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23. A touch screen system comprising: a touch screen graphical display; means for translating user interaction with a selectable object on the touch screen graphical display into commands that determine which of two different input modes are used, based on a determination of whether the user interaction matches a type of input associated with selection of the selectable object; and one or more persistent data storage devices storing rules accessible by the means for translating, wherein the rules comprise a first set of rules for interpreting user interaction with the graphical display that is used when the touch screen system is in a first input mode and a second set of rules for interpreting user interaction with the graphical display that is used when the touch screen system is in a second input mode, wherein the second set of rules interprets inputs on the touch screen graphical display as glyph inputs, and wherein the second mode is used in response to determining that an input over the selectable object does not match a type of input associated with selection of the selectable object. | 23. A touch screen system comprising: a touch screen graphical display; means for translating user interaction with a selectable object on the touch screen graphical display into commands that determine which of two different input modes are used, based on a determination of whether the user interaction matches a type of input associated with selection of the selectable object; and one or more persistent data storage devices storing rules accessible by the means for translating, wherein the rules comprise a first set of rules for interpreting user interaction with the graphical display that is used when the touch screen system is in a first input mode and a second set of rules for interpreting user interaction with the graphical display that is used when the touch screen system is in a second input mode, wherein the second set of rules interprets inputs on the touch screen graphical display as glyph inputs, and wherein the second mode is used in response to determining that an input over the selectable object does not match a type of input associated with selection of the selectable object. 24. The touch screen system of claim 23 , wherein the means for translating comprises: a clock; and a timer that relies on the clock and configured to start in response to identification of a stationary contact with the touch screen graphical display. | 0.54424 |
15. An electronic device, including: a display interface; and a processor in communication with the display interface, the processor being capable of: receiving an instruction to scale a region of a displayed structured document, the region including at least one element or a portion thereof; in response to the received instruction: identifying a dominant alignment of the region, the dominant alignment being an alignment of a dominant image in the region or an alignment of text within a dominant text block in the region; scaling the region; and outputting to the display interface a portion of the scaled region intersecting a viewport defined for a display, the viewport being aligned with the scaled region according to the dominant alignment when it is intersected with the scaled region. | 15. An electronic device, including: a display interface; and a processor in communication with the display interface, the processor being capable of: receiving an instruction to scale a region of a displayed structured document, the region including at least one element or a portion thereof; in response to the received instruction: identifying a dominant alignment of the region, the dominant alignment being an alignment of a dominant image in the region or an alignment of text within a dominant text block in the region; scaling the region; and outputting to the display interface a portion of the scaled region intersecting a viewport defined for a display, the viewport being aligned with the scaled region according to the dominant alignment when it is intersected with the scaled region. 17. The electronic device of claim 15 , wherein identifying the dominant alignment comprises identifying a dominant element according to a hierarchy of elements or an attribute of the dominant element. | 0.722766 |
63. A computer-implemented method comprising: receiving a creative associated with an advertisement wherein the creative includes a title, and one or more lines of text including a second line of text and optionally a reference portion; determining, using one or more processors, when the second line of text can be promoted into the title including determining when the second line of text constitutes a sentence by evaluating the text included in the one or more lines of text; promoting, using the one or more processors, the second line of text into the title when the second line of text constitutes a sentence including modifying the title to append the second line of text to the title; and providing the creative including the title with the promoted second line of text. | 63. A computer-implemented method comprising: receiving a creative associated with an advertisement wherein the creative includes a title, and one or more lines of text including a second line of text and optionally a reference portion; determining, using one or more processors, when the second line of text can be promoted into the title including determining when the second line of text constitutes a sentence by evaluating the text included in the one or more lines of text; promoting, using the one or more processors, the second line of text into the title when the second line of text constitutes a sentence including modifying the title to append the second line of text to the title; and providing the creative including the title with the promoted second line of text. 65. The method of claim 63 wherein the one or more lines of text comprise a body portion that includes two lines of text. | 0.671576 |
7. A method of implementing a business process application, the method comprising: designing via a design interface of a processing device a business process application, the business process application including at least one object associated with business data of a database and an individual workflow for each of the at least one object, wherein designing the business process application includes: defining one or more archetypes, wherein each of the archetypes include at least one data-table having columns and storage attributes with object-relational mapping information for the at least one object, defining the at least one object according to the one or more archetypes, and designing one or more processes of the individual workflow for each of the at least one object, wherein the individual workflow includes at least one step, the at least one step including a business rule and a designated output; and processing via an object query language interface of the processing device each of the at least one object of the business process application that executes the business rule of the individual workflow for each of the at least one object against the business data of the database and generates the designated output according to the executed business rule. | 7. A method of implementing a business process application, the method comprising: designing via a design interface of a processing device a business process application, the business process application including at least one object associated with business data of a database and an individual workflow for each of the at least one object, wherein designing the business process application includes: defining one or more archetypes, wherein each of the archetypes include at least one data-table having columns and storage attributes with object-relational mapping information for the at least one object, defining the at least one object according to the one or more archetypes, and designing one or more processes of the individual workflow for each of the at least one object, wherein the individual workflow includes at least one step, the at least one step including a business rule and a designated output; and processing via an object query language interface of the processing device each of the at least one object of the business process application that executes the business rule of the individual workflow for each of the at least one object against the business data of the database and generates the designated output according to the executed business rule. 10. The method of claim 7 , wherein the method further comprises executing one or more queries against the database using one or more of the at least one object. | 0.686477 |
1. A method for determining age categories of people, comprising the following steps of: a) annotating a facial image database according to the demographics classes of the individual face, b) training a plurality of learning machines so that each learning machine outputs auxiliary demographics class information and age information of any given facial image, c) detecting and tracking a facial image from the input image frame, d) processing said facial image to extract image features, and e) processing said image features obtained from said facial image using classification techniques for determining age or age categories, whereby the age classes can be any partition based on age in multiple groups, wherein the method further comprises a step of determining the target outputs of the plurality of learning machines so that each learning machine maps a first input data, whose facial images belong to a first auxiliary demographics class, to first vector-valued points on a manifold in the space of facial images, whereas each learning machine maps a second input data, whose facial images do not belong to a first auxiliary demographics class, to second vector-valued points away from the manifold. | 1. A method for determining age categories of people, comprising the following steps of: a) annotating a facial image database according to the demographics classes of the individual face, b) training a plurality of learning machines so that each learning machine outputs auxiliary demographics class information and age information of any given facial image, c) detecting and tracking a facial image from the input image frame, d) processing said facial image to extract image features, and e) processing said image features obtained from said facial image using classification techniques for determining age or age categories, whereby the age classes can be any partition based on age in multiple groups, wherein the method further comprises a step of determining the target outputs of the plurality of learning machines so that each learning machine maps a first input data, whose facial images belong to a first auxiliary demographics class, to first vector-valued points on a manifold in the space of facial images, whereas each learning machine maps a second input data, whose facial images do not belong to a first auxiliary demographics class, to second vector-valued points away from the manifold. 3. The method according to claim 1 , wherein the method further comprises a step of annotating the facial image database with the auxiliary class labels and the age labels of each facial image, whereby the auxiliary class is a demographics class defined by the same gender and ethnicity categories. | 0.657853 |
34. The method of claim 32 , wherein the search phrase explicitly defined by the members of the at least one community is defined responsive to member feedback based on relevancy of search results. | 34. The method of claim 32 , wherein the search phrase explicitly defined by the members of the at least one community is defined responsive to member feedback based on relevancy of search results. 35. The method of claim 34 , wherein the member feedback based on relevancy of search results is comprised by member click-through rates of search results. | 0.941826 |
14. A method for operating an intelligent automated assistant, the method comprising: at an electronic device with a processor and memory storing one or more programs for execution by the processor: receiving, from a user, a speech input; processing the speech input using an automatic speech recognition system to determine a text string corresponding to the speech input; determining an actionable intent based on the text string; generating a dialogue response to the speech input based on the actionable intent, wherein the dialogue response includes a heteronym; determining a correct pronunciation of the heteronym using an n-gram language model of the automatic speech recognition system and based on the heteronym and one or more additional words in the dialogue response; and outputting the dialogue response as a speech output, wherein the heteronym in the dialogue response is pronounced in the speech output according to the determined correct pronunciation. | 14. A method for operating an intelligent automated assistant, the method comprising: at an electronic device with a processor and memory storing one or more programs for execution by the processor: receiving, from a user, a speech input; processing the speech input using an automatic speech recognition system to determine a text string corresponding to the speech input; determining an actionable intent based on the text string; generating a dialogue response to the speech input based on the actionable intent, wherein the dialogue response includes a heteronym; determining a correct pronunciation of the heteronym using an n-gram language model of the automatic speech recognition system and based on the heteronym and one or more additional words in the dialogue response; and outputting the dialogue response as a speech output, wherein the heteronym in the dialogue response is pronounced in the speech output according to the determined correct pronunciation. 19. The method of claim 14 , wherein the correct pronunciation of the heteronym is determined based at least in part on a custom pronunciation of the heteronym that is associated with the user, and wherein the custom pronunciation is based on a previous speech input received from the user. | 0.72572 |
11. A method of determining relevance of an electronic advertisement to a target content, said method comprising: extracting a set of terms from said electronic advertisement and said target content; calculating a first content match feature using said set of terms, the first content match feature comprising a translation evaluation feature indicating a degree to which n-grams of the electronic advertisement and the target content match; calculating a second content match feature using said set of terms, said second content match feature comprising a translation proportion feature indicating a proportion of related terms in the electronic advertisement and the target content; and processing said first content match feature and said second content match feature with a machine learning model to output a relevance score indicating the relevance of the electronic advertisement to the target content, the machine learning model comprising individual weights for the first and second content match features, the machine learning model being trained using said first and second content match features and machine learning techniques. | 11. A method of determining relevance of an electronic advertisement to a target content, said method comprising: extracting a set of terms from said electronic advertisement and said target content; calculating a first content match feature using said set of terms, the first content match feature comprising a translation evaluation feature indicating a degree to which n-grams of the electronic advertisement and the target content match; calculating a second content match feature using said set of terms, said second content match feature comprising a translation proportion feature indicating a proportion of related terms in the electronic advertisement and the target content; and processing said first content match feature and said second content match feature with a machine learning model to output a relevance score indicating the relevance of the electronic advertisement to the target content, the machine learning model comprising individual weights for the first and second content match features, the machine learning model being trained using said first and second content match features and machine learning techniques. 15. The method of claim 11 , wherein said electronic advertisement and target content comprise different vocabularies, said first and second content match features providing a translation between said electronic advertisement and target content vocabularies. | 0.738911 |
1. A method operating on one or more network devices, comprising: detecting a communication about a target media content; obtaining a plurality of target media content variables that map to one or more social interaction attributes associated with the communication; nominally factoring at least one of the plurality of target media content variables; and determining a classification for the target media content by providing the plurality of target media content variables, including the nominally factored target media content variable, to a classifier trained using at least one nominally factored training media content dataset that maps to at least one training social interaction attribute. | 1. A method operating on one or more network devices, comprising: detecting a communication about a target media content; obtaining a plurality of target media content variables that map to one or more social interaction attributes associated with the communication; nominally factoring at least one of the plurality of target media content variables; and determining a classification for the target media content by providing the plurality of target media content variables, including the nominally factored target media content variable, to a classifier trained using at least one nominally factored training media content dataset that maps to at least one training social interaction attribute. 5. The method of claim 1 , further comprising: obtaining the plurality of target media content variables from a synchronous social activity or asynchronous social activity associated with the communication. | 0.782105 |
1. A method to reduce security vulnerability in association with a cloud-based static analysis security tool that is accessible by a set of application development environments, comprising: associating a social networking platform with the application development environments; enabling anonymous access to the social networking platform by users of the application development environments, the anonymous access enabling users to upload messages for posting to a forum; prior to posting, filtering a message and, responsive to the filtering, automatically obfuscating sensitive data associated with a particular application development environment and any application code included in the message; receiving security findings generated as users of the application development environments use the cloud-based static analysis security tool; processing the received security findings using machine learning, and storing the processed security findings into a knowledgebase; and providing social network content associated with the processed security findings from the knowledgebase as crowdsourced security knowledge generated from use of the cloud-based static analysis security tool by users of the application development environments. | 1. A method to reduce security vulnerability in association with a cloud-based static analysis security tool that is accessible by a set of application development environments, comprising: associating a social networking platform with the application development environments; enabling anonymous access to the social networking platform by users of the application development environments, the anonymous access enabling users to upload messages for posting to a forum; prior to posting, filtering a message and, responsive to the filtering, automatically obfuscating sensitive data associated with a particular application development environment and any application code included in the message; receiving security findings generated as users of the application development environments use the cloud-based static analysis security tool; processing the received security findings using machine learning, and storing the processed security findings into a knowledgebase; and providing social network content associated with the processed security findings from the knowledgebase as crowdsourced security knowledge generated from use of the cloud-based static analysis security tool by users of the application development environments. 5. The method as described in claim 1 further including: collecting information about use of the social networking platform; and modifying at least one function or characteristic of the social networking platform based on the collected information. | 0.62448 |
1. A method for generating a graph segment providing a gist or summary of an online social network conversation, the method comprising: generating, by a processor, a graph of the online social network conversation, wherein the graph of the online social network conversation comprises a plurality of nodes and each node connecting at least one other node by an edge, each node representing a message of the online social network conversation and each edge corresponding to an action by a participant in the online social network conversation; determining, by the processor, an edge weight for each edge; analyzing, by the processor, the graph of the online social network conversation, by the processor, using at least the edge weight of at least some of the edges; and generating, by the processor, a graph segment comprising a reduced number of nodes of the graph of the online social network conversation based on analyzing the graph of the online social network conversation and the graph segment providing a gist or summary comprising an abbreviated view of the online social network conversation based on the analysis, each node of the reduced number of nodes corresponding to its own respective node of the graph of the online social network conversation. | 1. A method for generating a graph segment providing a gist or summary of an online social network conversation, the method comprising: generating, by a processor, a graph of the online social network conversation, wherein the graph of the online social network conversation comprises a plurality of nodes and each node connecting at least one other node by an edge, each node representing a message of the online social network conversation and each edge corresponding to an action by a participant in the online social network conversation; determining, by the processor, an edge weight for each edge; analyzing, by the processor, the graph of the online social network conversation, by the processor, using at least the edge weight of at least some of the edges; and generating, by the processor, a graph segment comprising a reduced number of nodes of the graph of the online social network conversation based on analyzing the graph of the online social network conversation and the graph segment providing a gist or summary comprising an abbreviated view of the online social network conversation based on the analysis, each node of the reduced number of nodes corresponding to its own respective node of the graph of the online social network conversation. 6. The method of claim 1 , wherein determining the edge weight of a particular edge associated with a particular message comprises one of: determining a frequency of posts by a user that posted the particular message, the frequency of posts by the user providing an indication of a strength of the user, the edge weight corresponding to the strength of the user; determining an expertise of the user on a topic of the particular message, the edge weight corresponding to a level of expertise of the user on the topic of the particular message, wherein the topic of the particular message is determined by natural language processing; and determining a number of followers of the user and an expertise of the user on the topic of the particular message, the edge weight corresponding to a function of the number of followers of the user and the level of expertise of the user on the topic of the particular message. | 0.5 |
1. A method, performed by a first application executing at a computer system having a digital data storage device, for annotating a multimedia file, comprising: displaying a timeline, the timeline indicative of a duration of the multimedia file; receiving an indication to add an annotation at an annotation time relative to the duration indicated by the timeline, the indication automatically made by the first application while observing a user action in respect to use by a user of a second application that is different from the first application and executing at the same computer system as the first application, wherein the annotation includes information relating to a change the user made to a document opened by the second application; identifying the annotation based on the user action; storing in the digital data storage device the received annotation; associating the stored annotation with the annotation time; and displaying at an area near the timeline an indication of the stored annotation, the area corresponding to the annotation time. | 1. A method, performed by a first application executing at a computer system having a digital data storage device, for annotating a multimedia file, comprising: displaying a timeline, the timeline indicative of a duration of the multimedia file; receiving an indication to add an annotation at an annotation time relative to the duration indicated by the timeline, the indication automatically made by the first application while observing a user action in respect to use by a user of a second application that is different from the first application and executing at the same computer system as the first application, wherein the annotation includes information relating to a change the user made to a document opened by the second application; identifying the annotation based on the user action; storing in the digital data storage device the received annotation; associating the stored annotation with the annotation time; and displaying at an area near the timeline an indication of the stored annotation, the area corresponding to the annotation time. 5. The method of claim 1 wherein the annotation is text. | 0.544209 |
14. A system of matching users to other users, the system comprising: at least one data store for storing event data comprising order data reflective of items ordered from an electronic catalog by each of a plurality of users; and at least one computing device including a processor in communication with the at least one data store, the at least one computing device operable to: programmatically generate a score that reflects a degree to which item preferences of a first user of said plurality of users are similar to item preferences of a second user of said plurality of users, said score taking into consideration a first plurality of items ordered by the first user, a second plurality of items ordered by the second user, and a type of one or more of the items ordered in common between the first and second users, said score further taking into consideration at least one additional type of event data reflective of user affinities for items represented in the electronic catalog, wherein generating the score further comprises accessing item similarity data to determine whether an item ordered by the first user is similar to an item ordered by the second user; and and based at least in part on the score, programmatically determine whether to recommend the second user to the first user. | 14. A system of matching users to other users, the system comprising: at least one data store for storing event data comprising order data reflective of items ordered from an electronic catalog by each of a plurality of users; and at least one computing device including a processor in communication with the at least one data store, the at least one computing device operable to: programmatically generate a score that reflects a degree to which item preferences of a first user of said plurality of users are similar to item preferences of a second user of said plurality of users, said score taking into consideration a first plurality of items ordered by the first user, a second plurality of items ordered by the second user, and a type of one or more of the items ordered in common between the first and second users, said score further taking into consideration at least one additional type of event data reflective of user affinities for items represented in the electronic catalog, wherein generating the score further comprises accessing item similarity data to determine whether an item ordered by the first user is similar to an item ordered by the second user; and and based at least in part on the score, programmatically determine whether to recommend the second user to the first user. 19. The system of claim 14 , wherein the score is further reflective of a degree to which respective search histories of the first and second users are similar. | 0.603471 |
4. The apparatus of claim 1 , wherein the start-shot determination unit comprises: a pre-processing unit to determine frames belonging to a respective scene by detecting scene change among frames included in the video sequences and to obtain the total number of main characters appearing in the video sequences; a face detection unit to detect faces from the determined frames belonging to the respective scene to determine face detection frames; and a key-frame determination unit to cluster the determined face detection frames according to the main characters corresponding to the total number of main characters to determine the key-frames. | 4. The apparatus of claim 1 , wherein the start-shot determination unit comprises: a pre-processing unit to determine frames belonging to a respective scene by detecting scene change among frames included in the video sequences and to obtain the total number of main characters appearing in the video sequences; a face detection unit to detect faces from the determined frames belonging to the respective scene to determine face detection frames; and a key-frame determination unit to cluster the determined face detection frames according to the main characters corresponding to the total number of main characters to determine the key-frames. 6. The apparatus of claim 4 , wherein the pre-processing unit obtains the total number of main characters from the electronic program guide (EPG) signal. | 0.775452 |
3. The computer implemented method of claim 2 , wherein the domain definition data structure comprises a plurality of stream processing component data structures in the description language, wherein each stream processing component data structure describes one or more input ports and one or more output ports. | 3. The computer implemented method of claim 2 , wherein the domain definition data structure comprises a plurality of stream processing component data structures in the description language, wherein each stream processing component data structure describes one or more input ports and one or more output ports. 4. The computer implemented method of claim 3 , wherein a given stream processing component data structure within the plurality of stream processing component data structures defines a plurality of output ports. | 0.874899 |
21. A computer program product comprising at least one recordable-type computer-readable medium encoded with a plurality of computer-executable instructions that, when executed, perform a method comprising: training a plurality of sentence annotation models on a corpus of annotated sentences, wherein each sentence annotation model of the plurality of sentence annotation models uses a different sentence annotation algorithm; applying each of the plurality of sentence annotation models to a first sentence not included in the corpus of annotated sentences, to generate a plurality of sentence annotations, each of the plurality of sentence annotations resulting from application of one of the plurality of sentence annotation models to the first sentence, each of the plurality of sentence annotations comprising a parse tree that includes a set of tags, labels, and/or connections for words of the first sentence; and comparing the plurality of sentence annotations to select a best sentence annotation for the first sentence from among the plurality of sentence annotations, wherein the comparing comprises: sending the parse tree resulting from application of each of the plurality of sentence annotation models to a rover; determining in the rover a best set of tags, labels, and/or connections for the first sentence based on a comparison of the sets of tags, labels, and/or connections resulting from application of the plurality of sentence annotation models; annotating words of the first sentence using the best set of tags, labels, and/or connections; and tagging the best set of tags, labels, and/or connections as reliable or unreliable. | 21. A computer program product comprising at least one recordable-type computer-readable medium encoded with a plurality of computer-executable instructions that, when executed, perform a method comprising: training a plurality of sentence annotation models on a corpus of annotated sentences, wherein each sentence annotation model of the plurality of sentence annotation models uses a different sentence annotation algorithm; applying each of the plurality of sentence annotation models to a first sentence not included in the corpus of annotated sentences, to generate a plurality of sentence annotations, each of the plurality of sentence annotations resulting from application of one of the plurality of sentence annotation models to the first sentence, each of the plurality of sentence annotations comprising a parse tree that includes a set of tags, labels, and/or connections for words of the first sentence; and comparing the plurality of sentence annotations to select a best sentence annotation for the first sentence from among the plurality of sentence annotations, wherein the comparing comprises: sending the parse tree resulting from application of each of the plurality of sentence annotation models to a rover; determining in the rover a best set of tags, labels, and/or connections for the first sentence based on a comparison of the sets of tags, labels, and/or connections resulting from application of the plurality of sentence annotation models; annotating words of the first sentence using the best set of tags, labels, and/or connections; and tagging the best set of tags, labels, and/or connections as reliable or unreliable. 25. The computer program product of claim 21 , wherein the method further comprises: adding the best sentence annotation in association with the first sentence to a set of training data that includes sentences annotated by a human annotator; and annotating a second sentence using the set of training data. | 0.537056 |
