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1. A method for accessing information in a data file stored in a memory in an electronic device, comprising the steps of: determining a file format for the data file; detecting an attempt to execute the data file in the electronic device; establishing that the electronic device holds no meta descriptor language file adapted to the file format; downloading the meta descriptor language file to a file memory in the electronic device from storage means through a data communication network; accessing the meta descriptor language file adapted to the file format of the data file; parsing the data file by means of a generic parser using said meta descriptor language file; extracting meta data from the data file; presenting information related to the data file from the extracted meta data. | 1. A method for accessing information in a data file stored in a memory in an electronic device, comprising the steps of: determining a file format for the data file; detecting an attempt to execute the data file in the electronic device; establishing that the electronic device holds no meta descriptor language file adapted to the file format; downloading the meta descriptor language file to a file memory in the electronic device from storage means through a data communication network; accessing the meta descriptor language file adapted to the file format of the data file; parsing the data file by means of a generic parser using said meta descriptor language file; extracting meta data from the data file; presenting information related to the data file from the extracted meta data. 3. The method as recited in claim 1 , prior to the step of accessing the meta descriptor language file, comprising the steps of: detecting an attempt to execute the data file in the electronic device; establishing that the electronic device holds no accessible application for handling the determined file format. | 0.536261 |
16. A method comprising: receiving, by a server comprising a processor, a voice message from a computing device; identifying, by the server, media content related to the voice message; determining, by the server, a context of the voice message, wherein the determining is based on the media content; recognizing, by the server, a word in the voice message, wherein the recognizing is based on the context of the voice message; generating text representing the voice message; obtaining, by the server, additional content, wherein the obtaining is based on the media content and on the context of the voice message; generating, by the server, an enhanced message comprising the text and comprising the additional content; and providing, by the server, a communication device with access to the enhanced message, wherein the communication device and the computing device are associated with each other via a social network. | 16. A method comprising: receiving, by a server comprising a processor, a voice message from a computing device; identifying, by the server, media content related to the voice message; determining, by the server, a context of the voice message, wherein the determining is based on the media content; recognizing, by the server, a word in the voice message, wherein the recognizing is based on the context of the voice message; generating text representing the voice message; obtaining, by the server, additional content, wherein the obtaining is based on the media content and on the context of the voice message; generating, by the server, an enhanced message comprising the text and comprising the additional content; and providing, by the server, a communication device with access to the enhanced message, wherein the communication device and the computing device are associated with each other via a social network. 20. The method of claim 16 , wherein the social network comprises a website managed by a social network server, and wherein the communication device is remote from the computing device. | 0.657054 |
1. A method in an apparatus comprising: receiving a media clip; receiving sensor data captured at least partly in connection with a capture of the media clip; deriving at least one context using a context model based at least partly on the sensor data; causing an indication on the context to be provided to a user by receiving a search query having at least one search criterion that is relevant to the context, deriving a similarity between the context and the at least one search criterion and causing at least a part of the media clip to be presented with an indication on the context based on the derived similarity as a response to the search query; receiving feedback on the relevance of the indication on the context of the presented media clip to the search query from the user; and adapting the context model based on the feedback. | 1. A method in an apparatus comprising: receiving a media clip; receiving sensor data captured at least partly in connection with a capture of the media clip; deriving at least one context using a context model based at least partly on the sensor data; causing an indication on the context to be provided to a user by receiving a search query having at least one search criterion that is relevant to the context, deriving a similarity between the context and the at least one search criterion and causing at least a part of the media clip to be presented with an indication on the context based on the derived similarity as a response to the search query; receiving feedback on the relevance of the indication on the context of the presented media clip to the search query from the user; and adapting the context model based on the feedback. 5. The method according to claim 1 , wherein said causing an indication on the context to be provided to the user comprises: associating a set of keywords with the context; and presenting the set of keywords to the user. | 0.634786 |
1. A method for use with at least one keyword retrieved from a first set of documents, wherein the keyword corresponds to a predefined subject matter, the method comprising: constructing snippets from textual material in said first set of documents stored on a computer to produce constructed snippets, each of said constructed snippets including at least one non-key word appearing within a specified text distance of said at least one keyword; defining, by a computer processor, a plurality of categories wherein each of said constructed snippets is assigned to one of said plurality of categories, only if said assigned snippet is not already assigned to another of said plurality of said categories, each of said plurality of categories being designated for receiving similar constructed snippets; creating a respective mathematical model for each of said plurality of categories; analyzing a second set of documents to determine an assignment for each document in said second set of documents to a selected one of said plurality of categories, said assignment based on matching each of said documents in said second set of documents to said mathematical model for the selected one of said plurality of categories; assigning a numeric vector to each document of the first and second sets of documents, wherein the numeric vector represents occurrences of one of the constructed snippets within the respective document; creating a partition taxonomy that includes less than all of the plurality of categories, wherein the partition taxonomy creation is based on a clustered configuration of the first and second sets of documents; editing, using a computer processor, less than all of the plurality of categories in the partition taxonomy using domain expertise to produce edited categories in an edited partition taxonomy, such that each document of the first and second sets of documents is assigned to a corresponding one of the less than all of the plurality of categories; creating a classification taxonomy based on the edited partition taxonomy, based on a number of documents in each of the edited categories, based on percentage similarity of words between documents in one of the edited categories, and based on distances between category centroids of the edited categories, wherein a category centroid for an edited category is an average of values of the numeric vectors for the documents in the category; identifying at least one white space in said classification taxonomy, said at least one white space including one or more of the edited categories that contain fewer than a specified number of documents. | 1. A method for use with at least one keyword retrieved from a first set of documents, wherein the keyword corresponds to a predefined subject matter, the method comprising: constructing snippets from textual material in said first set of documents stored on a computer to produce constructed snippets, each of said constructed snippets including at least one non-key word appearing within a specified text distance of said at least one keyword; defining, by a computer processor, a plurality of categories wherein each of said constructed snippets is assigned to one of said plurality of categories, only if said assigned snippet is not already assigned to another of said plurality of said categories, each of said plurality of categories being designated for receiving similar constructed snippets; creating a respective mathematical model for each of said plurality of categories; analyzing a second set of documents to determine an assignment for each document in said second set of documents to a selected one of said plurality of categories, said assignment based on matching each of said documents in said second set of documents to said mathematical model for the selected one of said plurality of categories; assigning a numeric vector to each document of the first and second sets of documents, wherein the numeric vector represents occurrences of one of the constructed snippets within the respective document; creating a partition taxonomy that includes less than all of the plurality of categories, wherein the partition taxonomy creation is based on a clustered configuration of the first and second sets of documents; editing, using a computer processor, less than all of the plurality of categories in the partition taxonomy using domain expertise to produce edited categories in an edited partition taxonomy, such that each document of the first and second sets of documents is assigned to a corresponding one of the less than all of the plurality of categories; creating a classification taxonomy based on the edited partition taxonomy, based on a number of documents in each of the edited categories, based on percentage similarity of words between documents in one of the edited categories, and based on distances between category centroids of the edited categories, wherein a category centroid for an edited category is an average of values of the numeric vectors for the documents in the category; identifying at least one white space in said classification taxonomy, said at least one white space including one or more of the edited categories that contain fewer than a specified number of documents. 4. The method of claim 1 wherein said analyzing step is performed using information from said predefined subject matter. | 0.606679 |
14. The organization system as claimed in claim 12 wherein the computing device is located at a remote location from the organization server. | 14. The organization system as claimed in claim 12 wherein the computing device is located at a remote location from the organization server. 15. The organization system as claimed in claim 14 wherein the communication mechanism is configured to communicate the encyclopedia-like entry via the internet, and wherein the communication mechanism is configured to receive one or more keywords designated by a user via the internet. | 0.933007 |
1. A method for processing natural language comprising: at an electronic device: receiving a first text phrase; determining whether editing the first text phrase to match a second text phrase requires one or more of: inserting a first word into the first text phrase, wherein the second text phrase includes the first word; deleting a second word from the first text phrase; wherein the first text phrase includes the second word; and substituting a third word of the first text phrase with a fourth word, wherein the second text phrase includes the fourth word; in response to determining that editing the first text phrase to match the second text phrase requires one or more of inserting the first word into the first text phrase, deleting the second word from the first text phrase, and substituting the third word of the first text phrase with the fourth word, determining one or more of: an insertion cost associated with inserting the first word into the first text phrase; a deletion cost associated with deleting the second word from the first text phrase; and a substitution cost associated with substituting the third word of the first text phrase with the fourth word; determining, based on the one or more of the insertion cost, the deletion cost, and the substitution cost, a semantic edit distance between the first text phrase and the second text phrase in a semantic space, wherein a degree of semantic similarity between the first text phrase and the second text phrase is based on the semantic edit distance; determining, based on the degree of semantic similarity between the first text phrase and the second text phrase, a first intent associated with the first text phrase; and performing, based on the first intent, a task associated with the first text phrase. | 1. A method for processing natural language comprising: at an electronic device: receiving a first text phrase; determining whether editing the first text phrase to match a second text phrase requires one or more of: inserting a first word into the first text phrase, wherein the second text phrase includes the first word; deleting a second word from the first text phrase; wherein the first text phrase includes the second word; and substituting a third word of the first text phrase with a fourth word, wherein the second text phrase includes the fourth word; in response to determining that editing the first text phrase to match the second text phrase requires one or more of inserting the first word into the first text phrase, deleting the second word from the first text phrase, and substituting the third word of the first text phrase with the fourth word, determining one or more of: an insertion cost associated with inserting the first word into the first text phrase; a deletion cost associated with deleting the second word from the first text phrase; and a substitution cost associated with substituting the third word of the first text phrase with the fourth word; determining, based on the one or more of the insertion cost, the deletion cost, and the substitution cost, a semantic edit distance between the first text phrase and the second text phrase in a semantic space, wherein a degree of semantic similarity between the first text phrase and the second text phrase is based on the semantic edit distance; determining, based on the degree of semantic similarity between the first text phrase and the second text phrase, a first intent associated with the first text phrase; and performing, based on the first intent, a task associated with the first text phrase. 15. The method according to claim 1 , wherein the degree of semantic similarity is based on whether the first text phrase includes a fifth word that the second text phrase does not include and whether a predetermined list of keywords includes the fifth word. | 0.590196 |
15. A system comprising: a processor; and a memory storing instructions that, when executed, cause the system to: determine one or more topics associated with a message based at least in part on message data included in the message; determine knowledge data describing the one or more topics associated with the message; determine social activity data describing one or more user activities associated with a group of one or more social users based at least in part on the knowledge data, the one or more user activities describing the one or more topics; generate a selectable tag based at least in part on the social activity data describing the one or more user activities, a selection of the selectable tag causing a display of the social activity data associated with the message; and generate graphical user interface data for displaying the social activity data associated with the message in response to the selectable tag being selected. | 15. A system comprising: a processor; and a memory storing instructions that, when executed, cause the system to: determine one or more topics associated with a message based at least in part on message data included in the message; determine knowledge data describing the one or more topics associated with the message; determine social activity data describing one or more user activities associated with a group of one or more social users based at least in part on the knowledge data, the one or more user activities describing the one or more topics; generate a selectable tag based at least in part on the social activity data describing the one or more user activities, a selection of the selectable tag causing a display of the social activity data associated with the message; and generate graphical user interface data for displaying the social activity data associated with the message in response to the selectable tag being selected. 16. The system of claim 15 , wherein the instructions, when executed, cause the system to also rank the social activity data based at least in part on one or more popularities associated with the social activity data. | 0.791188 |
1. A method for providing information to a plurality of users based on the relevancy of the information to the users, the method comprising steps of: (A) receiving an incoming message; (B) generating similarity scores indicating similarities of the incoming message to features of a plurality of messages previously received, wherein each similarity score is generated based on a comparison of the incoming message to one of the plurality of messages and indicates a degree of similarity between the incoming message and the one of the plurality of messages; (C) generating relevancy scores for the plurality of users, the relevancy scores indicating relevancies of the incoming message to the plurality of users based on the similarity scores and a plurality of user profiles including information descriptive of the plurality of users' preferences for the features of the plurality of users; and (D) delivering, to at least some of the plurality of users, message information derived from the incoming message, the relevancy scores, and the plurality of user profiles. | 1. A method for providing information to a plurality of users based on the relevancy of the information to the users, the method comprising steps of: (A) receiving an incoming message; (B) generating similarity scores indicating similarities of the incoming message to features of a plurality of messages previously received, wherein each similarity score is generated based on a comparison of the incoming message to one of the plurality of messages and indicates a degree of similarity between the incoming message and the one of the plurality of messages; (C) generating relevancy scores for the plurality of users, the relevancy scores indicating relevancies of the incoming message to the plurality of users based on the similarity scores and a plurality of user profiles including information descriptive of the plurality of users' preferences for the features of the plurality of users; and (D) delivering, to at least some of the plurality of users, message information derived from the incoming message, the relevancy scores, and the plurality of user profiles. 9. The method of claim 1 , wherein the plurality of user profiles includes a minimum number of users to whom the message information is to be delivered, and wherein the step (D) comprises a step of: (D)(1) delivering the message information to no fewer than the minimum number of users. | 0.534019 |
3. The method of claim 2 , in which the matches are determined based on at least one of: literal, distributional, statistical, and co-occurrence similarity. | 3. The method of claim 2 , in which the matches are determined based on at least one of: literal, distributional, statistical, and co-occurrence similarity. 4. The method of claim 3 , in which the conceptual similarity is based on at least one of: a lexicon; an ontology; statistics and a machine-readable information source. | 0.919489 |
1. A computer-executable method for tracing information leaks, comprising: obtaining, by a computing device, a disseminated document to analyze; determining, from a collection of original documents, an original document that is most similar to the disseminated document; comparing the disseminated document to the most similar original document to determine differences between the disseminated document and the most similar original document; querying a database containing changes to documents, using the determined differences, to determine a most similar changed document; determining a distance value by comparing changes from the most similar changed document with the determined differences from the disseminated document; and responsive to determining that the distance value is less than a threshold value, determining a user identifier for a user associated with the most similar changed document. | 1. A computer-executable method for tracing information leaks, comprising: obtaining, by a computing device, a disseminated document to analyze; determining, from a collection of original documents, an original document that is most similar to the disseminated document; comparing the disseminated document to the most similar original document to determine differences between the disseminated document and the most similar original document; querying a database containing changes to documents, using the determined differences, to determine a most similar changed document; determining a distance value by comparing changes from the most similar changed document with the determined differences from the disseminated document; and responsive to determining that the distance value is less than a threshold value, determining a user identifier for a user associated with the most similar changed document. 2. The method of claim 1 , further comprising: searching among change records for changes that are most similar to a determined difference between a second most similar original document and a second disseminated document; and determining a second user identifier associated with the changes that are most similar to the determined difference. | 0.643357 |
1. A method for recalling previously generated user data in a computer which includes a memory, the method comprising: generating user data in response to signals generated by a user; recording the user data in the memory; associating with the user data a description of the user data wherein the description comprises one or more instances of each of one or more elements of a collection of two or more elements; forming two or more categories corresponding respectively to two or more of the elements; and associating the user data with a selected one of the categories, which corresponds to a selected one of the elements, wherein one or more instances of the selected element are part of the description of the user data; and recalling the user data from memory, the step of recalling comprising: receiving signals which are generated by a first gesture of the user and which specify the selected category; and receiving data selection signals which are generated by a second gesture of the user and which identify the user data within the selected category. | 1. A method for recalling previously generated user data in a computer which includes a memory, the method comprising: generating user data in response to signals generated by a user; recording the user data in the memory; associating with the user data a description of the user data wherein the description comprises one or more instances of each of one or more elements of a collection of two or more elements; forming two or more categories corresponding respectively to two or more of the elements; and associating the user data with a selected one of the categories, which corresponds to a selected one of the elements, wherein one or more instances of the selected element are part of the description of the user data; and recalling the user data from memory, the step of recalling comprising: receiving signals which are generated by a first gesture of the user and which specify the selected category; and receiving data selection signals which are generated by a second gesture of the user and which identify the user data within the selected category. 2. The method of claim 1 wherein the elements are symbols of the user data. | 0.954436 |
2. A system as set forth in claim 1 , wherein said requirement solver comprises a partial evaluator, a model-finder and a SAT solver. | 2. A system as set forth in claim 1 , wherein said requirement solver comprises a partial evaluator, a model-finder and a SAT solver. 5. A system as set forth in claim 2 , wherein said SAT solver is a MiniSat Prover. | 0.937967 |
15. An apparatus for extracting semantic information from unstructured text associated with a plurality of content items, each content item having associated metadata, the apparatus comprising a processor and a memory device storing executable instructions thereon that when executed causes the processor to perform a method comprising: selecting an ordered set of scale values for a plurality of scales; determining for each scale value at least one subset of metadata related to a subset of the scale value; determining for each of the scales and associated subsets a statistic on occurrences of one or more content items from the subset of metadata, the statistic comprising a number of instances of the one or more content items in a respective scale and subset; aggregating the statistics for each scale and associated subsets and determining therefrom a semantic level for each scale and associated subsets; determining which of the plurality of scales correspond to the semantics of the one or more content items on the basis of the semantic level; identifying one or more clusters of scales having a semantic level that exceeds a threshold value of occurrences; and extracting semantic information from the metadata associated with the one or more content items of one or more identified cluster of scales. | 15. An apparatus for extracting semantic information from unstructured text associated with a plurality of content items, each content item having associated metadata, the apparatus comprising a processor and a memory device storing executable instructions thereon that when executed causes the processor to perform a method comprising: selecting an ordered set of scale values for a plurality of scales; determining for each scale value at least one subset of metadata related to a subset of the scale value; determining for each of the scales and associated subsets a statistic on occurrences of one or more content items from the subset of metadata, the statistic comprising a number of instances of the one or more content items in a respective scale and subset; aggregating the statistics for each scale and associated subsets and determining therefrom a semantic level for each scale and associated subsets; determining which of the plurality of scales correspond to the semantics of the one or more content items on the basis of the semantic level; identifying one or more clusters of scales having a semantic level that exceeds a threshold value of occurrences; and extracting semantic information from the metadata associated with the one or more content items of one or more identified cluster of scales. 16. The apparatus of claim 15 , wherein the text associated with the content items comprises tag data input by one or more users. | 0.550102 |
2. The method of claim 1 , further comprising: repeating the step of determining, for each document in the collection at the value of the parameter, and the step of increasing the value of the parameter until the first class has split into two child classes. | 2. The method of claim 1 , further comprising: repeating the step of determining, for each document in the collection at the value of the parameter, and the step of increasing the value of the parameter until the first class has split into two child classes. 3. The method of claim 2 , further comprising: performing the clustering process for each child class until each of the respective child class splits into two new child classes reflecting clusters descendant from the respective child class. | 0.919941 |
7. The method of claim 1 , further comprising: identifying lesser order n-grams, the lesser order n-grams being derived from the first n-gram; and identifying a respective scaled probability of each of the lesser order n-grams identifying a word, the scaled probability for a particular lesser order n-gram composed of a particular number of atomic units identifying a word being determined by adjusting an initial probability of the lesser order n-gram identifying a word based at least in part on the particular number of atomic units. | 7. The method of claim 1 , further comprising: identifying lesser order n-grams, the lesser order n-grams being derived from the first n-gram; and identifying a respective scaled probability of each of the lesser order n-grams identifying a word, the scaled probability for a particular lesser order n-gram composed of a particular number of atomic units identifying a word being determined by adjusting an initial probability of the lesser order n-gram identifying a word based at least in part on the particular number of atomic units. 8. The method of claim 7 , wherein segmenting the plurality of tokens into one or more words comprises: when a product of the respective scaled probabilities of the lesser order n-grams derived from the first n-gram identifying a word exceeds the scaled probability of the first n-gram identifying a word, segmenting the first n-gram such that each of the lesser order n-grams identifies a respective word. | 0.683599 |
