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25. The apparatus of claim 20 , wherein the graphical user interface provides a printing interface for a user to specify one or more parameters that constrain printing of the multimedia representation to a target. | 25. The apparatus of claim 20 , wherein the graphical user interface provides a printing interface for a user to specify one or more parameters that constrain printing of the multimedia representation to a target. 26. The apparatus of claim 25 , wherein the printing interface includes one or more of the following: a content selection section, an audio setting section, and an imported content section. | 0.97336 |
1. A method comprising: accessing a corpus of terms by a parser using a processor in each of a plurality of speech applications; parsing, using said parser and said processor, said corpus of terms in each speech application to produce a plurality of first output sets, in which expressions identified in the corpus are replaced with corresponding grammar tags from a grammar that is specific to the application, wherein said grammar tags are selected from among command grammar tags and collection grammar tags; accessing said plurality of first output sets by a class-relabeler and said processor; replacing by the class-relabeler and said processor, for each of the plurality of speech applications, each of the grammar tags in the plurality of first output sets with a class identifier of an application-generic class, to produce plurality of a second output sets; accessing said plurality of second output sets by a token selector and said processor; processing collectively, by said token selector and said processor, the plurality of second output sets or data derived from the output sets with a statistical language model (SLM) trainer; and generating, using said processor, an application-generic class-based SLM using a set of results from said SLM trainer. | 1. A method comprising: accessing a corpus of terms by a parser using a processor in each of a plurality of speech applications; parsing, using said parser and said processor, said corpus of terms in each speech application to produce a plurality of first output sets, in which expressions identified in the corpus are replaced with corresponding grammar tags from a grammar that is specific to the application, wherein said grammar tags are selected from among command grammar tags and collection grammar tags; accessing said plurality of first output sets by a class-relabeler and said processor; replacing by the class-relabeler and said processor, for each of the plurality of speech applications, each of the grammar tags in the plurality of first output sets with a class identifier of an application-generic class, to produce plurality of a second output sets; accessing said plurality of second output sets by a token selector and said processor; processing collectively, by said token selector and said processor, the plurality of second output sets or data derived from the output sets with a statistical language model (SLM) trainer; and generating, using said processor, an application-generic class-based SLM using a set of results from said SLM trainer. 5. A method as recited in claim 1 , wherein said parsing comprises: for each identified expression, identifying, using said processor, a type of grammar to which the expression corresponds; and selecting a grammar tag to replace the expression based on the identified type of grammar. | 0.669325 |
1. A computer system for providing real-time resources to participants in an audio conference session, the computer system comprising: a conference system for establishing an audio conference session between a plurality of computing devices connected via a communication network; and a server configured to communicate with the conference system and the plurality of computing devices via the communication network, the server comprising: a processor and a memory; a pre-processing engine stored in the memory and executed by the processor, the pre-processing engine comprising logic configured to: receive an audio stream associated with one or more of the computing devices, the audio stream comprising a speech signal; and extract the speech signal from the audio stream; a speech-to-text conversion engine stored in the memory and executed by the processor, the speech-to-text conversion engine comprising logic configured to extract words from the speech signal; a relevance engine stored in the memory and executed by the processor, the relevance engine comprising an algorithm for outputting a relevant keyword or topic being discussed in the audio conference session based on a plurality of data inputs, the plurality of data inputs comprising the extracted words from the speech-to-text conversion engine, a speaker identity with a corresponding role or category of one or more participants who spoke the extracted words, the algorithm identifying the relevant keyword or topic by calculating and updating a relevance score during the audio conference session and, if the relevance score exceeds a threshold, outputting the relevant keyword or topic, wherein the relevance score is based on a usage density associated with the one or more extracted words; and a resources engine stored in the memory and executed by the processor, the resources engine operatively coupled to the relevance engine and comprising logic configured to: receive from the relevance engine the relevant keyword or topic identified by the algorithm based on the speaker identity with the corresponding role or category; identify a plurality of resources related to the relevant keyword or topic; display in a graphical user interface and during the audio conference session, the plurality of resources to the one or more computing devices in a conference user interface associated with the audio conference session; and enable user-selection of one or more of the plurality of resources via the conference user interface. | 1. A computer system for providing real-time resources to participants in an audio conference session, the computer system comprising: a conference system for establishing an audio conference session between a plurality of computing devices connected via a communication network; and a server configured to communicate with the conference system and the plurality of computing devices via the communication network, the server comprising: a processor and a memory; a pre-processing engine stored in the memory and executed by the processor, the pre-processing engine comprising logic configured to: receive an audio stream associated with one or more of the computing devices, the audio stream comprising a speech signal; and extract the speech signal from the audio stream; a speech-to-text conversion engine stored in the memory and executed by the processor, the speech-to-text conversion engine comprising logic configured to extract words from the speech signal; a relevance engine stored in the memory and executed by the processor, the relevance engine comprising an algorithm for outputting a relevant keyword or topic being discussed in the audio conference session based on a plurality of data inputs, the plurality of data inputs comprising the extracted words from the speech-to-text conversion engine, a speaker identity with a corresponding role or category of one or more participants who spoke the extracted words, the algorithm identifying the relevant keyword or topic by calculating and updating a relevance score during the audio conference session and, if the relevance score exceeds a threshold, outputting the relevant keyword or topic, wherein the relevance score is based on a usage density associated with the one or more extracted words; and a resources engine stored in the memory and executed by the processor, the resources engine operatively coupled to the relevance engine and comprising logic configured to: receive from the relevance engine the relevant keyword or topic identified by the algorithm based on the speaker identity with the corresponding role or category; identify a plurality of resources related to the relevant keyword or topic; display in a graphical user interface and during the audio conference session, the plurality of resources to the one or more computing devices in a conference user interface associated with the audio conference session; and enable user-selection of one or more of the plurality of resources via the conference user interface. 3. The computer system of claim 1 , wherein the calculating and updating the relevance score comprises: identifying a current instance of the extracted word; generating a timestamp for the current instance of the extracted word; and updating the relevance score for the extracted word based on the timestamp. | 0.512783 |
3. The method of claim 1 , further comprising displaying the output on a screen. | 3. The method of claim 1 , further comprising displaying the output on a screen. 4. The method of claim 3 , wherein the generated exception object data record is temporarily removed by removing the generated exception object data record from the screen until the resubmission date is reached, at which time the generated exception object data record reappears on the screen. | 0.890648 |
2. The method of claim 1 wherein identifying the link color conversion CMR comprises: creating the rule for converting the input color space to the output color space; associating the first descriptor value and the second descriptor value with the rule for converting; and storing the rule for converting and the associated descriptor values in the link color conversion CMR. | 2. The method of claim 1 wherein identifying the link color conversion CMR comprises: creating the rule for converting the input color space to the output color space; associating the first descriptor value and the second descriptor value with the rule for converting; and storing the rule for converting and the associated descriptor values in the link color conversion CMR. 3. The method of claim 2 wherein creating the rule for converting comprises: identifying a first rule for converting the input color space to an intermediate format color space; identifying a second rule for converting the intermediate format color space to the output color space; and creating the rule for converting the input color space to the output color space by combining the first rule for converting and the second rule for converting. | 0.815855 |
1. A system that detects similarities between name strings in a document set, comprising: a processor and a memory, the memory comprising a preprocessing module, a matching module and a generation module; the preprocessing module configured to: extract a plurality of name strings from the document set by generating additional name strings based on an alternative spelling of one or more name strings in the document set, each name string comprising a similar entity with names that are misspelled, mistranslated, incorrectly transcribed, have multiple aliases, and/or have multiple equally valid spellings, the alternate spelling comprising determining typical misspellings, creating language specific lists of spelling corrections, and generating the alternative spelling based on the spelling corrections; the matching module configured to: detect possible matching pairs from the plurality of name strings, and detect a plurality of similarity scores to each of the possible matching pairs using a plurality of algorithms that execute in parallel; and the generation module configured to: generate a set of equivalent names by its relating name strings from the possible matching pairs based on a comparison between the similarity scores and a threshold. | 1. A system that detects similarities between name strings in a document set, comprising: a processor and a memory, the memory comprising a preprocessing module, a matching module and a generation module; the preprocessing module configured to: extract a plurality of name strings from the document set by generating additional name strings based on an alternative spelling of one or more name strings in the document set, each name string comprising a similar entity with names that are misspelled, mistranslated, incorrectly transcribed, have multiple aliases, and/or have multiple equally valid spellings, the alternate spelling comprising determining typical misspellings, creating language specific lists of spelling corrections, and generating the alternative spelling based on the spelling corrections; the matching module configured to: detect possible matching pairs from the plurality of name strings, and detect a plurality of similarity scores to each of the possible matching pairs using a plurality of algorithms that execute in parallel; and the generation module configured to: generate a set of equivalent names by its relating name strings from the possible matching pairs based on a comparison between the similarity scores and a threshold. 6. The system of claim 1 , wherein the memory further comprises a storage module configured to store a set of equivalent name strings in a database. | 0.559254 |
20. A non-transitory computer readable medium comprising computer executable instructions for retrieving items stored in memory, said computer readable medium comprising instructions for: obtaining zero or more characters as a search input; examining said search input and traversing a tree built from one or more items each having at least one integer associated therewith, each integer representing a component of a respective item and having been generated using a first value indicative of a location where said item can be found in a memory, a second value indicative of a bias level for said item, a third value indicative of an offset within said item where said component begins, and a fourth value indicative of a length of said component within said item to enable said component to be found; upon reaching a terminus in said tree according to said zero or more characters, returning all integers stored at one or more leaf nodes beneath said terminus in said tree; for each integer, determining from said integer, said first value indicative of said location and said second value indicative of said bias level, accessing said item in said memory at said location, determining said third and fourth values, finding said component in said item using said third value, extracting said component according to said fourth value, and returning said component and its bias level for a list of search results; sorting said list of search results using bias levels from said at least one integer; and providing said list of search results. | 20. A non-transitory computer readable medium comprising computer executable instructions for retrieving items stored in memory, said computer readable medium comprising instructions for: obtaining zero or more characters as a search input; examining said search input and traversing a tree built from one or more items each having at least one integer associated therewith, each integer representing a component of a respective item and having been generated using a first value indicative of a location where said item can be found in a memory, a second value indicative of a bias level for said item, a third value indicative of an offset within said item where said component begins, and a fourth value indicative of a length of said component within said item to enable said component to be found; upon reaching a terminus in said tree according to said zero or more characters, returning all integers stored at one or more leaf nodes beneath said terminus in said tree; for each integer, determining from said integer, said first value indicative of said location and said second value indicative of said bias level, accessing said item in said memory at said location, determining said third and fourth values, finding said component in said item using said third value, extracting said component according to said fourth value, and returning said component and its bias level for a list of search results; sorting said list of search results using bias levels from said at least one integer; and providing said list of search results. 22. The non-transitory computer readable medium according to claim 20 , further comprising instructions for highlighting said component in said item in said list of search results. | 0.50801 |
15. A machine readable device having stored thereon a set of instructions, which when executed, perform a method comprising: receiving an excerpt of information associated with the user from a first client computer including a first information handling system; in response to receipt of the excerpt, automatically translating the excerpt into an XML format to be compatible, without further translation, for operation with a second client computer including at least one second information handling system of the user; saving the translated excerpt in a first personal folder associated with the user of the first information handling system, the translated excerpt including a user-specified item of music, a website, a search query, and a search result; and synchronizing the translated excerpt with the second information handling system wherein a version of the translated excerpt is saved in a second personal folder associated with the user of the second information handling system and a third personal folder associated with the user of the server; and associating a name, a source, and a comment with the translated excerpt; and associating a name, a source, and a comment with the translated excerpt. | 15. A machine readable device having stored thereon a set of instructions, which when executed, perform a method comprising: receiving an excerpt of information associated with the user from a first client computer including a first information handling system; in response to receipt of the excerpt, automatically translating the excerpt into an XML format to be compatible, without further translation, for operation with a second client computer including at least one second information handling system of the user; saving the translated excerpt in a first personal folder associated with the user of the first information handling system, the translated excerpt including a user-specified item of music, a website, a search query, and a search result; and synchronizing the translated excerpt with the second information handling system wherein a version of the translated excerpt is saved in a second personal folder associated with the user of the second information handling system and a third personal folder associated with the user of the server; and associating a name, a source, and a comment with the translated excerpt; and associating a name, a source, and a comment with the translated excerpt. 16. The machine readable device of claim 15 , wherein the excerpt has a non-XML format, further comprising: In response to the receipt of the excerpt, automatically translating the excerpt from the non-XML format into the XML format to be compatible for operation with the second information handling system. | 0.552 |
1. An apparatus for creating an electronic version of machine printed matter, the apparatus including: a data reading means arranged to optically obtain image data which can be used to present an electronic image of the printed matter, the electronic image having substantially the same appearance as the printed matter, and a region containing machine printed information which cannot be readily discerned; an input means arranged to obtain and modify text-based information data entered by a user and representing the information contained in the region containing machine printed information which cannot be readily discerned when viewed by a viewer different and remote from the user in a manner that allows the information to be readily discerned; a creating means arranged to create a reference which can be used to retrieve the information data; and a processing means arranged to process the image data and the reference in order to create presentation data, wherein the presentation data can be used to present the electronic image, and to retrieve the information data so that it can be used to present the information contained in the region in a manner that is readily discernible by the viewer. | 1. An apparatus for creating an electronic version of machine printed matter, the apparatus including: a data reading means arranged to optically obtain image data which can be used to present an electronic image of the printed matter, the electronic image having substantially the same appearance as the printed matter, and a region containing machine printed information which cannot be readily discerned; an input means arranged to obtain and modify text-based information data entered by a user and representing the information contained in the region containing machine printed information which cannot be readily discerned when viewed by a viewer different and remote from the user in a manner that allows the information to be readily discerned; a creating means arranged to create a reference which can be used to retrieve the information data; and a processing means arranged to process the image data and the reference in order to create presentation data, wherein the presentation data can be used to present the electronic image, and to retrieve the information data so that it can be used to present the information contained in the region in a manner that is readily discernible by the viewer. 5. The apparatus of claim 1 , wherein the data reading means is capable of changing the image data in order to effect a change in a resolution of the electronic image. | 0.581753 |
1. A program media having stored computer program code that when executed by a computer causes a computer system to recognize a character-based user interface having a plurality of host component types and to transform the character-based user interface to a web enabled user interface, the medium having code to control the computer, the medium comprising: code for scanning the character-based user interface by a plurality of agents; code in each agent for determining the existence of a different host component type unique to the agent; code for defining a match region for each host component type found to exist by an agent in the character-based user interface; code for determining whether two or more match regions overlap; code for resolving a conflict between the two or more match regions that overlap; code for rendering match regions associated with each agent to compose the web enabled user interface and code for rendering each match region as a widget, the aggregated widgets composing a formatted output page. | 1. A program media having stored computer program code that when executed by a computer causes a computer system to recognize a character-based user interface having a plurality of host component types and to transform the character-based user interface to a web enabled user interface, the medium having code to control the computer, the medium comprising: code for scanning the character-based user interface by a plurality of agents; code in each agent for determining the existence of a different host component type unique to the agent; code for defining a match region for each host component type found to exist by an agent in the character-based user interface; code for determining whether two or more match regions overlap; code for resolving a conflict between the two or more match regions that overlap; code for rendering match regions associated with each agent to compose the web enabled user interface and code for rendering each match region as a widget, the aggregated widgets composing a formatted output page. 2. The program media of claim 1 wherein the resolving code is executed before the rendering code, and further comprises: code for resolving a conflict between two or more match regions which overlap based on a policy to determine which agent associated with a match region controls the overlap region. | 0.5 |
17. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: displaying a tabstrip widget including at least first and second tabs, each of the at least first and second tabs further including a tab conditions panel and a tab summary panel, the tab summary panel configured to display a first statistic associated with a term of a Boolean expression defined by the corresponding tab conditions panel, a first update element operable to, in response to user selection, update the first statistic, a second statistic associated with the entire Boolean expression, and a second update element operable to, in response to user selection, update the second statistic, and the tabstrip widget being configured to display one tab conditions panel of the at least first and second tabs at a time, receiving a first user input defining a first term of a Boolean expression including a first number of condition statements, displaying the first term of the Boolean expression in the tab conditions panel of the first tab, superimposing the tab conditions panel of the second tab on the tab conditions panel of the first tab, receiving a second user input defining a second term of the Boolean expression including a second number of condition statements, the second number of condition statements being different than the first number of condition statements, displaying the second term of the Boolean expression in the tab conditions panel of the second tab, in response to user selection of the first update element included in the tab summary panel of the second tab, updating the first statistic included in the tab summary panel of the second tab based on the second term of the Boolean expression including the second number of condition statements, in response to user selection of the second update element included in the tab summary panel of the second tab, updating the second statistic included in the tab summary panel of the second tab based on the entire Boolean expression defined by the first term of the Boolean expression including the first number of condition statements and the second term of the Boolean expression including the second number of condition statements, and outputting data satisfying the first and second terms of the Boolean expression. | 17. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: displaying a tabstrip widget including at least first and second tabs, each of the at least first and second tabs further including a tab conditions panel and a tab summary panel, the tab summary panel configured to display a first statistic associated with a term of a Boolean expression defined by the corresponding tab conditions panel, a first update element operable to, in response to user selection, update the first statistic, a second statistic associated with the entire Boolean expression, and a second update element operable to, in response to user selection, update the second statistic, and the tabstrip widget being configured to display one tab conditions panel of the at least first and second tabs at a time, receiving a first user input defining a first term of a Boolean expression including a first number of condition statements, displaying the first term of the Boolean expression in the tab conditions panel of the first tab, superimposing the tab conditions panel of the second tab on the tab conditions panel of the first tab, receiving a second user input defining a second term of the Boolean expression including a second number of condition statements, the second number of condition statements being different than the first number of condition statements, displaying the second term of the Boolean expression in the tab conditions panel of the second tab, in response to user selection of the first update element included in the tab summary panel of the second tab, updating the first statistic included in the tab summary panel of the second tab based on the second term of the Boolean expression including the second number of condition statements, in response to user selection of the second update element included in the tab summary panel of the second tab, updating the second statistic included in the tab summary panel of the second tab based on the entire Boolean expression defined by the first term of the Boolean expression including the first number of condition statements and the second term of the Boolean expression including the second number of condition statements, and outputting data satisfying the first and second terms of the Boolean expression. 19. The system of claim 17 , wherein the operations further comprise receiving user selection indicative of the second tab, wherein the tab conditions panel of the second tab is superimposed on the tab conditions panel of the first tab based upon receiving the user selection. | 0.568 |
