sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
0.99
|
|---|---|---|
1. A computer-implemented system that facilitates data handling, the computer-implemented system having a processing unit executing computer-executable components stored in memory comprising: a data component associated with a datastore of the computer-implemented system that stores a collection of document data catalogs for providing a comprehensive collection of correlated data, the document data catalogs comprising data elements obtained from existing documents, wherein: an existing document is decomposed into a document data catalog for the existing document of corresponding data elements of the existing document according to one or more document templates defining a structure of the data elements of the existing document, each corresponding data element of the document data catalog for the existing document comprises a subset of data included in the existing document, the document data catalog for the existing document includes element metadata for each of the corresponding data elements of the document data catalog for the existing document, the element metadata for each corresponding data element of the document data catalog for the existing document is based on past user interaction with the existing document, and the element metadata for the corresponding data elements of the document data catalog for the existing document defines data element relationships and attributes for correlating the corresponding data elements of the document data catalog for the existing document to related data elements of related document data catalogs for different existing documents; a data selection component for automatically selecting and elevating a subset of the collection of correlated data based in part on current user activity associated with a core document by: selecting a core document data catalog for the core document from the collection of data catalogs and elevating, to a presentation surface, one or more relevant data elements of the core document data catalog based on the element metadata for the corresponding data elements of the core document data catalog in order to display one or more subsets of data included in the core document that are relevant to the current user activity associated with the core document, wherein the element metadata for the corresponding data elements of the core document data catalog is based on past user interaction with the core document, and selecting one or more related document data catalogs for different existing documents from the collection of data catalogs and elevating, to the presentation surface, one or more related data elements of the one or more related document data catalogs based on the element metadata for the one or more relevant data elements of the core document data catalog in order to display one or more subsets of data included in the different existing documents that are related to the one or more subsets of data that are relevant to the current user activity associated with the core document, wherein the element metadata for the one or more relevant data elements of the core document data catalog defines data element relationships and attributes for correlating the one or more relevant data elements of the core document data catalog to the one or more related data elements of the one or more related document data catalogs for the different existing documents; and an interface component for receiving and dynamically presenting the subset of the collection of correlated data in a user interface, wherein the interface component: displays the one or more subsets of data included in the core document that are relevant to the current user activity associated with the core document and the one or more subsets of data included in the different existing documents that are related to the one or more subsets of data that are relevant to the current user activity associated with the core document, and enables editing by a user of the one or more subsets of data included in the core document that are relevant to the current user activity associated with the core document and the one or more subsets of data included in the different existing documents that are related to the one or more subsets of data that are relevant to the current user activity associated with the core document for updating the core document and the different existing documents. | 1. A computer-implemented system that facilitates data handling, the computer-implemented system having a processing unit executing computer-executable components stored in memory comprising: a data component associated with a datastore of the computer-implemented system that stores a collection of document data catalogs for providing a comprehensive collection of correlated data, the document data catalogs comprising data elements obtained from existing documents, wherein: an existing document is decomposed into a document data catalog for the existing document of corresponding data elements of the existing document according to one or more document templates defining a structure of the data elements of the existing document, each corresponding data element of the document data catalog for the existing document comprises a subset of data included in the existing document, the document data catalog for the existing document includes element metadata for each of the corresponding data elements of the document data catalog for the existing document, the element metadata for each corresponding data element of the document data catalog for the existing document is based on past user interaction with the existing document, and the element metadata for the corresponding data elements of the document data catalog for the existing document defines data element relationships and attributes for correlating the corresponding data elements of the document data catalog for the existing document to related data elements of related document data catalogs for different existing documents; a data selection component for automatically selecting and elevating a subset of the collection of correlated data based in part on current user activity associated with a core document by: selecting a core document data catalog for the core document from the collection of data catalogs and elevating, to a presentation surface, one or more relevant data elements of the core document data catalog based on the element metadata for the corresponding data elements of the core document data catalog in order to display one or more subsets of data included in the core document that are relevant to the current user activity associated with the core document, wherein the element metadata for the corresponding data elements of the core document data catalog is based on past user interaction with the core document, and selecting one or more related document data catalogs for different existing documents from the collection of data catalogs and elevating, to the presentation surface, one or more related data elements of the one or more related document data catalogs based on the element metadata for the one or more relevant data elements of the core document data catalog in order to display one or more subsets of data included in the different existing documents that are related to the one or more subsets of data that are relevant to the current user activity associated with the core document, wherein the element metadata for the one or more relevant data elements of the core document data catalog defines data element relationships and attributes for correlating