1. A system for problem solving, comprising: a brain agent configured to receive input data representing an input query from a peripheral device, the brain agent configured as processor-readable software code stored on a processor readable medium, the brain agent being configured to identify a predetermined data format associated with the input data and invokes a decomposition process associated with that predetermined data format, the decomposition step including outputting the data to a first intelligent agent configured as processor-readable software code stored on a computer readable medium, and the brain agent being configured to receive the input data in a textual form and conceptually parse the input data in textual form and a plurality of sub-queries; and a plurality of second intelligent agents, each configured to receive at least one of the plurality of sub-queries and the corresponding conceptually parsed text and provide responsive output to the brain agent based on the conceptually parsed text; the brain agent being further configured to generate an answer to the input query based upon at least the responsive output of the plurality of second intelligent agents. | 1. A system for problem solving, comprising: a brain agent configured to receive input data representing an input query from a peripheral device, the brain agent configured as processor-readable software code stored on a processor readable medium, the brain agent being configured to identify a predetermined data format associated with the input data and invokes a decomposition process associated with that predetermined data format, the decomposition step including outputting the data to a first intelligent agent configured as processor-readable software code stored on a computer readable medium, and the brain agent being configured to receive the input data in a textual form and conceptually parse the input data in textual form and a plurality of sub-queries; and a plurality of second intelligent agents, each configured to receive at least one of the plurality of sub-queries and the corresponding conceptually parsed text and provide responsive output to the brain agent based on the conceptually parsed text; the brain agent being further configured to generate an answer to the input query based upon at least the responsive output of the plurality of second intelligent agents. 15. The system as recited in claim 1 , further comprising: a sound agent configured as processor-readable software code stored on a processor readable medium, and wherein said brain agent is further adapted to selectively interact with said sound agent to interpret the input query and to provide output in response to the input query. | 0.558019 |
15. A non-transitory computer-readable storage medium having instructions stored thereon, which, when executed by one or more data processors, cause the one or more processors to perform operations comprising: receiving during a search session a first search query comprising a first set of search terms, each search term in the first set having a respective first ordinal position, each first ordinal position defining a position of a respective search term in the first set relative to other search terms in the first set; receiving during the search session and after receipt of the first search query a subsequent search query comprising a second set of search terms, each term in the second set having a respective second ordinal position, each second ordinal position defining a position of a respective search term in the second set relative to other search terms in the second set; determining that the second set of search terms in the subsequent search query includes differing search terms, each of the differing search terms being a search term that is not included in the first set of search terms in the first search query; identifying additional search terms from the second set of search terms in the subsequent search query, each additional search term being a differing term and having a second ordinal position in the second set that is greater than any first ordinal position of any search term in the first set of search terms in the first search query; and performing an n-gram analysis on the additional search terms separately from an n-gram analysis on common terms between the first and subsequent search queries, each common term being a search term that is included in both the first set of search terms in the first search query and the second set of search terms in the subsequent search query and has a first ordinal position in the first set that matches that of a second ordinal position in the second set. | 15. A non-transitory computer-readable storage medium having instructions stored thereon, which, when executed by one or more data processors, cause the one or more processors to perform operations comprising: receiving during a search session a first search query comprising a first set of search terms, each search term in the first set having a respective first ordinal position, each first ordinal position defining a position of a respective search term in the first set relative to other search terms in the first set; receiving during the search session and after receipt of the first search query a subsequent search query comprising a second set of search terms, each term in the second set having a respective second ordinal position, each second ordinal position defining a position of a respective search term in the second set relative to other search terms in the second set; determining that the second set of search terms in the subsequent search query includes differing search terms, each of the differing search terms being a search term that is not included in the first set of search terms in the first search query; identifying additional search terms from the second set of search terms in the subsequent search query, each additional search term being a differing term and having a second ordinal position in the second set that is greater than any first ordinal position of any search term in the first set of search terms in the first search query; and performing an n-gram analysis on the additional search terms separately from an n-gram analysis on common terms between the first and subsequent search queries, each common term being a search term that is included in both the first set of search terms in the first search query and the second set of search terms in the subsequent search query and has a first ordinal position in the first set that matches that of a second ordinal position in the second set. 20. The non-transitory computer-readable storage medium of claim 15 , wherein performing an n-gram analysis on the additional search terms comprises: determining that the additional search terms match a known n-gram in an n-gram data store; and identifying the additional search terms as an n-gram. | 0.764738 |
1. A method comprising: accessing, using one or more processors associated with one or more computing devices, a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, wherein each edge between two nodes represents a single degree of separation between the two nodes, the plurality of nodes comprising: a first user node corresponding to a first user associated with an online social network; one or more second user nodes corresponding to one or more second users associated with the online social network, respectively, wherein each of the second user nodes is within a threshold degree of separation from the first user node; and one or more concept nodes corresponding to one or more concepts, respectively; identifying, using the one or more processors, a first set of concept nodes that are connected to one or more of the second user nodes by one or more edges, respectively, wherein each of the concept nodes in the first set of concept nodes corresponds to a multimedia object that is associated with an application accessible by users associated with the online social network; selecting, using the one or more processors, a second set of concept nodes from the first set of concept nodes based at least in part on a number of edges connected to the concept nodes, wherein for each concept node in the second set of concept nodes, each edge connected to the concept node indicates that one of the second users accessed, created, or managed the multimedia object corresponding to the content node with the application; and generating, using the one or more processors, an advertisement of the application for display to the first user, the advertisement comprising a reference to the application and further comprising information representing one or more multimedia objects corresponding to one or more concept nodes, respectively, in the second set of concept nodes. | 1. A method comprising: accessing, using one or more processors associated with one or more computing devices, a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, wherein each edge between two nodes represents a single degree of separation between the two nodes, the plurality of nodes comprising: a first user node corresponding to a first user associated with an online social network; one or more second user nodes corresponding to one or more second users associated with the online social network, respectively, wherein each of the second user nodes is within a threshold degree of separation from the first user node; and one or more concept nodes corresponding to one or more concepts, respectively; identifying, using the one or more processors, a first set of concept nodes that are connected to one or more of the second user nodes by one or more edges, respectively, wherein each of the concept nodes in the first set of concept nodes corresponds to a multimedia object that is associated with an application accessible by users associated with the online social network; selecting, using the one or more processors, a second set of concept nodes from the first set of concept nodes based at least in part on a number of edges connected to the concept nodes, wherein for each concept node in the second set of concept nodes, each edge connected to the concept node indicates that one of the second users accessed, created, or managed the multimedia object corresponding to the content node with the application; and generating, using the one or more processors, an advertisement of the application for display to the first user, the advertisement comprising a reference to the application and further comprising information representing one or more multimedia objects corresponding to one or more concept nodes, respectively, in the second set of concept nodes. 15. The method of claim 1 , wherein selecting the second set of concept nodes from the first set of concept nodes based on edges connected to the concept node comprises: identifying, for each concept node of the first set of concept nodes, a first set of edges between the concept node and the one or more second user nodes; determining, for each concept node of the first set of concept nodes, a value for the concept node based on information associated with the first set of edges; and selecting one or more of the concept nodes of the first set of concept nodes based on the values for the concept nodes. | 0.5 |
7. A system for controlling spam, comprising: memory; one or more processors; and one or more modules stored in the memory and configured for execution by the one or more processors, the modules comprising: instructions to determine, for a set of documents created by an creator, a metric whose value indicates an extent to which the set of documents includes spam, wherein the value is on a predefined scale and wherein the instructions to determine the metric comprise include instructions to determine at least one spam score for the set of documents; instructions to determine a challenge rate associated with the creator based on the determined metric whose value indicates the extent to which the set of documents includes spam, wherein the challenge rate is less than one hundred percent and wherein the instructions to determine the challenge rate comprise instructions to determine the challenge rate associated with the creator based on the at least one spam score; and instructions to present to the creator a challenge in accordance with the challenge rate whenever the creator attempts to create a document. | 7. A system for controlling spam, comprising: memory; one or more processors; and one or more modules stored in the memory and configured for execution by the one or more processors, the modules comprising: instructions to determine, for a set of documents created by an creator, a metric whose value indicates an extent to which the set of documents includes spam, wherein the value is on a predefined scale and wherein the instructions to determine the metric comprise include instructions to determine at least one spam score for the set of documents; instructions to determine a challenge rate associated with the creator based on the determined metric whose value indicates the extent to which the set of documents includes spam, wherein the challenge rate is less than one hundred percent and wherein the instructions to determine the challenge rate comprise instructions to determine the challenge rate associated with the creator based on the at least one spam score; and instructions to present to the creator a challenge in accordance with the challenge rate whenever the creator attempts to create a document. 8. The system of claim 7 , wherein the challenge comprises a CAPTCHA. | 0.628544 |
1. A handheld computing apparatus, comprising: a display to present human-readable information; a user input facility; and a digital data processing apparatus coupled to the display and the user input facility and programmed to provide the following: at least one application program module programmed to perform designated application program tasks and currently configured such that output is presented in a current operating language, the application programs module further programmed to perform operations comprising: responsive to events requiring the application program module to present given data, before any presenting of said given data the application program determining any of: (1) if a type of said given data matches any entry of a predetermined type listing, (2) if an operation being performed by said application program upon said given data matches any entry of a predetermined operation listing; where entries of the type listing include various data types all having the following in common: different languages would require presentation of data of said data types differently solely due to said type of data and independent of any translation; where the entries of the operation listing include various operations having the following in common: different languages would require presentation of data undergoing any of said operations differently solely due to a nature of said operation and independent of any translation; if said determining operation answers NO, then the application program module presenting the data; if said determining operation answers YES, then the application program module refraining from presenting said given data and instead performing operations including invoking a rules engine as to said given data and identifying the current operating language to the rules engine and thereafter instead of presenting the given data presenting manipulated data returned by the rules engine; a rules module prescribing rules to manipulate any of data matching said type listing or said operation listing for presentation appropriate to said current operating language, said manipulation being independent of translation; a rules engine responsive to being invoked by any of the application programs modules to perform operations comprising identifying in said rules module each rule applicable to the given data and the current operating language, applying the identified rule to manipulate the given data for presentation appropriate to the current operating language, and returning the manipulated data to the application program module that invoked the rules engine. | 1. A handheld computing apparatus, comprising: a display to present human-readable information; a user input facility; and a digital data processing apparatus coupled to the display and the user input facility and programmed to provide the following: at least one application program module programmed to perform designated application program tasks and currently configured such that output is presented in a current operating language, the application programs module further programmed to perform operations comprising: responsive to events requiring the application program module to present given data, before any presenting of said given data the application program determining any of: (1) if a type of said given data matches any entry of a predetermined type listing, (2) if an operation being performed by said application program upon said given data matches any entry of a predetermined operation listing; where entries of the type listing include various data types all having the following in common: different languages would require presentation of data of said data types differently solely due to said type of data and independent of any translation; where the entries of the operation listing include various operations having the following in common: different languages would require presentation of data undergoing any of said operations differently solely due to a nature of said operation and independent of any translation; if said determining operation answers NO, then the application program module presenting the data; if said determining operation answers YES, then the application program module refraining from presenting said given data and instead performing operations including invoking a rules engine as to said given data and identifying the current operating language to the rules engine and thereafter instead of presenting the given data presenting manipulated data returned by the rules engine; a rules module prescribing rules to manipulate any of data matching said type listing or said operation listing for presentation appropriate to said current operating language, said manipulation being independent of translation; a rules engine responsive to being invoked by any of the application programs modules to perform operations comprising identifying in said rules module each rule applicable to the given data and the current operating language, applying the identified rule to manipulate the given data for presentation appropriate to the current operating language, and returning the manipulated data to the application program module that invoked the rules engine. 12. The apparatus of claim 1 , where said rules include rules to sort text as appropriate to the current operating language. | 0.592518 |
1. A reconfigurable multimedia collaboration system, comprising: a SIP engine implemented in hardware only that executes functions defined by Session Initiation Protocol (SIP); a XML engine implemented in hardware only that executes functions defined by Extensible Markup Language (XML); and an interface configured to receive an incoming data packet into a set of registers used to communicate with a software component and coordinates functions executed by the SIP engine and the XML engine, wherein the interface invokes the SIP engine to parse an incoming data packet, the SIP engine operates to parse the incoming data packet to determine a packet type for the incoming data packet in accordance with SIP and sends a response to the interface, such that the response depends on the packet type determined for the incoming data packet, and wherein the interface invokes the XML engine in response to a determination that the incoming data packet is formatted in accordance with Presence Information Data Format. | 1. A reconfigurable multimedia collaboration system, comprising: a SIP engine implemented in hardware only that executes functions defined by Session Initiation Protocol (SIP); a XML engine implemented in hardware only that executes functions defined by Extensible Markup Language (XML); and an interface configured to receive an incoming data packet into a set of registers used to communicate with a software component and coordinates functions executed by the SIP engine and the XML engine, wherein the interface invokes the SIP engine to parse an incoming data packet, the SIP engine operates to parse the incoming data packet to determine a packet type for the incoming data packet in accordance with SIP and sends a response to the interface, such that the response depends on the packet type determined for the incoming data packet, and wherein the interface invokes the XML engine in response to a determination that the incoming data packet is formatted in accordance with Presence Information Data Format. 9. The reconfigurable multimedia collaboration system of claim 1 is implemented in either a field programmable gate array or an application specific integrated circuit. | 0.544974 |
1. In an apparatus for processing signals in the form of digital words, comprising (a) filtering means having an input terminal for receiving a sequence of input digital words, and an output terminal for supplying a sequence of filtered words; (b) selection means having input and output terminals, said selection means input terminal being connected with the output terminal of said filtering means, said selection means being operable to omit predetermined words from the sequence thereof and for supplying a reduced number of digital words to said selection means output terminal; and (c) output means connected with said selection means output terminal for acting upon the reduced number of words; the improvement which comprises (d) monitoring means connected with the input terminal of said filtering means for determining if the input digital words have a characteristic similar to the filtered words; and (e) bypass means operable by said monitoring means when said monitoring means determines that an input digital word has a characteristic similar to a filtered word for causing the input digital word to bypass said filter means and thereby remain in the non-altered condition. | 1. In an apparatus for processing signals in the form of digital words, comprising (a) filtering means having an input terminal for receiving a sequence of input digital words, and an output terminal for supplying a sequence of filtered words; (b) selection means having input and output terminals, said selection means input terminal being connected with the output terminal of said filtering means, said selection means being operable to omit predetermined words from the sequence thereof and for supplying a reduced number of digital words to said selection means output terminal; and (c) output means connected with said selection means output terminal for acting upon the reduced number of words; the improvement which comprises (d) monitoring means connected with the input terminal of said filtering means for determining if the input digital words have a characteristic similar to the filtered words; and (e) bypass means operable by said monitoring means when said monitoring means determines that an input digital word has a characteristic similar to a filtered word for causing the input digital word to bypass said filter means and thereby remain in the non-altered condition. 4. Apparatus as defined in claim 1, wherein said filtering means has a characteristic such that there is only one non-zero multiplying coefficient in the set of coefficients spatially separated by a number of words equal to the number of initial words per unit time divided by the reduced number of words per unit time. | 0.527603 |
1. A system for providing coded reference electronically stored information items as a suggestion for classifying uncoded electronically stored information, comprising: a database to store a coded reference set comprising electronically stored information items each associated with a classification code; a cluster module to designate clusters of uncoded electronically stored information items; a similarity module to compare one or more of the uncoded electronically stored information items from at least one cluster of the uncoded electronically stored information items to the coded reference set of the coded electronically stored information items and to identify at least one of the coded electronically stored information items in the coded reference set that is similar to the one or more uncoded electronically stored information items; an injection module to inject the similar coded electronically stored information items into the at least one cluster of the uncoded electronically stored information items; and a display to visually depict relationships between the uncoded electronically stored information items and the similar coded electronically stored information items in the at least one cluster as suggestions for classifying the uncoded electronically stored information items, wherein each of the uncoded electronically stored information items are displayed via a first symbol and each of the similar coded electronically stored information items are displayed via a second symbol. | 1. A system for providing coded reference electronically stored information items as a suggestion for classifying uncoded electronically stored information, comprising: a database to store a coded reference set comprising electronically stored information items each associated with a classification code; a cluster module to designate clusters of uncoded electronically stored information items; a similarity module to compare one or more of the uncoded electronically stored information items from at least one cluster of the uncoded electronically stored information items to the coded reference set of the coded electronically stored information items and to identify at least one of the coded electronically stored information items in the coded reference set that is similar to the one or more uncoded electronically stored information items; an injection module to inject the similar coded electronically stored information items into the at least one cluster of the uncoded electronically stored information items; and a display to visually depict relationships between the uncoded electronically stored information items and the similar coded electronically stored information items in the at least one cluster as suggestions for classifying the uncoded electronically stored information items, wherein each of the uncoded electronically stored information items are displayed via a first symbol and each of the similar coded electronically stored information items are displayed via a second symbol. 2. The system according to claim 1 , wherein the comparison of the one or more uncoded electronically stored information items and the coded reference set of the coded electronically stored information items comprises identifying a cluster center for the at least one cluster of the uncoded electronically stored information items based on the one or more uncoded electronically stored information items and comparing the cluster center to the reference set of the coded electronically stored information items. | 0.539112 |
9. A system comprising: a server configured to receive a post from a user; a real time search engine comprising an indexing module configured to determine a post identifier of the post and a term identifier of a term in the post and an aggregator module configured to determine a user identifier of the user, a forward index configured to store the received post based upon the post identifier; and a user-term index comprising a plurality of partitions, wherein the aggregator module is further configured to select a partition of the user-term index that is associated with the user identifier from among the plurality of partitions of the user-term index and the indexing module is further configured to index the term of the post and the post identifier based upon the user identifier and the term identifier. | 9. A system comprising: a server configured to receive a post from a user; a real time search engine comprising an indexing module configured to determine a post identifier of the post and a term identifier of a term in the post and an aggregator module configured to determine a user identifier of the user, a forward index configured to store the received post based upon the post identifier; and a user-term index comprising a plurality of partitions, wherein the aggregator module is further configured to select a partition of the user-term index that is associated with the user identifier from among the plurality of partitions of the user-term index and the indexing module is further configured to index the term of the post and the post identifier based upon the user identifier and the term identifier. 12. The system of claim 9 , wherein the selected partition of the user-term index comprises a plurality of database shards organized by time, and the indexing module is further configured to: select a record in a most recent database shard of the plurality of database shards, the record comprising the user identifier, the term identifier, and a list of post identifiers; and add the post identifier into the list of post identifiers of the selected record in the most recent database shard. | 0.5 |