3. The method of claim 1 , where identifying that the search query is associated with the type of media includes: determining whether the candidate queries match words in a keyword list associated with the type of media, and identifying, based on the first ratio and the second ratio, that the search query is associated with the type of media when the category matches one of the candidate queries and when the candidate queries match the words in the keyword list. | 3. The method of claim 1 , where identifying that the search query is associated with the type of media includes: determining whether the candidate queries match words in a keyword list associated with the type of media, and identifying, based on the first ratio and the second ratio, that the search query is associated with the type of media when the category matches one of the candidate queries and when the candidate queries match the words in the keyword list. 6. The method of claim 3 , where determining whether the candidate queries match the words in the keyword list includes: determining a sum of values associated with one or more of the words in the keyword list that match one or more words included in the candidate queries, and determining that the candidate queries match the words in the keyword list when the sum of the values is greater than a threshold. | 0.878717 |
1. A method comprising: determining, by one or more computing devices, a target geographic feature that does not initially have associated targeting information for providing targeted content associated with the target geographic feature, the target geographic feature defining a first geographic area; determining, by the one or more computing devices, one or more similar geographic features to the target geographic feature based at least in part on a comparison of query counts for each of a plurality of geographic features, the one or more similar geographic features defining one or more geographic areas distinct from the first geographic area, the one or more similar geographic features having associated targeting information; attributing, by the one or more computing devices, targeting information associated with at least one of the one or more similar geographic features to the target geographic feature; and providing, by the one or more computing devices, related targeted content responsive to one or more queries that relate to the target geographic feature, the related targeted content identified based at least in part on the attributed targeting information. | 1. A method comprising: determining, by one or more computing devices, a target geographic feature that does not initially have associated targeting information for providing targeted content associated with the target geographic feature, the target geographic feature defining a first geographic area; determining, by the one or more computing devices, one or more similar geographic features to the target geographic feature based at least in part on a comparison of query counts for each of a plurality of geographic features, the one or more similar geographic features defining one or more geographic areas distinct from the first geographic area, the one or more similar geographic features having associated targeting information; attributing, by the one or more computing devices, targeting information associated with at least one of the one or more similar geographic features to the target geographic feature; and providing, by the one or more computing devices, related targeted content responsive to one or more queries that relate to the target geographic feature, the related targeted content identified based at least in part on the attributed targeting information. 7. The method of claim 1 , further comprising: creating a graph of geographic features where 1) each vertex in the graph is one of the plurality of geographic features, 2) edges of the graph that connect the geographic features are weighted, and 3) geographic features that are found to be similar are connected in the graph; and propagating labels over the graph. | 0.591718 |
13. The computer readable medium of claim 12 , wherein the table schema represents a graph of the applied data model. | 13. The computer readable medium of claim 12 , wherein the table schema represents a graph of the applied data model. 14. The computer readable medium of claim 13 , wherein the set of statements is operable to perform a graph search. | 0.971954 |
15. A computer program product comprising a computer-readable storage medium including instructions that, when executed by a processor, cause the processor to: generate a location store comprising a plurality of entries maintained by a social networking system, each entry including a physical location description and one or more terms associated with the physical location description; identify a plurality of entries having a physical location description within an area; determine a local frequency associated with each term included the identified plurality of entries, the local frequency of a term representing a number of occurrences of the term within the identified plurality of entries; determine a global frequency associated with each term included in the identified plurality of entries, the global frequency of the term representing a number of occurrences of the term within the location store; identify one or more terms having an associated local frequency exceeding an associated global frequency by at least a threshold amount as trending terms; generate a score for an entry from the plurality of entries based at least in part on one or more difference between terms in the entry from the plurality of entries and terms in an additional entry from a plurality of entries and whether a term in the entry differing from a term in the additional entry is a trending term; and generate a combined entry including terms from the entry and from the additional entry if the score is less than a threshold value. | 15. A computer program product comprising a computer-readable storage medium including instructions that, when executed by a processor, cause the processor to: generate a location store comprising a plurality of entries maintained by a social networking system, each entry including a physical location description and one or more terms associated with the physical location description; identify a plurality of entries having a physical location description within an area; determine a local frequency associated with each term included the identified plurality of entries, the local frequency of a term representing a number of occurrences of the term within the identified plurality of entries; determine a global frequency associated with each term included in the identified plurality of entries, the global frequency of the term representing a number of occurrences of the term within the location store; identify one or more terms having an associated local frequency exceeding an associated global frequency by at least a threshold amount as trending terms; generate a score for an entry from the plurality of entries based at least in part on one or more difference between terms in the entry from the plurality of entries and terms in an additional entry from a plurality of entries and whether a term in the entry differing from a term in the additional entry is a trending term; and generate a combined entry including terms from the entry and from the additional entry if the score is less than a threshold value. 19. The computer program product of claim 15 , wherein identify one or more terms having the associated local frequency exceeding the associated global frequency by at least a threshold amount as trending terms comprises: identify one or more terms having a ratio of a local frequency associated with a term to a global frequency associated with the term that equals or exceeds a specified value as one or more trending terms. | 0.570616 |
1. In a medical implant assembly having first and second bone attachment structures cooperating with a longitudinal connecting member, the improvement wherein the longitudinal connecting member comprises: a) an anchor member portion passing through and secured directly to the first bone attachment structure, the anchor member portion having a first width and having an integral core extension of reduced second width, the core extension extending from the anchor member portion along a substantially central axis of the longitudinal connecting member, the first and second widths being measured perpendicular to the central axis; b) a first elastic outer spacer, the core extension being received in the spacer, the spacer being positioned between the two bone attachment structures; c) a second elastic outer spacer, the core extension being received in the second spacer, the second spacer being more compressible than the first spacer, both the first and second spacers being pre-compressed prior to attachment of the assembly to the bone attachment structures; the second elastic outer spacer being located relative to the core extension so as to not be between the first and second bone attachment structures; and d) a substantially inelastic sleeve, the core extension being received through the sleeve and in slidable relationship therewith, the sleeve passing through and secured in the second bone attachment structure, the sleeve being disposed between the first and second pre-compressed spacers, the pre-compressed spacers exerting axial forces on the sleeve. | 1. In a medical implant assembly having first and second bone attachment structures cooperating with a longitudinal connecting member, the improvement wherein the longitudinal connecting member comprises: a) an anchor member portion passing through and secured directly to the first bone attachment structure, the anchor member portion having a first width and having an integral core extension of reduced second width, the core extension extending from the anchor member portion along a substantially central axis of the longitudinal connecting member, the first and second widths being measured perpendicular to the central axis; b) a first elastic outer spacer, the core extension being received in the spacer, the spacer being positioned between the two bone attachment structures; c) a second elastic outer spacer, the core extension being received in the second spacer, the second spacer being more compressible than the first spacer, both the first and second spacers being pre-compressed prior to attachment of the assembly to the bone attachment structures; the second elastic outer spacer being located relative to the core extension so as to not be between the first and second bone attachment structures; and d) a substantially inelastic sleeve, the core extension being received through the sleeve and in slidable relationship therewith, the sleeve passing through and secured in the second bone attachment structure, the sleeve being disposed between the first and second pre-compressed spacers, the pre-compressed spacers exerting axial forces on the sleeve. 21. The improvement of claim 1 further comprising at least a third elastic and pre-compressed spacer. | 0.579171 |
8. A computer program product for query processing based on normalized search terms, the computer program product comprising: a non-transitory computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code comprising: computer-readable program code configured to, responsive to receiving a query, generate a normalized search term for a concept in the query based on a first language model, of a plurality of language models each having a predefined association with a respective concept; computer-readable program code configured to modify the query to include the normalized search term; computer-readable program code configured to execute the modified query against the indexed corpus of evidence, where the corpus of evidence is indexed based on the plurality of language models to include a set of normalized terms for each respective item of evidence in the corpus, wherein the indexed corpus of evidence includes a first item of evidence used to support a first candidate answer, of a plurality of candidate answers; and computer-readable program code configured to, upon determining that the set of normalized terms for the first item of evidence includes the normalized search term, returning the first candidate answer as responsive to the query. | 8. A computer program product for query processing based on normalized search terms, the computer program product comprising: a non-transitory computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code comprising: computer-readable program code configured to, responsive to receiving a query, generate a normalized search term for a concept in the query based on a first language model, of a plurality of language models each having a predefined association with a respective concept; computer-readable program code configured to modify the query to include the normalized search term; computer-readable program code configured to execute the modified query against the indexed corpus of evidence, where the corpus of evidence is indexed based on the plurality of language models to include a set of normalized terms for each respective item of evidence in the corpus, wherein the indexed corpus of evidence includes a first item of evidence used to support a first candidate answer, of a plurality of candidate answers; and computer-readable program code configured to, upon determining that the set of normalized terms for the first item of evidence includes the normalized search term, returning the first candidate answer as responsive to the query. 14. The computer program product of claim 8 , wherein the corpus of evidence is a closed corpus. | 0.608423 |
13. A non-transitory memory having computer instructions stored therein, which computer instructions, when executed by a processor, cause the processor to: simultaneously display a first character-entry field that corresponds to a first function and a second character-entry field that corresponds to a second function, which second function is different from the first function; as a key of a character-input keyboard having at least some keys that correspond to at least two differing characters is asserted, dynamically determine at least a portion of a corresponding character entry to present in the second character-entry field by considering at least one likelihood of at least one interpretation of the key assertion. | 13. A non-transitory memory having computer instructions stored therein, which computer instructions, when executed by a processor, cause the processor to: simultaneously display a first character-entry field that corresponds to a first function and a second character-entry field that corresponds to a second function, which second function is different from the first function; as a key of a character-input keyboard having at least some keys that correspond to at least two differing characters is asserted, dynamically determine at least a portion of a corresponding character entry to present in the second character-entry field by considering at least one likelihood of at least one interpretation of the key assertion. 14. The non-transitory memory of claim 13 wherein the first character-entry field comprises a search entry text field. | 0.802381 |
1. A computer-implemented method comprising: receiving, at a computing system including one or more processors, a plurality of n-grams, each n-gram representing a sequence of one or more consecutive words, and each n-gram being associated with a value for a parameter related to a probability of the n-gram with respect to a corpus; determining, at the computing system, a fingerprint for each of the plurality of n-grams to obtain a plurality of fingerprints, each fingerprint representing a distinct index for a specific n-gram; identifying, at the computing system, a location in an array for each of the plurality of n-grams using a perfect hash function to obtain a plurality of locations, wherein the array associates the plurality of fingerprints with the plurality of n-grams, respectively; and encoding, at the computing system, the value of the parameter for each of the plurality of n-grams in the array to obtain a modified array, wherein the value of the parameter for a specific n-gram is encoded at a specific location in the array that is associated with the specific n-gram. | 1. A computer-implemented method comprising: receiving, at a computing system including one or more processors, a plurality of n-grams, each n-gram representing a sequence of one or more consecutive words, and each n-gram being associated with a value for a parameter related to a probability of the n-gram with respect to a corpus; determining, at the computing system, a fingerprint for each of the plurality of n-grams to obtain a plurality of fingerprints, each fingerprint representing a distinct index for a specific n-gram; identifying, at the computing system, a location in an array for each of the plurality of n-grams using a perfect hash function to obtain a plurality of locations, wherein the array associates the plurality of fingerprints with the plurality of n-grams, respectively; and encoding, at the computing system, the value of the parameter for each of the plurality of n-grams in the array to obtain a modified array, wherein the value of the parameter for a specific n-gram is encoded at a specific location in the array that is associated with the specific n-gram. 10. The computer-implemented method of claim 1 , wherein identifying locations in the array further comprises: building the array having a specified number of locations; identifying the plurality of locations corresponding to the plurality of n-grams, respectively; identifying a first n-gram-location pair corresponding to a first n-gram associated with a first location of degree one, where the first location is of degree one when no other n-gram of the plurality of n-grams is associated with the first location; and removing the first n-gram-location pair such that the n-gram no longer corresponds to any other locations in the array such that one or more other locations in the array are of degree one. | 0.5 |
15. A method for combining multiple clusterings comprising the steps of: automatically iteratively determining, using at least one computer, whether a matrix convergence criterion is satisfied, and if not, automatically computing S (h) ←S (h) ⊙((M (h) ) T M+βk1 khk )/(D+ε); computing M = 1 r ∑ h = 1 r M ( h ) S ( h ) ; and storing M in a memory, wherein: ⊙ denotes the Hadamard product of two matrices, M denotes a membership matrix of a target clustering, M (h) denotes a membership matrix of a source clustering, S (h) denotes a correspondence matrix of M (h) with respect to M. β is a constant ≧0, for scaling a penalty term added to a consensus function f(M,S (1) ,S (2) , . . . , S (r) ) to deal with an external constraint Σ j S (h) ij =1 efficiently, k denotes the number of clusters, r denotes the number of correspondence matrices 1 khkh denotes a k h -by-k h matrix of 1s,
D= ( M (h) ) T M (h) S (h) −αS (h) +(α /k h )1 khkh S (h) +βkS (h) 1 kk , α is a constant ≧0, selected to enforce a column-sparseness constraint, by adding a term to the consensus function, and ε is a very small positive number used to avoid dividing by 0. | 15. A method for combining multiple clusterings comprising the steps of: automatically iteratively determining, using at least one computer, whether a matrix convergence criterion is satisfied, and if not, automatically computing S (h) ←S (h) ⊙((M (h) ) T M+βk1 khk )/(D+ε); computing M = 1 r ∑ h = 1 r M ( h ) S ( h ) ; and storing M in a memory, wherein: ⊙ denotes the Hadamard product of two matrices, M denotes a membership matrix of a target clustering, M (h) denotes a membership matrix of a source clustering, S (h) denotes a correspondence matrix of M (h) with respect to M. β is a constant ≧0, for scaling a penalty term added to a consensus function f(M,S (1) ,S (2) , . . . , S (r) ) to deal with an external constraint Σ j S (h) ij =1 efficiently, k denotes the number of clusters, r denotes the number of correspondence matrices 1 khkh denotes a k h -by-k h matrix of 1s,
D= ( M (h) ) T M (h) S (h) −αS (h) +(α /k h )1 khkh S (h) +βkS (h) 1 kk , α is a constant ≧0, selected to enforce a column-sparseness constraint, by adding a term to the consensus function, and ε is a very small positive number used to avoid dividing by 0. 17. The method according to claim 15 , wherein the multiple clusterings comprise clusterings of content anchor text, uniform resource locators (URLs), and hyperlinks of respective hyperlinked documents. | 0.653734 |
2. A method according to claim 1 , further comprising: during the registration process by said user of said telephone call management system: assigning an identification to said user; associating said identification with said first speech sample in said database; during the each subsequent access attempt by said user to said telephone call management system to place said telephone call: receiving said identification from said user; and locating said first speech sample in said database using said identification. | 2. A method according to claim 1 , further comprising: during the registration process by said user of said telephone call management system: assigning an identification to said user; associating said identification with said first speech sample in said database; during the each subsequent access attempt by said user to said telephone call management system to place said telephone call: receiving said identification from said user; and locating said first speech sample in said database using said identification. 5. A method according to claim 2 , wherein allowing said telephone call to be completed further comprises: querying said database with said identification to determining whether said user is authorized to place said call; and allowing said telephone call to be completed when said user is authorized to place said telephone call and when a voice characteristic of a second speech sample matches a voice characteristic of said first speech sample. | 0.750586 |
1. A computer-implemented method for controlling access to a portion of a document, the document comprising a plurality of portions, the method performed by at least one processor, the method comprising: receiving a request to access the document portion; identifying a variable accessibility rule associated with the requested document portion; evaluating the rule based on data describing past accesses of other ones of the plurality of document portions; determining whether to provide access to the requested document portion responsive to the evaluation of the rule; and responding to the request based on the determination. | 1. A computer-implemented method for controlling access to a portion of a document, the document comprising a plurality of portions, the method performed by at least one processor, the method comprising: receiving a request to access the document portion; identifying a variable accessibility rule associated with the requested document portion; evaluating the rule based on data describing past accesses of other ones of the plurality of document portions; determining whether to provide access to the requested document portion responsive to the evaluation of the rule; and responding to the request based on the determination. 10. The method of claim 1 , wherein evaluating the rule based on data describing past accesses of other ones of the plurality of document portions comprises evaluating the rule based on data describing past accesses of other ones of the plurality of document portions and further based on data describing past accesses of the requested document portion. | 0.576691 |
1. A computer-implemented method for providing a knowledge-embedded answer to a content-dependent question received in an online tax-related question-answer website, comprising: providing an information-viewing application to a first user computer for installation on the first user computer; receiving, at a transmission server for a provider of an online tax-related question-answer website, a first question from a first user, wherein the transmission server comprises a processor and a memory, and wherein the first question is related to taxes; accessing a partitioned standardized terminology data section of the memory to retrieve standardized terminology associated with the first question; replacing user-specific terminology in the first question with the accessed standardized terminology; receiving, at the transmission server for the provider of the online tax-related question-answer website, a second question from a second user, wherein the second question is related to taxes; accessing the partitioned standardized terminology data section of the memory to retrieve a standardized terminology associated with the second question; replacing user-specific terminology in the second question with the accessed standardized terminology; evaluating, with the processor, a relationship between the first question and the second question based on a determined metric, wherein the metric involves one or more statistical associations calculated based on either a hierarchical level or weighted sum between tax phrases and tax concepts in the first and second questions; combining the first question and the second question to generate a third question based on the evaluation; identifying partitioned tax-information data sections of the memory associated with the tax phrases and tax concepts in the third question, wherein the partitioned tax-information data sections of the memory comprise tax phrases, context information associated with the tax phrases, and tax concepts that encompass multiple tax phrases; associating a hyperlink with at least one of the tax phrases; generating, by the processor, an answer to the third question based on the identified one or more locations in the tax-information data sections; transmitting, over a data channel, from the transmission server of the provider of the online tax-related question-answer website, the generated answer to the first user for display at the information-viewing application on the first user computer for viewing by the first user; transmitting, over the data channel, from the transmission server of the provider of the online tax-related question-answer website, the associated hyperlink; and activating, in the information viewing application on the first user computer, a display of the hyperlink for interaction with the first user. | 1. A computer-implemented method for providing a knowledge-embedded answer to a content-dependent question received in an online tax-related question-answer website, comprising: providing an information-viewing application to a first user computer for installation on the first user computer; receiving, at a transmission server for a provider of an online tax-related question-answer website, a first question from a first user, wherein the transmission server comprises a processor and a memory, and wherein the first question is related to taxes; accessing a partitioned standardized terminology data section of the memory to retrieve standardized terminology associated with the first question; replacing user-specific terminology in the first question with the accessed standardized terminology; receiving, at the transmission server for the provider of the online tax-related question-answer website, a second question from a second user, wherein the second question is related to taxes; accessing the partitioned standardized terminology data section of the memory to retrieve a standardized terminology associated with the second question; replacing user-specific terminology in the second question with the accessed standardized terminology; evaluating, with the processor, a relationship between the first question and the second question based on a determined metric, wherein the metric involves one or more statistical associations calculated based on either a hierarchical level or weighted sum between tax phrases and tax concepts in the first and second questions; combining the first question and the second question to generate a third question based on the evaluation; identifying partitioned tax-information data sections of the memory associated with the tax phrases and tax concepts in the third question, wherein the partitioned tax-information data sections of the memory comprise tax phrases, context information associated with the tax phrases, and tax concepts that encompass multiple tax phrases; associating a hyperlink with at least one of the tax phrases; generating, by the processor, an answer to the third question based on the identified one or more locations in the tax-information data sections; transmitting, over a data channel, from the transmission server of the provider of the online tax-related question-answer website, the generated answer to the first user for display at the information-viewing application on the first user computer for viewing by the first user; transmitting, over the data channel, from the transmission server of the provider of the online tax-related question-answer website, the associated hyperlink; and activating, in the information viewing application on the first user computer, a display of the hyperlink for interaction with the first user. 4. The method of claim 1 , wherein, after generating the answer, the method further involves providing the third question to other users. | 0.564202 |
13. A system comprising: a specialized language processor; and a graphic user interface operatively connected to said specialized language processor, said specialized language processor automatically monitoring communications, said communications comprising computerized text forming a conversation conducted between at least two conversation partners, said conversation partners comprising an agent using a specialized language processor and a user, said conversation comprising multiple turns of text utterances exchanged between said conversation partners relating to a specific issue; said specialized language processor automatically analyzing said communications to simultaneously determine, for said conversation, mental state variables of said user, said mental state variables comprising: an emotion of said user; a mood of said user; and a personality of said user; and said specialized language processor automatically aggregating said emotion, said mood, and said personality using a hierarchical probabilistic graphical model that determines a highest probability path through a directed probabilistic graph to infer said mental state of said user, said directed probabilistic graph comprising a single personality node that maintains a single unchanging state, multiple mood nodes, multiple emotion nodes, and multiple evidence nodes, each of said mood nodes, said emotion nodes, and said evidence nodes being for a different time portion of said conversation, said specialized language processor automatically and constantly updating said mental state of said user during said conversation by maintaining, in said directed probabilistic graph, a single unchanging state for said personality for all of said conversation, and maintaining multiple changing states for said emotion and said mood as said conversation progresses to track said mental state of said user during said conversation, said specialized language processor automatically and constantly updating said mental state of said user as said specialized language processor tracks said mental state of said user during said conversation, and said graphic user interface automatically and constantly displaying said mental state to said agent as said mental state is constantly updated during said conversation by displaying said emotion, said mood, and said personality. | 13. A system comprising: a specialized language processor; and a graphic user interface operatively connected to said specialized language processor, said specialized language processor automatically monitoring communications, said communications comprising computerized text forming a conversation conducted between at least two conversation partners, said conversation partners comprising an agent using a specialized language processor and a user, said conversation comprising multiple turns of text utterances exchanged between said conversation partners relating to a specific issue; said specialized language processor automatically analyzing said communications to simultaneously determine, for said conversation, mental state variables of said user, said mental state variables comprising: an emotion of said user; a mood of said user; and a personality of said user; and said specialized language processor automatically aggregating said emotion, said mood, and said personality using a hierarchical probabilistic graphical model that determines a highest probability path through a directed probabilistic graph to infer said mental state of said user, said directed probabilistic graph comprising a single personality node that maintains a single unchanging state, multiple mood nodes, multiple emotion nodes, and multiple evidence nodes, each of said mood nodes, said emotion nodes, and said evidence nodes being for a different time portion of said conversation, said specialized language processor automatically and constantly updating said mental state of said user during said conversation by maintaining, in said directed probabilistic graph, a single unchanging state for said personality for all of said conversation, and maintaining multiple changing states for said emotion and said mood as said conversation progresses to track said mental state of said user during said conversation, said specialized language processor automatically and constantly updating said mental state of said user as said specialized language processor tracks said mental state of said user during said conversation, and said graphic user interface automatically and constantly displaying said mental state to said agent as said mental state is constantly updated during said conversation by displaying said emotion, said mood, and said personality. 18. The system according to claim 13 , said single personality node being stable over said conversation, said multiple mood nodes having short term temporal stability over said conversation, and said multiple emotion nodes having instantaneous temporal stability over said conversation. | 0.5 |