the one or more relevant data elements of the core document data catalog to the one or more related data elements of the one or more related document data catalogs for the different existing documents; and an interface component for receiving and dynamically presenting the subset of the collection of correlated data in a user interface, wherein the interface component: displays the one or more subsets of data included in the core document that are relevant to the current user activity associated with the core document and the one or more subsets of data included in the different existing documents that are related to the one or more subsets of data that are relevant to the current user activity associated with the core document, and enables editing by a user of the one or more subsets of data included in the core document that are relevant to the current user activity associated with the core document and the one or more subsets of data included in the different existing documents that are related to the one or more subsets of data that are relevant to the current user activity associated with the core document for updating the core document and the different existing documents. 4. The system of claim 1 , wherein the interface component presents the subset of the collection of correlated data in a dynamic form that enables viewing of the one or more subsets of data included in the core document that are relevant to the current user activity associated with the core document and the one or more subsets of data included in the different existing documents that are related to the one or more subsets of data that are relevant to the current user activity associated with the core document in different formats. | 0.507724 |
18. The method of claim 13 wherein: the step of receiving the second symbol sequence comprises the step of receiving the second symbol sequence from a user directly served by the switching system. | 18. The method of claim 13 wherein: the step of receiving the second symbol sequence comprises the step of receiving the second symbol sequence from a user directly served by the switching system. 19. The method of claim 18 wherein: the received second symbol sequence is an emergency-services access-number. | 0.969557 |
13. A system for detecting a presence of a third party participating in a monitored telephone conversation, the system comprising: a speech recognition module configured to detect a plurality of characteristics of the monitored telephone conversation; a scoring module configured to score the monitored telephone conversation based on the plurality of characteristics, the scoring including: accessing a scoring database that stores scores of detectable characteristics; looking up a corresponding score for each of the plurality of characteristics; and assigning each of the plurality of characteristics the corresponding scores; a three-way call detection module configured to detect the presence of the third party based on a comparison of the score to a predetermined threshold; and a tagging module configured to associate additional information with the monitored telephone call following the detection of the presence of the third party. | 13. A system for detecting a presence of a third party participating in a monitored telephone conversation, the system comprising: a speech recognition module configured to detect a plurality of characteristics of the monitored telephone conversation; a scoring module configured to score the monitored telephone conversation based on the plurality of characteristics, the scoring including: accessing a scoring database that stores scores of detectable characteristics; looking up a corresponding score for each of the plurality of characteristics; and assigning each of the plurality of characteristics the corresponding scores; a three-way call detection module configured to detect the presence of the third party based on a comparison of the score to a predetermined threshold; and a tagging module configured to associate additional information with the monitored telephone call following the detection of the presence of the third party. 15. The system of claim 13 , wherein the scoring module is configured to score the monitored telephone conversation, and the three-way call detection module is configured to compare the score to the predetermined threshold, after each detection by the speech recognition module of one of the plurality of characteristics of the monitored telephone conversation. | 0.5 |
10. The system of claim 9 , wherein the first metadata are about the first audiovisual portion of the first content object, including at least one of a show description, an airdate and a television rating. | 10. The system of claim 9 , wherein the first metadata are about the first audiovisual portion of the first content object, including at least one of a show description, an airdate and a television rating. 12. The system of claim 10 , wherein the building of the metadata pool using the second metadata includes replacing the first metadata in the metadata pool having the first metadata with the second metadata. | 0.931315 |
12. The system of claim 10 wherein the namespace data store is further configured to store, in association with each of the grouping labels, a characteristic value and wherein the namespace manager is further configured to support searching for a desired characteristic value. | 12. The system of claim 10 wherein the namespace data store is further configured to store, in association with each of the grouping labels, a characteristic value and wherein the namespace manager is further configured to support searching for a desired characteristic value. 13. The system of claim 12 wherein the characteristic value is a category name descriptive of subject matter of a content item. | 0.914559 |
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. 4. The method according to claim 1 , wherein said finding step comprises the steps of: comparing said second image to said first image using said image library wherein said second image and said first image are contained within said image library; finding a relevant image wherein said relevant image is an image from said first relevant document which is highly similar to an image from second relevant document; and finding a third relevant document based on said relevant image and said mapping between said text library and said image library. | 0.502495 |
1. A method of identifying web pages of a world wide web having relevance to a first file, comprising: identifying a plurality of web pages within the world wide web, wherein the plurality of web pages each have a relationship with the first file, wherein the world wide web provides a platform for sharing web pages, and wherein each web page includes a document or information resource that is suitable for the world wide web and is accessible through a web browser; generating, by a system server, a list of inquiries based on the plurality of web pages; providing, by the system server, the list of inquiries to at least one first author of the first file; receiving from the at least one first author at least one response to the list of inquiries; selecting a subset of the plurality of web pages based on the at least one response; storing information related to the selected subset of the plurality of web pages for access if the first file is selected; generating, by the system server, a second list of inquiries based on the plurality of web pages; providing, by the system server, the second list of inquiries to at least one second