony device via the at least one voice processor, the hearing assistance processor is configured to receive additional audio data from the telephony device and interact with the at least one recognition processor to determine if the additional audio data is clear or otherwise of sufficient quality to be processed by the at least one recognition processor, and upon determining that the additional audio data is not clear or of insufficient quality to be processed, sending audio feedback to the telephony device that prompts for improved audio data; the hearing assistance application being configured to receive additional audio data from the user of the mobile device and transmit the additional audio data to the hearing assistance processor; the hearing assistance processor being configured to transmit the additional audio data to the at least one recognition processor to convert the additional audio data into corresponding additional text data, receive the additional text data from the at least one recognition processor, and transmit the additional text data to the hearing assistance application; the hearing assistance application being configured to display at least a portion of the additional text data on the display screen of the mobile device and receive confirmation to transmit the additional audio data or the text data to the telephony device, and transmit the confirmation to the hearing assistance processor; and the hearing assistance processor being configured to, in response to receiving the confirmation, transmit the additional audio data, the text data or generated audio data corresponding to the text data to the telephony device via the at least one voice processor. | 13. A system of providing speech recognition to a user on a mobile device, the system comprising: a hearing assistance application on a mobile device, the mobile device having a display screen, the hearing assistance application configured to receive audio data and transmit the audio data; a hearing assistance processor configured for real-time data exchange with the hearing assistance application, at least one voice processor and at least one recognition processor, the hearing assistance processor configured to receive the audio data from the hearing assistance application and transmit the audio data to the at least one recognition processor to convert the audio data into corresponding text data, receive the text data from the at least one recognition processor, and transmit the text data to the hearing assistance application; the hearing assistance application configured to display at least a portion of the text data on the display screen of the mobile device and receive confirmation to transmit the audio data, the text data or additional audio data derived from the text data to the telephony device, and transmit the confirmation to the hearing assistance processor; and the hearing assistance processor is configured to, in response to receiving the confirmation, transmit the audio data, the text data, or the additional audio data derived from the text data to the telephony device via the at least one voice processor, the hearing assistance processor is configured to receive additional audio data from the telephony device and interact with the at least one recognition processor to determine if the additional audio data is clear or otherwise of sufficient quality to be processed by the at least one recognition processor, and upon determining that the additional audio data is not clear or of insufficient quality to be processed, sending audio feedback to the telephony device that prompts for improved audio data; the hearing assistance application being configured to receive additional audio data from the user of the mobile device and transmit the additional audio data to the hearing assistance processor; the hearing assistance processor being configured to transmit the additional audio data to the at least one recognition processor to convert the additional audio data into corresponding additional text data, receive the additional text data from the at least one recognition processor, and transmit the additional text data to the hearing assistance application; the hearing assistance application being configured to display at least a portion of the additional text data on the display screen of the mobile device and receive confirmation to transmit the additional audio data or the text data to the telephony device, and transmit the confirmation to the hearing assistance processor; and the hearing assistance processor being configured to, in response to receiving the confirmation, transmit the additional audio data, the text data or generated audio data corresponding to the text data to the telephony device via the at least one voice processor. 18. The system of claim 13 , wherein the hearing assistance processor is configured to identify a user providing the audio data and transmit the identity of the user to the at least one recognition processor to improve accuracy of recognition. | 0.544802 |
12. An apparatus for converting a dataset into at least one table, said apparatus comprising: at least one processor for identifying at least one hierarchical structure in said dataset; and a converter for converting said dataset associated with said at least one identified hierarchical structure, said converter comprising: at least one processor for determining a node element set for said at least one identified hierarchical structure of said dataset, wherein at least one node element in said node element set is a discrete level of said at least one identified hierarchical structure of said dataset; at least one processor for determining one or more nodes of said dataset, each of said one or more nodes being an instance of a node element from said node element set; an allocator for allocating to said instance of said node element a unique node identifier; and a generator for generating said at least one table, said at least one table containing one or more records, each record corresponding to a respective one of said allocated node identifiers; wherein said node element set is selected to reduce the need for at least one downstream application to assemble data from an elemental level; wherein said at least one table is as required by said at least one downstream application; wherein said dataset comprises a plurality of predefined portions of text-based data, at least one of said plurality of predefined portions of text-based data being associated with at least one attribute for organizing at least one of said plurality of predefined portions of text-based data; and wherein said plurality of predefined portions of text-based data comprise at least one modified and stored predefined portion of text based data associated with at least one attribute for organizing at least one of said plurality of predefined portions of text based data and said at least one modified and stored predefined portion of text-based data. | 12. An apparatus for converting a dataset into at least one table, said apparatus comprising: at least one processor for identifying at least one hierarchical structure in said dataset; and a converter for converting said dataset associated with said at least one identified hierarchical structure, said converter comprising: at least one processor for determining a node element set for said at least one identified hierarchical structure of said dataset, wherein at least one node element in said node element set is a discrete level of said at least one identified hierarchical structure of said dataset; at least one processor for determining one or more nodes of said dataset, each of said one or more nodes being an instance of a node element from said node element set; an allocator for allocating to said instance of said node element a unique node identifier; and a generator for generating said at least one table, said at least one table containing one or more records, each record corresponding to a respective one of said allocated node identifiers; wherein said node element set is selected to reduce the need for at least one downstream application to assemble data from an elemental level; wherein said at least one table is as required by said at least one downstream application; wherein said dataset comprises a plurality of predefined portions of text-based data, at least one of said plurality of predefined portions of text-based data being associated with at least one attribute for organizing at least one of said plurality of predefined portions of text-based data; and wherein said plurality of predefined portions of text-based data comprise at least one modified and stored predefined portion of text based data associated with at least one attribute for organizing at least one of said plurality of predefined portions of text based data and said at least one modified and stored predefined portion of text-based data. 21. The apparatus according to claim 12 further comprising: a generator for generating an complex properties table having a node identifier field and a value field. | 0.575363 |
2. The method of claim 1 wherein the set of constraints includes a second multiplication constraint that includes one or more common variables with the multiplication constraint, the method further comprising performing factorization for the second multiplication constraint. | 2. The method of claim 1 wherein the set of constraints includes a second multiplication constraint that includes one or more common variables with the multiplication constraint, the method further comprising performing factorization for the second multiplication constraint. 3. The method of claim 2 further comprising determining a greatest common divisor (GCD) for the multiplication constraint and the second multiplication constraint; and performing factorization of the GCD to produce factoring values for the one or more common variables. | 0.797824 |
2. The method of claim 1 , wherein determining the non-textual object suggestion further comprises: comparing, by the computing device, the graphical representation of the user input to a plurality of non-textual objects; ranking, by the computing device, the plurality of non-textual objects based at least on the comparison of the graphical representation of the user input to the plurality of non-textual objects; and selecting, by the computing device, based at least in part on the ranking of the plurality of non-textual objects, a particular non-textual object from the plurality of non-textual objects as the non-textual object suggestion. | 2. The method of claim 1 , wherein determining the non-textual object suggestion further comprises: comparing, by the computing device, the graphical representation of the user input to a plurality of non-textual objects; ranking, by the computing device, the plurality of non-textual objects based at least on the comparison of the graphical representation of the user input to the plurality of non-textual objects; and selecting, by the computing device, based at least in part on the ranking of the plurality of non-textual objects, a particular non-textual object from the plurality of non-textual objects as the non-textual object suggestion. 3. The method of claim 2 , wherein for each respective non-textual object from the plurality of non-textual objects, a rank of the respective non-textual object is based at least in part on how closely the graphical representation of the user input matches a portion of the respective non-textual object. | 0.747522 |
17. A computer-implemented process for associating an entity with a document, comprising: accessing a classifier associated with an entity name in the document, wherein the classifier incorporates an estimated probability that is a function of a. a probability that an entity has the entity name related to the partition and b. an estimated size of a population larger than the dictionary; and applying the classifier to the document to obtain probabilities that the document is associated with specific entities having the entity name. | 17. A computer-implemented process for associating an entity with a document, comprising: accessing a classifier associated with an entity name in the document, wherein the classifier incorporates an estimated probability that is a function of a. a probability that an entity has the entity name related to the partition and b. an estimated size of a population larger than the dictionary; and applying the classifier to the document to obtain probabilities that the document is associated with specific entities having the entity name. 20. The computer implemented process of claim 17 , further comprising identifying the document in response to a user query on a database of documents separate from the dictionary. | 0.601875 |
1. A device, comprising: a memory that stores instructions; and a processor coupled to the memory, wherein responsive to executing the instructions, the processor performs operations comprising: receiving, at a first time, a first signal from a first communication device to start a first media evaluation session of media content, wherein the first time is during a theatrical release of the media content; receiving, in a first message, first comments from the first communication device during the first evaluation session; receiving, at a second time, a second signal from a second communication device to start a second media evaluation session of the media content, wherein the second time occurs after the theatrical release of the media content; receiving, in a second message, second comments from the second communication device during the second media evaluation session, wherein the first media evaluation session and the second media evaluation session are asynchronous with each other; synchronizing the first comments and the second comments into a single commentary timeline to substantially reduce asynchronicity between the first media evaluation session and the second media evaluation session; inserting the synchronized first and second comments in an overlay for playback with the media content by a media device, wherein the overlay comprises the single commentary timeline in which the first comments and the second comments are presented on the commentary timeline and temporally associated with the media content; and identifying a cluster of frequent comments, as an identified cluster, comprising one of the first comments, the second comments, or any combination thereof. | 1. A device, comprising: a memory that stores instructions; and a processor coupled to the memory, wherein responsive to executing the instructions, the processor performs operations comprising: receiving, at a first time, a first signal from a first communication device to start a first media evaluation session of media content, wherein the first time is during a theatrical release of the media content; receiving, in a first message, first comments from the first communication device during the first evaluation session; receiving, at a second time, a second signal from a second communication device to start a second media evaluation session of the media content, wherein the second time occurs after the theatrical release of the media content; receiving, in a second message, second comments from the second communication device during the second media evaluation session, wherein the first media evaluation session and the second media evaluation session are asynchronous with each other; synchronizing the first comments and the second comments into a single commentary timeline to substantially reduce asynchronicity between the first media evaluation session and the second media evaluation session; inserting the synchronized first and second comments in an overlay for playback with the media content by a media device, wherein the overlay comprises the single commentary timeline in which the first comments and the second comments are presented on the commentary timeline and temporally associated with the media content; and identifying a cluster of frequent comments, as an identified cluster, comprising one of the first comments, the second comments, or any combination thereof. 4. The device of claim 1 , wherein the operations further comprise: receiving additional comments from additional communication devices, wherein the additional comments are received from either one of the first time or the second time; synchronizing the additional comments to generate synchronized additional comments; and inserting the synchronized additional comments in the single commentary timeline. | 0.5 |