17. A non-transitory, computer storage medium comprising code stored therein and executable by a computer system to configure the computer system into a machine for: providing controlled, electronic access to resource data in a variable domain data model that is stored in the computer system, wherein providing controlled, electronic access to resource data in a variable domain data model that is stored in the computer system comprises: receiving information from a computer system of a principal that includes information identifying the principal; storing at least the information identifying the principal; accessing a data security model and a variable domain data model from the memory; performing one or more logical relationship operations on a data security model and a variable domain data model using security attributes of the data security model to determine a level of access to resource data in the variable domain data model to be granted to the principal, wherein the data security model and the variable domain model share a common logical relationship data structure, and the logical data relationship structure includes logical relationship expressions that define data within the data security model and the variable domain model; and granting the principal access via the computer system of the principal to the resource data in accordance with the determined level of resource data access to be granted to the principal, wherein the principal comprises an entity that has controlled access to the resource data. | 17. A non-transitory, computer storage medium comprising code stored therein and executable by a computer system to configure the computer system into a machine for: providing controlled, electronic access to resource data in a variable domain data model that is stored in the computer system, wherein providing controlled, electronic access to resource data in a variable domain data model that is stored in the computer system comprises: receiving information from a computer system of a principal that includes information identifying the principal; storing at least the information identifying the principal; accessing a data security model and a variable domain data model from the memory; performing one or more logical relationship operations on a data security model and a variable domain data model using security attributes of the data security model to determine a level of access to resource data in the variable domain data model to be granted to the principal, wherein the data security model and the variable domain model share a common logical relationship data structure, and the logical data relationship structure includes logical relationship expressions that define data within the data security model and the variable domain model; and granting the principal access via the computer system of the principal to the resource data in accordance with the determined level of resource data access to be granted to the principal, wherein the principal comprises an entity that has controlled access to the resource data. 23. The storage medium of claim 17 wherein the encoded data further comprises code for: providing display data to allow the resource data to be displayed on an electronic monitor, wherein a display of the resource data includes an indication of the level of resource data access granted to the principal. | 0.508652 |
1. A method comprising: receiving, by a Session Initiation Protocol (SIP) server, first call event information, associated with a first call event, from a first module, the first call event information from the first module being processed by the first module using a first type of proprietary application; receiving, by the SIP server, second call event information, associated with a second call event, from a second module, the second call event information from the second module being processed by the second module using a second type of proprietary application, the second type of proprietary application being different from the first type of proprietary application; converting, by the SIP server, the first call event information from a first format associated with the first type of proprietary application into a first Extensible Markup Language (XML) document to generate a first call event record for the first call event information; converting, by the SIP server, the second call event information from a second format associated with the second type of proprietary application into a second XML document to generate a second call event record for the second call event information; creating, by the SIP server, an XML call event file based on the first XML document and the second XML document, creating the XML call event file including: generating a first section that includes data identifying relationships associated with one or more tags included in the XML call event file, generating a second section that includes data identifying the SIP server, generating third section that identifies a type of a first message associated with the first call event and a type of a second message associated with the second call event record, and generating a fourth section that includes information associated with a processing of the first message and information associated with a processing of the second message; and monitoring, by the SIP server, network traffic associated with the SIP server based on the XML call event file using a third type of proprietary application that is different than the first type of proprietary application and the second type of proprietary application. | 1. A method comprising: receiving, by a Session Initiation Protocol (SIP) server, first call event information, associated with a first call event, from a first module, the first call event information from the first module being processed by the first module using a first type of proprietary application; receiving, by the SIP server, second call event information, associated with a second call event, from a second module, the second call event information from the second module being processed by the second module using a second type of proprietary application, the second type of proprietary application being different from the first type of proprietary application; converting, by the SIP server, the first call event information from a first format associated with the first type of proprietary application into a first Extensible Markup Language (XML) document to generate a first call event record for the first call event information; converting, by the SIP server, the second call event information from a second format associated with the second type of proprietary application into a second XML document to generate a second call event record for the second call event information; creating, by the SIP server, an XML call event file based on the first XML document and the second XML document, creating the XML call event file including: generating a first section that includes data identifying relationships associated with one or more tags included in the XML call event file, generating a second section that includes data identifying the SIP server, generating third section that identifies a type of a first message associated with the first call event and a type of a second message associated with the second call event record, and generating a fourth section that includes information associated with a processing of the first message and information associated with a processing of the second message; and monitoring, by the SIP server, network traffic associated with the SIP server based on the XML call event file using a third type of proprietary application that is different than the first type of proprietary application and the second type of proprietary application. 12. The method of claim 1 , where one of the first call event or the second call event comprises receiving a SIP error message. | 0.608767 |
1. A method for routing input business documents received from client computers via a network to one or more operations running on processing servers, the method including: storing on a first server a plurality of operation interface specification data structures that include operation interface specifications, the operation interface specifications including descriptions of operations and definitions of input and output documents; receiving data comprising a document at a second server from a client computer via a network; parsing the document using the second server according to the operation interface specifications to identify an input document and to identify one or more operations that run on one or more processing servers, which accept the identified input document; and routing at least a portion of the input document from the second server to the one or more identified operations running on the processing servers, which accept the identified input document. | 1. A method for routing input business documents received from client computers via a network to one or more operations running on processing servers, the method including: storing on a first server a plurality of operation interface specification data structures that include operation interface specifications, the operation interface specifications including descriptions of operations and definitions of input and output documents; receiving data comprising a document at a second server from a client computer via a network; parsing the document using the second server according to the operation interface specifications to identify an input document and to identify one or more operations that run on one or more processing servers, which accept the identified input document; and routing at least a portion of the input document from the second server to the one or more identified operations running on the processing servers, which accept the identified input document. 2. The method of claim 1 , wherein said operation interface specifications further include data identifying respective descriptions of sets of storage units and logical structures for the sets of storage units. | 0.636499 |
9. A computer system for customizing help content, the computer system comprising: one or more computer processors; one or more computer-readable storage media; program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to receive a request for help content, wherein the request for help content is received after an error is encountered while performing a task with a software product, the request for help content identifying a topic of interest based on the error; program instructions to identify an annotated help file that corresponds to the request for help content; program instructions to identify a plurality of variables in the identified annotated help file, wherein at least a first variable of the plurality of variables includes another variable of the plurality of variables within the first variable; program instructions to retrieve a value for each of the plurality of variables from the software product, wherein the software product queries resources to obtain the value for each of the plurality of variables, wherein the retrieved values include at least two distinct values each of which is a server level parameter value retrieved from a product configuration file, an application user-level parameter value retrieved from a product configuration file, a database level parameter value retrieved from a services file, or a database level parameter value retrieved from a database configuration file; and program instructions to replace each of the plurality of variables in the identified annotated help file with the retrieved value to generate a customized help content. | 9. A computer system for customizing help content, the computer system comprising: one or more computer processors; one or more computer-readable storage media; program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to receive a request for help content, wherein the request for help content is received after an error is encountered while performing a task with a software product, the request for help content identifying a topic of interest based on the error; program instructions to identify an annotated help file that corresponds to the request for help content; program instructions to identify a plurality of variables in the identified annotated help file, wherein at least a first variable of the plurality of variables includes another variable of the plurality of variables within the first variable; program instructions to retrieve a value for each of the plurality of variables from the software product, wherein the software product queries resources to obtain the value for each of the plurality of variables, wherein the retrieved values include at least two distinct values each of which is a server level parameter value retrieved from a product configuration file, an application user-level parameter value retrieved from a product configuration file, a database level parameter value retrieved from a services file, or a database level parameter value retrieved from a database configuration file; and program instructions to replace each of the plurality of variables in the identified annotated help file with the retrieved value to generate a customized help content. 10. The computer system of claim 9 , wherein the annotated help file is annotated with variables for environment and configuration values. | 0.529787 |
6. The communications network of claim 5 wherein said receiving display station further includes: means for storing digital representations of said screen pages, and wherein said means for sampling said visual information density samples said stored representations. | 6. The communications network of claim 5 wherein said receiving display station further includes: means for storing digital representations of said screen pages, and wherein said means for sampling said visual information density samples said stored representations. 7. The communications network of claim 6 wherein said receiving display station further includes: means for calculating a distance by which the width of a screen page exceeds the width of the window within which the page is to be displayed, and means for setting said sequence of horizontal sampling positions at increments of said distance. | 0.786021 |
1. A computing device comprising: a memory; a network interface, when operational, configured to receive web page content and to store the web page content into a memory; a display; and a processor communicatively coupled to the display, the processor, when operational, configured to: use a first application to access the web page content to retrieve address information for a second application, the first application to access hypertext markup language (HTML) web content including the address information and the HTML web content accessible to a web browser, the second application comprising a non-browser application; automatically identify a variable value signifying the address information associated with a hypertext element within a hypertext document for the web page; automatically extract the address information data; provide the extracted address information data as input data to the second application; and request to display an overlaying icon corresponding to the second application on a user interface, the second application to access the address information. | 1. A computing device comprising: a memory; a network interface, when operational, configured to receive web page content and to store the web page content into a memory; a display; and a processor communicatively coupled to the display, the processor, when operational, configured to: use a first application to access the web page content to retrieve address information for a second application, the first application to access hypertext markup language (HTML) web content including the address information and the HTML web content accessible to a web browser, the second application comprising a non-browser application; automatically identify a variable value signifying the address information associated with a hypertext element within a hypertext document for the web page; automatically extract the address information data; provide the extracted address information data as input data to the second application; and request to display an overlaying icon corresponding to the second application on a user interface, the second application to access the address information. 8. The device of claim 1 , wherein the processor is to store the address information in a data structure associated with the second application. | 0.528846 |
1. A method for processing queries comprising: executing a query to generate a relation defined by a model clause specified in said query, said model clause specifying: one or more dimension columns of said relation, and a rule, wherein said rule comprises: a left-side expression, wherein said left-side expression includes one or more existential predicates, wherein each of said one or more existential predicates evaluates to a Boolean value and refers to at least one of said one or more dimension columns of said relation; and a right-side expression; wherein executing said query comprises evaluating said rule, wherein evaluating said rule includes performing an UPSERT operation to insert a row into said relation; and wherein the method is performed by one or more computer systems. | 1. A method for processing queries comprising: executing a query to generate a relation defined by a model clause specified in said query, said model clause specifying: one or more dimension columns of said relation, and a rule, wherein said rule comprises: a left-side expression, wherein said left-side expression includes one or more existential predicates, wherein each of said one or more existential predicates evaluates to a Boolean value and refers to at least one of said one or more dimension columns of said relation; and a right-side expression; wherein executing said query comprises evaluating said rule, wherein evaluating said rule includes performing an UPSERT operation to insert a row into said relation; and wherein the method is performed by one or more computer systems. 5. The method of claim 1 , wherein the method is performed by a database server that executes on the one or more computer systems. | 0.780157 |
16. A system for augmenting a machine translation phrase table with additional phrase pairs each pair of which associates a phrase in a source language with a phrase in a target language, comprising: one or more computing devices, wherein said computing devices are in communication with each other via a computer network whenever there are multiple computing devices; and a computer program having program modules executable by the one or more computing devices, the one or more computing devices being directed by the program modules of the computer program to, input one or more syntactic transfer patterns, each of said patterns defining the syntax of a translation to the target language of a different phrase structure in the source language, wherein each source language phrase type represents a phase having a particular syntactic structure that is different from the other source language phrase types; for each inputted syntactic transfer pattern, synthesize phrases in the source language of the type associated with the pattern under consideration using a lexicon of the source language, eliminate synthesized phrases not found in a monolingual corpus of the source language, for each remaining synthesized phrase, translate the synthesized phrase into the target language using the syntactic transfer pattern under consideration, a bilingual source-to-target language dictionary, and a morphological synthesizer to properly inflect the words of each translated phrase, eliminate translated phrases not found in a monolingual corpus of the target language, and for each remaining translated phrase, generate a phrase pair comprising the translated phrase and its corresponding source language phrase, eliminate phrase pairs that are already found in a current version of the phrase table, and add the generated phrase pair to the current version of the phrase table. | 16. A system for augmenting a machine translation phrase table with additional phrase pairs each pair of which associates a phrase in a source language with a phrase in a target language, comprising: one or more computing devices, wherein said computing devices are in communication with each other via a computer network whenever there are multiple computing devices; and a computer program having program modules executable by the one or more computing devices, the one or more computing devices being directed by the program modules of the computer program to, input one or more syntactic transfer patterns, each of said patterns defining the syntax of a translation to the target language of a different phrase structure in the source language, wherein each source language phrase type represents a phase having a particular syntactic structure that is different from the other source language phrase types; for each inputted syntactic transfer pattern, synthesize phrases in the source language of the type associated with the pattern under consideration using a lexicon of the source language, eliminate synthesized phrases not found in a monolingual corpus of the source language, for each remaining synthesized phrase, translate the synthesized phrase into the target language using the syntactic transfer pattern under consideration, a bilingual source-to-target language dictionary, and a morphological synthesizer to properly inflect the words of each translated phrase, eliminate translated phrases not found in a monolingual corpus of the target language, and for each remaining translated phrase, generate a phrase pair comprising the translated phrase and its corresponding source language phrase, eliminate phrase pairs that are already found in a current version of the phrase table, and add the generated phrase pair to the current version of the phrase table. 19. The system of claim 16 , wherein the program module for synthesizing phrases in the source language of the type associated with the pattern under consideration using a lexicon of the source language, comprises a sub-module for synthesizing a phrase for every possible combination of words in the lexicon that correspond to syntactic constituents of the source language phrase type associated with the pattern under consideration. | 0.508735 |
13. The apparatus of claim 12 wherein the total number of words in a phrase is random. | 13. The apparatus of claim 12 wherein the total number of words in a phrase is random. 14. The apparatus of claim 13 wherein the total number of words in a phrase has a maximum of five words. | 0.949772 |
5. The system of claim 4 , further comprises a training component that classifies the text input as at least one of indicating that an action is to occur or indicating that an action is not to occur based at least in part upon evaluating a previous action observed in conjunction with a similar input. | 5. The system of claim 4 , further comprises a training component that classifies the text input as at least one of indicating that an action is to occur or indicating that an action is not to occur based at least in part upon evaluating a previous action observed in conjunction with a similar input. 6. The system of claim 5 , the training component stores the classification as a case and the action probability component utilizes previous relevant case information in computing the probability value. | 0.822324 |
1. A computer-implemented method for predicting answers to questions concerning medical image analytics reports, the method comprising: splitting a medical image analytics report into a plurality of sentences; generating a plurality of sentence embedding vectors by applying a natural language processing framework to the plurality of sentences; receiving a question related to subject matter included in the medical image analytics report; generating a question embedding vector by applying the natural language processing framework to the question; identifying a subset of the sentence embedding vectors most similar to the question embedding vector by applying a similarity matching process to the sentence embedding vectors and the question embedding vector; and using a trained recurrent neural network (RNN) to determine a predicted answer to the question based on the subset of the sentence embedding vectors. | 1. A computer-implemented method for predicting answers to questions concerning medical image analytics reports, the method comprising: splitting a medical image analytics report into a plurality of sentences; generating a plurality of sentence embedding vectors by applying a natural language processing framework to the plurality of sentences; receiving a question related to subject matter included in the medical image analytics report; generating a question embedding vector by applying the natural language processing framework to the question; identifying a subset of the sentence embedding vectors most similar to the question embedding vector by applying a similarity matching process to the sentence embedding vectors and the question embedding vector; and using a trained recurrent neural network (RNN) to determine a predicted answer to the question based on the subset of the sentence embedding vectors. 9. The method of claim 1 , wherein the similarity matching process comprises: calculating a cosine product between each sentence embedding vector and the question embedding vector to yield a similarity score for each sentence embedding vector; ranking the sentence embedding vectors according to similarity score; and selecting a predetermined number of highest ranking sentence embedding vectors as the subset of the sentence embedding vectors. | 0.573128 |
9. The one or more non-transitory computer-readable media of claim 5 , wherein the receiving the search query from the user device comprises receiving the search query from an electronic book reader device. | 9. The one or more non-transitory computer-readable media of claim 5 , wherein the receiving the search query from the user device comprises receiving the search query from an electronic book reader device. 10. The one or more non-transitory computer-readable media of claim 9 , wherein the receiving the search query comprises receiving a selection of text from the electronic book being displayed on the electronic book reader device. | 0.951271 |
1. A method of spell checking a document, the method comprising: at a client device, activating a browser-based application received from a server through a network; on the client device, receiving a data structure for a dictionary comprising a list of correctly spelled words from the server, the data structure utilized to prune the number of searches of the dictionary to match a word to strings associated with valid words in the dictionary, wherein the data structure is independent of the browser-based application and is received from the server in a data file separate from the browser-based application; and by the browser-based application at the client device, determining a word as having a correct spelling when the word matches a string associated with a valid word in the data structure for the dictionary. | 1. A method of spell checking a document, the method comprising: at a client device, activating a browser-based application received from a server through a network; on the client device, receiving a data structure for a dictionary comprising a list of correctly spelled words from the server, the data structure utilized to prune the number of searches of the dictionary to match a word to strings associated with valid words in the dictionary, wherein the data structure is independent of the browser-based application and is received from the server in a data file separate from the browser-based application; and by the browser-based application at the client device, determining a word as having a correct spelling when the word matches a string associated with a valid word in the data structure for the dictionary. 7. The method of claim 1 , wherein the data structure for the dictionary is a prefix tree, the prefix tree comprising a plurality of nodes in a parent-child hierarchical relationship, each node associated with a character, each node further associated with a string, all descendants of a node having a common prefix of the string associated with that node. | 0.612865 |
16. A processing system, comprising: a processor; and a memory coupled with the processor and storing instructions which, when executed by the processor, cause the processing system to perform a process that includes: intercepting emails sent by a first entity while the emails are being transmitted on a network; automatically constructing a knowledge profile of the first entity based on a plurality of sets of text from the intercepted emails; storing the knowledge profile as part of a knowledge base stored in a machine-accessible storage facility; in response to preparation of a particular email prepared by a second entity and intended for at least one other entity, identifying, prior to sending the particular email by the second entity, one or more suggested potential recipients as meeting one or more criteria based at least in part on a comparison of the knowledge profile of the one or more suggested potential recipients and text contained in the particular email prepared by the second entity; outputting a recommendation to include at least a first entity as a recipient of the particular email prepared by the second entity, the first entity meeting the one or more criteria and being one of the one or more suggested potential recipients; and providing a matching metric indicative of a relative strength of the recommendation for the one or more suggested potential recipients, the matching metric comprises a sum of confidence level values associated with the one or more suggested potential recipients. | 16. A processing system, comprising: a processor; and a memory coupled with the processor and storing instructions which, when executed by the processor, cause the processing system to perform a process that includes: intercepting emails sent by a first entity while the emails are being transmitted on a network; automatically constructing a knowledge profile of the first entity based on a plurality of sets of text from the intercepted emails; storing the knowledge profile as part of a knowledge base stored in a machine-accessible storage facility; in response to preparation of a particular email prepared by a second entity and intended for at least one other entity, identifying, prior to sending the particular email by the second entity, one or more suggested potential recipients as meeting one or more criteria based at least in part on a comparison of the knowledge profile of the one or more suggested potential recipients and text contained in the particular email prepared by the second entity; outputting a recommendation to include at least a first entity as a recipient of the particular email prepared by the second entity, the first entity meeting the one or more criteria and being one of the one or more suggested potential recipients; and providing a matching metric indicative of a relative strength of the recommendation for the one or more suggested potential recipients, the matching metric comprises a sum of confidence level values associated with the one or more suggested potential recipients. 17. The processing system as recited in claim 16 , the memory further storing instructions which, when executed by the processor, cause the processing system to: in response to identifying that the first entity meets the one or more criteria, indicate to the second entity that the first entity meets the one or more criteria. | 0.52194 |