author of the plurality of web pages; receiving from the at least one second author of the plurality of web pages at least one second response to the second list of inquiries; re-selecting the subset of the plurality of web pages based on the at least one response and the at least one second response; and storing information related to the re-selected subset of the plurality of web pages for access if the first file is selected; providing, by the system server, the re-selected subset of the plurality of web pages or the selected subset of the plurality of web pages to a user that selects the first file; and identifying the at least one second author or the at least one first author to the user. | 1. A method of identifying web pages of a world wide web having relevance to a first file, comprising: identifying a plurality of web pages within the world wide web, wherein the plurality of web pages each have a relationship with the first file, wherein the world wide web provides a platform for sharing web pages, and wherein each web page includes a document or information resource that is suitable for the world wide web and is accessible through a web browser; generating, by a system server, a list of inquiries based on the plurality of web pages; providing, by the system server, the list of inquiries to at least one first author of the first file; receiving from the at least one first author at least one response to the list of inquiries; selecting a subset of the plurality of web pages based on the at least one response; storing information related to the selected subset of the plurality of web pages for access if the first file is selected; generating, by the system server, a second list of inquiries based on the plurality of web pages; providing, by the system server, the second list of inquiries to at least one second author of the plurality of web pages; receiving from the at least one second author of the plurality of web pages at least one second response to the second list of inquiries; re-selecting the subset of the plurality of web pages based on the at least one response and the at least one second response; and storing information related to the re-selected subset of the plurality of web pages for access if the first file is selected; providing, by the system server, the re-selected subset of the plurality of web pages or the selected subset of the plurality of web pages to a user that selects the first file; and identifying the at least one second author or the at least one first author to the user. 2. The method of claim 1 , wherein identifying the at least one first author comprises providing the user with a name, qualifications or institution of the at least one first author. | 0.56425 |
21. A computer-implemented method comprising: receiving, using a microphone of a computing device, a request to designate a particular candidate hotword that is not currently designated as a hotword, as a hotword; determining that the particular candidate hotword satisfies one or more hotword suitability criteria; in response to determining that the particular candidate hotword satisfies one or more hotword suitability criteria, designating the particular candidate hotword as a custom hotword; after designating the particular candidate hotword as a custom hotword, determining that subsequently received audio data received using the microphone of the computing device includes sounds that are characteristic of an utterance of the custom hotword; in response to determining that the subsequently received audio data includes sounds that are characteristic of an utterance of the custom hotword: providing, on a display of the computing device or using a speaker of the computing device, an indication that the custom hotword was detected; and causing the computing device to enter a ready state for receiving and processing voice commands uttered after the utterance of the custom hotword. | 21. A computer-implemented method comprising: receiving, using a microphone of a computing device, a request to designate a particular candidate hotword that is not currently designated as a hotword, as a hotword; determining that the particular candidate hotword satisfies one or more hotword suitability criteria; in response to determining that the particular candidate hotword satisfies one or more hotword suitability criteria, designating the particular candidate hotword as a custom hotword; after designating the particular candidate hotword as a custom hotword, determining that subsequently received audio data received using the microphone of the computing device includes sounds that are characteristic of an utterance of the custom hotword; in response to determining that the subsequently received audio data includes sounds that are characteristic of an utterance of the custom hotword: providing, on a display of the computing device or using a speaker of the computing device, an indication that the custom hotword was detected; and causing the computing device to enter a ready state for receiving and processing voice commands uttered after the utterance of the custom hotword. 22. The computer-implemented method of claim 21 , further comprising: determining that the particular candidate hotword includes a particular quantity of syllables or phones; and wherein determining that the particular candidate hotword satisfies one or more hotword suitability criteria comprises determining, based at least on the particular quantity of syllables or phones, that the particular candidate hotword satisfies one or more hotword suitability criteria. | 0.692589 |
13. The system of claim 12 , further comprising an executable transformer generable to produce the output document transformed from the input document. | 13. The system of claim 12 , further comprising an executable transformer generable to produce the output document transformed from the input document. 14. The system of claim 13 , wherein the executable transformer comprises: a parser to parse the input document; an optimized program code to transform the input document to produce the output document. | 0.922311 |
17. A system comprising: a storage device; a processor coupled to the storage device, the processor to: identifying a plurality of document features in a document image; correlate each of the plurality of document features with one or more of different document classes; selecting a first group of document features and a second group of document features from the plurality of document features based on document feature types of the plurality of document features; for the first group of document features, generate a first decision tree that includes one or more nodes corresponding to document features of a document feature type corresponding to the first group; for the second group of document features, generate a second decision tree that includes one or more nodes corresponding to document features of a document feature type corresponding to the second group; and associate the document image with one of the different document classes based at least in part on the first decision tree and the second decision tree. | 17. A system comprising: a storage device; a processor coupled to the storage device, the processor to: identifying a plurality of document features in a document image; correlate each of the plurality of document features with one or more of different document classes; selecting a first group of document features and a second group of document features from the plurality of document features based on document feature types of the plurality of document features; for the first group of document features, generate a first decision tree that includes one or more nodes corresponding to document features of a document feature type corresponding to the first group; for the second group of document features, generate a second decision tree that includes one or more nodes corresponding to document features of a document feature type corresponding to the second group; and associate the document image with one of the different document classes based at least in part on the first decision tree and the second decision tree. 18. The system of claim 17 , wherein: the feature is a feature that was previously determined to be a feature capable of distinguishing the document image or a document that comprises the document image, and the feature was previously identified by analysis of a plurality of training documents each having at least one unique feature different from at least one of the other training documents. | 0.547847 |