1. A method of providing environmental transparency for entities, comprising: displaying via a website, a plurality of environmental categories, the plurality of environmental categories comprising recycling practices, use of public transportation, and energy saving practices; creating a nonpublic database of a plurality of the entities directly employing the actions within one or more of the plurality of environmental categories, wherein the non-public database allows a certified entity to measure the change in population of entities that are choosing to employ environmental actions; via the web site, receiving input from a first entity, the input comprising an indication of the first entity's performance of actions within one or more of the plurality of environmental categories; via the web site, storing on a computer readable storage medium; via the web site, publicly displaying: the plurality of environmental categories and showing, based on the input, that the first entity performs actions within selected categories; and a visual entity identifier adjacent to the plurality of environmental categories, wherein the visual entity identifier comprises one of a logo and a name of the first entity; and via the website, publicly displaying inspirational information regarding the first entity, wherein: the inspirational information is associated with the first entity and is collected by the website from at least one second entity, the inspirational information identifying the first entity as having inspired the at least one second entity; and the inspirational information includes a numerical exhibit reflecting a number of entities that the first entity has inspired, the numerical exhibit including a tally of the entities inspired by the first entity, wherein the method allows consumers or other relationship partners to have access to the input from the first entity, which provides transparency regarding the first entity's environmental conduct and inspirational effect. | 1. A method of providing environmental transparency for entities, comprising: displaying via a website, a plurality of environmental categories, the plurality of environmental categories comprising recycling practices, use of public transportation, and energy saving practices; creating a nonpublic database of a plurality of the entities directly employing the actions within one or more of the plurality of environmental categories, wherein the non-public database allows a certified entity to measure the change in population of entities that are choosing to employ environmental actions; via the web site, receiving input from a first entity, the input comprising an indication of the first entity's performance of actions within one or more of the plurality of environmental categories; via the web site, storing on a computer readable storage medium; via the web site, publicly displaying: the plurality of environmental categories and showing, based on the input, that the first entity performs actions within selected categories; and a visual entity identifier adjacent to the plurality of environmental categories, wherein the visual entity identifier comprises one of a logo and a name of the first entity; and via the website, publicly displaying inspirational information regarding the first entity, wherein: the inspirational information is associated with the first entity and is collected by the website from at least one second entity, the inspirational information identifying the first entity as having inspired the at least one second entity; and the inspirational information includes a numerical exhibit reflecting a number of entities that the first entity has inspired, the numerical exhibit including a tally of the entities inspired by the first entity, wherein the method allows consumers or other relationship partners to have access to the input from the first entity, which provides transparency regarding the first entity's environmental conduct and inspirational effect. 7. The method of claim 1 , wherein the input regarding the first entity's performance of the actions within one or more of the plurality of environmental categories is one of the group consisting of yes or no. | 0.506968 |
4. The method of claim 1 , further comprising: estimating an end point candidate location as the end location of the block, based on the second location where the second anchor interaction is input; and displaying one of the second plurality of candidate anchors at the estimated end point candidate location. | 4. The method of claim 1 , further comprising: estimating an end point candidate location as the end location of the block, based on the second location where the second anchor interaction is input; and displaying one of the second plurality of candidate anchors at the estimated end point candidate location. 5. The method of claim 4 , wherein determining the second candidate anchor to be the second definite anchor comprises: determining the one of the second plurality of candidate anchors, corresponding to the end point candidate location, as the second definite anchor. | 0.948656 |
46. A method for enhancing communication within a community, the method comprising the steps of: (a) receiving in an application in an application platform a communication sent by a user from a first communication device, wherein said communication is associated with a user selected topic of a plurality of topics such that said user selected topic is selected by said user, and receiving a link to a resource associated with said communication; (b) determining an access right said user has to information stored in a database of said application in said application platform based upon an access status and wherein said access status is selected from the group consisting of an inclusive access in which access to each of said stored communications in said hierarchical structure is allowed except where excluded by an inherited parameter and an exclusive access in which access to each of said stored communications in said hierarchical structure is allowed only where explicitly assigned; (c) accessing a current database hierarchy, authorization parameters, and interaction control parameters for said application; (d) granting access to said user, according to said access right of said user, to a portion of said information stored in said database, wherein said portion of said information is stored in association with said user selected topic; (e) determining a dynamic interaction capability for said user with said portion of said information based on said database hierarchy, said authorization parameters, and said interaction control parameters; (f) prioritizing an order of said portion of said information, wherein an initial thread of said information is assigned a higher priority than a response to a thread of said information; (g) presenting said portion of said information that is ordered to said user for review, wherein said presentation is based on said prioritization; (h) receiving a selection input by said user an item type to respond to; (i) accepting a response input from said user according to said dynamic interaction capability from said first communication device for storage in said database, wherein said response input comprises said communication and said link; and (j) outputting said response input from said user to at least a second communication device. | 46. A method for enhancing communication within a community, the method comprising the steps of: (a) receiving in an application in an application platform a communication sent by a user from a first communication device, wherein said communication is associated with a user selected topic of a plurality of topics such that said user selected topic is selected by said user, and receiving a link to a resource associated with said communication; (b) determining an access right said user has to information stored in a database of said application in said application platform based upon an access status and wherein said access status is selected from the group consisting of an inclusive access in which access to each of said stored communications in said hierarchical structure is allowed except where excluded by an inherited parameter and an exclusive access in which access to each of said stored communications in said hierarchical structure is allowed only where explicitly assigned; (c) accessing a current database hierarchy, authorization parameters, and interaction control parameters for said application; (d) granting access to said user, according to said access right of said user, to a portion of said information stored in said database, wherein said portion of said information is stored in association with said user selected topic; (e) determining a dynamic interaction capability for said user with said portion of said information based on said database hierarchy, said authorization parameters, and said interaction control parameters; (f) prioritizing an order of said portion of said information, wherein an initial thread of said information is assigned a higher priority than a response to a thread of said information; (g) presenting said portion of said information that is ordered to said user for review, wherein said presentation is based on said prioritization; (h) receiving a selection input by said user an item type to respond to; (i) accepting a response input from said user according to said dynamic interaction capability from said first communication device for storage in said database, wherein said response input comprises said communication and said link; and (j) outputting said response input from said user to at least a second communication device. 51. A method according to claim 46 wherein said determining dynamic interaction capability further comprises: stratifying said portion of said information into at least one item type. | 0.758142 |
15. A non-transitory computer-readable medium having instructions stored thereon which, when executed by one or more processors of a server, causes the server to perform operations comprising: outputting, to a developer of a web page in a source language, an offer to opt-in to a translation feature that enables one or more other users to translate the web page to a different target language; receiving, from the developer, a first request to opt-in to the translation feature; and in response to receiving the first request to opt-in to the translation feature: generating and storing a copy of the web page; obtaining, from the one or more other users, translations of at least a portion of the web page from the source language to the target language; modifying the web page copy based on the obtained translations to obtain a translated web page, the translated web page being a translated version of the web page; detecting a second request for the web page from a computing device associated with the target language; and in response to detecting the second request, outputting, to the computing device, the translated web page with additional content relevant to the computing device or a user associated with the computing device. | 15. A non-transitory computer-readable medium having instructions stored thereon which, when executed by one or more processors of a server, causes the server to perform operations comprising: outputting, to a developer of a web page in a source language, an offer to opt-in to a translation feature that enables one or more other users to translate the web page to a different target language; receiving, from the developer, a first request to opt-in to the translation feature; and in response to receiving the first request to opt-in to the translation feature: generating and storing a copy of the web page; obtaining, from the one or more other users, translations of at least a portion of the web page from the source language to the target language; modifying the web page copy based on the obtained translations to obtain a translated web page, the translated web page being a translated version of the web page; detecting a second request for the web page from a computing device associated with the target language; and in response to detecting the second request, outputting, to the computing device, the translated web page with additional content relevant to the computing device or a user associated with the computing device. 20. The computer-readable medium of claim 15 , wherein the operations further comprise in response to receiving the first request to opt-in to the translation feature, modifying a document object model (DOM) of the web page copy to include JavaScript for providing the additional content. | 0.578549 |
1. A method comprising: displaying, on a display device of a system, a predetermined number of at least one image with at least one non-corresponding label in at least one language; having the user state, into an input device of the system, the at least one image; and determining, with a processor of the system, whether the user is misrepresenting his skill in the language as less than it actually is based on whether the at least one user statement was made with a delay. | 1. A method comprising: displaying, on a display device of a system, a predetermined number of at least one image with at least one non-corresponding label in at least one language; having the user state, into an input device of the system, the at least one image; and determining, with a processor of the system, whether the user is misrepresenting his skill in the language as less than it actually is based on whether the at least one user statement was made with a delay. 5. The method of claim 1 , wherein the at least one image is related to other images employed to introduce and/or improve detection of concealment. | 0.827103 |
12. A computer system for training an artificial neural network (ANN), the computing system comprising: a CPU, a computer readable memory, and a computer readable storage media; program instructions to collect a plurality of text inputs which comprises a plurality of dialects which correspond to at least one language, and store the plurality of text inputs in a database of the computing system; program instructions to categorize each input message in the plurality of text inputs as a good message which does not include obscene language or a bad message which does include the obscene language based on a vectorized form of the input message by comparing each word in the input message to a predetermined dictionary; and program instructions to train an artificial neural network (ANN) based on the vectorized form of the input message in the database and its corresponding category; and program instructions to determine inappropriate language in another text using the trained ANN and a string-structure similarity measure, and wherein the program instructions are stored on the computer readable storage media for execution by the CPU via the computer readable memory, and the obscene language corresponds to a specific dialect. | 12. A computer system for training an artificial neural network (ANN), the computing system comprising: a CPU, a computer readable memory, and a computer readable storage media; program instructions to collect a plurality of text inputs which comprises a plurality of dialects which correspond to at least one language, and store the plurality of text inputs in a database of the computing system; program instructions to categorize each input message in the plurality of text inputs as a good message which does not include obscene language or a bad message which does include the obscene language based on a vectorized form of the input message by comparing each word in the input message to a predetermined dictionary; and program instructions to train an artificial neural network (ANN) based on the vectorized form of the input message in the database and its corresponding category; and program instructions to determine inappropriate language in another text using the trained ANN and a string-structure similarity measure, and wherein the program instructions are stored on the computer readable storage media for execution by the CPU via the computer readable memory, and the obscene language corresponds to a specific dialect. 14. The computer system of claim 12 , wherein each input message in the plurality of text inputs is categorized as the good message or the bad message in a specified dialect corresponding to the at least one language based on user input from a plurality of users. | 0.543336 |