1. A computer-implemented document-searching method for searching a document having a hierarchical structure with elements separated by element identifiers, comprising the steps of: generating an XPATH query automaton, wherein XPATH is an XML (Extensible Markup Language) path for searching an XML document; wherein the XPATH query automaton is a table that contains a plurality of states of backward nodes, a condition for transition, and a search state; wherein a collection of entries of the XPATH query automaton expresses a state transition; wherein the generating the XPATH query automaton comprises steps of: generating and registering the state transition, wherein the generating and registering the state transition comprises: replacing an XPATH axis including an XPATH axis in a forward direction that is exemplified as an axis child, or a descendant in an XPATH into the state transition, replacing an XPATH axis including an XPATH axis in an opposite direction that is exemplified as axis parent, ancestor in an XPATH into the state transition, replacing an XPATH axis including an XPATH axis in a direction of a following-sibling, or a preceding-sibling in said XPATH into the state transition, replacement of a predicate of an XPATH into the state transition, replacement of a logical product AND of a predicate of an XPATH into the state transition, replacement of a logical add OR of a predicate of an XPATH into the state transition, replacement of a logical NOT of a predicate of an XPATH into the state transition, and wherein replacing and replacement keep an input XPATH query expression equal in terms of a search, and generates the XPATH query automaton including the plurality of states of the backward nodes, the condition for transition, and the search state, wherein the search state includes two states of said input XPATH query expression concurrently in the state transition, and wherein every axis regarding sibling relationship among nodes of the document is included in a condition for the XPATH query automaton; a query automaton evaluator determining the state transition of a node under determination by storing a left node and a lower node in correspondence with an identified element identifier, wherein information obtained from said left node and information obtained from said lower node for the state transition is used concurrently, and evaluating said XPATH query automaton with a search result of said left node and said lower node; storing the XPATH query automaton generated by a compiling device in a query automaton storage device; reading out the XPATH query automaton from said query automaton storage device and storing the XPATH query automaton while reading in said document and performing a stream search with the XPATH query automaton evaluator by using states of a plurality of different types of nodes in said element identifiers included in said document and said XPATH query automaton, thereby using two inputs and a search state; and storing an output of the query automaton evaluator in a result-storage device and thereafter outputting the stored output of the query automaton evaluator and the output of a searched node. | 1. A computer-implemented document-searching method for searching a document having a hierarchical structure with elements separated by element identifiers, comprising the steps of: generating an XPATH query automaton, wherein XPATH is an XML (Extensible Markup Language) path for searching an XML document; wherein the XPATH query automaton is a table that contains a plurality of states of backward nodes, a condition for transition, and a search state; wherein a collection of entries of the XPATH query automaton expresses a state transition; wherein the generating the XPATH query automaton comprises steps of: generating and registering the state transition, wherein the generating and registering the state transition comprises: replacing an XPATH axis including an XPATH axis in a forward direction that is exemplified as an axis child, or a descendant in an XPATH into the state transition, replacing an XPATH axis including an XPATH axis in an opposite direction that is exemplified as axis parent, ancestor in an XPATH into the state transition, replacing an XPATH axis including an XPATH axis in a direction of a following-sibling, or a preceding-sibling in said XPATH into the state transition, replacement of a predicate of an XPATH into the state transition, replacement of a logical product AND of a predicate of an XPATH into the state transition, replacement of a logical add OR of a predicate of an XPATH into the state transition, replacement of a logical NOT of a predicate of an XPATH into the state transition, and wherein replacing and replacement keep an input XPATH query expression equal in terms of a search, and generates the XPATH query automaton including the plurality of states of the backward nodes, the condition for transition, and the search state, wherein the search state includes two states of said input XPATH query expression concurrently in the state transition, and wherein every axis regarding sibling relationship among nodes of the document is included in a condition for the XPATH query automaton; a query automaton evaluator determining the state transition of a node under determination by storing a left node and a lower node in correspondence with an identified element identifier, wherein information obtained from said left node and information obtained from said lower node for the state transition is used concurrently, and evaluating said XPATH query automaton with a search result of said left node and said lower node; storing the XPATH query automaton generated by a compiling device in a query automaton storage device; reading out the XPATH query automaton from said query automaton storage device and storing the XPATH query automaton while reading in said document and performing a stream search with the XPATH query automaton evaluator by using states of a plurality of different types of nodes in said element identifiers included in said document and said XPATH query automaton, thereby using two inputs and a search state; and storing an output of the query automaton evaluator in a result-storage device and thereafter outputting the stored output of the query automaton evaluator and the output of a searched node. 2. The document-searching method according to claim 1 , wherein the step of generating an XPATH query automaton comprises a step of generating an XPATH query automaton with the state transition corresponding to an initial state, a final state, and a search state registered thereon. | 0.5 |
1. A method, comprising: receiving a query; generating, by a master node, a query plan to perform the query, wherein the generating of the query plan includes dividing the query plan into at least a first portion and a second portion, and wherein the master node comprises one or more hardware processors; selecting, by the master node, from a set of available query processing segments a first subset of query processing segments to perform a first assigned portion of the query plan corresponding to the first portion of the query plan, and a second subset of query processing segments to perform a second assigned portion of the query plan corresponding to the second portion of the query plan, wherein at least one segment of the set of available query processing segments is included in the first subset and the second subset of query processing segments, wherein a first number of segments selected to perform the first portion of the query plan is dynamically determined according to one or both of (1) data locality of data corresponding to the first portion of the query plan associated with the query in relation to the first subset of query processing segments, and (2) available resources, wherein the first subset of query processing segments is selected based at least in part on a co-locality of one or more of the selected query processing segments with data with which the assigned portion of the query plan is associated, and wherein the first number of segments is selected to perform the first portion of the query plan and a second number of segments, different from the first number, is selected to perform the second portion of the query plan; and dispatching to the selected first subset of query processing segments an assignment to perform the first assigned portion of the query plan, wherein the dispatching of the assignment to perform the first assigned portion of the query plan includes providing to the selected first subset of query processing segments with corresponding metadata that is obtained from a central metadata store, wherein the metadata provided to the corresponding selected first subset of query processing segments is determined to be used to perform the first assigned portion of the query plan. | 1. A method, comprising: receiving a query; generating, by a master node, a query plan to perform the query, wherein the generating of the query plan includes dividing the query plan into at least a first portion and a second portion, and wherein the master node comprises one or more hardware processors; selecting, by the master node, from a set of available query processing segments a first subset of query processing segments to perform a first assigned portion of the query plan corresponding to the first portion of the query plan, and a second subset of query processing segments to perform a second assigned portion of the query plan corresponding to the second portion of the query plan, wherein at least one segment of the set of available query processing segments is included in the first subset and the second subset of query processing segments, wherein a first number of segments selected to perform the first portion of the query plan is dynamically determined according to one or both of (1) data locality of data corresponding to the first portion of the query plan associated with the query in relation to the first subset of query processing segments, and (2) available resources, wherein the first subset of query processing segments is selected based at least in part on a co-locality of one or more of the selected query processing segments with data with which the assigned portion of the query plan is associated, and wherein the first number of segments is selected to perform the first portion of the query plan and a second number of segments, different from the first number, is selected to perform the second portion of the query plan; and dispatching to the selected first subset of query processing segments an assignment to perform the first assigned portion of the query plan, wherein the dispatching of the assignment to perform the first assigned portion of the query plan includes providing to the selected first subset of query processing segments with corresponding metadata that is obtained from a central metadata store, wherein the metadata provided to the corresponding selected first subset of query processing segments is determined to be used to perform the first assigned portion of the query plan. 3. The method of claim 1 , wherein selecting the first subset of query processing segments includes receiving from a resource manager an indication of a degree of availability of processing segments included in the set of available query processing segments. | 0.506189 |
2. The method of claim 1 wherein step (e) is repeated for each selected word starting with the longest selected word as the given selected word and wherein the method comprises the further step of: (f) extending the shortest extendible selected word including the step of forming a list of likely follower words, each of which has a relatively high probability of following the extendible selected word, each word in the list of likely follower words being from the vocabulary of words. | 2. The method of claim 1 wherein step (e) is repeated for each selected word starting with the longest selected word as the given selected word and wherein the method comprises the further step of: (f) extending the shortest extendible selected word including the step of forming a list of likely follower words, each of which has a relatively high probability of following the extendible selected word, each word in the list of likely follower words being from the vocabulary of words. 4. The method of claim 2 wherein the list forming step comprises the steps of: (k) choosing a word from the vocabulary; (m) evaluating the acoustic probability of the chosen word producing the labels in the string which follow the most likely boundary label interval of the extendible selected word; (n) repeating steps (k) and (m) for each word in the vocabulary; each chosen word having an acoustic probability satisfying a first predefined threshold being a candidate word; and (o) evaluating a respective language model probability for each candidate word; each candidate word having a language model probability satisfying a second predefined threshold being a likely follower word. | 0.806636 |
1. A method of indexing documents, the method comprising: extracting, by a computer processor, feature information from each of a plurality of documents to be indexed; defining a plurality of indexes based on statistical properties of the extracted feature information, wherein the defining includes establishing, for each of the indexes, an upper limit on each of one or more parameters measuring a size of the index; for each of at least some of the documents: selecting one of the indexes as a destination index for the document based on the feature information extracted from the document, wherein the selecting includes: identifying a current index from among the plurality of indexes; determining, for each of the one or more parameters, whether adding the document to the current index will result in the index exceeding the upper limit on the parameter; and selecting the current index as the destination index for the document in the event that adding the document to the current index will not result in the index exceeding the upper limit on any of the one or more parameters; and adding a searchable representation of the document to the destination index; and storing the plurality of indexes in a computer-readable storage medium. | 1. A method of indexing documents, the method comprising: extracting, by a computer processor, feature information from each of a plurality of documents to be indexed; defining a plurality of indexes based on statistical properties of the extracted feature information, wherein the defining includes establishing, for each of the indexes, an upper limit on each of one or more parameters measuring a size of the index; for each of at least some of the documents: selecting one of the indexes as a destination index for the document based on the feature information extracted from the document, wherein the selecting includes: identifying a current index from among the plurality of indexes; determining, for each of the one or more parameters, whether adding the document to the current index will result in the index exceeding the upper limit on the parameter; and selecting the current index as the destination index for the document in the event that adding the document to the current index will not result in the index exceeding the upper limit on any of the one or more parameters; and adding a searchable representation of the document to the destination index; and storing the plurality of indexes in a computer-readable storage medium. 3. The method of claim 1 further comprising: defining a garbage index; and wherein selecting one of the indexes as the destination index includes: determining whether the document satisfies a criterion indicating that the document is unlikely to be relevant to a subsequent search query; and selecting the garbage index as the destination index for the document in the event that the document satisfies the criterion. | 0.5 |
41. A method of generating attribute models for use in a navigation system in a vehicle, the method comprising: for each of a plurality of driving sessions, during which the user travelled over a plurality of road segments in the vehicle: collecting sensor data of the vehicle for each of the plurality road segments travelled during a driving session; and associating the sensor data with at least one of a plurality of conditions, each condition descriptive of the driving session at the time the user travelled on the road segment; for each of the plurality of road segments, determining a value of a road attribute of the road segment based upon the sensor data collected for that road segment, and associated with at least one of the conditions; and for each of the plurality of conditions, storing the values of the road attribute in a conditional variant model associated with the condition, wherein storing the values of the road attribute in a conditional variant model associated with the condition comprises: partitioning values of the road attribute into separate data buckets by explicit conditions; and forming a conditional variant model for each respective explicit condition based on the values of the road attribute in that bucket. | 41. A method of generating attribute models for use in a navigation system in a vehicle, the method comprising: for each of a plurality of driving sessions, during which the user travelled over a plurality of road segments in the vehicle: collecting sensor data of the vehicle for each of the plurality road segments travelled during a driving session; and associating the sensor data with at least one of a plurality of conditions, each condition descriptive of the driving session at the time the user travelled on the road segment; for each of the plurality of road segments, determining a value of a road attribute of the road segment based upon the sensor data collected for that road segment, and associated with at least one of the conditions; and for each of the plurality of conditions, storing the values of the road attribute in a conditional variant model associated with the condition, wherein storing the values of the road attribute in a conditional variant model associated with the condition comprises: partitioning values of the road attribute into separate data buckets by explicit conditions; and forming a conditional variant model for each respective explicit condition based on the values of the road attribute in that bucket. 42. The method of claim 41 , wherein the road attribute is road speed. | 0.556108 |
13. The method of claim 1 , wherein the digital document is provided by one of: a rigidly-structured document, a nearly-rigidly-structured document, a semi-structured document, and an un-structured document. | 13. The method of claim 1 , wherein the digital document is provided by one of: a rigidly-structured document, a nearly-rigidly-structured document, a semi-structured document, and an un-structured document. 14. The method of claim 13 , further comprising: based on the document type, executing a computer-executable action with respect to the digital document. | 0.934103 |
6. The apparatus according to claim 1 , wherein the information on the priority includes a plurality of rules relating to merge processing, and the plurality of rules are each specified by an identifier. | 6. The apparatus according to claim 1 , wherein the information on the priority includes a plurality of rules relating to merge processing, and the plurality of rules are each specified by an identifier. 7. The apparatus according to claim 6 , further comprising a storage unit for storing therein information on a correspondence of each element constituting the third target model and the second target model to the identifier, wherein according to a rule specified by the identifier, the merge unit merges change information on a change of the element in the first change information, and change information on a change of the element in the second change information. | 0.839076 |
4. The method according to claim 1 , further comprising the step of arranging the content in the second language so that the format of the current content in the first language is preserved. | 4. The method according to claim 1 , further comprising the step of arranging the content in the second language so that the format of the current content in the first language is preserved. 12. The method according to claim 4 , wherein the step of arranging includes inserting a link contained in the content in the first language in the current content in the second language. | 0.90167 |
1. A method, comprising: analyzing, by at least one automatic speech recognition component, at least one voice interaction by at least one agent following at least one script in at least one of a plurality of panels; and determining whether the at least one agent has adequately followed the at least one script based on a score using confidence level thresholds of the least one automatic speech recognition component such that confidence level thresholds are assigned to each of the plurality of panels. | 1. A method, comprising: analyzing, by at least one automatic speech recognition component, at least one voice interaction by at least one agent following at least one script in at least one of a plurality of panels; and determining whether the at least one agent has adequately followed the at least one script based on a score using confidence level thresholds of the least one automatic speech recognition component such that confidence level thresholds are assigned to each of the plurality of panels. 9. The method of claim 1 , wherein the at least one voice interaction includes at least one voice interaction on at least one of a communications network, a publicly switched telephone network (PSTN), and the Internet. | 0.610422 |
10. A method for providing a dynamic trust score for evaluating ongoing online relationships, the method comprising: receiving a first request from an online service for a trust score assigned to an online relationship between a first user and a second user; calculating the trust score using a plurality of user data variables derived from a platform database referencing the first user and the second user, the user data variables including certified data and proffered data, wherein a weight given to each of the plurality of user data variables corresponds to a trust importance of each of the plurality of user data variables, and wherein the weight is adjusted over time for calculation of future trust scores based on a change in the trust importance of each of the plurality of user data variables; saving the trust score as a previous trust score in a memory; sending the trust score to the online service in response to the first request, wherein the trust score affects a client of the first user, and performing dynamic recalculation of the trust score in response to a change to the plurality of user data variables over a period of time, wherein the change includes varying the weight given to each of the plurality of user data variables over the period of time, wherein the dynamic recalculation includes using the previous trust score. | 10. A method for providing a dynamic trust score for evaluating ongoing online relationships, the method comprising: receiving a first request from an online service for a trust score assigned to an online relationship between a first user and a second user; calculating the trust score using a plurality of user data variables derived from a platform database referencing the first user and the second user, the user data variables including certified data and proffered data, wherein a weight given to each of the plurality of user data variables corresponds to a trust importance of each of the plurality of user data variables, and wherein the weight is adjusted over time for calculation of future trust scores based on a change in the trust importance of each of the plurality of user data variables; saving the trust score as a previous trust score in a memory; sending the trust score to the online service in response to the first request, wherein the trust score affects a client of the first user, and performing dynamic recalculation of the trust score in response to a change to the plurality of user data variables over a period of time, wherein the change includes varying the weight given to each of the plurality of user data variables over the period of time, wherein the dynamic recalculation includes using the previous trust score. 15. The method of claim 10 , wherein the user data variables further include observed data regarding the first user and the second user including at least one of a location, a timestamp, a user behavior, a user generated content, a biometric analysis, and a biometric data. | 0.729249 |
12. A computer system, comprising: at least one processor; memory including instructions that, when executed by the at least one processor, cause the computer system to: receive a query from a searching entity; submit the query to a plurality of search indexes, each search index corresponding to a respective category of items, at least one of the plurality of search indexes utilizing at least one of a different ranking property, scale, function, or definition for ranking items relative to other search indexes; receive one of a plurality of search index result sets from each of the plurality of search indexes in response to the query; determine a plurality of appropriateness scores each corresponding to one of the plurality of search indexes, each of the plurality of appropriateness scores indicating an appropriateness of the category of items corresponding to the respective search index with respect to the query and being based at least in part on historical queries similar to the query that were submitted to the respective search index; determine a universal item score for each of a plurality of items in the plurality of search index result sets at least in part by normalizing the at least one of the different ranking property, scale, function, and definition to a ranking scale common to all the search index result sets; for each of the plurality of items, determine a probability that the item satisfies the query based at least in part on the appropriateness score for the search index associated with the item and the universal item score for the item; include in the universal query result set ones of the plurality of items selected in an order based at least in part on the probabilities of the plurality of items satisfying the query; and provide the universal query result set to the searching entity, wherein determining the plurality of appropriateness scores comprises modifying the plurality of appropriateness scores differently based at least in part on different types of recorded actions associated with the historical queries that were submitted to a corresponding search index. | 12. A computer system, comprising: at least one processor; memory including instructions that, when executed by the at least one processor, cause the computer system to: receive a query from a searching entity; submit the query to a plurality of search indexes, each search index corresponding to a respective category of items, at least one of the plurality of search indexes utilizing at least one of a different ranking property, scale, function, or definition for ranking items relative to other search indexes; receive one of a plurality of search index result sets from each of the plurality of search indexes in response to the query; determine a plurality of appropriateness scores each corresponding to one of the plurality of search indexes, each of the plurality of appropriateness scores indicating an appropriateness of the category of items corresponding to the respective search index with respect to the query and being based at least in part on historical queries similar to the query that were submitted to the respective search index; determine a universal item score for each of a plurality of items in the plurality of search index result sets at least in part by normalizing the at least one of the different ranking property, scale, function, and definition to a ranking scale common to all the search index result sets; for each of the plurality of items, determine a probability that the item satisfies the query based at least in part on the appropriateness score for the search index associated with the item and the universal item score for the item; include in the universal query result set ones of the plurality of items selected in an order based at least in part on the probabilities of the plurality of items satisfying the query; and provide the universal query result set to the searching entity, wherein determining the plurality of appropriateness scores comprises modifying the plurality of appropriateness scores differently based at least in part on different types of recorded actions associated with the historical queries that were submitted to a corresponding search index. 14. A computer system according to claim 12 , wherein the plurality of search indexes reside, at least in part, on at least one computing device distinct from the computer system receiving the query. | 0.577474 |
9. The computer-readable medium of claim 8 , computer-readable medium further to: save the set of objects to serialize and deserialize input parameters into the file system. | 9. The computer-readable medium of claim 8 , computer-readable medium further to: save the set of objects to serialize and deserialize input parameters into the file system. 10. The computer-readable medium of claim 9 , the computer-readable medium further to: persist the set of objects to serialize and deserialize input parameters, the archive, and the metadata descriptors to a database. | 0.908755 |
18. A computerized system, comprising: a first computing subsystem that is configured to receive text of a message entered by a user into a communication application program that represents typed or audibly spoken content of input provided by the user, parse the text into multiple different portions of the text, and provide the multiple different portions to another subsystem for analysis; a second computing subsystem that is configured to repeatedly receive a portion of text from the first computing subsystem, determine a level of randomness of characters in the received portion of text, identify a threshold level of randomness from a plurality of different threshold levels of randomness based at least in part on a particular label of a text entry field into which the received portion of the text was input; and provide the determined level of randomness of the characters in the received portion of text and the identified threshold level of randomness to yet another subsystem for analysis; and a third computing subsystem that is configured to repeatedly receive from the second computing subsystem a determined level of randomness of characters in a received portion of text, determine whether the determined level of randomness of characters in the received portion of text exceeds a corresponding threshold level of randomness, and to prevent portions of text with randomness levels that do exceed the corresponding threshold level of randomness from being provided to a text processing system to execute a spell checking procedure on the received portions of text or a word auto-complete procedure on the received portions of text. | 18. A computerized system, comprising: a first computing subsystem that is configured to receive text of a message entered by a user into a communication application program that represents typed or audibly spoken content of input provided by the user, parse the text into multiple different portions of the text, and provide the multiple different portions to another subsystem for analysis; a second computing subsystem that is configured to repeatedly receive a portion of text from the first computing subsystem, determine a level of randomness of characters in the received portion of text, identify a threshold level of randomness from a plurality of different threshold levels of randomness based at least in part on a particular label of a text entry field into which the received portion of the text was input; and provide the determined level of randomness of the characters in the received portion of text and the identified threshold level of randomness to yet another subsystem for analysis; and a third computing subsystem that is configured to repeatedly receive from the second computing subsystem a determined level of randomness of characters in a received portion of text, determine whether the determined level of randomness of characters in the received portion of text exceeds a corresponding threshold level of randomness, and to prevent portions of text with randomness levels that do exceed the corresponding threshold level of randomness from being provided to a text processing system to execute a spell checking procedure on the received portions of text or a word auto-complete procedure on the received portions of text. 19. The computerized system of claim 18 , wherein the first computing subsystem is configured to parse the text into multiple different portions of the text by performing a sliding window parsing operation on the text in order to generate portions of text that are of a same size and so that a character in the text is included in more than one of the multiple different portions of the text. | 0.5 |