6. The system of claim 1 , further comprising a user recognition component that recognizes a user based upon a dialect associated with the voice commands. | 6. The system of claim 1 , further comprising a user recognition component that recognizes a user based upon a dialect associated with the voice commands. 7. The system of claim 6 , further comprising a classification component that aids in voice recognition upon recognition of identity of the user. | 0.954146 |
2. The method of claim 1 , wherein generating a speech model based on the text string and the set of user spoken utterances further comprises obtaining a Hidden Markov Model of the text string. | 2. The method of claim 1 , wherein generating a speech model based on the text string and the set of user spoken utterances further comprises obtaining a Hidden Markov Model of the text string. 3. The method of claim 2 , wherein obtaining the Hidden Markov Model of the text string includes training a set of phoneme Hidden Markov Models with speech data. | 0.951929 |
26. The apparatus of claim 17 , wherein the speech signal is represented by a residual signal generated by filtering the speech signal with a Linear Predictive Coding (LPC) analysis filter, and wherein said plurality of encoding means includes a NELP encoding means comprising: energy estimator means for calculating an estimate of the energy of the residual signal, and encoding codebook means for selecting a codevector from a first codebook, wherein said codevector approximates said estimated energy; and wherein said plurality of decoding means includes a NELP decoding means comprising: random number generator means for generating a random vector, decoding codebook means for retrieving said codevector from a second codebook, multiply means for scaling said random vector based on said codevector, such that the energy of said scaled random vector approximates said estimate, and means for filtering said scaled random vector with an LPC synthesis filter, wherein said filtered scaled random vector forms said synthesized speech signal. | 26. The apparatus of claim 17 , wherein the speech signal is represented by a residual signal generated by filtering the speech signal with a Linear Predictive Coding (LPC) analysis filter, and wherein said plurality of encoding means includes a NELP encoding means comprising: energy estimator means for calculating an estimate of the energy of the residual signal, and encoding codebook means for selecting a codevector from a first codebook, wherein said codevector approximates said estimated energy; and wherein said plurality of decoding means includes a NELP decoding means comprising: random number generator means for generating a random vector, decoding codebook means for retrieving said codevector from a second codebook, multiply means for scaling said random vector based on said codevector, such that the energy of said scaled random vector approximates said estimate, and means for filtering said scaled random vector with an LPC synthesis filter, wherein said filtered scaled random vector forms said synthesized speech signal. 29. The apparatus of claim 26 , wherein said first codebook and said second codebook are trained codebooks. | 0.682681 |
21. A computer-implemented method, comprising: analyzing electronic messages of a first user with respect to one or more features associated with the electronic messages; associating descriptive tags with the electronic messages of the first user based on the analyzing; and performing tasks with respect to the electronic messages of the first user, on behalf of the first user, based on the descriptive tags associated with the respective electronic messages; wherein the analyzing includes identifying a sender of a first electronic message received by the first user and determining relevance of the first electronic message with respect to the first user as a function of at least one of, a relationship between the sender and the first user within an implied social graph of electronic message users, a quality of the relationship between the sender and the first user, a syntactic structure of the first electronic message, metadata associated with the first electronic message, a language used in the first electronic message, a character set used in the first electronic message, an action taken by the first user with respect to a second electronic message for which one or more features are similar to one or more corresponding features of the first electronic message, and an action taken by a second user with respect to an electronic message received by the second user for which one or more features are similar to one or more corresponding features of the first electronic message. | 21. A computer-implemented method, comprising: analyzing electronic messages of a first user with respect to one or more features associated with the electronic messages; associating descriptive tags with the electronic messages of the first user based on the analyzing; and performing tasks with respect to the electronic messages of the first user, on behalf of the first user, based on the descriptive tags associated with the respective electronic messages; wherein the analyzing includes identifying a sender of a first electronic message received by the first user and determining relevance of the first electronic message with respect to the first user as a function of at least one of, a relationship between the sender and the first user within an implied social graph of electronic message users, a quality of the relationship between the sender and the first user, a syntactic structure of the first electronic message, metadata associated with the first electronic message, a language used in the first electronic message, a character set used in the first electronic message, an action taken by the first user with respect to a second electronic message for which one or more features are similar to one or more corresponding features of the first electronic message, and an action taken by a second user with respect to an electronic message received by the second user for which one or more features are similar to one or more corresponding features of the first electronic message. 26. The method of claim 21 , wherein the determining relevance includes: determining the relevance based at least in part on the character set used in the first electronic message. | 0.64686 |
1. A method of providing user communications, the method comprising: creating, by a computing system comprising a computing device and a network interface, a user account at least partly in response to receiving account registration information from a user; providing an application software program for installation on a mobile computing device associated with the user; receiving, at the computing system, from a first visitor to a web document of the user, a communication request to communicate with the user via a communication interface displayed in association with the web document of the user; at least partly in response to receiving a presence indication at the computing system that the application software program is online, transmitting, by the computing system, to the application software program installed on the mobile computing device associated with the user, a text message entered by the first visitor into a text entry field, without the first visitor providing, and without revealing to the first visitor, a mobile communication device phone address of the user; and notifying the user, via the application software program installed on the mobile computing device associated with the user, of the text message transmission. | 1. A method of providing user communications, the method comprising: creating, by a computing system comprising a computing device and a network interface, a user account at least partly in response to receiving account registration information from a user; providing an application software program for installation on a mobile computing device associated with the user; receiving, at the computing system, from a first visitor to a web document of the user, a communication request to communicate with the user via a communication interface displayed in association with the web document of the user; at least partly in response to receiving a presence indication at the computing system that the application software program is online, transmitting, by the computing system, to the application software program installed on the mobile computing device associated with the user, a text message entered by the first visitor into a text entry field, without the first visitor providing, and without revealing to the first visitor, a mobile communication device phone address of the user; and notifying the user, via the application software program installed on the mobile computing device associated with the user, of the text message transmission. 11. The method as defined in claim 1 , wherein the web document is a web page of the user. | 0.930851 |
1. A computer-implemented method of refining a search query, comprising: receiving a search request from a client device, the search request including a query term and a selected search category from a hierarchical search categorization; providing a first set of search results corresponding to the query term and the selected search category to be displayed on the client device; providing an editable search refinement specification including a plurality of editable elements to be displayed along with the first set of search results, the plurality of editable elements including a first editable element, a second editable element, and a third editable element corresponding to each parent category of the selected search category in the hierarchical search categorization, each of the first editable element, the second editable element, and the third editable element being associated with text and a respective text input box element; providing a displayable option element utilized to modify a currently selected editable element of the plurality of editable elements and to be displayed along with the plurality of editable elements, the displayable option element including two or more of a set of selectable operation icons including an edit operation icon, a remove operation icon, an undo operation icon, a save operation icon, a share operation icon, an auto-complete operation icon, a help operation icon, and a suggestion operation icon; receiving an input to independently modify the text of the first editable element of the editable search refinement specification via the respective text input box element without modifying the second editable element and the third element of the editable search refinement specification; and in response to receiving the input to modify the text of the first editable element of the editable search refinement specification via the respective text input box element, providing a second set of search results corresponding to the modified first editable element, the second editable element, and the third editable element of the editable search refinement specification to be displayed on the client device. | 1. A computer-implemented method of refining a search query, comprising: receiving a search request from a client device, the search request including a query term and a selected search category from a hierarchical search categorization; providing a first set of search results corresponding to the query term and the selected search category to be displayed on the client device; providing an editable search refinement specification including a plurality of editable elements to be displayed along with the first set of search results, the plurality of editable elements including a first editable element, a second editable element, and a third editable element corresponding to each parent category of the selected search category in the hierarchical search categorization, each of the first editable element, the second editable element, and the third editable element being associated with text and a respective text input box element; providing a displayable option element utilized to modify a currently selected editable element of the plurality of editable elements and to be displayed along with the plurality of editable elements, the displayable option element including two or more of a set of selectable operation icons including an edit operation icon, a remove operation icon, an undo operation icon, a save operation icon, a share operation icon, an auto-complete operation icon, a help operation icon, and a suggestion operation icon; receiving an input to independently modify the text of the first editable element of the editable search refinement specification via the respective text input box element without modifying the second editable element and the third element of the editable search refinement specification; and in response to receiving the input to modify the text of the first editable element of the editable search refinement specification via the respective text input box element, providing a second set of search results corresponding to the modified first editable element, the second editable element, and the third editable element of the editable search refinement specification to be displayed on the client device. 4. The computer-implemented method of claim 1 , wherein the user is able to remove at least one of the plurality of the editable elements from the editable search refinement specification. | 0.583205 |
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, the system being separate from and communicatively coupled to a user device, the user device having an application installed which is associated with trigger terms for performing voice actions, the operations comprising: receiving a user utterance for a new voice action; determining multiple candidate transcriptions of the user utterance; determining whether any of the multiple candidate transcriptions contains one or more of the trigger terms; and biasing the system based on the determination, such that the system favors one of the multiple candidate transcriptions that is associated with the new voice action, wherein upon the system receiving the user utterance from the user device, the system sends an action trigger to the user device, the action trigger causing the application to perform the new voice action. | 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, the system being separate from and communicatively coupled to a user device, the user device having an application installed which is associated with trigger terms for performing voice actions, the operations comprising: receiving a user utterance for a new voice action; determining multiple candidate transcriptions of the user utterance; determining whether any of the multiple candidate transcriptions contains one or more of the trigger terms; and biasing the system based on the determination, such that the system favors one of the multiple candidate transcriptions that is associated with the new voice action, wherein upon the system receiving the user utterance from the user device, the system sends an action trigger to the user device, the action trigger causing the application to perform the new voice action. 15. The system of claim 11 , wherein the operations further include generating, based on the received user utterance, a graph comprising nodes and edges between some of the nodes, and wherein the multiple candidate transcriptions are determined, and the system is biased, using the generated graph, and wherein the nodes correspond to connections between terms, wherein the edges correspond to a candidate term that corresponds to a portion of audio data from the user utterance, and wherein the nodes or the edges, or both, are associated with probabilities indicating a determined confidence that the user utterance includes a particular term or connection between terms corresponding to the nodes or edges. | 0.5 |
1. A system for determining a mapping between a textual representation in a document and a concept, comprising: a communications interface configured to receive a document; and a processor configured to: identify a set of candidate textual representations in the document; determine, the set of candidate textual representation included in the set, a set of associated concepts included in a taxonomy of concepts; and sum a plurality of category vectors to generate a document vector, each category vector associated with an associated concept of the set of associated concepts and indicating correspondence of related concepts to the associated concept; compute a set of document similarity scores for the set of associated concepts according to a correspondence of the category vectors corresponding thereto and the document vector; select at least one representative concept of the associated concepts according to the set of document similarity scores; provide as output the representative concept and a candidate textual representation of the set of candidate textual representations corresponding thereto; and a memory coupled to the processor and configured to provide the processor with instructions. | 1. A system for determining a mapping between a textual representation in a document and a concept, comprising: a communications interface configured to receive a document; and a processor configured to: identify a set of candidate textual representations in the document; determine, the set of candidate textual representation included in the set, a set of associated concepts included in a taxonomy of concepts; and sum a plurality of category vectors to generate a document vector, each category vector associated with an associated concept of the set of associated concepts and indicating correspondence of related concepts to the associated concept; compute a set of document similarity scores for the set of associated concepts according to a correspondence of the category vectors corresponding thereto and the document vector; select at least one representative concept of the associated concepts according to the set of document similarity scores; provide as output the representative concept and a candidate textual representation of the set of candidate textual representations corresponding thereto; and a memory coupled to the processor and configured to provide the processor with instructions. 15. The system of claim 1 , wherein the processor is further configured to: determine a set of linkworthiness scores for the set of associated concepts; and further select the at lest one representative concept according to the linkworthiness scores of the set of associated concepts. | 0.5 |
9. The article of claim 8 , further comprising associating with the transaction at least one of social data, time of the transaction, date of the transaction, information about the consumer involved in the transaction or merchant feedback from the transaction. | 9. The article of claim 8 , further comprising associating with the transaction at least one of social data, time of the transaction, date of the transaction, information about the consumer involved in the transaction or merchant feedback from the transaction. 10. The article of claim 9 , further comprising adjusting, by the computer-based system and based upon the normalized popularity score, the list of the merchants that is output by a recommender system based upon a communication channel through which the consumer receives the list. | 0.937927 |
1. A computer-implemented method for providing, via a computer processor, at least one readable object that is readable by a search engine from at least one structured data object stored in a database, the method comprising: extracting, via the computer processor, the structured data object from the database, wherein the structured data object includes a hierarchical sequence of nodes related by at least one link and a plurality of content, and wherein at least one content of the plurality of content is nonreadable content that cannot be read by the search engine; mapping, via the computer processor, the structured data object into a generic data model according to the hierarchical sequence of nodes and content; and creating, via the computer processor, the readable object from the generic data model, wherein creating includes converting the nonreadable content of the structured data object into readable content for the search engine. | 1. A computer-implemented method for providing, via a computer processor, at least one readable object that is readable by a search engine from at least one structured data object stored in a database, the method comprising: extracting, via the computer processor, the structured data object from the database, wherein the structured data object includes a hierarchical sequence of nodes related by at least one link and a plurality of content, and wherein at least one content of the plurality of content is nonreadable content that cannot be read by the search engine; mapping, via the computer processor, the structured data object into a generic data model according to the hierarchical sequence of nodes and content; and creating, via the computer processor, the readable object from the generic data model, wherein creating includes converting the nonreadable content of the structured data object into readable content for the search engine. 19. The computer-implemented method of claim 1 , wherein providing the readable object from the structured data object occurs after a variable time interval. | 0.599045 |
1. A computer program product embodied on a non-transitory computer readable medium, comprising code executable by a computer having a processor and a graphical user interface and arranged to communicate with at least one audio file messaging software-as-a-service platform, to cause the computer to carry out the following steps: accessing the at least one audio file messaging software-as-a-service platform; communicating to the at least one audio file messaging software-as-a-service platform a set of first information, the set of first information including a message personalized for an intended recipient; selecting, via the graphical user interface, at least one category of pre-existing recording to be retrieved; retrieving, from the at least one audio messaging software-as-a-service platform, at least one pre-existing recording, said pre-existing recording associated with the at least one selected category; selecting, via the graphical user interface, a desired phrase from within a pre-existing recording; communicating the selection of the desired phrase to the at least one audio file messaging software-as-a-service platform in the form of non-audio data identifying a phrase from an audio recording, the at least one audio file messaging software-as-a-service platform comprising an audio extraction engine that (i) receives the non-audio data identifying the phrase together with an instance of the audio recording, (ii) identifies a portion of the audio recording where the phrase is likely to be found at least in part by mapping each word in the phrase to one and only vocal interval determined to exist in the audio recording, (iii) extracts the portion of the audio recording into a short snippet; and (iv) writes the short snippet into a database; and directing the at least one audio file messaging software-as-a-service platform, via the graphical user interface, to generate, output, and deliver an audio message note for the intended recipient, wherein the music message note is based on the short snippet. | 1. A computer program product embodied on a non-transitory computer readable medium, comprising code executable by a computer having a processor and a graphical user interface and arranged to communicate with at least one audio file messaging software-as-a-service platform, to cause the computer to carry out the following steps: accessing the at least one audio file messaging software-as-a-service platform; communicating to the at least one audio file messaging software-as-a-service platform a set of first information, the set of first information including a message personalized for an intended recipient; selecting, via the graphical user interface, at least one category of pre-existing recording to be retrieved; retrieving, from the at least one audio messaging software-as-a-service platform, at least one pre-existing recording, said pre-existing recording associated with the at least one selected category; selecting, via the graphical user interface, a desired phrase from within a pre-existing recording; communicating the selection of the desired phrase to the at least one audio file messaging software-as-a-service platform in the form of non-audio data identifying a phrase from an audio recording, the at least one audio file messaging software-as-a-service platform comprising an audio extraction engine that (i) receives the non-audio data identifying the phrase together with an instance of the audio recording, (ii) identifies a portion of the audio recording where the phrase is likely to be found at least in part by mapping each word in the phrase to one and only vocal interval determined to exist in the audio recording, (iii) extracts the portion of the audio recording into a short snippet; and (iv) writes the short snippet into a database; and directing the at least one audio file messaging software-as-a-service platform, via the graphical user interface, to generate, output, and deliver an audio message note for the intended recipient, wherein the music message note is based on the short snippet. 9. The computer program product of claim 1 , further comprising: receiving an advertisement from a sponsor to be displayed to the sender; displaying the advertisement on the graphical user interface; determining whether the sender has met an exposure threshold for exposure to the advertisement; and debiting a cost associated with generating, outputting, and delivering an audio message note from the sponsor. | 0.5 |
5. The computer-implemented method according to claim 2 , wherein the hierarchical coded payment system includes a plurality of classification levels defining a payment determined, the plurality of classification levels comprising: a primary level including a set of driving elements used to encode the service provider activity at a transactional level; an intermediary level including a set of groups, each group mapping one or more driving elements to a particular payment rate; and an aggregate level including a set of categories, each category being mapped to one or more of the groups according to predetermined industry classification schemes. | 5. The computer-implemented method according to claim 2 , wherein the hierarchical coded payment system includes a plurality of classification levels defining a payment determined, the plurality of classification levels comprising: a primary level including a set of driving elements used to encode the service provider activity at a transactional level; an intermediary level including a set of groups, each group mapping one or more driving elements to a particular payment rate; and an aggregate level including a set of categories, each category being mapped to one or more of the groups according to predetermined industry classification schemes. 6. The computer-implemented method according to claim 5 , wherein the hierarchical coded payment system comprises a Medicare Inpatient Hospital Prospective Payment System, the driving elements comprise Diagnosis Codes, the groups comprise Diagnosis Related Groups, and the categories comprise Major Disease Categories. | 0.848131 |
4. The method of claim 1 , further comprising: receiving a reply message in a first language from the second user to the first user; accessing a client processing device associated with the first user to determine a preferred language of the first user; and translating the reply message to the preferred language of the first user when the first language is not the same as the preferred language of the first user. | 4. The method of claim 1 , further comprising: receiving a reply message in a first language from the second user to the first user; accessing a client processing device associated with the first user to determine a preferred language of the first user; and translating the reply message to the preferred language of the first user when the first language is not the same as the preferred language of the first user. 6. The method of claim 4 , further comprising: broadcasting the reply message in the preferred language of the first user to a plurality of users in a chat session. | 0.82577 |
29. A method of managing the printing of characters by a printing device, said method comprising: providing said printing device a first font file storing first glyph data corresponding to a first set of characters, characters within said first font file being identified by multi-byte words; providing said printing device a second font file storing second glyph data corresponding to a second set of characters, characters of said second font file being identified by single-byte words, wherein: upon said printing device receiving a multi-byte word that identifies a character within said first font file, determining whether the second font file contains an equivalent character; if not, using the received multi-byte word to extract first glyph data from the first font file; and if so, using the received multi-byte word to extract second glyph data from the second font file. | 29. A method of managing the printing of characters by a printing device, said method comprising: providing said printing device a first font file storing first glyph data corresponding to a first set of characters, characters within said first font file being identified by multi-byte words; providing said printing device a second font file storing second glyph data corresponding to a second set of characters, characters of said second font file being identified by single-byte words, wherein: upon said printing device receiving a multi-byte word that identifies a character within said first font file, determining whether the second font file contains an equivalent character; if not, using the received multi-byte word to extract first glyph data from the first font file; and if so, using the received multi-byte word to extract second glyph data from the second font file. 34. The method of claim 29 , wherein the identified character within said first font file is comprised of multiple sub-characters within said first font file, glyph data for each sub-character being separately extractable for printing. | 0.699693 |
1. A method of processing data retrieved from a structured data source that is stored on a computer storage medium, comprising: receiving natural language input; analyzing the natural language input to identify semantic information contained therein; associating portions of the natural language input with a command object identifying a command from a plurality of commands, wherein the plurality of commands are related to rendering data that has been retrieved from the structured data source and designated for rendering, a frame object identifying an arrangement for rendering data, and an entity object of a schema based on the semantic information and the natural language input, wherein the entity object relates to the designated data that is to be rendered based on the command object and the frame object; rendering the designated data in a plurality of candidate tables based on a plurality of candidate interpretations of semantic information provided in the natural language input, wherein each candidate table includes columns and rows based on the schema and the associated portions of the natural language input. | 1. A method of processing data retrieved from a structured data source that is stored on a computer storage medium, comprising: receiving natural language input; analyzing the natural language input to identify semantic information contained therein; associating portions of the natural language input with a command object identifying a command from a plurality of commands, wherein the plurality of commands are related to rendering data that has been retrieved from the structured data source and designated for rendering, a frame object identifying an arrangement for rendering data, and an entity object of a schema based on the semantic information and the natural language input, wherein the entity object relates to the designated data that is to be rendered based on the command object and the frame object; rendering the designated data in a plurality of candidate tables based on a plurality of candidate interpretations of semantic information provided in the natural language input, wherein each candidate table includes columns and rows based on the schema and the associated portions of the natural language input. 17. The method of claim 1 wherein analyzing further comprises identifying ambiguous terms in the natural language input and presenting candidate alternatives for the ambiguous terms. | 0.582296 |
6. A computer-implemented method comprising: determining, by a computing device, popularity values for a plurality of content items based on a corresponding type of content item, wherein a popularity value for a first type of content item is determined differently than a popularity value for a second type of content item; receiving a search query; modifying the popularity values based on the search query; comparing a first modified popularity value of a first content item of at least two content items to a second modified popularity value of a second content item of the at least two content items; in response to determining that the first modified popularity value is equal to the second modified popularity value, ranking the first content item and the second content item based on a factor other than modified popularity value; and in response to the ranking, returning a ranked list of the at least two content items of the plurality of content items as results for the search query. | 6. A computer-implemented method comprising: determining, by a computing device, popularity values for a plurality of content items based on a corresponding type of content item, wherein a popularity value for a first type of content item is determined differently than a popularity value for a second type of content item; receiving a search query; modifying the popularity values based on the search query; comparing a first modified popularity value of a first content item of at least two content items to a second modified popularity value of a second content item of the at least two content items; in response to determining that the first modified popularity value is equal to the second modified popularity value, ranking the first content item and the second content item based on a factor other than modified popularity value; and in response to the ranking, returning a ranked list of the at least two content items of the plurality of content items as results for the search query. 9. The computer-implemented method of claim 6 , wherein the factor comprises a degree of match with the search query. | 0.676187 |