22. An apparatus for recognizing an identifier entered by a user, the entered identifier including a first plurality of predetermined characters, wherein the characters are selected from a first set of characters, the first set of characters including a first total number of characters, the system comprising: means for receiving a recognized identifier based on the entered identifier, the recognized identifier comprising a second plurality of predetermined characters; a first memory that stores a plurality of reference identifiers, each one of the reference identifiers comprising a different plurality of predetermined characters, each one of the different plurality of predetermined characters belonging to the first set of characters; a second memory that stores a first arrangement of character recognition probabilities, the first arrangement of character recognition probabilities encompassing a second set of characters having a second total number of characters and is a superset of the characters of the first set of characters, each of the character recognition probabilities representing a probability that a certain recognized character corresponds to a certain entered character; and a third memory that stores constraint data; and a processor, in communication with the means for receiving, the first memory, the second memory, and the third memory, that produces in accordance with the constraint data of the third memory a constrained arrangement of character recognition probabilities, the constrained arrangement of character recognition probabilities being produced by constraining the first arrangement of character recognition probabilities to encompass a third set of characters constituting a subset of the second set of characters, the processor determining for every one of the plurality of reference identifiers a corresponding identifier recognition probability, each of the corresponding identifier recognition probabilities being determined on the basis of the constrained arrangement of character recognition probabilities, the processor selecting the reference identifier most likely matching the entered identifier based on the identifier recognition probabilities. | 22. An apparatus for recognizing an identifier entered by a user, the entered identifier including a first plurality of predetermined characters, wherein the characters are selected from a first set of characters, the first set of characters including a first total number of characters, the system comprising: means for receiving a recognized identifier based on the entered identifier, the recognized identifier comprising a second plurality of predetermined characters; a first memory that stores a plurality of reference identifiers, each one of the reference identifiers comprising a different plurality of predetermined characters, each one of the different plurality of predetermined characters belonging to the first set of characters; a second memory that stores a first arrangement of character recognition probabilities, the first arrangement of character recognition probabilities encompassing a second set of characters having a second total number of characters and is a superset of the characters of the first set of characters, each of the character recognition probabilities representing a probability that a certain recognized character corresponds to a certain entered character; and a third memory that stores constraint data; and a processor, in communication with the means for receiving, the first memory, the second memory, and the third memory, that produces in accordance with the constraint data of the third memory a constrained arrangement of character recognition probabilities, the constrained arrangement of character recognition probabilities being produced by constraining the first arrangement of character recognition probabilities to encompass a third set of characters constituting a subset of the second set of characters, the processor determining for every one of the plurality of reference identifiers a corresponding identifier recognition probability, each of the corresponding identifier recognition probabilities being determined on the basis of the constrained arrangement of character recognition probabilities, the processor selecting the reference identifier most likely matching the entered identifier based on the identifier recognition probabilities. 23. The apparatus according to claim 22, wherein the selected reference identifier corresponds to the highest identifier recognition probability. | 0.643361 |
1. A method comprising: receiving data including chat room data from a chat room server; receiving input data from at least one input device; preparing a user interface screen for output to a display device, the user interface screen including a chat room list including a plurality of chat room panels, each one chat room panel of the plurality of chat room panels including information about a different chat room from a plurality of chat rooms; and a chat room icon of the different chat room, wherein a first chat room panel of the plurality of chat room panels includes an indication of how many chat room members of a first chat room from the plurality of chat rooms have read a first message posted in the first chat room. | 1. A method comprising: receiving data including chat room data from a chat room server; receiving input data from at least one input device; preparing a user interface screen for output to a display device, the user interface screen including a chat room list including a plurality of chat room panels, each one chat room panel of the plurality of chat room panels including information about a different chat room from a plurality of chat rooms; and a chat room icon of the different chat room, wherein a first chat room panel of the plurality of chat room panels includes an indication of how many chat room members of a first chat room from the plurality of chat rooms have read a first message posted in the first chat room. 2. The method according to claim 1 , further comprising: interpreting the input data to include selecting entry to, and posting the first message in, the first chat room; and sending the first message to the chat room server. | 0.757908 |
5. An instructional globe comprising a globe-shaped body forming a representation of the earth by a number of information-laden, spherical surface appendages, and wherein said appendages comprise spherical surface segments and wherein there are cues on the surface of the globe having a profile corresponding in configuration to said specific ones of said spherical surface segments, wherein there are attaching means for removably attaching said segments to the globe-shaped body in manners and positions to visually or tactically reinforce the geographical concepts of the world, wherein said cues comprise a plurality of indentations and wherein each of said spherical surface segments in geometrically similar in outline to a corresponding indentation. | 5. An instructional globe comprising a globe-shaped body forming a representation of the earth by a number of information-laden, spherical surface appendages, and wherein said appendages comprise spherical surface segments and wherein there are cues on the surface of the globe having a profile corresponding in configuration to said specific ones of said spherical surface segments, wherein there are attaching means for removably attaching said segments to the globe-shaped body in manners and positions to visually or tactically reinforce the geographical concepts of the world, wherein said cues comprise a plurality of indentations and wherein each of said spherical surface segments in geometrically similar in outline to a corresponding indentation. 6. An instructional globe according to claim 5 wherein said cues comprise a plurality of indentations and each of said spherical segments is geometrically similar in outline to a corresponding indentation. | 0.734944 |
4. The computer-implemented method of claim 1 , wherein storing a seed includes storing a seed associated with a constraint solve call. | 4. The computer-implemented method of claim 1 , wherein storing a seed includes storing a seed associated with a constraint solve call. 7. The computer-implemented method of claim 4 , wherein storing includes storing each seed for each of a plurality of constraint solve calls. | 0.926614 |
17. A non-transitory computer readable recording medium on which a program is recorded, said program executed on a computer to function as a system comprising: an input part for inputting image data; a word extracting part for extracting a word from texts contained in said image data; a synonym obtaining part for obtaining a synonym corresponding to said word, and for associating said obtained synonym with said word; a position identifying part for identifying a display position on said image data of said word with which said synonym is associated; a layer creating part for creating an accompanying layer to add to an original layer, which is said image data containing said word, and for embedding said synonym associated with said word within a position on said accompanying layer that is the same as the display position of the word in said original layer identified by said position identifying part so that the synonym in the accompanying layer overlaps the word in the original layer without replacing the word in the original layer, wherein the location of a first character of the synonym in the accompanying layer matches the location of a first character of the word in the original layer, or the display area of the synonym in the accompanying layer has the same size as the display area of the word in the original layer and is at the same location in the accompanying layer as the display area of the word in the original layer; and an output image generating part for generating output image data including said original layer containing said word and said accompanying layer within which said synonym is embedded and overlaps the word. | 17. A non-transitory computer readable recording medium on which a program is recorded, said program executed on a computer to function as a system comprising: an input part for inputting image data; a word extracting part for extracting a word from texts contained in said image data; a synonym obtaining part for obtaining a synonym corresponding to said word, and for associating said obtained synonym with said word; a position identifying part for identifying a display position on said image data of said word with which said synonym is associated; a layer creating part for creating an accompanying layer to add to an original layer, which is said image data containing said word, and for embedding said synonym associated with said word within a position on said accompanying layer that is the same as the display position of the word in said original layer identified by said position identifying part so that the synonym in the accompanying layer overlaps the word in the original layer without replacing the word in the original layer, wherein the location of a first character of the synonym in the accompanying layer matches the location of a first character of the word in the original layer, or the display area of the synonym in the accompanying layer has the same size as the display area of the word in the original layer and is at the same location in the accompanying layer as the display area of the word in the original layer; and an output image generating part for generating output image data including said original layer containing said word and said accompanying layer within which said synonym is embedded and overlaps the word. 18. The non-transitory computer readable recording medium according to claim 17 , wherein said layer creating part, when said synonym obtaining part obtains multiple synonyms corresponding to said single word, creates more than one said accompanying layers and embeds each of said multiple synonyms associated with said single word within said different accompanying layer. | 0.581357 |
4. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by a mobile computing device that is (i) configured to process voice commands that are preceded by a predefined hotword, and (ii) is in proximity to another mobile computing device that is also configured to process voice commands that are preceded by the same, predefined hotword, an audio input representing an utterance by the speaker of a voice command that is preceded by the predefined hotword; while receiving the audio input representing the utterance by the speaker of the voice command that is preceded by the predefined hotword, performing, by the mobile computing device, an operation; after receiving the audio input representing the utterance by the speaker of the voice command that is preceded by the predefined hotword, receiving an ultrasonic signal from the other mobile computing device; in response to receiving the ultrasonic signal from the other mobile computing device, (i) placing the mobile device into a sleep mode, (ii) bypassing, by the mobile computing device, further processing of the voice command, (iii) bypassing, by the mobile computing device, emitting an ultrasonic signal, and (iv) bypassing, by the mobile computing device, outputting a visual indication that the mobile computing device is processing the voice command; and while receiving the ultrasonic signal from the other mobile computing device and bypassing processing of the voice command, continuing, by the mobile computing device, to perform the operation without interruption. | 4. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by a mobile computing device that is (i) configured to process voice commands that are preceded by a predefined hotword, and (ii) is in proximity to another mobile computing device that is also configured to process voice commands that are preceded by the same, predefined hotword, an audio input representing an utterance by the speaker of a voice command that is preceded by the predefined hotword; while receiving the audio input representing the utterance by the speaker of the voice command that is preceded by the predefined hotword, performing, by the mobile computing device, an operation; after receiving the audio input representing the utterance by the speaker of the voice command that is preceded by the predefined hotword, receiving an ultrasonic signal from the other mobile computing device; in response to receiving the ultrasonic signal from the other mobile computing device, (i) placing the mobile device into a sleep mode, (ii) bypassing, by the mobile computing device, further processing of the voice command, (iii) bypassing, by the mobile computing device, emitting an ultrasonic signal, and (iv) bypassing, by the mobile computing device, outputting a visual indication that the mobile computing device is processing the voice command; and while receiving the ultrasonic signal from the other mobile computing device and bypassing processing of the voice command, continuing, by the mobile computing device, to perform the operation without interruption. 13. The system of claim 4 , wherein the operation comprises playing a video. | 0.835213 |
21. The system of claim 14 , wherein the operations further comprise: associating the document with a non-weighted overall quality of result statistic; receiving the query, and in response to receiving the query, determining whether to select either the weighted overall quality of result statistic or the non-weighted overall quality of result statistic; selecting either the weighted overall quality of result statistic or the non-weighted overall quality of result statistic in response to the determination; and providing the selected overall quality of result statistic to a ranking engine implemented on one or more computers. | 21. The system of claim 14 , wherein the operations further comprise: associating the document with a non-weighted overall quality of result statistic; receiving the query, and in response to receiving the query, determining whether to select either the weighted overall quality of result statistic or the non-weighted overall quality of result statistic; selecting either the weighted overall quality of result statistic or the non-weighted overall quality of result statistic in response to the determination; and providing the selected overall quality of result statistic to a ranking engine implemented on one or more computers. 22. The system of claim 21 , wherein the operations further comprise determining a difference score for the reference version of the document and a current version of the document, and wherein selecting either the weighted overall quality of result statistic or non-weighted overall quality of result statistic comprises selecting a statistic according to the difference score. | 0.845096 |
7. A computer-implemented method, comprising: under control of one or more computing devices including executable instructions, acquiring image information from at least one image captured using at least one image sensor of a computing device, the image information being stored for a duration of time on a rolling basis; analyzing the image information to detect a hand gesture performed by a user; determining, in the image information, movement of one or more fingers, the movement corresponding to a first portion of a candidate hand gesture; analyzing the image information stored for the duration of time to detect a second portion of the candidate hand gesture; comparing the first portion of the candidate hand gesture and the second portion of the candidate hand gesture to at least one gesture associated with the user, the second portion of the candidate hand gesture having been performed before the first portion; and providing an input to an application executing on the computing device in response to the first portion of the candidate hand gesture and the second portion of the candidate hand gesture being determined to correspond to the at least one gesture associated with the user, the at least one gesture associated with the user being specific to the user for providing the input to the application. | 7. A computer-implemented method, comprising: under control of one or more computing devices including executable instructions, acquiring image information from at least one image captured using at least one image sensor of a computing device, the image information being stored for a duration of time on a rolling basis; analyzing the image information to detect a hand gesture performed by a user; determining, in the image information, movement of one or more fingers, the movement corresponding to a first portion of a candidate hand gesture; analyzing the image information stored for the duration of time to detect a second portion of the candidate hand gesture; comparing the first portion of the candidate hand gesture and the second portion of the candidate hand gesture to at least one gesture associated with the user, the second portion of the candidate hand gesture having been performed before the first portion; and providing an input to an application executing on the computing device in response to the first portion of the candidate hand gesture and the second portion of the candidate hand gesture being determined to correspond to the at least one gesture associated with the user, the at least one gesture associated with the user being specific to the user for providing the input to the application. 17. The computer-implemented method of claim 7 , wherein the performed gesture is a static gesture made with a hand or a finger of the user for a period of time. | 0.613968 |
64. The system of claim 60 , wherein at least one of the one or more profiles is a user profile that pertains to the user's general preferences that are not specifically associated with a search, and wherein at least one of the one or more profiles is a search profile that pertains to a particular query or query type not specifically associated with the user. | 64. The system of claim 60 , wherein at least one of the one or more profiles is a user profile that pertains to the user's general preferences that are not specifically associated with a search, and wherein at least one of the one or more profiles is a search profile that pertains to a particular query or query type not specifically associated with the user. 65. The system of claim 64 , further comprising combining the user profile and the search profile to create a biased profile, wherein weights in the search profile are biased by weights in the user profile using a biasing function selected from a group consisting of: a mean, a geometric mean, a generalized mean, a trimmed mean, a winsorized mean, and a median. | 0.903846 |
7. A system, comprising: a processor; and one or more computer-readable storage media having computer-executable instructions stored thereon that, when executed by the processor, implement: an extensible editor that processes editing events requesting manipulation of a document, the extensible editor having an event routing controller and a default event handler; and a first extension and a second extension coupled with the extensible editor for processing the editing events, wherein the event routing controller provides an editing event received by the extensible editor to the first extension prior to providing the editing event to be processed by the default event handler, wherein the event routing controller provides the editing event to the second extension prior to providing the editing event to be processed by the default event handler when the first extension does not consume the editing event, and wherein an order in which the editing event is routed to the first extension and the second extension is based on an order in which the first extension and the second extension were registered with the extensible editor. | 7. A system, comprising: a processor; and one or more computer-readable storage media having computer-executable instructions stored thereon that, when executed by the processor, implement: an extensible editor that processes editing events requesting manipulation of a document, the extensible editor having an event routing controller and a default event handler; and a first extension and a second extension coupled with the extensible editor for processing the editing events, wherein the event routing controller provides an editing event received by the extensible editor to the first extension prior to providing the editing event to be processed by the default event handler, wherein the event routing controller provides the editing event to the second extension prior to providing the editing event to be processed by the default event handler when the first extension does not consume the editing event, and wherein an order in which the editing event is routed to the first extension and the second extension is based on an order in which the first extension and the second extension were registered with the extensible editor. 12. The system as recited in claim 7 , wherein the extensible editor further comprises an edit designer interface that includes a pre-handle event method for providing the event to the first extension prior to the default event handler receiving the event. | 0.604324 |
1. A method comprising: displaying text in a display region using an initial display size; detecting a selection of a desired text collection; receiving an instruction to increase a display size of the desired text collection, wherein the instruction is provided by an input detected within the display region; determining a sequence of display sizes based on the desired text collection; detecting a selection of an increased display size larger than the initial display size from the sequence of display sizes; and displaying the desired text collection in the display region using the increased display size. | 1. A method comprising: displaying text in a display region using an initial display size; detecting a selection of a desired text collection; receiving an instruction to increase a display size of the desired text collection, wherein the instruction is provided by an input detected within the display region; determining a sequence of display sizes based on the desired text collection; detecting a selection of an increased display size larger than the initial display size from the sequence of display sizes; and displaying the desired text collection in the display region using the increased display size. 4. The method of claim 1 , further comprising: increasing a size of the display region to accommodate the text displayed using the increased display size. | 0.532824 |
10. The method of claim 8 , wherein the step of performing a threshold selection on the word segmentation hypotheses further uses automatically generated over and under segmentation training data. | 10. The method of claim 8 , wherein the step of performing a threshold selection on the word segmentation hypotheses further uses automatically generated over and under segmentation training data. 11. The method of claim 10 , wherein the over and under segmentation training data is obtained by performing the steps of: providing a collection of training documents containing text line and word information; computing estimates of average intra-word and inter-word distances; generating over-segmented text lines by merging neighboring connected components closer than given first threshold percentage of the average intra-word distance; generating over-segmented text lines by merging neighboring connected components closer than given second threshold percentage of the average inter-word distance. | 0.731758 |
24. The database proxy system of claim 21 , wherein the language identifying module receives an update to the plurality of pattern datasets from a rules database communicatively coupled to the database proxy system. | 24. The database proxy system of claim 21 , wherein the language identifying module receives an update to the plurality of pattern datasets from a rules database communicatively coupled to the database proxy system. 25. The database proxy system of claim 24 , wherein the rules database updates the plurality of pattern datasets in response to receiving an update to rules associated with rewriting the identified language. | 0.93069 |
1. A method, in a question answering (QA) system comprising a processor and a memory comprising instructions executed by the processor, for performing persona-based question answering, the method comprising: receiving, by the processor, an identification of a requested persona from a user; receiving, by the processor, a natural language question input specifying an input question to be answered by the QA system; responsive to receiving the requested persona, customizing, by the processor, components of the QA system to answer questions from a viewpoint of the requested persona; generating, by the processor, an answer to the input question from the viewpoint of the requested persona based on the customization of the components of the QA system; and outputting, by the processor, the answer to the input question in a form representative of the requested persona at least by re-formatting the answer utilizing a language style and word choice corresponding to the requested persona. | 1. A method, in a question answering (QA) system comprising a processor and a memory comprising instructions executed by the processor, for performing persona-based question answering, the method comprising: receiving, by the processor, an identification of a requested persona from a user; receiving, by the processor, a natural language question input specifying an input question to be answered by the QA system; responsive to receiving the requested persona, customizing, by the processor, components of the QA system to answer questions from a viewpoint of the requested persona; generating, by the processor, an answer to the input question from the viewpoint of the requested persona based on the customization of the components of the QA system; and outputting, by the processor, the answer to the input question in a form representative of the requested persona at least by re-formatting the answer utilizing a language style and word choice corresponding to the requested persona. 4. The method of claim 1 , wherein customizing the components of the QA system comprises: ingesting, by the QA system, a persona-specific corpus, generated as a sub-corpus from one or more larger size corpora, wherein the persona-specific corpus comprises content of the one or more larger size corpora that is at least one of authored by the requested persona, contains statements attributed to the persona, descriptive of the requested persona, or descriptive of information that would have been known to the requested persona. | 0.565897 |