9. A computer-implemented method of analyzing complexity of a document, comprising: receiving the document with a processing system, the document including a plurality of words; identifying, with the processing system, content words within the document based on parts of speech for the plurality of words; selecting, with the processing system, a plurality of pairs of the content words that appear in a same sentence or paragraph to form multiple groups of content words; determining, with the processing system, an association measure for each group of content words by determining how often the pair of content words in each group appears in a same sentence or paragraph in a corpus of documents; determining, with the processing system, a complexity score for the document based on the association measures determined for each group of content words, wherein determining the complexity of the document includes computing an average of the association measures included in the word association profile, wherein the average is inversely correlated to the complexity of the document. | 9. A computer-implemented method of analyzing complexity of a document, comprising: receiving the document with a processing system, the document including a plurality of words; identifying, with the processing system, content words within the document based on parts of speech for the plurality of words; selecting, with the processing system, a plurality of pairs of the content words that appear in a same sentence or paragraph to form multiple groups of content words; determining, with the processing system, an association measure for each group of content words by determining how often the pair of content words in each group appears in a same sentence or paragraph in a corpus of documents; determining, with the processing system, a complexity score for the document based on the association measures determined for each group of content words, wherein determining the complexity of the document includes computing an average of the association measures included in the word association profile, wherein the average is inversely correlated to the complexity of the document. 10. The computer-implemented method of claim 9 , wherein the complexity score of the document corresponds to a reading level of the document. | 0.606738 |
2. The speech synthesis method of claim 1 , wherein the identifying comprises: identifying the second speech segment based, at least in part, on how well acoustic characteristics of the second speech segment match acoustic characteristics associated with the desired speaking style. | 2. The speech synthesis method of claim 1 , wherein the identifying comprises: identifying the second speech segment based, at least in part, on how well acoustic characteristics of the second speech segment match acoustic characteristics associated with the desired speaking style. 3. The speech synthesis method of claim 2 , wherein the identifying the second speech segment is based, at least in part, on how well prosodic characteristics of the second speech segment match prosodic characteristics associated with the desired speaking style. | 0.889149 |
6. The system for creating a unique signature as described in claim 5 , wherein the at least one segment has at least one color. | 6. The system for creating a unique signature as described in claim 5 , wherein the at least one segment has at least one color. 7. The system for creating a unique signature as described in claim 6 , wherein the signature includes the at least one segment has a pattern different from the pattern of a second segment. | 0.919316 |
20. The method of claim 17, wherein the fuzzy search comprises a degradation process effective to selectively increase the number of records retrievable by the fuzzy search. | 20. The method of claim 17, wherein the fuzzy search comprises a degradation process effective to selectively increase the number of records retrievable by the fuzzy search. 23. The method of claim 20, wherein each record of the plurality of records corresponds to an article of a plurality of articles, and wherein the degradation process further comprises a linking routine effective to identify a record corresponding to a substitute article of the plurality of articles when no record is found corresponding to the article. | 0.893678 |
1. A method comprising: receiving, by a processor, symbolic input as labeled speech data; overgenerating potential pronunciations based on the symbolic input, wherein the overgenerating comprises: establishing a set of conversion rules; and converting portions of the symbolic input into a number of possible lexical pronunciation variants based on the set of conversion rules; identifying potential pronunciations in a speech recognition context to yield identified potential pronunciations; and storing the identified potential pronunciations in a lexicon. | 1. A method comprising: receiving, by a processor, symbolic input as labeled speech data; overgenerating potential pronunciations based on the symbolic input, wherein the overgenerating comprises: establishing a set of conversion rules; and converting portions of the symbolic input into a number of possible lexical pronunciation variants based on the set of conversion rules; identifying potential pronunciations in a speech recognition context to yield identified potential pronunciations; and storing the identified potential pronunciations in a lexicon. 5. The method of claim 1 , wherein labeled speech data includes words as text and recorded audio. | 0.900609 |
12. A method, comprising: receiving a search query; providing a structured presentation for display on a display device responsive to the search query, the structured presentation visually presenting information in a systematic and structured arrangement that conforms with a structured design, the structured presentation denoting associations between an instance and values that characterize attributes an entity corresponding to of the instance using an arrangement of the values in respective cells of the structured presentation responsive to the search query; receiving a user interaction with a first cell of the structured presentation, the first cell having a first value for a particular attribute of an instance associated with the first cell; and in response to the received user interaction with the first cell: determining that the first value of the first cell provided in the structured presentations resulted from a prior search of the unstructured collection of electronic documents by a system comprising one or more computers that identified one or more particular electronic documents as including content characterizing the particular attribute of the instance, wherein the first value was determined from the content of the one or more particular electronic documents; and in response to determining that the prior search was conducted, providing information regarding the prior search including providing a search interface associated with the first value of the first cell for presentation on the display device, the search interface configured to present search result information characterizing the prior search including providing information identifying a first electronic document of the particular electronic documents from which the first value for the attribute of the instance was determined including providing for display a link to the first electronic document. | 12. A method, comprising: receiving a search query; providing a structured presentation for display on a display device responsive to the search query, the structured presentation visually presenting information in a systematic and structured arrangement that conforms with a structured design, the structured presentation denoting associations between an instance and values that characterize attributes an entity corresponding to of the instance using an arrangement of the values in respective cells of the structured presentation responsive to the search query; receiving a user interaction with a first cell of the structured presentation, the first cell having a first value for a particular attribute of an instance associated with the first cell; and in response to the received user interaction with the first cell: determining that the first value of the first cell provided in the structured presentations resulted from a prior search of the unstructured collection of electronic documents by a system comprising one or more computers that identified one or more particular electronic documents as including content characterizing the particular attribute of the instance, wherein the first value was determined from the content of the one or more particular electronic documents; and in response to determining that the prior search was conducted, providing information regarding the prior search including providing a search interface associated with the first value of the first cell for presentation on the display device, the search interface configured to present search result information characterizing the prior search including providing information identifying a first electronic document of the particular electronic documents from which the first value for the attribute of the instance was determined including providing for display a link to the first electronic document. 18. The method of claim 12 , further comprising displaying a snippet characterizing a context of the first value in a first document of the electronic document collection. | 0.612765 |
1. A non-transitory processor-readable medium storing code representing instructions that when executed cause a processor to: select a narrative template based at least in part on a predetermined content type associated with a real-world event; select a narrative tone type based at least in part on a tone associated with the real-world event; and for each phrase included in an ordered set of phrases associated with the narrative template: select, based at least in part on the narrative tone type, a phrase variation from a set of phrase variations associated with that phrase; define, based on the selected phrase variation and at least one datum from a set of data, a narrative content portion associated with the real-world event; and send a signal such that the narrative content portion is output at a display. | 1. A non-transitory processor-readable medium storing code representing instructions that when executed cause a processor to: select a narrative template based at least in part on a predetermined content type associated with a real-world event; select a narrative tone type based at least in part on a tone associated with the real-world event; and for each phrase included in an ordered set of phrases associated with the narrative template: select, based at least in part on the narrative tone type, a phrase variation from a set of phrase variations associated with that phrase; define, based on the selected phrase variation and at least one datum from a set of data, a narrative content portion associated with the real-world event; and send a signal such that the narrative content portion is output at a display. 3. The non-transitory processor-readable medium of claim 1 , wherein the narrative template is one of a set of narrative templates associated with the predetermined content type, and the narrative template is selected based at least in part on a pseudo-random selection process. | 0.717277 |
1. An apparatus for generating an avatar based video message, the apparatus comprising: an audio input unit configured to receive speech of a user; a user input unit configured to receive input from the user; a display unit configured to output display information; and a control unit configured to perform speech recognition based on the speech of the user to generate a word sequence of the speech of the user, to generate editing information comprising the word sequence divided into a plurality of editable units based on a measured energy of the speech of the user, to generate avatar animation that moves based on the word sequence, and to generate an avatar based video message that vocalizes the word sequence of the speech of the user and that displays the avatar animation such that the avatar animation moves in synchronization with the vocalized word sequence. | 1. An apparatus for generating an avatar based video message, the apparatus comprising: an audio input unit configured to receive speech of a user; a user input unit configured to receive input from the user; a display unit configured to output display information; and a control unit configured to perform speech recognition based on the speech of the user to generate a word sequence of the speech of the user, to generate editing information comprising the word sequence divided into a plurality of editable units based on a measured energy of the speech of the user, to generate avatar animation that moves based on the word sequence, and to generate an avatar based video message that vocalizes the word sequence of the speech of the user and that displays the avatar animation such that the avatar animation moves in synchronization with the vocalized word sequence. 11. The apparatus of claim 1 , wherein the control unit is further configured to generate the editing information comprising the word sequence divided into the plurality of editable units based on clear sounds and based on linked sounds. | 0.598382 |
6. A computer implemented method for creating searchable associations of a user's interaction with a computer system's resources comprising: recording the user's interactions with the computer system's resources; wherein the computer system's resources include files accessed by the user on the computer system; and creating associations between the resources based on the user's interactions; wherein the associations group resources together that are accessed by the user within a time range to create a time based association of the grouped resources based on the time between when a resource is opened and closed on the computer system; wherein creating associations include: defining one or more tasks, wherein each task is associated with a set of resources used within the computer system by the user in a given period; wherein the resources can belong to several tasks; defining a lifecycle for at least one of the resources; wherein the lifecycle represents the time between the opening and closing of the resource on the computer system; wherein at least one association for the resource is associating other resources accessed between the opening and closing of the resource on the computer system with the resource; and defining a key for each of the one or more tasks, wherein the key is based on the lifecycles for resources in the set of one or more resources for the each task of the one or more tasks. | 6. A computer implemented method for creating searchable associations of a user's interaction with a computer system's resources comprising: recording the user's interactions with the computer system's resources; wherein the computer system's resources include files accessed by the user on the computer system; and creating associations between the resources based on the user's interactions; wherein the associations group resources together that are accessed by the user within a time range to create a time based association of the grouped resources based on the time between when a resource is opened and closed on the computer system; wherein creating associations include: defining one or more tasks, wherein each task is associated with a set of resources used within the computer system by the user in a given period; wherein the resources can belong to several tasks; defining a lifecycle for at least one of the resources; wherein the lifecycle represents the time between the opening and closing of the resource on the computer system; wherein at least one association for the resource is associating other resources accessed between the opening and closing of the resource on the computer system with the resource; and defining a key for each of the one or more tasks, wherein the key is based on the lifecycles for resources in the set of one or more resources for the each task of the one or more tasks. 7. The method of claim 6 wherein the associations denote a commonality between the resources based on the user's interactions, file access patterns, and implicit user tasks of user activity sequences. | 0.640162 |
8. A computer program product for dynamically evaluating an electronic communication, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code executable by a processor to: observe an electronic communication; upon detection of movement of indicia proximal to a phrase in the communication, activate an idiom search application, the application including program code to; identify an idiom within the phrase; search a corpus for a translation of the idiom and one or more associated characteristics; in response to detection of the translation, collect profile metadata related to the observed communication, compare the one or more characteristics with the collected profile metadata, and store the identified idiom with the collected profile metadata; and in response to absence of the translation, dynamically translate the idiom, and present the translated idiom proximal to the evaluated expression. | 8. A computer program product for dynamically evaluating an electronic communication, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code executable by a processor to: observe an electronic communication; upon detection of movement of indicia proximal to a phrase in the communication, activate an idiom search application, the application including program code to; identify an idiom within the phrase; search a corpus for a translation of the idiom and one or more associated characteristics; in response to detection of the translation, collect profile metadata related to the observed communication, compare the one or more characteristics with the collected profile metadata, and store the identified idiom with the collected profile metadata; and in response to absence of the translation, dynamically translate the idiom, and present the translated idiom proximal to the evaluated expression. 13. The computer program product of claim 8 , wherein the indicia is an element selected from the group consisting of: a cursor and a pointer. | 0.61128 |
12. A computer-implemented method of comparing two or more documents, comprising: linguistically analyzing a plurality of documents to identify at least one term group in each document, each term group comprising a main term and at least one subordinate term semantically related to the main term; generating a semantic vector associated with each document, the semantic vector comprising a plurality of components, each component including: a term group as a scalar in the document; a frequency value relating to a number of occurrences of the term group; and processing the semantic vector by a digital computer; and comparing a semantic vector of an identified document to the semantic vector for each document in the plurality of documents to determine at least one document semantically similar to the identified document using a defined metric, wherein said metric measures the semantic distance between documents as a function of at least the frequency values included in the semantic vectors for the documents, and wherein said metric is related to: Sqrt(f1 2 +f2 2 +f3 2 +f4 2 + +f(N−1) 2 fN 2 )*100n 2 wherein f is a difference in frequency of a common term between the plurality of documents and n is the number of terms those documents have in common. | 12. A computer-implemented method of comparing two or more documents, comprising: linguistically analyzing a plurality of documents to identify at least one term group in each document, each term group comprising a main term and at least one subordinate term semantically related to the main term; generating a semantic vector associated with each document, the semantic vector comprising a plurality of components, each component including: a term group as a scalar in the document; a frequency value relating to a number of occurrences of the term group; and processing the semantic vector by a digital computer; and comparing a semantic vector of an identified document to the semantic vector for each document in the plurality of documents to determine at least one document semantically similar to the identified document using a defined metric, wherein said metric measures the semantic distance between documents as a function of at least the frequency values included in the semantic vectors for the documents, and wherein said metric is related to: Sqrt(f1 2 +f2 2 +f3 2 +f4 2 + +f(N−1) 2 fN 2 )*100n 2 wherein f is a difference in frequency of a common term between the plurality of documents and n is the number of terms those documents have in common. 20. The method of claim 12 , wherein one or more of the at least one subordinate term or the main term comprises a phrase. | 0.587095 |
10. A system for detecting open caption text in a video, the system comprising at least one processor and a memory storing one or more program modules to be executed by the processor, the program modules comprising: a text region segmentation module having one or more instructions that when executed by the processor is configured to: mark location of one or more pixels in a threshold marked buffer if a difference between pixel value of a pixel in an original frame and pixel value of a pixel in a filtered frame is above a first predefined threshold; mark location of one or more pixels in the original frame lying in a high density region by calculating spatial discontinuity at each pixel in a text candidate map buffer; determine a neighborhood size based on a coarse font size, the neighborhood size being a multiple of the coarse font size; determine one or more seed pixels in the threshold marked buffer and the text candidate map buffer, by determining one or more marked pixels in the threshold marked buffer and the text candidate map buffer, having a number of marked pixels within the neighborhood size greater than a second predefined threshold; determine one or more connected components, by determining marked of the threshold marked buffer pixels in a first predefined neighborhood of each seed pixel present in the threshold marked buffer and connecting all the marked pixels in the first predefined neighborhood of each seed pixel in the threshold marked buffer and that seed pixel; and determine one or more connected components by determining marked pixels of the text candidate map buffer in a second predefined neighborhood of each seed pixel present in the text candidate map buffer and connecting all the marked pixels in the second predefined neighborhood of each seed pixel in the text candidate map buffer and that seed pixel; a character validation module having one or more instructions that when executed by the processor is configured to: determine one or more valid candidates in the original frame by using the determined one or more connected components, by determining one or more connected components having width to height ratio above a third predefined threshold, and having height within a first predefined range, and having a uniform font width; a sentence validation module having one or more instructions that when executed by the processor is configured to: compute one or more moments of the determined one or more valid candidates; determine one or more clusters by clustering one or more of the determined one or more valid candidates together if the font width and moments of the one or more valid candidates are in a second predefined range; and determine one or more valid clusters by analyzing the valid candidates within each of the one or more clusters, wherein a valid cluster has spatially neighboring connected components; and a temporal validation module having one or more instructions that when executed by the processor is configured to: determine motion profile of each of one or more frames or fields, wherein the motion profile includes a measure of a displacement of the one or more valid candidates in the one or more valid clusters for consecutive frames or fields; and analyze the motion profile of all the frames in the video for determining uniformity in the frames by comparing the motion profile of a pair of current frame and previous frame. | 10. A system for detecting open caption text in a video, the system comprising at least one processor and a memory storing one or more program modules to be executed by the processor, the program modules comprising: a text region segmentation module having one or more instructions that when executed by the processor is configured to: mark location of one or more pixels in a threshold marked buffer if a difference between pixel value of a pixel in an original frame and pixel value of a pixel in a filtered frame is above a first predefined threshold; mark location of one or more pixels in the original frame lying in a high density region by calculating spatial discontinuity at each pixel in a text candidate map buffer; determine a neighborhood size based on a coarse font size, the neighborhood size being a multiple of the coarse font size; determine one or more seed pixels in the threshold marked buffer and the text candidate map buffer, by determining one or more marked pixels in the threshold marked buffer and the text candidate map buffer, having a number of marked pixels within the neighborhood size greater than a second predefined threshold; determine one or more connected components, by determining marked of the threshold marked buffer pixels in a first predefined neighborhood of each seed pixel present in the threshold marked buffer and connecting all the marked pixels in the first predefined neighborhood of each seed pixel in the threshold marked buffer and that seed pixel; and determine one or more connected components by determining marked pixels of the text candidate map buffer in a second predefined neighborhood of each seed pixel present in the text candidate map buffer and connecting all the marked pixels in the second predefined neighborhood of each seed pixel in the text candidate map buffer and that seed pixel; a character validation module having one or more instructions that when executed by the processor is configured to: determine one or more valid candidates in the original frame by using the determined one or more connected components, by determining one or more connected components having width to height ratio above a third predefined threshold, and having height within a first predefined range, and having a uniform font width; a sentence validation module having one or more instructions that when executed by the processor is configured to: compute one or more moments of the determined one or more valid candidates; determine one or more clusters by clustering one or more of the determined one or more valid candidates together if the font width and moments of the one or more valid candidates are in a second predefined range; and determine one or more valid clusters by analyzing the valid candidates within each of the one or more clusters, wherein a valid cluster has spatially neighboring connected components; and a temporal validation module having one or more instructions that when executed by the processor is configured to: determine motion profile of each of one or more frames or fields, wherein the motion profile includes a measure of a displacement of the one or more valid candidates in the one or more valid clusters for consecutive frames or fields; and analyze the motion profile of all the frames in the video for determining uniformity in the frames by comparing the motion profile of a pair of current frame and previous frame. 11. The system of claim 10 , wherein the system further comprising a low pass filter for determining a filtered frame by filtering the original frame. | 0.631737 |
37. The computer system of claim 36, wherein the predefined rendering characteristic is a feature of the one of the objects allowing the at least one element to be rendered as the text element while preserving the appearance of the overlap group. | 37. The computer system of claim 36, wherein the predefined rendering characteristic is a feature of the one of the objects allowing the at least one element to be rendered as the text element while preserving the appearance of the overlap group. 38. The computer system of claim 37, wherein the predefined rendering characteristic is unrotated text, no gradient filled background, no pattern filled background, and no border art. | 0.963897 |
13. The method of claim 11 where the source includes the blog. | 13. The method of claim 11 where the source includes the blog. 14. The method of claim 13 where the source includes an update feed and the blog, where the information extracted from the update feed includes at least one of a title of the blog, an author of the blog, or a profile of the author of the blog, and where the information extracted from the blog includes at least one of the title of the blog, the profile of the author of the blog, or a blogroll. | 0.839676 |