1. A decryption system for decrypting user information encrypted on a storage device associated with an identity document of a user, the system comprising: a server configured to collect user identity document data from the user and to construct a token comprising the user identity document data, wherein the server is further configured to send the token to a mobile device associated with the user for storing the token at the mobile device and wherein the mobile device is physically separate from said storage device; a key construction unit communicatively coupled to a machine reader configured to read the data from the token by radio frequency identification communication with the mobile device, wherein the token further comprises user identification information and in particular in which the reader is further configured to read the user identification information from the token and wherein the key construction unit uses the user identity document data read from the token, stored on the mobile device, to construct a key for decrypting the user information stored on said storage device; a comparator for comparing the user identification information read from the token stored on the mobile device and the user information decrypted from said storage device associated with the user identity document; and authentication means for authenticating the user depending upon the result of the comparison. | 1. A decryption system for decrypting user information encrypted on a storage device associated with an identity document of a user, the system comprising: a server configured to collect user identity document data from the user and to construct a token comprising the user identity document data, wherein the server is further configured to send the token to a mobile device associated with the user for storing the token at the mobile device and wherein the mobile device is physically separate from said storage device; a key construction unit communicatively coupled to a machine reader configured to read the data from the token by radio frequency identification communication with the mobile device, wherein the token further comprises user identification information and in particular in which the reader is further configured to read the user identification information from the token and wherein the key construction unit uses the user identity document data read from the token, stored on the mobile device, to construct a key for decrypting the user information stored on said storage device; a comparator for comparing the user identification information read from the token stored on the mobile device and the user information decrypted from said storage device associated with the user identity document; and authentication means for authenticating the user depending upon the result of the comparison. 8. A decryption system according to claim 1 in which the identity document reader is primed to decrypt the user identification information encrypted on or within the storage device in response to the reader reading the user identity document data from the token. | 0.552483 |
1. A method in a data processing system for providing a consulting assessment environment, the method comprising: a processor adapted to perform the steps of: determining an intended use for the consulting assessment environment, wherein the intended use is one of defining assessment business logic and conducting a self-assessment, wherein defining assessment business logic is performed by a consultant, wherein conducting a self-assessment is performed by the consultant or a client, and wherein self-assessment data is stored separately from the assessment business logic; responsive to determining that the intended use is defining assessment business logic, defining a data template, an assessment framework template, a suggested actions template, and a report template to create the assessment business logic for multiple types of assessments for assessing businesses, further comprising: encoding the data template, the assessment framework template, the suggested actions template, and the report template with formulas and logic rule definitions to define how self-assessment data is used to generate assessment results and recommendations; translating a plurality of hypotheses into interview questions for assessing a current state of a business; and encoding proprietary information and trade secrets into the data template, the assessment framework template, the suggested actions template, and the report template, wherein the proprietary information and the trade secrets of the consulting assessment environment are accessible to the consultant and are made inaccessible to clients using a hiding feature; responsive to determining that the intended use is conducting a self-assessment, receiving the self-assessment data about the business through a questionnaire, wherein the questionnaire is defined using the data template encoded with the interview questions and business-related domain knowledge of business practices; responsive to receiving the self-assessment data about the business, computing at least one assessment score based on the formulas and the logic rule definitions encoded in the assessment framework template; responsive to computing the at least one assessment score, determining an appropriate action based on the at least one assessment score and the suggested actions template encoded with business-related domain knowledge that defines actions to achieve desired states of businesses; and reporting results of the self-assessment data based on the at least one assessment score and the appropriate action in accordance with the report template, wherein the data template, the assessment framework template, and the suggested actions template encode business-related domain knowledge including at least one of best practices, business consultant expertise, and business goals, and wherein the proprietary information and the trade secrets of the consulting assessment environment are hidden from the client. | 1. A method in a data processing system for providing a consulting assessment environment, the method comprising: a processor adapted to perform the steps of: determining an intended use for the consulting assessment environment, wherein the intended use is one of defining assessment business logic and conducting a self-assessment, wherein defining assessment business logic is performed by a consultant, wherein conducting a self-assessment is performed by the consultant or a client, and wherein self-assessment data is stored separately from the assessment business logic; responsive to determining that the intended use is defining assessment business logic, defining a data template, an assessment framework template, a suggested actions template, and a report template to create the assessment business logic for multiple types of assessments for assessing businesses, further comprising: encoding the data template, the assessment framework template, the suggested actions template, and the report template with formulas and logic rule definitions to define how self-assessment data is used to generate assessment results and recommendations; translating a plurality of hypotheses into interview questions for assessing a current state of a business; and encoding proprietary information and trade secrets into the data template, the assessment framework template, the suggested actions template, and the report template, wherein the proprietary information and the trade secrets of the consulting assessment environment are accessible to the consultant and are made inaccessible to clients using a hiding feature; responsive to determining that the intended use is conducting a self-assessment, receiving the self-assessment data about the business through a questionnaire, wherein the questionnaire is defined using the data template encoded with the interview questions and business-related domain knowledge of business practices; responsive to receiving the self-assessment data about the business, computing at least one assessment score based on the formulas and the logic rule definitions encoded in the assessment framework template; responsive to computing the at least one assessment score, determining an appropriate action based on the at least one assessment score and the suggested actions template encoded with business-related domain knowledge that defines actions to achieve desired states of businesses; and reporting results of the self-assessment data based on the at least one assessment score and the appropriate action in accordance with the report template, wherein the data template, the assessment framework template, and the suggested actions template encode business-related domain knowledge including at least one of best practices, business consultant expertise, and business goals, and wherein the proprietary information and the trade secrets of the consulting assessment environment are hidden from the client. 6. The method of claim 1 , wherein the data template includes at least one of the interview questions, weighing factors, desired states, benefit descriptions, risk descriptions, suggested actions, cost areas, and terminology. | 0.858926 |
9. A method comprising: receiving, by a server, a request from a client device to access a first content that is not available from a first Web domain; identifying, by the server, at least one interest keyword based on a combination of keywords that yield search results including the first Web domain and a user's clickstream data responsive to the search results; classifying, by the server, the first content that is not available based on the at least one interest keyword; identifying, by the server, a second web domain based on historical relevance data and the classification of the first content that is not available, the historical relevance data including one or more previous attempts to access the first Web domain and session data representing activity performed with respect to the first Web domain; and providing the user access to second content similar to the first content from the second Web domain using the identified at least one keyword. | 9. A method comprising: receiving, by a server, a request from a client device to access a first content that is not available from a first Web domain; identifying, by the server, at least one interest keyword based on a combination of keywords that yield search results including the first Web domain and a user's clickstream data responsive to the search results; classifying, by the server, the first content that is not available based on the at least one interest keyword; identifying, by the server, a second web domain based on historical relevance data and the classification of the first content that is not available, the historical relevance data including one or more previous attempts to access the first Web domain and session data representing activity performed with respect to the first Web domain; and providing the user access to second content similar to the first content from the second Web domain using the identified at least one keyword. 15. The method of claim 9 , wherein the identifying operation includes: identifying the user's perceived interest based on a combination of the user's keyword search results and the user's clickstream data responsive to the user's keyword search results; and selecting the at least one interest keyword based on the user's perceived interest, wherein the first content that is not available is relevant to the user's perceived interest. | 0.656447 |
17. A print processing method comprising: acquiring first identification information associated with an electronic document; identifying the electronic document by using the first identification information before printing of a document image of the electronic document onto a medium is ended; generating second identification information uniquely specifying the electronic document or the medium at a time of printing the document image of the electronic document and a code image which contains the second identification information onto the medium, wherein the second identification information includes information indicating a printout time at which the document image of the electronic document is printed onto the medium; identifying the electronic document or the medium by using the second identification information after the document image of the electronic document and the code image are printed onto the medium; and associating the first identification information and the second identification information and outputting the first identification information and the second identification information, which are associated with each other to a document management unit, where the document management unit discards information of the first identification information after the document management unit determines, based on the first identification information, a correspondence between the second identification information and the electronic document. | 17. A print processing method comprising: acquiring first identification information associated with an electronic document; identifying the electronic document by using the first identification information before printing of a document image of the electronic document onto a medium is ended; generating second identification information uniquely specifying the electronic document or the medium at a time of printing the document image of the electronic document and a code image which contains the second identification information onto the medium, wherein the second identification information includes information indicating a printout time at which the document image of the electronic document is printed onto the medium; identifying the electronic document or the medium by using the second identification information after the document image of the electronic document and the code image are printed onto the medium; and associating the first identification information and the second identification information and outputting the first identification information and the second identification information, which are associated with each other to a document management unit, where the document management unit discards information of the first identification information after the document management unit determines, based on the first identification information, a correspondence between the second identification information and the electronic document. 20. The print processing method according to claim 17 , wherein the second identification information is generated in printing the document image of the electronic document. | 0.542694 |
20. A decompression unit of executable code by a microprocessor, saved in a program memory zone in compressed form, the decompression unit being connected to the microprocessor, the decompression unit comprising: means for receiving from the microprocessor instruction requests of executable code comprising an instruction address to be executed, means for determining a reading address of an addressing table as a function of the instruction address to be executed, the addressing table localizing in the program memory certain saved compressed words, means for reading to the reading address in the addressing table addressing information of compressed words corresponding to the instruction to be executed, means for determining as a function of the read addressing information a reading address of the program memory, means for reading compressed words in the program memory to the reading address, means for decompressing the read compressed words to produce an executable instruction, and means for transmitting to the microprocessor the executable instruction, wherein each word of the executable code is compressed in the form of a part of predefined fixed length and a part of variable length, whereof the length is defined by the part of fixed length, all the parts of fixed length and all the parts of variable length of the words of executable code being combined into a program memory zone respectively in a block of parts of fixed length and in a block of parts of variable length, at least certain parts of variable length being localized in the block of parts of variable length by means of an addressing table, the decompression unit further comprising: means for determining a reading address in the block of parts of fixed length as a function of the address of the instruction to be executed, means for reading the block of parts of fixed length to the determined reading address, and means for decompressing the parts of fixed and variable length read to produce an executable instruction. | 20. A decompression unit of executable code by a microprocessor, saved in a program memory zone in compressed form, the decompression unit being connected to the microprocessor, the decompression unit comprising: means for receiving from the microprocessor instruction requests of executable code comprising an instruction address to be executed, means for determining a reading address of an addressing table as a function of the instruction address to be executed, the addressing table localizing in the program memory certain saved compressed words, means for reading to the reading address in the addressing table addressing information of compressed words corresponding to the instruction to be executed, means for determining as a function of the read addressing information a reading address of the program memory, means for reading compressed words in the program memory to the reading address, means for decompressing the read compressed words to produce an executable instruction, and means for transmitting to the microprocessor the executable instruction, wherein each word of the executable code is compressed in the form of a part of predefined fixed length and a part of variable length, whereof the length is defined by the part of fixed length, all the parts of fixed length and all the parts of variable length of the words of executable code being combined into a program memory zone respectively in a block of parts of fixed length and in a block of parts of variable length, at least certain parts of variable length being localized in the block of parts of variable length by means of an addressing table, the decompression unit further comprising: means for determining a reading address in the block of parts of fixed length as a function of the address of the instruction to be executed, means for reading the block of parts of fixed length to the determined reading address, and means for decompressing the parts of fixed and variable length read to produce an executable instruction. 31. A microprocessor comprising a decompression unit as claimed in claim 20 . | 0.71684 |
17. A computer implemented natural language processing method for resolving partial matches when a natural language input query does not fully specify an entity, comprising: tokenizing, using a computer processor, the input query into a constituent set of query tokens; comparing the query tokens to contents of an index searchable by the processor, the contents representing a plurality of entities, each of which is tokenized into a constituent set of entity tokens associated with the tokenized entity; identifying, using the computer processor, a plurality of partial match query tokens from the set of query tokens, each partial match query token matching at least one entity token in the index; determining, using the computer processor, whether there is a sequential break in the input query between the partial match query tokens; for each partial match query token, identifying, using the computer processor, the entity associated with each entity token in the index that matches the partial match query token; determining, using the computer processor, whether there is an intersection between the identified entities corresponding to the partial match query tokens; and when a sequential break exists in the input query between the partial match query tokens and there is no intersection between the identified entities corresponding to the partial match query tokens determining, using the computer processor, that the input query relates to a plurality of entities, and generate and provide a response to the received natural language input query to a user based upon the identified entities. | 17. A computer implemented natural language processing method for resolving partial matches when a natural language input query does not fully specify an entity, comprising: tokenizing, using a computer processor, the input query into a constituent set of query tokens; comparing the query tokens to contents of an index searchable by the processor, the contents representing a plurality of entities, each of which is tokenized into a constituent set of entity tokens associated with the tokenized entity; identifying, using the computer processor, a plurality of partial match query tokens from the set of query tokens, each partial match query token matching at least one entity token in the index; determining, using the computer processor, whether there is a sequential break in the input query between the partial match query tokens; for each partial match query token, identifying, using the computer processor, the entity associated with each entity token in the index that matches the partial match query token; determining, using the computer processor, whether there is an intersection between the identified entities corresponding to the partial match query tokens; and when a sequential break exists in the input query between the partial match query tokens and there is no intersection between the identified entities corresponding to the partial match query tokens determining, using the computer processor, that the input query relates to a plurality of entities, and generate and provide a response to the received natural language input query to a user based upon the identified entities. 19. The computer-implemented method according to claim 17 , further comprising: generating, using the computer processor, a query response to the input query, the query response requesting information about the input query; transmitting, using the computer processor, the query response to the user; and receiving information from the user in response to the query response. | 0.560962 |
1. In a distributed computing system environment that includes a plurality of computing devices that each comprise a processor and system memory, a method of transmitting a secure message from a first party to a second party, the first party using a first cryptographic technology and the second party using a second cryptographic technology, wherein the first and second parties are within a generic security framework and wherein the generic security framework abstracts cryptographic technologies and license formats, the method comprising: determining that a message is to be sent to the second party; a processor creating at least one security credential using a modular security policy and creating an encrypted message from the message, wherein the modular security policy: establishes security rules and procedures of the generic security framework; implements a security policy of the generic security framework with one or more protocols and transports; and describes security aspects, including properties, capabilities, requirements and interaction semantics, of a plurality of modular security components which define behaviors corresponding to the first and second cryptographic technologies used by the first and second parties, and which are written in a security policy language as selectable, deployable and combinable security modules and which enables the security components to be negotiated, partitioned and modified, and rather than being hard-coded, and which include: a store component for storing, retrieving, encrypting, and managing credentials; an integrity component for signing portions of a message and for verifying integrity and signatures of received messages; and a confidentiality component for encrypting and decrypting portions of a message; and formatting a second message with a markup language wherein the markup language comprises at least one header and wherein the second message contains the encrypted message; inserting at least the one security credential into the at least one header in the markup language in the second message; and transmitting the second message to the second party and wherein the second party can use the modular security policy to decrypt and verify the message. | 1. In a distributed computing system environment that includes a plurality of computing devices that each comprise a processor and system memory, a method of transmitting a secure message from a first party to a second party, the first party using a first cryptographic technology and the second party using a second cryptographic technology, wherein the first and second parties are within a generic security framework and wherein the generic security framework abstracts cryptographic technologies and license formats, the method comprising: determining that a message is to be sent to the second party; a processor creating at least one security credential using a modular security policy and creating an encrypted message from the message, wherein the modular security policy: establishes security rules and procedures of the generic security framework; implements a security policy of the generic security framework with one or more protocols and transports; and describes security aspects, including properties, capabilities, requirements and interaction semantics, of a plurality of modular security components which define behaviors corresponding to the first and second cryptographic technologies used by the first and second parties, and which are written in a security policy language as selectable, deployable and combinable security modules and which enables the security components to be negotiated, partitioned and modified, and rather than being hard-coded, and which include: a store component for storing, retrieving, encrypting, and managing credentials; an integrity component for signing portions of a message and for verifying integrity and signatures of received messages; and a confidentiality component for encrypting and decrypting portions of a message; and formatting a second message with a markup language wherein the markup language comprises at least one header and wherein the second message contains the encrypted message; inserting at least the one security credential into the at least one header in the markup language in the second message; and transmitting the second message to the second party and wherein the second party can use the modular security policy to decrypt and verify the message. 11. The method of claim 1 , wherein: the security policy is configurable. | 0.572877 |
19. A method comprising: storing at a social networking system a social graph comprising a plurality of graph objects interconnected by graph actions, the graph actions having graph action types defined by entities external to, and independent from, the social networking system, where each of the graph actions represent a relationship between two or more graph objects and each of the graph action types define the relationship between the two or more graph objects; providing a music listening interface for display to a second user, the music listening interface including a link associated with a graph action being performed by a first user upon a graph object on an external system; receiving from the second user a selection of the link associated with the graph action being performed by the first user upon the graph object on the external system; responsive to the selection of the link, sending a request to the external system for the second user to perform the graph action being performed by the first user upon the graph object on the external system; and enabling a collaborative music listening interaction with the external system, the collaborative music listening interaction including the first user and the second user synchronously performing the graph action on the graph object; and updating the social graph based on the graph action performed, where the graph action is of a graph action type that was defined by one of the entities external to the social networking system. | 19. A method comprising: storing at a social networking system a social graph comprising a plurality of graph objects interconnected by graph actions, the graph actions having graph action types defined by entities external to, and independent from, the social networking system, where each of the graph actions represent a relationship between two or more graph objects and each of the graph action types define the relationship between the two or more graph objects; providing a music listening interface for display to a second user, the music listening interface including a link associated with a graph action being performed by a first user upon a graph object on an external system; receiving from the second user a selection of the link associated with the graph action being performed by the first user upon the graph object on the external system; responsive to the selection of the link, sending a request to the external system for the second user to perform the graph action being performed by the first user upon the graph object on the external system; and enabling a collaborative music listening interaction with the external system, the collaborative music listening interaction including the first user and the second user synchronously performing the graph action on the graph object; and updating the social graph based on the graph action performed, where the graph action is of a graph action type that was defined by one of the entities external to the social networking system. 25. The method of claim 19 , wherein providing the music listening interface further comprises: providing a chat interface that enables real-time communication between the first user and the second user; and providing within the chat interface a link associated with the first user, the link associated with the first user providing a pop up window including information about the graph action being performed by the first user on the external system as the second user generates a user input over the link associated with the first user. | 0.661813 |
12. The computer program product of claim 1 , wherein the computer program product is operable such that first indicia is displayed with particular web content for use in connection with at least one aspect of the posting in association with the particular web content on the website in response to a selection thereof and an interface is displayed for allowing the user to type the new message, and further wherein the computer program product is operable such that second indicia is displayed with the particular web content for use in connection with at least one aspect of replying to a posted message that is posted with the particular web content on the website in response to a selection thereof, and further wherein the computer program product is operable such that the user is capable of posting the new message in association with the particular web content to both: the website associated with the particular web content and a different website that is not a source of the particular web content. | 12. The computer program product of claim 1 , wherein the computer program product is operable such that first indicia is displayed with particular web content for use in connection with at least one aspect of the posting in association with the particular web content on the website in response to a selection thereof and an interface is displayed for allowing the user to type the new message, and further wherein the computer program product is operable such that second indicia is displayed with the particular web content for use in connection with at least one aspect of replying to a posted message that is posted with the particular web content on the website in response to a selection thereof, and further wherein the computer program product is operable such that the user is capable of posting the new message in association with the particular web content to both: the website associated with the particular web content and a different website that is not a source of the particular web content. 20. The computer program product of claim 12 , wherein the computer program product is operable such that the first indicia and the second indicia include buttons, the at least one aspect includes at least one of receiving the new message or submitting the new message, and the interface includes at least a portion of a web page, and the new message is displayed simultaneously with the particular web content. | 0.845584 |
6. A tangible machine readable memory having instructions stored thereon that, when executed, cause a machine to at least: extract object data associated with user interface elements from a file associated with a user interface; store an object definition for respective ones of the user interface elements in the machine readable memory; reference an automation rule with the object definition to obtain a testing sequence for the user interface elements, wherein the testing sequence obtained from the automation rule depends on which types of user interface elements are present in the user interface, wherein extracting the object data from the file associated with the user interface comprises referencing a set of extraction rules configured to identify the types of the user interface elements; reference a test definition with the object definition to obtain one or more attributes of the user interface elements to be tested, wherein the object data associated with the user interface elements includes the attributes of the corresponding user interface elements; and generate a test script for the user interface using the one or more attributes of the user interface elements and the testing sequence. | 6. A tangible machine readable memory having instructions stored thereon that, when executed, cause a machine to at least: extract object data associated with user interface elements from a file associated with a user interface; store an object definition for respective ones of the user interface elements in the machine readable memory; reference an automation rule with the object definition to obtain a testing sequence for the user interface elements, wherein the testing sequence obtained from the automation rule depends on which types of user interface elements are present in the user interface, wherein extracting the object data from the file associated with the user interface comprises referencing a set of extraction rules configured to identify the types of the user interface elements; reference a test definition with the object definition to obtain one or more attributes of the user interface elements to be tested, wherein the object data associated with the user interface elements includes the attributes of the corresponding user interface elements; and generate a test script for the user interface using the one or more attributes of the user interface elements and the testing sequence. 10. The memory as defined in claim 6 , wherein the testing sequence defined by the automation rule includes the user interface elements of a first type being tested before the user interface elements of a second type when the user interface includes a third type of user interface element, and wherein the testing sequence defined by the automation rule includes the user interface elements of the first type being tested after the user interface elements of the second type when the user interface does not include the third type of user interface element. | 0.5 |
