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7,711,673 | 1 | 11 | 1. A computer-implemented method for handling an email message received through a communication network, said email message including a target document, said target document involving an encoding scheme, the method comprising: training, using a plurality of text document samples that have been encoded with different encoding schemes and selected for training purposes to obtain a set of machine learning models, said different encoding schemes pertaining to charset encoding for transmission over a network, said training including using SIM (Similarity Algorithm) to generate said set of machine learning models from feature vectors converted from said plurality of text document samples, said feature vectors are grouped by charsets, wherein said training including generating fundamental units from said plurality of text document samples for charsets of said plurality of text document samples and extracting a subset of said fundamental units to form a set of feature lists, said feature vectors are converted from said set of feature lists and said plurality of text document samples, said extracting said subset of said fundamental units includes filtering said fundamental units to obtain fundamental units that are more discriminatory in describing differences among said different encoding schemes; applying said set of machine learning models against a set of target document feature vectors converted from said target document, said applying including analyzing said set of target document feature vectors using said set of machine learning models to compute similarity indicia between said set of target document feature vectors and said set of machine learning models associated with said different encoding schemes, said similarity indicia including at least a set of cross-angles between said set of target document feature vectors and said set of machine learning models, wherein a first encoding scheme associated with said set of machine learning models is designated as said encoding scheme if characteristics of said first encoding scheme as represented by said set of machine learning models are computed to be most similar, relative to other encoding schemes of said different encoding schemes, to said set of target document feature vectors; decoding said target document to obtain decoded content of said document based on at least said first encoding scheme; determining whether said email message is a spam message based on at least said decoded content of said document; and preventing said email message from reaching an email user if said email message is determined to be spam according to said determining. | 1. A computer-implemented method for handling an email message received through a communication network, said email message including a target document, said target document involving an encoding scheme, the method comprising: training, using a plurality of text document samples that have been encoded with different encoding schemes and selected for training purposes to obtain a set of machine learning models, said different encoding schemes pertaining to charset encoding for transmission over a network, said training including using SIM (Similarity Algorithm) to generate said set of machine learning models from feature vectors converted from said plurality of text document samples, said feature vectors are grouped by charsets, wherein said training including generating fundamental units from said plurality of text document samples for charsets of said plurality of text document samples and extracting a subset of said fundamental units to form a set of feature lists, said feature vectors are converted from said set of feature lists and said plurality of text document samples, said extracting said subset of said fundamental units includes filtering said fundamental units to obtain fundamental units that are more discriminatory in describing differences among said different encoding schemes; applying said set of machine learning models against a set of target document feature vectors converted from said target document, said applying including analyzing said set of target document feature vectors using said set of machine learning models to compute similarity indicia between said set of target document feature vectors and said set of machine learning models associated with said different encoding schemes, said similarity indicia including at least a set of cross-angles between said set of target document feature vectors and said set of machine learning models, wherein a first encoding scheme associated with said set of machine learning models is designated as said encoding scheme if characteristics of said first encoding scheme as represented by said set of machine learning models are computed to be most similar, relative to other encoding schemes of said different encoding schemes, to said set of target document feature vectors; decoding said target document to obtain decoded content of said document based on at least said first encoding scheme; determining whether said email message is a spam message based on at least said decoded content of said document; and preventing said email message from reaching an email user if said email message is determined to be spam according to said determining. 11. The computer-implemented method of claim 1 wherein said target document represents an attachment to said email message. | 0.7607 |
8,775,406 | 39 | 49 | 39. A method of predicting content of a future unpublished news story with a computing system comprising: a) identifying a first event described in content published in a knowledge domain including one or more social network domains, news content domains, blog domains and/or message board domains; b) automatically predicting future content for a plurality of different alternative future unpublished stories for said first event or updates to said first event, based on a comparison of characteristics of said first event to characteristics of prior events of a same type; wherein said future content is derived from content of prior stories describing said prior events; c) automatically searching for a numerical outcome associated with said first event by querying at least one of a social network, message board, blog and/or search engine. | 39. A method of predicting content of a future unpublished news story with a computing system comprising: a) identifying a first event described in content published in a knowledge domain including one or more social network domains, news content domains, blog domains and/or message board domains; b) automatically predicting future content for a plurality of different alternative future unpublished stories for said first event or updates to said first event, based on a comparison of characteristics of said first event to characteristics of prior events of a same type; wherein said future content is derived from content of prior stories describing said prior events; c) automatically searching for a numerical outcome associated with said first event by querying at least one of a social network, message board, blog and/or search engine. 49. The method of claim 39 further including a step: adjusting an advertising pricing for keywords based on identifying said numerical outcome. | 0.714 |
8,098,409 | 11 | 14 | 11. The image distribution system via e-mail according to claim 1 , wherein the system is adapted to enable the user of the first user terminal to input a plurality of different ideogram string element or elements to change the images corresponding to the respective ideogram string element or elements. | 11. The image distribution system via e-mail according to claim 1 , wherein the system is adapted to enable the user of the first user terminal to input a plurality of different ideogram string element or elements to change the images corresponding to the respective ideogram string element or elements. 14. The image distribution system via e-mail according to claim 11 , wherein the system includes morphing means for processing the plurality of different images by so that the different images are continuous one to another. | 0.5 |
9,552,562 | 8 | 10 | 8. A non-transitory computer-readable medium storing one or more sequences of instructions which, when executed by one or more processors, cause performing of: receiving a request to launch a visual information builder for a specific task of an application that uses a rule engine; accessing a stored rule model of two or more different candidate rule models, wherein the rule model comprises a plurality of objects including nodes and attributes wherein the nodes correspond to conditions and actions and wherein the attributes comprise parameters for defining the conditions and actions; wherein the plurality of objects are retrieved from a rule dictionary of the rule engine based on the specific task; wherein a particular node of the plurality of objects is associated with a template defining one or more options, for the particular node, that are based on the specific task; presenting a user interface of the visual information builder that is configured to receive user input specifying a selection of one or more objects from the rule model and specifying a logical combination of the one or more objects that were selected from the rule model, wherein the particular node is editable in the user interface according to the template; receiving user input specifying one or more selected objects and a particular logical combination of the one or more selected objects; converting the particular logical combination of the one or more selected objects into one or more rules evaluable by the rule engine; and storing the one or more rules in the rule dictionary. | 8. A non-transitory computer-readable medium storing one or more sequences of instructions which, when executed by one or more processors, cause performing of: receiving a request to launch a visual information builder for a specific task of an application that uses a rule engine; accessing a stored rule model of two or more different candidate rule models, wherein the rule model comprises a plurality of objects including nodes and attributes wherein the nodes correspond to conditions and actions and wherein the attributes comprise parameters for defining the conditions and actions; wherein the plurality of objects are retrieved from a rule dictionary of the rule engine based on the specific task; wherein a particular node of the plurality of objects is associated with a template defining one or more options, for the particular node, that are based on the specific task; presenting a user interface of the visual information builder that is configured to receive user input specifying a selection of one or more objects from the rule model and specifying a logical combination of the one or more objects that were selected from the rule model, wherein the particular node is editable in the user interface according to the template; receiving user input specifying one or more selected objects and a particular logical combination of the one or more selected objects; converting the particular logical combination of the one or more selected objects into one or more rules evaluable by the rule engine; and storing the one or more rules in the rule dictionary. 10. The non-transitory computer-readable medium of claim 8 , wherein the attributes retrieved from the rule dictionary are based on the particular node. | 0.672414 |
9,754,279 | 1 | 9 | 1. A computerized method comprising: sampling one or more streams of electronic data, the electronic data comprising user communications data, to obtain sample data, wherein sampling the streams of electronic data comprises real-time sampling, sensing, and detection of user communications data comprising user-generated content data streams that are in transmission to, but not yet received by, intended recipients; analyzing the user-generated content data streams in the sample data to obtain targeting data for use in targeting electronic advertisements to electronic device users, wherein the targeting data comprises data relating to topics of interest to the electronic device users; based at least in part on the analyzing of the user-generated content data streams in the sample data, increasing one or more sampling frequencies or rates during at least one period based on a determination that targeting data is more likely to be concentrated during the at least one period than during other periods, wherein the increasing of the one or more sampling frequencies or rates is determined by utilizing one or more analytic correlation applications in detecting patterns, and wherein the patterns can include time-based or frequency-based patterns associated with the user-generated content data streams; based at least in part on the targeting data obtained, selecting electronic advertisements for serving to targeted electronic device users; and serving the selected electronic advertisements to the targeted electronic device users, the serving including causing an advertisement serving system to initiate or modify an automated advertising campaign that includes the selected electronic advertisements. | 1. A computerized method comprising: sampling one or more streams of electronic data, the electronic data comprising user communications data, to obtain sample data, wherein sampling the streams of electronic data comprises real-time sampling, sensing, and detection of user communications data comprising user-generated content data streams that are in transmission to, but not yet received by, intended recipients; analyzing the user-generated content data streams in the sample data to obtain targeting data for use in targeting electronic advertisements to electronic device users, wherein the targeting data comprises data relating to topics of interest to the electronic device users; based at least in part on the analyzing of the user-generated content data streams in the sample data, increasing one or more sampling frequencies or rates during at least one period based on a determination that targeting data is more likely to be concentrated during the at least one period than during other periods, wherein the increasing of the one or more sampling frequencies or rates is determined by utilizing one or more analytic correlation applications in detecting patterns, and wherein the patterns can include time-based or frequency-based patterns associated with the user-generated content data streams; based at least in part on the targeting data obtained, selecting electronic advertisements for serving to targeted electronic device users; and serving the selected electronic advertisements to the targeted electronic device users, the serving including causing an advertisement serving system to initiate or modify an automated advertising campaign that includes the selected electronic advertisements. 9. The method of claim 1 , wherein the sampling comprises intercepting sample data but not intercepting non-sample data, and wherein the sampling comprises intercepting sample data from a plurality of data modes, wherein the data modes may comprise any of voice, audio, video, gaming, social network or blogging. | 0.5 |
9,196,075 | 12 | 13 | 12. A system for animating a computer-generated display component, comprising: a processor; and a memory device containing computer executable instructions that when executed by the processor provide: an animation engine operative to enable animation of computer-generated display components displayed on a computer-enabled display surface; the animation engine comprising: a user interface (UI) thread operative to schedule animations on display layers in response to property changes on the display layers; a compositor thread operative to receive from the UI thread display layers with property changes for generating an animation scheduling communication, and to flatten all display layers without property changes into a single non-animating display layer; and a rendering thread operative to receive the animation scheduling communication from the compositor thread for rendering display components associated with the display layers according to the property changes on the associated display layers. | 12. A system for animating a computer-generated display component, comprising: a processor; and a memory device containing computer executable instructions that when executed by the processor provide: an animation engine operative to enable animation of computer-generated display components displayed on a computer-enabled display surface; the animation engine comprising: a user interface (UI) thread operative to schedule animations on display layers in response to property changes on the display layers; a compositor thread operative to receive from the UI thread display layers with property changes for generating an animation scheduling communication, and to flatten all display layers without property changes into a single non-animating display layer; and a rendering thread operative to receive the animation scheduling communication from the compositor thread for rendering display components associated with the display layers according to the property changes on the associated display layers. 13. The system of claim 12 , wherein the UI thread is further operative to: create the display layers onto which the display components are rendered; add display components onto associated display layers; apply one or more animation behaviors to the associated display layers; and change animation properties on the associated display layers for scheduling animations. | 0.5 |
7,503,012 | 1 | 6 | 1. A method of automatically invoking a program or system function on a computer system comprising the steps of: receiving a user-selected first insertion point or replacement area within a first user interface to a destination computer file; subsequent to receiving said first insertion point within a destination file, providing a second user interface to content of a source computer file upon user command; subsequent to providing said second user interface to said source file, responsive to a user highlighting text within said second user interface of an application program on a computer display, automatically copying said highlighted text from said application program to a clipboard buffer, wherein said application program comprises an application program selected from a group of a word processor, a spreadsheet, a contact management utility, an electronic address book, an electronic calendar, an email client, a presentation program, a financial program, and a bookkeeping program; searching a plurality of auto-trigger rules for a rule which correlates to said highlighted text copied to said clipboard; and upon finding a correlating rule, invoking one or more programs or system functions according to said found rule without need to modify or change said application program. | 1. A method of automatically invoking a program or system function on a computer system comprising the steps of: receiving a user-selected first insertion point or replacement area within a first user interface to a destination computer file; subsequent to receiving said first insertion point within a destination file, providing a second user interface to content of a source computer file upon user command; subsequent to providing said second user interface to said source file, responsive to a user highlighting text within said second user interface of an application program on a computer display, automatically copying said highlighted text from said application program to a clipboard buffer, wherein said application program comprises an application program selected from a group of a word processor, a spreadsheet, a contact management utility, an electronic address book, an electronic calendar, an email client, a presentation program, a financial program, and a bookkeeping program; searching a plurality of auto-trigger rules for a rule which correlates to said highlighted text copied to said clipboard; and upon finding a correlating rule, invoking one or more programs or system functions according to said found rule without need to modify or change said application program. 6. The method as set forth in claim 1 further comprising the steps of: categorizing said information items in one or more user-selected categories; and including a category criteria in said auto-trigger rules as a condition for matching a highlighting event. | 0.715859 |
7,703,015 | 3 | 4 | 3. The method of claim 2 , wherein the specific component is a tag within the page-document. | 3. The method of claim 2 , wherein the specific component is a tag within the page-document. 4. The method of claim 3 , wherein the writer-function is a function of a class that is written in an object-oriented programming language. | 0.5 |
7,684,974 | 3 | 4 | 3. The system of claim 1 , wherein an idea distance comprises a distance between idea positions. | 3. The system of claim 1 , wherein an idea distance comprises a distance between idea positions. 4. The system of claim 3 , wherein an idea position comprises a beginning of the input text. | 0.5 |
9,183,511 | 14 | 15 | 14. The computer system of claim 9 , wherein the question answering system generates two or more structured queries, and these are ranked using one or more ranking operations. | 14. The computer system of claim 9 , wherein the question answering system generates two or more structured queries, and these are ranked using one or more ranking operations. 15. The computer system of claim 14 , wherein the ranking of the structured queries is based on ranking score calculated for each structured query based on one or more of: (a) popularity of associated templates surfaces; (b) popularity of associated entity surfaces; (c) probability of applicable relation paths corresponding to the templates; and (d) depth of the nesting structured queries. | 0.5 |
7,818,179 | 27 | 28 | 27. The method of claim 21 , wherein alerting the speaker comprises providing a tactile alert signal. | 27. The method of claim 21 , wherein alerting the speaker comprises providing a tactile alert signal. 28. The method of claim 27 , wherein the tactile alert signal comprises a vibration. | 0.5 |
8,447,588 | 1 | 6 | 1. A computer implemented method, comprising: recording in a memory input data having delimited strings; recording in the memory a region-matching transducer defining one or more patterns of one or more sequences of delimited strings, with at least one of the patterns defined in the region-matching transducer having an arrangement of a plurality of class-matching networks; the plurality of class-matching networks defining a combination of two or more entity classes from one or both of part-of-speech classes and application-specific classes; the region-matching transducer (i) having, for each of the one or more patterns, an arc that leads from a penultimate state with a transition label that identifies the entity class of the pattern, and (ii) sharing states between patterns leading to a penultimate state when segments of delimited strings making up two or more patterns overlap; applying the region-matching transducer recorded in the memory to the input data with an apply-stage replacement method, which apply-stage replacement method follows a longest match principle for identifying one or more patterns in the region-matching transducer that match one or more sequences of delimited strings in the input data; at least one of the matching sequences of delimited strings satisfying at least one pattern in the region-matching transducer defined by an arrangement of a plurality of class-matching networks, wherein the input data is not labeled with morphological tags when applying the region-matching transducer to the input data; and recording in the memory, in response to said applying, the one or more sequences of delimited strings in the input data matching the one or more patterns in the region-matching transducer. | 1. A computer implemented method, comprising: recording in a memory input data having delimited strings; recording in the memory a region-matching transducer defining one or more patterns of one or more sequences of delimited strings, with at least one of the patterns defined in the region-matching transducer having an arrangement of a plurality of class-matching networks; the plurality of class-matching networks defining a combination of two or more entity classes from one or both of part-of-speech classes and application-specific classes; the region-matching transducer (i) having, for each of the one or more patterns, an arc that leads from a penultimate state with a transition label that identifies the entity class of the pattern, and (ii) sharing states between patterns leading to a penultimate state when segments of delimited strings making up two or more patterns overlap; applying the region-matching transducer recorded in the memory to the input data with an apply-stage replacement method, which apply-stage replacement method follows a longest match principle for identifying one or more patterns in the region-matching transducer that match one or more sequences of delimited strings in the input data; at least one of the matching sequences of delimited strings satisfying at least one pattern in the region-matching transducer defined by an arrangement of a plurality of class-matching networks, wherein the input data is not labeled with morphological tags when applying the region-matching transducer to the input data; and recording in the memory, in response to said applying, the one or more sequences of delimited strings in the input data matching the one or more patterns in the region-matching transducer. 6. The method according to claim 1 , further comprising producing one of the plurality of class-matching networks by retaining one part-of-speech for each word forming part of a morphological-analyzing network. | 0.660194 |