1. A method comprising: providing a usage tracking engine in an in-memory database and in communication with usage data of a data object of the in-memory database; causing the usage tracking engine to track access to the data object by a database user; causing the usage tracking engine to receive a ranking of the data object from a heuristic learning module in the in-memory database that considers: a geographic location of the database user, a time stamp of access to the data object by the database user, and prior manual placement of the data object in a shelf by the database user; causing the usage tracking engine to check a personalization setting reflecting a number of data objects to be located on the shelf in an application layer accessible to the database user, the number based upon a storage capacity available to the database user; and causing the usage tracking engine to displace the data object from the shelf based upon the ranking and the personalization setting. | 1. A method comprising: providing a usage tracking engine in an in-memory database and in communication with usage data of a data object of the in-memory database; causing the usage tracking engine to track access to the data object by a database user; causing the usage tracking engine to receive a ranking of the data object from a heuristic learning module in the in-memory database that considers: a geographic location of the database user, a time stamp of access to the data object by the database user, and prior manual placement of the data object in a shelf by the database user; causing the usage tracking engine to check a personalization setting reflecting a number of data objects to be located on the shelf in an application layer accessible to the database user, the number based upon a storage capacity available to the database user; and causing the usage tracking engine to displace the data object from the shelf based upon the ranking and the personalization setting. 6. The method of claim 1 wherein the heuristic learning module further considers whether the database user changed the data object, wherein a change in the data object increases the ranking. | 0.739071 |
1. A computer-implemented method for generating recommendations of alternative unique items, the computer-implemented method comprising: receiving electronic data indicating a selection of a selected item; updating, using a computer system, a set of base items to include the selected item, wherein the selected item and the base items each comprise a plurality of attributes; determining, using the computer system, a set of base attributes from the plurality of attributes of the items in the set of base items to use for determining the similarity of alternative unique items to the set of base items; selecting, using the computer system, a set of alternative unique items from a plurality of unique items for comparison to the set of base items; calculating, using the computer system, a first dissimilarity penalty for a first attribute of the set of base attributes for the set of alternative unique items at least partially based on a magnitude of dissimilarity between a value of the first attribute of the set of alternative items and the values of the first attribute of the set of base attributes; calculating, using the computer system, a second dissimilarity penalty for a second attribute of the set of base attributes for the set of alternative unique items at least partially based on a magnitude of dissimilarity between a value of the second attribute of the set of alternative items and the values of the second attribute of the set of base attributes; and generating, using the computer system, a recommendation of alternative unique items, the recommendation comprising ranking of at least a portion of the plurality of the set of alternative unique items, the ranking based at least partially on the generated dissimilarity penalties; wherein the computer system comprises a computer processor and electronic memory. | 1. A computer-implemented method for generating recommendations of alternative unique items, the computer-implemented method comprising: receiving electronic data indicating a selection of a selected item; updating, using a computer system, a set of base items to include the selected item, wherein the selected item and the base items each comprise a plurality of attributes; determining, using the computer system, a set of base attributes from the plurality of attributes of the items in the set of base items to use for determining the similarity of alternative unique items to the set of base items; selecting, using the computer system, a set of alternative unique items from a plurality of unique items for comparison to the set of base items; calculating, using the computer system, a first dissimilarity penalty for a first attribute of the set of base attributes for the set of alternative unique items at least partially based on a magnitude of dissimilarity between a value of the first attribute of the set of alternative items and the values of the first attribute of the set of base attributes; calculating, using the computer system, a second dissimilarity penalty for a second attribute of the set of base attributes for the set of alternative unique items at least partially based on a magnitude of dissimilarity between a value of the second attribute of the set of alternative items and the values of the second attribute of the set of base attributes; and generating, using the computer system, a recommendation of alternative unique items, the recommendation comprising ranking of at least a portion of the plurality of the set of alternative unique items, the ranking based at least partially on the generated dissimilarity penalties; wherein the computer system comprises a computer processor and electronic memory. 5. The computer-implemented method of claim 1 , wherein receiving an indication of electronic data indicating a selection of a selected item includes receiving an indication of a level of interest in the selected item. | 0.570495 |
2. A method comprising the steps of: manipulating keywords via a user interface; a plurality of grouping blocks wherein each of the plurality of grouping blocks displays summary information about the keywords contained within each of the plurality of grouping blocks; and displaying keywords via a user interface, the user interface providing a general way to display and interact with groups and hierarchies using blocks, including an inverted “L” shaped block, wherein at least a first inverted “L” shaped block represents a single keyword concept. | 2. A method comprising the steps of: manipulating keywords via a user interface; a plurality of grouping blocks wherein each of the plurality of grouping blocks displays summary information about the keywords contained within each of the plurality of grouping blocks; and displaying keywords via a user interface, the user interface providing a general way to display and interact with groups and hierarchies using blocks, including an inverted “L” shaped block, wherein at least a first inverted “L” shaped block represents a single keyword concept. 19. The method of claim 2 wherein the groups and hierarchies represent at least one hierarchical relationship based on categories. | 0.880312 |
7. A social bookmarking data processing system configured for displaying search results for weighted, multi-term content searches, the system comprising: a hardware processor and memory; a social bookmarking system coupled to a data store of social bookmarks and coupled to a plurality of content sources over a computer communications network; a multi-term search engine module executing by the hardware processor and memory in a computing platform and coupled to the social bookmarking system, the module comprising program code enabled to perform a content search for both content and content meta-data according to specified weighted search terms, to retrieve search results for the content search, to compute a relevance for each of the weighted search terms, and to present both the search results and also a relevance indicator for each computed relevance for each of the weighted search terms found in connection with each of the search results in a user interface to the search engine. | 7. A social bookmarking data processing system configured for displaying search results for weighted, multi-term content searches, the system comprising: a hardware processor and memory; a social bookmarking system coupled to a data store of social bookmarks and coupled to a plurality of content sources over a computer communications network; a multi-term search engine module executing by the hardware processor and memory in a computing platform and coupled to the social bookmarking system, the module comprising program code enabled to perform a content search for both content and content meta-data according to specified weighted search terms, to retrieve search results for the content search, to compute a relevance for each of the weighted search terms, and to present both the search results and also a relevance indicator for each computed relevance for each of the weighted search terms found in connection with each of the search results in a user interface to the search engine. 8. The system of claim 7 , wherein the program code of the module is further enabled to present an iconic representation of confidence for each of the search results, the confidence for a search result reflecting a number of bookmarks established for a the search result. | 0.651113 |
1. An apparatus for enabling an object-oriented application, including object-oriented statements to access a procedural operating system including procedural functions saved as executable program logic which are called to access services provided by said procedural operating system to enable communications between a host computer and a second computer, comprising: (a) computer; (b) a memory component in said computer; (c) a code library, stored in said memory component, comprising: means for storing said executable program logic in an object-oriented class library; means for interfacing said object-oriented application to said procedural operating system utilizing said executable program logic; (d) means, in said computer, for processing object-oriented statements by inserting said executable program logic which corresponds to said object-oriented statements into said object-oriented application to access said host computer; and (e) said host computer comprising a plurality of processors operating in parallel, and wherein one of said plurality of processors contains said means for processing object-oriented statements by inserting said executable program logic which corresponds to said object-oriented statements into said object-oriented application to interface said procedural operating system and facilitate communication with said second computer. | 1. An apparatus for enabling an object-oriented application, including object-oriented statements to access a procedural operating system including procedural functions saved as executable program logic which are called to access services provided by said procedural operating system to enable communications between a host computer and a second computer, comprising: (a) computer; (b) a memory component in said computer; (c) a code library, stored in said memory component, comprising: means for storing said executable program logic in an object-oriented class library; means for interfacing said object-oriented application to said procedural operating system utilizing said executable program logic; (d) means, in said computer, for processing object-oriented statements by inserting said executable program logic which corresponds to said object-oriented statements into said object-oriented application to access said host computer; and (e) said host computer comprising a plurality of processors operating in parallel, and wherein one of said plurality of processors contains said means for processing object-oriented statements by inserting said executable program logic which corresponds to said object-oriented statements into said object-oriented application to interface said procedural operating system and facilitate communication with said second computer. 3. The apparatus of claim 1, wherein said code library comprises an object-oriented class which includes as data a protocol for accessing a port in each of said plurality of processors, and methods for utilizing said protocol to enable and disable scheduling policies, to set a maximum priority for one of said plurality of processors, and to define tasks and threads which execute on one of said plurality of processors. | 0.5 |
1. A computer-implemented method, comprising: receiving, from a client device and by an image search engine, an image search query including (i) a query image and (ii) an indication of a particular image acquisition template that was overlaid on a viewfinder of the client device when the query image was captured and that depicts a canonical pose or view of a particular type of object; obtaining, by the image search engine, search results based at least on (i) the query image and (ii) the indication of the particular image acquisition template that was overlaid on the view finder of the client device when the query image was captured and that depicts the canonical pose or view of the particular type of object; and providing, by the image search engine to the client device, the search results for display on the client device. | 1. A computer-implemented method, comprising: receiving, from a client device and by an image search engine, an image search query including (i) a query image and (ii) an indication of a particular image acquisition template that was overlaid on a viewfinder of the client device when the query image was captured and that depicts a canonical pose or view of a particular type of object; obtaining, by the image search engine, search results based at least on (i) the query image and (ii) the indication of the particular image acquisition template that was overlaid on the view finder of the client device when the query image was captured and that depicts the canonical pose or view of the particular type of object; and providing, by the image search engine to the client device, the search results for display on the client device. 7. The method of claim 1 , wherein receiving an image search query including (i) a query image and (ii) an indication of a particular image acquisition template that was overlaid on a viewfinder of the client device when the query image was captured and that depicts a canonical pose or view of a particular type of object comprises: receiving an image file and a separate indication of the particular image acquisition template used to capture the query image. | 0.651122 |
12. The system of claim 8 , wherein: identifying, using the event model, one or more current or future events related to the user that are relevant to the action comprises: identifying user data from the event model that is potentially relevant to the action; determining a level of confidence for an association of the one or more potentially relevant current or future events from the identified user data and the context of the voice input; and identifying one or more current or future events related to the user that are relevant to the action from the potentially relevant events based on the determined level of confidence. | 12. The system of claim 8 , wherein: identifying, using the event model, one or more current or future events related to the user that are relevant to the action comprises: identifying user data from the event model that is potentially relevant to the action; determining a level of confidence for an association of the one or more potentially relevant current or future events from the identified user data and the context of the voice input; and identifying one or more current or future events related to the user that are relevant to the action from the potentially relevant events based on the determined level of confidence. 13. The system of claim 12 , the operations further comprising, when the level of confidence is sufficiently low, presenting a refining prompt to allow the user to select one or more possible values for the one or more missing parameters, the one or more possible values being determined based on data associated with the one or more current or future events. | 0.816632 |
1. A method comprising, by one or more processors associated with one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the plurality of nodes corresponding to a plurality of users associated with an online social network, respectively; identifying a plurality of non-overlapping clusters in the social graph using graph clustering, each cluster comprising a discrete set of nodes from the plurality of nodes; providing a treatment to at least a first set of users and a second set of users, the first and second sets of users corresponding to a first set of clusters and a second set of clusters of the plurality of clusters, respectively, the first set of clusters being discrete from the second set of clusters; and determining, for each of at least the first and second sets of users, a treatment effect of the treatment on the users of the set of users based on a network exposure to the treatment for each user, wherein, for each respective cluster, the network exposure of the nodes in the cluster is absolute k-neighborhood exposure, absolute k-core exposure, fractional q-neighborhood exposure, or fractional q-core exposure. | 1. A method comprising, by one or more processors associated with one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the plurality of nodes corresponding to a plurality of users associated with an online social network, respectively; identifying a plurality of non-overlapping clusters in the social graph using graph clustering, each cluster comprising a discrete set of nodes from the plurality of nodes; providing a treatment to at least a first set of users and a second set of users, the first and second sets of users corresponding to a first set of clusters and a second set of clusters of the plurality of clusters, respectively, the first set of clusters being discrete from the second set of clusters; and determining, for each of at least the first and second sets of users, a treatment effect of the treatment on the users of the set of users based on a network exposure to the treatment for each user, wherein, for each respective cluster, the network exposure of the nodes in the cluster is absolute k-neighborhood exposure, absolute k-core exposure, fractional q-neighborhood exposure, or fractional q-core exposure. 7. The method of claim 1 , wherein, for each cluster, the social-graph affinity of the nodes in the cluster with respect to the other nodes in the cluster is greater than a threshold social-graph affinity. | 0.702746 |
4. The method of claim 1 wherein the compiling step comprises providing to a student one or more of the plurality of materials comprising a percentage of words of the materials within one or more of the groups above a predetermined percentage. | 4. The method of claim 1 wherein the compiling step comprises providing to a student one or more of the plurality of materials comprising a percentage of words of the materials within one or more of the groups above a predetermined percentage. 5. The method of claim 4 additionally comprising the step of displaying one or more of the plurality of materials with words within one or more of the groups of core words. | 0.75419 |
1. A method for processing a plurality of references included in a document, the method comprising: receiving a job request including a document for processing from a user, wherein the document comprises at least one of: a hardcopy document and a digital document, wherein the document comprises one or more references; prompting the user to select a reference processing option when the user wants at least one reference of the document to be processed; based on the selection of the reference processing option, determining the one or more references included in the document; based on the determined one or more references, searching for a referred content information corresponding to each of the one or more references; and presenting the referred content information along with one or more options including at least one of: a print option, a save option and a send option to the user. | 1. A method for processing a plurality of references included in a document, the method comprising: receiving a job request including a document for processing from a user, wherein the document comprises at least one of: a hardcopy document and a digital document, wherein the document comprises one or more references; prompting the user to select a reference processing option when the user wants at least one reference of the document to be processed; based on the selection of the reference processing option, determining the one or more references included in the document; based on the determined one or more references, searching for a referred content information corresponding to each of the one or more references; and presenting the referred content information along with one or more options including at least one of: a print option, a save option and a send option to the user. 2. The method of claim 1 , wherein the referred content information along with one or more options including at least one of a print option, a save option and a send option are presented via a user interface of a multi-function device, wherein the referred content information further comprises a purchase information for purchasing the referred content and a download information for downloading the referred content. | 0.578717 |
1. A computer implemented method comprising: integrating a set of standardization functions into database engines to allow access to standardization of data via database queries executed in the database engines against databases; storing a plurality of standardization tables; with an extract module, extracting data before a transform portion of an extract, transform, and load process by issuing a first database query from the database queries to a first database engine of the database engines and a second database query from the database queries to a second database engine of the database engines, wherein the first database query includes a first standardization function, and wherein the second database query includes a second standardization function; with the first database engine, determining a first context included in the first standardization function; and invoking the first standardization function within the first database engine to convert a first data value having the first context using a first standard value and a first standardization table from the plurality of standardization tables that includes a context column for the first context; with the second database engine, determining a second context using metadata values by: identifying the metadata values of a column name and a database schema; mapping the metadata values to the second context using a lookup table; and identifying a second standardization table from the plurality of standardization tables based on the second context, wherein the second standardization table does not include any context column; and invoking the second standardization function within the second database engine to convert a second data value having the second context using a second standard value and the second standardization table; and providing cleansed data in the databases before another transform portion of another extract, transform, and load process by storing the converted first data value and the converted second data value. | 1. A computer implemented method comprising: integrating a set of standardization functions into database engines to allow access to standardization of data via database queries executed in the database engines against databases; storing a plurality of standardization tables; with an extract module, extracting data before a transform portion of an extract, transform, and load process by issuing a first database query from the database queries to a first database engine of the database engines and a second database query from the database queries to a second database engine of the database engines, wherein the first database query includes a first standardization function, and wherein the second database query includes a second standardization function; with the first database engine, determining a first context included in the first standardization function; and invoking the first standardization function within the first database engine to convert a first data value having the first context using a first standard value and a first standardization table from the plurality of standardization tables that includes a context column for the first context; with the second database engine, determining a second context using metadata values by: identifying the metadata values of a column name and a database schema; mapping the metadata values to the second context using a lookup table; and identifying a second standardization table from the plurality of standardization tables based on the second context, wherein the second standardization table does not include any context column; and invoking the second standardization function within the second database engine to convert a second data value having the second context using a second standard value and the second standardization table; and providing cleansed data in the databases before another transform portion of another extract, transform, and load process by storing the converted first data value and the converted second data value. 6. The method of claim 1 wherein the first standardization table contains information for performing measurement conversion. | 0.563302 |
1. An object recognition system comprising: a display; a processor operatively connected to the display; and a memory module operatively connected to the processor, the memory module having program instructions stored therein, wherein the program instructions are executable by the processor to perform a method for object recognition comprising the steps of: generating a set of rules, each rule of the set of rules containing one or more predicates and a consequent, each of the predicates comprising a rule token identifier and a rule probability of recognition associated with the rule token identifier, the rule token identifiers generated from a plurality of systems, each rule token identifier representing a recognized object by at least one of the systems, each rule of the set of rules derived by associating a range of rule probabilities of recognition for one or more rule token identifiers to a known object, wherein the range of rule probabilities of recognition for each rule token identifier is determined by combining multiple rule probabilities of recognition for each rule token identifier, each rule probability of recognition determined by at least one of the systems, using the plurality of systems to recognize a target object, each system producing a response, the response comprising at least one response token identifier and a response probability of recognition associated with each response token identifier, wherein each response is combined to form a set of responses, applying the set of rules to the set of responses to determine an output, wherein the output comprises an identification of a known object and an identification probability of recognition associated with the known object, and displaying the output to a user on the display. | 1. An object recognition system comprising: a display; a processor operatively connected to the display; and a memory module operatively connected to the processor, the memory module having program instructions stored therein, wherein the program instructions are executable by the processor to perform a method for object recognition comprising the steps of: generating a set of rules, each rule of the set of rules containing one or more predicates and a consequent, each of the predicates comprising a rule token identifier and a rule probability of recognition associated with the rule token identifier, the rule token identifiers generated from a plurality of systems, each rule token identifier representing a recognized object by at least one of the systems, each rule of the set of rules derived by associating a range of rule probabilities of recognition for one or more rule token identifiers to a known object, wherein the range of rule probabilities of recognition for each rule token identifier is determined by combining multiple rule probabilities of recognition for each rule token identifier, each rule probability of recognition determined by at least one of the systems, using the plurality of systems to recognize a target object, each system producing a response, the response comprising at least one response token identifier and a response probability of recognition associated with each response token identifier, wherein each response is combined to form a set of responses, applying the set of rules to the set of responses to determine an output, wherein the output comprises an identification of a known object and an identification probability of recognition associated with the known object, and displaying the output to a user on the display. 4. The object recognition system of claim 1 , wherein the step of applying the set of rules to the set of responses to determine an output comprises the steps of: determining if a set of responses matches at least one rule, wherein a set of responses matches a rule if each response token identifier and associated response probability of recognition of the set of responses are all found among the predicates of the rule and the rule probabilities of recognition overlap the response probabilities of recognition for each of the response token identifiers; if a set of responses matches at least one rule, then determining the most-specific matched rule; and applying the most-specific matched rule to determine an output. | 0.5 |