1. A method for performing a search for content in an electronic database using a tuple index with separately indexed tuple word combinations, the method comprising: creating the tuple index comprising a plurality of tuples, wherein each tuple comprises three or more terms found within electronic content, wherein at least two tuples in the tuple index include two terms in common and one different term; receiving a search request that includes two or more search terms; creating one or more tuples from the two or more search terms including creating a first sequence identifier to represent a first tuple created from the two or more search terms; performing a search for documents of the electronic content that match the search request by comparing the one or more tuples created from the two or more search terms to the plurality of tuples in the tuple index; and providing a plurality of documents as results of the performed search including ranking two or more documents in the results based on the two or more documents each containing the first tuple, but having a different sequence identifier associated with the first tuple such that a document containing the first tuple and a sequence identifier that matches the first sequence identifier is ranked higher than a document containing the first tuple and a sequence identifier that does not match the first sequence identifier. | 1. A method for performing a search for content in an electronic database using a tuple index with separately indexed tuple word combinations, the method comprising: creating the tuple index comprising a plurality of tuples, wherein each tuple comprises three or more terms found within electronic content, wherein at least two tuples in the tuple index include two terms in common and one different term; receiving a search request that includes two or more search terms; creating one or more tuples from the two or more search terms including creating a first sequence identifier to represent a first tuple created from the two or more search terms; performing a search for documents of the electronic content that match the search request by comparing the one or more tuples created from the two or more search terms to the plurality of tuples in the tuple index; and providing a plurality of documents as results of the performed search including ranking two or more documents in the results based on the two or more documents each containing the first tuple, but having a different sequence identifier associated with the first tuple such that a document containing the first tuple and a sequence identifier that matches the first sequence identifier is ranked higher than a document containing the first tuple and a sequence identifier that does not match the first sequence identifier. 9. A method as recited in claim 1 , wherein the search is performed dynamically while search input is still being entered such that the plurality of documents are provided as results while search input is still being entered. | 0.541615 |
1. A method of semantically parsing a natural language expression, comprising: constructing, by a processor, a first ambiguous meaning representation for a first natural language expression; fully or partially disambiguating, by a processor, the first meaning representation by specializing it by replacing a first semantic descriptor in it by a second, more specific semantic descriptor; associating with at least one semantic descriptor in the meaning representation a weight indicating an evaluation of how good an alternative it is; and adjusting at least one such weight in response to a later parsing or disambiguation action. | 1. A method of semantically parsing a natural language expression, comprising: constructing, by a processor, a first ambiguous meaning representation for a first natural language expression; fully or partially disambiguating, by a processor, the first meaning representation by specializing it by replacing a first semantic descriptor in it by a second, more specific semantic descriptor; associating with at least one semantic descriptor in the meaning representation a weight indicating an evaluation of how good an alternative it is; and adjusting at least one such weight in response to a later parsing or disambiguation action. 3. The method of claim 1 , further comprising further disambiguating a meaning representation that has already been partially disambiguated by further specializing it by replacing the second semantic descriptor in it by a third, even more specific semantic descriptor. | 0.606667 |
1. A method of printing simple data within a complex datastream, the method comprising: receiving the complex datastream for processing, wherein the complex datastream includes simple data in a non-complex page description language (PDL) format and a copy of the simple data in a complex PDL format; processing the complex datastream to embed at least one control structure in the complex datastream, wherein the at least one control structure indicates to a raster image processor a location of the simple data in the non-complex PDL format; determining if the raster image processor recognizes the at least one control structure in the complex datastream; and processing the complex datastream by the raster image processor to generate a printable format by: converting the simple data in the non-complex PDL format to the printable format responsive to the raster image processor recognizing the at least one control structure; and converting the simple data in the complex PDL format to the printable format responsive to the raster image processor not recognizing the at least one control structure. | 1. A method of printing simple data within a complex datastream, the method comprising: receiving the complex datastream for processing, wherein the complex datastream includes simple data in a non-complex page description language (PDL) format and a copy of the simple data in a complex PDL format; processing the complex datastream to embed at least one control structure in the complex datastream, wherein the at least one control structure indicates to a raster image processor a location of the simple data in the non-complex PDL format; determining if the raster image processor recognizes the at least one control structure in the complex datastream; and processing the complex datastream by the raster image processor to generate a printable format by: converting the simple data in the non-complex PDL format to the printable format responsive to the raster image processor recognizing the at least one control structure; and converting the simple data in the complex PDL format to the printable format responsive to the raster image processor not recognizing the at least one control structure. 5. The method of claim 1 wherein the at least one control structure provides control information regarding the simple data in the non-complex PDL format, the control information indicating at least one location of portions of the simple data in the non-complex PDL format and providing a method for constructing at least one image of the simple data and wherein processing the complex datastream further comprises: assembling the portions of the simple data in the non-complex PDL format to form the at least one image. | 0.540172 |
15. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program instructions stored therein, the computer-readable program instructions comprising program instructions configured to cause an apparatus to perform a method comprising: receiving an input indicating a search criteria; determining, by a processor, at least one search result position related to the search criteria; determining a relationship between the at least one search result position and a multi-level map; and causing, based at least in part on the relationship, a level of the map and the at least one search result position to be displayed as a search result position indicator, wherein the displayed search result position indicator is presented in a different manner based at least in part on whether the search result position is on the level of the map that is displayed or is on another level of the map. | 15. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program instructions stored therein, the computer-readable program instructions comprising program instructions configured to cause an apparatus to perform a method comprising: receiving an input indicating a search criteria; determining, by a processor, at least one search result position related to the search criteria; determining a relationship between the at least one search result position and a multi-level map; and causing, based at least in part on the relationship, a level of the map and the at least one search result position to be displayed as a search result position indicator, wherein the displayed search result position indicator is presented in a different manner based at least in part on whether the search result position is on the level of the map that is displayed or is on another level of the map. 17. The computer program product of claim 15 configured to cause an apparatus to perform a method wherein causing the at least one search result position to be displayed further comprises causing the at least one search result position indicator to be displayed in an instance in which the at least one search result position is located within the portion of the map that is displayed. | 0.503846 |
14. A non-transitory machine readable storage medium having computer readable program code embedded therein for providing product recommendations, comprising: a context item processor to receive and track context items as a product page is navigated; a plurality of similarities datasets comprising products with a similarity to a product on the product page, each of the plurality of similarities datasets being derived from a separate source; a data store selection module to select one of the plurality of similarities datasets as a source of product recommendations based on the context items, wherein the one of the plurality of similarities datasets is selected using a machine learning model that yields patterns representative of an underlying mechanism based on the context items as input for the machine model, and wherein the plurality of similarities datasets are prepared for the product page, and the machine learning model selects the one of the plurality of similarities datasets based on a fallback strategy where one of the plurality of similarity datasets is a new similarities dataset, wherein the fallback strategy is learned by the machine learning model using logged data regarding the plurality of similarities datasets used for past recommendations; a logging module to log the similarities dataset selected by the machine learning model for use in making future recommendations; a ranking module to rank products in the selected one of the plurality of similarities datasets based on the context items; and a content page module to provide the product recommendations for display based on the context items. | 14. A non-transitory machine readable storage medium having computer readable program code embedded therein for providing product recommendations, comprising: a context item processor to receive and track context items as a product page is navigated; a plurality of similarities datasets comprising products with a similarity to a product on the product page, each of the plurality of similarities datasets being derived from a separate source; a data store selection module to select one of the plurality of similarities datasets as a source of product recommendations based on the context items, wherein the one of the plurality of similarities datasets is selected using a machine learning model that yields patterns representative of an underlying mechanism based on the context items as input for the machine model, and wherein the plurality of similarities datasets are prepared for the product page, and the machine learning model selects the one of the plurality of similarities datasets based on a fallback strategy where one of the plurality of similarity datasets is a new similarities dataset, wherein the fallback strategy is learned by the machine learning model using logged data regarding the plurality of similarities datasets used for past recommendations; a logging module to log the similarities dataset selected by the machine learning model for use in making future recommendations; a ranking module to rank products in the selected one of the plurality of similarities datasets based on the context items; and a content page module to provide the product recommendations for display based on the context items. 20. The system of claim 14 , wherein the context items comprise a context identification of the product page, and the context identification results in selection of a specific similarities dataset as a source of product recommendations. | 0.506494 |
14. A method of creating a plurality of different target software development tools, the method comprising: receiving at least one computer-readable specification specifying functionality specific to one or more software development scenarios, wherein the at least one computer-readable specification specifies the following software development scenario functionality of the plurality of different target software development tools: target processor execution architecture; type checking rule set; managed execution environment; input programming language or input binary format; and compilation type; creating at least one software development component for the plurality of different software development tools from the at least one specification; integrating the at least one software development component for the plurality of different software development tools into a software development scenario-independent framework; and compiling, at least in part, the at least one software development component and framework to create the plurality of different target software development tools; wherein the computer-readable specification comprises functionality for processing an intermediate representation format capable of representing a plurality of different programming languages; and wherein the intermediate representation format comprises one or more exception handling models capable of supporting a plurality of programming language-specific exception handling models for the plurality of different programming languages. | 14. A method of creating a plurality of different target software development tools, the method comprising: receiving at least one computer-readable specification specifying functionality specific to one or more software development scenarios, wherein the at least one computer-readable specification specifies the following software development scenario functionality of the plurality of different target software development tools: target processor execution architecture; type checking rule set; managed execution environment; input programming language or input binary format; and compilation type; creating at least one software development component for the plurality of different software development tools from the at least one specification; integrating the at least one software development component for the plurality of different software development tools into a software development scenario-independent framework; and compiling, at least in part, the at least one software development component and framework to create the plurality of different target software development tools; wherein the computer-readable specification comprises functionality for processing an intermediate representation format capable of representing a plurality of different programming languages; and wherein the intermediate representation format comprises one or more exception handling models capable of supporting a plurality of programming language-specific exception handling models for the plurality of different programming languages. 16. The method of claim 14 wherein the computer-readable specification comprises one or more rulesets for type-checking one or more languages. | 0.541342 |
97. The method of claim 3 , comprising controlling scaling of the detecting and controlling to generate coincidence between virtual space and physical space, wherein the virtual space comprises space depicted on a display device coupled to the computer, wherein the physical space comprises space inhabited by the body. | 97. The method of claim 3 , comprising controlling scaling of the detecting and controlling to generate coincidence between virtual space and physical space, wherein the virtual space comprises space depicted on a display device coupled to the computer, wherein the physical space comprises space inhabited by the body. 98. The method of claim 97 , comprising determining dimensions, orientations, and positions in the physical space of the display device. | 0.741848 |
11. The computer program product of claim 10 , wherein the extracted image format includes extracted information associated with the extracted at least one table or at least one chart. | 11. The computer program product of claim 10 , wherein the extracted image format includes extracted information associated with the extracted at least one table or at least one chart. 12. The computer program product of claim 11 , wherein the extracted information comprises at least one of a data label, a header, a footer, a legend, an overlay, a data value or numeral, a unit, a line or an axis, a shape, a length, a proportion, and an angle. | 0.936453 |
1. A method, comprising: receiving, by a computing device, a target image of a target biological cell having a target phenotype; obtaining, by the computing device, a semantic embedding associated with the target image, wherein the semantic embedding associated with the target image is generated using a machine-learned, deep metric network model; obtaining, by the computing device for each of a plurality of candidate images of candidate biological cells each having a respective candidate phenotype, a semantic embedding associated with the respective candidate image, wherein the semantic embedding associated with the respective candidate image is generated using the machine-learned, deep metric network model; determining, by the computing device, a similarity score for each candidate image, wherein determining the similarity score for a respective candidate image comprises computing, by the computing device, a vector distance in a multi-dimensional space described by the semantic embeddings between the respective candidate image and the target image, and wherein the similarity score for each candidate image represents a degree of similarity between the target phenotype and the respective candidate phenotype; determining, by the computing device, a threshold similarity score; and determining, by the computing device, those candidate images having similarity scores that satisfy the threshold similarity score, wherein the target phenotype is a healthy phenotype, wherein the candidate images having similarity scores that satisfy the threshold similarity score have respective candidate phenotypes corresponding to the healthy phenotype, and wherein those candidate images having similarity scores that do not satisfy the threshold similarity score have respective candidate phenotypes corresponding to an unhealthy phenotype. | 1. A method, comprising: receiving, by a computing device, a target image of a target biological cell having a target phenotype; obtaining, by the computing device, a semantic embedding associated with the target image, wherein the semantic embedding associated with the target image is generated using a machine-learned, deep metric network model; obtaining, by the computing device for each of a plurality of candidate images of candidate biological cells each having a respective candidate phenotype, a semantic embedding associated with the respective candidate image, wherein the semantic embedding associated with the respective candidate image is generated using the machine-learned, deep metric network model; determining, by the computing device, a similarity score for each candidate image, wherein determining the similarity score for a respective candidate image comprises computing, by the computing device, a vector distance in a multi-dimensional space described by the semantic embeddings between the respective candidate image and the target image, and wherein the similarity score for each candidate image represents a degree of similarity between the target phenotype and the respective candidate phenotype; determining, by the computing device, a threshold similarity score; and determining, by the computing device, those candidate images having similarity scores that satisfy the threshold similarity score, wherein the target phenotype is a healthy phenotype, wherein the candidate images having similarity scores that satisfy the threshold similarity score have respective candidate phenotypes corresponding to the healthy phenotype, and wherein those candidate images having similarity scores that do not satisfy the threshold similarity score have respective candidate phenotypes corresponding to an unhealthy phenotype. 13. The method of claim 1 , wherein the target biological cell was acquired from a first anatomical region of a patient during a biopsy, and wherein the candidate biological cells comprise biological cells acquired from anatomical regions of the patient during the biopsy other than the first anatomical region. | 0.707822 |
16. The computer readable medium of claim 15 , wherein said XML entity is a local element declaration and wherein said computer-executable instructions further cause said computing device to: determine an original type of said local element declaration; create a derived type based on said original type; and change the type of said local element declaration from said original type to said derived type. | 16. The computer readable medium of claim 15 , wherein said XML entity is a local element declaration and wherein said computer-executable instructions further cause said computing device to: determine an original type of said local element declaration; create a derived type based on said original type; and change the type of said local element declaration from said original type to said derived type. 17. The computer readable medium of claim 16 , wherein said rendering option further specifies a target namespace for said additional attribute and wherein said computer-executable instructions further cause said computing device to, if said target namespace for said additional attribute is null or the same as a target namespace of said derived type, add to said derived type a local attribute declaration having said specified attribute name and said specified attribute value. | 0.839395 |
11. A system for speech recognition, comprising: a speech recognition engine configured to generate a set of likely hypotheses using a speech recognition method for recognizing speech; a unified language model including a semantic language model and a lexical language model configured for rescoring the likely hypotheses to improve recognition results by using sentence-based semantic content and lexical content wherein the unified language model is trained by including a unigram feature, a bigram feature, a trigram feature, a current active parent label (Li), a number of tokens (Ni) to the left since current parent label (Li) starts, a previous closed constituent label (Oi), a number of tokens (Mi) to the left after the previous closed constituent label finishes, and a number of questions to classify parser tree entries, wherein the questions include a default, (wj−1), (wj−1, wj−2), (Li), (Li,Ni), (Li,Ni, wj−1), and (Oi,Mi), where w represents a word and j is and index representing word position to compute word probabilities; and the speech recognition engine configured to score parse trees to identify a best sentence according to the sentences' parse tree by employing semantic information and lexical information in the parse tree to clarify the recognized speech. | 11. A system for speech recognition, comprising: a speech recognition engine configured to generate a set of likely hypotheses using a speech recognition method for recognizing speech; a unified language model including a semantic language model and a lexical language model configured for rescoring the likely hypotheses to improve recognition results by using sentence-based semantic content and lexical content wherein the unified language model is trained by including a unigram feature, a bigram feature, a trigram feature, a current active parent label (Li), a number of tokens (Ni) to the left since current parent label (Li) starts, a previous closed constituent label (Oi), a number of tokens (Mi) to the left after the previous closed constituent label finishes, and a number of questions to classify parser tree entries, wherein the questions include a default, (wj−1), (wj−1, wj−2), (Li), (Li,Ni), (Li,Ni, wj−1), and (Oi,Mi), where w represents a word and j is and index representing word position to compute word probabilities; and the speech recognition engine configured to score parse trees to identify a best sentence according to the sentences' parse tree by employing semantic information and lexical information in the parse tree to clarify the recognized speech. 14. The system as recited in claim 11 , wherein the semantic language model includes one or more of relative labels, token numbers, and answers to questions related to word order or placement. | 0.577228 |
4. A handheld electronic device comprising: a processor; and a memory storing a plurality of language objects and a number of routines which, when executed on the processor, cause the handheld electronic device to perform operations comprising: detecting input of a set of characters; determining that at least a first language object and a second language object each correspond with at least a portion of the set of characters, one of the first language object and the second language object being associated with a frequency value higher than the frequency value with which the other of the first language object and the second language object is associated; making a determination that the first and second language objects are in a special category, the special category including word objects stored in the memory that correspond to a particular ambiguous input sequence and are of a same length; and responsive to said making a determination, maintaining the one of the first language object and the second language object associated with a frequency value higher than the frequency value with which the other of the first language object and the second language object is associated. | 4. A handheld electronic device comprising: a processor; and a memory storing a plurality of language objects and a number of routines which, when executed on the processor, cause the handheld electronic device to perform operations comprising: detecting input of a set of characters; determining that at least a first language object and a second language object each correspond with at least a portion of the set of characters, one of the first language object and the second language object being associated with a frequency value higher than the frequency value with which the other of the first language object and the second language object is associated; making a determination that the first and second language objects are in a special category, the special category including word objects stored in the memory that correspond to a particular ambiguous input sequence and are of a same length; and responsive to said making a determination, maintaining the one of the first language object and the second language object associated with a frequency value higher than the frequency value with which the other of the first language object and the second language object is associated. 5. The handheld electronic device of claim 4 , wherein the operations further comprise: outputting a default output and a number of variant outputs in order of decreasing frequency value, the default output comprising the one of the first language object and the second language object, the number of variants comprising the other of the first language object and the second language object. | 0.5 |
1. A computer-implemented method for predicting security threat attacks, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying candidate security threat targets with latent attributes that describe features of the candidate security threat targets; identifying historical attack data that describes which of the candidate security threat targets experienced an actual security threat attack; determining, by a software security prediction program, a similarity relationship between latent attributes of at least one specific candidate security threat target and latent attributes of the candidate security threat targets that experienced the actual security threat attack according to the historical attack data by analyzing a matrix that indicates that the actual security threat attack targeted the candidate security threat targets by populating a respective entry of the matrix at each intersection between a vector of the matrix that corresponds to the actual security threat attack and each vector of the matrix that corresponds to the candidate security threat targets that experienced the actual security threat attack; predicting by the software security prediction program based on the determined similarity relationship, that the specific candidate security threat target will experience a future security threat attack; and performing, by the software security prediction program, at least one remedial action to protect the specific candidate security threat target in response to predicting the future security threat attack, wherein the candidate security threat targets comprise enterprise organizations that include customers of a vendor of the software security prediction program. | 1. A computer-implemented method for predicting security threat attacks, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying candidate security threat targets with latent attributes that describe features of the candidate security threat targets; identifying historical attack data that describes which of the candidate security threat targets experienced an actual security threat attack; determining, by a software security prediction program, a similarity relationship between latent attributes of at least one specific candidate security threat target and latent attributes of the candidate security threat targets that experienced the actual security threat attack according to the historical attack data by analyzing a matrix that indicates that the actual security threat attack targeted the candidate security threat targets by populating a respective entry of the matrix at each intersection between a vector of the matrix that corresponds to the actual security threat attack and each vector of the matrix that corresponds to the candidate security threat targets that experienced the actual security threat attack; predicting by the software security prediction program based on the determined similarity relationship, that the specific candidate security threat target will experience a future security threat attack; and performing, by the software security prediction program, at least one remedial action to protect the specific candidate security threat target in response to predicting the future security threat attack, wherein the candidate security threat targets comprise enterprise organizations that include customers of a vendor of the software security prediction program. 5. The method of claim 1 , wherein determining the similarity relationship comprises: identifying an additional candidate security threat target that stored a cluster of benign files and that experienced a same security threat attack as the predicted future security threat attack; and determining that the specific candidate security threat target also stored the cluster of benign files. | 0.555032 |