9. The method of claim 1 such that the combined graph is a histogram of RWEs and IOs known to the network. | 9. The method of claim 1 such that the combined graph is a histogram of RWEs and IOs known to the network. 10. The method of claim 9 such that the histogram comprises a plurality of categories, wherein each RWE and IO are in a respective one category of a plurality of categories, and a count is assigned to each category of the plurality of categories, each count comprising a number of observations in the data available for RWEs and IOs that fall into the respective one category of the plurality of categories. | 0.932187 |
3. The method of claim 1 , wherein the method further comprises creating a partial uncertain graph data set by substituting alternative values for a portion of all variables in the incomplete data graph, wherein each variable is replaced by a given group of alternative values selected from the set of alternative values. | 3. The method of claim 1 , wherein the method further comprises creating a partial uncertain graph data set by substituting alternative values for a portion of all variables in the incomplete data graph, wherein each variable is replaced by a given group of alternative values selected from the set of alternative values. 4. The method of claim 3 , wherein the step of creating the partial uncertain graph data set further comprises creating a plurality of partial uncertain graph data sets by substituting alternative values for variables in each one of a plurality of portions of all variables in the incomplete data set, each portion in the plurality of portions comprising a distinct portion. | 0.92268 |
1. A method comprising steps of: receiving one or more criteria that identifies particular nodes within one or more XML documents to exclude from query evaluation; based on the one or more criteria, generating a representation of the one or more XML documents that excludes the particular nodes; receiving a query that specifies a path operation based on a path, wherein one or more of said particular nodes is under said path in the one or more XML documents; and using the representation to compute the path operation as if the one or more of said particular nodes are not in the one or more XML documents; wherein the steps are performed by one or more computing devices. | 1. A method comprising steps of: receiving one or more criteria that identifies particular nodes within one or more XML documents to exclude from query evaluation; based on the one or more criteria, generating a representation of the one or more XML documents that excludes the particular nodes; receiving a query that specifies a path operation based on a path, wherein one or more of said particular nodes is under said path in the one or more XML documents; and using the representation to compute the path operation as if the one or more of said particular nodes are not in the one or more XML documents; wherein the steps are performed by one or more computing devices. 3. The method of claim 1 , wherein the representation is an index of the one or more XML documents, and wherein the steps further include accessing the index to compute the path operation. | 0.806748 |
22. A computer program product for conducting a search of electronically stored information, said computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by the processor, cause that processor to: (a) provide a user with an interactive targeting rule editor to enable the user to formulate a targeting rule to identify desired search results, the targeting rule comprising a natural language text string, the interactive targeting rule editor allowing the user to change one or more designated editable portions of the natural language text string to one of a set of specified alternate portions to form a syntactically valid targeting rule in accordance with a targeting rule grammar, wherein at least one of the specified alternate portions includes one or more further designated editable portions that are changeable by the user to one of a further set of specified alternate portions to form the syntactically valid targeting rule; (b) translate a natural language text string generated by the user or a representation of said natural language text string into an executable query; and (c) execute the executable query against the electronically stored information to generate search results. | 22. A computer program product for conducting a search of electronically stored information, said computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by the processor, cause that processor to: (a) provide a user with an interactive targeting rule editor to enable the user to formulate a targeting rule to identify desired search results, the targeting rule comprising a natural language text string, the interactive targeting rule editor allowing the user to change one or more designated editable portions of the natural language text string to one of a set of specified alternate portions to form a syntactically valid targeting rule in accordance with a targeting rule grammar, wherein at least one of the specified alternate portions includes one or more further designated editable portions that are changeable by the user to one of a further set of specified alternate portions to form the syntactically valid targeting rule; (b) translate a natural language text string generated by the user or a representation of said natural language text string into an executable query; and (c) execute the executable query against the electronically stored information to generate search results. 24. The computer program product of claim 22 wherein the interactive targeting rule editor only permits the formation of syntactically-valid targeting rules in accordance with a targeting rule grammar upon each change, delete, or add step by the user. | 0.571573 |
5. A system for interpreting natural language utterances using out-of-vocabulary and noise toleration capabilities, comprising: an input device configured to receive an utterance; and a speech interpretation engine configured to: recognize a phoneme stream contained in the received utterance; map the recognized phoneme stream to a syllable series that includes one or more syllables that an acoustic grammar phonemically represents in accordance with an acoustic speech model; and generate an interpretation of the utterance, wherein the generated interpretation includes the one or more syllables in the syllable series mapped to the recognized phoneme stream. | 5. A system for interpreting natural language utterances using out-of-vocabulary and noise toleration capabilities, comprising: an input device configured to receive an utterance; and a speech interpretation engine configured to: recognize a phoneme stream contained in the received utterance; map the recognized phoneme stream to a syllable series that includes one or more syllables that an acoustic grammar phonemically represents in accordance with an acoustic speech model; and generate an interpretation of the utterance, wherein the generated interpretation includes the one or more syllables in the syllable series mapped to the recognized phoneme stream. 7. The system of claim 5 , wherein the acoustic speech model includes an unstressed central vowel that links sequential phonemic elements in the acoustic speech model. | 0.507732 |
1. A data processing method comprising: causing displaying a first user interface at a first computer; receiving at a production manager computer, from the first computer via the first user interface, scene metadata defining a plurality of scenes of a media production; causing displaying a second user interface at a second computer that is different from the first computer; receiving at the production manager computer, via the second user interface, at a time after the scene metadata was received and before closing the media production, item metadata for a particular item appearing in the media production, wherein the item metadata specifies a scene, from among the plurality of scenes, in which the particular item appears; using the production manager computer: based on the scene metadata and the item metadata, creating a record in an item database that associates the particular item with the specified scene; determining one or more time values representing a time period during which the particular item appears in the media production based on the scene metadata; generating data specifying when the particular item and each of a plurality of other items appears in the media production based on the time period, wherein the data includes the one or more time values; wherein the method is performed by one or more computing devices. | 1. A data processing method comprising: causing displaying a first user interface at a first computer; receiving at a production manager computer, from the first computer via the first user interface, scene metadata defining a plurality of scenes of a media production; causing displaying a second user interface at a second computer that is different from the first computer; receiving at the production manager computer, via the second user interface, at a time after the scene metadata was received and before closing the media production, item metadata for a particular item appearing in the media production, wherein the item metadata specifies a scene, from among the plurality of scenes, in which the particular item appears; using the production manager computer: based on the scene metadata and the item metadata, creating a record in an item database that associates the particular item with the specified scene; determining one or more time values representing a time period during which the particular item appears in the media production based on the scene metadata; generating data specifying when the particular item and each of a plurality of other items appears in the media production based on the time period, wherein the data includes the one or more time values; wherein the method is performed by one or more computing devices. 6. The method of claim 1 , wherein the scene metadata defines each scene in the plurality of scenes by one or more of: start timecode, end timecode, or scene number. | 0.702579 |
1. A method for operating an automated assistant, comprising: at a server computer system comprising a processor and memory storing instructions for execution by the processor: receiving, from a speech recognition service operated separately from the server computer system, a text string corresponding to a voice command received at a portable electronic device; receiving contextual information from the portable electronic device; processing the text string and the contextual information; and transmitting results associated with processing the text string and the contextual information to the portable electronic device. | 1. A method for operating an automated assistant, comprising: at a server computer system comprising a processor and memory storing instructions for execution by the processor: receiving, from a speech recognition service operated separately from the server computer system, a text string corresponding to a voice command received at a portable electronic device; receiving contextual information from the portable electronic device; processing the text string and the contextual information; and transmitting results associated with processing the text string and the contextual information to the portable electronic device. 17. The method of claim 1 , wherein the speech recognition service comprises a software application executed by a second computer system remote from the server computer system. | 0.658859 |
19. Document processing apparatus, comprising: means for inputting data representing documents and titles respectively associated with the documents by a plurality of key input operations and indicating a registration of the input documents and titles; means, in response to the registration indication by said inputting means, for storing in a random order characters comprising documents and titles input by said inputting means, said storing means having a field for numbering, an evaluation value obtained by comparing each of the titles being stored in the field and a currently displayed title being changed to a title to be displayed with other titles in a reverse sequence or in a forward sequence in accordance with the stored value; means for displaying a portion of the titles stored in said storing means; means for generating first and second display control signals; means for assigning the titles stored in said storing means an order by comparing each of the titles and generating the evaluation value for each of the titles, the order of the titles being indicated by the generated evaluation values; and control means responsive to said first display control signal for controlling said display means to display a first title stored in said storing means, the first title being first with respect to the other titles stored in said storing means in the order assigned thereto by said assigning means until successive second display control signals are generated and then responsive to said second display control signals for controlling said display means to sequentially display each of the titles stored in said storing means in the assigned order following the first displayed title. | 19. Document processing apparatus, comprising: means for inputting data representing documents and titles respectively associated with the documents by a plurality of key input operations and indicating a registration of the input documents and titles; means, in response to the registration indication by said inputting means, for storing in a random order characters comprising documents and titles input by said inputting means, said storing means having a field for numbering, an evaluation value obtained by comparing each of the titles being stored in the field and a currently displayed title being changed to a title to be displayed with other titles in a reverse sequence or in a forward sequence in accordance with the stored value; means for displaying a portion of the titles stored in said storing means; means for generating first and second display control signals; means for assigning the titles stored in said storing means an order by comparing each of the titles and generating the evaluation value for each of the titles, the order of the titles being indicated by the generated evaluation values; and control means responsive to said first display control signal for controlling said display means to display a first title stored in said storing means, the first title being first with respect to the other titles stored in said storing means in the order assigned thereto by said assigning means until successive second display control signals are generated and then responsive to said second display control signals for controlling said display means to sequentially display each of the titles stored in said storing means in the assigned order following the first displayed title. 25. Document processing apparatus according to claim 19, wherein said control means sequentially updates a part of the displayed titles in response to the second display control signals. | 0.60978 |
4. The method for voice communication as claimed in claim 1 further comprising a method for performing a function of emitting memory sound, which comprises the following steps: (J) receiving a memory message generated after the user clicks at least one storage location unit of the plurality of storage location units; (K) searching for a corresponding storage location according to the memory message; and (L) playing each of the voice files sequentially recorded in the storage location. | 4. The method for voice communication as claimed in claim 1 further comprising a method for performing a function of emitting memory sound, which comprises the following steps: (J) receiving a memory message generated after the user clicks at least one storage location unit of the plurality of storage location units; (K) searching for a corresponding storage location according to the memory message; and (L) playing each of the voice files sequentially recorded in the storage location. 5. The method for voice communication as claimed in claim 4 , wherein the plurality of function units further comprise a memory playback unit, and the method for performing a function of emitting memory sounds further comprises the following step before step (I): (M) receiving a playback command generated after the user clicks the memory playback unit. | 0.895504 |