5. A computer-implemented method, comprising: under the control of one or more computer systems configured with executable instructions, acquiring, using a first camera of a computing device, at least one first image; acquiring, using a second camera of the computing device, information corresponding to an environment of the computing device, wherein the second camera faces a different direction than the first camera; determine one or more conditions of the environment using the information acquired by the second camera of the computing device; determining at least one parameter associated with the one or more conditions; performing at least one preprocessing operation associated with the at least one first image, wherein the at least one preprocessing operation includes binarizing at least a portion of each of the at least one first image based upon the one or more conditions; and causing the at least one first image to be processed using an optical character recognition (OCR) engine in electronic communication with at least one of the one or more computer systems, wherein (i) the at least one parameter is used when performing the preprocessing operation or (ii) the at least one parameter is used by the OCR engine. | 5. A computer-implemented method, comprising: under the control of one or more computer systems configured with executable instructions, acquiring, using a first camera of a computing device, at least one first image; acquiring, using a second camera of the computing device, information corresponding to an environment of the computing device, wherein the second camera faces a different direction than the first camera; determine one or more conditions of the environment using the information acquired by the second camera of the computing device; determining at least one parameter associated with the one or more conditions; performing at least one preprocessing operation associated with the at least one first image, wherein the at least one preprocessing operation includes binarizing at least a portion of each of the at least one first image based upon the one or more conditions; and causing the at least one first image to be processed using an optical character recognition (OCR) engine in electronic communication with at least one of the one or more computer systems, wherein (i) the at least one parameter is used when performing the preprocessing operation or (ii) the at least one parameter is used by the OCR engine. 11. The computer-implemented method of claim 5 , wherein the information corresponding to the environment captured by the second camera is a representation of a face and the at least one parameter indicates a facial expression. | 0.635828 |
8. A system comprising: one or more devices to: provide a user interface to a client device, the user interface including: a first field to receive a first search term that is to be included in documents included within a set of search results, and a plurality of: a second field to receive a second search term that is to be excluded from the documents within the set of search results, a third field to receive information regarding a web site or a domain to which the set of search results will be restricted, a fourth field to receive selection of information regarding a language to which the set of search results will be restricted; receive, from the client device, input including the first search term within the first field; receive, from the client device, inputs including a plurality of: input including the second search term within the second field, input including the information regarding the web site or the domain within the third field, or input including the information regarding the language selected via the fourth field; identify a set of documents; filter the set of documents to obtain a filtered set of documents, documents in the filtered set of documents including the first search term and: excluding the second search term when the input including the second search term is received, being associated with the web site or the domain when the input including the information regarding the web site or the domain is received, or containing text in the language when the input including the information regarding the language is received; and provide information identifying the documents in the filtered set of documents. | 8. A system comprising: one or more devices to: provide a user interface to a client device, the user interface including: a first field to receive a first search term that is to be included in documents included within a set of search results, and a plurality of: a second field to receive a second search term that is to be excluded from the documents within the set of search results, a third field to receive information regarding a web site or a domain to which the set of search results will be restricted, a fourth field to receive selection of information regarding a language to which the set of search results will be restricted; receive, from the client device, input including the first search term within the first field; receive, from the client device, inputs including a plurality of: input including the second search term within the second field, input including the information regarding the web site or the domain within the third field, or input including the information regarding the language selected via the fourth field; identify a set of documents; filter the set of documents to obtain a filtered set of documents, documents in the filtered set of documents including the first search term and: excluding the second search term when the input including the second search term is received, being associated with the web site or the domain when the input including the information regarding the web site or the domain is received, or containing text in the language when the input including the information regarding the language is received; and provide information identifying the documents in the filtered set of documents. 11. The system of claim 8 , where the user interface includes the first field, the third field, and at least one of the second field or the fourth field, and where, when receiving the inputs, the one or more devices are to: receive the input including the information regarding the web site or the domain within the third field and at least one of: the input including the second search term within the second field, or the input including the information regarding the language within the fourth field. | 0.552667 |
1. A computer-implemented method for translating a first social feed, the method comprising: receiving, with a processor, social feed data and a request from a first user for a translation, the social feed data configured to cause a client to display the first social feed in a first language; determining, with the processor, a social context for the translation, the social context including which relationships are associated with the social feed data using a social graph, wherein the social graph comprises relationships between the first user and at least one second user; receiving, with the processor, a user input from the first user specifying a particular relationship for which the social feed data should be translated; determining, with the processor, a relationship between the first user and the second user based at least in part on the social context for the translation and whether the relationship matches the particular relationship specified by the user input; determining, with the processor, a first portion of the first social feed for translation based at least in part on whether the relationship between the first user and the second user matches the particular relationship, the first portion including one or more portions of the social feed data associated with the second user; translating, with the processor, the social feed data that is associated with the first portion of the first social feed so that the translated social feed data causes the client to display the first portion translated into one or more second languages based at least in part on the request and the social context; and transmitting, with the processor, the translated social feed data to the client for the first user to view. | 1. A computer-implemented method for translating a first social feed, the method comprising: receiving, with a processor, social feed data and a request from a first user for a translation, the social feed data configured to cause a client to display the first social feed in a first language; determining, with the processor, a social context for the translation, the social context including which relationships are associated with the social feed data using a social graph, wherein the social graph comprises relationships between the first user and at least one second user; receiving, with the processor, a user input from the first user specifying a particular relationship for which the social feed data should be translated; determining, with the processor, a relationship between the first user and the second user based at least in part on the social context for the translation and whether the relationship matches the particular relationship specified by the user input; determining, with the processor, a first portion of the first social feed for translation based at least in part on whether the relationship between the first user and the second user matches the particular relationship, the first portion including one or more portions of the social feed data associated with the second user; translating, with the processor, the social feed data that is associated with the first portion of the first social feed so that the translated social feed data causes the client to display the first portion translated into one or more second languages based at least in part on the request and the social context; and transmitting, with the processor, the translated social feed data to the client for the first user to view. 2. The method of claim 1 , further comprising: identifying a second portion of the first social feed that is associated with a third user, the third user having a different relationship with the first user than the particular relationship; and excluding the second portion from translation based at least in part on the different relationship. | 0.656448 |
15. The computer program product of claim 13 , further comprising computer readable program code adapted to, when executed by a computer, cause the computer to assign a confidence weight to each indicator n-gram. | 15. The computer program product of claim 13 , further comprising computer readable program code adapted to, when executed by a computer, cause the computer to assign a confidence weight to each indicator n-gram. 16. The computer program product of claim 15 , wherein the computer readable program code adapted to, when executed by a computer, cause the computer to assign a confidence weight to each indicator n-gram comprises computer readable program code adapted to, when executed by a computer, cause the computer to assign to each indicator n-gram a confidence weight equal to p divided by a total number of appearances in the training corpus of instances of the particular n-gram represented by that particular indicator n-gram; where instances of the particular n-gram represented by that particular indicator n-gram appear p times in the training corpus in association with the single cognitive motivation orientation with which instances of the particular n-gram represented by that particular indicator n-gram are most frequently associated in the training corpus. | 0.91969 |
6. An alphanumeric registration method, comprising the steps of: generating first key data and second key data by manually manipulating a plurality of alphanumeric entry keys of a system using a push button telephone set with said alphanumeric entry keys collectively representing a plurality of alphanumeric symbols, said plurality of alphanumeric symbols being greater than said plurality of alphanumeric entry keys; temporarily storing said first key data in a first temporary memory, after entering said first key data as a first electrical signal through said alphanumeric entry keys; temporarily storing said second key data in a second temporary memory, after entering said second key data as a second electrical signal through said alphanumeric entry keys; temporarily storing in a third temporary memory alphanumeric information generated by performing an alphanumeric registration subroutine using said first key data and said second key data as variable electrical values, said alphanumeric information comprising one of said plurality of alphanumeric symbols; and registering said alphanumeric information temporarily stored in said third temporary memory into an alphanumeric registration memory area when a predetermined quantity of said alphanumeric information has been generated after repeating said steps of temporarily storing said first key data, said second key data and said alphanumeric information. | 6. An alphanumeric registration method, comprising the steps of: generating first key data and second key data by manually manipulating a plurality of alphanumeric entry keys of a system using a push button telephone set with said alphanumeric entry keys collectively representing a plurality of alphanumeric symbols, said plurality of alphanumeric symbols being greater than said plurality of alphanumeric entry keys; temporarily storing said first key data in a first temporary memory, after entering said first key data as a first electrical signal through said alphanumeric entry keys; temporarily storing said second key data in a second temporary memory, after entering said second key data as a second electrical signal through said alphanumeric entry keys; temporarily storing in a third temporary memory alphanumeric information generated by performing an alphanumeric registration subroutine using said first key data and said second key data as variable electrical values, said alphanumeric information comprising one of said plurality of alphanumeric symbols; and registering said alphanumeric information temporarily stored in said third temporary memory into an alphanumeric registration memory area when a predetermined quantity of said alphanumeric information has been generated after repeating said steps of temporarily storing said first key data, said second key data and said alphanumeric information. 8. The alphanumeric registration method as claimed in claim 6, wherein said first key data corresponds to group information designated in said alphanumeric registration subroutine, and said second key data corresponds to party information designated in said alphanumeric registration subroutine. | 0.632436 |
12. A foreign language learning method using a function of reading an input sentence in voice through a Text To Speech (TTS) engine, the foreign language learning method correcting pronunciation through sentence input, comprising the steps of: (a) receiving a first sentence from a user via a sentence input unit; (b) detecting, by a linked letter detection unit, at least one letter corresponding to at least one linking rule by searching letters that form the first sentence received via the sentence input unit; (c) removing, by a linked letter removal unit, the letter corresponding to the linking rule detected by the linked letter detection unit, and generating, by the linked letter removal unit, a second sentence by inserting a linking code into a part from which the letter has been removed; (d) generating, by a partial waveform generation unit, one or more partial waveforms using the TTS engine with respect to a portion from a start point of the second sentence generated by the linked letter removal unit before a part into which the linking code has been inserted, a portion from the part into which the linking code has been inserted before a part into which a subsequent linking code has been inserted, and a portion from the part into which the subsequent linking code has been inserted to an end point of the second sentence; (d) converting, by an input waveform generation unit, a voice corresponding to the first sentence received through the sentence input unit into an input waveform when the voice is received from a user; and (e) calculating, by a matching degree calculation unit, a matching degree by comparing the input waveform generated by the input waveform generation unit with the one or more partial waveforms generated by the partial waveform generation unit, and calculating, by the matching degree calculation unit, a partial matching degree of a part having a highest matching degree in each of the partial waveforms by detecting the part having the highest matching degree while moving from a beginning of the input waveform to an end thereof in an order in which the one or more partial waveforms are disposed, wherein: step (b) comprises the steps of: (b1) detecting, by a word detection unit, an identical word by determining whether or not a word including the letter corresponding to the linking rule is identical with a word previously stored in a data storage unit when the letter corresponding to the linking rule is detected by the linked letter detection unit; and (b2) inserting, by a word waveform insertion unit, a word waveform corresponding to the previously stored word into a part corresponding to the word detected by the word detection unit; the word waveform comprises one or more phonemic waveforms that corresponds to phonemes for respective letters that form the word; the linked letter removal unit removes a phonemic waveform of the part corresponding to the letter that belongs to the letters of the word corresponding to the word waveform and that has been removed by the linked letter removal unit; the partial waveform generation unit generates the one or more partial waveforms using the TTS engine with respect to a portion from the start point of the second sentence generated by the linked letter removal unit to a letter prior to the part into which the word waveform has been inserted, a portion from a letter posterior to the part into which the word waveform has been inserted to a letter prior to a part into which a subsequent word waveform has been inserted, and a portion from a letter posterior to the part into which the word waveform has been inserted to the end point of the second sentence; and the matching degree calculation unit calculates a matching degree by comparing the input waveform generated by the input waveform generation unit with one or more word waveforms generated by the linked letter removal unit and then calculating a word matching degree of a part having a highest matching degree in each of the word waveforms by detecting the part having the highest matching degree while moving from the beginning of the input waveform to the end thereof in the order in which the one or more word waveforms are disposed. | 12. A foreign language learning method using a function of reading an input sentence in voice through a Text To Speech (TTS) engine, the foreign language learning method correcting pronunciation through sentence input, comprising the steps of: (a) receiving a first sentence from a user via a sentence input unit; (b) detecting, by a linked letter detection unit, at least one letter corresponding to at least one linking rule by searching letters that form the first sentence received via the sentence input unit; (c) removing, by a linked letter removal unit, the letter corresponding to the linking rule detected by the linked letter detection unit, and generating, by the linked letter removal unit, a second sentence by inserting a linking code into a part from which the letter has been removed; (d) generating, by a partial waveform generation unit, one or more partial waveforms using the TTS engine with respect to a portion from a start point of the second sentence generated by the linked letter removal unit before a part into which the linking code has been inserted, a portion from the part into which the linking code has been inserted before a part into which a subsequent linking code has been inserted, and a portion from the part into which the subsequent linking code has been inserted to an end point of the second sentence; (d) converting, by an input waveform generation unit, a voice corresponding to the first sentence received through the sentence input unit into an input waveform when the voice is received from a user; and (e) calculating, by a matching degree calculation unit, a matching degree by comparing the input waveform generated by the input waveform generation unit with the one or more partial waveforms generated by the partial waveform generation unit, and calculating, by the matching degree calculation unit, a partial matching degree of a part having a highest matching degree in each of the partial waveforms by detecting the part having the highest matching degree while moving from a beginning of the input waveform to an end thereof in an order in which the one or more partial waveforms are disposed, wherein: step (b) comprises the steps of: (b1) detecting, by a word detection unit, an identical word by determining whether or not a word including the letter corresponding to the linking rule is identical with a word previously stored in a data storage unit when the letter corresponding to the linking rule is detected by the linked letter detection unit; and (b2) inserting, by a word waveform insertion unit, a word waveform corresponding to the previously stored word into a part corresponding to the word detected by the word detection unit; the word waveform comprises one or more phonemic waveforms that corresponds to phonemes for respective letters that form the word; the linked letter removal unit removes a phonemic waveform of the part corresponding to the letter that belongs to the letters of the word corresponding to the word waveform and that has been removed by the linked letter removal unit; the partial waveform generation unit generates the one or more partial waveforms using the TTS engine with respect to a portion from the start point of the second sentence generated by the linked letter removal unit to a letter prior to the part into which the word waveform has been inserted, a portion from a letter posterior to the part into which the word waveform has been inserted to a letter prior to a part into which a subsequent word waveform has been inserted, and a portion from a letter posterior to the part into which the word waveform has been inserted to the end point of the second sentence; and the matching degree calculation unit calculates a matching degree by comparing the input waveform generated by the input waveform generation unit with one or more word waveforms generated by the linked letter removal unit and then calculating a word matching degree of a part having a highest matching degree in each of the word waveforms by detecting the part having the highest matching degree while moving from the beginning of the input waveform to the end thereof in the order in which the one or more word waveforms are disposed. 14. The foreign language learning method of claim 12 , wherein the linked letter detection unit comprises: a first linking rule in which a letter corresponding to a middle consonant of three consonants is detected if the three consonants are consecutive in one word or two words; a second linking rule in which “p,” “t,” or “k” is detected if “p,” “t,” or “k” is placed behind “s”; a third linking rule in which a rearmost consonant of a front word and a foremost vowel of a rear word are detected if the two words are consecutive, the front word ends with a consonant and the rear word starts with a vowel; and a fourth linking rule in which “d” or “t” is detected if “d” or “t” is placed between vowels. | 0.526052 |
3. The method of claim 1 , wherein the space of possible classifiers is represented by a set of parameterized weights and basis functions, and the optimization procedure searches the parameterized weight space to identify the combined spam classifier for which the given penalty function is minimal on the labeled e-mail corpus. | 3. The method of claim 1 , wherein the space of possible classifiers is represented by a set of parameterized weights and basis functions, and the optimization procedure searches the parameterized weight space to identify the combined spam classifier for which the given penalty function is minimal on the labeled e-mail corpus. 5. The method of claim 3 , wherein the basis functions are individual output scores of the constituent spam classifiers. | 0.953819 |
7. The method of claim 1 , further comprising: mapping communications operations from the TTCN-3 format into the SystemVerilog format. | 7. The method of claim 1 , further comprising: mapping communications operations from the TTCN-3 format into the SystemVerilog format. 8. The method of claim 7 , wherein the communications operations include message-based and signature-based communication operations, and the communications operations are mapped into a mailbox system. | 0.866887 |
7. A computer implemented method of forensic data analysis, the method comprising: extracting, with a data extraction module, unknown raw data from a plurality of raw data sources; providing the extracted unknown raw data to an interpreter module; receiving, at the interpreter module, the extracted unknown raw data from the data extraction module; storing a plurality of search packs wherein the search packs are adapted to reference other search packs from different platforms; accessing, at the interpreter module, one or more of the search packs each having associated suspect data features; determining which one or more search packs to send the unknown raw data to wherein the determination is based on categories of data; automatically identifying, using the interpreter module, suspect data from among the extracted raw data by applying a hash function to the extracted raw data to generate an extracted data hash value, and comparing the extracted data hash value to find identical and similar suspect data features; and generating, using the interpreter module, a report indicating any matches between the extracted data and any similar suspect data features. | 7. A computer implemented method of forensic data analysis, the method comprising: extracting, with a data extraction module, unknown raw data from a plurality of raw data sources; providing the extracted unknown raw data to an interpreter module; receiving, at the interpreter module, the extracted unknown raw data from the data extraction module; storing a plurality of search packs wherein the search packs are adapted to reference other search packs from different platforms; accessing, at the interpreter module, one or more of the search packs each having associated suspect data features; determining which one or more search packs to send the unknown raw data to wherein the determination is based on categories of data; automatically identifying, using the interpreter module, suspect data from among the extracted raw data by applying a hash function to the extracted raw data to generate an extracted data hash value, and comparing the extracted data hash value to find identical and similar suspect data features; and generating, using the interpreter module, a report indicating any matches between the extracted data and any similar suspect data features. 8. The method of claim 7 , further comprising storing, using the interpreter module, the report onto a portable memory device. | 0.623061 |
8. A computer-implemented method for determining relevance, and for semantic search and personalized advertising based on association, comprising: receiving a first text content, wherein the first text content comprises one or more terms each comprising a word or a phrase; identifying a first term in the first text content, wherein the first term represents a topic or category name, wherein the topic or category name includes the name of a concept or object, or a product or service or activity or event; receiving a dataset based on the topic or category name, wherein the dataset comprises a plurality of property names representing a plurality of properties associated with the topic or category name, wherein there are at least two property names in the dataset each having an association strength value, wherein the plurality of property names are divided into a first group and a second group based on whether the association strength value is above or below a pre-defined threshold; receiving a second text content, wherein the second text content comprises one or more terms each comprising a word or a phrase; and determining a relevance measure between the first text content and the second text content based on whether the second term matches a property name in the first group or in the second group. | 8. A computer-implemented method for determining relevance, and for semantic search and personalized advertising based on association, comprising: receiving a first text content, wherein the first text content comprises one or more terms each comprising a word or a phrase; identifying a first term in the first text content, wherein the first term represents a topic or category name, wherein the topic or category name includes the name of a concept or object, or a product or service or activity or event; receiving a dataset based on the topic or category name, wherein the dataset comprises a plurality of property names representing a plurality of properties associated with the topic or category name, wherein there are at least two property names in the dataset each having an association strength value, wherein the plurality of property names are divided into a first group and a second group based on whether the association strength value is above or below a pre-defined threshold; receiving a second text content, wherein the second text content comprises one or more terms each comprising a word or a phrase; and determining a relevance measure between the first text content and the second text content based on whether the second term matches a property name in the first group or in the second group. 13. The method of claim 8 , wherein the matched property name in the dataset has an association strength value representing the strength of the association between the property name and the topic or category name, the method further comprising: determining the relevance measure further based on the association strength value. | 0.709229 |