2. An event-collection-and-event-processing system comprising: one or more computer systems, each having one or more processors, one or more memories, and one or more mass-storage devices; an event-collection subsystem, operating within one or more of the one or more computer systems, which: receives encoded data from one or more browser applications, executing on one or more remote user computers, the encoded data event generated by instrumentation within one or more instrumented web pages processed and rendered for display by the one or more browser applications; processes the received encoded data to produce a set of initially processed events, each of the set of initially processed events having an initial number of data entities; and stores the set of initially processed events in one or more of the one or more memories; an abstraction layer, operating within one or more of the one or more computer systems, that: receives the set of initially processed events from the event-collection subsystem; further processes the set of initially processed events to generate a corresponding set of processed events, each processed event in the set of processed events having a data entity that represents a topic assignment output assigned to the processed event, the further processing including: accessing a set of current distributions, the set of current distributions including: a regular-word distribution associated with a global topic; a seed-word distribution associated with the global topic; for each of a set of topics, a regular-word distribution associated with the topic; and for each of the set of topics, a seed-word distribution associated with the topic, the seed-word distribution associated with the topic including, for each seed word a plurality of seed words, a quantity indicating a number of observations where the seed word was included in an event and was associated with the topic; performing a set of iteration operations that include: for each word of a plurality of words in the set of initially processed events: determining, based on the set of current distributions, whether the word corresponds to a regular word or a seed word; determining, based on the set of current distributions, whether the word corresponds to a global topic or a discovered topic; and updating the set of current distributions based on, for each word of the plurality of words, the determination as to whether the word corresponds to a regular word or a seed word and the determination as to whether the word corresponds to a global topic or a discovered topic; and based on one or more iterations of the set of iteration operations, identifying, for each initially processed event in the set of initially processed events, the topic-assignment output to be represented in a processed event in the set of processed events corresponding to the initially processed event, and an event-consuming application, operating within one or more of the one or more computer systems, that receives the topic-assignment outputs of the set of initially processed events from the abstraction layer and uses the topic-assignment outputs processed events to produce one or more results. | 2. An event-collection-and-event-processing system comprising: one or more computer systems, each having one or more processors, one or more memories, and one or more mass-storage devices; an event-collection subsystem, operating within one or more of the one or more computer systems, which: receives encoded data from one or more browser applications, executing on one or more remote user computers, the encoded data event generated by instrumentation within one or more instrumented web pages processed and rendered for display by the one or more browser applications; processes the received encoded data to produce a set of initially processed events, each of the set of initially processed events having an initial number of data entities; and stores the set of initially processed events in one or more of the one or more memories; an abstraction layer, operating within one or more of the one or more computer systems, that: receives the set of initially processed events from the event-collection subsystem; further processes the set of initially processed events to generate a corresponding set of processed events, each processed event in the set of processed events having a data entity that represents a topic assignment output assigned to the processed event, the further processing including: accessing a set of current distributions, the set of current distributions including: a regular-word distribution associated with a global topic; a seed-word distribution associated with the global topic; for each of a set of topics, a regular-word distribution associated with the topic; and for each of the set of topics, a seed-word distribution associated with the topic, the seed-word distribution associated with the topic including, for each seed word a plurality of seed words, a quantity indicating a number of observations where the seed word was included in an event and was associated with the topic; performing a set of iteration operations that include: for each word of a plurality of words in the set of initially processed events: determining, based on the set of current distributions, whether the word corresponds to a regular word or a seed word; determining, based on the set of current distributions, whether the word corresponds to a global topic or a discovered topic; and updating the set of current distributions based on, for each word of the plurality of words, the determination as to whether the word corresponds to a regular word or a seed word and the determination as to whether the word corresponds to a global topic or a discovered topic; and based on one or more iterations of the set of iteration operations, identifying, for each initially processed event in the set of initially processed events, the topic-assignment output to be represented in a processed event in the set of processed events corresponding to the initially processed event, and an event-consuming application, operating within one or more of the one or more computer systems, that receives the topic-assignment outputs of the set of initially processed events from the abstraction layer and uses the topic-assignment outputs processed events to produce one or more results. 10. The event-collection-and-event-processing system of claim 2 , wherein the further processing further includes: for each iteration of at least one iteration: determining, after a most recent updating the set of current distributions, that another iteration is to be performed; and redefining, in response to determining that another iteration is to be performed, the set of current distributions to be the updated set of distributions and repeating the set of iteration operations; and determining, after a most recent updating the set of current distributions, that another iteration is not to be performed; and wherein the topic-assignment output is identified in response to determining that another iteration is not to be performed, the topic-assignment output being based on the determination as to whether the word corresponds to a regular word or a seed word and the determination as to whether the word corresponds to a global topic or a discovered topic. | 0.529194 |
1. A method for providing context-based task reminders, comprising: receiving a task item associated with a first reminder; receiving one or more context information data sources, wherein receiving one or more context information data sources includes receiving one or more context information data sources from one of a calendar data source, a contacts data source, a tasks data source, a presence data source, a location data source, an email data source, an Internet content data source, a social networking content data source, one or more electronic documents, a person proximity data source, a motion detection data source, a communications data source and a light sensing data source; parsing the task item for one or more task item information components; parsing the one or more context information data sources for determining information relevant to the received task item, including parsing content contained in the one or more context information data sources for one or more data sources information components; comparing the one or more data sources information components with the one or more task item information components to determine if the one or more data sources information components matches the one or more task item information components; if the one or more data sources information components matches the one or more task item information components, then determining the information relevant to the received task item including determining the data sources containing the one or more data sources information components matching the one or more task item information components that are relevant to the received task item; determining a revised reminder for the task item based on the information relevant to the received task item; and displaying the revised reminder for the task item based on the information relevant to the received task item. | 1. A method for providing context-based task reminders, comprising: receiving a task item associated with a first reminder; receiving one or more context information data sources, wherein receiving one or more context information data sources includes receiving one or more context information data sources from one of a calendar data source, a contacts data source, a tasks data source, a presence data source, a location data source, an email data source, an Internet content data source, a social networking content data source, one or more electronic documents, a person proximity data source, a motion detection data source, a communications data source and a light sensing data source; parsing the task item for one or more task item information components; parsing the one or more context information data sources for determining information relevant to the received task item, including parsing content contained in the one or more context information data sources for one or more data sources information components; comparing the one or more data sources information components with the one or more task item information components to determine if the one or more data sources information components matches the one or more task item information components; if the one or more data sources information components matches the one or more task item information components, then determining the information relevant to the received task item including determining the data sources containing the one or more data sources information components matching the one or more task item information components that are relevant to the received task item; determining a revised reminder for the task item based on the information relevant to the received task item; and displaying the revised reminder for the task item based on the information relevant to the received task item. 3. The method of claim 1 , wherein displaying the revised reminder for the task item based on the information relevant to the received task item includes filtering and reordering a display of the task item relative to other displayed task items based on the information relevant to the received task item. | 0.542455 |
29. One or more non-transitory computer readable media storing instructions that are executable by a processing device, and upon such execution cause the processing device to perform operations comprising: receiving data representing a glyph in a font to present the glyph on a display; in response to operations being executed to present the glyph on the display, identifying one or more values shared by glyphs of the font for adjusting the appearance of the glyph, from a data table stored with the glyph in the font, either one or multiple instructions being executed based upon a comparison of adjusted versions of the glyph to identify the one or more shared values; and adjusting a representation of the glyph using the identified one or more shared values for presentation on the display. | 29. One or more non-transitory computer readable media storing instructions that are executable by a processing device, and upon such execution cause the processing device to perform operations comprising: receiving data representing a glyph in a font to present the glyph on a display; in response to operations being executed to present the glyph on the display, identifying one or more values shared by glyphs of the font for adjusting the appearance of the glyph, from a data table stored with the glyph in the font, either one or multiple instructions being executed based upon a comparison of adjusted versions of the glyph to identify the one or more shared values; and adjusting a representation of the glyph using the identified one or more shared values for presentation on the display. 42. The non-transitory computer readable media of claim 29 , wherein adjusting a representation of the glyph using the identified one or more shared values includes adjusting the position of one or more data points located on an outline of the glyph. | 0.577621 |
1. A computer-implemented method comprising: for a first document that is included in first search results responsive to a first user-submitted query, selecting a plurality of previously submitted queries for which the first document was a responsive search result, wherein the selected previously submitted queries are selected using a document-to-query-to-document model that associates the first document to the plurality of previously submitted queries and that associates each of the plurality of previously submitted queries to one or more of second documents for which each of the one or more second documents was a responsive search result; for each of the selected previously submitted queries, determining whether there is at least a threshold level of diversity between the first search results and second documents identified as being relevant to the selected previously submitted query, wherein second documents are determined to be relevant to the previously submitted query based on data that is indicative of user behavior relative to the second documents as search results for the previously submitted query; based on the determination of whether there is at least a threshold level of diversity between the first search results and the second documents, identifying one or more queries from the selected previously submitted queries to provide as first suggested queries; and providing the one or more identified queries as the first suggested queries with the first search results for the first user-submitted query. | 1. A computer-implemented method comprising: for a first document that is included in first search results responsive to a first user-submitted query, selecting a plurality of previously submitted queries for which the first document was a responsive search result, wherein the selected previously submitted queries are selected using a document-to-query-to-document model that associates the first document to the plurality of previously submitted queries and that associates each of the plurality of previously submitted queries to one or more of second documents for which each of the one or more second documents was a responsive search result; for each of the selected previously submitted queries, determining whether there is at least a threshold level of diversity between the first search results and second documents identified as being relevant to the selected previously submitted query, wherein second documents are determined to be relevant to the previously submitted query based on data that is indicative of user behavior relative to the second documents as search results for the previously submitted query; based on the determination of whether there is at least a threshold level of diversity between the first search results and the second documents, identifying one or more queries from the selected previously submitted queries to provide as first suggested queries; and providing the one or more identified queries as the first suggested queries with the first search results for the first user-submitted query. 16. The computer program product of claim 1 , where associations between the first document, the plurality of previously submitted queries, and the second documents of the document-to-query-to-document model are derived from data that is indicative of user behavior relative to the first document and the second documents as search results for the plurality of previously submitted queries. | 0.57964 |
1. An Internet-based system for managing and delivering consumer product brand information to consumers at points of presence along the World Wide Web (WWW), said Internet-based system comprising: a plurality of Web-based information servers, operably connected to the infrastructure of the Internet, serving a plurality of Web-sites on the WWW, wherein each said Web-site includes a plurality of HTML-encoded pages; a plurality of Internet-based consumer product information (CPI) servers, operably connected to the infrastructure of the Internet, and serving a plurality of consumer product information (CPI) resources located on the WWW, and related to a particular consumer product or group of consumer products registered with said Internet-based system and being marketed along the WWW; a first Internet-based subsystem, operably connected to the infrastructure of the Internet, and configured to allow manufacturer team members associated with said particular consumer product or group of consumer products, and/or authorized parties, to implement a plurality of consumer product information (CPI) requesting and graphical user interface (GUI) displaying subsystems (CPI-requesting and GUI-displaying subsystems) for said plurality of consumer products being marketed along the WWW, so that each said CPI-requesting and GUI-displaying subsystem is accessed by consumers at points of presence along the WWW, using a client subsystem supporting a Web browser; an object-oriented server operably connected to the infrastructure of the Internet; wherein each said CPI-requesting and GUI-displaying subsystem is implemented by (i) a consumer product information request (CPIR) enabling servlet stored on and executed within said object-oriented server independent of the operation of said CPI resource servers, and (ii) an HTML servlet tag embodied with a unique URL referencing said CPIR-enabling servlet, and embedded within at least one of said plurality of HTML-encoded pages, at a point of presence on the WWW; wherein said object-oriented server generates each said CPI-requesting and GUI-displaying subsystem, and serves a CPI graphical user interface (GUI) at the point of presence, for displaying a set of said plurality of CPI resources for selection by the consumer; a UPN/TM/URL database, operably connected to said object-oriented server, for storing and managing a UPN/TM/URL link structure for each consumer product registered with said Internet-based system, wherein each said UPN/TM/URL link structure includes a Universal Product Number (UPN) assigned to the consumer product registered within said Internet-based system; a Trademark (TM) assigned to the consumer product; and a set of URLs for said plurality of CPI resources being served from said plurality of Internet-based CPI servers; wherein said CPIR-enabling servlet installed on said object-oriented server, for each said consumer product, includes code stored on a medium operable to execute said code specifying: (i) a connection to said UPN/TM/URL database; (ii) a CPI query to be executed on said UPN/TM/URL database, dependent on the UPN assigned to said consumer product, and returning a set of URLs stored in said UPN/TM/URL database and associated with said UPN; and (iii) a CPI GUI, object-oriented controlled, displaying the results of the UPN-dependent CPI query at the point of presence where said corresponding HTML servlet tag is embedded within at least one said HTML-encoded page along the WWW; wherein said HTML servlet tag embodies the unique URL referencing said corresponding CPIR-enabling servlet; a second Internet-based subsystem configured to allow manufacturer team members associated with a particular consumer product or group of consumer products, and/or authorized parties, to program said set of CPI resources for display in the CPI GUI of each said CPI-requesting and GUI-displaying subsystem; and wherein, upon the Web-browser of the consumer encountering said HTML servlet tag installed in said HTML-encoded page, (a) the CPIR-enabling servlet corresponding to said HTML servlet tag is automatically executed, (b) the CPI GUI of said corresponding CPI-requesting and GUI-displaying subsystem is automatically generated by said object-oriented server, (c) said object-oriented controlled CPI GUI is served to the Web browser at the point of presence where said HTML servlet tag is embedded, and (d) then said object-oriented controlled CPI GUI displays information content that is (i) associated with one or more CPI resources having URLs returned by said UPN-dependent CPI query, and (ii) served from one or more of said plurality of Internet-based CPI servers, display and review by the consumer at the point of presence along the WWW where said HTML servlet tag has been encountered by the Web browser. | 1. An Internet-based system for managing and delivering consumer product brand information to consumers at points of presence along the World Wide Web (WWW), said Internet-based system comprising: a plurality of Web-based information servers, operably connected to the infrastructure of the Internet, serving a plurality of Web-sites on the WWW, wherein each said Web-site includes a plurality of HTML-encoded pages; a plurality of Internet-based consumer product information (CPI) servers, operably connected to the infrastructure of the Internet, and serving a plurality of consumer product information (CPI) resources located on the WWW, and related to a particular consumer product or group of consumer products registered with said Internet-based system and being marketed along the WWW; a first Internet-based subsystem, operably connected to the infrastructure of the Internet, and configured to allow manufacturer team members associated with said particular consumer product or group of consumer products, and/or authorized parties, to implement a plurality of consumer product information (CPI) requesting and graphical user interface (GUI) displaying subsystems (CPI-requesting and GUI-displaying subsystems) for said plurality of consumer products being marketed along the WWW, so that each said CPI-requesting and GUI-displaying subsystem is accessed by consumers at points of presence along the WWW, using a client subsystem supporting a Web browser; an object-oriented server operably connected to the infrastructure of the Internet; wherein each said CPI-requesting and GUI-displaying subsystem is implemented by (i) a consumer product information request (CPIR) enabling servlet stored on and executed within said object-oriented server independent of the operation of said CPI resource servers, and (ii) an HTML servlet tag embodied with a unique URL referencing said CPIR-enabling servlet, and embedded within at least one of said plurality of HTML-encoded pages, at a point of presence on the WWW; wherein said object-oriented server generates each said CPI-requesting and GUI-displaying subsystem, and serves a CPI graphical user interface (GUI) at the point of presence, for displaying a set of said plurality of CPI resources for selection by the consumer; a UPN/TM/URL database, operably connected to said object-oriented server, for storing and managing a UPN/TM/URL link structure for each consumer product registered with said Internet-based system, wherein each said UPN/TM/URL link structure includes a Universal Product Number (UPN) assigned to the consumer product registered within said Internet-based system; a Trademark (TM) assigned to the consumer product; and a set of URLs for said plurality of CPI resources being served from said plurality of Internet-based CPI servers; wherein said CPIR-enabling servlet installed on said object-oriented server, for each said consumer product, includes code stored on a medium operable to execute said code specifying: (i) a connection to said UPN/TM/URL database; (ii) a CPI query to be executed on said UPN/TM/URL database, dependent on the UPN assigned to said consumer product, and returning a set of URLs stored in said UPN/TM/URL database and associated with said UPN; and (iii) a CPI GUI, object-oriented controlled, displaying the results of the UPN-dependent CPI query at the point of presence where said corresponding HTML servlet tag is embedded within at least one said HTML-encoded page along the WWW; wherein said HTML servlet tag embodies the unique URL referencing said corresponding CPIR-enabling servlet; a second Internet-based subsystem configured to allow manufacturer team members associated with a particular consumer product or group of consumer products, and/or authorized parties, to program said set of CPI resources for display in the CPI GUI of each said CPI-requesting and GUI-displaying subsystem; and wherein, upon the Web-browser of the consumer encountering said HTML servlet tag installed in said HTML-encoded page, (a) the CPIR-enabling servlet corresponding to said HTML servlet tag is automatically executed, (b) the CPI GUI of said corresponding CPI-requesting and GUI-displaying subsystem is automatically generated by said object-oriented server, (c) said object-oriented controlled CPI GUI is served to the Web browser at the point of presence where said HTML servlet tag is embedded, and (d) then said object-oriented controlled CPI GUI displays information content that is (i) associated with one or more CPI resources having URLs returned by said UPN-dependent CPI query, and (ii) served from one or more of said plurality of Internet-based CPI servers, display and review by the consumer at the point of presence along the WWW where said HTML servlet tag has been encountered by the Web browser. 2. The Internet-based system of claim 1 , wherein each said UPN comprises a Universal Product Code (UPC). | 0.57884 |
1. A computer-implemented method for generating genre models used to identify genres of a document, comprising: on a computer system having one or more processors executing one or more programs stored on memory of the computer system: for each document image in a set of document images that are associated with one or more genres, segmenting the document image into a plurality of tiles, wherein the tiles in the plurality of tiles are sized so that document page features are identifiable; and computing features of the document image and the plurality of tiles; and training at least one genre classifier to classify document images as being associated with one or more genres based on the features of the document images in the set of document images, the features of the plurality of tiles of the set of documents images, and the one or more genres associated with each document image in the set of documents images, wherein training the at least one genre classifier to classify document images as being associated with a respective genre in the one or more genres includes: training a first genre classifier corresponding to the respective genre based on the features of a first subset of the set of document images and the features of the plurality of tiles associated with the first subset of the set of document images; tuning parameters of the first genre classifier using a second subset of the set of document images, wherein the first subset and the second subset of the set of document images are mutually-exclusive sets of document images; training a second genre classifier corresponding to the respective genre based on the features of a second subset of the set of document images and the features of the plurality of tiles associated with the second subset of the set of document images; and tuning parameters of the second genre classifier using the first subset of the set of document images. | 1. A computer-implemented method for generating genre models used to identify genres of a document, comprising: on a computer system having one or more processors executing one or more programs stored on memory of the computer system: for each document image in a set of document images that are associated with one or more genres, segmenting the document image into a plurality of tiles, wherein the tiles in the plurality of tiles are sized so that document page features are identifiable; and computing features of the document image and the plurality of tiles; and training at least one genre classifier to classify document images as being associated with one or more genres based on the features of the document images in the set of document images, the features of the plurality of tiles of the set of documents images, and the one or more genres associated with each document image in the set of documents images, wherein training the at least one genre classifier to classify document images as being associated with a respective genre in the one or more genres includes: training a first genre classifier corresponding to the respective genre based on the features of a first subset of the set of document images and the features of the plurality of tiles associated with the first subset of the set of document images; tuning parameters of the first genre classifier using a second subset of the set of document images, wherein the first subset and the second subset of the set of document images are mutually-exclusive sets of document images; training a second genre classifier corresponding to the respective genre based on the features of a second subset of the set of document images and the features of the plurality of tiles associated with the second subset of the set of document images; and tuning parameters of the second genre classifier using the first subset of the set of document images. 10. The computer-implemented method of claim 1 , wherein a respective genre classifier is a trained support vector machine (SVM). | 0.545583 |
12. The computer storage medium of claim 11 , wherein the operation for causing the image to be rendered includes specifying a content that is to be displayed in response to detecting the selection input. | 12. The computer storage medium of claim 11 , wherein the operation for causing the image to be rendered includes specifying a content that is to be displayed in response to detecting the selection input. 30. The computer storage medium of claim 12 , wherein the one or more processors are configured to specify the content to display, in response to detecting the selection input, by identifying additional images that contain the selected one or more objects. | 0.773181 |
16. The computer implemented method of claim 11 wherein the database further includes business hours information identifying business hours for specific ones of the retail locations, the method further comprising identifying the subset of the retail locations with reference to the business hours information. | 16. The computer implemented method of claim 11 wherein the database further includes business hours information identifying business hours for specific ones of the retail locations, the method further comprising identifying the subset of the retail locations with reference to the business hours information. 17. The computer implemented method of claim 16 wherein identifying the subset of the retail locations with reference to the business hours information comprises inferring first business hours for a third one of the subset of the retail locations from the business hours associated with one or more of the specific retail locations having specified business hours, wherein the third retail location and the one or more of the specific retail locations having specified business hours have associated retail categories that are related. | 0.89525 |