8. The method according to claim 1 , wherein the character string is a ZIP code and the request information is a city name. | 8. The method according to claim 1 , wherein the character string is a ZIP code and the request information is a city name. 9. The method according to claim 8 , wherein the request information corresponds to an element of the first ambiguous speech recognition result, the element being inconsistent with the character string. | 0.937074 |
12. The discussion-topic server of claim 10 , wherein the at least one processor is further configured to execute instructions that adapt the discussion-topic server to: receive a request from a second device of the at least one second devices for discussion content associated with the first discussion topic; responsive to receiving the request from the second device, transmit the active tag data and the first discussion content to the second device; receive, from the second device, an indication that an active button or active text associated with the active tag data has been selected; and perform, responsive to receiving the indication, a functional operation associated with the active tag. | 12. The discussion-topic server of claim 10 , wherein the at least one processor is further configured to execute instructions that adapt the discussion-topic server to: receive a request from a second device of the at least one second devices for discussion content associated with the first discussion topic; responsive to receiving the request from the second device, transmit the active tag data and the first discussion content to the second device; receive, from the second device, an indication that an active button or active text associated with the active tag data has been selected; and perform, responsive to receiving the indication, a functional operation associated with the active tag. 15. The discussion-topic server of claim 12 , wherein the argument comprises an identifier for a second discussion topic. | 0.897387 |
15. A computer program product for generating a synonym list from a natural language query, the computer program product comprising a non-transitory computer usable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method comprising: preparing a first feature vector from a natural language query and preparing a second feature vector from a result of the natural language query; determining, using a processor, whether a combination of a first feature from the first feature vector and a second feature from the second feature vector is included as a synonym pair in the existing thesaurus; and generating the synonym list by adding the combination to the synonym list when the determination is positive. | 15. A computer program product for generating a synonym list from a natural language query, the computer program product comprising a non-transitory computer usable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method comprising: preparing a first feature vector from a natural language query and preparing a second feature vector from a result of the natural language query; determining, using a processor, whether a combination of a first feature from the first feature vector and a second feature from the second feature vector is included as a synonym pair in the existing thesaurus; and generating the synonym list by adding the combination to the synonym list when the determination is positive. 20. The computer program product according to claim 15 , wherein the synonym list is for a specific purpose. | 0.669076 |
1. A social networking website system that supports user interactions in a plurality of social networks, the social networking website system comprising: a server configured to create a new social network automatically, the server enabling communication among a plurality of mobile devices used by a corresponding plurality of users via the new social network, each of the plurality of mobile devices identifies a corresponding current location information based on GPS coordinates; the server automatically, without need of user consent, without any upfront registration requirements or invitations, without employing invitations and explicit user acceptance, automatically registering and including a first user among the plurality of users in the new social network based on the GPS coordinates from the corresponding one of the plurality of mobile devices; and the social networking website system facilitating creation and sharing of new postings, the new postings each comprising audio inputs recorded by the user, a digital photo recorded, a video recorded, and textual inputs provided by the user on a corresponding one the plurality of mobile devices; and wherein a current location to social networks mapping is used to determine appropriate social networks and associated social groups, in the street, city, county, region, state or country in which the user can participate in; wherein the social networking website system also provides each user the ability to create their own social groups to share postings on common interests or affiliations. | 1. A social networking website system that supports user interactions in a plurality of social networks, the social networking website system comprising: a server configured to create a new social network automatically, the server enabling communication among a plurality of mobile devices used by a corresponding plurality of users via the new social network, each of the plurality of mobile devices identifies a corresponding current location information based on GPS coordinates; the server automatically, without need of user consent, without any upfront registration requirements or invitations, without employing invitations and explicit user acceptance, automatically registering and including a first user among the plurality of users in the new social network based on the GPS coordinates from the corresponding one of the plurality of mobile devices; and the social networking website system facilitating creation and sharing of new postings, the new postings each comprising audio inputs recorded by the user, a digital photo recorded, a video recorded, and textual inputs provided by the user on a corresponding one the plurality of mobile devices; and wherein a current location to social networks mapping is used to determine appropriate social networks and associated social groups, in the street, city, county, region, state or country in which the user can participate in; wherein the social networking website system also provides each user the ability to create their own social groups to share postings on common interests or affiliations. 8. The social networking website system of claim 1 wherein a mobile device of a user enables pre-registration, of the mobile device with the server for a default social network, at a point of sale. | 0.604863 |