9,008,416 | 12 | 14 | 12. A computer-implemented method as in claim 11 , wherein the steps of providing one or more goals, receiving from the first plurality of untrained providers images created in response to the step of providing one or more goals, sending to a second plurality of untrained providers requests to rate, and receiving ratings of the second plurality of untrained providers are performed by a computer-based system over a network coupling the computer-based system to provider machines of the providers of the first and second pluralities of untrained providers. | 12. A computer-implemented method as in claim 11 , wherein the steps of providing one or more goals, receiving from the first plurality of untrained providers images created in response to the step of providing one or more goals, sending to a second plurality of untrained providers requests to rate, and receiving ratings of the second plurality of untrained providers are performed by a computer-based system over a network coupling the computer-based system to provider machines of the providers of the first and second pluralities of untrained providers. 14. A computer-implemented method as in claim 12 , wherein the step of providing one or more goals comprises sending one or more images over the network from the computer-based system to the provider machines of the providers of the first plurality of untrained providers. | 0.646753 |
9,135,662 | 19 | 20 | 19. A method for communicating information, the method comprising: providing a data processor with a plurality of predetermined message templates stored in a database; providing and/or receiving with the data processor relevant data extracted from a data broadcast; the data processor automatically selecting a corresponding message template from the plurality of predetermined message templates for the extracted relevant data; the data processor automatically ranking the extracted relevant data with a number and/or letter for each of a plurality of predetermined categories; the data processor automatically populating the selected corresponding message template with the extracted relevant data to create an output data message; the data processor automatically associating a graphic indicator comprising a color and a shape to the ranking; the data processor automatically displaying the ranking with the associated graphic indicator within a corresponding one of the data output messages; and the data processor automatically delivering the output data message to a user device. | 19. A method for communicating information, the method comprising: providing a data processor with a plurality of predetermined message templates stored in a database; providing and/or receiving with the data processor relevant data extracted from a data broadcast; the data processor automatically selecting a corresponding message template from the plurality of predetermined message templates for the extracted relevant data; the data processor automatically ranking the extracted relevant data with a number and/or letter for each of a plurality of predetermined categories; the data processor automatically populating the selected corresponding message template with the extracted relevant data to create an output data message; the data processor automatically associating a graphic indicator comprising a color and a shape to the ranking; the data processor automatically displaying the ranking with the associated graphic indicator within a corresponding one of the data output messages; and the data processor automatically delivering the output data message to a user device. 20. The method according to claim 19 , wherein the extracted relevant data comprises structured data including textual and numerical data of each of financial news, financial news event analytics data, and/or trading exchange market data, and the graphic indicator is one of a plurality of predetermined market ranking indicators. | 0.5 |
8,584,226 | 1 | 25 | 1. A method for a geographic country of origin filter of information transmitting on a network: a) a network object on which the method is embodied, which extracts a network address from Internet traffic routed or collected by said network object; and performs at least one data lookup operation to obtain country of origin geographic information pertaining to said Internet network address; b) configuring said geographic country of origin filter by: Sending or receiving information used to generate a set of persistent geographic country of origin associations comprising a plurality of Internet address blocks; Performing at least one data processing operating to associate a geographic country of origin location pertaining to each block; and Generating at least one geographic country of origin security assertion wherein a device action is defined for at least one geographic country of origin association wherein the device action is triggered for any Internet address belonging to a defined network address block having an estimated country of origin geographic location, wherein the device action either: Allows Internet traffic to be sent or received from said Internet address to the desired destination; Disallows Internet traffic to be sent or received from said Internet address to the desired destination; or Mows Internet traffic to be sent or received from said Internet address to an undesired destination determined by said geographic filter; c) Optimizing said geographic country of origin information pertaining to Internet network addresses in accordance with at least one algorithm, wherein an algorithm is applied to the plurality of geographic country of origin associations between IP address blocks and geographic country of origin locations. | 1. A method for a geographic country of origin filter of information transmitting on a network: a) a network object on which the method is embodied, which extracts a network address from Internet traffic routed or collected by said network object; and performs at least one data lookup operation to obtain country of origin geographic information pertaining to said Internet network address; b) configuring said geographic country of origin filter by: Sending or receiving information used to generate a set of persistent geographic country of origin associations comprising a plurality of Internet address blocks; Performing at least one data processing operating to associate a geographic country of origin location pertaining to each block; and Generating at least one geographic country of origin security assertion wherein a device action is defined for at least one geographic country of origin association wherein the device action is triggered for any Internet address belonging to a defined network address block having an estimated country of origin geographic location, wherein the device action either: Allows Internet traffic to be sent or received from said Internet address to the desired destination; Disallows Internet traffic to be sent or received from said Internet address to the desired destination; or Mows Internet traffic to be sent or received from said Internet address to an undesired destination determined by said geographic filter; c) Optimizing said geographic country of origin information pertaining to Internet network addresses in accordance with at least one algorithm, wherein an algorithm is applied to the plurality of geographic country of origin associations between IP address blocks and geographic country of origin locations. 25. The method of claim 1 , wherein said IP addresses are converted into or out of CIDR (Classless Inter-Domain Routing) notation. | 0.80826 |
7,765,469 | 1 | 9 | 1. A system for resolving variable information (VI) documents comprising: I/O components for receiving a request including a document having data and a dynamic reference and a request to resolve the document, wherein the dynamic reference indirectly references content to be integrated into the document with the data, wherein the indirect reference references by describing at least one characteristic of the content, and for communicating with a plurality of data sources; at least one server at least one tangible processor; a series of programmable instructions executable by the at least one processor for processing the request comprising: a mapping module for mapping between respective namespaces and schemas used by the plurality of data sources and a namespace and schema used by the dynamic reference; a query handler for: comparing subject matter of content available from the plurality of data sources and subject matter of the content described by the indirect reference of the dynamic reference; selecting at least one data source from the plurality of data sources to query in accordance with the comparison; generating at least one query in accordance with the dynamic reference and the mapping; querying the selected at least one data source using the generated at least one query; and an output handler for integrating data received in response to the querying with the document in order to generate at least one resolved document that has the data originally in the document and data received in response to the querying. | 1. A system for resolving variable information (VI) documents comprising: I/O components for receiving a request including a document having data and a dynamic reference and a request to resolve the document, wherein the dynamic reference indirectly references content to be integrated into the document with the data, wherein the indirect reference references by describing at least one characteristic of the content, and for communicating with a plurality of data sources; at least one server at least one tangible processor; a series of programmable instructions executable by the at least one processor for processing the request comprising: a mapping module for mapping between respective namespaces and schemas used by the plurality of data sources and a namespace and schema used by the dynamic reference; a query handler for: comparing subject matter of content available from the plurality of data sources and subject matter of the content described by the indirect reference of the dynamic reference; selecting at least one data source from the plurality of data sources to query in accordance with the comparison; generating at least one query in accordance with the dynamic reference and the mapping; querying the selected at least one data source using the generated at least one query; and an output handler for integrating data received in response to the querying with the document in order to generate at least one resolved document that has the data originally in the document and data received in response to the querying. 9. The system according to claim 1 , wherein the VI request is a document template written in XML. | 0.916808 |
7,970,599 | 1 | 4 | 1. A computer-implemented method comprising: extracting a text string and context information for the text string using a processor, wherein the extracting extracts the text string and the context information for the text string from an application to be translated, the text string is to be translated, the context information for the text string is configured to identify a location of the text string in the application to be translated, and the context information comprises a plurality of identifiers; searching an application archive for an existing translation of the text string, using the processor, wherein the searching is performed using a subset of the identifiers, the subset of identifiers is a plurality of the plurality of identifiers of the context information for the text string, the searching for the existing translation is limited using at least one identifier in the subset of identifiers, the searching results in a set of translations, each translation in the set of translations matches at least one identifier from the subset of identifiers, and the set of translations comprises the existing translation; and selecting the existing translation from the set of translations using the processor, wherein the existing translation is selected from the set of translations as the translation that matches the most identifiers from the subset of identifiers. | 1. A computer-implemented method comprising: extracting a text string and context information for the text string using a processor, wherein the extracting extracts the text string and the context information for the text string from an application to be translated, the text string is to be translated, the context information for the text string is configured to identify a location of the text string in the application to be translated, and the context information comprises a plurality of identifiers; searching an application archive for an existing translation of the text string, using the processor, wherein the searching is performed using a subset of the identifiers, the subset of identifiers is a plurality of the plurality of identifiers of the context information for the text string, the searching for the existing translation is limited using at least one identifier in the subset of identifiers, the searching results in a set of translations, each translation in the set of translations matches at least one identifier from the subset of identifiers, and the set of translations comprises the existing translation; and selecting the existing translation from the set of translations using the processor, wherein the existing translation is selected from the set of translations as the translation that matches the most identifiers from the subset of identifiers. 4. The computer-implemented method of claim 1 , further comprising: sending the existing translation to a validation process using the processor; and linking the text string with the existing translation, using the processor, if the validation process validates the existing translation. | 0.5 |
8,676,802 | 21 | 22 | 21. The method of claim 12 , the method further comprising mapping each of the first set of retrieved documents to at least one of the clusters provided to the user. | 21. The method of claim 12 , the method further comprising mapping each of the first set of retrieved documents to at least one of the clusters provided to the user. 22. The method of claim 21 , wherein the mapping comprises at least one of: match-any, match-all, or match-partial. | 0.5 |
9,292,658 | 1 | 2 | 1. A method of providing a confidence-estimation-based inference, the method comprising: receiving a query concerning a patient from a user; accessing an electronic health record (EHR) for the patient, the EHR including a first component regarding the patient; querying the user, using a conversational interface, for a second component regarding the patient, the second component being in a natural language information form; receiving the second component regarding the patient in response to the query; calculating a first probability density function using the first component, and a second probability density function using the second component; combining the first and second probability density functions using a Gaussian mixture model; calculating at least one conditional probability table using the Gaussian mixture model; and providing the confidence-estimation-based inference based on the at least one conditional probability table. | 1. A method of providing a confidence-estimation-based inference, the method comprising: receiving a query concerning a patient from a user; accessing an electronic health record (EHR) for the patient, the EHR including a first component regarding the patient; querying the user, using a conversational interface, for a second component regarding the patient, the second component being in a natural language information form; receiving the second component regarding the patient in response to the query; calculating a first probability density function using the first component, and a second probability density function using the second component; combining the first and second probability density functions using a Gaussian mixture model; calculating at least one conditional probability table using the Gaussian mixture model; and providing the confidence-estimation-based inference based on the at least one conditional probability table. 2. The method of claim 1 , wherein the inference is one of a medical diagnosis or a medical prognosis. | 0.943396 |
7,706,780 | 11 | 12 | 11. An apparatus comprising: a user interface, a processor for mobile communication, an application run by said processor, wherein an item is generated in said application, and a notification text is associated with said item, a text-to-speech generator for generating synthetic speech corresponding to said notification text; a call generator for generating a call to a telephone; and an output for rendering said synthetic speech through said call. | 11. An apparatus comprising: a user interface, a processor for mobile communication, an application run by said processor, wherein an item is generated in said application, and a notification text is associated with said item, a text-to-speech generator for generating synthetic speech corresponding to said notification text; a call generator for generating a call to a telephone; and an output for rendering said synthetic speech through said call. 12. The apparatus according to claim 11 , comprising said telephone, and said call is a simulated call generated in said apparatus through said user interface. | 0.710909 |
8,739,031 | 1 | 5 | 1. A method comprising: receiving text, wherein a portion of the text comprises an abbreviation; associating a sender of the text with one of a plurality of groups, to yield a sender group; associating a recipient of the text with one of the plurality of groups, to yield a recipient group; and upon determining a difference in the sender and the recipient group, wherein the different indicates distinct cultures of the sender and the recipient: expanding, via a processor, the abbreviation based on the distinct cultures, to yield expanded text; transmitting a message to the recipient which comprises the abbreviation and the expanded text; modifying, via the processor, a display presented to the sender in which the expanded text is added to the text having the abbreviations; and presenting a first advertisement to the sender based on the text and the sender group, wherein the first advertisement is distinct from a second advertisement presented to the recipient. | 1. A method comprising: receiving text, wherein a portion of the text comprises an abbreviation; associating a sender of the text with one of a plurality of groups, to yield a sender group; associating a recipient of the text with one of the plurality of groups, to yield a recipient group; and upon determining a difference in the sender and the recipient group, wherein the different indicates distinct cultures of the sender and the recipient: expanding, via a processor, the abbreviation based on the distinct cultures, to yield expanded text; transmitting a message to the recipient which comprises the abbreviation and the expanded text; modifying, via the processor, a display presented to the sender in which the expanded text is added to the text having the abbreviations; and presenting a first advertisement to the sender based on the text and the sender group, wherein the first advertisement is distinct from a second advertisement presented to the recipient. 5. The method of claim 1 , wherein expanding the abbreviation is sender-selectable. | 0.730519 |
9,318,103 | 1 | 11 | 1. An automatic speech recognition system for recognizing a user voice command in a noisy environment, comprising: matching means for matching elements retrieved from speech units forming the command with templates stored in a template library; processing means for determining a sequence of templates that minimizes a distance between the elements and the templates, wherein the templates are posterior templates, the elements retrieved from the speech units are posterior vectors, and the posterior templates and the posterior vectors are generated with a MultiLayer Perceptron; calculating means for automatically selecting a subset of the posterior templates, the selection of the subset of the posterior templates including: (i) determining Gabriel or relative neighbors of the selected subset of the posterior templates by calculating a matrix of distances between all of the posterior templates, (ii) visiting each template of the subset of posterior templates, (iii) marking a template of the subset of the posterior templates if all of its neighbours are of a same phone class as the template; and (iv) deleting all marked posterior templates, wherein the remaining posterior templates constitute the selected subset of the posterior templates; and a dynamic time warping (DTW) decoder for matching the posterior vectors with the selected subset of posterior templates, wherein the DTW decoder receives input, the input comprising a sequence of posterior vectors to be recognized, a posterior template library, a dictionary and optionally a grammar, and the DTW decoder outputs one or more sequences of recognized words, time information and confidence measures. | 1. An automatic speech recognition system for recognizing a user voice command in a noisy environment, comprising: matching means for matching elements retrieved from speech units forming the command with templates stored in a template library; processing means for determining a sequence of templates that minimizes a distance between the elements and the templates, wherein the templates are posterior templates, the elements retrieved from the speech units are posterior vectors, and the posterior templates and the posterior vectors are generated with a MultiLayer Perceptron; calculating means for automatically selecting a subset of the posterior templates, the selection of the subset of the posterior templates including: (i) determining Gabriel or relative neighbors of the selected subset of the posterior templates by calculating a matrix of distances between all of the posterior templates, (ii) visiting each template of the subset of posterior templates, (iii) marking a template of the subset of the posterior templates if all of its neighbours are of a same phone class as the template; and (iv) deleting all marked posterior templates, wherein the remaining posterior templates constitute the selected subset of the posterior templates; and a dynamic time warping (DTW) decoder for matching the posterior vectors with the selected subset of posterior templates, wherein the DTW decoder receives input, the input comprising a sequence of posterior vectors to be recognized, a posterior template library, a dictionary and optionally a grammar, and the DTW decoder outputs one or more sequences of recognized words, time information and confidence measures. 11. The system of claim 1 , further comprising voice activity detector means that can be selected and de-selected by the user. | 0.66129 |