9. A computer system for rendering graphics for display on a display screen, the computer system comprising: at least one processing unit; and at least one memory communicatively coupled to the at least one processing unit and storing computer readable instructions that when executed by the at least one processor perform a method, comprising: receiving selection of a first graphic definition for rendering a first graphical hierarchical diagram, the first graphic definition specifying a first graphical element; in response to the selection of the first graphic definition, rendering the first graphical element within the first graphical hierarchical diagram in a drawing pane on the display device; receiving content text within the first graphical element; receiving a first customization to a presentation property of the first graphical element; updating the presentation property of the first graphical element with the first customization; receiving a second customization to a semantic property of the first graphical element; updating the semantic property of the first graphical element with the second customization; receiving a selection of a second graphic definition; and in response to the selection of the second graphic definition, rendering a second graphical hierarchical diagram comprising a second graphical element that includes the content text and the updated semantic property but not the updated presentation property. | 9. A computer system for rendering graphics for display on a display screen, the computer system comprising: at least one processing unit; and at least one memory communicatively coupled to the at least one processing unit and storing computer readable instructions that when executed by the at least one processor perform a method, comprising: receiving selection of a first graphic definition for rendering a first graphical hierarchical diagram, the first graphic definition specifying a first graphical element; in response to the selection of the first graphic definition, rendering the first graphical element within the first graphical hierarchical diagram in a drawing pane on the display device; receiving content text within the first graphical element; receiving a first customization to a presentation property of the first graphical element; updating the presentation property of the first graphical element with the first customization; receiving a second customization to a semantic property of the first graphical element; updating the semantic property of the first graphical element with the second customization; receiving a selection of a second graphic definition; and in response to the selection of the second graphic definition, rendering a second graphical hierarchical diagram comprising a second graphical element that includes the content text and the updated semantic property but not the updated presentation property. 10. The computer system of claim 9 , wherein the first graphical hierarchical diagram and the second hierarchical diagram are selected from the group consisting of: a wheel diagram and a pyramid diagram. | 0.614203 |
10. One or more computer storage media having a system embodied thereon including computer-executable instructions that, when executed, perform a method for identifying query rewriting replacement terms, the system comprising: an intake component that receives a list of related string pairs, each pair comprising a first string and a second string, wherein the first string of each related string pair is a user search query extracted from user click log data, the user click log data including one or more search query sessions including at least one dwell time associated with one or more search results and a number of links clicked; a statistical machine translation model that, for one or more of the related string pairs: receives the string pair as inputs, identifies one or more pairs of corresponding terms, each pair of corresponding terms including a first term from the first string and a second term from the second string, and calculates a probability of relatedness for each of the one or more pairs of corresponding terms; a characterization component that, upon determining that the probability of relatedness of a pair of corresponding terms calculated by the statistical machine translation model exceeds a threshold, characterizes the second term as a query term replacement for the first term; and a candidate term population component that, for each pair of corresponding terms for which the calculated probability of relatedness exceeds a threshold, incorporates the first term, the second term, and the probability of relatedness for the pair into a query rewriting candidate database. | 10. One or more computer storage media having a system embodied thereon including computer-executable instructions that, when executed, perform a method for identifying query rewriting replacement terms, the system comprising: an intake component that receives a list of related string pairs, each pair comprising a first string and a second string, wherein the first string of each related string pair is a user search query extracted from user click log data, the user click log data including one or more search query sessions including at least one dwell time associated with one or more search results and a number of links clicked; a statistical machine translation model that, for one or more of the related string pairs: receives the string pair as inputs, identifies one or more pairs of corresponding terms, each pair of corresponding terms including a first term from the first string and a second term from the second string, and calculates a probability of relatedness for each of the one or more pairs of corresponding terms; a characterization component that, upon determining that the probability of relatedness of a pair of corresponding terms calculated by the statistical machine translation model exceeds a threshold, characterizes the second term as a query term replacement for the first term; and a candidate term population component that, for each pair of corresponding terms for which the calculated probability of relatedness exceeds a threshold, incorporates the first term, the second term, and the probability of relatedness for the pair into a query rewriting candidate database. 14. The media of claim 10 , wherein the second string of each related string pair is identified by analyzing the user click log data. | 0.553927 |
13. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device, cause the device to: provide, at the user device, a graphical user interface including an at least partially speech-based conversational interface for interacting with the user, the graphical user interface displaying at least a portion of a conversational interaction between the user and the user device, the graphical user interface displaying at least a portion of a conversational interaction between the user and the user device; obtain context information associated with an interaction between the user and the user device; receive a speech input from the user through the conversational interface; process the speech input to determine a user intent associated with the speech input; and upon determination that the user intent associated with the speech input is for invoking a software application installed on the user device: invoke the software application on the user device external to the graphical user interface including the conversational interface; and provide a response based on the user intent and the context information. | 13. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device, cause the device to: provide, at the user device, a graphical user interface including an at least partially speech-based conversational interface for interacting with the user, the graphical user interface displaying at least a portion of a conversational interaction between the user and the user device, the graphical user interface displaying at least a portion of a conversational interaction between the user and the user device; obtain context information associated with an interaction between the user and the user device; receive a speech input from the user through the conversational interface; process the speech input to determine a user intent associated with the speech input; and upon determination that the user intent associated with the speech input is for invoking a software application installed on the user device: invoke the software application on the user device external to the graphical user interface including the conversational interface; and provide a response based on the user intent and the context information. 24. The computer readable storage medium of claim 13 , wherein displaying at least a portion of the conversational interaction includes displaying a paraphrase of user input. | 0.799145 |
28. The system of claim 24, further comprising a NetWare Core Protocol API, also known as the NCP API, wherein the driver is also capable of translating a relational database language statement into an executable NCP API sequence that includes a call to a callable element of the NCP API and produces an NCP API result, and the driver is also capable of translating the NCP API result into a relational database result. | 28. The system of claim 24, further comprising a NetWare Core Protocol API, also known as the NCP API, wherein the driver is also capable of translating a relational database language statement into an executable NCP API sequence that includes a call to a callable element of the NCP API and produces an NCP API result, and the driver is also capable of translating the NCP API result into a relational database result. 51. The system of claim 28, wherein the directory services repository component includes an attribute, the relational database language statement identifies a column of a table, and the drive and the API together map the attribute to the column. | 0.825247 |
11. 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, at an Internet search system, a search query; receiving multiple search results, each of the search results identifying an Internet resource indexed by the search system that satisfies the query; determining that the search query matches a name of a user that submitted the search query; providing, in response to the search query, a ranking of one or more of the search results and a personal knowledge panel comprising one or more items of user-provided information about the user, wherein the personal knowledge panel includes multiple input fields for updating the user-provided information of the knowledge panel; receiving updated user information that was provided using the input fields of the personal knowledge panel; and associating the updated user information with an account of the user. | 11. 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, at an Internet search system, a search query; receiving multiple search results, each of the search results identifying an Internet resource indexed by the search system that satisfies the query; determining that the search query matches a name of a user that submitted the search query; providing, in response to the search query, a ranking of one or more of the search results and a personal knowledge panel comprising one or more items of user-provided information about the user, wherein the personal knowledge panel includes multiple input fields for updating the user-provided information of the knowledge panel; receiving updated user information that was provided using the input fields of the personal knowledge panel; and associating the updated user information with an account of the user. 19. The system of claim 11 , wherein receiving updated user information that was provided using the input fields of the personal knowledge panel comprises receiving an indication of visibility that is specific to an item of the updated user information. | 0.705993 |
5. A method, comprising: retrieving, by a processor, a plurality of advertisements from multiple content sources; identifying, by the processor, keywords of the plurality of advertisements; determining, by the processor, similarity rankings of the advertisements based at least in part on the keywords; selecting, by the processor, a keyword based at least in part on the similarity rankings; and purchasing, by the processor, the keyword from a seller for placement of a first linked advertisement, the first linked advertisement configured to be selected to cause the presentation of a second advertisement of a buyer. | 5. A method, comprising: retrieving, by a processor, a plurality of advertisements from multiple content sources; identifying, by the processor, keywords of the plurality of advertisements; determining, by the processor, similarity rankings of the advertisements based at least in part on the keywords; selecting, by the processor, a keyword based at least in part on the similarity rankings; and purchasing, by the processor, the keyword from a seller for placement of a first linked advertisement, the first linked advertisement configured to be selected to cause the presentation of a second advertisement of a buyer. 13. The method of claim 5 , further comprising: counting a number of advertisements within a specified similarity ranking to select the keyword. | 0.731747 |
8. A system for transparent data loss prevention classifications, the system comprising: an identification module programmed to identify a document that received a classification by a machine learning classifier for data loss prevention; a constituent module programmed to identify at least one linguistic constituent within the document that contributed to the classification; a contextualization module programmed to identify a relevant passage of the document that contextualizes the linguistic constituent; a interface module programmed to: display a user interface comprising the linguistic constituent in context of the relevant passage; receive user input via the user interface indicating a type of mistake, selected via the user interface from a plurality of types of mistakes, that potentially caused the machine learning classifier to misclassify the document, wherein indicating the type of mistake that potentially caused the machine learning classifier to misclassify the document comprises indicating a basis of classification relied upon by the machine learning classifier that resulted in the machine learning classifier misclassifying the document; at least one processor configured to execute the identification module, the constituent module, the contextualization module, and the interface module. | 8. A system for transparent data loss prevention classifications, the system comprising: an identification module programmed to identify a document that received a classification by a machine learning classifier for data loss prevention; a constituent module programmed to identify at least one linguistic constituent within the document that contributed to the classification; a contextualization module programmed to identify a relevant passage of the document that contextualizes the linguistic constituent; a interface module programmed to: display a user interface comprising the linguistic constituent in context of the relevant passage; receive user input via the user interface indicating a type of mistake, selected via the user interface from a plurality of types of mistakes, that potentially caused the machine learning classifier to misclassify the document, wherein indicating the type of mistake that potentially caused the machine learning classifier to misclassify the document comprises indicating a basis of classification relied upon by the machine learning classifier that resulted in the machine learning classifier misclassifying the document; at least one processor configured to execute the identification module, the constituent module, the contextualization module, and the interface module. 9. The system of claim 8 , wherein the interface module is further programmed to provide, via the user interface, a selection element for selecting from the plurality of types of mistakes in response to receiving user input via the user interface indicating that the machine learning classifier misclassified the document. | 0.633429 |
11. A computer program product comprising a computer-readable medium storing computer executable instructions which, when executed by one or more processors, cause said one or more processors to provide a method of providing secure credentials for accessing a target resource comprising: receiving a connection request to the target resource from an unattended requestor application, the connection request including target resource information identifying the target resource and configuration information necessary to authenticate the requestor application, wherein the configuration information of the requestor application is fingerprint information, which uniquely identifies a node of the requestor application; decoding the request to extract the target resource information and the configuration information required by a credential manager to authenticate the requestor application and to retrieve the secure credentials for accessing the target resource, the credential manager managing and storing credentials for the target resource; securely communicating the extracted information to the credential manager; based on the extracted information, authenticating, by the credential manager, the requestor application and in response to the success of the authentication retrieving, by the credential manager, corresponding one or more credential for accessing the target resource; generating a native database connection request to the target resource, including the retrieved credential; and passing the native database connection request to the native database connectivity component to establish the connection. | 11. A computer program product comprising a computer-readable medium storing computer executable instructions which, when executed by one or more processors, cause said one or more processors to provide a method of providing secure credentials for accessing a target resource comprising: receiving a connection request to the target resource from an unattended requestor application, the connection request including target resource information identifying the target resource and configuration information necessary to authenticate the requestor application, wherein the configuration information of the requestor application is fingerprint information, which uniquely identifies a node of the requestor application; decoding the request to extract the target resource information and the configuration information required by a credential manager to authenticate the requestor application and to retrieve the secure credentials for accessing the target resource, the credential manager managing and storing credentials for the target resource; securely communicating the extracted information to the credential manager; based on the extracted information, authenticating, by the credential manager, the requestor application and in response to the success of the authentication retrieving, by the credential manager, corresponding one or more credential for accessing the target resource; generating a native database connection request to the target resource, including the retrieved credential; and passing the native database connection request to the native database connectivity component to establish the connection. 18. The computer program product of claim 11 , wherein the functional modules comprise Open Database Connectivity (ODBC) APIs. | 0.519733 |
7. A method performed by one or more server devices, the method comprising: providing, by at least one of the one or more server devices and in a document, un-secure content and a reference associated with secure content, the un-secure content and the reference being included in a web feed, the secure content including at least one of text content, image content, or video content; sending, by at least one of the one or more server devices, a request for the secure content based on selection of the reference by a client device, the request being sent to a device associated with the secure content; receiving, by at least one of the one or more server devices, authentication information associated with the secure content after sending the request for the secure content, the authentication information being received from the client device, the authentication information identifying a user of the client device; sending, by at least one of the one or more server devices, the authentication information to the device associated with the secure content, the authentication information being sent to the device, associated with the secure content, to authenticate the user; receiving, by at least one of the one or more server devices, the secure content based on sending the authentication information to the device to authenticate the user, the secure content being received from the device associated with the secure content; and replacing, by at least one of the one or more server devices and in the document, the reference with the received secure content, replacing the reference including: replacing the reference with the at least one of the text content, the image content, or the video content to provide the at least one of the text content, the image content, or the video content within the document. | 7. A method performed by one or more server devices, the method comprising: providing, by at least one of the one or more server devices and in a document, un-secure content and a reference associated with secure content, the un-secure content and the reference being included in a web feed, the secure content including at least one of text content, image content, or video content; sending, by at least one of the one or more server devices, a request for the secure content based on selection of the reference by a client device, the request being sent to a device associated with the secure content; receiving, by at least one of the one or more server devices, authentication information associated with the secure content after sending the request for the secure content, the authentication information being received from the client device, the authentication information identifying a user of the client device; sending, by at least one of the one or more server devices, the authentication information to the device associated with the secure content, the authentication information being sent to the device, associated with the secure content, to authenticate the user; receiving, by at least one of the one or more server devices, the secure content based on sending the authentication information to the device to authenticate the user, the secure content being received from the device associated with the secure content; and replacing, by at least one of the one or more server devices and in the document, the reference with the received secure content, replacing the reference including: replacing the reference with the at least one of the text content, the image content, or the video content to provide the at least one of the text content, the image content, or the video content within the document. 9. The method of claim 7 , further comprising: receiving the web feed, where providing the un-secure content and the reference includes providing, in the document, a plurality of entries associated with the received web feed, where each of the plurality of entries includes a respective reference associated with different secure content, and where the plurality of references include the provided reference. | 0.586575 |
3. A computing system configured to manage services provided to users, the system comprising: one or more computer processors; one or more communications links configured to communicate with a billing and content server and with a hotel property management system; a subscriber interface configured to provide a subscriber computer with access to at least one network and to adapt to the subscriber computer to facilitate communications between the subscriber computer and the at least one network; and an XML processing module, configured to cause the one or more computer processors to perform operations comprising: receiving an XML command from the billing and content server; parsing the XML command to determine a type of operation requested by the billing and content server and to determine a user associated with the XML command; transmitting data, in a format specific to the hotel property management system, to the hotel property management system to authorize and bill an account associated with the user in accordance with data in the XML command; receiving an authorization result from the hotel property management system; and transmitting an XML response to the billing and content server, the XML response comprising a confirmation identifier based on the authorization result. | 3. A computing system configured to manage services provided to users, the system comprising: one or more computer processors; one or more communications links configured to communicate with a billing and content server and with a hotel property management system; a subscriber interface configured to provide a subscriber computer with access to at least one network and to adapt to the subscriber computer to facilitate communications between the subscriber computer and the at least one network; and an XML processing module, configured to cause the one or more computer processors to perform operations comprising: receiving an XML command from the billing and content server; parsing the XML command to determine a type of operation requested by the billing and content server and to determine a user associated with the XML command; transmitting data, in a format specific to the hotel property management system, to the hotel property management system to authorize and bill an account associated with the user in accordance with data in the XML command; receiving an authorization result from the hotel property management system; and transmitting an XML response to the billing and content server, the XML response comprising a confirmation identifier based on the authorization result. 8. The computing system of claim 3 , wherein the XML command comprises an identifier of a hotel room number associated with the user, and wherein the data in the format specific to the hotel property management system comprises an identifier of a hotel room number based on the hotel room number included in the XML command. | 0.657225 |
15. A non-transitory computer-readable medium containing instructions for submitting and checking a password without additional input, the non-transitory computer-readable medium comprising: instructions for presenting a password entry form to a user, the password entry form having a text field for entering a password; wherein the password entry form is configured to accept passwords of variable length; instructions for detecting text input from the user; instructions for, in response to detecting the text input from the user, displaying text characters in the text field; instructions for, in response to the user entering text characters in the text field, submitting the contents of the text field for password verification; wherein the instructions for submitting the contents of the text field for password verification include instructions for submitting the contents of the text field for password verification without additional user input besides the user entering text characters in the text field; wherein the instructions for the submitting the contents of the text field for password verification further include instructions for submitting the contents of the text field for password verification before the user has completed entry of the password in the text field; instructions for determining that a password submitted for verification is not a correct password of the user and denying access to a protected computer resource; instructions for determining that a password submitted for verification is a correct password of the user, logging in the user to provide access to the protected computer resource, and notifying the user that he or she is logged in; instructions for determining whether a password submitted for verification is correct or not in parallel with continuing to receive text input from the user and updating the contents of the text field in response to the received text input. | 15. A non-transitory computer-readable medium containing instructions for submitting and checking a password without additional input, the non-transitory computer-readable medium comprising: instructions for presenting a password entry form to a user, the password entry form having a text field for entering a password; wherein the password entry form is configured to accept passwords of variable length; instructions for detecting text input from the user; instructions for, in response to detecting the text input from the user, displaying text characters in the text field; instructions for, in response to the user entering text characters in the text field, submitting the contents of the text field for password verification; wherein the instructions for submitting the contents of the text field for password verification include instructions for submitting the contents of the text field for password verification without additional user input besides the user entering text characters in the text field; wherein the instructions for the submitting the contents of the text field for password verification further include instructions for submitting the contents of the text field for password verification before the user has completed entry of the password in the text field; instructions for determining that a password submitted for verification is not a correct password of the user and denying access to a protected computer resource; instructions for determining that a password submitted for verification is a correct password of the user, logging in the user to provide access to the protected computer resource, and notifying the user that he or she is logged in; instructions for determining whether a password submitted for verification is correct or not in parallel with continuing to receive text input from the user and updating the contents of the text field in response to the received text input. 16. The non-transitory computer-readable medium of claim 15 , further comprising instructions for determining that a threshold time has elapsed from the most recent entry of a text character in the text field before, in response to the user entering text characters in the text field, submitting the contents of the text field for password verification. | 0.78259 |