411. A computer program product, to be used on a computer, for improving a precision ratio when searching a resume database, comprising: a computer readable medium storing: program code for receiving a resume; program code for parsing the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; program code for storing the resume in the resume database; program code for associating at least one of said at least one skill or experience-related phrase located in the resume with at least one implied skill or experience-related phrase, wherein a term of experience for each said at least one implied skill or experience-related phrase is the term of experience computed for said at least one of said at least one skill or experience-related phrase, and wherein said at least one skill or experience-related phrase and said at least one implied skill or experience-related phrase are searchable phrases in the resume; program code for creating a parsed resume based on the resume, the parsed resume including each searchable phrase in the resume, the term of experience for each searchable phrase, and a relationship between the term of experience and each searchable phrase; program code for storing the parsed resume in the resume database; program code for sending a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and program code for receiving a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. | 411. A computer program product, to be used on a computer, for improving a precision ratio when searching a resume database, comprising: a computer readable medium storing: program code for receiving a resume; program code for parsing the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; program code for storing the resume in the resume database; program code for associating at least one of said at least one skill or experience-related phrase located in the resume with at least one implied skill or experience-related phrase, wherein a term of experience for each said at least one implied skill or experience-related phrase is the term of experience computed for said at least one of said at least one skill or experience-related phrase, and wherein said at least one skill or experience-related phrase and said at least one implied skill or experience-related phrase are searchable phrases in the resume; program code for creating a parsed resume based on the resume, the parsed resume including each searchable phrase in the resume, the term of experience for each searchable phrase, and a relationship between the term of experience and each searchable phrase; program code for storing the parsed resume in the resume database; program code for sending a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and program code for receiving a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. 447. The computer program product of claim 411 , wherein the job description further includes a required level of education or a required field of specialization, the computer readable medium further storing: program code for storing the job description in the resume database; and program code for sending a portion of the result set, wherein the result set includes at least one matching resume from the resume database, each said at least one matching resume satisfying the job description. | 0.514343 |
19. An apparatus for adapting a model for a speech recognition system using an adaptation process, the apparatus comprising: a processor that is operable to determine an error rate, corresponding to either recognition of instances of a word or recognition of instances of various words among a set of words; and a controller that is operable to adjust an adaptation process for the model for the word or various models for the various words, based on the error rate. | 19. An apparatus for adapting a model for a speech recognition system using an adaptation process, the apparatus comprising: a processor that is operable to determine an error rate, corresponding to either recognition of instances of a word or recognition of instances of various words among a set of words; and a controller that is operable to adjust an adaptation process for the model for the word or various models for the various words, based on the error rate. 23. The apparatus of claim 19 , wherein the controller adjusts the adaptation process by making a comparison of the error rate to an error rate threshold; and adapting the model or the various models or withholding adapting the model or the various models based on the comparison. | 0.5 |
1. A document rating calculation system comprising: a first information processing apparatus including, an item information database that stores a mutual dependent relationship based on topics represented by each item, among the items into which a document is divided and a rating for each of the items which is calculated based on a predetermined criterion; a document retrieval unit that electronically retrieves a document fulfilling a given retrieval condition, and, for each condition item of the retrieval condition, specifies an item fulfilling the condition item in the retrieved document; a related item selection unit that, for each condition item of the retrieval condition, i) specifies an item related to the item fulfilling the condition item for each item fulfilling the condition item and specified by the document retrieval unit in the document retrieved by the document retrieval unit, based on the mutual dependent relationship among the items which is stored in the item information database, and ii) selects a set of related items including the item fulfilling the condition item and the item specified and related to the item fulfilling the condition item; a fulfilling-item set specifying unit that performs a logical operation of the retrieval condition between sets of related items selected by the related item selection unit to specify a set of items fulfilling the retrieval condition; and a score calculation unit that calculates a document rating of the document fulfilling the retrieval condition based on the ratings of items stored in the item information database and included in the set of fulfilling items specified by the fulfilling-item set specifying unit, wherein the item information database stores a value calculated based on a predetermined degree of account for a number of elements included in an item of the document and a type of the elements, as the rating of the item, wherein the types of elements included in the items of the document include any combination of a sentence, a figure, a table, an equation, an emphasis expression, a citation and a key word, and the item information database stores a value calculated based on a sum of product of a number of elements for each of the types of the elements included in the items of the document, a predetermined index for each of the types of the elements, and a predetermined weight set for the index, as a rating for each of the items. | 1. A document rating calculation system comprising: a first information processing apparatus including, an item information database that stores a mutual dependent relationship based on topics represented by each item, among the items into which a document is divided and a rating for each of the items which is calculated based on a predetermined criterion; a document retrieval unit that electronically retrieves a document fulfilling a given retrieval condition, and, for each condition item of the retrieval condition, specifies an item fulfilling the condition item in the retrieved document; a related item selection unit that, for each condition item of the retrieval condition, i) specifies an item related to the item fulfilling the condition item for each item fulfilling the condition item and specified by the document retrieval unit in the document retrieved by the document retrieval unit, based on the mutual dependent relationship among the items which is stored in the item information database, and ii) selects a set of related items including the item fulfilling the condition item and the item specified and related to the item fulfilling the condition item; a fulfilling-item set specifying unit that performs a logical operation of the retrieval condition between sets of related items selected by the related item selection unit to specify a set of items fulfilling the retrieval condition; and a score calculation unit that calculates a document rating of the document fulfilling the retrieval condition based on the ratings of items stored in the item information database and included in the set of fulfilling items specified by the fulfilling-item set specifying unit, wherein the item information database stores a value calculated based on a predetermined degree of account for a number of elements included in an item of the document and a type of the elements, as the rating of the item, wherein the types of elements included in the items of the document include any combination of a sentence, a figure, a table, an equation, an emphasis expression, a citation and a key word, and the item information database stores a value calculated based on a sum of product of a number of elements for each of the types of the elements included in the items of the document, a predetermined index for each of the types of the elements, and a predetermined weight set for the index, as a rating for each of the items. 7. The document rating calculation system according to claim 1 , wherein the score calculation unit sets an average value obtained by dividing a sum of ratings of items included in a set of related items fulfilling the retrieval condition and stored in the item information database by a number of items in the set of related items fulfilling the retrieval condition to a document rating of a document fulfilling the retrieval condition. | 0.575597 |
14. A system, comprising: a computer processor; and a memory containing a program, which when executed by the computer processor, performs an operation to detect a keyword in speech, the operation comprising: generating, from a sequence of spectral feature vectors generated from the speech, a plurality of blocked feature vector sequences, wherein each of the plurality of blocked feature vector sequences comprises a respective subset of the plurality of feature vectors, wherein each of the plurality of blocked feature vector sequences overlap adjacent blocked feature vector sequences by a predefined count of feature vector sequences; and analyzing, by a neural network, each of the plurality of blocked feature vector sequences to detect the presence of the keyword in the speech. | 14. A system, comprising: a computer processor; and a memory containing a program, which when executed by the computer processor, performs an operation to detect a keyword in speech, the operation comprising: generating, from a sequence of spectral feature vectors generated from the speech, a plurality of blocked feature vector sequences, wherein each of the plurality of blocked feature vector sequences comprises a respective subset of the plurality of feature vectors, wherein each of the plurality of blocked feature vector sequences overlap adjacent blocked feature vector sequences by a predefined count of feature vector sequences; and analyzing, by a neural network, each of the plurality of blocked feature vector sequences to detect the presence of the keyword in the speech. 17. The system of claim 14 , wherein the neural network comprises a plurality of blocks, wherein each block of the neural network is configured to process a respective block of the plurality of blocked feature vector sequences. | 0.653169 |
25. A non-transitory computer-readable medium storing instruction code that when executed by a general purpose computer system causes the general purpose computer system to perform a method comprising: for each table of a plurality of database tables and for each column of a plurality of columns within the each table, creating a profile for the each column by accessing and analyzing a subset of values stored in the column; establishing a join graph of nodes, wherein each node represents one of the plurality of database tables; for each pair of a plurality of pairs of a first table and a second table from the plurality of database tables, wherein the first table is different than the second table and wherein no defined relationship exists between the first table and the second table: for each pair of a plurality of pairs of a first column from the first table and a second column from the second table, calculating a joinability score representative of a predicted level of success in performing a join from the first table on the first column to the second table on the second column, wherein the score is determined based upon the profile for the first column and the profile for the second column, and for one pair of the plurality of pairs of the first column from the first table and the second column from the second table, adding, based on the joinability score, a directed edge to the join graph from a node representing the first table to a node representing the second table; receiving a selection of a subset of the plurality of database tables; creating a join tree comprising a subset of edges in the join graph that spans a subset of nodes in the join graph corresponding to the selected subset of the plurality of database tables; extracting a set of joins represented by the subset of edges; and providing the extracted set of joins as a result, wherein creating a profile for the each column comprises: processing the each column to create a set of m observables, with m being a positive integer constant greater than one, wherein each observable is a function of a set of elements in the each column, independent of replications, and including the set of m observables in the profile for the each column, and wherein calculating the joinability score comprises: combining the set of m observables included in the profile for the first column and the set of m observables included in the profile for the second column to create a combined set of m observables, wherein each observable in the combined set of m observables is a function of a set of elements in a union between the first column and the second column, independent of replications, computing an estimated cardinality of a union between the first column and the second column based on the combined set of m observables without creating a union between the first column and the second column, computing an estimated cardinality of an intersection between the first column and the second column by subtracting the estimated cardinality of the union from the sum of an estimated cardinality of the first column and an estimated cardinality of the second column, and dividing the estimated cardinality of the intersection by the estimated cardinality of the first column. | 25. A non-transitory computer-readable medium storing instruction code that when executed by a general purpose computer system causes the general purpose computer system to perform a method comprising: for each table of a plurality of database tables and for each column of a plurality of columns within the each table, creating a profile for the each column by accessing and analyzing a subset of values stored in the column; establishing a join graph of nodes, wherein each node represents one of the plurality of database tables; for each pair of a plurality of pairs of a first table and a second table from the plurality of database tables, wherein the first table is different than the second table and wherein no defined relationship exists between the first table and the second table: for each pair of a plurality of pairs of a first column from the first table and a second column from the second table, calculating a joinability score representative of a predicted level of success in performing a join from the first table on the first column to the second table on the second column, wherein the score is determined based upon the profile for the first column and the profile for the second column, and for one pair of the plurality of pairs of the first column from the first table and the second column from the second table, adding, based on the joinability score, a directed edge to the join graph from a node representing the first table to a node representing the second table; receiving a selection of a subset of the plurality of database tables; creating a join tree comprising a subset of edges in the join graph that spans a subset of nodes in the join graph corresponding to the selected subset of the plurality of database tables; extracting a set of joins represented by the subset of edges; and providing the extracted set of joins as a result, wherein creating a profile for the each column comprises: processing the each column to create a set of m observables, with m being a positive integer constant greater than one, wherein each observable is a function of a set of elements in the each column, independent of replications, and including the set of m observables in the profile for the each column, and wherein calculating the joinability score comprises: combining the set of m observables included in the profile for the first column and the set of m observables included in the profile for the second column to create a combined set of m observables, wherein each observable in the combined set of m observables is a function of a set of elements in a union between the first column and the second column, independent of replications, computing an estimated cardinality of a union between the first column and the second column based on the combined set of m observables without creating a union between the first column and the second column, computing an estimated cardinality of an intersection between the first column and the second column by subtracting the estimated cardinality of the union from the sum of an estimated cardinality of the first column and an estimated cardinality of the second column, and dividing the estimated cardinality of the intersection by the estimated cardinality of the first column. 35. The computer-readable medium of claim 25 , wherein the one pair of the plurality of pairs has a maximum joinability score of the plurality of pairs. | 0.800752 |
13. The communication device of claim 10 , wherein the processor is further configured to read computer executable instructions that when executed display a second updated predicted string at or near the key location. | 13. The communication device of claim 10 , wherein the processor is further configured to read computer executable instructions that when executed display a second updated predicted string at or near the key location. 14. The communication device of claim 13 , wherein the updated predicted string and the second updated predicted string are presented in a selection list. | 0.868337 |
8. The method of claim 1 , wherein the variables for which data and associated probabilities are assigned comprise at least one variable representing a presently measurable or observable quantity and the unknown variables solved for include at least one representing paleoenvironmental conditions. | 8. The method of claim 1 , wherein the variables for which data and associated probabilities are assigned comprise at least one variable representing a presently measurable or observable quantity and the unknown variables solved for include at least one representing paleoenvironmental conditions. 9. The method of claim 8 , further comprising assigning, to each variable for which data and associated probabilities are assigned, a single date value or range of data values with probability of unity. | 0.913055 |
31. A computer system for compiling a pattern into a non-deterministic finite automata (NFA) graph, the system comprising: a memory; and a processor, the processor coupled to the memory and configured to examine the pattern for a plurality of elements and a plurality of node types, each node type corresponding with an element, each element of the pattern to be matched at least zero times, the element representing a character, character class or string; and wherein the processor is further configured to generate a plurality of nodes of the NFA graph, each node of the plurality of nodes configured to match with one of the plurality of elements and store the node type corresponding to the element, a next node address in the NFA graph, a count value, and the element, wherein the next node address and the count value are applicable as a function of the node type stored and wherein the plurality of nodes generated enable a graph walk engine to identify the pattern in a payload with less nodes relative to another NFA graph representing the pattern and employed by the graph walk engine to identify the pattern in the payload. | 31. A computer system for compiling a pattern into a non-deterministic finite automata (NFA) graph, the system comprising: a memory; and a processor, the processor coupled to the memory and configured to examine the pattern for a plurality of elements and a plurality of node types, each node type corresponding with an element, each element of the pattern to be matched at least zero times, the element representing a character, character class or string; and wherein the processor is further configured to generate a plurality of nodes of the NFA graph, each node of the plurality of nodes configured to match with one of the plurality of elements and store the node type corresponding to the element, a next node address in the NFA graph, a count value, and the element, wherein the next node address and the count value are applicable as a function of the node type stored and wherein the plurality of nodes generated enable a graph walk engine to identify the pattern in a payload with less nodes relative to another NFA graph representing the pattern and employed by the graph walk engine to identify the pattern in the payload. 40. The system of claim 31 , wherein the plurality of node types includes a variable count node type and the examining includes examining the pattern for the variable count node type, and wherein examining the pattern for the variable count node type includes determining whether a portion of the pattern indicates matching for the element a variable number of times. | 0.605552 |
9. A system, comprising: a hardware processor; and a memory storing a set of instructions which when executed by the processor cause the processor to: receive a request to build a new application developed using an application development framework; receive a template application, the template application comprising one or more binary artifacts and declarative information, the template application being pre-compiled using a build toolkit; modify the declarative information associated with the template application using metadata associated with the new application, the metadata configuring one or more components included in the new application, and the modifying comprising replacing a first set of definition files associated with the template application with a second set of definition files associated with the new application; and build the new application to target a mobile device using the one or more binary artifacts of the template application and the modified declarative information, wherein the set of instructions that cause the processor to modify the declarative information associated with the template application further comprise instructions that cause the processor to modify a reference to the declarative information to include a reference to declarative information associated with one or more portions of the new application. | 9. A system, comprising: a hardware processor; and a memory storing a set of instructions which when executed by the processor cause the processor to: receive a request to build a new application developed using an application development framework; receive a template application, the template application comprising one or more binary artifacts and declarative information, the template application being pre-compiled using a build toolkit; modify the declarative information associated with the template application using metadata associated with the new application, the metadata configuring one or more components included in the new application, and the modifying comprising replacing a first set of definition files associated with the template application with a second set of definition files associated with the new application; and build the new application to target a mobile device using the one or more binary artifacts of the template application and the modified declarative information, wherein the set of instructions that cause the processor to modify the declarative information associated with the template application further comprise instructions that cause the processor to modify a reference to the declarative information to include a reference to declarative information associated with one or more portions of the new application. 10. The system of claim 9 , wherein the set of instructions that cause the processor to receive the request to build the new application further comprise instructions that cause the processor to receive a request to package the new application for an operating system of the mobile device. | 0.77025 |
1. A computer-implemented method, comprising: receiving, at a computing device having one or more processors, composition inputs; determining, at the computing device, candidate selections for two or more different languages based on the composition inputs; evaluating, at the computing device, the candidate selections for the two or more different languages against language models for the two or more different languages, wherein each language model includes a rule set for a language, and wherein the language models collectively include rule sets for the two or more different languages; determining, at the computing device, a language context value for each of the two or more different languages based on the evaluation; identifying, at the computing device, candidate selections for presentation based on the language context values, the candidate selections including at least one candidate selection in each of the two or more languages; and providing for display, at the computing device, the candidate selections in a single, interleaved list of candidate selections, wherein the single, interleaved list of candidate selections (i) includes at least one candidate selection in each of the two or more languages and (ii) identifies a rank for each of the candidate selections, each rank being indicative of a relative likelihood that its corresponding candidate selection was intended from the composition inputs. | 1. A computer-implemented method, comprising: receiving, at a computing device having one or more processors, composition inputs; determining, at the computing device, candidate selections for two or more different languages based on the composition inputs; evaluating, at the computing device, the candidate selections for the two or more different languages against language models for the two or more different languages, wherein each language model includes a rule set for a language, and wherein the language models collectively include rule sets for the two or more different languages; determining, at the computing device, a language context value for each of the two or more different languages based on the evaluation; identifying, at the computing device, candidate selections for presentation based on the language context values, the candidate selections including at least one candidate selection in each of the two or more languages; and providing for display, at the computing device, the candidate selections in a single, interleaved list of candidate selections, wherein the single, interleaved list of candidate selections (i) includes at least one candidate selection in each of the two or more languages and (ii) identifies a rank for each of the candidate selections, each rank being indicative of a relative likelihood that its corresponding candidate selection was intended from the composition inputs. 6. The method of claim 1 , further comprising: receiving, at the computing device, additional composition inputs after receiving the composition inputs; determining, at the computing device, modified candidate selections for the two or more different languages based on the composition inputs and the additional composition inputs; evaluating, at the computing device, the modified candidate selections for the two or more different languages against language models for the two or more different languages; determining, at the computing device, a modified language context value for each of the two or more different languages based on the evaluation; identifying, at the computing device, modified candidate selections for presentation based on the language context values, the modified candidate selections including at least one of the modified candidate selections in each of the two or more languages; and providing for display, at the computing device, the modified candidate selections in a single, interleaved list of the modified candidate selections. | 0.654062 |
7. The method of claim 1 , wherein recommending another program further comprises: training a neural network using as training stimuli at least the program attributes of the currently viewed program determined to be included within the user-selected attribute category; and applying program attributes associated with available programs to the trained neural network to recommend the other program. | 7. The method of claim 1 , wherein recommending another program further comprises: training a neural network using as training stimuli at least the program attributes of the currently viewed program determined to be included within the user-selected attribute category; and applying program attributes associated with available programs to the trained neural network to recommend the other program. 9. The method of claim 7 further comprising ignoring selected program types in training the neural network. | 0.834742 |
7. A local domain name service (DNS) server, comprising: a network interface to provide a first DNS query for a first domain name to a network for provision to a domain-name dependency server (DDS), wherein the first domain name identifies a webpage; a cache to store a first set of domain names used to indicate content included in the webpage and received in response to the first DNS query, wherein the first set of domain names indicate other domains that are different than a domain indicated by the first domain name, and the first set of domain names is determined based on DNS queries from multiple devices over a wide area network; a processor configured to generate a set of DNS queries at the local DNS server to identify addresses for the first set of domain names, wherein the cache is to store a second set of domain names related to the first domain name, the processor is to merge the second set of domain names with the first set of domain names at the local DNS server to determine a third set of domain names, the processor is to generate the set of DNS queries based on the third set of domain names, the processor is to identify a time sequence of DNS queries for one of the local devices based on the client identifiers, and the processor is to determine the second set of domain names comprises based on DNS queries received from local devices via a local network, based on client identifiers included in the DNS queries, and based on the time sequence of DNS queries. | 7. A local domain name service (DNS) server, comprising: a network interface to provide a first DNS query for a first domain name to a network for provision to a domain-name dependency server (DDS), wherein the first domain name identifies a webpage; a cache to store a first set of domain names used to indicate content included in the webpage and received in response to the first DNS query, wherein the first set of domain names indicate other domains that are different than a domain indicated by the first domain name, and the first set of domain names is determined based on DNS queries from multiple devices over a wide area network; a processor configured to generate a set of DNS queries at the local DNS server to identify addresses for the first set of domain names, wherein the cache is to store a second set of domain names related to the first domain name, the processor is to merge the second set of domain names with the first set of domain names at the local DNS server to determine a third set of domain names, the processor is to generate the set of DNS queries based on the third set of domain names, the processor is to identify a time sequence of DNS queries for one of the local devices based on the client identifiers, and the processor is to determine the second set of domain names comprises based on DNS queries received from local devices via a local network, based on client identifiers included in the DNS queries, and based on the time sequence of DNS queries. 8. The local DNS server of claim 7 , wherein the processor is to: provide a response to a second DNS query including an address for a domain name of the second DNS query, the second DNS query to be received from a client device; and include with the response an indication that the address is not to be cached at the client device. | 0.59806 |
1. A method, comprising: obtaining, at a processor, (1) a first font name which includes a prefix portion and a remainder portion and (2) a second font name that includes a remainder portion but does not include a prefix portion; sorting, at the processor, the first font name and the second font name into a sorted order based at least in part on the remainder portion of the first font name and the remainder portion of the second font name without considering the prefix portion of the first font name; and displaying the first font name and the second font name in the sorted order, wherein the prefix portion of the first font name is displayed using a first display property and the remainder portion of the first font name and the remainder portion of the second font name are displayed using a second display property. | 1. A method, comprising: obtaining, at a processor, (1) a first font name which includes a prefix portion and a remainder portion and (2) a second font name that includes a remainder portion but does not include a prefix portion; sorting, at the processor, the first font name and the second font name into a sorted order based at least in part on the remainder portion of the first font name and the remainder portion of the second font name without considering the prefix portion of the first font name; and displaying the first font name and the second font name in the sorted order, wherein the prefix portion of the first font name is displayed using a first display property and the remainder portion of the first font name and the remainder portion of the second font name are displayed using a second display property. 3. A method as recited in claim 1 , wherein: the first display property is associated with a first column and the second display property is associated with a second column; and displaying includes: aligning the prefix portion of the first font name to the first column; and aligning the remainder portion of the first font name and the remainder portion of the second font name to the second column. | 0.803045 |