8,285,047 | 6 | 7 | 6. A system for automatically identifying and associating text in a scanned document, the system comprising: a scanner for scanning a first physical document having one or more selected portions of text that are manually marked into image data, the scanner configured to form a first scanned document of image data corresponding to the first physical document and configured to scan at least a second physical document to form at least a second scanned document of image data corresponding to the at least second physical document; a module for recognizing the one or more selected portions of manually marked text in the image data of the first scanned document; a module for identifying a location of the recognized one or more selected portions of manually marked text in the image data of the first scanned document; a module for storing the location of the recognized one or more selected portions of manually marked text of the first scanned document, wherein the module for identifying the location of the recognized one or more selected portions of manually marked text in the first scanned document is configured to identify a corresponding location in the at least second scanned document and configured to recognize text in the corresponding location of the at least second scanned document, and wherein the system further comprises: a module for generating text in response to recognizing the text in the corresponding location of the at least second scanned document, a module for assigning the image data of the at least second scanned document a name using the generated text before storing the second scanned document, and a module for storing the image data for the at least second scanned document with the assigned name. | 6. A system for automatically identifying and associating text in a scanned document, the system comprising: a scanner for scanning a first physical document having one or more selected portions of text that are manually marked into image data, the scanner configured to form a first scanned document of image data corresponding to the first physical document and configured to scan at least a second physical document to form at least a second scanned document of image data corresponding to the at least second physical document; a module for recognizing the one or more selected portions of manually marked text in the image data of the first scanned document; a module for identifying a location of the recognized one or more selected portions of manually marked text in the image data of the first scanned document; a module for storing the location of the recognized one or more selected portions of manually marked text of the first scanned document, wherein the module for identifying the location of the recognized one or more selected portions of manually marked text in the first scanned document is configured to identify a corresponding location in the at least second scanned document and configured to recognize text in the corresponding location of the at least second scanned document, and wherein the system further comprises: a module for generating text in response to recognizing the text in the corresponding location of the at least second scanned document, a module for assigning the image data of the at least second scanned document a name using the generated text before storing the second scanned document, and a module for storing the image data for the at least second scanned document with the assigned name. 7. A system according to claim 6 , further comprising: a module for populating a field associated with the image data of the second scanned document using the recognized text in the corresponding location of the at least second document. | 0.5 |
9,460,149 | 15 | 17 | 15. The user interface of claim 12 , further comprising identifying a plurality of input-imprecision traits between the entered-attribute and the resolved-attribute, for each of the plurality of search queries, wherein the plurality of input-imprecision traits are specific systematic traits. | 15. The user interface of claim 12 , further comprising identifying a plurality of input-imprecision traits between the entered-attribute and the resolved-attribute, for each of the plurality of search queries, wherein the plurality of input-imprecision traits are specific systematic traits. 17. The user interface of claim 15 , wherein the input-precision score is one of a plurality of factors associated with the accuracy profile. | 0.786364 |
8,738,630 | 10 | 13 | 10. The method of claim 8 , wherein the providing a web page to a client includes: configuring the web page to provide a user selectable annotation content format, the user selectable annotation content format being one of either a question format or an answer format. | 10. The method of claim 8 , wherein the providing a web page to a client includes: configuring the web page to provide a user selectable annotation content format, the user selectable annotation content format being one of either a question format or an answer format. 13. The method of claim 10 , wherein the providing a web page to a client further includes: configuring the web page to provide, in conjunction with the answer format, a category selection format that is selectable by the user, wherein the user selects a category of a product corresponding to an answer submitted by the user. | 0.745313 |
9,798,813 | 8 | 10 | 8. A system that resolves uncoordinated person objects and person-related objects in a database, the system including: a processor, memory coupled to the processor, and program instructions loaded in the memory that, when executed on the processor, cause the processor to carry out steps of: receiving a query directed to a first person for objects stored in a database, in which multiple users in multiple departments created uncoordinated person objects that do not share a common key, and in which the person objects are linked to person-related objects; identifying a plurality of candidate person objects responsive to the query for the first person, wherein the identified candidate person objects share at least some matching data; transmitting data for display to a user that lists the candidate person objects; receiving data from the user specifying linking among the candidate person objects; linking the specified candidate person objects to a coordinating customer relations management (CRM) object using a system-generated unique person identifier as a common key and preserving linkage to respective person-related objects associated with the specified candidate person objects, thereby creating a first person-related set; identifying one of the person objects in the first person-related set as a lead active person object; receiving a subsequent request for CRM data related to the first person, retrieving the coordinating CRM object and using the links from the coordinating CRM object to at least some coordinated person objects in the first person-related set; and transmitting responsive data for display that lists data from the coordinated person objects, featuring data from the lead active person object. | 8. A system that resolves uncoordinated person objects and person-related objects in a database, the system including: a processor, memory coupled to the processor, and program instructions loaded in the memory that, when executed on the processor, cause the processor to carry out steps of: receiving a query directed to a first person for objects stored in a database, in which multiple users in multiple departments created uncoordinated person objects that do not share a common key, and in which the person objects are linked to person-related objects; identifying a plurality of candidate person objects responsive to the query for the first person, wherein the identified candidate person objects share at least some matching data; transmitting data for display to a user that lists the candidate person objects; receiving data from the user specifying linking among the candidate person objects; linking the specified candidate person objects to a coordinating customer relations management (CRM) object using a system-generated unique person identifier as a common key and preserving linkage to respective person-related objects associated with the specified candidate person objects, thereby creating a first person-related set; identifying one of the person objects in the first person-related set as a lead active person object; receiving a subsequent request for CRM data related to the first person, retrieving the coordinating CRM object and using the links from the coordinating CRM object to at least some coordinated person objects in the first person-related set; and transmitting responsive data for display that lists data from the coordinated person objects, featuring data from the lead active person object. 10. The system of claim 8 , wherein the lead active person object is identified as an oldest person object in the first person-related set. | 0.673709 |
9,286,189 | 1 | 7 | 1. A computer-implemented method including executing, by at least one processor, instructions recorded on a non-transitory computer-readable storage medium, the method comprising: identifying, by the at least one processor, a template from a set of templates, each template included in the set of templates including respective meta-data describing a configuration for a corresponding computing services platform, and the template being associated with a translation program that translates the template into a service blueprint for a computing services platform associated with the service blueprint; verifying the translation program associated with the template, the verifying comprising: applying a first fitness function to the translation program; determining, by the first fitness function, that the translation program is valid; based on the first fitness function determining that the translation program is valid, applying a second fitness function to the translation program; and determining, by the second fitness function, that the translation program is valid; and based on the second fitness function determining that the translation program is valid and based on the first fitness function determining that the translation program is valid, adding the translation program to a set of validated translation programs for use in translating the set of templates. | 1. A computer-implemented method including executing, by at least one processor, instructions recorded on a non-transitory computer-readable storage medium, the method comprising: identifying, by the at least one processor, a template from a set of templates, each template included in the set of templates including respective meta-data describing a configuration for a corresponding computing services platform, and the template being associated with a translation program that translates the template into a service blueprint for a computing services platform associated with the service blueprint; verifying the translation program associated with the template, the verifying comprising: applying a first fitness function to the translation program; determining, by the first fitness function, that the translation program is valid; based on the first fitness function determining that the translation program is valid, applying a second fitness function to the translation program; and determining, by the second fitness function, that the translation program is valid; and based on the second fitness function determining that the translation program is valid and based on the first fitness function determining that the translation program is valid, adding the translation program to a set of validated translation programs for use in translating the set of templates. 7. The computer-implemented method of claim 1 , further comprising: determining, by the first fitness function, that the translation program is not valid; and based on the first fitness function determining that the translation program is not valid, discarding the translation program, the discarding not adding the translation program to a set of validated translation programs for use in translating the set of templates. | 0.681955 |
9,383,977 | 11 | 13 | 11. A computer system comprising: one or more computer processors; and a non-transitory computer readable storage medium comprising instructions that when executed by the one or more computer processors implement a method comprising: extracting, by a compiler description generator, information from an architecture description describing an architecture of an application specific instruction set processor (ASIP); receiving, by the compiler description generator via a source different than the architecture description, definitions for a plurality of abstract elements of a compiler that have no direct representative in the architecture description, the abstract elements comprising a non-terminal representing a data path in common with a plurality of compiler instructions; extracting, by the compiler description generator, a mapping of compiler rules to instructions included in the architecture description; and automatically generating, by the compiler description generator, a compiler description of the compiler for the architecture of the ASIP based on the extracted information, the received definitions for the plurality of abstract elements, and the extracted mapping, wherein a compiler generator generates the compiler based on the compiler description. | 11. A computer system comprising: one or more computer processors; and a non-transitory computer readable storage medium comprising instructions that when executed by the one or more computer processors implement a method comprising: extracting, by a compiler description generator, information from an architecture description describing an architecture of an application specific instruction set processor (ASIP); receiving, by the compiler description generator via a source different than the architecture description, definitions for a plurality of abstract elements of a compiler that have no direct representative in the architecture description, the abstract elements comprising a non-terminal representing a data path in common with a plurality of compiler instructions; extracting, by the compiler description generator, a mapping of compiler rules to instructions included in the architecture description; and automatically generating, by the compiler description generator, a compiler description of the compiler for the architecture of the ASIP based on the extracted information, the received definitions for the plurality of abstract elements, and the extracted mapping, wherein a compiler generator generates the compiler based on the compiler description. 13. The computer system of claim 11 , wherein the architecture description comprises information organized in a hierarchical format. | 0.795031 |
8,234,561 | 47 | 49 | 47. The software product of claim 43 , wherein the determined characteristic of the current form field object comprises a determined field predictability of a form field to which the current form field object corresponds. | 47. The software product of claim 43 , wherein the determined characteristic of the current form field object comprises a determined field predictability of a form field to which the current form field object corresponds. 49. The software product of claim 47 , wherein the determined field predictability is determined based on a ratio of a number of past values entered in the form field and a number of past unique values entered in the form field. | 0.5 |
9,569,728 | 8 | 9 | 8. The method of claim 1 , further comprising: receiving, via the network, an indication that the third user has taken an action on the second web page. | 8. The method of claim 1 , further comprising: receiving, via the network, an indication that the third user has taken an action on the second web page. 9. The method of claim 8 , wherein the action comprises one of: viewing the second web page, ignoring the second web page, blacklisting the second web page, and requesting to save the second web page with another folder in the content repository. | 0.5 |
10,026,393 | 12 | 14 | 12. A computer-implemented method of converting text to speech, the method comprising: generate a response text and a response intent based on user input; receiving response text and an intent representative of intended meaning of the response text that can be conveyed by non-lexical cues; determining, on the one or more computing devices, an insertion point of a non-lexical cue, in the response text, based on the intent; inserting by the one or more computing devices a non-lexical cue at the insertion point within the response text to generate augmented text; and providing the augmented text to a speech synthesizer to synthesize speech from the augmented text using speech units associated with the response text and the inserted response intent. | 12. A computer-implemented method of converting text to speech, the method comprising: generate a response text and a response intent based on user input; receiving response text and an intent representative of intended meaning of the response text that can be conveyed by non-lexical cues; determining, on the one or more computing devices, an insertion point of a non-lexical cue, in the response text, based on the intent; inserting by the one or more computing devices a non-lexical cue at the insertion point within the response text to generate augmented text; and providing the augmented text to a speech synthesizer to synthesize speech from the augmented text using speech units associated with the response text and the inserted response intent. 14. The method of claim 12 , wherein the non-lexical cue inserted at the insertion point is parasitic on at least a portion of a word within the response text. | 0.722997 |
7,996,227 | 1 | 6 | 1. A method of inserting a description of an image into an audio recording, comprising: interpreting, using a computer device, an image, including: applying a template to the image to extract file content; constructing a logical structure from the image; populating the logical structure with the extracted file content; and producing a word description of the image including at least one image keyword from the interpreted image; parsing, using the computer device, an audio recording into a plurality of audio clips; producing a transcription of each audio clip; extracting a plurality of noun phrases from the transcription; calculating an importance value for each noun phrase and identifying at least one audio keyword based upon the importance value; calculating, using the computer device, a similarity distance between the at least one image keyword and the at least one audio keyword of each audio clip; and selecting, using the computer device, the audio clip transcription having a shortest similarity distance to the at least one image keyword as a location to insert the word description of the image. | 1. A method of inserting a description of an image into an audio recording, comprising: interpreting, using a computer device, an image, including: applying a template to the image to extract file content; constructing a logical structure from the image; populating the logical structure with the extracted file content; and producing a word description of the image including at least one image keyword from the interpreted image; parsing, using the computer device, an audio recording into a plurality of audio clips; producing a transcription of each audio clip; extracting a plurality of noun phrases from the transcription; calculating an importance value for each noun phrase and identifying at least one audio keyword based upon the importance value; calculating, using the computer device, a similarity distance between the at least one image keyword and the at least one audio keyword of each audio clip; and selecting, using the computer device, the audio clip transcription having a shortest similarity distance to the at least one image keyword as a location to insert the word description of the image. 6. The method of claim 1 , further comprising: calculating the similarity distance between the image and an audio clip by calculating the similarity distance between at least one image keyword of an image and the at least one audio keyword of an audio clip. | 0.5 |
8,306,977 | 20 | 21 | 20. A machine-readable medium comprising instructions stored therein, which when executed by a machine, cause the machine to perform operations comprising: detecting a user request to tag an item, while the item is being displayed to the user; identifying a content identifier corresponding to the item; selecting a set of user-generated labels from a plurality of user-generated labels corresponding to the content identifier comprising selecting at least one of the set of user-generated labels from the plurality of user-generated labels based on a fitness value of the at least one user-generated label, wherein the set of user-generated labels comprises two or more user-generated labels of the plurality of user-generated labels, each of the plurality of user-generated labels representing a sentiment regarding the item, the selecting operation further comprising analyzing the sentiment represented by one or more of the user-generated labels of the set of user-generated labels based on the relation of the sentiment represented by the user-generated label to a pre-defined set of basic emotions; wherein the set of user-generated labels are selected to provide a full spectrum of sentiments regarding the item, such that at least two of the user-generated labels of the selected user-generated labels provide opposite sentiments from one another; identifying display information regarding the set of user-generated labels, the display information including one or more of size, color or location information for visually representing the set of user-generated labels; and providing the set of user-generated labels to be displayed to the user on a display area, wherein the set of user-generated labels is provided for display to the user according to the display information and wherein the display information for at least one user-generated label of the set of user-generated labels is different from at least another user-generated label of the set of user-generated labels. | 20. A machine-readable medium comprising instructions stored therein, which when executed by a machine, cause the machine to perform operations comprising: detecting a user request to tag an item, while the item is being displayed to the user; identifying a content identifier corresponding to the item; selecting a set of user-generated labels from a plurality of user-generated labels corresponding to the content identifier comprising selecting at least one of the set of user-generated labels from the plurality of user-generated labels based on a fitness value of the at least one user-generated label, wherein the set of user-generated labels comprises two or more user-generated labels of the plurality of user-generated labels, each of the plurality of user-generated labels representing a sentiment regarding the item, the selecting operation further comprising analyzing the sentiment represented by one or more of the user-generated labels of the set of user-generated labels based on the relation of the sentiment represented by the user-generated label to a pre-defined set of basic emotions; wherein the set of user-generated labels are selected to provide a full spectrum of sentiments regarding the item, such that at least two of the user-generated labels of the selected user-generated labels provide opposite sentiments from one another; identifying display information regarding the set of user-generated labels, the display information including one or more of size, color or location information for visually representing the set of user-generated labels; and providing the set of user-generated labels to be displayed to the user on a display area, wherein the set of user-generated labels is provided for display to the user according to the display information and wherein the display information for at least one user-generated label of the set of user-generated labels is different from at least another user-generated label of the set of user-generated labels. 21. The machine-readable medium of claim 20 , wherein the pre-defined set of basic emotions comprise the set of basic emotions as defined by Plutchik's psychoevolutionary theory of basic emotions. | 0.5 |
8,400,944 | 1 | 4 | 1. A system for displaying message-related relationships, comprising: an analysis module to analyze messages, comprising: an entity identification module to identify entities associated with each message, wherein the entities comprise senders and recipients of the messages; and a communication module to accumulate a number of messages communicated between each sender and each recipient; a social network generator to create a social network by connecting one or more of the senders and recipients via a link based on the number of messages communicated between that sender and that recipient; a semantic network generator to generate a semantic network comprising concepts of the messages; and a display module to simultaneously display the social network and the semantic network. | 1. A system for displaying message-related relationships, comprising: an analysis module to analyze messages, comprising: an entity identification module to identify entities associated with each message, wherein the entities comprise senders and recipients of the messages; and a communication module to accumulate a number of messages communicated between each sender and each recipient; a social network generator to create a social network by connecting one or more of the senders and recipients via a link based on the number of messages communicated between that sender and that recipient; a semantic network generator to generate a semantic network comprising concepts of the messages; and a display module to simultaneously display the social network and the semantic network. 4. A system according to claim 1 , further comprising: a reduction module to reduce the social network based on one or more of the concepts selected from the semantic network by a user. | 0.729532 |