1. A method implemented at least in part by a computing device for natural language dependent stream ciphers, the method comprising: receiving an input in a first natural language; generating encrypted output comprising a natural language dependent stream cipher from the input in the first natural language, the generating comprising: translating the input in the first natural language to an input in a second natural language; and wherein the first and the second natural languages are not a same natural language, and wherein each of the first and second natural languages is a particular language spoken by human beings for normal communications: performing an XOR operation on the binary Unicode representation of the input in the second natural language and a binary key to generate an encrypted output; outputting the encrypted output to a computing device for access by a viewer capable of decrypting the encrypted output. | 1. A method implemented at least in part by a computing device for natural language dependent stream ciphers, the method comprising: receiving an input in a first natural language; generating encrypted output comprising a natural language dependent stream cipher from the input in the first natural language, the generating comprising: translating the input in the first natural language to an input in a second natural language; and wherein the first and the second natural languages are not a same natural language, and wherein each of the first and second natural languages is a particular language spoken by human beings for normal communications: performing an XOR operation on the binary Unicode representation of the input in the second natural language and a binary key to generate an encrypted output; outputting the encrypted output to a computing device for access by a viewer capable of decrypting the encrypted output. 2. The method of claim 1 wherein the second natural language is selected automatically. | 0.632502 |
1. A method of identifying files of a file storage system having relevance to a first file, comprising: identifying a plurality of files within the file storage system, wherein the plurality of files each have a relationship with the first file, and wherein the file storage system allows sharing of the plurality of files between multiple users through a network; generating, by a system server, a list of inquiries based on the plurality of files, wherein the list of inquiries includes search terms used in a search that identified the plurality of files; providing, by the system server, the list of inquiries to at least one collaborator of the first file; receiving from the at least one collaborator at least one response to the list of inquiries; selecting a subset of the plurality of files based on the at least one response; storing information related to the selected subset of the plurality of files for access if the first file is selected; providing, by the system server, the selected subset of the plurality of files to a user who has performed a search on a search term that yields a plurality of results containing the first file; and identifying the at least one collaborator to the user. | 1. A method of identifying files of a file storage system having relevance to a first file, comprising: identifying a plurality of files within the file storage system, wherein the plurality of files each have a relationship with the first file, and wherein the file storage system allows sharing of the plurality of files between multiple users through a network; generating, by a system server, a list of inquiries based on the plurality of files, wherein the list of inquiries includes search terms used in a search that identified the plurality of files; providing, by the system server, the list of inquiries to at least one collaborator of the first file; receiving from the at least one collaborator at least one response to the list of inquiries; selecting a subset of the plurality of files based on the at least one response; storing information related to the selected subset of the plurality of files for access if the first file is selected; providing, by the system server, the selected subset of the plurality of files to a user who has performed a search on a search term that yields a plurality of results containing the first file; and identifying the at least one collaborator to the user. 6. The method of claim 1 , further comprising providing, by the system server, the selected subset of the plurality of files to a user that selects the first file. | 0.643573 |
1. A computer-implemented process for establishing a measure of an image-based semantic distance between semantic concepts, comprising: using a computer to perform the following process actions: respectively computing a semantic concept representation for each concept based on images associated with the concept; and computing a degree of difference between two semantic concept representations to produce said image-based semantic distance measure for the pair of corresponding semantic concepts. | 1. A computer-implemented process for establishing a measure of an image-based semantic distance between semantic concepts, comprising: using a computer to perform the following process actions: respectively computing a semantic concept representation for each concept based on images associated with the concept; and computing a degree of difference between two semantic concept representations to produce said image-based semantic distance measure for the pair of corresponding semantic concepts. 9. The process of claim 1 , further comprising the process action of computing an image-based semantic distance measure between each of multiple pairs of semantic concepts, and using the measures in a semantic concept clustering application. | 0.774219 |
8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving a user query in a first language; identifying a local language associated with a current location of a user device; and when the first language is distinct from the local language: querying a database based on the user query, to yield search results, wherein the search results comprise (1) a first result having a first word in the first language and a second word in the local language and (2) a second result predominantly in the first language; prioritizing the search results by first presenting the first result followed by the second result, to yield prioritized search results; and presenting the prioritized search results with an indication associated with the second result identifying that the second result is predominantly in the first language. | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving a user query in a first language; identifying a local language associated with a current location of a user device; and when the first language is distinct from the local language: querying a database based on the user query, to yield search results, wherein the search results comprise (1) a first result having a first word in the first language and a second word in the local language and (2) a second result predominantly in the first language; prioritizing the search results by first presenting the first result followed by the second result, to yield prioritized search results; and presenting the prioritized search results with an indication associated with the second result identifying that the second result is predominantly in the first language. 13. The system of claim 8 , wherein the indication of amounts further comprises presenting a graphical representation illustrating how much of the document is in the first language and how much is in the local language, the graphical representation comprising a flag. | 0.562081 |