17. A system comprising: one or more processors and one or more computer-readable storage media storing instructions that are operable, when executed by the one or more processors, to cause the one or more processors to perform operations comprising: performing a first training process comprising: obtaining, for a first sequence-training speech model, a first batch of training frames that represent speech features of first training utterances; obtaining, for the first sequence-training speech model, one or more first neural network parameters; and determining, for the first sequence-training speech model, one or more adjusted first neural network parameters based on (i) the first batch of training frames and (ii) the one or more first neural network parameters; performing a second training process comprising: obtaining, for a second sequence-training speech model, a second batch of training frames that represent speech features of second training utterances, wherein the obtaining of the second batch of training frames by the second sequence-training speech model is independent of the obtaining of the first batch of training frames by the first sequence-training speech model; obtaining, for the second sequence-training speech model, one or more second neural network parameters, wherein the obtaining of the second neural network parameters by the second sequence-training speech model is independent of (i) the obtaining of the first neural network parameters by the first sequence-training speech model and (ii) the determining of the one or more adjusted first neural network parameters by the first sequence-training speech model; and determining, for the second sequence-training speech model, one or more adjusted second neural network parameters based on (i) the second batch of training frames and (ii) the one or more second neural network parameters, wherein the determining of the one or more adjusted second neural network parameters for the second sequence-training speech model is independent of the determining of the one or more adjusted first neural network parameters for the first sequence-training speech model; providing the one or more adjusted first neural network parameters and the one or more adjusted second neural network parameters to a computing system comprising at least one of the one or more processors; and determining, by the computing system, neural network parameters for a third sequence-training speech model based on the one or more adjusted first neural network parameters and the one or more adjusted second neural network parameters; wherein the first training process is performed concurrently with the second training process and asynchronously with respect to the second training process. | 17. A system comprising: one or more processors and one or more computer-readable storage media storing instructions that are operable, when executed by the one or more processors, to cause the one or more processors to perform operations comprising: performing a first training process comprising: obtaining, for a first sequence-training speech model, a first batch of training frames that represent speech features of first training utterances; obtaining, for the first sequence-training speech model, one or more first neural network parameters; and determining, for the first sequence-training speech model, one or more adjusted first neural network parameters based on (i) the first batch of training frames and (ii) the one or more first neural network parameters; performing a second training process comprising: obtaining, for a second sequence-training speech model, a second batch of training frames that represent speech features of second training utterances, wherein the obtaining of the second batch of training frames by the second sequence-training speech model is independent of the obtaining of the first batch of training frames by the first sequence-training speech model; obtaining, for the second sequence-training speech model, one or more second neural network parameters, wherein the obtaining of the second neural network parameters by the second sequence-training speech model is independent of (i) the obtaining of the first neural network parameters by the first sequence-training speech model and (ii) the determining of the one or more adjusted first neural network parameters by the first sequence-training speech model; and determining, for the second sequence-training speech model, one or more adjusted second neural network parameters based on (i) the second batch of training frames and (ii) the one or more second neural network parameters, wherein the determining of the one or more adjusted second neural network parameters for the second sequence-training speech model is independent of the determining of the one or more adjusted first neural network parameters for the first sequence-training speech model; providing the one or more adjusted first neural network parameters and the one or more adjusted second neural network parameters to a computing system comprising at least one of the one or more processors; and determining, by the computing system, neural network parameters for a third sequence-training speech model based on the one or more adjusted first neural network parameters and the one or more adjusted second neural network parameters; wherein the first training process is performed concurrently with the second training process and asynchronously with respect to the second training process. 19. The system of claim 17 , wherein the operations comprise: before obtaining, by the first sequence-training speech model, the first batch of training frames: obtaining an initial batch of training frames, wherein each training frame represents a sequence of utterances spoken by a training speaker; pseudo-randomly selecting candidate training frames from the initial batch of training frames; and generating the first batch of training frames using the pseudo-randomly selected candidate training frames. | 0.559358 |
17. A method of mitigating hazards in a voice-driven control system for controlling a medical device in an operating room, comprising the steps of: providing a medical device; providing a database including a plurality of rules, a first one of the plurality of rules immediately stopping a system or device activity if one or more speech commands is begun within a predetermined period of time after the activity was commenced, and a second one of the plurality of rules alerting if a disconnection with a microphone is detected; receiving an audio input including the one or more speech commands; identifying at least one event of the audio input; determining a system status including actions currently being performed by devices; determining whether hazard mitigation is necessary based on a comparison of the at least one event, the system status, and at least one rule; and if having determined that hazard mitigation is necessary, sending a control command to the medical device in communication with the voice-driven control system instructing it to perform an action. | 17. A method of mitigating hazards in a voice-driven control system for controlling a medical device in an operating room, comprising the steps of: providing a medical device; providing a database including a plurality of rules, a first one of the plurality of rules immediately stopping a system or device activity if one or more speech commands is begun within a predetermined period of time after the activity was commenced, and a second one of the plurality of rules alerting if a disconnection with a microphone is detected; receiving an audio input including the one or more speech commands; identifying at least one event of the audio input; determining a system status including actions currently being performed by devices; determining whether hazard mitigation is necessary based on a comparison of the at least one event, the system status, and at least one rule; and if having determined that hazard mitigation is necessary, sending a control command to the medical device in communication with the voice-driven control system instructing it to perform an action. 21. The method of claim 17 , wherein the event is an audio input error. | 0.683985 |
1. A method, in an information handling system comprising a processor and a memory, for analyzing concept vectors over time to detect changes in a corpus, the method comprising: generating, by the system, at least a first concept vector set V1, . . . , Vk derived from a first set of concept sequences over k concepts that are extracted from the corpus and applied to a vector learning component; generating, by the system, at least a second concept vector set V′1, . . . , V′k+b derived from a second set of concept sequences over k old and b new concepts that are extracted from the corpus and applied to the vector learning component, where the second set of concept sequences is effectively collected after collection of the first set of concept sequences; and performing, by the system, a natural language processing (NLP) analysis of the first concept vector set and second concept vector set to detect changes in the corpus over time by analyzing relationship strengths between concepts that persist in the first set of concept sequences and the second set of concept sequences to identify market trends for answering questions submitted to the information handling system by identifying vector changes for one or more concepts included in the first and/or second set of concept sequences, wherein analyzing relationship strengths comprises: computing, by the system, a first cosine distance between each vector pair Vi, Vj from the first concept vector set V1, . . . , Vk for all i≠j, 1≤i, j≤k; computing, by the system, a second cosine distance between each vector pair V′i, V′j from the second concept vector set V′1, . . . , V′k+b for all i≠j, 1≤i, j≤k; and identifying concept pairs from the first set of concept sequences whose interrelationship has changed by reporting each concept pair Vi, Vj whereby a subtraction of the second cosine distance from the first cosine distance exceeds a first specified reporting threshold. | 1. A method, in an information handling system comprising a processor and a memory, for analyzing concept vectors over time to detect changes in a corpus, the method comprising: generating, by the system, at least a first concept vector set V1, . . . , Vk derived from a first set of concept sequences over k concepts that are extracted from the corpus and applied to a vector learning component; generating, by the system, at least a second concept vector set V′1, . . . , V′k+b derived from a second set of concept sequences over k old and b new concepts that are extracted from the corpus and applied to the vector learning component, where the second set of concept sequences is effectively collected after collection of the first set of concept sequences; and performing, by the system, a natural language processing (NLP) analysis of the first concept vector set and second concept vector set to detect changes in the corpus over time by analyzing relationship strengths between concepts that persist in the first set of concept sequences and the second set of concept sequences to identify market trends for answering questions submitted to the information handling system by identifying vector changes for one or more concepts included in the first and/or second set of concept sequences, wherein analyzing relationship strengths comprises: computing, by the system, a first cosine distance between each vector pair Vi, Vj from the first concept vector set V1, . . . , Vk for all i≠j, 1≤i, j≤k; computing, by the system, a second cosine distance between each vector pair V′i, V′j from the second concept vector set V′1, . . . , V′k+b for all i≠j, 1≤i, j≤k; and identifying concept pairs from the first set of concept sequences whose interrelationship has changed by reporting each concept pair Vi, Vj whereby a subtraction of the second cosine distance from the first cosine distance exceeds a first specified reporting threshold. 5. The method of claim 1 , wherein performing the NLP analysis comprises detecting an appearance of one or more disruptive concepts in the second set of concept sequences that are related to a specified technology area represented by a sum of a plurality of concept vectors. | 0.568142 |
21. The method of claim 20 , wherein the neural network system comprises: an encoder LSTM that is configured to receive a current sequence of words authored by a current author and to process the current sequence to convert the current sequence into an alternative representation of the current sequence in accordance with current values of a set of encoder parameters, an embedding layer that is configured to map an identifier for the current author to a current author vector for the current author in accordance with current values of a set of author parameters, a combining subsystem that is configured to combine the alternative representation of the current sequence and the current author vector for the current author into a combined representation, and a decoder LSTM that is configured to receive the combined representation and to process the combined representation to predict a sequence of words that follows the current sequence in accordance with current values of a set of decoder parameters. | 21. The method of claim 20 , wherein the neural network system comprises: an encoder LSTM that is configured to receive a current sequence of words authored by a current author and to process the current sequence to convert the current sequence into an alternative representation of the current sequence in accordance with current values of a set of encoder parameters, an embedding layer that is configured to map an identifier for the current author to a current author vector for the current author in accordance with current values of a set of author parameters, a combining subsystem that is configured to combine the alternative representation of the current sequence and the current author vector for the current author into a combined representation, and a decoder LSTM that is configured to receive the combined representation and to process the combined representation to predict a sequence of words that follows the current sequence in accordance with current values of a set of decoder parameters. 22. The method of claim 21 , wherein the combining system is configured to: combine the alternative representation of the current sequence and the current author vector for the current author to generate a neural network input; and process the neural network input through one or more feedforward neural network layers to generate the combined representation. | 0.64955 |
15. The computer-implemented system of claim 10 , wherein the system is further programmed to determine that changes have been made in the document, identify one or more rows whose height could be affected by the changes, and mark the one or more rows in the cache as dirty, without immediately making a new determination of the heights of the one or more rows in the cache identified as dirty. | 15. The computer-implemented system of claim 10 , wherein the system is further programmed to determine that changes have been made in the document, identify one or more rows whose height could be affected by the changes, and mark the one or more rows in the cache as dirty, without immediately making a new determination of the heights of the one or more rows in the cache identified as dirty. 16. The computer-implemented system of claim 15 , wherein the system is further programmed to, after multiple instances of determining that changes have been made in the document, and associated marking of identified rows as dirty, identify a batch of dirty rows, determine heights for each of the identified rows, and record the heights in the cache for the identified rows. | 0.77396 |
12. The computer program product of claim 9 , the code for producing a print dialog in a user interface further comprising: code for providing a sensitivity meter input control to the user; code for receiving from the user a degree of sensitivity through said sensitivity meter input control; and code for causing the analysis of said electronically stored document to identify potential locations of relevant discussion based upon the degree of sensitivity. | 12. The computer program product of claim 9 , the code for producing a print dialog in a user interface further comprising: code for providing a sensitivity meter input control to the user; code for receiving from the user a degree of sensitivity through said sensitivity meter input control; and code for causing the analysis of said electronically stored document to identify potential locations of relevant discussion based upon the degree of sensitivity. 13. The computer program product of claim 12 , wherein at a low sensitivity, more locations are included in the locations of text relevant to the concept than at a high sensitivity, and at least one of the more locations is not of actual interest; and at the high sensitivity, a majority of denoted locations are included in the locations of text relevant to the concept, and at least one other relevant location is not included in the locations of text relevant to the concept. | 0.848112 |
6. A method comprising: performing operations to facilitate a displaying of an aggregate in at least near-real-time in a user interface, the facilitating including reducing an amount of processing time and an amount of resources required to perform the displaying of the aggregate by incrementally updating the aggregate instead of using a batch process to create an additional aggregate, the operations including: acquiring a data stream of payment card and transaction data from a first source, the data stream of the payment card and transaction data comprising a first data stream; storing a first set of data in a data structure, the first set of data taken from the first data stream, the first set of data including at least a portion of the payment card and transaction data; producing the aggregate from the first set of data by running a query on the data structure; acquiring a data stream of interaction data from a second source, the data stream of the interaction data comprising a second data stream; performing the incremental updating the aggregate, the incremental updating including creating a modified data structure based on the first data structure, the modified data structure including a second set of data into the aggregate and including at least a subset of the interaction data; and based on the incremental updating of the aggregate, running the query on the modified data structure and modifying the user interface in at least near-real time to include at least some of the second set of data as it is acquired from the second data stream, one or more modules incorporated into one or more memories of a computer system to configure one or more processors of the computer system to implement the performing of the incremental updating and modifying of the user interface. | 6. A method comprising: performing operations to facilitate a displaying of an aggregate in at least near-real-time in a user interface, the facilitating including reducing an amount of processing time and an amount of resources required to perform the displaying of the aggregate by incrementally updating the aggregate instead of using a batch process to create an additional aggregate, the operations including: acquiring a data stream of payment card and transaction data from a first source, the data stream of the payment card and transaction data comprising a first data stream; storing a first set of data in a data structure, the first set of data taken from the first data stream, the first set of data including at least a portion of the payment card and transaction data; producing the aggregate from the first set of data by running a query on the data structure; acquiring a data stream of interaction data from a second source, the data stream of the interaction data comprising a second data stream; performing the incremental updating the aggregate, the incremental updating including creating a modified data structure based on the first data structure, the modified data structure including a second set of data into the aggregate and including at least a subset of the interaction data; and based on the incremental updating of the aggregate, running the query on the modified data structure and modifying the user interface in at least near-real time to include at least some of the second set of data as it is acquired from the second data stream, one or more modules incorporated into one or more memories of a computer system to configure one or more processors of the computer system to implement the performing of the incremental updating and modifying of the user interface. 7. The method of claim 6 , wherein the data structure is stored in random access memory of a cluster computing framework configured to process data within the data structure in at least near real-time. | 0.535445 |
3. A character input device, comprising: a display unit; a touch sensor for detecting a contact with a surface thereof; a character recognition processing unit for performing a first character recognition process for recognizing a character used for a first function and a second character recognition process for recognizing a character used for a second function, on the basis of a locus connecting positions where the contact is detected by the touch sensor; and an input control unit for displaying, on the display unit, a first input screen for the first function onto which the character recognized by the first character recognition process is input and/or a second input screen for the second function onto which the character recognized by the second character recognition process is input, wherein the input control unit is configured to display the first input screen and/or the second input screen on the display unit, on the basis of a recognition accuracy of the character by the first character recognition process and a recognition accuracy of the character by the second character recognition process. | 3. A character input device, comprising: a display unit; a touch sensor for detecting a contact with a surface thereof; a character recognition processing unit for performing a first character recognition process for recognizing a character used for a first function and a second character recognition process for recognizing a character used for a second function, on the basis of a locus connecting positions where the contact is detected by the touch sensor; and an input control unit for displaying, on the display unit, a first input screen for the first function onto which the character recognized by the first character recognition process is input and/or a second input screen for the second function onto which the character recognized by the second character recognition process is input, wherein the input control unit is configured to display the first input screen and/or the second input screen on the display unit, on the basis of a recognition accuracy of the character by the first character recognition process and a recognition accuracy of the character by the second character recognition process. 5. The character input device according to claim 3 , wherein the input control unit is configured to display the first input screen when the recognition accuracy of the character by the first character recognition process is greater than a first threshold value, display the second input screen when the recognition accuracy of the character by the first character recognition process is less than a second threshold value set to be less than the first threshold value, and display both the first input screen and the second input screen when the recognition accuracy of the character by the first character recognition process is between the first threshold value and the second threshold value. | 0.577429 |
1. A method, performed in a computer, for synthesizing one or more relationships between concept definitions in a plurality of concept definitions, wherein each of the concept definitions comprises at least one of a plurality of attributes, the method comprising: providing a user interface comprising a web page that renders a view of data elements corresponding to an active content node in a domain of information, the active content node being associated with an active concept definition in the plurality of concept definitions; determining, based at least in part on input received via the user interface, whether any implicit relationships exist between the active concept definition and a first concept definition of the plurality of concept definitions, wherein an implicit relationship between the active concept definition and the first concept definition is determined to exist if the active concept definition and the first concept definition share at least one common attribute in the plurality of attributes; in response to determining that at least one implicit relationship exists between the active concept definition and the first concept definition, using the computer, synthesizing a previously unrecognized relationship between the active concept definition and the first concept definition; and generating a dimensional concept hierarchy based on dimensional concept relationships synthesized between the active concept definition and the plurality of concept definitions. | 1. A method, performed in a computer, for synthesizing one or more relationships between concept definitions in a plurality of concept definitions, wherein each of the concept definitions comprises at least one of a plurality of attributes, the method comprising: providing a user interface comprising a web page that renders a view of data elements corresponding to an active content node in a domain of information, the active content node being associated with an active concept definition in the plurality of concept definitions; determining, based at least in part on input received via the user interface, whether any implicit relationships exist between the active concept definition and a first concept definition of the plurality of concept definitions, wherein an implicit relationship between the active concept definition and the first concept definition is determined to exist if the active concept definition and the first concept definition share at least one common attribute in the plurality of attributes; in response to determining that at least one implicit relationship exists between the active concept definition and the first concept definition, using the computer, synthesizing a previously unrecognized relationship between the active concept definition and the first concept definition; and generating a dimensional concept hierarchy based on dimensional concept relationships synthesized between the active concept definition and the plurality of concept definitions. 3. The method of claim 1 , further comprising: defining a limit for a number of hierarchical steps in the dimensional concept hierarchy. | 0.580247 |
9. An apparatus for performing calculations in a character input mode of a electronic device, comprising: a display unit displaying input characters in a character input window in the character input mode; and a control unit determining whether a preset calculation enabling condition is satisfied, checking whether an arithmetic expression is present in the displayed input characters, evaluating the arithmetic expression when the preset calculation enabling condition is satisfied, and controlling the display unit to display a result of the evaluation. | 9. An apparatus for performing calculations in a character input mode of a electronic device, comprising: a display unit displaying input characters in a character input window in the character input mode; and a control unit determining whether a preset calculation enabling condition is satisfied, checking whether an arithmetic expression is present in the displayed input characters, evaluating the arithmetic expression when the preset calculation enabling condition is satisfied, and controlling the display unit to display a result of the evaluation. 13. The apparatus of claim 9 , wherein the control unit controls the display unit to replace the arithmetic expression with the evaluation result on the character input window. | 0.532132 |
15. At least one non-transitory computer-readable medium encoded with instructions that, when executed by a computer system, cause the computer system to perform a method for facilitating development of a natural language understanding (NLU) model associated with an NLU application executing on a computer system comprising a combination of hardware and, the method comprising acts of: receiving, from a developer of the NLU application, at least one expected user entry expected user entry and a corresponding to-a desired routing destination; determining whether the NLU model associates the at least one expected user entry with the desired routing destination, the determining comprising: interpreting the at least one expected user entry via the NLU model to determine an actual routing destination for the at least one expected user entry, and expected user entry, and comparing the actual routing destination to the desired routing destination; if it is determined that the actual routing destination does not match the desired routing destination of the at least one expected user entry matches the desired routing destination, selecting the at least one expected user entry for presentation to a user during a help prompt of the NLU application as an example of a legitimate utterance the user could speak to be routed to the desired routing destination; and if it is determined that the actual routing destination does not match the desired routing destination: (i) adding the at least one expected user entry to an NLU entry data set associated with the NLU model, and (ii) training the NLU model to associate the at least one expected user entry with the desired routing destination. | 15. At least one non-transitory computer-readable medium encoded with instructions that, when executed by a computer system, cause the computer system to perform a method for facilitating development of a natural language understanding (NLU) model associated with an NLU application executing on a computer system comprising a combination of hardware and, the method comprising acts of: receiving, from a developer of the NLU application, at least one expected user entry expected user entry and a corresponding to-a desired routing destination; determining whether the NLU model associates the at least one expected user entry with the desired routing destination, the determining comprising: interpreting the at least one expected user entry via the NLU model to determine an actual routing destination for the at least one expected user entry, and expected user entry, and comparing the actual routing destination to the desired routing destination; if it is determined that the actual routing destination does not match the desired routing destination of the at least one expected user entry matches the desired routing destination, selecting the at least one expected user entry for presentation to a user during a help prompt of the NLU application as an example of a legitimate utterance the user could speak to be routed to the desired routing destination; and if it is determined that the actual routing destination does not match the desired routing destination: (i) adding the at least one expected user entry to an NLU entry data set associated with the NLU model, and (ii) training the NLU model to associate the at least one expected user entry with the desired routing destination. 17. The at least one computer-readable medium of claim 15 , wherein training the NLU model to associate the at least one expected user entry with the desired routing destination causes the NLU model to form an association between the at least one expected user entry and the desired routing destination such that a user providing the at least one expected user entry during an interaction with the NLU application is connected to the desired routing destination. | 0.5 |
6. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain audio data representing an utterance of a user; obtain a decoding graph comprising: a first path associated with a first intent, wherein the first path comprises a first arc associated with a first token and a first content slot, and wherein the first content slot is associated with the first intent; a second path associated with the first intent, wherein the second path comprises a second arc associated with a second token and the first content slot; and a third path associated with a second intent that is different than the first intent; determine a first score using a value associated with the first path; determine a second score using a value associated with the second path; determine a third score using a value associated with the third path, wherein the third score is greater than the second score; modify at least one of the second score or the third score based at least partly on the second path being associated with the first intent and the third path being associated with the second intent, wherein the second score is greater than the third score after modifying at least one of the second score or the third score; generate, using at least a portion of the audio data and the first path, a first transcription of the utterance comprising the first token, wherein the first transcription is generated based at least partly on the first score; and generate, using at least a portion of the audio data and the second path, a second transcription of the utterance comprising the second token, wherein the second transcription is generated based at least partly on the second score. | 6. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain audio data representing an utterance of a user; obtain a decoding graph comprising: a first path associated with a first intent, wherein the first path comprises a first arc associated with a first token and a first content slot, and wherein the first content slot is associated with the first intent; a second path associated with the first intent, wherein the second path comprises a second arc associated with a second token and the first content slot; and a third path associated with a second intent that is different than the first intent; determine a first score using a value associated with the first path; determine a second score using a value associated with the second path; determine a third score using a value associated with the third path, wherein the third score is greater than the second score; modify at least one of the second score or the third score based at least partly on the second path being associated with the first intent and the third path being associated with the second intent, wherein the second score is greater than the third score after modifying at least one of the second score or the third score; generate, using at least a portion of the audio data and the first path, a first transcription of the utterance comprising the first token, wherein the first transcription is generated based at least partly on the first score; and generate, using at least a portion of the audio data and the second path, a second transcription of the utterance comprising the second token, wherein the second transcription is generated based at least partly on the second score. 16. The system of claim 6 , wherein the decoding graph comprises a plurality of metadata tags, wherein a first metadata tag of the plurality of metadata tags represents the first intent and is associated with the first path, wherein a second metadata tag of the plurality of metadata tags represents the first intent and is associated with the second path, and wherein a third metadata tag of the plurality of metadata tags represents the second intent and is associated with the third path. | 0.57923 |