9,582,554 | 18 | 19 | 18. The computer implemented system of claim 15 , wherein determining that the set of entries belong to the category comprises matching a subset of the set of entries with one of the plurality of entity tags. | 18. The computer implemented system of claim 15 , wherein determining that the set of entries belong to the category comprises matching a subset of the set of entries with one of the plurality of entity tags. 19. The computer implemented system of claim 18 , wherein the plurality of entity tags include a text field and matching the subset of the set of entries comprises comparing the plain text for each of the subset of entries with the text field of the plurality of entities. | 0.5 |
10,011,285 | 2 | 3 | 2. The autonomous vehicle pictorial language system of claim 1 , wherein the processing circuitry is further configured to display the plan sentence, receive a driver response sentence, determine if the driver sentence received does not match the plan sentence more than a predetermined number of times, change the first adverb of the plan sentence in response to the driver sentence not matching the plan sentence more than the predetermined number of times, change the noun of the plan sentence in response to the driver sentence not matching the plan sentence more than the predetermined number of times, and update the driver model in response to one or more changes to the first adverb and the noun. | 2. The autonomous vehicle pictorial language system of claim 1 , wherein the processing circuitry is further configured to display the plan sentence, receive a driver response sentence, determine if the driver sentence received does not match the plan sentence more than a predetermined number of times, change the first adverb of the plan sentence in response to the driver sentence not matching the plan sentence more than the predetermined number of times, change the noun of the plan sentence in response to the driver sentence not matching the plan sentence more than the predetermined number of times, and update the driver model in response to one or more changes to the first adverb and the noun. 3. The autonomous vehicle pictorial language system of claim 2 , wherein driver confirmation of the plan sentence causes the vehicle to execute a maneuver displayed by the plan sentence when the driver would otherwise execute the maneuver manually. | 0.5 |
8,577,907 | 1 | 7 | 1. A computer-implemented method comprising: receiving, by a search system, a search query; generating, by the search system, a potential substitute term that is related to a query term of the search query; identifying, by the search system, an original set of documents that are responsive to the search query; weighting each potential substitute term that appears in a document in the original set based on a prevalence of the potential substitute term in the original set of documents; producing a pruned set of terms whose weight satisfies a condition; determining that the potential substitute term is a member of the pruned set of terms; and in response to determining that the potential substitute term is a member of the pruned set of terms, modifying, by the search system, the search query to include the potential substitute term. | 1. A computer-implemented method comprising: receiving, by a search system, a search query; generating, by the search system, a potential substitute term that is related to a query term of the search query; identifying, by the search system, an original set of documents that are responsive to the search query; weighting each potential substitute term that appears in a document in the original set based on a prevalence of the potential substitute term in the original set of documents; producing a pruned set of terms whose weight satisfies a condition; determining that the potential substitute term is a member of the pruned set of terms; and in response to determining that the potential substitute term is a member of the pruned set of terms, modifying, by the search system, the search query to include the potential substitute term. 7. The method of claim 1 , wherein weighting each potential substitute term comprises using a number of times the potential substitute terms appears in the original set of documents to measure the prevalence of the substitute term. | 0.5 |
9,292,488 | 12 | 15 | 12. A system for processing a natural language message in a computerized system, comprising: a recording device that receives and stores a speech utterance in the computerized system, the utterance comprising a message portion and a communication portion, and storing the utterance in a system storage; a processor coupled to a memory storing instructions, the instructions which when executed cause the processor to perform: parsing the utterance using the computerized system to identify and separate the message portion and the communication portion; identifying communication parameters from the communication portion using the computerized system, the communication parameters including one or more destinations; wherein the communication parameters indicate that the message portion should be saved as a memo, and transmitting includes recording the message portion for future playback in the computerized system; and automatically transmitting the message portion from the storage to the destination as a voice message. | 12. A system for processing a natural language message in a computerized system, comprising: a recording device that receives and stores a speech utterance in the computerized system, the utterance comprising a message portion and a communication portion, and storing the utterance in a system storage; a processor coupled to a memory storing instructions, the instructions which when executed cause the processor to perform: parsing the utterance using the computerized system to identify and separate the message portion and the communication portion; identifying communication parameters from the communication portion using the computerized system, the communication parameters including one or more destinations; wherein the communication parameters indicate that the message portion should be saved as a memo, and transmitting includes recording the message portion for future playback in the computerized system; and automatically transmitting the message portion from the storage to the destination as a voice message. 15. The system of claim 12 , wherein the destination is a user account on a social networking website. | 0.68323 |
7,813,920 | 2 | 5 | 2. The method of claim 1 , wherein a recognizer generates the alternate list and applies post processing to the alternate list. | 2. The method of claim 1 , wherein a recognizer generates the alternate list and applies post processing to the alternate list. 5. The method of claim 2 , wherein the recognizer uses of one of the following statistical learning methodologies when post processing the alternate list: a neural network, a support vector machine, a Bayesian network, a simple linear regression network and a network using a maximum entropy classifier. | 0.5 |
8,918,736 | 10 | 20 | 10. A mobile electronic device, comprising: a display; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying a current set of characters in response to receiving a sequence of character entry commands, wherein the current set of characters includes a current sequence of words; receiving deletion commands that specify characters to sequentially delete from the current set of characters, wherein each respective deletion command deletes a respective character; in response to receiving the deletion commands that specify characters to delete from the current set of characters, deleting characters from the current set of characters, wherein the deleted characters include a plurality of adjacent words from the current sequence of words; and after deleting characters from the current set of characters in response to receiving the deletion commands: receiving one or more character entry commands that specify characters to add to the current set of characters; and displaying replay recommendations to be added to the current set of characters, wherein the replay recommendations include at least a subset of deleted words in the plurality of adjacent words from the deleted characters and are presented in a reverse sequential order relative to an order in which at least the subset of the deleted words in the plurality of adjacent words was deleted; receiving a first recommended word selection command that accepts a first recommended word in the replay recommendations; in response to receiving the first recommended word selection command that accepts the first recommended word in the replay recommendations: removing the first recommended word from the provided replay recommendations; and adding the first recommended word to the current set of characters. | 10. A mobile electronic device, comprising: a display; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying a current set of characters in response to receiving a sequence of character entry commands, wherein the current set of characters includes a current sequence of words; receiving deletion commands that specify characters to sequentially delete from the current set of characters, wherein each respective deletion command deletes a respective character; in response to receiving the deletion commands that specify characters to delete from the current set of characters, deleting characters from the current set of characters, wherein the deleted characters include a plurality of adjacent words from the current sequence of words; and after deleting characters from the current set of characters in response to receiving the deletion commands: receiving one or more character entry commands that specify characters to add to the current set of characters; and displaying replay recommendations to be added to the current set of characters, wherein the replay recommendations include at least a subset of deleted words in the plurality of adjacent words from the deleted characters and are presented in a reverse sequential order relative to an order in which at least the subset of the deleted words in the plurality of adjacent words was deleted; receiving a first recommended word selection command that accepts a first recommended word in the replay recommendations; in response to receiving the first recommended word selection command that accepts the first recommended word in the replay recommendations: removing the first recommended word from the provided replay recommendations; and adding the first recommended word to the current set of characters. 20. The device of claim 10 , wherein the deletion, character entry, and recommended word selection commands are provided using an interface that is configured for use with one finger. | 0.69702 |
8,155,962 | 9 | 14 | 9. A system for asynchronously processing natural language utterances, comprising: a speech unit connected to a computer device, wherein the speech unit is configured to receive a natural language utterance and convert the received natural language speech into an electronic signal; a speech recognition engine that operates on the computer device, wherein the speech recognition engine is configured to recognize one or more words in the electronic signal converted from the natural language utterance; a parser that further operates on the computer device, wherein the parser is configured to identify a request contained in the natural language utterance from the one or more recognized words and determine a context relating to the identified request; and a domain agent associated with the context relating to the identified request, wherein the domain agent further operates on the computer device and is configured to: submit a plurality of asynchronous queries created with the domain agent to a plurality of information sources, wherein the plurality of information sources include one or more local information sources and one or more network information sources; asynchronously evaluate results that the plurality of information sources return to the domain agent in response to the plurality of asynchronous queries; score the asynchronously evaluated results returned from the plurality of information sources until one or more of the asynchronously evaluated results have a score that satisfies a predetermined confidence level; extract a single best response to the request from the one or more of the asynchronously evaluated results having the score that satisfies the predetermined confidence level; and present the single best response to the request on the computer device. | 9. A system for asynchronously processing natural language utterances, comprising: a speech unit connected to a computer device, wherein the speech unit is configured to receive a natural language utterance and convert the received natural language speech into an electronic signal; a speech recognition engine that operates on the computer device, wherein the speech recognition engine is configured to recognize one or more words in the electronic signal converted from the natural language utterance; a parser that further operates on the computer device, wherein the parser is configured to identify a request contained in the natural language utterance from the one or more recognized words and determine a context relating to the identified request; and a domain agent associated with the context relating to the identified request, wherein the domain agent further operates on the computer device and is configured to: submit a plurality of asynchronous queries created with the domain agent to a plurality of information sources, wherein the plurality of information sources include one or more local information sources and one or more network information sources; asynchronously evaluate results that the plurality of information sources return to the domain agent in response to the plurality of asynchronous queries; score the asynchronously evaluated results returned from the plurality of information sources until one or more of the asynchronously evaluated results have a score that satisfies a predetermined confidence level; extract a single best response to the request from the one or more of the asynchronously evaluated results having the score that satisfies the predetermined confidence level; and present the single best response to the request on the computer device. 14. The system of claim 9 , wherein the domain agent is further configured to: request additional information relating to the identified request via the speech unit if none of the asynchronously evaluated results returned from the plurality of information sources has the score that satisfies the predetermined confidence level or an irresolvable ambiguity arises in formulating the single best response to the request; and submit one or more new asynchronous queries to one or more of the plurality of information sources in response to receiving the requested additional information relating to the identified request, wherein the domain agent is configured to create the one or more new asynchronous queries based on the received additional information. | 0.524528 |
7,509,345 | 14 | 27 | 14. The system of claim 12 further comprising: filtering the available clippings to present a subset of clippings that are associated with a category; and automatically associating a new clipping with the category upon receiving a request to persist a new clipping. | 14. The system of claim 12 further comprising: filtering the available clippings to present a subset of clippings that are associated with a category; and automatically associating a new clipping with the category upon receiving a request to persist a new clipping. 27. The method of claim 14 , wherein, upon association with the category, the new clipping inherits one or more portions of metadata corresponding to the category. | 0.5 |
6,079,047 | 5 | 7 | 5. In a computer operating on a specialized original native file format with a Disk File Header (DFH) for each file, a system for accessing a CD-ROM holding a first format Container (CD.backslash.FILE) with industry standard byte stream data files and Directory of a first format and converting said first format to individual second format files compatible for said specialized original native file format, said system comprising: (a) means for accessing said first format Container (21d)(CD.backslash.FILE) holding said byte stream files of first format; (b) means to execute a first interface program (MCP.sub.-- FILEWRAPPER, 36) which initiates an input read procedure (35i) to transfer said first format Container (21d, CD.backslash.FILE) to a second interface program (38); (c) means to execute said second interface program (MCP.sub.-- WRAPPER, 38) to re-create said first format Container (21d) into resultant multiple native second format files (MY/FILE/=(21). | 5. In a computer operating on a specialized original native file format with a Disk File Header (DFH) for each file, a system for accessing a CD-ROM holding a first format Container (CD.backslash.FILE) with industry standard byte stream data files and Directory of a first format and converting said first format to individual second format files compatible for said specialized original native file format, said system comprising: (a) means for accessing said first format Container (21d)(CD.backslash.FILE) holding said byte stream files of first format; (b) means to execute a first interface program (MCP.sub.-- FILEWRAPPER, 36) which initiates an input read procedure (35i) to transfer said first format Container (21d, CD.backslash.FILE) to a second interface program (38); (c) means to execute said second interface program (MCP.sub.-- WRAPPER, 38) to re-create said first format Container (21d) into resultant multiple native second format files (MY/FILE/=(21). 7. The system of claim 5 to wherein said second interface program (38) includes: (c1) means to verify each output file name and call said input Read procedure (35i) and verify option information for each data file in said first format Container (CD.backslash.FILE 21d); (c2) means to verify that each said data file in said first format Container is a "wrapped" file in said first byte stream format; (c3) means to call said input procedure (35i) to access the Disk File Header (DFH) of each data file of said wrapped file; (c4) means to verify the options selected and to verify the DFH information for said wrapped file. (c5) means to call an input procedure (35i) to complete the access of the DFH and DFH checksum for each said data file; (c6) means to calculate the running checksum located in local memory for each said data file; (c7) means for creating a new system Disk File Header as an output file for placement in local memory (18); (c8) means to use said input read procedure (35i) to read each input data file of said first format Container and then write an output file (MY/FILE 21) on disk (20, MYDISK); (c9) means to calculate the running checksum in local memory (18) for each row of each file being processed within said first format Container (CD.backslash.FILE); (c10) means to convert each input file of said first format Container (CD.backslash.FILE) to an output file of said second specialized format Container (MY/FILE/=) (21); (c11) means to obtain the stored checksum of the entire first format Container (CD.backslash.FILE, 21d) for comparison to the calculated running checksum that was set in local memory (18); (c12) means to exit the interface program (38) when the checksums match or to send an error signal if the checksums do not match. | 0.5 |
7,974,972 | 1 | 14 | 1. A method of providing records to a user, comprising: identifying a set of different languages from an interaction of a user with a server; automatically discerning a set of suspected geographical origins of the user from the interaction with the server; finding a best combination of a language and a suspected geographical origin from the sets of languages and origins; and using the best combination to guide retrieval of search results responsive to a query submitted to the server by the user, and to rank the search results. | 1. A method of providing records to a user, comprising: identifying a set of different languages from an interaction of a user with a server; automatically discerning a set of suspected geographical origins of the user from the interaction with the server; finding a best combination of a language and a suspected geographical origin from the sets of languages and origins; and using the best combination to guide retrieval of search results responsive to a query submitted to the server by the user, and to rank the search results. 14. The method of claim 1 , further comprising partitioning a records repository storing records from which the search results are retrieved. | 0.652709 |
7,840,409 | 8 | 10 | 8. The apparatus of claim 7 wherein sorting, by the VoiceXML interpreter, the plurality of recognition results in dependence upon the weight for each recognition result comprises sorting, by the VoiceXML interpreter, the plurality of recognition results in dependence upon the weight for each recognition result in accordance with a sorting attribute for the grammar defining a sorting scheme, the sorting attribute specified by the multimodal application using a VoiceXML <grammar> element. | 8. The apparatus of claim 7 wherein sorting, by the VoiceXML interpreter, the plurality of recognition results in dependence upon the weight for each recognition result comprises sorting, by the VoiceXML interpreter, the plurality of recognition results in dependence upon the weight for each recognition result in accordance with a sorting attribute for the grammar defining a sorting scheme, the sorting attribute specified by the multimodal application using a VoiceXML <grammar> element. 10. The apparatus of claim 8 wherein the sorting attribute specifies sorting the plurality of recognition results according to an ECMAScript script. | 0.579545 |
7,676,375 | 5 | 9 | 5. The method of claim 4 wherein each said relative value number is a measure of at least one characteristic intrinsic to the corresponding patent. | 5. The method of claim 4 wherein each said relative value number is a measure of at least one characteristic intrinsic to the corresponding patent. 9. The method of claim 5 wherein said at least one characteristic includes a number of claims. | 0.624 |
9,332,380 | 17 | 19 | 17. The one or more computer-readable media of claim 16 , wherein the acts further comprise obtaining geographic information associated with the user device, and wherein the determining the geographic area associated with the user device comprises determining the geographic area based on the geographic information. | 17. The one or more computer-readable media of claim 16 , wherein the acts further comprise obtaining geographic information associated with the user device, and wherein the determining the geographic area associated with the user device comprises determining the geographic area based on the geographic information. 19. The one or more computer-readable media of claim 17 , wherein the acts further comprise: determining that another phrase corresponding to a third string is not in the geographic word database; analyzing the geographic information to determine an additional geographic area associated with the user device; and determining another phrase using an additional geographic word database corresponding to the additional geographic area. | 0.5 |
7,542,820 | 27 | 29 | 27. The article of manufacture of claim 20 wherein said recipe editor creates a BKM driven recipe after receiving value inputs for said parameters. | 27. The article of manufacture of claim 20 wherein said recipe editor creates a BKM driven recipe after receiving value inputs for said parameters. 29. The article of manufacture of claim 27 wherein said recipe editor issues a warning when said comparison indicates incompatibility between said actual configuration settings and said BKM driven recipe. | 0.635714 |