4. The method of claim 1 , wherein said evaluating comprises: calculating a relative probability that a given token has been generated by a model of interest; calculating a relative probability that the given token has been generated by a model that is not of interest; comparing the calculated relative probabilities; and associating each token with the model that yields the greater relative probability. | 4. The method of claim 1 , wherein said evaluating comprises: calculating a relative probability that a given token has been generated by a model of interest; calculating a relative probability that the given token has been generated by a model that is not of interest; comparing the calculated relative probabilities; and associating each token with the model that yields the greater relative probability. 5. The method of claim 4 , wherein a Markov model is used to determine the relative probabilities. | 0.786392 |
1. A method for providing data to a web browser, comprising the steps of: generating the data which includes a display region having associated content; determining if a pre-selected locale is mandatory; if the pre-selected locale is mandatory, formatting at least a portion of the associated content according to the pre-selected locale when generating the data; if the pre-selected locale is not mandatory: identifying a user-selected locale, and formatting at least a portion of the associated content according to the user-selected locale when generating the data; and transmitting the data to the web browser of a computer. | 1. A method for providing data to a web browser, comprising the steps of: generating the data which includes a display region having associated content; determining if a pre-selected locale is mandatory; if the pre-selected locale is mandatory, formatting at least a portion of the associated content according to the pre-selected locale when generating the data; if the pre-selected locale is not mandatory: identifying a user-selected locale, and formatting at least a portion of the associated content according to the user-selected locale when generating the data; and transmitting the data to the web browser of a computer. 9. The method of claim 1 , further comprising the step of: determining whether the user selected locale is supported; if the user-selected locale is not supported then, formatting the associated content according to a default locale when generating the data. | 0.52993 |
1. A method in a Multitenant Database System, the method comprising: generating tenant-level statistics for each of a plurality of tenants having data stored within a database system of the Multitenant Database System, wherein the database system includes one or more data tables to store the data, each data table having one or more columns defining data categories and one or more rows associated with one or more tenants among the plurality of tenants having data stored within the data tables; receiving communications from user systems over a network to request tenant-level data from the Multitenant Database System, the communications received at an interface of the Multitenant Database System; generating one or more queries designed to access the information requested; and optimizing the one or more queries based on the tenant-level statistics to increase system performance for an individual tenant among the plurality of tenants whose data is being searched. | 1. A method in a Multitenant Database System, the method comprising: generating tenant-level statistics for each of a plurality of tenants having data stored within a database system of the Multitenant Database System, wherein the database system includes one or more data tables to store the data, each data table having one or more columns defining data categories and one or more rows associated with one or more tenants among the plurality of tenants having data stored within the data tables; receiving communications from user systems over a network to request tenant-level data from the Multitenant Database System, the communications received at an interface of the Multitenant Database System; generating one or more queries designed to access the information requested; and optimizing the one or more queries based on the tenant-level statistics to increase system performance for an individual tenant among the plurality of tenants whose data is being searched. 13. The method of claim 1 , wherein optimizing the one or more queries based on the tenant-level statistics comprises choosing a filter which is most selective for fields that contain enumerated lists of values. | 0.557296 |
1. A method for monitoring multiple online resources in different formats, the method comprising the steps of: identifying a plurality of online resources to monitor, the plurality of online resources being stored in a plurality of formats, at least one of the plurality of online resources including data in a non-strict architectural structure; identifying whether each of the online resources of the plurality of online resources is a non-HyperText Markup Language application; for each of the plurality of online resources from the non-HyperText Markup Language application, converting the online resource from the non-HyperText Markup Language application to a HyperText Markup Language application; for each of the online resources of the plurality of online resources, determining whether the online resource meets a minimum level of content structure to allow an Extensible Style Sheet Transform to be used to convert the online resource to the strict formatted file; converting each of the plurality of online resources that is determined as meeting the minimum level of content structure to a strict formatted file having a common format, wherein the strict formatted file is an Extensible Markup Language application, and wherein data in the plurality of formats of the plurality of online resources is converted into a strict architectural structure; converting each of the plurality of online resources that is determined as not meeting the minimum level of content structure to a strict formatted file, wherein the strict formatted file is a document object model of the online resource; after converting to the strict formatted file, identifying relevant data in each of the strict formatted files based on the strict architectural structure of the data using an analytic parser; and comparing the identified relevant data to a most recent archived copy of the identified relevant data to determine whether the identified relevant data has been altered. | 1. A method for monitoring multiple online resources in different formats, the method comprising the steps of: identifying a plurality of online resources to monitor, the plurality of online resources being stored in a plurality of formats, at least one of the plurality of online resources including data in a non-strict architectural structure; identifying whether each of the online resources of the plurality of online resources is a non-HyperText Markup Language application; for each of the plurality of online resources from the non-HyperText Markup Language application, converting the online resource from the non-HyperText Markup Language application to a HyperText