15. One or more non-transitory computer-readable media comprising computer-executable instructions that, when executed, configure a processor of a device to perform acts comprising: receiving query terms input to the device by a user; compiling a list of electronic items stored in memory of the device that contain at least one instance of each query term; sorting the list of electronic items based on a number of instances of the query terms in each electronic item, wherein sorting the list comprises: determining a fuzz factor for each electronic item in the list, and organizing the list based on the fuzz factor wherein the fuzz factor comprises a number that is derived using less processing than determining that at least one instance of the query terms are located within a predetermined proximity of each other and which is indicative of a likelihood that each electronic item has the query terms located within the predetermined proximity of each other; determining electronic items from the sorted list having at least one instance of the query terms located within the predetermined proximity of each other in an electronic item, wherein the predetermined proximity varies based on one or more of the following: size of each respective electronic item, a quantity of query terms input to the device, or average word size of the electronic item; and displaying, on a display of the device, results including electronic items from the sorted list determined to have at least one instance of the query terms located within the predetermined proximity of each other. | 15. One or more non-transitory computer-readable media comprising computer-executable instructions that, when executed, configure a processor of a device to perform acts comprising: receiving query terms input to the device by a user; compiling a list of electronic items stored in memory of the device that contain at least one instance of each query term; sorting the list of electronic items based on a number of instances of the query terms in each electronic item, wherein sorting the list comprises: determining a fuzz factor for each electronic item in the list, and organizing the list based on the fuzz factor wherein the fuzz factor comprises a number that is derived using less processing than determining that at least one instance of the query terms are located within a predetermined proximity of each other and which is indicative of a likelihood that each electronic item has the query terms located within the predetermined proximity of each other; determining electronic items from the sorted list having at least one instance of the query terms located within the predetermined proximity of each other in an electronic item, wherein the predetermined proximity varies based on one or more of the following: size of each respective electronic item, a quantity of query terms input to the device, or average word size of the electronic item; and displaying, on a display of the device, results including electronic items from the sorted list determined to have at least one instance of the query terms located within the predetermined proximity of each other. 21. The one or more non-transitory computer-readable media of claim 15 , wherein the predetermined proximity comprises a byte offset between query terms. | 0.626925 |
3. The method of claim 1 , wherein the generating the item models based on the user preference data of the plurality of users and the item information of the plurality of items comprises generating the item models using a combination of content-based features associated with the plurality of items and collaborative-based features associated with the user preference data of the plurality of users. | 3. The method of claim 1 , wherein the generating the item models based on the user preference data of the plurality of users and the item information of the plurality of items comprises generating the item models using a combination of content-based features associated with the plurality of items and collaborative-based features associated with the user preference data of the plurality of users. 6. The method of claim 3 , further comprising: generating the collaborative-based features by applying a dimensionality reduction method on the user preference data of the plurality of users. | 0.923166 |
17. A system comprising: one or more processors; and a memory storing instructions that, when executed, cause the system to: identify a channel category of a channel for a user based on one of a historical trend and a user activity; receive a request to customize a stream of content for the channel category; responsive to the request to customize, query new content items based on the channel category and a channel attribute; receive candidate content items that include the channel category and the channel attribute; determine a user-independent score for each of the candidate content items to approximate popularity of each candidate content item within the stream of content that produced it; compute a global score for each of the candidate content items by normalizing the user-independent score for each candidate content item across a plurality of streams of content, the global score identifying a popularity of each candidate content item within the plurality of streams of content; customize the stream of content for the channel by adding the candidate content items to the stream of content based on the global score of each candidate content item; and provide the customized stream of content. | 17. A system comprising: one or more processors; and a memory storing instructions that, when executed, cause the system to: identify a channel category of a channel for a user based on one of a historical trend and a user activity; receive a request to customize a stream of content for the channel category; responsive to the request to customize, query new content items based on the channel category and a channel attribute; receive candidate content items that include the channel category and the channel attribute; determine a user-independent score for each of the candidate content items to approximate popularity of each candidate content item within the stream of content that produced it; compute a global score for each of the candidate content items by normalizing the user-independent score for each candidate content item across a plurality of streams of content, the global score identifying a popularity of each candidate content item within the plurality of streams of content; customize the stream of content for the channel by adding the candidate content items to the stream of content based on the global score of each candidate content item; and provide the customized stream of content. 22. The system of claim 17 wherein the system is further configured to receive a request from the user to subscribe to an existing channel. | 0.614202 |
12. The headset of claim 11 , wherein detecting at least one of a start or a stop of speech comprises for each of a set of two or more fragments: determining how many of the fragments in the set are classified as a first one of the classifications; and treating the entire set as either speech or non-speech based on how many of the fragments in the set are classified as the first one of the classifications. | 12. The headset of claim 11 , wherein detecting at least one of a start or a stop of speech comprises for each of a set of two or more fragments: determining how many of the fragments in the set are classified as a first one of the classifications; and treating the entire set as either speech or non-speech based on how many of the fragments in the set are classified as the first one of the classifications. 13. The headset of claim 12 , wherein detecting a start of speech comprises identifying a set of fragments in which the number of fragments individually classified as speech exceeds a threshold as constituting speech. | 0.892782 |
1. A computer-implemented method for overlaying text content on a digital image with a foreground text color computed automatically given a particular text location region and size on the image, the method comprising the steps of: extracting all unique colors from an initial image by examining each of the image pixels, in order to create a foreground color set; filtering the foreground color set to remove one or more colors; for each foreground color in the filtered foreground color set: identifying one or more cluster colors, the cluster colors comprising colors that are similar to the foreground color; and calculating a cluster color count by summing the number of occurrences within the image of cluster colors; filtering out foreground colors that do not sufficiently contrast with the average background color of the text location region; sorting foreground colors by color contrast score; filtering non-distinct foreground colors; adding to the foreground color set one or more predetermined colors that contrast with the average background color of the text location region; selecting a rendering color from amongst the foreground color set; and generating an output image comprising text rendered in the rendering color at the text location region, over the initial image. | 1. A computer-implemented method for overlaying text content on a digital image with a foreground text color computed automatically given a particular text location region and size on the image, the method comprising the steps of: extracting all unique colors from an initial image by examining each of the image pixels, in order to create a foreground color set; filtering the foreground color set to remove one or more colors; for each foreground color in the filtered foreground color set: identifying one or more cluster colors, the cluster colors comprising colors that are similar to the foreground color; and calculating a cluster color count by summing the number of occurrences within the image of cluster colors; filtering out foreground colors that do not sufficiently contrast with the average background color of the text location region; sorting foreground colors by color contrast score; filtering non-distinct foreground colors; adding to the foreground color set one or more predetermined colors that contrast with the average background color of the text location region; selecting a rendering color from amongst the foreground color set; and generating an output image comprising text rendered in the rendering color at the text location region, over the initial image. 4. The method of claim 1 , in which the step of filtering unique foreground color set comprises removing colors with low cluster counts. | 0.766559 |
7. A user-interface method of incrementally searching among multiple documents and incrementally searching for subsections within individual documents using a single incremental search interface on an input-constrained user device having a screen and a keypad, the method comprising: displaying, in a first portion of the screen, a user interface text input component operable to receive incremental keystrokes entered using the keypad; receiving a sequence of incremental keystrokes entered into the text input component by a user of the device, wherein the sequence of incremental keystrokes represents a search query input; in response to each incremental keystroke of the sequence of incremental keystrokes, receiving a set of document index section indicators, wherein each document index section indicator uniquely identifies a specific point within a document associated with a subsection within said document, and wherein the subsection associated with the specific point matches at least a portion of the sequence of incremental keystrokes; in response to each incremental keystroke of the sequence of incremental keystrokes, receiving a set of document pointers, where each pointer uniquely identifies a document; displaying, in a second portion of the screen, said document index section indicators and document pointers; receiving browse actions from the user to browse through and to select one of said document index section indicators and document pointers; displaying, if a document index section indicator is selected, the identified document, beginning at the identified point within said document so that the user is presented with the subsection within said document that is relatively more relevant to the matched portion of the sequence of incremental keystrokes without having to first scan through one or more other subsections within said document that are relatively less relevant to the matched portion of the sequence of incremental keystrokes, or displaying, if a document pointer is selected, the beginning of the identified document; setting, responsive to the document selection, a query context that includes at least one document context associated with the selected document, wherein the document context represents an attribute of the selected document; subsequent to displaying the selected document, receiving a subsequent sequence of incremental keystrokes entered into the text input component by the user of the device, wherein the subsequent sequence of incremental keystrokes represents a subsequent search query input; and in response to each incremental keystroke of the subsequent sequence of incremental keystrokes, displaying a set of document index section indicators for the selected document in the second portion of the screen based on the set query context and at least a portion of the subsequent sequence of incremental keystrokes. | 7. A user-interface method of incrementally searching among multiple documents and incrementally searching for subsections within individual documents using a single incremental search interface on an input-constrained user device having a screen and a keypad, the method comprising: displaying, in a first portion of the screen, a user interface text input component operable to receive incremental keystrokes entered using the keypad; receiving a sequence of incremental keystrokes entered into the text input component by a user of the device, wherein the sequence of incremental keystrokes represents a search query input; in response to each incremental keystroke of the sequence of incremental keystrokes, receiving a set of document index section indicators, wherein each document index section indicator uniquely identifies a specific point within a document associated with a subsection within said document, and wherein the subsection associated with the specific point matches at least a portion of the sequence of incremental keystrokes; in response to each incremental keystroke of the sequence of incremental keystrokes, receiving a set of document pointers, where each pointer uniquely identifies a document; displaying, in a second portion of the screen, said document index section indicators and document pointers; receiving browse actions from the user to browse through and to select one of said document index section indicators and document pointers; displaying, if a document index section indicator is selected, the identified document, beginning at the identified point within said document so that the user is presented with the subsection within said document that is relatively more relevant to the matched portion of the sequence of incremental keystrokes without having to first scan through one or more other subsections within said document that are relatively less relevant to the matched portion of the sequence of incremental keystrokes, or displaying, if a document pointer is selected, the beginning of the identified document; setting, responsive to the document selection, a query context that includes at least one document context associated with the selected document, wherein the document context represents an attribute of the selected document; subsequent to displaying the selected document, receiving a subsequent sequence of incremental keystrokes entered into the text input component by the user of the device, wherein the subsequent sequence of incremental keystrokes represents a subsequent search query input; and in response to each incremental keystroke of the subsequent sequence of incremental keystrokes, displaying a set of document index section indicators for the selected document in the second portion of the screen based on the set query context and at least a portion of the subsequent sequence of incremental keystrokes. 9. The method according to claim 7 , wherein the received document index section indicators point to documents that have been previously selected by the user. | 0.685507 |