1. A system for facilitating cognitive processing of simultaneous remote voice conversations, comprising: a communication module configured to receive a plurality of remote voice conversations between distributed participants provided over a shared communications channel; a floor module to identify from within the remote voice conversations each of a main conversation between at least two of the distributed participants and one or more subconversations between at least two other of the distributed participants; an identification module to define segments of interest to one of the distributed participants comprising a conversation excerpt having a lower attention activation threshold for the one distributed participant; an analysis module to parse each of the subconversations into live conversation excerpts and to compare the live conversation excerpts to the segments of interest; a gap prediction module to continually monitor the main conversation and to predict one or more gaps between conversation flow in the main conversation; and an injection module to selectively inject the live conversation excerpts into the gaps of the main conversation as provided to the one distributed participant over the shared communications channel. | 1. A system for facilitating cognitive processing of simultaneous remote voice conversations, comprising: a communication module configured to receive a plurality of remote voice conversations between distributed participants provided over a shared communications channel; a floor module to identify from within the remote voice conversations each of a main conversation between at least two of the distributed participants and one or more subconversations between at least two other of the distributed participants; an identification module to define segments of interest to one of the distributed participants comprising a conversation excerpt having a lower attention activation threshold for the one distributed participant; an analysis module to parse each of the subconversations into live conversation excerpts and to compare the live conversation excerpts to the segments of interest; a gap prediction module to continually monitor the main conversation and to predict one or more gaps between conversation flow in the main conversation; and an injection module to selectively inject the live conversation excerpts into the gaps of the main conversation as provided to the one distributed participant over the shared communications channel. 4. A system according to claim 1 , wherein the segments of interest are selected from the group comprising parts of words, words, sentence fragments, sentences, and sounds. | 0.63604 |
2. A system according to claim 1 , further comprising: a similarity module to determine a similarity between each candidate seed document and each of the one or more cluster centers based on the comparison. | 2. A system according to claim 1 , further comprising: a similarity module to determine a similarity between each candidate seed document and each of the one or more cluster centers based on the comparison. 3. A system according to claim 2 , wherein the similarity is determined as an inner product of the candidate seed document and the cluster center. | 0.962988 |
6. The method of claim 1 , where: evolving the baseline network model over time comprises analyzing an overlapping, moving window of network activity. | 6. The method of claim 1 , where: evolving the baseline network model over time comprises analyzing an overlapping, moving window of network activity. 7. The method of claim 6 , further comprising: aggregating results from analyzing the moving window into the baseline network model to capture the changes in the expected nominal operational profile of the enterprise network. | 0.924113 |
13. The non-transitory computer readable data storage medium article of manufacture of claim 1 , wherein tagging the interaction record with user-generated descriptions of content includes: labeling the interaction record with a first classification scheme; and rating the first classification scheme. | 13. The non-transitory computer readable data storage medium article of manufacture of claim 1 , wherein tagging the interaction record with user-generated descriptions of content includes: labeling the interaction record with a first classification scheme; and rating the first classification scheme. 15. The non-transitory computer readable data storage medium article of manufacture of claim 13 , wherein the method further comprises: sending a message to a user based upon the first classification scheme of the interaction record. | 0.900123 |
6. The method of claim 1 , wherein the session is a first session, wherein the language is a first language, wherein the desired display language is a first desired display language, and further comprising: associating, by the processor, the first session with the first language and the first desired display language; initiating, by the processor, the second session of electronic communications prior to a termination of the first session; and associating, by the processor, the second session with a second language and a second desired display language. | 6. The method of claim 1 , wherein the session is a first session, wherein the language is a first language, wherein the desired display language is a first desired display language, and further comprising: associating, by the processor, the first session with the first language and the first desired display language; initiating, by the processor, the second session of electronic communications prior to a termination of the first session; and associating, by the processor, the second session with a second language and a second desired display language. 7. The method of claim 6 , wherein the translated incoming electronic communication is a first translated incoming electronic communication, and further comprising: associating, by the processor, the first translated incoming electronic communication with the first session; associating, by the processor, a second translated incoming electronic communication with the second session; retrieving, by the processor, a first text-to-speech engine from the translation service computer corresponding to the first desired display language; retrieving, by the processor, a second text-to-speech engine from the translation service computer corresponding to the second desired display language; converting, by the processor, the first translated incoming electronic communication to a first computer vocalization using the first text-to-speech engine; audibly reciting, by the processor, the first translated incoming electronic communication in the first desired display language; converting, by the processor, the second translated incoming electronic communication to a second computer vocalization using the second text-to-speech engine; and audibly reciting, by the processor, the second translated incoming electronic communication in the second desired display language. | 0.667609 |
11. An image forming device comprising: one or more processors; and a memory communicatively coupled to the one or more processors, the memory storing instructions which, when processed by one or more processors, causes: authenticating user data received by the image forming device, wherein the user data corresponds to a particular user; determining electronic document data to be processed, retrieving, from a plurality of user preference data, particular user preference data that is specific to the user data and which specifies one or more types of content and one or more actions to be performed on each type of content, searching the electronic document data to identify, in the electronic document data, content of one or more types that match the one or more types of content specified by the particular user preference data that is specific to the user data and which specifies the one or more types of content and the one or more actions to be performed on each type of content, and automatically processing the electronic document data based upon the particular user preference data that is specific to the user data and which specifies the one or more types of content and the one or more actions to be performed on each type of content and generate processed electronic document data by changing, in the electronic document data, one or more of one or more color values and one or more consumable values for one or more consumable resources of the content of one or more types that match the one or more types of content specified by the particular user preference data. | 11. An image forming device comprising: one or more processors; and a memory communicatively coupled to the one or more processors, the memory storing instructions which, when processed by one or more processors, causes: authenticating user data received by the image forming device, wherein the user data corresponds to a particular user; determining electronic document data to be processed, retrieving, from a plurality of user preference data, particular user preference data that is specific to the user data and which specifies one or more types of content and one or more actions to be performed on each type of content, searching the electronic document data to identify, in the electronic document data, content of one or more types that match the one or more types of content specified by the particular user preference data that is specific to the user data and which specifies the one or more types of content and the one or more actions to be performed on each type of content, and automatically processing the electronic document data based upon the particular user preference data that is specific to the user data and which specifies the one or more types of content and the one or more actions to be performed on each type of content and generate processed electronic document data by changing, in the electronic document data, one or more of one or more color values and one or more consumable values for one or more consumable resources of the content of one or more types that match the one or more types of content specified by the particular user preference data. 20. The image forming device recited in claim 11 , wherein the instructions include additional instructions which, when processed by the one or more processors, causes, based upon workflow preference data contained in the user preference data, workflow optimization to be performed on the processed electronic document data. | 0.782172 |
5. The method of claim 4 , wherein the collected horizontal sets of pixels are combined into bi-level regions. | 5. The method of claim 4 , wherein the collected horizontal sets of pixels are combined into bi-level regions. 6. The method of claim 5 , wherein pixels associated with a foreground color are distinguished from pixels from a background color, in response to determining that a bi-level region contains text. | 0.880316 |
19. A non-transitory computer-readable storage medium having stored thereon a computer-executable program that when executed directs a computing system to, at least: receive a query from a searching entity; submit the query to a plurality of search indexes, each search index corresponding to a respective category of items, at least one of the plurality of search indexes utilizing at least one of a different ranking property, scale, function, or definition for ranking items relative to other search indexes; receive one of a plurality of search index result sets from each of the plurality of search indexes in response to the query; determine a plurality of appropriateness scores each corresponding to one of the plurality of search indexes, each of the plurality of appropriateness scores indicating an appropriateness of the category of items corresponding to the respective search index with respect to the query and being based at least in part on historical queries similar to the query that were submitted to the respective search index; determine a universal item score for each of a plurality of items in the plurality of search index result sets at least in part by normalizing the at least one of the different ranking property, scale, function, and definition to a ranking scale common to all the search index result sets; for each of the plurality of items, determine a probability that the item satisfies the query based at least in part on the appropriateness score for the search index associated with the item and the universal item score for the item; include in the universal query result set ones of the plurality of items selected in an order based at least in part on the probabilities of the plurality of items satisfying the query; and provide the universal query result set to the searching entity, wherein determining the plurality of appropriateness scores comprises modifying the plurality of appropriateness scores differently based at least in part on different types of recorded actions associated with the historical queries that were submitted to a corresponding search index. | 19. A non-transitory computer-readable storage medium having stored thereon a computer-executable program that when executed directs a computing system to, at least: receive a query from a searching entity; submit the query to a plurality of search indexes, each search index corresponding to a respective category of items, at least one of the plurality of search indexes utilizing at least one of a different ranking property, scale, function, or definition for ranking items relative to other search indexes; receive one of a plurality of search index result sets from each of the plurality of search indexes in response to the query; determine a plurality of appropriateness scores each corresponding to one of the plurality of search indexes, each of the plurality of appropriateness scores indicating an appropriateness of the category of items corresponding to the respective search index with respect to the query and being based at least in part on historical queries similar to the query that were submitted to the respective search index; determine a universal item score for each of a plurality of items in the plurality of search index result sets at least in part by normalizing the at least one of the different ranking property, scale, function, and definition to a ranking scale common to all the search index result sets; for each of the plurality of items, determine a probability that the item satisfies the query based at least in part on the appropriateness score for the search index associated with the item and the universal item score for the item; include in the universal query result set ones of the plurality of items selected in an order based at least in part on the probabilities of the plurality of items satisfying the query; and provide the universal query result set to the searching entity, wherein determining the plurality of appropriateness scores comprises modifying the plurality of appropriateness scores differently based at least in part on different types of recorded actions associated with the historical queries that were submitted to a corresponding search index. 26. A non-transitory computer-readable storage medium according to claim 19 , wherein determining the plurality of appropriateness scores comprises determining the plurality of appropriateness scores based at least in part on how similar the historical queries submitted to a corresponding search index are to the query. | 0.552842 |
8. A system for suggesting a completion to text entered by a user on a computing device, the system comprising: at least one server computer comprising at least one processor and at least one memory, the at least one server computer configured to: receive, at the server, text of a message from a first computing device of a first user; compute a topic vector using the text of the message from the first computing device, wherein each element of the topic vector comprises a score corresponding to a topic of a plurality of topics; cause the message to be presented by a second computing device to a second user; receive text from the second computing device entered by the second user; compute a first feature vector using the topic vector and the text entered by the second user; identify a first plurality of characters to follow the text entered by the second user by processing, by the server, the first feature vector, wherein the first plurality of characters comprises a first character; compute a second feature vector using the topic vector and the first character; identify a second plurality of characters to follow the first character by processing, by the server, the second feature vector, wherein the second plurality of characters comprises a second character; generate a suggested completion to the text entered by the second user, the suggested completion comprising the first character and the second character, and transmit the suggested completion to the second computing device for presenting to the second user. | 8. A system for suggesting a completion to text entered by a user on a computing device, the system comprising: at least one server computer comprising at least one processor and at least one memory, the at least one server computer configured to: receive, at the server, text of a message from a first computing device of a first user; compute a topic vector using the text of the message from the first computing device, wherein each element of the topic vector comprises a score corresponding to a topic of a plurality of topics; cause the message to be presented by a second computing device to a second user; receive text from the second computing device entered by the second user; compute a first feature vector using the topic vector and the text entered by the second user; identify a first plurality of characters to follow the text entered by the second user by processing, by the server, the first feature vector, wherein the first plurality of characters comprises a first character; compute a second feature vector using the topic vector and the first character; identify a second plurality of characters to follow the first character by processing, by the server, the second feature vector, wherein the second plurality of characters comprises a second character; generate a suggested completion to the text entered by the second user, the suggested completion comprising the first character and the second character, and transmit the suggested completion to the second computing device for presenting to the second user. 13. The system of claim 8 , wherein the at least one server computer is configured to: present the suggested completion to the second user; receive a selection of the suggested completion by the second user; transmit a message to the first user, the transmitted message comprising the suggested completion. | 0.518217 |
7. An system for clustering a set of objects having object types, object attributes, homogeneous relationships between objects of the same object type, and heterogeneous relationships between objects having different object types, the system comprising: a programmable processor configured to: iteratively optimize a clustering of the set of objects within a plurality of latent classes, dependent on object types, object attributes, homogeneous relationships, and heterogeneous relationships, by performing, in an expectation step, wherein the programmable processor is configured to: update a set of posteriors to maximize a probability that an object is associated with a respective latent class, comprising, for each object, a substep to individually fix an assigned cluster for all other objects, and maximize an objective function for the respective object, comprising a substep to minimize a computational distance between an observation of the object attributes, homogeneous relationships, and heterogeneous relationships of a respective object and parameters of a corresponding expectation that the object is associated with the respective latent class, and repeat until no object changes in assigned cluster between successive repetition, and in a minimization step, updating the plurality of latent classes based on the updated set of posteriors; and store the optimized clustering in a memory; and a communications port configured to communicate at least one of an object and clustering-related information. | 7. An system for clustering a set of objects having object types, object attributes, homogeneous relationships between objects of the same object type, and heterogeneous relationships between objects having different object types, the system comprising: a programmable processor configured to: iteratively optimize a clustering of the set of objects within a plurality of latent classes, dependent on object types, object attributes, homogeneous relationships, and heterogeneous relationships, by performing, in an expectation step, wherein the programmable processor is configured to: update a set of posteriors to maximize a probability that an object is associated with a respective latent class, comprising, for each object, a substep to individually fix an assigned cluster for all other objects, and maximize an objective function for the respective object, comprising a substep to minimize a computational distance between an observation of the object attributes, homogeneous relationships, and heterogeneous relationships of a respective object and parameters of a corresponding expectation that the object is associated with the respective latent class, and repeat until no object changes in assigned cluster between successive repetition, and in a minimization step, updating the plurality of latent classes based on the updated set of posteriors; and store the optimized clustering in a memory; and a communications port configured to communicate at least one of an object and clustering-related information. 8. The system according to claim 7 , wherein the computational distance comprises a Bregman distance. | 0.784672 |
1. A method of processing an original data stream of digitized speech samples, comprising: converting a stream of digitized speech samples to a stream of text and associated reliability measures, the reliability measures indicating a level of confidence in the correctness of the speech to text conversion of the associated portions of the stream of text; and creating a mixed-media data stream comprising the stream of text as a text component and selected portions of the digitized stream of speech as a speech component, each selected portion corresponding to a portion of the stream of text having a reliability measure below a threshold. | 1. A method of processing an original data stream of digitized speech samples, comprising: converting a stream of digitized speech samples to a stream of text and associated reliability measures, the reliability measures indicating a level of confidence in the correctness of the speech to text conversion of the associated portions of the stream of text; and creating a mixed-media data stream comprising the stream of text as a text component and selected portions of the digitized stream of speech as a speech component, each selected portion corresponding to a portion of the stream of text having a reliability measure below a threshold. 2. The method of claim 1 of processing and transmitting speech, further comprising: transmitting the speech by transmitting the mixed-media data stream. | 0.693694 |
13. The apparatus of claim 12 further including a pair of voltage generators producing potentials greater in absolute value than any supply potential in response to one or another of said distinctive outputs of said multi-bit comparator, said multi-bit comparator is coupled to both said vital driving means, each said vital driving means producing said potential responsive to the corresponding multi-bit comparator output, each said vital driving means having a capacitively coupled output. | 13. The apparatus of claim 12 further including a pair of voltage generators producing potentials greater in absolute value than any supply potential in response to one or another of said distinctive outputs of said multi-bit comparator, said multi-bit comparator is coupled to both said vital driving means, each said vital driving means producing said potential responsive to the corresponding multi-bit comparator output, each said vital driving means having a capacitively coupled output. 14. The apparatus of claim 13 in which each said vital driving means is coupled to further logic means producing a distinctive signal if, and only if, both said vital driving means produce said DC potentials, said distinctive signal enabling said output means. | 0.874667 |
1. A method for enabling a developer of a steering application to associate semantic tags with user responses, the method comprising: obtaining user responses to an open-ended steering question posed by an interactive response system; automatically grouping the user responses into groups, wherein each group is a set of sentences that are semantically related; automatically assigning preliminary semantic tags to each of the groups; and providing a computer user interface that enables a user to validate the content of the groups to ensure that all sentences within a group have the same semantic meaning and to view and edit the preliminary semantic tags associated with the groups, wherein the computer user interface includes: a groups view that displays a list of the groups and corresponding semantic tags for each group, wherein the groups view enables a user to edit the preliminary semantic tags associated with each of the groups, a sentence view that displays, for a selected group in the groups view, a list of unique sentences associated with the selected group, wherein in the sentence view a user is able to verify whether or not a sentence belongs to the group selected in the groups view, and a related-groups view that displays, for a selected sentence in the sentence view, a plurality of groups most closely-related to the selected sentence, wherein the computer user interface enables the user to apply semantic clustering to unverified sentences, and wherein applying semantic clustering to unverified sentences re-distributes the unverified sentences into groups based at least in part on the group memberships of verified sentences. | 1. A method for enabling a developer of a steering application to associate semantic tags with user responses, the method comprising: obtaining user responses to an open-ended steering question posed by an interactive response system; automatically grouping the user responses into groups, wherein each group is a set of sentences that are semantically related; automatically assigning preliminary semantic tags to each of the groups; and providing a computer user interface that enables a user to validate the content of the groups to ensure that all sentences within a group have the same semantic meaning and to view and edit the preliminary semantic tags associated with the groups, wherein the computer user interface includes: a groups view that displays a list of the groups and corresponding semantic tags for each group, wherein the groups view enables a user to edit the preliminary semantic tags associated with each of the groups, a sentence view that displays, for a selected group in the groups view, a list of unique sentences associated with the selected group, wherein in the sentence view a user is able to verify whether or not a sentence belongs to the group selected in the groups view, and a related-groups view that displays, for a selected sentence in the sentence view, a plurality of groups most closely-related to the selected sentence, wherein the computer user interface enables the user to apply semantic clustering to unverified sentences, and wherein applying semantic clustering to unverified sentences re-distributes the unverified sentences into groups based at least in part on the group memberships of verified sentences. 17. The method of claim 1 , wherein the computer user interface enables the user to merge groups. | 0.61057 |
1. In a computing system environment, a method of differentiating files stored on one or more computing devices, each file having a plurality of symbols derived from an underlying data stream of all original bits of raw data of said each file, comprising: encoding said each file as a plurality of symbols representing an underlying data stream of all original bits of binary data of the file; determining a number of occurrences of each said symbol in said each file; and computing a distance between said each file and every other file based on the determined number of occurrences. | 1. In a computing system environment, a method of differentiating files stored on one or more computing devices, each file having a plurality of symbols derived from an underlying data stream of all original bits of raw data of said each file, comprising: encoding said each file as a plurality of symbols representing an underlying data stream of all original bits of binary data of the file; determining a number of occurrences of each said symbol in said each file; and computing a distance between said each file and every other file based on the determined number of occurrences. 6. The method of claim 1 , further including sorting into an ordered list the computed said distances between said each file and every other file. | 0.59784 |