9,384,226 | 15 | 18 | 15. A computer-implemented method performed at a user computer comprising one or more processors, the method comprising: obtaining, by at least one of the processors, a search query to search user's content items hosted by an online content management service; using, by at least one of the processors, the search query to identify in a local index at the user computer a first set of one or more of the user's hosted content items that satisfy the search query; displaying, by at least one of the processors, in a graphical user interface at the user computer, for at least a first content item in the first set of one or more of the user's hosted content items that satisfy the search query, a first search answer summary for the first content item; wherein a version of the first content item is stored at the user computer at the time the search query is obtained; wherein the first search answer summary indicates that the version of the first content item stored at the user computer is older than a version of the first content item hosted by the online content management service; sending, by at least one of the processors, the search query over a communications network to the online content management service; receiving, by at least one of the processors, over the communications network from the online content management service, one or more remote answers to the search query, the one or more remote answers corresponding to a second set of one or more of the user's hosted content items identified by the online content management service, using a remote index at the online content management service, as satisfying the search query; updating, by at least one of the processors, the graphical user interface at the user computer to display, for at least a second content item in the second set of one or more content items of the user's hosted content items that satisfy the search query, a second search answer summary for the second content item; and wherein, after the updating, the graphical user interface at the user computer displays at least both the first search answer summary for the first content item and the second search answer summary for the second content item. | 15. A computer-implemented method performed at a user computer comprising one or more processors, the method comprising: obtaining, by at least one of the processors, a search query to search user's content items hosted by an online content management service; using, by at least one of the processors, the search query to identify in a local index at the user computer a first set of one or more of the user's hosted content items that satisfy the search query; displaying, by at least one of the processors, in a graphical user interface at the user computer, for at least a first content item in the first set of one or more of the user's hosted content items that satisfy the search query, a first search answer summary for the first content item; wherein a version of the first content item is stored at the user computer at the time the search query is obtained; wherein the first search answer summary indicates that the version of the first content item stored at the user computer is older than a version of the first content item hosted by the online content management service; sending, by at least one of the processors, the search query over a communications network to the online content management service; receiving, by at least one of the processors, over the communications network from the online content management service, one or more remote answers to the search query, the one or more remote answers corresponding to a second set of one or more of the user's hosted content items identified by the online content management service, using a remote index at the online content management service, as satisfying the search query; updating, by at least one of the processors, the graphical user interface at the user computer to display, for at least a second content item in the second set of one or more content items of the user's hosted content items that satisfy the search query, a second search answer summary for the second content item; and wherein, after the updating, the graphical user interface at the user computer displays at least both the first search answer summary for the first content item and the second search answer summary for the second content item. 18. The method of claim 15 , further comprising: updating, by at least one of the processors, the graphical user interface at the user computer to display, for a fourth content item in the second set of one or more content items of the user's hosted content items that satisfy the search query, a fourth search answer summary for the fourth content item; wherein the fourth content item is not stored at the user computer at the time the search query is obtained; and wherein the fourth search answer summary for the fourth content item indicates that the fourth content item is not stored at the user computer. | 0.5 |
9,355,139 | 7 | 15 | 7. The computer-implemented method of claim 1 , further comprising: processing a query comprising a plurality of selectors, and at least one disjunctive Boolean operator, using results of one or more conjunctive or single selector queries which have been processed prior to creation of said query. | 7. The computer-implemented method of claim 1 , further comprising: processing a query comprising a plurality of selectors, and at least one disjunctive Boolean operator, using results of one or more conjunctive or single selector queries which have been processed prior to creation of said query. 15. The computer-implemented method of claim 7 , wherein the results of the queries processed prior to the creation of said query have previously been cached. | 0.565934 |
8,799,885 | 17 | 18 | 17. The computer system of claim 10 , wherein said method further comprises: replacing each original class loader in the class loader tree with a policy class loader that is populated with said metadata. | 17. The computer system of claim 10 , wherein said method further comprises: replacing each original class loader in the class loader tree with a policy class loader that is populated with said metadata. 18. The computer system of claim 17 , wherein said method further comprises: accessing said metadata to determine state and configuration information for classes in a policy class loader tree. | 0.5 |
8,150,679 | 15 | 16 | 15. The method of claim 12 wherein said analyzing comprises accessing a grammatical rules error set and comparing error rules therein with the received message. | 15. The method of claim 12 wherein said analyzing comprises accessing a grammatical rules error set and comparing error rules therein with the received message. 16. The method of claim 15 wherein the grammatical rules error set comprises rules identifying non-native language syntax. | 0.606452 |
7,797,310 | 18 | 21 | 18. The computer-readable volatile or non-volatile storage medium of claim 17 , wherein said estimated CPU cost is computed with an input size of data to be queried, a size of the output from the query and a plurality of factors specific to an implementation of the database system. | 18. The computer-readable volatile or non-volatile storage medium of claim 17 , wherein said estimated CPU cost is computed with an input size of data to be queried, a size of the output from the query and a plurality of factors specific to an implementation of the database system. 21. The computer-readable volatile or non-volatile storage medium of claim 18 , wherein CPU cost in a query with multiple XPath expressions is the sum of a first product, a second product, a third product, and an Nth product, wherein the first product is a product of a first factor specific to the database system implementation and the input size of data to be queried; the second product is a product of a second factor specific to the database system implementation and the size of output from the first query; the third product is a product of a third factor specific to the database system implementation and the size of output from the second query; and the Nth product is a product of an Nth factor specific to the database system implementation and the size of output from the (N-1) query. | 0.5 |
8,312,418 | 1 | 4 | 1. A method, executable by a processor, for visualization of implicit relationships in a trace query for model driven development (MDD), the method comprising: issuing a model query in an MDD tool to search a model for artifacts associated with the query; retrieving in response to the model query an implicit relationship between a participant and a collaboration within at least one of a requirements document for the model, the model and source code produced from the model; generating a trace link for the implicit relationship; and, displaying the trace link in a trace query diagram for the MDD tool. | 1. A method, executable by a processor, for visualization of implicit relationships in a trace query for model driven development (MDD), the method comprising: issuing a model query in an MDD tool to search a model for artifacts associated with the query; retrieving in response to the model query an implicit relationship between a participant and a collaboration within at least one of a requirements document for the model, the model and source code produced from the model; generating a trace link for the implicit relationship; and, displaying the trace link in a trace query diagram for the MDD tool. 4. The method of claim 1 , further comprising: selecting the trace link in the trace query diagram; and, navigating to the participant of the traceability in the model in the MDD tool. | 0.636364 |
8,683,323 | 1 | 5 | 1. A method comprising: obtaining a first XML schema and a second XML schema; with a processor, identifying one or more schema objects of each of the first XML schema and the second XML schema; comparing one of the identified schema objects of the first XML schema with one of the identified schema objects of the second XML schema; if a difference is detected between the compared schema objects, evaluating a risk of the detected difference affecting operation of a composite application incorporating the first schema or the second schema; and issuing a notification of the evaluated risk of the detected difference; wherein evaluating the risk comprises evaluating the risk in accordance with a predetermined rule. | 1. A method comprising: obtaining a first XML schema and a second XML schema; with a processor, identifying one or more schema objects of each of the first XML schema and the second XML schema; comparing one of the identified schema objects of the first XML schema with one of the identified schema objects of the second XML schema; if a difference is detected between the compared schema objects, evaluating a risk of the detected difference affecting operation of a composite application incorporating the first schema or the second schema; and issuing a notification of the evaluated risk of the detected difference; wherein evaluating the risk comprises evaluating the risk in accordance with a predetermined rule. 5. The method of claim 1 , wherein comparing the identified schema objects comprises comparing names of objects to detect whether an named schema object is present in one, but not in the other, of the first and second XML schema. | 0.552734 |
7,561,780 | 66 | 71 | 66. A text subtitle decoder for decoding a text subtitle stream downloaded from the external source, the text subtitle decoder comprising: a subtitle preloading buffer configured to preload the text subtitle stream at once, the text subtitle stream including a style segment defining region styles and a presentation segment including presentation information and text data for at least one region, the text data including a region style identifier and one or more text strings for each region; a font preloading buffer configured to preload related font data at once; a composition buffer configured to store the style segment after the text subtitle stream is preloaded, the style segment including rendering information and composition information; a text subtitle processor configured to parse the presentation information into the composition information and the text data for each region, the parsed composition information being stored in the composition buffer for each region; a buffer configured to store the parsed text data for each region; a text renderer configured to render the text strings into a bitmap object for each region based on the rendering information and the preloaded font data; a bitmap object buffer configured to store the rendered bitmap object for each region; a graphics plane in which the bitmap object stored in the bitmap object buffer for each region is composed according to the composition information; and a presentation controller configured to provide the rendering information and the composition information to the text renderer and the graphics plane, respectively. | 66. A text subtitle decoder for decoding a text subtitle stream downloaded from the external source, the text subtitle decoder comprising: a subtitle preloading buffer configured to preload the text subtitle stream at once, the text subtitle stream including a style segment defining region styles and a presentation segment including presentation information and text data for at least one region, the text data including a region style identifier and one or more text strings for each region; a font preloading buffer configured to preload related font data at once; a composition buffer configured to store the style segment after the text subtitle stream is preloaded, the style segment including rendering information and composition information; a text subtitle processor configured to parse the presentation information into the composition information and the text data for each region, the parsed composition information being stored in the composition buffer for each region; a buffer configured to store the parsed text data for each region; a text renderer configured to render the text strings into a bitmap object for each region based on the rendering information and the preloaded font data; a bitmap object buffer configured to store the rendered bitmap object for each region; a graphics plane in which the bitmap object stored in the bitmap object buffer for each region is composed according to the composition information; and a presentation controller configured to provide the rendering information and the composition information to the text renderer and the graphics plane, respectively. 71. The text subtitle decoder of claim 66 , wherein the text subtitle processor is configured to parse the text subtitle stream into the composition information including at least one of presentation time information, palette update information, and a region position for each region. | 0.559006 |
3,934,357 | 3 | 4 | 3. A method as set forth in claim 2; selecting a base numeral having a value greater than 1 from among said series of cutouts; and discriminatingly choosing from said cutouts remaining in said series a group of at least two numerals having a combined length equal to that of said base numeral for physical arrangement in an end-to-end abutting relationship proximal said base numeral whereby the sum of the values of said chosen group of numerals is equal to the value of said base numeral. | 3. A method as set forth in claim 2; selecting a base numeral having a value greater than 1 from among said series of cutouts; and discriminatingly choosing from said cutouts remaining in said series a group of at least two numerals having a combined length equal to that of said base numeral for physical arrangement in an end-to-end abutting relationship proximal said base numeral whereby the sum of the values of said chosen group of numerals is equal to the value of said base numeral. 4. A method as set forth in claim 3; and selecting additional groups of numerals, each of which have an accumulated value equal to that of said base numeral from those cutouts remaining in said series and physically placing them in an end-to-end relationship proximal said base numeral whereby multiple combinations of various numerals are associated with said | 0.5 |
8,239,562 | 1 | 15 | 1. In a computing environment, a method implemented by computing system having a processor, the method comprising: receiving a canonical enveloped message from a computer implemented application, wherein the canonical enveloped message comprises payload data and is associated with a context store that stores context information of the canonical enveloped message in a form that is independent of one or more protocols employed by the canonical enveloped message; at a protocol pipeline comprising a plurality of protocol components processing the canonical enveloped message including using two or more of the protocol components to process the canonical enveloped message, and by at least adding, removing or modifying context entries in the context store, wherein each portion of the context information is stored in the context store as a context entry that comprises at least a name element to identify the portion, a value element representing the value of the identified portion, and optionally a metadata element that defines any additional information about the identified portion, such that context information for a plurality of protocol components is aggregated using a common format in the context store; converting the canonical enveloped message to a raw message that does not include the context store; and sending at least a portion of the raw message on a computer implemented communication medium. | 1. In a computing environment, a method implemented by computing system having a processor, the method comprising: receiving a canonical enveloped message from a computer implemented application, wherein the canonical enveloped message comprises payload data and is associated with a context store that stores context information of the canonical enveloped message in a form that is independent of one or more protocols employed by the canonical enveloped message; at a protocol pipeline comprising a plurality of protocol components processing the canonical enveloped message including using two or more of the protocol components to process the canonical enveloped message, and by at least adding, removing or modifying context entries in the context store, wherein each portion of the context information is stored in the context store as a context entry that comprises at least a name element to identify the portion, a value element representing the value of the identified portion, and optionally a metadata element that defines any additional information about the identified portion, such that context information for a plurality of protocol components is aggregated using a common format in the context store; converting the canonical enveloped message to a raw message that does not include the context store; and sending at least a portion of the raw message on a computer implemented communication medium. 15. The method of claim 1 , wherein the context information is included in hidden form fields. | 0.841751 |
7,757,234 | 8 | 11 | 8. A computer-implemented method, comprising: accepting control of a wizard based on a first user request, the wizard configured to perform a step-by-step process, each step associated with a step type, the step type being one of confirmation, processing, optional input, or mandatory input, wherein the wizard is capable of presenting a user interface associated with each step in the step-by-step process; causing execution of the wizard process in batch mode by a batch job manager until a first step associated with a step type that requires user input is encountered; presenting an augmented user interface of the wizard associated with the first step to the user, where the augmented user interface of the wizard incorporates at least one user interface element associated with the operations of the batch job manager configured to correspond to the first step, where completion of the first step is based at least in part on a second user request; and resuming execution of the wizard process in batch mode after completion of the first step based on the second user request. | 8. A computer-implemented method, comprising: accepting control of a wizard based on a first user request, the wizard configured to perform a step-by-step process, each step associated with a step type, the step type being one of confirmation, processing, optional input, or mandatory input, wherein the wizard is capable of presenting a user interface associated with each step in the step-by-step process; causing execution of the wizard process in batch mode by a batch job manager until a first step associated with a step type that requires user input is encountered; presenting an augmented user interface of the wizard associated with the first step to the user, where the augmented user interface of the wizard incorporates at least one user interface element associated with the operations of the batch job manager configured to correspond to the first step, where completion of the first step is based at least in part on a second user request; and resuming execution of the wizard process in batch mode after completion of the first step based on the second user request. 11. The method of claim 8 , where accepting control of the wizard includes obtaining state information for the wizard. | 0.691099 |
8,601,079 | 1 | 7 | 1. A network device, comprising: a storage device for storing one or more files that are associated with a user of at least one client device; and a processor for enabling actions, the actions comprising: receiving one or more message file attachments, wherein the one or more message file attachments are associated with the user; automatically determining one or more automatic tags that are associated with the one or more message file attachments, wherein each of the one or more message file attachments is associated with at least one of the one or more automatic tags; automatically generating a personalized hierarchical structure of tags (“PHST”) from the one or more automatic tags; receiving, from the user, one or more custom tags for at least one of the one or more message file attachments; associating the at least one of the one or more message file attachments with the one or more custom tags; automatically generating at least one custom generated tag using the one or more custom tags; automatically modifying the PHST to include the at least one custom generated tag within the hierarchy; and displaying the PHST which separately indicates the one or more automatic tags and the at least one custom generated tag to the user such that the user is enabled to select at least one tag which in turn selects one or more files associated with the selected tag for attachment to a message. | 1. A network device, comprising: a storage device for storing one or more files that are associated with a user of at least one client device; and a processor for enabling actions, the actions comprising: receiving one or more message file attachments, wherein the one or more message file attachments are associated with the user; automatically determining one or more automatic tags that are associated with the one or more message file attachments, wherein each of the one or more message file attachments is associated with at least one of the one or more automatic tags; automatically generating a personalized hierarchical structure of tags (“PHST”) from the one or more automatic tags; receiving, from the user, one or more custom tags for at least one of the one or more message file attachments; associating the at least one of the one or more message file attachments with the one or more custom tags; automatically generating at least one custom generated tag using the one or more custom tags; automatically modifying the PHST to include the at least one custom generated tag within the hierarchy; and displaying the PHST which separately indicates the one or more automatic tags and the at least one custom generated tag to the user such that the user is enabled to select at least one tag which in turn selects one or more files associated with the selected tag for attachment to a message. 7. The network device of claim 1 , wherein the one or more automatic tags are determined from a data type of an associated file. | 0.882784 |
9,966,078 | 1 | 2 | 1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: generating, by the processor, a plurality of information elements based upon a voice conversation between a first entity and a second entity over a communication network; constructing a current conversation pattern from the plurality of information elements, wherein the current conversation pattern specifies an order of the plurality of information elements based upon the voice conversation; identifying one or more deceptive conversation properties of the current conversation pattern based upon analyzing the order of the plurality of information elements in the current conversation pattern against one or more domain-based conversation patterns; and sending an alert message to the first entity based upon the identified one or more deceptive conversation properties. | 1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: generating, by the processor, a plurality of information elements based upon a voice conversation between a first entity and a second entity over a communication network; constructing a current conversation pattern from the plurality of information elements, wherein the current conversation pattern specifies an order of the plurality of information elements based upon the voice conversation; identifying one or more deceptive conversation properties of the current conversation pattern based upon analyzing the order of the plurality of information elements in the current conversation pattern against one or more domain-based conversation patterns; and sending an alert message to the first entity based upon the identified one or more deceptive conversation properties. 2. The method of claim 1 wherein the voice conversation comprises one or more conversation statements, the method further comprising: parsing the one or more conversation statements into a plurality of information phrases based upon cognitive analysis of the one or more conversation statements by a question answer system, wherein the plurality of information elements are generated from the plurality of information phrases; determining the order of the plurality of information elements based upon a relative order of the plurality of information phrases in the voice conversation; and storing the plurality of information elements in the determined order into the current conversation pattern. | 0.5 |