5. The method as claimed in claim 1 , comprising: identifying a new service version based on monitored message traffic; and comparing the new service version with known service versions to match to an earlier version of the service. | 5. The method as claimed in claim 1 , comprising: identifying a new service version based on monitored message traffic; and comparing the new service version with known service versions to match to an earlier version of the service. 7. The method as claimed in claim 5 , comprising: constructing a service version gateway for the matched earlier version of the service. | 0.968302 |
10. A computing system, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the one or more programs comprising instructions for: obtaining, using the one or more processors, a plurality of documents, wherein a respective document in the plurality of document is associated with a query independent score; selecting a first document in the plurality of documents in accordance with a query independent score associated with the first document, wherein the first document has a fingerprint that indicates that the first document has substantially identical content to every other document in the plurality of documents; indexing, in accordance with the query independent score, the first document thereby producing an indexed first document; and with respect to the plurality of documents, including only the indexed first document in a document index. | 10. A computing system, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the one or more programs comprising instructions for: obtaining, using the one or more processors, a plurality of documents, wherein a respective document in the plurality of document is associated with a query independent score; selecting a first document in the plurality of documents in accordance with a query independent score associated with the first document, wherein the first document has a fingerprint that indicates that the first document has substantially identical content to every other document in the plurality of documents; indexing, in accordance with the query independent score, the first document thereby producing an indexed first document; and with respect to the plurality of documents, including only the indexed first document in a document index. 11. The computing system of claim 10 , wherein the query independent score includes a document ranking value indicative of document importance. | 0.850511 |
8. The apparatus of claim 1, wherein the browser further automatically removes the entry from the bookmark list when the viewed page is not subsequently visited within a pre-determined time. | 8. The apparatus of claim 1, wherein the browser further automatically removes the entry from the bookmark list when the viewed page is not subsequently visited within a pre-determined time. 10. The apparatus of claim 8, wherein removing the entry further comprises the browser moving the entry to an archive folder. | 0.904639 |
6. A method of processing natural language assertions (NLAs), the method including auto-verification, the method comprising: demarcating elements of a register transfer language (RTL) description, the elements including at least one of predetermined terms or expressions; identifying an NLA; using a computer, translating the NLA into a verification language assertion (VLA) using a natural language parser (NLP) and synthesis techniques, wherein said translating includes replacing said elements with tokens, each token being a unique identifier, said tokens being treated by the NLP as nouns, thereby ensuring text maintenance during NLP processing; translating the VLA into an interpreted NLA (NLA*) using a VLA parser and pattern matching techniques; translating the NLA* into an interpreted VLA (VLA*); comparing the VLA and the VLA*; providing a warning when the VLA and the VLA* are different; and performing verification using the VLA when the VLA and the VLA* are not different. | 6. A method of processing natural language assertions (NLAs), the method including auto-verification, the method comprising: demarcating elements of a register transfer language (RTL) description, the elements including at least one of predetermined terms or expressions; identifying an NLA; using a computer, translating the NLA into a verification language assertion (VLA) using a natural language parser (NLP) and synthesis techniques, wherein said translating includes replacing said elements with tokens, each token being a unique identifier, said tokens being treated by the NLP as nouns, thereby ensuring text maintenance during NLP processing; translating the VLA into an interpreted NLA (NLA*) using a VLA parser and pattern matching techniques; translating the NLA* into an interpreted VLA (VLA*); comparing the VLA and the VLA*; providing a warning when the VLA and the VLA* are different; and performing verification using the VLA when the VLA and the VLA* are not different. 9. The method of claim 6 , further including comparing the NLA to a set of NLAs in a cache, and proceeding directly to the performing verification when the NLA matches one NLA in the set of NLAs, wherein the verification is performed with a one VLA stored in the cache and associated with the matched NLA. | 0.531053 |
1. A system comprising: a processor; a display; and a memory executing a computer program for dynamic playback of playable content, by a player application that has at least one of a stop control, a play control and a pause control, the computer program comprises instructions to cause the processor to: launch the player application; receive by the player application information content from user selected resources; determine formats of the information content from the user selected resources; determine which of the user selected resources are not in a specified mark-up language format; convert information content from the user selected resources that are not in the specified mark-up language format into the specified mark-up language format: parse and decode the converted information content into code functions and data elements to provide a dataset; load the dataset and the code functions into a player window to convert the dataset into produced visual playable content items; store by the player application the produced visual playable content items in a queue of visual playable content items; receive by the player application an assertion of at least one of the stop control, the play control and the pause control to play a user selection of the queued visual playable content items; and visually render in a player window user selected ones of the queued visual playable content items in a sequence for a period of time, with the sequence being regularly repeated, and with the period of time of the sequence, the selection of the queued visual playable content items, and a repetition rate of the sequence being based on user defined parameters. | 1. A system comprising: a processor; a display; and a memory executing a computer program for dynamic playback of playable content, by a player application that has at least one of a stop control, a play control and a pause control, the computer program comprises instructions to cause the processor to: launch the player application; receive by the player application information content from user selected resources; determine formats of the information content from the user selected resources; determine which of the user selected resources are not in a specified mark-up language format; convert information content from the user selected resources that are not in the specified mark-up language format into the specified mark-up language format: parse and decode the converted information content into code functions and data elements to provide a dataset; load the dataset and the code functions into a player window to convert the dataset into produced visual playable content items; store by the player application the produced visual playable content items in a queue of visual playable content items; receive by the player application an assertion of at least one of the stop control, the play control and the pause control to play a user selection of the queued visual playable content items; and visually render in a player window user selected ones of the queued visual playable content items in a sequence for a period of time, with the sequence being regularly repeated, and with the period of time of the sequence, the selection of the queued visual playable content items, and a repetition rate of the sequence being based on user defined parameters. 4. The system of claim 1 wherein the received information content is from resources that include one or more of feeds including syndication feeds, podcast feeds and web folders of images, text, and video data, and with at least some of the syndication feeds, podcast feeds and web folders of images, text, and video data. | 0.606061 |
12. A system, comprising: a data processing apparatus; and a computer-readable storage medium coupled to the data processing apparatus and storing a dictionary defining query triggers, each of the query triggers being one or more terms; wherein the computer-readable medium also stores instructions that, when executed by the data processing apparatus, cause the data processing apparatus to perform operations comprising: identifying query triggers in a resource displayed in a web browser application environment on the data processing apparatus, wherein the resource is a non-query resource; for each query trigger identified in the resource, calculating a rank score for the query trigger based on attributes of the query trigger, the attributes including at least one of: a context of the query trigger defined by a display format of the query trigger in the resource; and a frequency of occurrence of the query trigger in the resource; ranking the query triggers according to the rank scores; generating search query suggestions from the query triggers identified in the resource; and presenting the search query suggestions in the web browser application environment according to the ranking of the query triggers. | 12. A system, comprising: a data processing apparatus; and a computer-readable storage medium coupled to the data processing apparatus and storing a dictionary defining query triggers, each of the query triggers being one or more terms; wherein the computer-readable medium also stores instructions that, when executed by the data processing apparatus, cause the data processing apparatus to perform operations comprising: identifying query triggers in a resource displayed in a web browser application environment on the data processing apparatus, wherein the resource is a non-query resource; for each query trigger identified in the resource, calculating a rank score for the query trigger based on attributes of the query trigger, the attributes including at least one of: a context of the query trigger defined by a display format of the query trigger in the resource; and a frequency of occurrence of the query trigger in the resource; ranking the query triggers according to the rank scores; generating search query suggestions from the query triggers identified in the resource; and presenting the search query suggestions in the web browser application environment according to the ranking of the query triggers. 19. The system of claim 12 , further comprising rendering the resource in a first thread of a browser application at the client device; and wherein identifying the query triggers in the resource comprises identifying the query triggers in a second thread of a browser application, the second thread independent of the first thread. | 0.717489 |
3. A system for defining a human resources system, comprising: a processor; a storage module for storing data associated with the human resources system; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to: receive at least one new metadata model that defines at least one new object class in the human resource system, wherein the new metadata model includes one or more attributes, one or more relationships, and one or more methods associated with the new object class; receive process definitions; store the new metadata model including data associated with the new metadata model, and the process definitions in a minimalistic metamodel for persistence, wherein the minimalistic metamodel for persistence comprises three tables comprising an instance table, an attribute table, and a reference table for all of the objects in the human resources system, wherein the new metadata model including data associated with the new metadata model is stored by storing one or more instances of the new object class in the instance table, the one or more attributes in the attribute table, and the one or more relationships in the reference table, wherein: the instance table stores all instances of object classes in the human resource system as defined by a plurality of metadata models; the attribute table stores attribute data associated with all the instances of the object classes as defined by the plurality of metadata models; the reference table stores relationship data associated with all the instances of the object classes as defined by the plurality of metadata models; the instance table, the attribute table, and the reference table store data that has been specified; metadata model definitions and the process definitions are able to be interpreted using an interpretive engine; and the interpretive engine is configured to process the metadata model definitions and process definitions without compilation of any code; at a time of execution by the interpretive engine, all the objects specified in the instance table, the attribute table, and the reference table and processes are loaded into the memory for easy modification of instances of objects defined by the plurality of metadata models and the new metadata model; and for a process of one or more processes defined by the process definitions: defining an element to which the process responds; defining one or more process steps in response to the element; and defining an output response, wherein the process when interpreted by the interpretive engine are sufficient to define a fully functional human resource system; receive an update, wherein the update includes a change to an existing instance of an object class in the human resource system; update the human resource system by adding, removing, or changing a plurality of entries associated with the existing instance of the object class in at least one of the instance table, the attribute table, and the reference table, comprising: validate a transaction request relating to the existing instance of the object class, comprising: ensure a requestor has privileges to perform a requested transaction; check whether the transaction request corresponds to a metadata definition of an element of the transaction request; and ensure that data in the requested transaction is of a correct type and in a correct range of values; determine whether a controlling object to be updated exists, wherein the instances of the object class are organized in a tree structure, the controlling object relating to a trunk of the tree structure; in the event that the controlling object to be updated does not exist create the controlling object; and in the event that the controlling object to be updated exists, locate the controlling object associated with an instance of the object class; transfer the plurality of entries associated with the existing instance of the object class in the at least one of the instance table, the attribute table, and the reference table to the storage module after the updating of the human resource system is performed, wherein the transferring of the plurality of entries to the storage module is performed after each of the adding, removing, or changing to the plurality of entries have been completed to avoid inconsistencies in the human resource system the storage module including permanent storage; and