Markup Language application; for each of the online resources of the plurality of online resources, determining whether the online resource meets a minimum level of content structure to allow an Extensible Style Sheet Transform to be used to convert the online resource to the strict formatted file; converting each of the plurality of online resources that is determined as meeting the minimum level of content structure to a strict formatted file having a common format, wherein the strict formatted file is an Extensible Markup Language application, and wherein data in the plurality of formats of the plurality of online resources is converted into a strict architectural structure; converting each of the plurality of online resources that is determined as not meeting the minimum level of content structure to a strict formatted file, wherein the strict formatted file is a document object model of the online resource; after converting to the strict formatted file, identifying relevant data in each of the strict formatted files based on the strict architectural structure of the data using an analytic parser; and comparing the identified relevant data to a most recent archived copy of the identified relevant data to determine whether the identified relevant data has been altered. 12. The method of claim 1 further comprising the step of automatically updating a database. | 0.528046 |
7. The method of claim 1 , further comprising the steps of: receiving a second extraction instruction to extract a second identified portion of the decrypted document; determining that the extraction instruction does not comply with one or more of the extraction permissives; and aborting the second extraction instruction. | 7. The method of claim 1 , further comprising the steps of: receiving a second extraction instruction to extract a second identified portion of the decrypted document; determining that the extraction instruction does not comply with one or more of the extraction permissives; and aborting the second extraction instruction. 8. The method of claim 7 , further comprising the steps of: communicating a message that the second extraction instruction does not comply with one or more of the extraction permissives; and indicating one or more extraction alternatives that do comply with the one or more extraction permissives. | 0.918453 |
1. A computer-implemented method, comprising: determining, using one or more processors, a first score for a first user based on interactions by other users with messages of the first user, or a quantity of other users that subscribe to messages of the first user; determining, using one or more processors, a second score for a second user based on interactions by other users with messages of the second user, or a quantity of other users that subscribe to messages of the second user; selecting a third user to which the first user and the second user subscribe; determining, using one or more processors, a third score for the third user, based on the first score for the first user and the second score for the second user; using the third score for the third user in a determination of a score for a particular message of the third user; ranking the particular message of the third user with respect to other messages of other users based on the score for the particular message and scores for the other messages; and providing the particular message and the other messages for display by a computing device in a ranked order according to the score for the particular message and the scores for the other messages. | 1. A computer-implemented method, comprising: determining, using one or more processors, a first score for a first user based on interactions by other users with messages of the first user, or a quantity of other users that subscribe to messages of the first user; determining, using one or more processors, a second score for a second user based on interactions by other users with messages of the second user, or a quantity of other users that subscribe to messages of the second user; selecting a third user to which the first user and the second user subscribe; determining, using one or more processors, a third score for the third user, based on the first score for the first user and the second score for the second user; using the third score for the third user in a determination of a score for a particular message of the third user; ranking the particular message of the third user with respect to other messages of other users based on the score for the particular message and scores for the other messages; and providing the particular message and the other messages for display by a computing device in a ranked order according to the score for the particular message and the scores for the other messages. 3. The computer-implemented method of claim 1 , wherein: determining the first score for the first user is based on a quantity of comments that other users have submitted as replies to the messages of the first user, and determining the second score for the second user is based on a quantity of comments that other users have submitted as replies to the messages of the second user. | 0.715134 |
12. A method for improving user navigation of a multi-page document on a small screen user device, the method comprising: presenting one page of the multi-page document to a user on a screen of the small screen user device; caching the most recently viewed one or more pages of the multi-page document viewed by the user as the user progresses through the multi-page document; deleting cached data associated with one or more successive pages when the user goes back to an earlier page of the multi-page document; receiving a request from the user to view the multi-page document as a full-page document; comparing text of the cached most recently viewed pages to text of the full-page document to determine a first appearance of non-duplicative text in the full-page document; returning all pages of the full-page document together; and presenting the full-page document to the user with the screen of the small screen user device showing a page containing the first appearance of non-duplicative text in the full-page document. | 12. A method for improving user navigation of a multi-page document on a small screen user device, the method comprising: presenting one page of the multi-page document to a user on a screen of the small screen user device; caching the most recently viewed one or more pages of the multi-page document viewed by the user as the user progresses through the multi-page document; deleting cached data associated with one or more successive pages when the user goes back to an earlier page of the multi-page document; receiving a request from the user to view the multi-page document as a full-page document; comparing text of the cached most recently viewed pages to text of the full-page document to determine a first appearance of non-duplicative text in the full-page document; returning all pages of the full-page document together; and presenting the full-page document to the user with the screen of the small screen user device showing a page containing the first appearance of non-duplicative text in the full-page document. 18. The method of claim 12 , wherein the presentation of the full-page document on the screen of the small screen user device includes at least one line of leading text before the presentation of the first appearance of non-duplicative text. | 0.569845 |