9. A computer-implemented method that, when executed by a computing device, presents on a search results page a plurality of preview videos that have been algorithmically determined to be most relevant to various informational items and that are played in succession without user intervention, the method comprising: receiving a selection of a search category; based on the search category, determining a first informational item and a second informational item; algorithmically determining a first preview video associated with the first informational item and a second preview video associated with the second informational item, wherein the first and the second preview videos are determined by a ranking system; algorithmically determining: (1) a first set of related content associated with the first preview video, the first set of related content being different from the first preview video and the first informational item, and (2) a second set of related content associated with the second preview video, the second set of related content being different from the second preview video and the second informational item; communicating for display on the search results page the first and second informational items and the first and the second preview videos; initiating play of the first preview video, wherein only the first set of related content associated with the first preview video is automatically displayed upon initiation of play of the first preview video; and upon completion of the first preview video: (1) removing from display the first set of related content, (2) initiating play of the second preview video without user intervention, and (3) upon removing from display the first set of related content, displaying only the second set of related content associated with the second preview video upon initiation of play of the second preview video. | 9. A computer-implemented method that, when executed by a computing device, presents on a search results page a plurality of preview videos that have been algorithmically determined to be most relevant to various informational items and that are played in succession without user intervention, the method comprising: receiving a selection of a search category; based on the search category, determining a first informational item and a second informational item; algorithmically determining a first preview video associated with the first informational item and a second preview video associated with the second informational item, wherein the first and the second preview videos are determined by a ranking system; algorithmically determining: (1) a first set of related content associated with the first preview video, the first set of related content being different from the first preview video and the first informational item, and (2) a second set of related content associated with the second preview video, the second set of related content being different from the second preview video and the second informational item; communicating for display on the search results page the first and second informational items and the first and the second preview videos; initiating play of the first preview video, wherein only the first set of related content associated with the first preview video is automatically displayed upon initiation of play of the first preview video; and upon completion of the first preview video: (1) removing from display the first set of related content, (2) initiating play of the second preview video without user intervention, and (3) upon removing from display the first set of related content, displaying only the second set of related content associated with the second preview video upon initiation of play of the second preview video. 11. The method of claim 9 , wherein the first and second set of related content include one or more of an article, a thumbnail video, an image, or an audio clip. | 0.652206 |
22. A system, comprising: a photolithography tool operable to generate a feature on a wafer using a commanded dose parameter and a commanded focus parameter; a metrology tool operable to measure a top critical dimension of the feature and a bottom critical dimension of the feature; a photolithography solver operable to define a reference model of the photolithography tool for modeling top and bottom critical dimension data associated with features formed by the photolithography tool as a function of dose and focus, the reference model having a plurality of terms, the photolithography solver being further operable to generate a reference fit error metric for the reference model, generate a set of evaluation models each having one term different than the reference model, generate an evaluation fit error metric for each of the evaluation models, replace the reference model with a selected evaluation model responsive to the selected evaluation model having an evaluation fit error metric less than the reference fit error metric, repeat, based on the replaced reference model, the generating of the reference fit error metric, the generating of the set of evaluation models, the generating of the evaluation fit error metrics, and the replacing of the reference model until no evaluation model has an evaluation fit error metric less than the reference fit error metric, and train the reference model for which no evaluation model has an evaluation fit error metric less than the reference fit error metric by using the top and bottom critical dimension data; and a photolithography monitor operable to receive the top critical dimension measurement and the bottom critical dimension measurement, employ the trained reference model using the top and bottom critical dimension measurements to determine values for a received dose parameter and a received focus parameter, and compare the received dose and focus parameters to the commanded dose and focus parameters to characterize the photolithography system. | 22. A system, comprising: a photolithography tool operable to generate a feature on a wafer using a commanded dose parameter and a commanded focus parameter; a metrology tool operable to measure a top critical dimension of the feature and a bottom critical dimension of the feature; a photolithography solver operable to define a reference model of the photolithography tool for modeling top and bottom critical dimension data associated with features formed by the photolithography tool as a function of dose and focus, the reference model having a plurality of terms, the photolithography solver being further operable to generate a reference fit error metric for the reference model, generate a set of evaluation models each having one term different than the reference model, generate an evaluation fit error metric for each of the evaluation models, replace the reference model with a selected evaluation model responsive to the selected evaluation model having an evaluation fit error metric less than the reference fit error metric, repeat, based on the replaced reference model, the generating of the reference fit error metric, the generating of the set of evaluation models, the generating of the evaluation fit error metrics, and the replacing of the reference model until no evaluation model has an evaluation fit error metric less than the reference fit error metric, and train the reference model for which no evaluation model has an evaluation fit error metric less than the reference fit error metric by using the top and bottom critical dimension data; and a photolithography monitor operable to receive the top critical dimension measurement and the bottom critical dimension measurement, employ the trained reference model using the top and bottom critical dimension measurements to determine values for a received dose parameter and a received focus parameter, and compare the received dose and focus parameters to the commanded dose and focus parameters to characterize the photolithography system. 23. The system of claim 22 , wherein a first subset of the evaluation models has one less term than the reference model, and a second subset of the evaluation models has one more term than the reference model. | 0.5 |
1. A method of constructing one or more message parsing rules in accordance with a user and a machine, comprising the steps of: obtaining message data representing past messages, wherein the past messages contain management information for at least one of a network, an application, and a system being analyzed; and the machine generating one or more message parsing rules by a process based on the obtained message data, and at least one of one or more existing rule templates and demonstrative classification of at least a portion of a message, wherein the one or more parsing rules are storable for use by a rule-based parsing system to translate at least a portion of the obtained message data into a common format; the method further comprising the step of establishing a message structure prior to the generating step; wherein the demonstrative classification comprises the user marking the at least a portion of the message as one of a positive example and a negative example; wherein when one or more existing rule templates are available, the step of establishing a message structure comprises the steps of: creating a message skeleton; matching the one or more rule templates against the message skeleton; and providing potential matches to the user for validation and choice of a proper message structure; wherein when the message structure is found to be insufficient, templates are built by an iterative process between the user and the machine; and wherein the message skeleton comprises information relating to one or more of a message start, a message end, and a separator between fields. | 1. A method of constructing one or more message parsing rules in accordance with a user and a machine, comprising the steps of: obtaining message data representing past messages, wherein the past messages contain management information for at least one of a network, an application, and a system being analyzed; and the machine generating one or more message parsing rules by a process based on the obtained message data, and at least one of one or more existing rule templates and demonstrative classification of at least a portion of a message, wherein the one or more parsing rules are storable for use by a rule-based parsing system to translate at least a portion of the obtained message data into a common format; the method further comprising the step of establishing a message structure prior to the generating step; wherein the demonstrative classification comprises the user marking the at least a portion of the message as one of a positive example and a negative example; wherein when one or more existing rule templates are available, the step of establishing a message structure comprises the steps of: creating a message skeleton; matching the one or more rule templates against the message skeleton; and providing potential matches to the user for validation and choice of a proper message structure; wherein when the message structure is found to be insufficient, templates are built by an iterative process between the user and the machine; and wherein the message skeleton comprises information relating to one or more of a message start, a message end, and a separator between fields. 6. The method of claim 1 , wherein each of the one or more generated parsing rules comprises a regular expression of a portion of a message. | 0.594745 |
1. A computer method of navigating information comprising: receiving a first source of information and one or more second sources of information, each second source having a parent-child relationship with the first source, the first source being the parent; automatically extracting keywords from the first source and each of the second sources in a manner such that, for each extracted keyword, the keyword correlates the first source and at least one second source, resulting in a respective set of second sources for each keyword and resulting in precise keywords that enhance retrieval of second sources of information; and displaying to a user a listing of the keywords resulting from the automatic extracting, the displayed listing enabling the user to navigate the one or more second sources, different keywords in the displayed listing effectively referencing the different respective sets of second sources and the different respective sets of second sources having subject matter of the first source of information shown to the user, wherein the automatic extracting utilizes a semantic lexicon tool, and includes: extracting initial keywords from the first source; forming an initial taxonomy from the extracted initial keywords; detecting in the second sources words that match the initial taxonomy but that do not duplicate the extracted initial keywords of the first source; and combining the extracted initial keywords from the first source and the detected words from the second sources, said combining forming the listing of keywords. | 1. A computer method of navigating information comprising: receiving a first source of information and one or more second sources of information, each second source having a parent-child relationship with the first source, the first source being the parent; automatically extracting keywords from the first source and each of the second sources in a manner such that, for each extracted keyword, the keyword correlates the first source and at least one second source, resulting in a respective set of second sources for each keyword and resulting in precise keywords that enhance retrieval of second sources of information; and displaying to a user a listing of the keywords resulting from the automatic extracting, the displayed listing enabling the user to navigate the one or more second sources, different keywords in the displayed listing effectively referencing the different respective sets of second sources and the different respective sets of second sources having subject matter of the first source of information shown to the user, wherein the automatic extracting utilizes a semantic lexicon tool, and includes: extracting initial keywords from the first source; forming an initial taxonomy from the extracted initial keywords; detecting in the second sources words that match the initial taxonomy but that do not duplicate the extracted initial keywords of the first source; and combining the extracted initial keywords from the first source and the detected words from the second sources, said combining forming the listing of keywords. 8. A method as claimed in claim 1 wherein the step of automatically extracting keywords includes: extracting from a second source, nouns relating to nouns from the first source; and eliminating extracted nouns that are duplicates of extracted keywords from the first source, remaining extracted nouns being keywords that correlate the first source and the second source. | 0.600576 |
12. One or more non-transitory computer-readable media as recited in claim 4 , wherein the determining comprises filtering out a portion of the corpus of phrases. | 12. One or more non-transitory computer-readable media as recited in claim 4 , wherein the determining comprises filtering out a portion of the corpus of phrases. 13. One or more non-transitory computer-readable media as recited in claim 12 , wherein the filtering out comprises filtering the corpus of phrases based at least in part on part-of-speech combinations of the phrases. | 0.92899 |
10. The computer storage medium of claim 9 , further comprising providing a direct comparison between the score of the user and a selected user obtained from the social networking site. | 10. The computer storage medium of claim 9 , further comprising providing a direct comparison between the score of the user and a selected user obtained from the social networking site. 15. The computer storage medium of claim 10 , wherein the other users obtained from the social networking site are displayed with each challenge. | 0.958482 |
16. A non-transitory computer-readable memory containing instructions that, when executed by a computing system, implement a method of selectively updating local language models used to predictively complete user input, the method comprising: receiving information about local language models including a first local language model and other local language models, wherein the information about local language models includes information about local language model events representing user changes to at least one of the local language models; receiving information characterizing users associated with the user changes, wherein the information includes social-networking friend data for the users; identifying a user cluster from the received characterization information, wherein the user cluster is for representing a subset of users sharing matching or associated instances of the social-networking friend data; identifying a set of the local language models including the first local language model and one or more other local language models, based at least in part on the other local language models having local language model events similar to first local language model events; for each local language model in the set, identifying additional local language model events; generating modifications to the first local language model using the additional local language model event information of one or more of the identified other local language models in the set, and also using the user cluster, wherein the generation of the modifications is initiated based on receiving the local language model events; filtering the generated modifications by excluding events associated with a blacklist of vocabulary not to be added or events associated with a whitelist of vocabulary not to be deleted before updating the first local language model with the generated modifications; and updating the first local language model with the generated modifications based on providing the generated modifications to a computing device of one or more users in the user cluster. | 16. A non-transitory computer-readable memory containing instructions that, when executed by a computing system, implement a method of selectively updating local language models used to predictively complete user input, the method comprising: receiving information about local language models including a first local language model and other local language models, wherein the information about local language models includes information about local language model events representing user changes to at least one of the local language models; receiving information characterizing users associated with the user changes, wherein the information includes social-networking friend data for the users; identifying a user cluster from the received characterization information, wherein the user cluster is for representing a subset of users sharing matching or associated instances of the social-networking friend data; identifying a set of the local language models including the first local language model and one or more other local language models, based at least in part on the other local language models having local language model events similar to first local language model events; for each local language model in the set, identifying additional local language model events; generating modifications to the first local language model using the additional local language model event information of one or more of the identified other local language models in the set, and also using the user cluster, wherein the generation of the modifications is initiated based on receiving the local language model events; filtering the generated modifications by excluding events associated with a blacklist of vocabulary not to be added or events associated with a whitelist of vocabulary not to be deleted before updating the first local language model with the generated modifications; and updating the first local language model with the generated modifications based on providing the generated modifications to a computing device of one or more users in the user cluster. 17. The non-transitory computer-readable memory of claim 16 , wherein receiving information about local language models comprises receiving a change log, local language models, or a combination thereof. | 0.550108 |
1. A computer-implemented method performed at a server system having one or more processors and memory, the method comprising: receiving a search query from a user; identifying search results associated with the search query; identifying a set of user-preferred search results that includes search results in a search history of the user, wherein each of the user-preferred search results has been previously selected by the user for at least a predefined minimum number of times; identifying in the search results, one or more search results, each of which is associated with a respective user-preferred search result; ordering the search results based at least in part on a popularity metric associated with each of the identified search results, wherein the popularity metric is a function of one or more parameters including at least one parameter that is a time span period from the user's most remote selection of the respective user-preferred search result to the user's most recent selection of the respective user-preferred search result; and providing the ordered search results to the user. | 1. A computer-implemented method performed at a server system having one or more processors and memory, the method comprising: receiving a search query from a user; identifying search results associated with the search query; identifying a set of user-preferred search results that includes search results in a search history of the user, wherein each of the user-preferred search results has been previously selected by the user for at least a predefined minimum number of times; identifying in the search results, one or more search results, each of which is associated with a respective user-preferred search result; ordering the search results based at least in part on a popularity metric associated with each of the identified search results, wherein the popularity metric is a function of one or more parameters including at least one parameter that is a time span period from the user's most remote selection of the respective user-preferred search result to the user's most recent selection of the respective user-preferred search result; and providing the ordered search results to the user. 4. The method of claim 1 , wherein previous selection of a search result by the user comprises clicking on the search result and staying on a corresponding document for at least a predefined minimum duration. | 0.697806 |
9. A device for computer system performance analysis, comprising: a performance log file receiver, executing using a processor, for receiving a computer system performance log file; a clustering handler for clustering instructions involved in the computer system performance log file at flexible granularity to acquire code clusters, wherein the clustering handler implements the following instruction clustering at flexible granularity: sorting all gaps in a descending order, the largest gap having a smallest number as its number, the numbers of other gaps increasing in order, wherein the gap is the difference between the address of a current instruction and the address of a next instruction adjacent to the current instruction, among all of the gaps, determining significant gaps which are significantly larger in relative to other gaps, and identifying instructions corresponding to the significant gaps to divide the codes into clusters, wherein determining the significant gaps comprises: determining a slope of each gap by: computing S=gap i /(N−i), wherein S is the sloe, gap i is the current gap, i is the ID of the current gap, and N is the total number of the gaps, and determining a gap with such a slope the rate of which to the slope of the next gap is larger than a significant gap threshold, identifying the gap as a first significant gap and other gaps larger than or equal to the gap as significant gaps; and a performance viewer for outputting the result of computer system performance analysis based on the code clusters. | 9. A device for computer system performance analysis, comprising: a performance log file receiver, executing using a processor, for receiving a computer system performance log file; a clustering handler for clustering instructions involved in the computer system performance log file at flexible granularity to acquire code clusters, wherein the clustering handler implements the following instruction clustering at flexible granularity: sorting all gaps in a descending order, the largest gap having a smallest number as its number, the numbers of other gaps increasing in order, wherein the gap is the difference between the address of a current instruction and the address of a next instruction adjacent to the current instruction, among all of the gaps, determining significant gaps which are significantly larger in relative to other gaps, and identifying instructions corresponding to the significant gaps to divide the codes into clusters, wherein determining the significant gaps comprises: determining a slope of each gap by: computing S=gap i /(N−i), wherein S is the sloe, gap i is the current gap, i is the ID of the current gap, and N is the total number of the gaps, and determining a gap with such a slope the rate of which to the slope of the next gap is larger than a significant gap threshold, identifying the gap as a first significant gap and other gaps larger than or equal to the gap as significant gaps; and a performance viewer for outputting the result of computer system performance analysis based on the code clusters. 14. The device according to claim 9 , further comprising: a comment generator for attaching meaning comments of the code clusters to the respective clusters. | 0.534829 |
8. A computer implemented method for providing context in an electronic text communication, the method comprising: setting a criteria for rendering metrics; storing the criteria for rendering the metrics; responsive to receiving a set of metrics and the electronic text communication from a sending data processing system, retrieving, by a processing unit in a computer, the criteria for rendering the metrics, wherein the set of metrics are generated by the processing unit based on a sender of the electronic text communication interacting with a biometric gathering input device during the generation of the electronic text communication; and responsive to retrieving the criteria, presenting the electronic text communication and the set of metrics using the criteria for rendering the metrics, wherein presenting the electronic text communication provides context to the electronic text communication. | 8. A computer implemented method for providing context in an electronic text communication, the method comprising: setting a criteria for rendering metrics; storing the criteria for rendering the metrics; responsive to receiving a set of metrics and the electronic text communication from a sending data processing system, retrieving, by a processing unit in a computer, the criteria for rendering the metrics, wherein the set of metrics are generated by the processing unit based on a sender of the electronic text communication interacting with a biometric gathering input device during the generation of the electronic text communication; and responsive to retrieving the criteria, presenting the electronic text communication and the set of metrics using the criteria for rendering the metrics, wherein presenting the electronic text communication provides context to the electronic text communication. 10. The computer implemented method of claim 8 , wherein the set of metrics includes at least one of determining a speed of engagement, pauses between keystrokes, pressure asserted upon a key, number of corrections performed by the sender associated with the composition of the electronic communication, and the hand temperature of the sender. | 0.840593 |
1. An information retrieval device comprising: a memory storing one or more selection logs that include: one or more items of first information corresponding to query information, and one or more items of second information associated with selected content; and a processor operatively coupled to the memory, the processor being programmed to perform a process including: obtaining, from the one or more selection logs, a first selectivity of content corresponding to each of the one or more items of second information; obtaining, from the one or more selection logs, a second selectivity of content corresponding to each of the one or more items of first information and each of the one or more items of second information; calculating, for each pair of each of the one or more items of first information and each of the one or more items of second information, a matching score between each of the one or more items of first information and each of the one or more items of second information, based on the first selectivity and the second selectivity; learning a transformation matrix based on the calculated matching score, the transformation matrix having, as an element, degree of association information indicating a degree of association between each of the one or more items of first information and each of the one or more items of second information; accepting a query including one or more items of query information, the one or more items of query information being one or more items of information used for retrieval of content; obtaining a value corresponding to each of the one or more items of second information by multiplying a query vector of the accepted one or more items of query information by the learned transformation matrix; and retrieving content based on the obtained value corresponding to each of the one or more items of second information. | 1. An information retrieval device comprising: a memory storing one or more selection logs that include: one or more items of first information corresponding to query information, and one or more items of second information associated with selected content; and a processor operatively coupled to the memory, the processor being programmed to perform a process including: obtaining, from the one or more selection logs, a first selectivity of content corresponding to each of the one or more items of second information; obtaining, from the one or more selection logs, a second selectivity of content corresponding to each of the one or more items of first information and each of the one or more items of second information; calculating, for each pair of each of the one or more items of first information and each of the one or more items of second information, a matching score between each of the one or more items of first information and each of the one or more items of second information, based on the first selectivity and the second selectivity; learning a transformation matrix based on the calculated matching score, the transformation matrix having, as an element, degree of association information indicating a degree of association between each of the one or more items of first information and each of the one or more items of second information; accepting a query including one or more items of query information, the one or more items of query information being one or more items of information used for retrieval of content; obtaining a value corresponding to each of the one or more items of second information by multiplying a query vector of the accepted one or more items of query information by the learned transformation matrix; and retrieving content based on the obtained value corresponding to each of the one or more items of second information. 4. The information retrieval device according to claim 1 , wherein: the content is associated with one or more items of to-be-retrieved information, the one or more items of to-be-retrieved information being a set of second information and weight information indicating a weight of the second information, and the processor retrieves content based on the obtained one or more sets of second information and a value. | 0.579798 |