execute the updated human resources system by interpreting the stored metadata model definitions and process definitions using the interpretive engine. | 3. A system for defining a human resources system, comprising: a processor; a storage module for storing data associated with the human resources system; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to: receive at least one new metadata model that defines at least one new object class in the human resource system, wherein the new metadata model includes one or more attributes, one or more relationships, and one or more methods associated with the new object class; receive process definitions; store the new metadata model including data associated with the new metadata model, and the process definitions in a minimalistic metamodel for persistence, wherein the minimalistic metamodel for persistence comprises three tables comprising an instance table, an attribute table, and a reference table for all of the objects in the human resources system, wherein the new metadata model including data associated with the new metadata model is stored by storing one or more instances of the new object class in the instance table, the one or more attributes in the attribute table, and the one or more relationships in the reference table, wherein: the instance table stores all instances of object classes in the human resource system as defined by a plurality of metadata models; the attribute table stores attribute data associated with all the instances of the object classes as defined by the plurality of metadata models; the reference table stores relationship data associated with all the instances of the object classes as defined by the plurality of metadata models; the instance table, the attribute table, and the reference table store data that has been specified; metadata model definitions and the process definitions are able to be interpreted using an interpretive engine; and the interpretive engine is configured to process the metadata model definitions and process definitions without compilation of any code; at a time of execution by the interpretive engine, all the objects specified in the instance table, the attribute table, and the reference table and processes are loaded into the memory for easy modification of instances of objects defined by the plurality of metadata models and the new metadata model; and for a process of one or more processes defined by the process definitions: defining an element to which the process responds; defining one or more process steps in response to the element; and defining an output response, wherein the process when interpreted by the interpretive engine are sufficient to define a fully functional human resource system; receive an update, wherein the update includes a change to an existing instance of an object class in the human resource system; update the human resource system by adding, removing, or changing a plurality of entries associated with the existing instance of the object class in at least one of the instance table, the attribute table, and the reference table, comprising: validate a transaction request relating to the existing instance of the object class, comprising: ensure a requestor has privileges to perform a requested transaction; check whether the transaction request corresponds to a metadata definition of an element of the transaction request; and ensure that data in the requested transaction is of a correct type and in a correct range of values; determine whether a controlling object to be updated exists, wherein the instances of the object class are organized in a tree structure, the controlling object relating to a trunk of the tree structure; in the event that the controlling object to be updated does not exist create the controlling object; and in the event that the controlling object to be updated exists, locate the controlling object associated with an instance of the object class; transfer the plurality of entries associated with the existing instance of the object class in the at least one of the instance table, the attribute table, and the reference table to the storage module after the updating of the human resource system is performed, wherein the transferring of the plurality of entries to the storage module is performed after each of the adding, removing, or changing to the plurality of entries have been completed to avoid inconsistencies in the human resource system the storage module including permanent storage; and execute the updated human resources system by interpreting the stored metadata model definitions and process definitions using the interpretive engine. 6. A system as in claim 3 , wherein at least one of the one or more attributes includes subclasses. | 0.576726 |
21. The system of claim 20 , wherein each sentence includes a language-specific property, wherein the generating the language independent semantic structure includes encoding the language-specific property with a language-independent parameter. | 21. The system of claim 20 , wherein each sentence includes a language-specific property, wherein the generating the language independent semantic structure includes encoding the language-specific property with a language-independent parameter. 22. The system of claim 21 , wherein the index generation component is further configured to index at least one meaning of each language-independent parameter. | 0.943504 |
2. The method of claim 1 wherein the plurality of search results are calculated according to one or more relationships between one or more of the plurality of common attributes shared by the one or more of the plurality of potential search terms and the one or more of the plurality of search terms. | 2. The method of claim 1 wherein the plurality of search results are calculated according to one or more relationships between one or more of the plurality of common attributes shared by the one or more of the plurality of potential search terms and the one or more of the plurality of search terms. 3. The method of claim 2 wherein the one or more relationships are established using a cluster analysis. | 0.934612 |
13. The client of claim 1 , wherein the client is a desktop computer. | 13. The client of claim 1 , wherein the client is a desktop computer. 16. The mobile phone of claim 13 , wherein the auxiliary information is at least one of an additional passage of text from the source text, an ISBN number corresponding to the source text, a title of source text, a or bar code corresponding to the source text. | 0.897567 |
19. A computer-program product, including executable instructions that when executed, cause a data processing apparatus to: receive a resource library at a calling entity, wherein the calling entity is located at a particular site, and wherein the resource library is a software resource library that includes a function, an embedded unique key, and an embedded text string specifying one or more use terms; run an application at the calling entity, wherein the application includes an embedded copy of the unique key and a copy of the text string, and wherein running the application includes using the resource library; extract the unique key and the text string from the resource library, wherein extracting includes using the function on the resource library; determine the authenticity of the extracted unique key and the text string, wherein determining includes using the function on the resource library; and determine whether the resource library is licensed for unrestricted use with any application at the particular site, wherein determining includes using the function on the resource library, and wherein extracting the unique key and the text string from the resource library, determining the authenticity of the extracted unique key and the text string, and determining whether the resource library is licensed for unrestricted use with any application at the particular site are based upon a license parameter. | 19. A computer-program product, including executable instructions that when executed, cause a data processing apparatus to: receive a resource library at a calling entity, wherein the calling entity is located at a particular site, and wherein the resource library is a software resource library that includes a function, an embedded unique key, and an embedded text string specifying one or more use terms; run an application at the calling entity, wherein the application includes an embedded copy of the unique key and a copy of the text string, and wherein running the application includes using the resource library; extract the unique key and the text string from the resource library, wherein extracting includes using the function on the resource library; determine the authenticity of the extracted unique key and the text string, wherein determining includes using the function on the resource library; and determine whether the resource library is licensed for unrestricted use with any application at the particular site, wherein determining includes using the function on the resource library, and wherein extracting the unique key and the text string from the resource library, determining the authenticity of the extracted unique key and the text string, and determining whether the resource library is licensed for unrestricted use with any application at the particular site are based upon a license parameter. 23. The computer-program product of claim 19 , wherein determining whether the calling entity is licensed to use the resource library includes determining whether the copy of the text string was validly issued by a resource library vendor. | 0.604372 |
11. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, the computer-program product including instructions operable to cause a computing device to perform operations including: receive an indication of a specified task to be performed, wherein the specified task comprises first and second subtasks; receive an indication of a specified source device to perform the first and second subtasks, wherein the source device stores a source data set to serve as an input to performance of the specified task; retrieve from the specified source device an indication of a source processing environment currently available within at least the specified source device in response to the receipt of the indication of the specified source device, wherein the indication of the source processing environment comprises indications of an identity and version level of a database routine of the specified source device; determine a first set of one or more languages able to be interpreted by the database routine of the specified source device based on the identity and version level of the database routine of the specified source device; determine whether to perform the first and second subtasks sequentially or at least partly in parallel based on at least one aspect of the source processing environment; select a language of the first set of languages in which to generate instructions to perform at least the first subtask based on the determination of whether to perform the first and second subtasks sequentially or at least partly in parallel; generate the instructions to perform the first subtask in the selected language; and transmit first task instructions comprising at least the instructions generated to perform at least the first subtask to the specified source device. | 11. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, the computer-program product including instructions operable to cause a computing device to perform operations including: receive an indication of a specified task to be performed, wherein the specified task comprises first and second subtasks; receive an indication of a specified source device to perform the first and second subtasks, wherein the source device stores a source data set to serve as an input to performance of the specified task; retrieve from the specified source device an indication of a source processing environment currently available within at least the specified source device in response to the receipt of the indication of the specified source device, wherein the indication of the source processing environment comprises indications of an identity and version level of a database routine of the specified source device; determine a first set of one or more languages able to be interpreted by the database routine of the specified source device based on the identity and version level of the database routine of the specified source device; determine whether to perform the first and second subtasks sequentially or at least partly in parallel based on at least one aspect of the source processing environment; select a language of the first set of languages in which to generate instructions to perform at least the first subtask based on the determination of whether to perform the first and second subtasks sequentially or at least partly in parallel; generate the instructions to perform the first subtask in the selected language; and transmit first task instructions comprising at least the instructions generated to perform at least the first subtask to the specified source device. 12. The computer-program product of claim 11 , the computing device caused to perform operations including: generate for presentation on a display a selection of tasks, wherein the selection of tasks comprises the specified task; generate for presentation on the display a selection of operations to perform on at least a portion of the source data set in response to the receipt of the indication of the specified task; receive an indication of selection of one or more operations from the presented selection of operations; and identify at least the first and second subtasks from the selected one or more operations. | 0.67649 |
1. An apparatus for acquiring data words which are present on synchronous logic circuitry of a system under test, comprising: (a) detecting means coupled to said data bus for producing an acquisition signal indicative of the occurrence of at least one particular data word on said logic circuitry; (b) data storage means having a plurality of storage locations and addresses corresponding with said locations, said data storage means coupled to said data bus for storing a plurality of successive data words; and (c) addressing means, responsive to said acquisition signal and to the presence of data words on said data bus, for producing the storage addresses of said successive data words in said data storage means such that a predetermined number of successive data words preceding each said particular data word on said logic circuitry are stored in locations in said data storage means corresponding to said storage addresses. | 1. An apparatus for acquiring data words which are present on synchronous logic circuitry of a system under test, comprising: (a) detecting means coupled to said data bus for producing an acquisition signal indicative of the occurrence of at least one particular data word on said logic circuitry; (b) data storage means having a plurality of storage locations and addresses corresponding with said locations, said data storage means coupled to said data bus for storing a plurality of successive data words; and (c) addressing means, responsive to said acquisition signal and to the presence of data words on said data bus, for producing the storage addresses of said successive data words in said data storage means such that a predetermined number of successive data words preceding each said particular data word on said logic circuitry are stored in locations in said data storage means corresponding to said storage addresses. 3. The apparatus of claim 1 wherein said addressing means comprises: (a) a first counting means responsive to said acquisition signal, for producing a first signal representative of a predetermined number of most significant bits of each said storage address; and (b) a second counting means, responsive to the presence of said data words, for producing a second pointer signal representative of a predetermined number of least significant bits of each said storage address. | 0.5 |