6. The method of claim 1 , comprising providing the modeled component to a runtime application. | 6. The method of claim 1 , comprising providing the modeled component to a runtime application. 7. The method of claim 6 , wherein the runtime application is for delivering rich web content. | 0.950105 |
19. A processor readable non-transitive storage media that includes data and instructions, wherein the execution of the instructions enables actions for printing a document at a printing device, comprising: receiving the document at a networked device, wherein the document includes text and identifies at least one target font reference for each character; determining if a name of the target font reference is listed in a font strategy table, then employing at least one of a corresponding logic component, substitute font data, and character data to provide substitute font information and width for each character to the printing device; determining if the name of the target font reference is unlisted in the font strategy table, then updating the font strategy table to include the name of the unlisted target font reference, wherein each updated target font reference corresponds to at least one logic component, substitute font data or character data; generating a first character table for the target font reference that includes at least a glyph index and a unicode; generating a second character table for the target font reference that includes at least a width and a glyph name; and enabling the printing device to employ provided font information and width for each character to print text included in the document. | 19. A processor readable non-transitive storage media that includes data and instructions, wherein the execution of the instructions enables actions for printing a document at a printing device, comprising: receiving the document at a networked device, wherein the document includes text and identifies at least one target font reference for each character; determining if a name of the target font reference is listed in a font strategy table, then employing at least one of a corresponding logic component, substitute font data, and character data to provide substitute font information and width for each character to the printing device; determining if the name of the target font reference is unlisted in the font strategy table, then updating the font strategy table to include the name of the unlisted target font reference, wherein each updated target font reference corresponds to at least one logic component, substitute font data or character data; generating a first character table for the target font reference that includes at least a glyph index and a unicode; generating a second character table for the target font reference that includes at least a width and a glyph name; and enabling the printing device to employ provided font information and width for each character to print text included in the document. 20. The media of claim 19 , wherein the actions further comprise determining if the name of the target font reference is non-listed in the font strategy table and target font information is available in a runtime environment for the networked device, then providing the target font information and width for each character to the printing device. | 0.620462 |
13. One or more non-transitory computer readable storage media embodying logic that is operable when executed by one or more processors to: retrieve one or more data elements from a data source; identify a structured data element among the one or more data elements; parse the structured data element using one or more filter processes to produce a plurality of tokens; classify the plurality of tokens based at least in part on one or more classification rules and an ontology, the ontology comprising a plurality of concepts and a plurality of relationships between the concepts; identify a conflict between a first classified token and a second classified token; resolve the conflict by evaluating the first and second classified tokens based at least in part on the ontology; and generate a knowledge assertion comprising the plurality of classified tokens and one or more relationships between the classified tokens. | 13. One or more non-transitory computer readable storage media embodying logic that is operable when executed by one or more processors to: retrieve one or more data elements from a data source; identify a structured data element among the one or more data elements; parse the structured data element using one or more filter processes to produce a plurality of tokens; classify the plurality of tokens based at least in part on one or more classification rules and an ontology, the ontology comprising a plurality of concepts and a plurality of relationships between the concepts; identify a conflict between a first classified token and a second classified token; resolve the conflict by evaluating the first and second classified tokens based at least in part on the ontology; and generate a knowledge assertion comprising the plurality of classified tokens and one or more relationships between the classified tokens. 14. The storage media of claim 13 , wherein: the ontology further comprises concept statistics associated with the plurality of concepts; and the logic is further operable when executed to resolve the conflict by evaluating the first and second classified tokens based at least in part on the concept statistics. | 0.569088 |
1. A method for message translation for multiple social media systems, comprising the steps of: a. receiving at a Messaging Translation Service Application Server (MTS AS) a message written in a first language; b. requesting and obtaining from multiple Social Media servers (SM servers) information related to a language used by each one of the SM servers; c. requesting translation of the message from the first language into the language or languages used by the SM servers; and d. sending a translation of the message in the language used by each one of the SM servers to the respective one of the multiple SM server. | 1. A method for message translation for multiple social media systems, comprising the steps of: a. receiving at a Messaging Translation Service Application Server (MTS AS) a message written in a first language; b. requesting and obtaining from multiple Social Media servers (SM servers) information related to a language used by each one of the SM servers; c. requesting translation of the message from the first language into the language or languages used by the SM servers; and d. sending a translation of the message in the language used by each one of the SM servers to the respective one of the multiple SM server. 3. The method of claim 1 , wherein the MTS AS is included in an SM server that receives the message written in the first language. | 0.760046 |
1. A computer-implemented method of constructing a search query in an electronic commerce environment, the method comprising: receiving, over a communications network, a search query from a user through a user interface of a user computing device; identifying a plurality of search terms within the search query, each of the plurality of search terms including at least a portion of the search query; executing the search query to generate search results including a list of merchandise items relevant to the search query; sending instructions to the user computing device to provide a graphical indication to the user in the user interface, neighboring the search query, graphically identifying one of the plurality of search terms from among the plurality of search terms; receiving, over the communication network, an indication of a selection, by the user, of a search term from among the plurality of search terms; generating, based at least in part on the search term, one or more alternative search terms that are each different from the search term; sending, over the communication network, instructions to the user computing device indicating the one or more alternative search terms to the user computing device; generating a plurality of search category selectors based, at least in part, on the search query, each of the plurality of search category selectors being categorically representative, at least in part, of one or more properties of a merchandise item and representing a list of one or more additional search terms in a different category of search terms, search terms in each list of one or more additional search terms being distinct from the search category selector representing the list, at least one of the plurality of search category selectors being inactive; and sending instructions to the user computing device to simultaneously display the plurality of search category selectors to the user in the user interface, and upon receipt of a selection of one of the plurality of search category selectors, sending instructions to the user computing device to display, to the user in the user interface, one or more additional search terms represented by the one of the one or more search category selectors with the plurality of search category selectors and with images representing the merchandise items in the list of merchandise items, wherein at least one of the plurality of search category selectors displayed in the user interface is inactive. | 1. A computer-implemented method of constructing a search query in an electronic commerce environment, the method comprising: receiving, over a communications network, a search query from a user through a user interface of a user computing device; identifying a plurality of search terms within the search query, each of the plurality of search terms including at least a portion of the search query; executing the search query to generate search results including a list of merchandise items relevant to the search query; sending instructions to the user computing device to provide a graphical indication to the user in the user interface, neighboring the search query, graphically identifying one of the plurality of search terms from among the plurality of search terms; receiving, over the communication network, an indication of a selection, by the user, of a search term from among the plurality of search terms; generating, based at least in part on the search term, one or more alternative search terms that are each different from the search term; sending, over the communication network, instructions to the user computing device indicating the one or more alternative search terms to the user computing device; generating a plurality of search category selectors based, at least in part, on the search query, each of the plurality of search category selectors being categorically representative, at least in part, of one or more properties of a merchandise item and representing a list of one or more additional search terms in a different category of search terms, search terms in each list of one or more additional search terms being distinct from the search category selector representing the list, at least one of the plurality of search category selectors being inactive; and sending instructions to the user computing device to simultaneously display the plurality of search category selectors to the user in the user interface, and upon receipt of a selection of one of the plurality of search category selectors, sending instructions to the user computing device to display, to the user in the user interface, one or more additional search terms represented by the one of the one or more search category selectors with the plurality of search category selectors and with images representing the merchandise items in the list of merchandise items, wherein at least one of the plurality of search category selectors displayed in the user interface is inactive. 7. The computer-implemented method of claim 1 , further comprising modifying the search query by adding at least one of the one or more alternative search terms to the search query in response to one or more alternative search terms being received from the user computing device from a single action of a user via the user interface. | 0.56281 |
2. An artificial intelligence system in accordance with claim 1 wherein: (a) the means for matching also determines if no match exists between the statements and any of the patterns of the sets of patterns stored at the node associated with the current concept; (b) the means for storing also stores from the node associated with the current concept additional information to be outputted by the output means as an inquiry for additional statements to be inputted by the input means; and (c) the control means causes the outputting of the additional information when no match is determined. | 2. An artificial intelligence system in accordance with claim 1 wherein: (a) the means for matching also determines if no match exists between the statements and any of the patterns of the sets of patterns stored at the node associated with the current concept; (b) the means for storing also stores from the node associated with the current concept additional information to be outputted by the output means as an inquiry for additional statements to be inputted by the input means; and (c) the control means causes the outputting of the additional information when no match is determined. 5. An artificial intelligence system in accordance with claim 2 wherein: (a) the statements are stored in the means for storing in the form of a list in the order of their input; and (b) the means for matching matches the list of statements with the sets of patterns in a last in first out order. | 0.895289 |
1. A server system comprising: one or more processors; and one or more computer-readable storage media storing computer-executable instructions that, when executed on the one or more processors, cause the one or more processors to perform acts comprising: storing, by the server system, annotation data from a first electronic book (eBook) reader device to a data store; determining that the annotation data is specific to a digital work; determining that an invariant location reference identifier is assigned to the annotation data, wherein the digital work is partitioned into a plurality of segments, a first segment has the invariant location reference identifier assigned thereto, such that the invariant location reference identifier is uniquely assigned with the first segment of the digital work, regardless of display conditions used to display the digital work; receiving a request from a second eBook reader device for the annotation data; synchronizing the annotation data stored in the data store with annotations stored on the second eBook reader device; determining that the second eBook reader device has presented a valid authorization credential for receiving the annotation data; and sending the second eBook reader device the annotation data. | 1. A server system comprising: one or more processors; and one or more computer-readable storage media storing computer-executable instructions that, when executed on the one or more processors, cause the one or more processors to perform acts comprising: storing, by the server system, annotation data from a first electronic book (eBook) reader device to a data store; determining that the annotation data is specific to a digital work; determining that an invariant location reference identifier is assigned to the annotation data, wherein the digital work is partitioned into a plurality of segments, a first segment has the invariant location reference identifier assigned thereto, such that the invariant location reference identifier is uniquely assigned with the first segment of the digital work, regardless of display conditions used to display the digital work; receiving a request from a second eBook reader device for the annotation data; synchronizing the annotation data stored in the data store with annotations stored on the second eBook reader device; determining that the second eBook reader device has presented a valid authorization credential for receiving the annotation data; and sending the second eBook reader device the annotation data. 4. The server system of claim 1 , the acts further comprising synchronizing content stored on the first eBook reader device with the data store. | 0.553987 |
32. A computer program product having a computer readable medium with computer program logic recorded thereon for assigning a behavior to a selected object, said computer program product comprising: code for graphically displaying a control icon as a part of said selected object; code for capturing a developer dragging said control icon with a pointer from said selected object to a target object; code for graphically rendering an association indicator referencing an association between said selected object and said target object responsive to said developer dragging; code for assigning said behavior to said selected object; and code for autonomously generating a computer-readable code defining said assigned behavior. | 32. A computer program product having a computer readable medium with computer program logic recorded thereon for assigning a behavior to a selected object, said computer program product comprising: code for graphically displaying a control icon as a part of said selected object; code for capturing a developer dragging said control icon with a pointer from said selected object to a target object; code for graphically rendering an association indicator referencing an association between said selected object and said target object responsive to said developer dragging; code for assigning said behavior to said selected object; and code for autonomously generating a computer-readable code defining said assigned behavior. 34. The computer program product of claim 32 wherein said code for assigning includes: code for automatically selecting said behavior responsive to a set of parameters. | 0.569444 |
1. A method, comprising: searching for resources in response to a search query with a number of search terms; retrieving search term position information for each resource; generating with a computing device a proximity feature value based on the search term position information using an unordered cost function, wherein the unordered cost function does not require search terms to be in the same order as in the search query and wherein the unordered cost function is proportional to a number of different search terms in a chunk of the resource and inversely proportional to a length of the chunk and the number of search terms in the search query; and ranking the resources based on the proximity feature value. | 1. A method, comprising: searching for resources in response to a search query with a number of search terms; retrieving search term position information for each resource; generating with a computing device a proximity feature value based on the search term position information using an unordered cost function, wherein the unordered cost function does not require search terms to be in the same order as in the search query and wherein the unordered cost function is proportional to a number of different search terms in a chunk of the resource and inversely proportional to a length of the chunk and the number of search terms in the search query; and ranking the resources based on the proximity feature value. 6. The method of claim 1 , comprising ranking the resources based on the proximity feature value using a neural network algorithm. | 0.808965 |
10. One or more non-transitory computer-readable media storing instructions which, when executed on one or more computing devices, cause the one or more computing devices to perform a method comprising: obtaining information that indicates the play personality of the user; wherein the information indicates which play type, of a plurality of play types, satisfies the user's need for play; wherein the plurality of play types includes two or more of: Object, Pretend, Social, Rough and Tumble, Body, Exploratory, Celebratory, Competitive, Ritual, Narrative, Fantasy or Games/Gaming; determining that the user is using the computing device; and during execution of software that generates output displayed on the computing device while the user is using the device, adapting operation of the software based, at least in part, on the play personality of the user. | 10. One or more non-transitory computer-readable media storing instructions which, when executed on one or more computing devices, cause the one or more computing devices to perform a method comprising: obtaining information that indicates the play personality of the user; wherein the information indicates which play type, of a plurality of play types, satisfies the user's need for play; wherein the plurality of play types includes two or more of: Object, Pretend, Social, Rough and Tumble, Body, Exploratory, Celebratory, Competitive, Ritual, Narrative, Fantasy or Games/Gaming; determining that the user is using the computing device; and during execution of software that generates output displayed on the computing device while the user is using the device, adapting operation of the software based, at least in part, on the play personality of the user. 17. The one or more non-transitory computer-readable media of claim 10 wherein adapting operation of the software comprises automatically selecting which quest, of a plurality of available quests, to present to an avatar of the user based on the play personality of the user. | 0.734114 |
9. A method, implemented by a computing device comprising a microphone, the method comprising: receiving, by a voice-controlled digital personal assistant, a digital voice input generated by a user, wherein the digital voice input is received via the microphone; performing natural language processing using the digital voice input to determine a user voice command, wherein the user voice command comprises a request to perform a pre-defined function of a third-party voice-enabled application, and wherein the pre-defined function is identified using a data structure that defines functions supported by available third-party voice-enabled applications using voice input, the third-party voice-enabled applications comprising pre-defined functions that are capable of being executed using user interfaces of the third-party voice-enabled applications and pre-defined functions that are capable of being headlessly executed without using the user interfaces of the third-party voice-enabled applications, and the data structure defining how the pre-defined function is capable of being executed by the digital personal assistant; in response to determining the user voice command comprising the request to perform the pre-defined function of the third-party application, using the data structure to select between headlessly executing the pre-defined function of the third-party voice-enabled application and executing the pre-defined function using the user interface of the third-party voice-enabled application; causing the third-party voice-enabled application to execute the pre-defined function as a background process without a user interface of the third-party voice-enabled application appearing on a display of the computing device; receiving a response from the third-party voice-enabled application indicating a state associated with the pre-defined function; and providing, by a user interface of the voice-controlled digital personal assistant, a response to the user based on the received state associated with the pre-defined function so that the response comes from within a context of the user interface of the voice-controlled digital personal assistant without surfacing the user interface of the third-party voice-enabled application. | 9. A method, implemented by a computing device comprising a microphone, the method comprising: receiving, by a voice-controlled digital personal assistant, a digital voice input generated by a user, wherein the digital voice input is received via the microphone; performing natural language processing using the digital voice input to determine a user voice command, wherein the user voice command comprises a request to perform a pre-defined function of a third-party voice-enabled application, and wherein the pre-defined function is identified using a data structure that defines functions supported by available third-party voice-enabled applications using voice input, the third-party voice-enabled applications comprising pre-defined functions that are capable of being executed using user interfaces of the third-party voice-enabled applications and pre-defined functions that are capable of being headlessly executed without using the user interfaces of the third-party voice-enabled applications, and the data structure defining how the pre-defined function is capable of being executed by the digital personal assistant; in response to determining the user voice command comprising the request to perform the pre-defined function of the third-party application, using the data structure to select between headlessly executing the pre-defined function of the third-party voice-enabled application and executing the pre-defined function using the user interface of the third-party voice-enabled application; causing the third-party voice-enabled application to execute the pre-defined function as a background process without a user interface of the third-party voice-enabled application appearing on a display of the computing device; receiving a response from the third-party voice-enabled application indicating a state associated with the pre-defined function; and providing, by a user interface of the voice-controlled digital personal assistant, a response to the user based on the received state associated with the pre-defined function so that the response comes from within a context of the user interface of the voice-controlled digital personal assistant without surfacing the user interface of the third-party voice-enabled application. 17. The method according to claim 9 , wherein performing natural language processing using the digital voice input to determine a user voice command comprises resolving contextual information so that the user voice command is context-free. | 0.52056 |
1. A method implemented by one or more computing devices, the method comprising: sampling first click-through data from a repository, the first click-through data identifying queries submitted by users to a search engine and specific result items that the users clicked from search results provided by the search engine in response to the queries; sampling structured knowledge data from one or more structured knowledge resources, the structured knowledge data providing semantic distances between various nouns identified in the one or more structured knowledge resources; processing the structured knowledge data to obtain second click-through the data second click-through data representing respective semantic distances between semantically related nouns as corresponding click values; and training a model using the first click-through data and the second click-through data as training data, the model being trained using a machine-learning training process, wherein the model is configured to process input linguistic items and identify output linguistic items that are related to the input linguistic items. | 1. A method implemented by one or more computing devices, the method comprising: sampling first click-through data from a repository, the first click-through data identifying queries submitted by users to a search engine and specific result items that the users clicked from search results provided by the search engine in response to the queries; sampling structured knowledge data from one or more structured knowledge resources, the structured knowledge data providing semantic distances between various nouns identified in the one or more structured knowledge resources; processing the structured knowledge data to obtain second click-through the data second click-through data representing respective semantic distances between semantically related nouns as corresponding click values; and training a model using the first click-through data and the second click-through data as training data, the model being trained using a machine-learning training process, wherein the model is configured to process input linguistic items and identify output linguistic items that are related to the input linguistic items. 3. The method of claim 1 , wherein each instance of the structured knowledge data comprises at least one frequency measure associated with a pair of semantically related nouns. | 0.543722 |
4. The method of claim 3 , further comprising encountering the subexpression when evaluating the at least one of the subqueries. | 4. The method of claim 3 , further comprising encountering the subexpression when evaluating the at least one of the subqueries. 5. The method of claim 4 , further comprising inquiring the director where to execute the subexpression. | 0.951321 |
2. The computer-implemented method of claim 1 , wherein the extended information further comprises the number of narrow screen glyphs necessary to display the string on a display screen. | 2. The computer-implemented method of claim 1 , wherein the extended information further comprises the number of narrow screen glyphs necessary to display the string on a display screen. 3. The computer-implemented method of claim 2 , wherein the method for retrieving the extended information from the HII database comprises a get extended string information method for retrieving the length of the string in Unicode characters and the number of narrow screen glyphs necessary to display the string on a display screen. | 0.884766 |
17. The method of claim 1 , wherein said displaying the interactive quality indicator further comprises displaying an icon. | 17. The method of claim 1 , wherein said displaying the interactive quality indicator further comprises displaying an icon. 18. The method of claim 17 , wherein the icon is displayed substantially apart from the document. | 0.967702 |