1. A method of arranging labels on a visual representation of a graph data structure, the method comprising: obtaining, with one or more processors, a graph to be visually represented in a graphical user interface of a client computing device, the visual representation including a plurality of icons each representing one or more nodes of a graph data structure and links extending between the icons in the visual representation; obtaining, with one or more processors, a set of text labels each corresponding to a respective collection of the nodes; determining, with one or more processors, a two dimensional or higher layout of the icons in the visual representation within a field of view; segmenting, with one or more processors, the field of view into a plurality of segments of the field of view; determining, with one or more processors, which icons are disposed within each of the segments of the field of view; determining, with one or more processors, positions of the text labels in the visual representation relative to one or more icons representing nodes in the respective collection of nodes based on the segment of the field of view in which the one or more icons representing nodes in the respective collection are disposed; causing, with one or more processors, the visual representation to be displayed; receiving a user request to zoom into a portion of the visual representation; re-determining which icons are in which of the segments of the field of view after zooming; and re-determining positions of the text labels based on changes in segments in which icons are disposed after zooming, wherein re-determining positions of the text labels based on changes in segments in which icons are disposed after zooming comprises: determining a plurality of sets of sub-segments, each set of sub-segments having a plurality of sub-segments, each set of sub-segments corresponding to a respective cluster, each of the sets of sub-segments being centered at a different respective position of the field of view; selecting, for each of the clusters, a respective sub-segment based on a segment of the field of view in which the respective cluster is disposed; and positioning respective text labels for respective clusters or icons therein based on, and at least partially in, respective selected sub-segment corresponding to the respective clusters. | 1. A method of arranging labels on a visual representation of a graph data structure, the method comprising: obtaining, with one or more processors, a graph to be visually represented in a graphical user interface of a client computing device, the visual representation including a plurality of icons each representing one or more nodes of a graph data structure and links extending between the icons in the visual representation; obtaining, with one or more processors, a set of text labels each corresponding to a respective collection of the nodes; determining, with one or more processors, a two dimensional or higher layout of the icons in the visual representation within a field of view; segmenting, with one or more processors, the field of view into a plurality of segments of the field of view; determining, with one or more processors, which icons are disposed within each of the segments of the field of view; determining, with one or more processors, positions of the text labels in the visual representation relative to one or more icons representing nodes in the respective collection of nodes based on the segment of the field of view in which the one or more icons representing nodes in the respective collection are disposed; causing, with one or more processors, the visual representation to be displayed; receiving a user request to zoom into a portion of the visual representation; re-determining which icons are in which of the segments of the field of view after zooming; and re-determining positions of the text labels based on changes in segments in which icons are disposed after zooming, wherein re-determining positions of the text labels based on changes in segments in which icons are disposed after zooming comprises: determining a plurality of sets of sub-segments, each set of sub-segments having a plurality of sub-segments, each set of sub-segments corresponding to a respective cluster, each of the sets of sub-segments being centered at a different respective position of the field of view; selecting, for each of the clusters, a respective sub-segment based on a segment of the field of view in which the respective cluster is disposed; and positioning respective text labels for respective clusters or icons therein based on, and at least partially in, respective selected sub-segment corresponding to the respective clusters. 15. The method of claim 1 , wherein segmenting the field of view comprises: sub-dividing the field of view according to a Voronoi diagram of the icons positions after determining the layout to form a plurality of Voronoi regions by performing a k-means cluster of vertical and horizontal coordinates of the icons in the field of view; segmenting each of the Voronoi regions into a plurality of sectors about a point at a location selected based on a centroid of the respective Voronoi region. | 0.695768 |
18. A circuit for recognizing a string of characters according to claim 17 wherein said reference character set selecting means comprises: means for searching said groups in order of most to least correspondence to the input character string including means for selecting the unsearched group having the closest correspondence to said input character string; means responsive to the reference character sets of the selected group and the character correspondence signals for forming a correspondence signal for each reference character set of the group; means responsive to the reference character set correspondence signals for selecting the reference character set having the closest correspondence to the input character string; and means responsive to the correspondence signal of the selected reference character set having closer correspondence to the input character string than the correspondence signals of the unsearched groups for identifying the input character string as the selected reference character set. | 18. A circuit for recognizing a string of characters according to claim 17 wherein said reference character set selecting means comprises: means for searching said groups in order of most to least correspondence to the input character string including means for selecting the unsearched group having the closest correspondence to said input character string; means responsive to the reference character sets of the selected group and the character correspondence signals for forming a correspondence signal for each reference character set of the group; means responsive to the reference character set correspondence signals for selecting the reference character set having the closest correspondence to the input character string; and means responsive to the correspondence signal of the selected reference character set having closer correspondence to the input character string than the correspondence signals of the unsearched groups for identifying the input character string as the selected reference character set. 19. A circuit for recognizing a string of spoken characters according to claim 18 wherein said group correspondence signal forming means comprises means for assigning each reference character to a predetermined one of a plurality of classes; means responsive to the classes for the reference characters of each reference character set for assigning the reference character set to a predetermined group; means responsive to the character correspondence signals for each input character for selecting a class correspondence signal for said input character; and means for combining the selected class correspondence signals for the input characters to generate a correspondence signal for each group. | 0.651569 |
1. A system for access to multimedia structures, the system comprising: telephone sets configured to connect to a telephone network; a storage device configured to store a plurality of multimedia structures representing at least one of messages, data and commands; a network access server that is associated with the telephone sets and is separate from the storage device and is comprises: a processor; and; memory storing at least one program that, when executed by the processor, causes the network access server to: receive a telephone call from one of the telephone sets; receive a number from the one telephone set after receiving the telephone call, wherein the number represents a remote hosting site in which the storage device is located; selectively instantiate the multimedia structures via an interconnection network by determining a network address of the remote hosting site using the received number; selectively instantiate the multimedia structures in a directory; download the multimedia structures contained in the directory; and instantiate a voice-recognition and speech-synthesis system that comprises modules for reading files in XML format, for associating these files with an XSL processing module, and for selectively mapping the XML files into the XSL processing module to obtain files in a format that is configured to be interpreted by the voice-recognition and speech-synthesis system. | 1. A system for access to multimedia structures, the system comprising: telephone sets configured to connect to a telephone network; a storage device configured to store a plurality of multimedia structures representing at least one of messages, data and commands; a network access server that is associated with the telephone sets and is separate from the storage device and is comprises: a processor; and; memory storing at least one program that, when executed by the processor, causes the network access server to: receive a telephone call from one of the telephone sets; receive a number from the one telephone set after receiving the telephone call, wherein the number represents a remote hosting site in which the storage device is located; selectively instantiate the multimedia structures via an interconnection network by determining a network address of the remote hosting site using the received number; selectively instantiate the multimedia structures in a directory; download the multimedia structures contained in the directory; and instantiate a voice-recognition and speech-synthesis system that comprises modules for reading files in XML format, for associating these files with an XSL processing module, and for selectively mapping the XML files into the XSL processing module to obtain files in a format that is configured to be interpreted by the voice-recognition and speech-synthesis system. 6. The system defined in claim 1 wherein the interconnection network is the internet. | 0.630399 |
13. The method according to claim 1 , wherein the collection of information comprises a collection of at least one document, and wherein the at least one document further comprises a unit of storage of digital data. | 13. The method according to claim 1 , wherein the collection of information comprises a collection of at least one document, and wherein the at least one document further comprises a unit of storage of digital data. 14. The method according to claim 13 , wherein the at least one document further comprises at least one of a data record, within a database, textual information, non-textual information, audio, video, streaming data, a defined entity, a programmatically defined entity, metadata, and information derived from a document. | 0.840634 |
1. In a computing network at which data is made available from a variety of different sources and in a variety of different data types and formats, a computer-implemented method for use at a computer system having a processor and memory, and which is running a database application configured to communicate with a database using at least one of a variety of different database schemas, the computer-implemented method facilitating the ability of the database application to more easily use the data from the variety of different sources, and comprising: receiving at the database application input data from a database; instantiating at the database application a metadata inferring module that infers object relational mapping (ORM) metadata for one or more database objects of the received input data, the ORM metadata inferred from at least one of the database schemas that the database application is configured to use, the inferred ORM metadata including an indication of database object properties and database schema settings associated with one or more database objects of the received input data, thereby allowing the database application to implement ORM capabilities to retrieve and access information from the database; instantiating at the database application an object relational mapping (ORM) query module configured to use ORM metadata to generate information that is used to generate an object graph, the ORM query module processing the ORM metadata for the one or more database objects of the received input data; instantiating an object graph generator and, using the information derived by the ORM query module after processing the ORM metadata, the object graph generator then mapping the one or more database objects of the input data into a graph of objects which enables the mapped one or more database objects to be sent to another application or to be subsequently displayed in an ORM object view. | 1. In a computing network at which data is made available from a variety of different sources and in a variety of different data types and formats, a computer-implemented method for use at a computer system having a processor and memory, and which is running a database application configured to communicate with a database using at least one of a variety of different database schemas, the computer-implemented method facilitating the ability of the database application to more easily use the data from the variety of different sources, and comprising: receiving at the database application input data from a database; instantiating at the database application a metadata inferring module that infers object relational mapping (ORM) metadata for one or more database objects of the received input data, the ORM metadata inferred from at least one of the database schemas that the database application is configured to use, the inferred ORM metadata including an indication of database object properties and database schema settings associated with one or more database objects of the received input data, thereby allowing the database application to implement ORM capabilities to retrieve and access information from the database; instantiating at the database application an object relational mapping (ORM) query module configured to use ORM metadata to generate information that is used to generate an object graph, the ORM query module processing the ORM metadata for the one or more database objects of the received input data; instantiating an object graph generator and, using the information derived by the ORM query module after processing the ORM metadata, the object graph generator then mapping the one or more database objects of the input data into a graph of objects which enables the mapped one or more database objects to be sent to another application or to be subsequently displayed in an ORM object view. 8. The method of claim 1 , further comprising: an act of determining that at least a portion of schema settings in the database have been updated; and an act of invalidating a displayed ORM object view based on the determination that schema settings in the database have been updated. | 0.522124 |
1. A method of analyzing data, comprising: generating, by an entity, a query based at least in part on a topic of interest; executing the query on a plurality of data sources, at least one of the plurality of data sources comprising data for summarization; selecting, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; monitoring, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; extracting data from the data source when at least the update to the stored data matches the query, the newly added data matches the query, or the combination thereof; determining an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; determining a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; dynamically adjusting the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; analyzing, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; establishing a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided the data to the data source, based on the analysis of the extracted data; transmitting, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and receiving, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. | 1. A method of analyzing data, comprising: generating, by an entity, a query based at least in part on a topic of interest; executing the query on a plurality of data sources, at least one of the plurality of data sources comprising data for summarization; selecting, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; monitoring, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; extracting data from the data source when at least the update to the stored data matches the query, the newly added data matches the query, or the combination thereof; determining an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; determining a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; dynamically adjusting the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; analyzing, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; establishing a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided the data to the data source, based on the analysis of the extracted data; transmitting, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and receiving, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. 10. The method of claim 1 , in which the two-way communication channel comprises at least one of short message service (SMS), click-to-voice, interactive voice response (IVR), e-mail, phone, Internet protocol, message board, social media, digital communication, or a combination thereof. | 0.559955 |
14. The system of claim 13 , wherein the word vector connects extracted semantic content mapped to at least two entries in the knowledge graph. | 14. The system of claim 13 , wherein the word vector connects extracted semantic content mapped to at least two entries in the knowledge graph. 26. The electronic device of claim 14 , wherein the at least one processor is further configured to: display one or more clusters on the UI according to one or more rules, and display a lower cluster or an upper cluster of the one or more clusters on the UI in response to a user's touch input. | 0.913082 |
7. A user terminal for managing at least one media asset maintained by a media asset repository, comprising: a presenting part configured to present information; said user terminal being configured to manage said media asset repository through a media server, said repository being coupled to said user terminal over a communications link; a media asset feedback detection part configured to detect an audible behavior of a user at said user terminal related to said at least one media asset at managing said at least one media asset by said user terminal; and a feedback interpreting part configured to determine an annotation to said at least one media asset based on an interpretation/analysis of said audible behavior of said user related to said at least one media asset; and wherein the annotation indicates that the user likes said at least one media asset; and wherein the feedback interpreting part is further configured to: determine the annotation that indicates that the user likes said at least one media asset based on a rules based reasoning; and allow users to customize their personal rules. | 7. A user terminal for managing at least one media asset maintained by a media asset repository, comprising: a presenting part configured to present information; said user terminal being configured to manage said media asset repository through a media server, said repository being coupled to said user terminal over a communications link; a media asset feedback detection part configured to detect an audible behavior of a user at said user terminal related to said at least one media asset at managing said at least one media asset by said user terminal; and a feedback interpreting part configured to determine an annotation to said at least one media asset based on an interpretation/analysis of said audible behavior of said user related to said at least one media asset; and wherein the annotation indicates that the user likes said at least one media asset; and wherein the feedback interpreting part is further configured to: determine the annotation that indicates that the user likes said at least one media asset based on a rules based reasoning; and allow users to customize their personal rules. 9. The user terminal according to claim 7 , wherein said media asset feedback detection part is configured to detect said audible behavior of a user at said user terminal by means of a sensor. | 0.744709 |
1. In an automatic speech processing system, a method for assessing pronunciation of a student speech sample using a computerized acoustic segmentation system, the method comprising: accepting said student speech sample which comprises a sequence of words spoken by a student speaker; operating said computerized acoustic segmentation system to define sample acoustic units within said student speech sample based on speech acoustic models within said segmentation system, said speech acoustic models being established using training speech data from at least one speaker, said training speech data not necessarily including said sequence of spoken words; measuring duration of said sample acoustic units; and comparing said durations of sample acoustic units to a model of exemplary acoustic unit duration to compute a duration score indicative of similarity between said sample acoustic unit durations and exemplary acoustic unit durations. | 1. In an automatic speech processing system, a method for assessing pronunciation of a student speech sample using a computerized acoustic segmentation system, the method comprising: accepting said student speech sample which comprises a sequence of words spoken by a student speaker; operating said computerized acoustic segmentation system to define sample acoustic units within said student speech sample based on speech acoustic models within said segmentation system, said speech acoustic models being established using training speech data from at least one speaker, said training speech data not necessarily including said sequence of spoken words; measuring duration of said sample acoustic units; and comparing said durations of sample acoustic units to a model of exemplary acoustic unit duration to compute a duration score indicative of similarity between said sample acoustic unit durations and exemplary acoustic unit durations. 4. The method according to claim 1 further comprising: mapping said duration score to a grade; and presenting said grade to a student. | 0.695806 |
1. A method for modifying computer mediated communications, the method comprising: at a computer system including one or more processors and memory: receiving input video data from a digital camera, the input video data including a first segment of the input video data corresponding to recorded non-verbal behavior of a first participant in a computer mediated communication; generating a first portion of an output stream of video data, wherein generating the first portion of the output stream of video data includes: comparing the recorded non-verbal behavior to a predefined behavioral model, wherein the behavioral model defines behavioral parameters; and in accordance with a determination that the recorded non-verbal behavior is inconsistent with the behavioral model, determining alternative behavior that is consistent with the behavioral model; and including the alternative behavior in the first portion of the output stream of video data in place of behavior representative of the recorded non-verbal behavior in the respective video segment; and transmitting the output stream of video data to a second participant in the computer mediated communication. | 1. A method for modifying computer mediated communications, the method comprising: at a computer system including one or more processors and memory: receiving input video data from a digital camera, the input video data including a first segment of the input video data corresponding to recorded non-verbal behavior of a first participant in a computer mediated communication; generating a first portion of an output stream of video data, wherein generating the first portion of the output stream of video data includes: comparing the recorded non-verbal behavior to a predefined behavioral model, wherein the behavioral model defines behavioral parameters; and in accordance with a determination that the recorded non-verbal behavior is inconsistent with the behavioral model, determining alternative behavior that is consistent with the behavioral model; and including the alternative behavior in the first portion of the output stream of video data in place of behavior representative of the recorded non-verbal behavior in the respective video segment; and transmitting the output stream of video data to a second participant in the computer mediated communication. 4. The method of claim 1 wherein including the alternative behavior in the first portion of the output stream further includes: replacing a portion of the first segment of the input video data with pre-recorded video of the first participant that includes the alternative behavior. | 0.657941 |
7. The method of claim 6 , further comprising: vetoing the altering by the Janus unit of how the semantic unit is networked in the network of semantic units. | 7. The method of claim 6 , further comprising: vetoing the altering by the Janus unit of how the semantic unit is networked in the network of semantic units. 8. The method of claim 7 , wherein the Janus unit of a semantic unit whose one of networking and content are to be altered stores one of the networking and the content and restores these if appropriate. | 0.939076 |
1. An electronic device comprising: a memory for storing a word, a first transcription of the word, and a second transcription of the word; a microphone for capturing a speech utterance; a speech recognition engine, coupled to the microphone and the memory, for evaluating through a predetermined number of times of speech utterances against the first transcription and the second transcription, for determining a first probability factor for the first transcription based on an accumulated acoustic score for the first transcription and a total accumulated score of the first transcription and the second transcription, and for determining a second probability factor for the second transcription based on an accumulated acoustic score for the second transcription and the total accumulated score of the first transcription and the second transcription; and a processor, coupled to the speech recognition engine, for inactivating the first transcription if the first probability factor is below a threshold. | 1. An electronic device comprising: a memory for storing a word, a first transcription of the word, and a second transcription of the word; a microphone for capturing a speech utterance; a speech recognition engine, coupled to the microphone and the memory, for evaluating through a predetermined number of times of speech utterances against the first transcription and the second transcription, for determining a first probability factor for the first transcription based on an accumulated acoustic score for the first transcription and a total accumulated score of the first transcription and the second transcription, and for determining a second probability factor for the second transcription based on an accumulated acoustic score for the second transcription and the total accumulated score of the first transcription and the second transcription; and a processor, coupled to the speech recognition engine, for inactivating the first transcription if the first probability factor is below a threshold. 4. An electronic device according to claim 1 further comprising: a display, coupled to the processor, for displaying the word. | 0.5868 |
19. A computerized method comprising: displaying a set of markup language template objects, the set comprising default and user-defined markup language template objects; generating a markup language object from multiple selected markup language template objects; modifying a property value in response to input data, the property value associated with the selected markup language template object; and regenerating the markup language object using the modified property value. | 19. A computerized method comprising: displaying a set of markup language template objects, the set comprising default and user-defined markup language template objects; generating a markup language object from multiple selected markup language template objects; modifying a property value in response to input data, the property value associated with the selected markup language template object; and regenerating the markup language object using the modified property value. 20. The method of claim 19 , wherein the default and user defined markup language template objects are displayed separately. | 0.61912 |
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