16. A non-transitory computer readable storage medium having embodied thereon instructions, the instructions being executable by a processor to perform a method for creating a forum, the method comprising: receiving a selection of a topic-based lesson from a plurality of topics of interest; providing an interface for the selected topic-based lesson, the interface generated from a first template of a plurality of templates, the first template providing a type of discussion and lesson content; receiving a submission associated with the topic-based lesson and in the form of the type of discussion, the submission received from a user through the interface, the user submission received as input in a structured format including quantitative collaborative input elements, and the user submission extensible to other individuals and embedded in an interactive environment, and wherein the selected topic-based lesson, the first template, and the user submission form a self-contained learning unit, the self-contained learning unit embeddable in a digital environment; and updating a forum interface based on the user submission. | 16. A non-transitory computer readable storage medium having embodied thereon instructions, the instructions being executable by a processor to perform a method for creating a forum, the method comprising: receiving a selection of a topic-based lesson from a plurality of topics of interest; providing an interface for the selected topic-based lesson, the interface generated from a first template of a plurality of templates, the first template providing a type of discussion and lesson content; receiving a submission associated with the topic-based lesson and in the form of the type of discussion, the submission received from a user through the interface, the user submission received as input in a structured format including quantitative collaborative input elements, and the user submission extensible to other individuals and embedded in an interactive environment, and wherein the selected topic-based lesson, the first template, and the user submission form a self-contained learning unit, the self-contained learning unit embeddable in a digital environment; and updating a forum interface based on the user submission. 17. The non-transitory computer readable storage medium of claim 16 , the method further comprising providing a current status of a plurality of forums. | 0.522476 |
5. The computer-based system of claim 4, wherein compliance with at least one of a legal requirement and a business practice comprises: a content block for a type of significant communication; and a protocol for manipulation of the content of such block. | 5. The computer-based system of claim 4, wherein compliance with at least one of a legal requirement and a business practice comprises: a content block for a type of significant communication; and a protocol for manipulation of the content of such block. 6. The computer-based system of claim 5, wherein the significant communication is a performative utterance. | 0.942184 |
9. A system comprising a set-top box with control circuitry configured to: generate for display a display item having a first program function, wherein the first program function is based on a non-markup language, and the first program function is preprogrammed on the set-top box; receive a markup language document from a remote source; interpret the markup language document to determine that the markup language document assigns a second program function to the display item; update the set-top box based on the markup language document such that the display item has the second program function; and generate for display, the display item having the second program function. | 9. A system comprising a set-top box with control circuitry configured to: generate for display a display item having a first program function, wherein the first program function is based on a non-markup language, and the first program function is preprogrammed on the set-top box; receive a markup language document from a remote source; interpret the markup language document to determine that the markup language document assigns a second program function to the display item; update the set-top box based on the markup language document such that the display item has the second program function; and generate for display, the display item having the second program function. 11. The system of claim 9 , wherein the second program function causes a display of the display item to change in response to a user input. | 0.863281 |
11. The method of claim 7 , wherein the performing of the matching algorithms on the query image and the generating of the scores comprises: configuring R, G and B channel images from the query image; performing a matching algorithm on the R, G and B channel images and generating R, G and B channel scores; normalizing the R, G and B channel scores; estimating a weight of each of the normalized R, G and B channel scores based on an EER and contribution of each of the normalized R, G and B channel images; and fusing the normalized R, G and B channel scores using the weights thereof. | 11. The method of claim 7 , wherein the performing of the matching algorithms on the query image and the generating of the scores comprises: configuring R, G and B channel images from the query image; performing a matching algorithm on the R, G and B channel images and generating R, G and B channel scores; normalizing the R, G and B channel scores; estimating a weight of each of the normalized R, G and B channel scores based on an EER and contribution of each of the normalized R, G and B channel images; and fusing the normalized R, G and B channel scores using the weights thereof. 12. The method of claim 11 , wherein the EER according to each matching algorithm is used in the estimating of the weights. | 0.881566 |
2. A computer-implemented method for collecting event information, comprising: on a server system having one or more processors for executing one or more programs stored in memory of the server system so as to perform the method: loading a plurality of XML documents, each XML document specifying event parsing logic for a respective group of related events; storing in one or more parsing trees a representation of the event parsing logic in the plurality of XML documents, the one or more parsing trees including event parsing logic for parsing events in a plurality of groups of events; receiving events, including a first event and a second event; processing the second event in accordance the event parsing logic for a first group of events that includes both the first event and second event, the processing of the second event including: extracting information from the first event in accordance with the event parsing logic for the first group of events; extracting information from the second event in accordance with the event parsing logic for the first group of events; supplementing at least a portion of the information extracted from the second event with at least a portion of the information extracted from the first event, in accordance with the event parsing logic for the first group of events, to produce enhanced information for the second event; and storing the enhanced information for the second event in computer readable memory. | 2. A computer-implemented method for collecting event information, comprising: on a server system having one or more processors for executing one or more programs stored in memory of the server system so as to perform the method: loading a plurality of XML documents, each XML document specifying event parsing logic for a respective group of related events; storing in one or more parsing trees a representation of the event parsing logic in the plurality of XML documents, the one or more parsing trees including event parsing logic for parsing events in a plurality of groups of events; receiving events, including a first event and a second event; processing the second event in accordance the event parsing logic for a first group of events that includes both the first event and second event, the processing of the second event including: extracting information from the first event in accordance with the event parsing logic for the first group of events; extracting information from the second event in accordance with the event parsing logic for the first group of events; supplementing at least a portion of the information extracted from the second event with at least a portion of the information extracted from the first event, in accordance with the event parsing logic for the first group of events, to produce enhanced information for the second event; and storing the enhanced information for the second event in computer readable memory. 3. The method of claim 2 , including adding a new XML document to the plurality of XML documents, the new XML document specifying event parsing logic for an additional group of events; and storing in a parsing tree a representation of the event parsing logic contained in the new XML document. | 0.546726 |
11. The simulation tool of claim 10 , wherein the customized mark-up language includes an internal variable for nominal output of the voice application. | 11. The simulation tool of claim 10 , wherein the customized mark-up language includes an internal variable for nominal output of the voice application. 12. The simulation tool of claim 11 , wherein the simulation tool is further configured to: (i) set the internal variable to equal the nominal output of the voice application; (ii) resolve a first conditional statement using a first conditional tag to generate the first simulated input if the internal variable equals a first nominal output of the voice application; and (iii) resolve a second conditional statement using a second conditional tag to generate the second simulated input if the internal variable equals a second nominal output of the voice application. | 0.727751 |
3. A method in a computing device for automatically identifying keywords for advertisement placement, the method comprising: extracting one or more keywords from a data feed, the data feed providing information about one or more content data; for each extracted keyword, identifying, facilitated by a computer processor, a category of products to advertise with the extracted keyword from among a plurality of categories of products, the products being related to the keyword but the category being independent of a subject of the keyword, the identification based at least in part on (1) an expected benefit of advertising in a first of the plurality of categories of products and (2) at least one attribute of text contained in at least one product of a second of the plurality of categories of products, the identification including selecting from among the first and the second of the plurality of categories of products based at least in part on scores determined for the expected benefit and the text, the scores normalized to facilitate comparison; generating a link for a landing page for the extracted keyword, the landing page for displaying search results of a query of the identified category based at least in part on the extracted keyword; and generating a creative for the extracted keyword; and submitting to an advertisement placement service an extracted keyword, the link for the extracted keyword, and the creative for the extracted keyword. | 3. A method in a computing device for automatically identifying keywords for advertisement placement, the method comprising: extracting one or more keywords from a data feed, the data feed providing information about one or more content data; for each extracted keyword, identifying, facilitated by a computer processor, a category of products to advertise with the extracted keyword from among a plurality of categories of products, the products being related to the keyword but the category being independent of a subject of the keyword, the identification based at least in part on (1) an expected benefit of advertising in a first of the plurality of categories of products and (2) at least one attribute of text contained in at least one product of a second of the plurality of categories of products, the identification including selecting from among the first and the second of the plurality of categories of products based at least in part on scores determined for the expected benefit and the text, the scores normalized to facilitate comparison; generating a link for a landing page for the extracted keyword, the landing page for displaying search results of a query of the identified category based at least in part on the extracted keyword; and generating a creative for the extracted keyword; and submitting to an advertisement placement service an extracted keyword, the link for the extracted keyword, and the creative for the extracted keyword. 5. The method of claim 3 wherein the extracted keywords are selected from the group consisting of proper names, statistically improbable phrases, capitalized phrases, and title of the data feed. | 0.602557 |
9. The computer-readable media of claim 1 , further comprising: receiving a schedule of resources; and comparing the forecast of resource needs to the schedule of resources to determine one or more differences. | 9. The computer-readable media of claim 1 , further comprising: receiving a schedule of resources; and comparing the forecast of resource needs to the schedule of resources to determine one or more differences. 10. The computer-readable media of claim 9 , further comprising: based on the determined one or more differences, automatically altering the schedule of resources. | 0.907443 |
1. An indexing system for linking formally expressed knowledge with a corpus of content having a plurality of pieces of content, the system comprising: a knowledge base containing a plurality of pieces of formally expressed knowledge, the formally represented knowledge further comprising one or more synsets wherein each synset contains a group of terms that have a similar meaning, one or more taxonomies wherein each taxonomy contains one or more synsets in a subject matter area that are organized from a synset having a general meaning to a synset having a specific meaning, one or more ontologies wherein each ontology contains one or more synsets associated with an area of interest and one or more facets wherein each facet is associated with a particular ontology and wherein a document is associated with the facet when the document contains the one or more synsets associated with the facet; a computer system having one or more software pieces each having a plurality of lines of computer instructions wherein the computer instructions are executed by the computer system, the software pieces further comprising an index engine that indexes each piece of content in a corpus to generate one or more indexes for each piece of content, the index engine further comprising an assignment engine that assigns an index to each piece of content based on the formally expressed knowledge contained in the knowledge base. | 1. An indexing system for linking formally expressed knowledge with a corpus of content having a plurality of pieces of content, the system comprising: a knowledge base containing a plurality of pieces of formally expressed knowledge, the formally represented knowledge further comprising one or more synsets wherein each synset contains a group of terms that have a similar meaning, one or more taxonomies wherein each taxonomy contains one or more synsets in a subject matter area that are organized from a synset having a general meaning to a synset having a specific meaning, one or more ontologies wherein each ontology contains one or more synsets associated with an area of interest and one or more facets wherein each facet is associated with a particular ontology and wherein a document is associated with the facet when the document contains the one or more synsets associated with the facet; a computer system having one or more software pieces each having a plurality of lines of computer instructions wherein the computer instructions are executed by the computer system, the software pieces further comprising an index engine that indexes each piece of content in a corpus to generate one or more indexes for each piece of content, the index engine further comprising an assignment engine that assigns an index to each piece of content based on the formally expressed knowledge contained in the knowledge base. 9. The system of claim 1 , wherein the index engine further comprises an authority determining engine that determines an authority score associated with each piece of content, the authority score being based on one or more factors including a reputation of the author of the piece of content and a reliability of the source of the piece of content. | 0.55707 |