7,499,948 | 6 | 7 | 6. The method of claim 1 , wherein the rules are stored in a rules repository that may be updated, and subsequently parsed by the rules engine, during-runtime, without stopping the execution of the rules engine. | 6. The method of claim 1 , wherein the rules are stored in a rules repository that may be updated, and subsequently parsed by the rules engine, during-runtime, without stopping the execution of the rules engine. 7. The method of claim 6 , wherein the rules repository, as updated, is parsed by the rules engine in response to each new event. | 0.5 |
8,577,882 | 1 | 8 | 1. A computer implemented method for searching multilingual documents, the method comprising the steps of: receiving a search request based on at least one language; searching a first relevant document using said search request wherein said first relevant document is written in a first language and includes a first image; searching a data source for a second relevant document having a second image which is similar to said first image and is written in a second language; searching said second relevant document using said search request; establishing a text library and an image library for multilingual documents, wherein said establishing comprises collecting, using a network automatic program, a multilingual document to establish a multilingual document library; extracting main texts and main images from said multilingual document library to establish the text library and the image library; mapping said text library to said image library; and wherein at least one of said steps are carried out by a computer device. | 1. A computer implemented method for searching multilingual documents, the method comprising the steps of: receiving a search request based on at least one language; searching a first relevant document using said search request wherein said first relevant document is written in a first language and includes a first image; searching a data source for a second relevant document having a second image which is similar to said first image and is written in a second language; searching said second relevant document using said search request; establishing a text library and an image library for multilingual documents, wherein said establishing comprises collecting, using a network automatic program, a multilingual document to establish a multilingual document library; extracting main texts and main images from said multilingual document library to establish the text library and the image library; mapping said text library to said image library; and wherein at least one of said steps are carried out by a computer device. 8. The method according to claim 1 , further comprising the step of: performing topic clustering on said first relevant document and said second relevant document. | 0.851005 |
9,658,989 | 13 | 14 | 13. A method for preparing a display document for analysis comprising: extracting character data from said display document, wherein a language of said character data in said display document is unknown when said character data is extracted; determining a first order associated with processing of said character data and a second order associated with a logical order of said character data; determining whether said first order is different from said second order; and reversing at least a portion of said character data in response to said determination that said first order is different from said second order; wherein determining the second order comprises identifying a punctuation character that is position dependent such that a space character will appear on only one side of the punctuation character, where the side of the punctuation character on which the space character appears depends on said second order; and comparing characters around said punctuation character data against a rule to determine said second order. | 13. A method for preparing a display document for analysis comprising: extracting character data from said display document, wherein a language of said character data in said display document is unknown when said character data is extracted; determining a first order associated with processing of said character data and a second order associated with a logical order of said character data; determining whether said first order is different from said second order; and reversing at least a portion of said character data in response to said determination that said first order is different from said second order; wherein determining the second order comprises identifying a punctuation character that is position dependent such that a space character will appear on only one side of the punctuation character, where the side of the punctuation character on which the space character appears depends on said second order; and comparing characters around said punctuation character data against a rule to determine said second order. 14. The method of claim 13 , wherein said second order is determined by identifying, in said character data, a full stop character and then determining on which side of said full stop character a space character appears. | 0.5 |
9,881,228 | 1 | 4 | 1. A method for removing a mark in a document image, the method comprising: extracting connected components from a binary image corresponding to the document image; clustering the connected components based on grayscale features of the connected components to obtain one clustering center; searching, within numerical ranges of a clustering radius R from the clustering center and a grayscale threshold T, for a combination (R, T) which causes an evaluation value based on the grayscale features of the connected components to be higher than a first evaluation threshold; and removing the mark in the document image based on the grayscale threshold in the combination; wherein the grayscale features of the connected components comprise: a minimum one of grayscale values of pixels in the document image, which correspond to all black pixels in each of connected components; wherein the removing the mark in the document image based on the grayscale threshold in the combination comprises: removing the connected components, the grayscale features of which are greater than the grayscale threshold, as the mark in the document image. | 1. A method for removing a mark in a document image, the method comprising: extracting connected components from a binary image corresponding to the document image; clustering the connected components based on grayscale features of the connected components to obtain one clustering center; searching, within numerical ranges of a clustering radius R from the clustering center and a grayscale threshold T, for a combination (R, T) which causes an evaluation value based on the grayscale features of the connected components to be higher than a first evaluation threshold; and removing the mark in the document image based on the grayscale threshold in the combination; wherein the grayscale features of the connected components comprise: a minimum one of grayscale values of pixels in the document image, which correspond to all black pixels in each of connected components; wherein the removing the mark in the document image based on the grayscale threshold in the combination comprises: removing the connected components, the grayscale features of which are greater than the grayscale threshold, as the mark in the document image. 4. The method according to claim 1 , wherein the evaluation value is further based on a number of black pixels in one connected component in the binary image. | 0.858169 |
9,710,451 | 1 | 4 | 1. A method for natural-language processing based on DNA computing, the method comprising: a processor of a computer system translating a grammatical rule of a natural language into a listing of a first sequence of nucleotides, wherein the grammatical rule comprises an ordered set of slots, and wherein each slot of the ordered set of slots is configured to be filled with a compatible token, and wherein a token is a string of characters comprised by a vocabulary of the natural language; the processor further translating a first token of the vocabulary into a listing of a second sequence of nucleotides; the processor decoding information represented by a first bonded pair of nucleotide sequences, wherein the first bonded pair was formed by a chemical bonding of a first nucleotide chain to a second nucleotide chain, wherein nucleotides of the first nucleotide chain are ordered in the first sequence, wherein nucleotides of the second nucleotide chain are ordered in the second sequence, and wherein the decoded information represents a data structure formed by filling a first slot of the ordered set of slots with the first token; the processor determining that the first token comprises an adjacent pair of duplicate substrings; the processor identifying a second token that, other than omitting one occurrence of the duplicate substrings, is identical to the first token; the processor translating the second token into a listing of a third sequence of nucleotides; and the processor decoding information represented by a second bonded pair of nucleotide sequences, wherein the second bonded pair was formed by a chemical bonding of a third nucleotide chain to a fourth nucleotide chain, wherein nucleotides of the third nucleotide chain are ordered in the third sequence, wherein nucleotides of the fourth nucleotide chain are ordered in the first sequence, and wherein the decoded information represents a data structure formed by filling a first slot of the ordered set of slots with the second token. | 1. A method for natural-language processing based on DNA computing, the method comprising: a processor of a computer system translating a grammatical rule of a natural language into a listing of a first sequence of nucleotides, wherein the grammatical rule comprises an ordered set of slots, and wherein each slot of the ordered set of slots is configured to be filled with a compatible token, and wherein a token is a string of characters comprised by a vocabulary of the natural language; the processor further translating a first token of the vocabulary into a listing of a second sequence of nucleotides; the processor decoding information represented by a first bonded pair of nucleotide sequences, wherein the first bonded pair was formed by a chemical bonding of a first nucleotide chain to a second nucleotide chain, wherein nucleotides of the first nucleotide chain are ordered in the first sequence, wherein nucleotides of the second nucleotide chain are ordered in the second sequence, and wherein the decoded information represents a data structure formed by filling a first slot of the ordered set of slots with the first token; the processor determining that the first token comprises an adjacent pair of duplicate substrings; the processor identifying a second token that, other than omitting one occurrence of the duplicate substrings, is identical to the first token; the processor translating the second token into a listing of a third sequence of nucleotides; and the processor decoding information represented by a second bonded pair of nucleotide sequences, wherein the second bonded pair was formed by a chemical bonding of a third nucleotide chain to a fourth nucleotide chain, wherein nucleotides of the third nucleotide chain are ordered in the third sequence, wherein nucleotides of the fourth nucleotide chain are ordered in the first sequence, and wherein the decoded information represents a data structure formed by filling a first slot of the ordered set of slots with the second token. 4. The method of claim 1 , wherein the vocabulary comprises natural-language text entered by a user. | 0.918831 |
6,082,775 | 32 | 33 | 32. The method of claim 30, wherein said molecular code is formed on said document as a chemical solution. | 32. The method of claim 30, wherein said molecular code is formed on said document as a chemical solution. 33. The method of claim 32, wherein said molecular code application step further comprises forming relief markings on said document and pressing said chemical solution into said document. | 0.5 |
10,031,912 | 12 | 13 | 12. The computer-program product of claim 11 , the operation further comprising submitting the case and an indication of the candidate value to the QA system for processing. | 12. The computer-program product of claim 11 , the operation further comprising submitting the case and an indication of the candidate value to the QA system for processing. 13. The computer-program product of claim 12 , wherein the processing comprises generating a treatment recommendation, and wherein the case is an electronic medical record (EMR). | 0.5 |
8,972,873 | 1 | 4 | 1. A device comprising: a computer readable storage medium storing instructions; and a processor in communication with the computer readable medium, wherein the instructions, which when executed by the processor, configure the processor to assemble widget content, the content assembly including: selecting a widget skeleton from a plurality of different widget skeletons, skeletons of the plurality representing a different type of target widget environment, and skeletons of the plurality for use in generating a widget by adapting a selected widget to work in a specific widget environment, the specific widget environment being an environment targeted by the selected widget skeleton, and returning the selected widget environmental skeleton to a widget assembly application for use in generating a widget in the selected widget environment, and integrating widget template embedded elements from the widget assembly application into widget content being created, wherein the instructions, which when executed by the processor, further configure the processor to return widget content to a requesting servlet, in response to a request for the widget content from the requesting servlet. | 1. A device comprising: a computer readable storage medium storing instructions; and a processor in communication with the computer readable medium, wherein the instructions, which when executed by the processor, configure the processor to assemble widget content, the content assembly including: selecting a widget skeleton from a plurality of different widget skeletons, skeletons of the plurality representing a different type of target widget environment, and skeletons of the plurality for use in generating a widget by adapting a selected widget to work in a specific widget environment, the specific widget environment being an environment targeted by the selected widget skeleton, and returning the selected widget environmental skeleton to a widget assembly application for use in generating a widget in the selected widget environment, and integrating widget template embedded elements from the widget assembly application into widget content being created, wherein the instructions, which when executed by the processor, further configure the processor to return widget content to a requesting servlet, in response to a request for the widget content from the requesting servlet. 4. The device of claim 1 wherein the content assembly further includes: receiving a network location of widget content and sending a retrieval query to the received network location of the widget content. | 0.66 |
9,536,146 | 19 | 20 | 19. The device of claim 17 , operations further comprising: constructing outlier trees based on temporal and spatial properties of the outliers being detected by determining dependencies of the outliers from a first time frame of the plurality of time frames through a last time frame of the plurality of time frames; and discovering frequent subtrees from the constructed outlier trees that correspond to a causality and a relationship among the frequent subtrees to represent abnormal traffic patterns in the GPS points. | 19. The device of claim 17 , operations further comprising: constructing outlier trees based on temporal and spatial properties of the outliers being detected by determining dependencies of the outliers from a first time frame of the plurality of time frames through a last time frame of the plurality of time frames; and discovering frequent subtrees from the constructed outlier trees that correspond to a causality and a relationship among the frequent subtrees to represent abnormal traffic patterns in the GPS points. 20. The device of claim 19 , operations further comprising providing, via a user interface associated with the device, recommendations based at least in part on the frequent subtrees including abnormal traffic patterns, the recommendations including diverting traffic to less travelled roads, building additional roads, suggesting a bus route, or suggesting a subway line. | 0.5 |
9,779,063 | 14 | 17 | 14. A document creation apparatus comprising: a processor adapted to: receive a request to create a document, the request comprising a document type, create a primary data object (“PDO”), associate the PDO with a document schema corresponding to the document type, the document schema comprising information relating to allowable node data object types and allowable node data object relationships; receive a first metadata data object comprising document-type dependent information; associate the first metadata data object with the PDO; receive a node data object comprising a node type, content, and relationship information; determine that the received node data object is allowed, based on the document schema and the type and relationship information of the received node data object; associate the received node data object with the PDO; select a document template, based on the document type; and create a storable document, based on the document template, the PDO, the first metadata data object, and the node data object; and a memory adapted to store: the PDO the metadata data object, the node data object, and the document schema. | 14. A document creation apparatus comprising: a processor adapted to: receive a request to create a document, the request comprising a document type, create a primary data object (“PDO”), associate the PDO with a document schema corresponding to the document type, the document schema comprising information relating to allowable node data object types and allowable node data object relationships; receive a first metadata data object comprising document-type dependent information; associate the first metadata data object with the PDO; receive a node data object comprising a node type, content, and relationship information; determine that the received node data object is allowed, based on the document schema and the type and relationship information of the received node data object; associate the received node data object with the PDO; select a document template, based on the document type; and create a storable document, based on the document template, the PDO, the first metadata data object, and the node data object; and a memory adapted to store: the PDO the metadata data object, the node data object, and the document schema. 17. A document creation apparatus according to claim 14 , wherein the processor is further adapted to present a document drafting interface to a user comprising an indicator of one or more allowable node data object types. | 0.5375 |
8,607,136 | 3 | 4 | 3. The method of claim 2 , further comprising enabling the user to associate the selected one or more tags with the selected one or more communities. | 3. The method of claim 2 , further comprising enabling the user to associate the selected one or more tags with the selected one or more communities. 4. The method of claim 3 , further comprising storing a universal resource locator (URL) associated with the document page associated with the one or more tags, wherein the document page can be identified based on the one or more tags and retrieved from a location addressed by the URL associated with the document page. | 0.5 |
9,823,910 | 8 | 11 | 8. A method, comprising: transforming a program from a first language to a second language using a compiler for a third language and data type representation conversion without helper classes, wherein said transforming step includes: generating, by a compiler for the first language, an abstract syntax tree; converting, by the compiler for the third language, the first abstract syntax tree to a given abstract syntax tree of the compiler for the third language using a conversion table; when a compilation error occurs in the compiler for the third language, generating therein a special node for error processing in a second abstract syntax tree of the compiler of the second language and storing an error token indicating information of the compilation error in the special node; and when unparsing by the compiler for the second language, outputting the error token stored in the special node. | 8. A method, comprising: transforming a program from a first language to a second language using a compiler for a third language and data type representation conversion without helper classes, wherein said transforming step includes: generating, by a compiler for the first language, an abstract syntax tree; converting, by the compiler for the third language, the first abstract syntax tree to a given abstract syntax tree of the compiler for the third language using a conversion table; when a compilation error occurs in the compiler for the third language, generating therein a special node for error processing in a second abstract syntax tree of the compiler of the second language and storing an error token indicating information of the compilation error in the special node; and when unparsing by the compiler for the second language, outputting the error token stored in the special node. 11. The method of claim 8 , further comprising performing a data representation type check between data representation types of the first compiler and the third compiler to detect the compilation error. | 0.5 |
8,434,000 | 13 | 14 | 13. A computer program product for archiving pertinent portions of a web application, the computer program product comprising: a computer readable memory, the computer readable memory being an apparatus that stores program code; first program instructions to execute a script in an HTML document beginning at an execution tag; second program instructions to create a temporary buffer; and third program instructions to output results of the script rendered between a start tag and an end tag to the temporary buffer and write the results from the temporary buffer to a file and into a response stream, without saving additional text rendered prior to the start tag and after the end tag, wherein: the response stream comprises data generated by the execution of the script, the data comprises the additional text rendered prior to the start tag and after the end tag, and the results of the script rendered between the start tag and the end tag, the start tag includes an attribute to name the file and the results are written to the response stream from the temporary buffer such that the results rendered to an end user from the temporary buffer and do not come directly from the execution of the script, the start tag includes an attribute to name the file, wherein the first, second and third program instructions are stored on the computer readable media, and the results are a pertinent portion of a web page for displaying to the end user, the pertinent portion including a confirmation of a transaction. | 13. A computer program product for archiving pertinent portions of a web application, the computer program product comprising: a computer readable memory, the computer readable memory being an apparatus that stores program code; first program instructions to execute a script in an HTML document beginning at an execution tag; second program instructions to create a temporary buffer; and third program instructions to output results of the script rendered between a start tag and an end tag to the temporary buffer and write the results from the temporary buffer to a file and into a response stream, without saving additional text rendered prior to the start tag and after the end tag, wherein: the response stream comprises data generated by the execution of the script, the data comprises the additional text rendered prior to the start tag and after the end tag, and the results of the script rendered between the start tag and the end tag, the start tag includes an attribute to name the file and the results are written to the response stream from the temporary buffer such that the results rendered to an end user from the temporary buffer and do not come directly from the execution of the script, the start tag includes an attribute to name the file, wherein the first, second and third program instructions are stored on the computer readable media, and the results are a pertinent portion of a web page for displaying to the end user, the pertinent portion including a confirmation of a transaction. 14. The computer program product of claim 13 , wherein the computer program product is provided by a service provider for a fee. | 0.5 |