7. A non-transitory computer-readable storage medium storing computer usable program code for enhancing a media file to enable speech-recognition of spoken navigation commands, comprising: computer usable program code for receiving a plurality of textual items relating to the subject matter of the media file; computer usable program code for generating at least one grammar one or more grammar entries, wherein the one or more grammar entries comprise grammar entries that are generated for at least some of the plurality of the textual items and comprise a word or word sequence recognizable by a speech recognition engine; computer usable program code for, for each of the grammar entries corresponding to content in the media file, determining one or more time stamps for the grammar entry, each time stamp indicating a location in the media file of content corresponding to the grammar entry; and computer usable program code for locating content in the media file during playback of the media file by (a) receiving speech input from a user, (b) recognizing the speech input using the speech recognition engine and the at least one grammar to produce a speech recognition result corresponding at least in part to a recognized grammar entry of the at least one grammar, and (c) identifying one or more locations in the media file by identifying the one or more time stamps determined for the recognized grammar entry and the current time position of the media file at playback when the user input is received, wherein upon identifying the location in the media file a media controller navigates to the time stamp identified and presents the media file to the user at the identified timestamp location. | 7. A non-transitory computer-readable storage medium storing computer usable program code for enhancing a media file to enable speech-recognition of spoken navigation commands, comprising: computer usable program code for receiving a plurality of textual items relating to the subject matter of the media file; computer usable program code for generating at least one grammar one or more grammar entries, wherein the one or more grammar entries comprise grammar entries that are generated for at least some of the plurality of the textual items and comprise a word or word sequence recognizable by a speech recognition engine; computer usable program code for, for each of the grammar entries corresponding to content in the media file, determining one or more time stamps for the grammar entry, each time stamp indicating a location in the media file of content corresponding to the grammar entry; and computer usable program code for locating content in the media file during playback of the media file by (a) receiving speech input from a user, (b) recognizing the speech input using the speech recognition engine and the at least one grammar to produce a speech recognition result corresponding at least in part to a recognized grammar entry of the at least one grammar, and (c) identifying one or more locations in the media file by identifying the one or more time stamps determined for the recognized grammar entry and the current time position of the media file at playback when the user input is received, wherein upon identifying the location in the media file a media controller navigates to the time stamp identified and presents the media file to the user at the identified timestamp location. 9. The non-transitory computer-readable storage medium of claim 7 , wherein the computer usable program code for receiving a plurality of textual items further comprises: computer usable program code for receiving textual data provided by a user via a user input device and generating a plurality of textual items based on the textual data. | 0.511692 |
62. The non-transitory computer-readable medium of claim 50 , wherein the first question instance further comprises a first question definition, and wherein the instructions to automatically generate a first answer comprises instructions to process the first question definition to automatically generate the first answer. | 62. The non-transitory computer-readable medium of claim 50 , wherein the first question instance further comprises a first question definition, and wherein the instructions to automatically generate a first answer comprises instructions to process the first question definition to automatically generate the first answer. 63. The non-transitory computer-readable medium of claim 62 , wherein the instructions to automatically generate a first answer comprises instructions to apply the first question definition as a query to the data set to select a subset of the data set as the first answer. | 0.890703 |
1. A method for performance analysis of a database, comprising: receiving, at a processor, a proposed data model; generating a hypothetical query workload, the generating comprising using a plurality of sample query templates representing different query constructs for the proposed data model, identifying fact tables and dimension tables using foreign key constraints between tables in the proposed data model, substituting join predicates based on the foreign key constraints, randomly selecting dimension properties and fact measures from table definitions, randomly selecting local predicates from the dimension tables for slice and filter conditions, and randomly substituting literal values based on a data-type of an associated dimension column; generating hypothetical optimizer statistics using predefined generating rules that include a projected cardinality for the proposed data model; creating a sample unpopulated database and database schema using the proposed data model; applying, by the processor, the hypothetical optimizer statistics to the sample unpopulated database; based on generating the hypothetical optimizer statistics, applying, by the processor, each query construct of the hypothetical query workload to the database schema; and estimating, by the processor, a cost of the hypothetical query workload for the proposed data model. | 1. A method for performance analysis of a database, comprising: receiving, at a processor, a proposed data model; generating a hypothetical query workload, the generating comprising using a plurality of sample query templates representing different query constructs for the proposed data model, identifying fact tables and dimension tables using foreign key constraints between tables in the proposed data model, substituting join predicates based on the foreign key constraints, randomly selecting dimension properties and fact measures from table definitions, randomly selecting local predicates from the dimension tables for slice and filter conditions, and randomly substituting literal values based on a data-type of an associated dimension column; generating hypothetical optimizer statistics using predefined generating rules that include a projected cardinality for the proposed data model; creating a sample unpopulated database and database schema using the proposed data model; applying, by the processor, the hypothetical optimizer statistics to the sample unpopulated database; based on generating the hypothetical optimizer statistics, applying, by the processor, each query construct of the hypothetical query workload to the database schema; and estimating, by the processor, a cost of the hypothetical query workload for the proposed data model. 5. A method as claimed in claim 1 , wherein generating hypothetical optimizer statistics and applying these to the sample unpopulated database, further comprises: applying calculated table, column and index cardinalities by updating relevant optimizer statistics values in the database catalog. | 0.575875 |
5. An apparatus comprising: a local computing system; a remote computing system having a message server to service messages formulated according to a messaging protocol; a network interface to provide a connection with the remote computing system; and a processor and logic executable thereon to request access to the remote computing system from the local computing system; query the message server of the remote computing system from the local computing system to identify and obtain a Graphical User interface (GUI) with which to access the remote computing system, wherein to query the message server is to send a message to the message server of the remote computing system, the message including a location indicator to specify a location of a client cache server with which the local computing system has a fast connection, and from which the local computer system can download the identified GUI using the fast connection; receive connection information from the message server of the remote computing system, responsive to requesting access, the received connection information to identify and instruct how to obtain the GUI with which to access the remote computing system, wherein to receive connection information is to receive an automatically generated message from the remote computing system, the automatically generated message containing the message that was sent to the message server of the remote computing system, the automatically generated message being overwritten with the connection information, the connection information including a GUI version identifier to specify a version of the identified GUI; forward the received connection information from the local computing system to a client cache server with which the local computing system has a fast connection, based, at least in part, on the received connection information to identify and instruct how to obtain the GUI, wherein to forward the received connection information is to send the automatically generated message containing the connection information including the GUI version indicator to the client cache server using the location indicator specifying the location of the client cache server, the client cache server having a code base for generating a file describing the identified GUI based, at least in part, on the automatically generated message; receive a Java Network Launching Protocol (JNLP) file describing the identified GUI corresponding to the GUI version indicator from the client cache server, wherein the code base for generating the file generates the JNLP file; download the GUI to the local computing system from the client cache server using the fast connection, the download based, at least in part, on the received connection information to identify and instruct how to obtain the GUI; and access the remote computing system via the identified GUI. | 5. An apparatus comprising: a local computing system; a remote computing system having a message server to service messages formulated according to a messaging protocol; a network interface to provide a connection with the remote computing system; and a processor and logic executable thereon to request access to the remote computing system from the local computing system; query the message server of the remote computing system from the local computing system to identify and obtain a Graphical User interface (GUI) with which to access the remote computing system, wherein to query the message server is to send a message to the message server of the remote computing system, the message including a location indicator to specify a location of a client cache server with which the local computing system has a fast connection, and from which the local computer system can download the identified GUI using the fast connection; receive connection information from the message server of the remote computing system, responsive to requesting access, the received connection information to identify and instruct how to obtain the GUI with which to access the remote computing system, wherein to receive connection information is to receive an automatically generated message from the remote computing system, the automatically generated message containing the message that was sent to the message server of the remote computing system, the automatically generated message being overwritten with the connection information, the connection information including a GUI version identifier to specify a version of the identified GUI; forward the received connection information from the local computing system to a client cache server with which the local computing system has a fast connection, based, at least in part, on the received connection information to identify and instruct how to obtain the GUI, wherein to forward the received connection information is to send the automatically generated message containing the connection information including the GUI version indicator to the client cache server using the location indicator specifying the location of the client cache server, the client cache server having a code base for generating a file describing the identified GUI based, at least in part, on the automatically generated message; receive a Java Network Launching Protocol (JNLP) file describing the identified GUI corresponding to the GUI version indicator from the client cache server, wherein the code base for generating the file generates the JNLP file; download the GUI to the local computing system from the client cache server using the fast connection, the download based, at least in part, on the received connection information to identify and instruct how to obtain the GUI; and access the remote computing system via the identified GUI. 6. The apparatus of claim 5 , wherein the logic executable thereon further comprises logic to: receive input selecting a hyperlink displayed in a browser of the local computer system, the hyperlink representing access to the remote computing system. | 0.664299 |
11. The method of claim 1 , wherein the amplitude of at least one kernel model is based on one or more attributes of the landmark associated with the kernel model. | 11. The method of claim 1 , wherein the amplitude of at least one kernel model is based on one or more attributes of the landmark associated with the kernel model. 14. The method of claim 11 , wherein the amplitude of the kernel model is based on reviews associated with the associated landmark. | 0.941074 |
1. A system comprising: a processor; an objective occurrence data acquisition module configured to acquire objective occurrence data, the objective occurrence data to be acquired including data indicating occurrence of at least one objective occurrence; a subjective user state data solicitation module configured to solicit subjective user state data including data indicating occurrence of at least one subjective user state associated with a user in response to the acquisition of the objective occurrence data; a subjective user state data acquisition module configured to acquire the subjective user state data; and a correlation module configured to correlate the objective occurrence data with the subjective user state data, wherein said correlation module configured to correlate the objective occurrence data with the subjective user state data comprises: a sequential pattern determination module configured to determine at least one sequential pattern associated with occurrence of the at least one subjective user state and occurrence of the at least one objective occurrence. | 1. A system comprising: a processor; an objective occurrence data acquisition module configured to acquire objective occurrence data, the objective occurrence data to be acquired including data indicating occurrence of at least one objective occurrence; a subjective user state data solicitation module configured to solicit subjective user state data including data indicating occurrence of at least one subjective user state associated with a user in response to the acquisition of the objective occurrence data; a subjective user state data acquisition module configured to acquire the subjective user state data; and a correlation module configured to correlate the objective occurrence data with the subjective user state data, wherein said correlation module configured to correlate the objective occurrence data with the subjective user state data comprises: a sequential pattern determination module configured to determine at least one sequential pattern associated with occurrence of the at least one subjective user state and occurrence of the at least one objective occurrence. 24. The system of claim 1 , wherein said subjective user state data solicitation module configured to solicit subjective user state data including data indicating occurrence of at least one subjective user state associated with a user in response to the acquisition of the objective occurrence data comprises: a subjective user state data solicitation module configured to solicit data indicating occurrence of at least one subjective user state during a specified time interval. | 0.604774 |
10. An article comprising a machine-readable medium storing instructions adapted to cause one or more machines to perform operations comprising: receiving a plurality of proposed character assignments for at least one instance of a character in an image on which optical character recognition is being performed, each of the character assignments representing a character determined from a character set for the at least one instance of the character by the optical character recognition, the at least one instance of the character residing in one or more character strings of multiple characters, at least one of the character strings of multiple characters known to exclude a subset of at least one character from the character set based at least in part on the at least one character string of multiple characters' location in the image; and eliminating at least one of the proposed character assignments by comparing the at least one of the proposed character assignments to the subset of at least one character excluded from the at least one character string of multiple characters. | 10. An article comprising a machine-readable medium storing instructions adapted to cause one or more machines to perform operations comprising: receiving a plurality of proposed character assignments for at least one instance of a character in an image on which optical character recognition is being performed, each of the character assignments representing a character determined from a character set for the at least one instance of the character by the optical character recognition, the at least one instance of the character residing in one or more character strings of multiple characters, at least one of the character strings of multiple characters known to exclude a subset of at least one character from the character set based at least in part on the at least one character string of multiple characters' location in the image; and eliminating at least one of the proposed character assignments by comparing the at least one of the proposed character assignments to the subset of at least one character excluded from the at least one character string of multiple characters. 11. The article of claim 10 wherein the specified subset of characters comprises at least one of alpha characters, numeric characters, punctuation characters, or special characters. | 0.725065 |
1. At least one non-transitory computer readable medium encoded with instructions which, when loaded on a computer, establish processes for contact information handling, implemented by a document editing program running in the computer, the processes comprising: allowing a user to enter textual information into a document using the document editing program; displaying the textual information in the document electronically using the document editing program; allowing, in the document editing program, the user to select in the document at least a portion of the textual information while the textual information is displayed; following user selection of textual information in the document, analyzing, by the document editing program, the selected textual information to determine if the selected textual information is regarded by the document editing program as contact information and what type or types of contact information the selected textual information is; providing an input device configured by the document editing program to allow the user to initiate an operation, such operation being of a type depending at least in part on the type or types of contact information of the selected textual information, the operation comprising identifying at least part of the selected textual information to use as a search term in order to find second information, of a specific type or types, associated with the search term in an information source external to the document; after identifying at least part of the selected information to use as a search term, and in consequence of receipt by the document editing program of an execute command from the input device, performing the operation, wherein the operation further comprises: causing an electronic search in the information source, by an information management program external to the document editing program, for the search term in order to find whether the search term is included in the information source; and performing an action having a type, wherein the type of action depends at least in part on whether the search term is included in the information source, and if the search term is so included, and if the information source includes the second information, the action comprises causing insertion of at least part of the second information into the document. | 1. At least one non-transitory computer readable medium encoded with instructions which, when loaded on a computer, establish processes for contact information handling, implemented by a document editing program running in the computer, the processes comprising: allowing a user to enter textual information into a document using the document editing program; displaying the textual information in the document electronically using the document editing program; allowing, in the document editing program, the user to select in the document at least a portion of the textual information while the textual information is displayed; following user selection of textual information in the document, analyzing, by the document editing program, the selected textual information to determine if the selected textual information is regarded by the document editing program as contact information and what type or types of contact information the selected textual information is; providing an input device configured by the document editing program to allow the user to initiate an operation, such operation being of a type depending at least in part on the type or types of contact information of the selected textual information, the operation comprising identifying at least part of the selected textual information to use as a search term in order to find second information, of a specific type or types, associated with the search term in an information source external to the document; after identifying at least part of the selected information to use as a search term, and in consequence of receipt by the document editing program of an execute command from the input device, performing the operation, wherein the operation further comprises: causing an electronic search in the information source, by an information management program external to the document editing program, for the search term in order to find whether the search term is included in the information source; and performing an action having a type, wherein the type of action depends at least in part on whether the search term is included in the information source, and if the search term is so included, and if the information source includes the second information, the action comprises causing insertion of at least part of the second information into the document. 11. At least one non-transitory computer readable medium according to claim 1 , wherein the instructions establish processes wherein the type of operation includes updating the document with information from the information source. | 0.548434 |
16. The system of claim 15 , the method comprising: receiving user input in a character entry field; and presenting the at least two terms from the first group of terms based upon the received user input. | 16. The system of claim 15 , the method comprising: receiving user input in a character entry field; and presenting the at least two terms from the first group of terms based upon the received user input. 17. The system of claim 16 , the method comprising inserting the generated phrase into the character entry field. | 0.921118 |
1. A method for generating an assent indication in a document approval and review function for collaborative document editing, the method comprising: loading into a memory of a computer a document for editing in a document editor; determining, by the processor of the computer, a set of authors for the document; modifying a file name of the document by the processor of the computer, by appending an identity of each author in the determined set author to the file name of the document; and, responsive to one of the authors in the determined set of authors assenting to a publication of the document, changing a visual appearance in the modified file name of an identity of the assenting author by removing the identity of the assenting author from the modified file name of the document resulting in leaving the identity of each author in the determined set of authors that has yet to assent to the publication of the document in the modified file name of the document. | 1. A method for generating an assent indication in a document approval and review function for collaborative document editing, the method comprising: loading into a memory of a computer a document for editing in a document editor; determining, by the processor of the computer, a set of authors for the document; modifying a file name of the document by the processor of the computer, by appending an identity of each author in the determined set author to the file name of the document; and, responsive to one of the authors in the determined set of authors assenting to a publication of the document, changing a visual appearance in the modified file name of an identity of the assenting author by removing the identity of the assenting author from the modified file name of the document resulting in leaving the identity of each author in the determined set of authors that has yet to assent to the publication of the document in the modified file name of the document. 2. The method of claim 1 , wherein changing a visual appearance in the file name of an identity of the assenting author, comprises removing the identity of the assenting author from the file name. | 0.8186 |
1. A method for building a search query in a data processing system having a graphical user interface, comprising the computer-implemented steps of: responsive to user input, dropping a first graphical component representing a first system object onto a second graphical component representing a query function, wherein said first system object contains an attribute having a value for which a user wishes to create the search query; responsive to the dropping of the first graphical component onto the second graphical component, presenting a set of attributes currently associated with the first system object on the graphical user interface, wherein the first system object is a pre-existing object within the data processing system and wherein the set of attributes that are presented on the graphical user interface specifies actual properties associated with the pre-existing object; receiving a user selection of at least one attribute in the set of attributes to create a selected attribute set; responsive to the user input, creating the search query from the selected attribute set and from a corresponding value of the first system object for each attribute in the selected attribute set; and using the search query to assemble a set of system objects, wherein each system object of the set of system objects has a value that is a same value for each respective attribute of the first system object, wherein the at least one attribute of the set of attributes is a data processing subsystem attribute that is currently associated with the first system object that is represented by the first graphical component that is dropped onto the second graphical component. | 1. A method for building a search query in a data processing system having a graphical user interface, comprising the computer-implemented steps of: responsive to user input, dropping a first graphical component representing a first system object onto a second graphical component representing a query function, wherein said first system object contains an attribute having a value for which a user wishes to create the search query; responsive to the dropping of the first graphical component onto the second graphical component, presenting a set of attributes currently associated with the first system object on the graphical user interface, wherein the first system object is a pre-existing object within the data processing system and wherein the set of attributes that are presented on the graphical user interface specifies actual properties associated with the pre-existing object; receiving a user selection of at least one attribute in the set of attributes to create a selected attribute set; responsive to the user input, creating the search query from the selected attribute set and from a corresponding value of the first system object for each attribute in the selected attribute set; and using the search query to assemble a set of system objects, wherein each system object of the set of system objects has a value that is a same value for each respective attribute of the first system object, wherein the at least one attribute of the set of attributes is a data processing subsystem attribute that is currently associated with the first system object that is represented by the first graphical component that is dropped onto the second graphical component. 4. The method as recited in claim 1 , wherein the presenting step further presents an input for a user-supplied attribute that is not otherwise provided. | 0.538588 |
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