1. A method for speech recognition in a motor vehicle, comprising: receiving voice inputs from a user at a vehicle-internal processing device, the voice inputs being received via a vehicle-internal capture device; supplying by the processing device: at least one voice input to a vehicle-internal onboard speech recognition unit for producing a first recognition result of spoken text; at least one voice input to a vehicle-external offboard speech recognition unit for producing a second recognition result of spoken text; receiving the first recognition result at the processing device from the onboard speech recognition unit; receiving the second recognition result at the processing device from the offboard speech recognition unit; and using the first and second recognition results by the processing device as a basis for automatically ascertaining recognition text corresponding to the voice inputs, wherein the processing device selects and activates based on a control parameter, one of the following modes for speech recognition purposes: sequential speech recognition in which keyword recognition is first performed using the onboard speech recognition unit, and then the first recognition result is used to extract at least one recognizable component and at least one unrecognizable component, the at least one recognizable component is used to select the vehicle-external offboard speech recognition unit among a plurality of vehicle-external offboard speech recognition units, and the at least one unrecognizable component is then supplied to the selected vehicle-external offboard speech recognition unit to produce the second recognition result; parallel speech recognition in which a single voice input is supplied in parallel to the onboard speech recognition unit and independently thereof to the offboard speech recognition unit; complete onboard speech recognition using the onboard speech recognition unit; and complete offboard speech recognition using the offboard speech recognition unit, and wherein the control parameter on which the processing device bases selection and activation, is a parameter relating to a current operational scenario, the operational scenario indicating what operator control process is meant to be performed by the user by way of the recognition text. | 1. A method for speech recognition in a motor vehicle, comprising: receiving voice inputs from a user at a vehicle-internal processing device, the voice inputs being received via a vehicle-internal capture device; supplying by the processing device: at least one voice input to a vehicle-internal onboard speech recognition unit for producing a first recognition result of spoken text; at least one voice input to a vehicle-external offboard speech recognition unit for producing a second recognition result of spoken text; receiving the first recognition result at the processing device from the onboard speech recognition unit; receiving the second recognition result at the processing device from the offboard speech recognition unit; and using the first and second recognition results by the processing device as a basis for automatically ascertaining recognition text corresponding to the voice inputs, wherein the processing device selects and activates based on a control parameter, one of the following modes for speech recognition purposes: sequential speech recognition in which keyword recognition is first performed using the onboard speech recognition unit, and then the first recognition result is used to extract at least one recognizable component and at least one unrecognizable component, the at least one recognizable component is used to select the vehicle-external offboard speech recognition unit among a plurality of vehicle-external offboard speech recognition units, and the at least one unrecognizable component is then supplied to the selected vehicle-external offboard speech recognition unit to produce the second recognition result; parallel speech recognition in which a single voice input is supplied in parallel to the onboard speech recognition unit and independently thereof to the offboard speech recognition unit; complete onboard speech recognition using the onboard speech recognition unit; and complete offboard speech recognition using the offboard speech recognition unit, and wherein the control parameter on which the processing device bases selection and activation, is a parameter relating to a current operational scenario, the operational scenario indicating what operator control process is meant to be performed by the user by way of the recognition text. 11. The method as claimed in claim 1 , wherein in parallel speech recognition, the single voice input is supplied in different formats to the onboard and offboard speech recognition units. | 0.611463 |
15. A non-transitory computer-readable medium storing instructions for improving identification of multimedia content for inclusion in a messaging conversation, the instructions comprising: one or more instructions that, when executed by a processor, cause the processor to: provide, for display, a messaging application user interface of a messaging application, the messaging application being for one or more of short messaging service (SMS) messages, enhanced messaging service (EMS) messages, or multimedia message service (MMS) messages, and the messaging application user interface comprising a text entry box, a submit button, and a messaging conversation display region; receive, in the text entry box, a text input; determine, using the messaging application, that the text input includes a search function indicator; replace, based on determining that the text input includes the search function indicator, the submit button with a search button, invoke, based on receiving a selection of the search button, a search application provided by a mobile device; provide one or more search terms, determined from the text input, to the invoked search application; identify, after providing the one or more search terms, one or more search results based on the search application using a particular search engine to search the Internet, the particular search engine being previously selected by a user of the mobile device; provide, for display, a menu of the one or more search results in the messaging application user interface, the one or more search results including a particular search result for the multimedia content; receive information identifying a selection of the particular search result from the menu of the one or more search results; incorporate, based on the information identifying the selection of the particular search result, the particular search result into a portion of the text input received in in the text entry box of the messaging application user interface; and replace the search button with the submit button in the messaging application user interface. | 15. A non-transitory computer-readable medium storing instructions for improving identification of multimedia content for inclusion in a messaging conversation, the instructions comprising: one or more instructions that, when executed by a processor, cause the processor to: provide, for display, a messaging application user interface of a messaging application, the messaging application being for one or more of short messaging service (SMS) messages, enhanced messaging service (EMS) messages, or multimedia message service (MMS) messages, and the messaging application user interface comprising a text entry box, a submit button, and a messaging conversation display region; receive, in the text entry box, a text input; determine, using the messaging application, that the text input includes a search function indicator; replace, based on determining that the text input includes the search function indicator, the submit button with a search button, invoke, based on receiving a selection of the search button, a search application provided by a mobile device; provide one or more search terms, determined from the text input, to the invoked search application; identify, after providing the one or more search terms, one or more search results based on the search application using a particular search engine to search the Internet, the particular search engine being previously selected by a user of the mobile device; provide, for display, a menu of the one or more search results in the messaging application user interface, the one or more search results including a particular search result for the multimedia content; receive information identifying a selection of the particular search result from the menu of the one or more search results; incorporate, based on the information identifying the selection of the particular search result, the particular search result into a portion of the text input received in in the text entry box of the messaging application user interface; and replace the search button with the submit button in the messaging application user interface. 17. The non-transitory computer-readable medium of claim 15 , wherein the instructions further comprise: one or more instructions that, when executed by the processor, cause the processor to: receive search suggestions from the search application based on providing the one or more search terms to the search application; and provide, for display, the received search suggestions. | 0.53727 |
5. A system on a mobile device for providing access to supplemental electronic materials associated with a document, the system comprising: a text capture component, wherein the text capture component includes a scanner programmed to capture a human-readable text sequence of a print version of a document, wherein the human-readable text sequence includes text that is perceptible to a human on the print version of the document; a processing component, wherein the processing component is programmed to process data from the text capture component to recognize the text; an identification component, wherein the identification component is programmed to determine, from the recognized text, a text string corresponding to the captured human-readable text sequence and identify the document using the text string; a content access component, wherein the content access component is programmed to: identify supplemental electronic materials associated with the document, the supplemental electronic materials being materials presentable using an audio or visual medium; determine that a request to access the supplemental electronic materials associated with the document is implicit in receiving the human-readable text sequence; receive a set of access rules for the supplemental electronic materials associated with the document; and resolve the request by enabling access to the supplemental electronic materials when the request satisfies the access rules or denying access to the supplemental electronic materials when the request does not satisfy the access rules, wherein resolving the request by enabling access to the supplemental electronic materials when the request satisfies the access rules includes permitting access to the supplemental electronic materials when the received human-readable text sequence includes an indication that the human-readable text sequence was captured from the print version of the document; and a content presentation component, wherein the content presentation component is programmed to present the supplemental electronic materials associated with the document to a user associated with the mobile device. | 5. A system on a mobile device for providing access to supplemental electronic materials associated with a document, the system comprising: a text capture component, wherein the text capture component includes a scanner programmed to capture a human-readable text sequence of a print version of a document, wherein the human-readable text sequence includes text that is perceptible to a human on the print version of the document; a processing component, wherein the processing component is programmed to process data from the text capture component to recognize the text; an identification component, wherein the identification component is programmed to determine, from the recognized text, a text string corresponding to the captured human-readable text sequence and identify the document using the text string; a content access component, wherein the content access component is programmed to: identify supplemental electronic materials associated with the document, the supplemental electronic materials being materials presentable using an audio or visual medium; determine that a request to access the supplemental electronic materials associated with the document is implicit in receiving the human-readable text sequence; receive a set of access rules for the supplemental electronic materials associated with the document; and resolve the request by enabling access to the supplemental electronic materials when the request satisfies the access rules or denying access to the supplemental electronic materials when the request does not satisfy the access rules, wherein resolving the request by enabling access to the supplemental electronic materials when the request satisfies the access rules includes permitting access to the supplemental electronic materials when the received human-readable text sequence includes an indication that the human-readable text sequence was captured from the print version of the document; and a content presentation component, wherein the content presentation component is programmed to present the supplemental electronic materials associated with the document to a user associated with the mobile device. 6. The system of claim 5 , wherein the content access component is programmed to enable access to additional supplemental electronic materials associated with the document upon determining that a user of the mobile device is a subscriber of the document. | 0.598545 |
8. The method of claim 1 , said recording step further comprising: initializing an abstraction recordation process responsive to the voice command; detecting a set of actions included in the abstraction; ascertaining a user triggered event to finalize the abstraction; and storing the abstraction for future use, wherein the abstraction is stored as the abstraction type specified by the voice command. | 8. The method of claim 1 , said recording step further comprising: initializing an abstraction recordation process responsive to the voice command; detecting a set of actions included in the abstraction; ascertaining a user triggered event to finalize the abstraction; and storing the abstraction for future use, wherein the abstraction is stored as the abstraction type specified by the voice command. 9. The method of claim 8 , wherein the user triggered event is an event triggered by a user stop recording voice command, wherein the stop recording voice command is a phrase used for a plurality of different types of abstractions to end an abstraction recording. | 0.778682 |
17. A system for converting a natural language query into a one or more logical queries, comprising: a plurality of domain independent specialized tools stored on a non-transitory computer readable storage medium, each of the plurality of specialized tools being adapted to perform a highly specific recognition task, each of the specialized tools operable independently from any of the other specialized tools, and each of the recognition tools being adapted to operate independent of any particular data; one or more knowledge bases stored on a non-transitory computer readable storage medium for use by one or more of the specialized tools to perform its specific recognition task; and an extensible engine, of a processor, which converts the natural language query to one or more logical queries in accordance with one or more of the plurality of specialized tools by causing a general purpose computer to generate a collective recognition judgment in accordance with individual recognition results received from a plurality of the plurality of specialized tools, at least two of the plurality specialized tools performing its highly specific recognition task on a similar portion of natural language query and providing distinct interpretation results, the computer outputting the collective judgment to a non-transitory computer readable storage medium. | 17. A system for converting a natural language query into a one or more logical queries, comprising: a plurality of domain independent specialized tools stored on a non-transitory computer readable storage medium, each of the plurality of specialized tools being adapted to perform a highly specific recognition task, each of the specialized tools operable independently from any of the other specialized tools, and each of the recognition tools being adapted to operate independent of any particular data; one or more knowledge bases stored on a non-transitory computer readable storage medium for use by one or more of the specialized tools to perform its specific recognition task; and an extensible engine, of a processor, which converts the natural language query to one or more logical queries in accordance with one or more of the plurality of specialized tools by causing a general purpose computer to generate a collective recognition judgment in accordance with individual recognition results received from a plurality of the plurality of specialized tools, at least two of the plurality specialized tools performing its highly specific recognition task on a similar portion of natural language query and providing distinct interpretation results, the computer outputting the collective judgment to a non-transitory computer readable storage medium. 29. The system of claim 17 , wherein the extensible engine has a main processing algorithm that engages portions of the tools and stores all intermediate results inside a plurality of data-structures. | 0.546885 |
1. A method of facilitating logo recognition training of a neural network via an image training set generated based on one or more logos, the method being implemented by a computer system that comprises one or more processors executing computer program instructions that, when executed, perform the method, the method comprising: obtaining logo information associated with a rendering of a logo that is to be recognized via a neural network; generating images based on the logo information, each of the images comprising (i) content other than the logo and (ii) a given rendering of the logo integrated with the other content; processing, via the neural network, the images to generate predictions related to recognition of the logo for the images, the generated predictions comprising a predicted boundary structure indicating a predicted location of the logo in a first image of the images; causing, via a user interface, presentation of the predicted boundary structure on an area of the first image; obtaining a reference feedback set, the reference feedback set comprising reference indications related to recognition of the logo for the images, the reference indications comprising a reference indication corresponding to (i) a user-initiated movement of the predicted boundary structure to another area of the first image that is initiated via the user interface or (ii) a user-initiated resizing of the predicted boundary structure that is initiated via the user interface; and updating the neural network based the generated predictions and the reference feedback set such that the neural network is updated based on the predicted boundary structure and the reference indication corresponding to the user-initiated movement or resizing. | 1. A method of facilitating logo recognition training of a neural network via an image training set generated based on one or more logos, the method being implemented by a computer system that comprises one or more processors executing computer program instructions that, when executed, perform the method, the method comprising: obtaining logo information associated with a rendering of a logo that is to be recognized via a neural network; generating images based on the logo information, each of the images comprising (i) content other than the logo and (ii) a given rendering of the logo integrated with the other content; processing, via the neural network, the images to generate predictions related to recognition of the logo for the images, the generated predictions comprising a predicted boundary structure indicating a predicted location of the logo in a first image of the images; causing, via a user interface, presentation of the predicted boundary structure on an area of the first image; obtaining a reference feedback set, the reference feedback set comprising reference indications related to recognition of the logo for the images, the reference indications comprising a reference indication corresponding to (i) a user-initiated movement of the predicted boundary structure to another area of the first image that is initiated via the user interface or (ii) a user-initiated resizing of the predicted boundary structure that is initiated via the user interface; and updating the neural network based the generated predictions and the reference feedback set such that the neural network is updated based on the predicted boundary structure and the reference indication corresponding to the user-initiated movement or resizing. 6. The method of claim 1 , further comprising: determining locations at which to place a given rendering of the logo on a given image, each of the locations being different from one another, wherein generating the images comprises generating at least some of the images based on the locations such that each image of the at least some images comprises a given rendering of the logo at different one of the locations. | 0.546663 |
13. The handheld electronic device of claim 12 , wherein the plurality of objects further include a plurality of frequency objects each having a frequency value, at least some of the artificial variants each being associated with an associated frequency object, and further comprising outputting the first character permutations in descending order of frequency value. | 13. The handheld electronic device of claim 12 , wherein the plurality of objects further include a plurality of frequency objects each having a frequency value, at least some of the artificial variants each being associated with an associated frequency object, and further comprising outputting the first character permutations in descending order of frequency value. 15. The handheld electronic device of claim 13 , wherein the ambiguous input comprises a number of initial character selections and a current character selection, and further comprising: responsive to the number of initial character selections, identifying at least one artificial variant that corresponds with a particular character permutation of the number of initial character selections; and outputting as one of the second character permutations the particular character permutation plus a character assigned to the input member of the current character selection. | 0.63607 |
4. The method of claim 2 , wherein determining whether the first document is the query-specific duplicate of a second document further comprises determining whether the one or more first query-relevant parts are similar to the one or more second query-relevant parts. | 4. The method of claim 2 , wherein determining whether the first document is the query-specific duplicate of a second document further comprises determining whether the one or more first query-relevant parts are similar to the one or more second query-relevant parts. 5. The method of claim 4 , further comprising determining whether the one or more first query-relevant parts are similar to the one or more second query relevant-parts according to one or more of an edit distance between the one or more first query-relevant parts and the one or more second query-relevant parts, a cosine distance between a feature vector for the one or more first query-relevant parts and a feature vector for the one or more second query-relevant parts, or an analysis of shingles in the one or more first query-relevant parts and shingles in the one or more second query-relevant parts. | 0.834097 |
10. A non-transitory computer-readable medium having contents that, when executed by a client device, facilitate electronic signatures via the client device by performing a method comprising in the client device: importing, by the client device, documents obtained from an email client of the client device into a remote electronic signature service, by: receiving an electronic signature document; in response to an input received from the signer, causing the received electronic signature document to be stored at the remote electronic signature service; providing access to the electronic signature document stored at the remote electronic signature service; and causing an electronic signature of the signer to be stored in association with the electronic signature document stored at the remote electronic signature service; wherein the electronic signature document is initially received by the email client, wherein the input received from the signer is received via a user interface of the email client, as modified by a plug-in module of the email client, wherein causing the received electronic signature document to be stored includes transmitting, by the plug-in module, the received electronic signature document to the remote electronic signature service, where the electronic signature document is converted into a standard format, and wherein providing access to the electronic signature document includes automatically causing, by the plug-in module, the electronic signature document to be displayed in a Web browser of the client device, such that the signer can review, modify, and sign the electronic signature document, and further comprising: after causing the electronic signature of the signer to be stored in association with the electronic signature document, automatically causing, by the plug-in module, the email client to prepare an outgoing email message that includes an attached file that represents the electronic signature document including the electronic signature of the signer. | 10. A non-transitory computer-readable medium having contents that, when executed by a client device, facilitate electronic signatures via the client device by performing a method comprising in the client device: importing, by the client device, documents obtained from an email client of the client device into a remote electronic signature service, by: receiving an electronic signature document; in response to an input received from the signer, causing the received electronic signature document to be stored at the remote electronic signature service; providing access to the electronic signature document stored at the remote electronic signature service; and causing an electronic signature of the signer to be stored in association with the electronic signature document stored at the remote electronic signature service; wherein the electronic signature document is initially received by the email client, wherein the input received from the signer is received via a user interface of the email client, as modified by a plug-in module of the email client, wherein causing the received electronic signature document to be stored includes transmitting, by the plug-in module, the received electronic signature document to the remote electronic signature service, where the electronic signature document is converted into a standard format, and wherein providing access to the electronic signature document includes automatically causing, by the plug-in module, the electronic signature document to be displayed in a Web browser of the client device, such that the signer can review, modify, and sign the electronic signature document, and further comprising: after causing the electronic signature of the signer to be stored in association with the electronic signature document, automatically causing, by the plug-in module, the email client to prepare an outgoing email message that includes an attached file that represents the electronic signature document including the electronic signature of the signer. 11. The computer-readable medium of claim 10 , wherein providing access to the electronic signature document includes, after the electronic signature document is stored at the remote electronic signature service, automatically causing a Web browser of the client device to access an electronic signature service application hosted by the remote electronic signature service, the application configured to facilitate review, modification, and signature by the signer of the electronic signature document. | 0.5 |
12. The system of claim 11 , wherein the advertising targeting application further directs the processor to measure the performance of the advertising campaign. | 12. The system of claim 11 , wherein the advertising targeting application further directs the processor to measure the performance of the advertising campaign. 13. The system of claim 12 , wherein the advertising targeting application further directs the processor to: obtain a set of messages related to the advertising campaign within the online social network, where the messages were posted by members of the online social network; and determine if the members that posted the messages in the set of messages are associated with the member groups targeted by the advertising campaign. | 0.929256 |
1. A method for classifying structural input data, the method comprising a computer system performing steps of: constructing multiple classifiers, wherein each classifier is constructed on a subset of training data, using selected composite features from the subset of training data, the composite features being selected by iteratively applying a feature selection step wherein multiple disjoint feature sets are identified to represent the structural input data in different feature spaces, and the structural input data, when characterized by a skewed prior class distribution, being subjected to a sampling step to obtain a balanced class distribution; and computing a consensus among the multiple classifiers in accordance with a voting scheme such that at least a portion of the structural input data is assigned to a particular class in accordance with the computed consensus; wherein the computer system comprises a memory and a processor device operatively coupled to the memory. | 1. A method for classifying structural input data, the method comprising a computer system performing steps of: constructing multiple classifiers, wherein each classifier is constructed on a subset of training data, using selected composite features from the subset of training data, the composite features being selected by iteratively applying a feature selection step wherein multiple disjoint feature sets are identified to represent the structural input data in different feature spaces, and the structural input data, when characterized by a skewed prior class distribution, being subjected to a sampling step to obtain a balanced class distribution; and computing a consensus among the multiple classifiers in accordance with a voting scheme such that at least a portion of the structural input data is assigned to a particular class in accordance with the computed consensus; wherein the computer system comprises a memory and a processor device operatively coupled to the memory. 3. The method of claim 1 , wherein the composite features are not the same across different classifiers. | 0.525047 |
1. A speech synthesis apparatus comprising: a statistical model storage configured to store a plurality of statistical models prepared by statistically modeling acoustic information included in speech; a basis model storage configured to store a basis model including a plurality of basis vectors, each of which expresses speech information for each limited frequency range; and a computer programmed to, based on instructions stored in a memory: analyze, by a language analyzer, text data and output language information data that represents linguistic information of the text data; select, by a model selector, a statistical model from the plurality of statistical models stored in the statistical model storage, based on the language information data output from the language analyzer; generate, by a parameter generator, a plurality of speech parameter sequences using the statistical model selected by the model selector; output, by a filter processor, synthetic speech by executing filter processing of the plurality of speech parameter sequences generated by the parameter generator and the basis model stored in the basis model storage, wherein any of the plurality of speech parameter sequences represents weights to be applied to the basis vectors upon linearly combining the plurality of basis vectors in the basis model in the basis model storage. | 1. A speech synthesis apparatus comprising: a statistical model storage configured to store a plurality of statistical models prepared by statistically modeling acoustic information included in speech; a basis model storage configured to store a basis model including a plurality of basis vectors, each of which expresses speech information for each limited frequency range; and a computer programmed to, based on instructions stored in a memory: analyze, by a language analyzer, text data and output language information data that represents linguistic information of the text data; select, by a model selector, a statistical model from the plurality of statistical models stored in the statistical model storage, based on the language information data output from the language analyzer; generate, by a parameter generator, a plurality of speech parameter sequences using the statistical model selected by the model selector; output, by a filter processor, synthetic speech by executing filter processing of the plurality of speech parameter sequences generated by the parameter generator and the basis model stored in the basis model storage, wherein any of the plurality of speech parameter sequences represents weights to be applied to the basis vectors upon linearly combining the plurality of basis vectors in the basis model in the basis model storage. 12. The apparatus according to claim 1 , wherein the computer is further programmed to learn, by a learning device, the statistical model using language information data based on speech data, and acoustic feature amounts extracted using the basis model based on the speech data. | 0.568672 |
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