9,426,160 | 10 | 12 | 10. The method of claim 9 , further comprising: prompting the user regarding following the verified author; and receiving user input regarding following the verified author. | 10. The method of claim 9 , further comprising: prompting the user regarding following the verified author; and receiving user input regarding following the verified author. 12. The method of claim 10 , in Which the verified author is a plurality of verified authors and the method further comprising prompting the user for which of the plurality of verified authors the user wishes to follow. | 0.5 |
8,407,190 | 1 | 3 | 1. A method for storing, on a cloud storage site, a secondary copy of an original data set, the method comprising: receiving, with a computing device, a primary copy of an original data set; updating, with the computing device, a content index to reflect at least some of data content in the original data set; identifying, with the computing device, a target cloud storage site on which to store a secondary copy of the original data set, wherein a network connection is to be established between the target cloud storage site and a media file system agent, and wherein the established network connection has an associated latency and bandwidth; determining, with the computing device, a size for a container file to utilize when deduplicating the primary copy of the original data set, wherein the container file size is determined at least in part on the latency, bandwidth, or both, associated with the network connection to be established; deduplicating, with the computing device, at least some of the data content in the primary copy in order to create one or more container files containing deduplicated data, wherein at least one of the container files has the determined size; establishing, with the computing device, the network connection between the target cloud storage site and the media file system agent; and transferring, with the computing device, the one or more container files to the target cloud storage site. | 1. A method for storing, on a cloud storage site, a secondary copy of an original data set, the method comprising: receiving, with a computing device, a primary copy of an original data set; updating, with the computing device, a content index to reflect at least some of data content in the original data set; identifying, with the computing device, a target cloud storage site on which to store a secondary copy of the original data set, wherein a network connection is to be established between the target cloud storage site and a media file system agent, and wherein the established network connection has an associated latency and bandwidth; determining, with the computing device, a size for a container file to utilize when deduplicating the primary copy of the original data set, wherein the container file size is determined at least in part on the latency, bandwidth, or both, associated with the network connection to be established; deduplicating, with the computing device, at least some of the data content in the primary copy in order to create one or more container files containing deduplicated data, wherein at least one of the container files has the determined size; establishing, with the computing device, the network connection between the target cloud storage site and the media file system agent; and transferring, with the computing device, the one or more container files to the target cloud storage site. 3. The method of claim 1 , wherein determining the size for the container file further comprises: determining at least two of the following factors: an estimate of the latency associated with the network connection established to the identified target cloud storage site; an estimate of the bandwidth associated with the network connection established to the identified target cloud storage site; whether the target cloud storage site imposes a restriction on a namespace associated with the target cloud storage site; whether the target cloud storage site permits sparsification of data files; a pricing structure used by the target cloud storage site, a maximum container file size specified by a user or by a storage policy; and a minimum container file size specified by a user or by a storage policy; and performing an optimization to establish a container size reflecting the determined two or more factors. | 0.666057 |
8,839,123 | 2 | 4 | 2. The method of claim 1 , further comprising: receiving signals from the display related to the visual interface, wherein the received signals represent physical actions performed on the display; and translating the received signals into operations related to the plurality of scrollable subsets of characters. | 2. The method of claim 1 , further comprising: receiving signals from the display related to the visual interface, wherein the received signals represent physical actions performed on the display; and translating the received signals into operations related to the plurality of scrollable subsets of characters. 4. The method of claim 2 , further comprising transferring a selected character associated with one of the plurality of scrollable subsets of characters to an application hosted by the computing device. | 0.555066 |
9,946,711 | 11 | 13 | 11. An apparatus for determining whether an operator text is to be generated in response to a received alert condition, the apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least: analyze a primary data feed and at least one confirmatory data feed to identify one or more features related to the received alert condition; determine whether the received alert condition in the primary data feed is confirmed by at least one confirmatory data feed, wherein the alert condition is validated in an instance in which a signal correlation between the primary data feed and the confirmatory data feed satisfies a correlation threshold; determine whether the one or more features in the primary data feed are explainable by at least one diagnostic data feed; and traverse, using the one or more features, a decision tree, wherein the decision tree is operable to determine that at least a portion of an operator text is to be generated in an instance in which a feature of the one or more features evaluates as true for at least one node of the decision tree; and generate an output text that is displayable in a user interface that describes at least a diagnosis based on the at least one diagnostic data feed for the feature of the one or more features that evaluated as true. | 11. An apparatus for determining whether an operator text is to be generated in response to a received alert condition, the apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least: analyze a primary data feed and at least one confirmatory data feed to identify one or more features related to the received alert condition; determine whether the received alert condition in the primary data feed is confirmed by at least one confirmatory data feed, wherein the alert condition is validated in an instance in which a signal correlation between the primary data feed and the confirmatory data feed satisfies a correlation threshold; determine whether the one or more features in the primary data feed are explainable by at least one diagnostic data feed; and traverse, using the one or more features, a decision tree, wherein the decision tree is operable to determine that at least a portion of an operator text is to be generated in an instance in which a feature of the one or more features evaluates as true for at least one node of the decision tree; and generate an output text that is displayable in a user interface that describes at least a diagnosis based on the at least one diagnostic data feed for the feature of the one or more features that evaluated as true. 13. The apparatus according to claim 11 , wherein the one or more features is at least one of a trend, spike, oscillation or step in a data feed. | 0.917707 |
8,300,023 | 3 | 5 | 3. The method of claim 1 , further comprising: determining a statistical envelope based upon received coordinates for each of the plurality of keys by calculating standard deviations about the calculated average coordinates for each of the plurality of keys; and saving the statistical envelope for each of the plurality of keys in the keypad layout data. | 3. The method of claim 1 , further comprising: determining a statistical envelope based upon received coordinates for each of the plurality of keys by calculating standard deviations about the calculated average coordinates for each of the plurality of keys; and saving the statistical envelope for each of the plurality of keys in the keypad layout data. 5. The method of claim 3 , further comprising: determining a first standard deviation envelope of key strike locations about the calculated average coordinates for each of the plurality of keys; and interpreting a key strike as intended for a selected key in response to the key strike occurring within the first standard deviation envelope for the selected key. | 0.5 |
9,507,857 | 2 | 8 | 2. The apparatus according to claim 1 , wherein the extracting of the feature words comprises extracting words subjected to intention representation by using more than one type of intention representation and selecting words from the extracted words based on a predefined criteria, as the feature words. | 2. The apparatus according to claim 1 , wherein the extracting of the feature words comprises extracting words subjected to intention representation by using more than one type of intention representation and selecting words from the extracted words based on a predefined criteria, as the feature words. 8. The apparatus according to claim 2 , wherein each of the documents included in the document set is a structured document that is separated into document elements each of which corresponds to one of intention representations, and the extracting of the feature words comprises extracting the feature word from the document elements. | 0.5 |
9,747,269 | 6 | 17 | 6. The method as recited in claim 1 , wherein the workflow comprises one or more of a telecommunications application or function; an insurance quote; a health care admission process; a signing ceremony; and a financial services application configured to facilitate one or more of: displaying at least one of an account statement, an account balance, and a payment due date; processing a deposit; preparing a tax return; and processing a loan application. | 6. The method as recited in claim 1 , wherein the workflow comprises one or more of a telecommunications application or function; an insurance quote; a health care admission process; a signing ceremony; and a financial services application configured to facilitate one or more of: displaying at least one of an account statement, an account balance, and a payment due date; processing a deposit; preparing a tax return; and processing a loan application. 17. The method as recited in claim 6 , wherein the context of the optical input is determined to be an enterprise service based at least in part on detecting the optical input comprises an invoice; and wherein the contextually-appropriate workflow comprises an enterprise application configured to display a status of the invoice. | 0.65625 |
9,436,755 | 17 | 22 | 17. A system including memory and one or more processors operable to execute instructions stored in memory, comprising instructions to: identify a plurality of messages from one or more databases; determine a plurality of interrogative sentences from the messages; determine starting n-grams from the interrogative sentences; determine a group of task indications, wherein each of the task indications of the group is based on a set of one or more of the starting n-grams, and wherein determining to include a given task indication of the task indications in the group is based on a count of the starting n-grams that conform to the given task indication; provide the group of the task indications; receive, in response to providing the group of the task indications, one or more task association measures for each of the task indications of the group, wherein a given task association measure for a given task indication is indicative of likelihood that the given task indication is associated with a task request; determine a task association score for each of the task indications of the group, wherein the task association score for the given task indication is based on the one or more task association measures received for the given task indication; and store the task association score for each of a plurality of the task indications of the group. | 17. A system including memory and one or more processors operable to execute instructions stored in memory, comprising instructions to: identify a plurality of messages from one or more databases; determine a plurality of interrogative sentences from the messages; determine starting n-grams from the interrogative sentences; determine a group of task indications, wherein each of the task indications of the group is based on a set of one or more of the starting n-grams, and wherein determining to include a given task indication of the task indications in the group is based on a count of the starting n-grams that conform to the given task indication; provide the group of the task indications; receive, in response to providing the group of the task indications, one or more task association measures for each of the task indications of the group, wherein a given task association measure for a given task indication is indicative of likelihood that the given task indication is associated with a task request; determine a task association score for each of the task indications of the group, wherein the task association score for the given task indication is based on the one or more task association measures received for the given task indication; and store the task association score for each of a plurality of the task indications of the group. 22. The system of claim 17 , wherein the instructions to identify the plurality of messages includes instructions to identify the messages based on recipients of the messages. | 0.741124 |
9,060,029 | 10 | 15 | 10. A computer software product, including a non-transitory computer-readable storage medium in which computer program instructions are stored, which instructions, when executed by a computer, cause the computer to perform the steps of: identifying properties of a target individual, wherein a correlation processor extracts user identifiers from retrieved data items, and correlates the user identifiers from different web sites; building an initial social circle of the target individual by crawling a plurality of web sites from different social media providers to identify direct and indirect associations between users of the social media providers and the target individual, wherein the target individual has no direct connection with at least one of the social media providers; deriving references to the target individual from the direct and indirect associations; and compiling a dossier on the target individual from the references to the target individual. | 10. A computer software product, including a non-transitory computer-readable storage medium in which computer program instructions are stored, which instructions, when executed by a computer, cause the computer to perform the steps of: identifying properties of a target individual, wherein a correlation processor extracts user identifiers from retrieved data items, and correlates the user identifiers from different web sites; building an initial social circle of the target individual by crawling a plurality of web sites from different social media providers to identify direct and indirect associations between users of the social media providers and the target individual, wherein the target individual has no direct connection with at least one of the social media providers; deriving references to the target individual from the direct and indirect associations; and compiling a dossier on the target individual from the references to the target individual. 15. The computer software product according to claim 10 , wherein compiling a dossier comprises correlating the references according to similarities and commonalities therebetween. | 0.770408 |
9,396,727 | 15 | 16 | 15. An arbitration method comprising: determining, with an arbitration module that includes a processor, a capability catalog associated with a plurality of devices accessible within a vehicle, the capability catalog including a list of the plurality of devices mapped to a list of spoken dialog services provided by each of the plurality of devices; receiving, with a speech understanding module that includes a processor, the spoken utterance; arbitrating, with an arbitration module that includes a processor, between the plurality of devices and the spoken dialog services in the capability catalog to determine a selected device and a selected dialog service, wherein the arbitrating includes classifying the spoken utterance to determine a set of candidate devices from the plurality of devices and a set of spoken dialog services based on the capability catalog, and determining the selected device from the set of candidate devices and the selected spoken dialog service from the list of candidate spoken dialog services based on a verification criterion; and processing the spoken utterance with the selected spoken dialog service on the selected device. | 15. An arbitration method comprising: determining, with an arbitration module that includes a processor, a capability catalog associated with a plurality of devices accessible within a vehicle, the capability catalog including a list of the plurality of devices mapped to a list of spoken dialog services provided by each of the plurality of devices; receiving, with a speech understanding module that includes a processor, the spoken utterance; arbitrating, with an arbitration module that includes a processor, between the plurality of devices and the spoken dialog services in the capability catalog to determine a selected device and a selected dialog service, wherein the arbitrating includes classifying the spoken utterance to determine a set of candidate devices from the plurality of devices and a set of spoken dialog services based on the capability catalog, and determining the selected device from the set of candidate devices and the selected spoken dialog service from the list of candidate spoken dialog services based on a verification criterion; and processing the spoken utterance with the selected spoken dialog service on the selected device. 16. The method of claim 15 , wherein the steps of receiving the first confidence score from the first spoken dialog service and receiving the second confidence score from the second spoken dialog service is followed by one or more steps of prompting the user for additional input and providing the additional user utterances to both services concurrently, and selecting one of the services when the confidence returned by that service is sufficiently higher than that of the other service. | 0.549724 |
8,359,190 | 23 | 25 | 23. Instructions on a computer-usable medium that when executed cause a computer to: identify sets of senses of words for corresponding portions in a text; determine, based on the identified sets of senses of the words, semantic positions in a semantic space of the corresponding portions of the text; and perform an action with respect to the text based on the determined semantic positions. | 23. Instructions on a computer-usable medium that when executed cause a computer to: identify sets of senses of words for corresponding portions in a text; determine, based on the identified sets of senses of the words, semantic positions in a semantic space of the corresponding portions of the text; and perform an action with respect to the text based on the determined semantic positions. 25. The instructions of claim 23 , which when executed cause the computer to further: access a position-based feature dictionary to identify semantic positions of the senses, wherein determining the semantic positions of the text portions is based on the identified semantic positions of the senses, wherein the position-based feature dictionary maps word forms to corresponding senses, the position-based feature dictionary to also identify semantic positions for respective senses in the position-based feature dictionary. | 0.5 |
9,230,280 | 3 | 6 | 3. The computer system of claim 2 , wherein the first clustering strategy further queries the one or more cluster data sources to determine data items matching one or more properties values of the first seed. | 3. The computer system of claim 2 , wherein the first clustering strategy further queries the one or more cluster data sources to determine data items matching one or more properties values of the first seed. 6. The computer system of claim 3 , wherein the at least one scoring criterion comprises a first scoring criterion, and the first scoring criterion scores the cluster based at least on the seed trade matching a prohibited time for trading by a trader executing the seed trade. | 0.734104 |
8,769,397 | 16 | 18 | 16. The computer program product of claim 12 , further operable to: parse the snippet to generate a Document Object Model (DOM) tree and a parsed Javascript expression tree; determine a target portion in the snippet based, at least in part, on the editing rules and the DOM tree and the parsed Javascript expression tree; and modify the target portion in accordance with the one or more editing rules. | 16. The computer program product of claim 12 , further operable to: parse the snippet to generate a Document Object Model (DOM) tree and a parsed Javascript expression tree; determine a target portion in the snippet based, at least in part, on the editing rules and the DOM tree and the parsed Javascript expression tree; and modify the target portion in accordance with the one or more editing rules. 18. The computer program product of claim 16 , wherein the computer-readable instructions operable to modify the target portion comprise computer-readable instructions operable to replace at least a substring of the target portion. | 0.5 |
9,965,774 | 3 | 4 | 3. The method of claim 1 , wherein the specified group of content items is associated with a topic and includes different content items associated with the topic. | 3. The method of claim 1 , wherein the specified group of content items is associated with a topic and includes different content items associated with the topic. 4. The method of claim 3 , wherein the topic is determined based on one or more characteristics of the digital magazine server user. | 0.5 |
8,909,616 | 12 | 19 | 12. A method of retrieving documents, the method comprising: receiving by a server a query, the query including a first term, from a requesting application presented by a client access device, the requesting application having a plurality of subject areas, the query associated with a subject area of the plurality of subject areas; selecting a taxonomy that is associated with the subject area of the query, the plurality of subject areas being related to different taxonomies; refining the query based on the taxonomy selected to include a second term in the query; processing the query as refined against at least one database storing documents to retrieve a search result including at least one document; and transmitting the search result to the client access device. | 12. A method of retrieving documents, the method comprising: receiving by a server a query, the query including a first term, from a requesting application presented by a client access device, the requesting application having a plurality of subject areas, the query associated with a subject area of the plurality of subject areas; selecting a taxonomy that is associated with the subject area of the query, the plurality of subject areas being related to different taxonomies; refining the query based on the taxonomy selected to include a second term in the query; processing the query as refined against at least one database storing documents to retrieve a search result including at least one document; and transmitting the search result to the client access device. 19. The method of claim 12 , wherein refining the query includes correcting at least one of spelling, case and syntax of the first term in the query based on the taxonomy selected. | 0.676259 |