21. The method of claim 12, wherein determining the placement for each character in the new comic panel further comprises determining the placement for each character in the new comic panel based upon the disposition of each character that is communicating in the new comic panel. | 21. The method of claim 12, wherein determining the placement for each character in the new comic panel further comprises determining the placement for each character in the new comic panel based upon the disposition of each character that is communicating in the new comic panel. 30. The method of claim 21, including providing the comic panel having a plurality of balloon bodies and wherein determining the position of the balloon further comprises determining a position of a balloon body of the balloon so that each balloon body in the comic panel is displayed in an order that the textual input for each character is received. | 0.918613 |
15. A method for processing a data stream of events, the method comprising: determining that multiple portions of a continuous event processing (CEP) query can be executed concurrently relative to an event in an event stream, the determining comprising: splitting the CEP query into a plurality of separate operators; determining a separate ordering constraint for each particular operator within the plurality of separate operators; determining an ordering constraint for the CEP query based at least in part on the ordering constraints that the processor determined for the plurality of separate operators; and determining, based on the ordering constraint for the CEP query, whether the multiple portions of the CEP query can be executed in a concurrent manner; and executing the multiple portions of the CEP query concurrently against a first event received via the event stream, the executing comprising: spawning multiple threads of execution that concurrently process the multiple portions of the CEP query against the first event received via the event stream in response to determining that the multiple portions of the CEP query can be executed in a concurrent manner. | 15. A method for processing a data stream of events, the method comprising: determining that multiple portions of a continuous event processing (CEP) query can be executed concurrently relative to an event in an event stream, the determining comprising: splitting the CEP query into a plurality of separate operators; determining a separate ordering constraint for each particular operator within the plurality of separate operators; determining an ordering constraint for the CEP query based at least in part on the ordering constraints that the processor determined for the plurality of separate operators; and determining, based on the ordering constraint for the CEP query, whether the multiple portions of the CEP query can be executed in a concurrent manner; and executing the multiple portions of the CEP query concurrently against a first event received via the event stream, the executing comprising: spawning multiple threads of execution that concurrently process the multiple portions of the CEP query against the first event received via the event stream in response to determining that the multiple portions of the CEP query can be executed in a concurrent manner. 20. The method of claim 15 , further comprising: merging, into a single shared operator, (a) a first operator that is used by a first CEP query that processes events in the event stream, and (b) a second operator that is used by a second CEP query that also processes events in the event stream, in response to determining that the first operator and the second operator both perform a particular type of operation; wherein determining the separate ordering constraint for each particular operator within the plurality of separate operators comprises determining the ordering constraint for a third operator, which receives input from the shared operator, based at least in part on the ordering constraint of the shared operator; wherein determining the separate ordering constraint for each particular operator within the plurality of separate operators comprises determining the ordering constraint for a fourth operator, which receives input from the shared operator, based at least in part on the ordering constraint of the shared operator; wherein the third operator is used by the first CEP query and is not used by the second CEP query; wherein the fourth operator is used by the second CEP query and is not used by the first CEP query. | 0.712702 |
1. A management system for a managed system, said management system comprising: a computer hardware processor, said hardware processor computing: a plurality of data sources, each data source interfaces with said managed system using a data sensor that collects data and attaches a hierarchical semantic tag to said collected data, said hierarchical semantic tag conveying information of: hierarchy information; a set of ontology trees that capture semantics comprising: monitoring metric relationships data; business functions data; and application components data; and a set of rules that capture relationships between hierarchical semantic tag hierarchies, relationships between nodes in different trees, relationships between metrics and relationships between application and business context of components monitored by said data sources; and a core engine that receives said data including said hierarchical semantic tag, and that performs domain-independent processing on said data based upon at least a portion of said hierarchical semantic tag, said core engine further comprising: a base event generation and aggregation layer that processes said hierarchical semantic tag to generate base events; an event composition filtering and correlation layer, that filters and composes said base events based on pre-defined rules to generate composite events; and an authoring tool for receiving from a user new hierarchies, and associations between hierarchical semantic tags and data sources, wherein said hierarchical semantic tag is associated with monitoring data, and is used by said managed system to apply management-specific functions to said data at a data center. | 1. A management system for a managed system, said management system comprising: a computer hardware processor, said hardware processor computing: a plurality of data sources, each data source interfaces with said managed system using a data sensor that collects data and attaches a hierarchical semantic tag to said collected data, said hierarchical semantic tag conveying information of: hierarchy information; a set of ontology trees that capture semantics comprising: monitoring metric relationships data; business functions data; and application components data; and a set of rules that capture relationships between hierarchical semantic tag hierarchies, relationships between nodes in different trees, relationships between metrics and relationships between application and business context of components monitored by said data sources; and a core engine that receives said data including said hierarchical semantic tag, and that performs domain-independent processing on said data based upon at least a portion of said hierarchical semantic tag, said core engine further comprising: a base event generation and aggregation layer that processes said hierarchical semantic tag to generate base events; an event composition filtering and correlation layer, that filters and composes said base events based on pre-defined rules to generate composite events; and an authoring tool for receiving from a user new hierarchies, and associations between hierarchical semantic tags and data sources, wherein said hierarchical semantic tag is associated with monitoring data, and is used by said managed system to apply management-specific functions to said data at a data center. 5. The management system according to claim 1 , wherein said core engine includes one or more processing modules, and said hierarchical semantic tags are used for routing said data to said processing modules. | 0.526776 |
15. The method of claim 1 , further comprising specifying a compound traversal record, being a combination of a plurality of the stored traversal records. | 15. The method of claim 1 , further comprising specifying a compound traversal record, being a combination of a plurality of the stored traversal records. 16. The method of claim 15 , further comprising playing back the compound traversal record by adjacently displaying the contents of each of the plurality of traversal records. | 0.917215 |
1. A method comprising, by one or more computing devices: receiving, from a client device associated with a first user of an online social network, a text query comprising one or more character strings, the online social network being associated with a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes; identifying one or more nodes and one or more edges of the social graph by determining one or more nodes and one or more edges of the social graph that match at least a portion of one or more of the character strings, wherein each of the identified nodes is within a threshold degree of separation within the social graph of a node corresponding to the first user; generating one or more recommended queries that each comprise the character strings of the text query and references to one or more of the identified nodes and one or more of the identified edges; and sending, to the client device associated with the first user in response to receiving the text query, one or more of the recommended queries for presentation to the first user. | 1. A method comprising, by one or more computing devices: receiving, from a client device associated with a first user of an online social network, a text query comprising one or more character strings, the online social network being associated with a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes; identifying one or more nodes and one or more edges of the social graph by determining one or more nodes and one or more edges of the social graph that match at least a portion of one or more of the character strings, wherein each of the identified nodes is within a threshold degree of separation within the social graph of a node corresponding to the first user; generating one or more recommended queries that each comprise the character strings of the text query and references to one or more of the identified nodes and one or more of the identified edges; and sending, to the client device associated with the first user in response to receiving the text query, one or more of the recommended queries for presentation to the first user. 6. The method of claim 1 , wherein identifying one or more nodes comprises, for each character string: determining for each node of the plurality of nodes whether the node matches the character string; and identifying each node that matches the character string. | 0.617625 |
1. A method comprising: receiving a request with respect to at least one resource in a cloud, wherein the received request is in the form of a service level agreement; determining a set of resources among the at least one resource in the cloud in accordance with the received request, wherein determining the set of resources comprises: consulting an ontology including metadata associated with the at least one resource in the cloud, wherein consulting the ontology comprises comparing terms in the service level agreement with terms describing the at least one resource in the cloud; and computing the set of resources based on the metadata and the received request, wherein computing the set of resources comprises evaluating relationships among the at least one resource in the cloud; computing a cost factor with respect to the determined set of resources; and rendering the determined set of resources and the cost factor with respect to the determined set of resources. | 1. A method comprising: receiving a request with respect to at least one resource in a cloud, wherein the received request is in the form of a service level agreement; determining a set of resources among the at least one resource in the cloud in accordance with the received request, wherein determining the set of resources comprises: consulting an ontology including metadata associated with the at least one resource in the cloud, wherein consulting the ontology comprises comparing terms in the service level agreement with terms describing the at least one resource in the cloud; and computing the set of resources based on the metadata and the received request, wherein computing the set of resources comprises evaluating relationships among the at least one resource in the cloud; computing a cost factor with respect to the determined set of resources; and rendering the determined set of resources and the cost factor with respect to the determined set of resources. 7. The method of claim 1 , wherein computing the cost factor with respect to the determined set of resources comprises at least one of computing a cost factor for each of the determined set of resources and computing a total cost factor with respect to the determined set of resources. | 0.623124 |
1. A computer-implemented method comprising: as implemented by one or more computing devices configured with specific executable instructions, receiving first descriptive information associated with an electronic version of a particular media content; searching a data store, based at least in part on the first descriptive information, to identify second descriptive information associated with a physical media product, wherein the physical media product includes the particular media content, and wherein the second descriptive information includes information about the particular media content that is not included in the first descriptive information; storing a data record relating the electronic version of the particular media content to the second descriptive information associated with the physical media product and identified by searching the data store; receiving a request for information related to the electronic version of the particular media content; and in response to the request, accessing the data record relating the electronic version of the particular media content to the second descriptive information associated with the physical media product; and generating instructions for presenting a user interface that includes at least a portion of the first descriptive information and at least a portion of the second descriptive information. | 1. A computer-implemented method comprising: as implemented by one or more computing devices configured with specific executable instructions, receiving first descriptive information associated with an electronic version of a particular media content; searching a data store, based at least in part on the first descriptive information, to identify second descriptive information associated with a physical media product, wherein the physical media product includes the particular media content, and wherein the second descriptive information includes information about the particular media content that is not included in the first descriptive information; storing a data record relating the electronic version of the particular media content to the second descriptive information associated with the physical media product and identified by searching the data store; receiving a request for information related to the electronic version of the particular media content; and in response to the request, accessing the data record relating the electronic version of the particular media content to the second descriptive information associated with the physical media product; and generating instructions for presenting a user interface that includes at least a portion of the first descriptive information and at least a portion of the second descriptive information. 3. The computer-implemented method of claim 1 , wherein the particular media content includes a recorded musical performance, wherein the first descriptive information includes information descriptive of the recorded musical performance, and wherein the second descriptive information includes information descriptive of a compilation including the recorded musical performance. | 0.622146 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.