8,605,039 | 14 | 35 | 14. A method for text input comprising: receiving input identifying a touch point at a first position wherein said input is a touch input identifying a virtual key and wherein said touch point is the point of touch for the touch input; displaying a first set of candidates comprising a plurality of candidates, the candidates comprising candidate wordstems at a second position offset from said touch point, said first position and said second position both being in a common display area, and interpreting subsequent touch input originating from the touch point as having an offset position at a projected touch point originating at the second position wherein the offset of the projected touch point and an offset of the subsequent touch input are related, wherein at least one of the wordstems comprises a word; receiving input referring to a first candidate being comprised in said first set; receiving a select command of said first candidate; and inputting said selected candidate as text. | 14. A method for text input comprising: receiving input identifying a touch point at a first position wherein said input is a touch input identifying a virtual key and wherein said touch point is the point of touch for the touch input; displaying a first set of candidates comprising a plurality of candidates, the candidates comprising candidate wordstems at a second position offset from said touch point, said first position and said second position both being in a common display area, and interpreting subsequent touch input originating from the touch point as having an offset position at a projected touch point originating at the second position wherein the offset of the projected touch point and an offset of the subsequent touch input are related, wherein at least one of the wordstems comprises a word; receiving input referring to a first candidate being comprised in said first set; receiving a select command of said first candidate; and inputting said selected candidate as text. 35. The method according to claim 14 , wherein the offset of the projected touch point and the offset of the subsequent touch input are related in that the offsets are equal. | 0.768617 |
10,108,599 | 1 | 4 | 1. A computer-implemented method comprising: receiving original content associated with a first language from a first client machine; translating, using one or more processors of a computing system, the original content to machine-translated content associated with a second language; determining individual confidence scores for a plurality of expressions of the machine-translated content, each expression comprising at least one of a word or a phrase; determining individual probability scores for the plurality of expressions; determining individual combined scores for the plurality of expressions from the individual confidence scores and the individual probability scores; determining, based on the individual combined scores for the plurality of expressions, that a part of the machine-translated content fails to satisfy a quality threshold; transmitting a part of the original content corresponding to—the part of the machine-translated content failing to satisfy the quality threshold to a second client machine; and receiving a translation of at least the part of the original content from the second client machine. | 1. A computer-implemented method comprising: receiving original content associated with a first language from a first client machine; translating, using one or more processors of a computing system, the original content to machine-translated content associated with a second language; determining individual confidence scores for a plurality of expressions of the machine-translated content, each expression comprising at least one of a word or a phrase; determining individual probability scores for the plurality of expressions; determining individual combined scores for the plurality of expressions from the individual confidence scores and the individual probability scores; determining, based on the individual combined scores for the plurality of expressions, that a part of the machine-translated content fails to satisfy a quality threshold; transmitting a part of the original content corresponding to—the part of the machine-translated content failing to satisfy the quality threshold to a second client machine; and receiving a translation of at least the part of the original content from the second client machine. 4. The computer-implemented method of claim 1 further including: receiving second original content associated with the first language; translating the second original content to second machine-translated content associated with the second language; determining that the second machine-translated content satisfies the quality threshold; and publishing the second machine-translated content without further translation by any human translator. | 0.586142 |
8,880,529 | 29 | 30 | 29. The apparatus of claim 23 , further comprising: a rating receiving component configured to receive ratings from users indicating a quality of associations between tags in the plurality of tags and associated items of multimedia content; a quality calculation component configured to calculates quality scores for the associations based at least upon the ratings from the users; a tag removal component configured to remove the association of the particular tag and the particular item of multimedia content if a quality score calculated for the association is below a specified threshold. | 29. The apparatus of claim 23 , further comprising: a rating receiving component configured to receive ratings from users indicating a quality of associations between tags in the plurality of tags and associated items of multimedia content; a quality calculation component configured to calculates quality scores for the associations based at least upon the ratings from the users; a tag removal component configured to remove the association of the particular tag and the particular item of multimedia content if a quality score calculated for the association is below a specified threshold. 30. The apparatus of claim 29 , wherein the tag provision component is configured to provide data that causes the user interfaces to display tags whose associations are rated highly more prominently than tags whose associations are rated lowly. | 0.5 |
7,702,691 | 1 | 2 | 1. A computer implemented system to support querying of a software object, comprising: at least one processor; a software object finder, which runs on the at least one processor, to perform the steps of: querying a plurality of databases using a plurality of queries in different query languages, wherein at least one database in the plurality of databases is associated with a different query language from another database in the plurality of databases; mapping a matched data entity from the plurality of databases to one or more instances of the software object; performing relationship caching of one or more additional software objects from the plurality of databases into a cache using queries in different query languages, wherein the one or more additional software objects are related to the software object by one or more predefined relationships, wherein the relationship caching allows the one or more additional software objects to be loaded into the cache in a join query prior to the mapping step, and wherein both the software object and the one or more additional software objects are created and managed by a container and run as part of an application server to support software applications, wherein the software object and the related software objects use one or more deployment descriptors at deploy time, wherein the one or more deployment descriptors allow an editing of structural information about the software object and the one or more additional software objects; and storing the one or more instances of the software object in a result set; and wherein the one or more deployment descriptors of the software object define: the different query languages used by the software object finder; and selection information of the different query languages. | 1. A computer implemented system to support querying of a software object, comprising: at least one processor; a software object finder, which runs on the at least one processor, to perform the steps of: querying a plurality of databases using a plurality of queries in different query languages, wherein at least one database in the plurality of databases is associated with a different query language from another database in the plurality of databases; mapping a matched data entity from the plurality of databases to one or more instances of the software object; performing relationship caching of one or more additional software objects from the plurality of databases into a cache using queries in different query languages, wherein the one or more additional software objects are related to the software object by one or more predefined relationships, wherein the relationship caching allows the one or more additional software objects to be loaded into the cache in a join query prior to the mapping step, and wherein both the software object and the one or more additional software objects are created and managed by a container and run as part of an application server to support software applications, wherein the software object and the related software objects use one or more deployment descriptors at deploy time, wherein the one or more deployment descriptors allow an editing of structural information about the software object and the one or more additional software objects; and storing the one or more instances of the software object in a result set; and wherein the one or more deployment descriptors of the software object define: the different query languages used by the software object finder; and selection information of the different query languages. 2. The system according to claim 1 , wherein: the software object is an entity bean. | 0.898795 |
7,877,343 | 28 | 41 | 28. A system for automatically extracting relational information from a corpus of text without specifying criteria or patterns for controlling extraction of the relational information, comprising: (a) a memory in which a plurality of machine instructions are stored; (b) a storage in which a corpus of text is stored; (c) an interface for coupling to the storage; and (d) a processor that is coupled to the memory and also coupled to the storage through the interface, the processor executing the machine instructions stored in the memory to carry out a plurality of functions, including: (i) employing a first module that determines a set of linguistic features that are domain independent and which can be used to extract relationships between objects from text; and (ii) employing a second module that uses an extractor and the linguistic features to automatically extract a plurality of tuples from the corpus of text, each tuple including a plurality of objects connected by at least one relationship, wherein the extractor provides the plurality of tuples by tagging at least a portion of words within the corpus of text with each tagged word's most probable part of speech, without parsing the corpus of text and without generating a parse tree. | 28. A system for automatically extracting relational information from a corpus of text without specifying criteria or patterns for controlling extraction of the relational information, comprising: (a) a memory in which a plurality of machine instructions are stored; (b) a storage in which a corpus of text is stored; (c) an interface for coupling to the storage; and (d) a processor that is coupled to the memory and also coupled to the storage through the interface, the processor executing the machine instructions stored in the memory to carry out a plurality of functions, including: (i) employing a first module that determines a set of linguistic features that are domain independent and which can be used to extract relationships between objects from text; and (ii) employing a second module that uses an extractor and the linguistic features to automatically extract a plurality of tuples from the corpus of text, each tuple including a plurality of objects connected by at least one relationship, wherein the extractor provides the plurality of tuples by tagging at least a portion of words within the corpus of text with each tagged word's most probable part of speech, without parsing the corpus of text and without generating a parse tree. 41. The system of claim 28 , wherein the machine instructions cause the processor to: (a) create a normalized form of relationships in each tuple that is extracted, by omitting non-essential modifiers of verbs and nouns in the tuple; (b) merge tuples for which objects and their normalized relationships are substantially identical; and (c) count a number of distinct sentences included in the corpus of text from which each retained tuple was extracted. | 0.5 |
8,892,422 | 1 | 2 | 1. A computer implemented method of identifying a phrase weighting of a sequence of words as a function of the position of words present in the sequence of words, comprising: identifying a sequence of words; determining, utilizing one or more processors, a centrality value for each of a plurality of identified words in the sequence of words, the centrality value for each of the identified words based on a co-occurrence consistency with other of the identified words in their respective relative positions in the sequence of words; and determining, utilizing one or more processors, a phrase weighting of the sequence of words based on the determined centrality value for each of the identified words, wherein the phrase weighting provides an indication of the likelihood that the sequence of words is a phrase. | 1. A computer implemented method of identifying a phrase weighting of a sequence of words as a function of the position of words present in the sequence of words, comprising: identifying a sequence of words; determining, utilizing one or more processors, a centrality value for each of a plurality of identified words in the sequence of words, the centrality value for each of the identified words based on a co-occurrence consistency with other of the identified words in their respective relative positions in the sequence of words; and determining, utilizing one or more processors, a phrase weighting of the sequence of words based on the determined centrality value for each of the identified words, wherein the phrase weighting provides an indication of the likelihood that the sequence of words is a phrase. 2. The method of claim 1 , wherein the step of determining the phrase weighting of the sequence of words includes combining the centrality value for each of the identified words. | 0.911706 |
9,917,751 | 3 | 5 | 3. The method of claim 2 , wherein the parsing includes generating tokenized shingles of the application startup data. | 3. The method of claim 2 , wherein the parsing includes generating tokenized shingles of the application startup data. 5. The method of claim 3 , further including using predetermined command parameters to create process rules that identify host-specific processes. | 0.879934 |
7,885,807 | 15 | 16 | 15. A system according to claim 14 , wherein said initial language has two or more different script modes. | 15. A system according to claim 14 , wherein said initial language has two or more different script modes. 16. A system according to claim 15 , wherein said received body of text is in a first script mode and said visual representation thereof is a second, different script mode. | 0.5 |
9,519,716 | 6 | 7 | 6. The method of claim 1 , wherein the search refinement data includes profile information, the method further comprising: accessing the plurality of user profiles, each profile including profile information stored therein; and selecting one of the user profiles as the most relevant user profile for refining the search query. | 6. The method of claim 1 , wherein the search refinement data includes profile information, the method further comprising: accessing the plurality of user profiles, each profile including profile information stored therein; and selecting one of the user profiles as the most relevant user profile for refining the search query. 7. The method of claim 6 further comprising: transmitting an interface to the user to enable the user to select one or more user profiles including an indication to whom the profile is associated; and receiving a user selection command of one of the user profiles for refinement of the search query based on the selected user profile. | 0.5 |
7,631,301 | 1 | 13 | 1. A computer program product for implementing a method for controlling a computing system, the computer program product comprising physical computer storage media containing computer-executable instructions for implementing a method for customizing a binary content file stored at the computing system without recompiling source code associated with the binary content file so as to modify the behavior of the binary content file when the binary content file is executed at a destination computing system, and wherein the method comprises: at a computing system performing an act of translating an object file compiled from source code into one or more compiled binary content files; an act of receiving at a computing system for storage one or more compiled binary content files that each includes one or more variables that are assigned current values; an act of preparing at a computing system one or more non-binary script files that each include one or more references to updated values for one or more of the variables in one or more of the compiled binary content files; inputting for storage at the computing system at which the one or more compiled binary content files are stored the prepared script files, and then performing at a variable initialization module of the computing system an act of processing the one or more non-binary script files to change the current values of one or more variables to updated values for the one or more variables in one or more of the compiled binary content files; and at the computing system where the one or more compiles binary content files are stored, using the variable initialization module to update the one or more compiled binary content files with the change to current values of the one or more variables obtained from the one or more script files without having to recompile the updated binary content files. | 1. A computer program product for implementing a method for controlling a computing system, the computer program product comprising physical computer storage media containing computer-executable instructions for implementing a method for customizing a binary content file stored at the computing system without recompiling source code associated with the binary content file so as to modify the behavior of the binary content file when the binary content file is executed at a destination computing system, and wherein the method comprises: at a computing system performing an act of translating an object file compiled from source code into one or more compiled binary content files; an act of receiving at a computing system for storage one or more compiled binary content files that each includes one or more variables that are assigned current values; an act of preparing at a computing system one or more non-binary script files that each include one or more references to updated values for one or more of the variables in one or more of the compiled binary content files; inputting for storage at the computing system at which the one or more compiled binary content files are stored the prepared script files, and then performing at a variable initialization module of the computing system an act of processing the one or more non-binary script files to change the current values of one or more variables to updated values for the one or more variables in one or more of the compiled binary content files; and at the computing system where the one or more compiles binary content files are stored, using the variable initialization module to update the one or more compiled binary content files with the change to current values of the one or more variables obtained from the one or more script files without having to recompile the updated binary content files. 13. The computer program product as recited in claim 1 , wherein the act of processing the one or more non-binary script files to change the current values of one or more variables to updated values for the one or more variables in one or more of the compiled binary content files comprises the following: an act of processing at least one non-binary script file to change the current values of one or more variables associated with authentication information to updated values for the one or more variables. | 0.562069 |
8,306,826 | 1 | 6 | 1. A method for displaying bi-directional text in a browser program on a computer coupled to drive a display and having an operating system such that the computer normally writes text to the display in a default language in a first, default direction, the method comprising: invoking a bi-directional language support utility program for processing bi-directional language text displayed by the browser program on the computer independent of, and without the need for, bi-directional support provided by the operating system or the browser program, wherein processing bi-directional language text displayed by the browser program comprises: the bi-directional language support utility program opening a window on the display, the bi-directional language support utility program displaying a virtual keyboard in the window to support input of text of a non-default language that is written and displayed in a second direction, opposite to the default direction; the bi-directional language support utility program receiving a string of codes, each code corresponding to a character in a passage of text, at least a portion of which is input in the non-default language using the virtual keyboard; writing codes to the string of codes corresponding to the portion of the passage in the non-default language in a reverse order such that the characters in the non-default language are displayed in proper order in the second direction; and the bi-directional language support utility program displaying the characters corresponding to the codes in the window such that the passage of text is displayed with all portions thereof arranged in respectively appropriate directions. | 1. A method for displaying bi-directional text in a browser program on a computer coupled to drive a display and having an operating system such that the computer normally writes text to the display in a default language in a first, default direction, the method comprising: invoking a bi-directional language support utility program for processing bi-directional language text displayed by the browser program on the computer independent of, and without the need for, bi-directional support provided by the operating system or the browser program, wherein processing bi-directional language text displayed by the browser program comprises: the bi-directional language support utility program opening a window on the display, the bi-directional language support utility program displaying a virtual keyboard in the window to support input of text of a non-default language that is written and displayed in a second direction, opposite to the default direction; the bi-directional language support utility program receiving a string of codes, each code corresponding to a character in a passage of text, at least a portion of which is input in the non-default language using the virtual keyboard; writing codes to the string of codes corresponding to the portion of the passage in the non-default language in a reverse order such that the characters in the non-default language are displayed in proper order in the second direction; and the bi-directional language support utility program displaying the characters corresponding to the codes in the window such that the passage of text is displayed with all portions thereof arranged in respectively appropriate directions. 6. The method according to claim 1 , wherein receiving the string of codes comprises reading codes of characters located in an area of the display overlaid by the window. | 0.564103 |
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