1. A circuit arrangement for secure data processing for program data with a protected data record, comprising: an internal memory which provides a protected data record having instruction words and at least one first check word associated with the instruction words; an arithmetic and logic unit having an input coupled to the internal memory and which outputs the at least one first check word from the applied protected data record; a checking apparatus having an input coupled between the internal memory and the arithmetic and logic unit and which allocates at least one second check word to the instruction words in the protected data record; and a comparison apparatus having respective inputs coupled to the checking apparatus and the arithmetic and logic unit and which compares the at least one first check word with the at least one second check word and outputs an alarm signal when the at least one first check word does not match the at least one second check word. | 1. A circuit arrangement for secure data processing for program data with a protected data record, comprising: an internal memory which provides a protected data record having instruction words and at least one first check word associated with the instruction words; an arithmetic and logic unit having an input coupled to the internal memory and which outputs the at least one first check word from the applied protected data record; a checking apparatus having an input coupled between the internal memory and the arithmetic and logic unit and which allocates at least one second check word to the instruction words in the protected data record; and a comparison apparatus having respective inputs coupled to the checking apparatus and the arithmetic and logic unit and which compares the at least one first check word with the at least one second check word and outputs an alarm signal when the at least one first check word does not match the at least one second check word. 4. The circuit anangement of claim 1 , wherein the arithmetic and logic unit processes program data which comprise at least one protected data record. | 0.541468 |
2. A method for compiling source code to p-code or machine-language instructions, wherein the source code contains high-level source code with embedded SQL statements, said method comprising the steps of: reading the source code one line at a time to generate a read line of source code; determining whether said read line of source code is high level source code or an SQL statement; and compiling said read line of source code to p-code or machine-language instructions, wherein if said read line of source code is an SQL statement, said compilation of said read line of source code occurs in a one-pass parsing mechanism. | 2. A method for compiling source code to p-code or machine-language instructions, wherein the source code contains high-level source code with embedded SQL statements, said method comprising the steps of: reading the source code one line at a time to generate a read line of source code; determining whether said read line of source code is high level source code or an SQL statement; and compiling said read line of source code to p-code or machine-language instructions, wherein if said read line of source code is an SQL statement, said compilation of said read line of source code occurs in a one-pass parsing mechanism. 6. A method for compiling source code to p-code or machine-language instructions according to claim 2, wherein said one-pass parsing mechanism comprises translating said SQL statement to a plurality of API statements. | 0.810764 |
41. A data collection system comprising: a data collection terminal having a encoded information reader device; and a computer spaced apart from said data collection terminal that receives from a user identification of first and second files for transfer to said data collection terminal, prompts a user to enter at least one action indicator for each file identified by a user, creates a single data package incorporating file data corresponding to the identified first and second files and at least one action indicator, and enables a transfer of the single data package to said data collection terminal. | 41. A data collection system comprising: a data collection terminal having a encoded information reader device; and a computer spaced apart from said data collection terminal that receives from a user identification of first and second files for transfer to said data collection terminal, prompts a user to enter at least one action indicator for each file identified by a user, creates a single data package incorporating file data corresponding to the identified first and second files and at least one action indicator, and enables a transfer of the single data package to said data collection terminal. 62. The data collection system of claim 41 , wherein file data corresponding to said first file is encrypted and file data corresponding to said second file is not encrypted. | 0.817456 |
1. A computer-based method of coding a document for presentation on a presentation apparatus, comprising: defining a structure section which specifies a structure for content of said document in terms of document elements, wherein the defining of the structure section includes defining the structure section in a hierarchical structured format which specifies the structure of said document in terms of said document elements; defining a time section including a time constraint which acts upon document elements in the structure section, wherein the defining of the time section includes defining the time section in said hierarchical structured format that includes said time constraint, wherein the time constraint specifies that the document elements it acts upon have to be presented consecutively; linking the time section with the structure section to establish the coding of the document, wherein the structure section and the time section are defined in separate sections, and wherein the coding of the document constitutes an hierarchical structured application; defining a style section in the hierarchical structured format which includes style rules specifying properties of one or more document elements selected from the structure section, the time constraint acts upon a style rule of the style section, the linking including linking the time section, style section, and the structure section to establish structural, style, and temporal coding of the document, wherein the document elements in the structure section which are acted upon by the time constraint are selected by a CSS (Cascading Style Sheets) selector syntax; and at least one of (i) presenting the coded document on a presentation apparatus and (ii) storing the coded document for subsequent presentation. | 1. A computer-based method of coding a document for presentation on a presentation apparatus, comprising: defining a structure section which specifies a structure for content of said document in terms of document elements, wherein the defining of the structure section includes defining the structure section in a hierarchical structured format which specifies the structure of said document in terms of said document elements; defining a time section including a time constraint which acts upon document elements in the structure section, wherein the defining of the time section includes defining the time section in said hierarchical structured format that includes said time constraint, wherein the time constraint specifies that the document elements it acts upon have to be presented consecutively; linking the time section with the structure section to establish the coding of the document, wherein the structure section and the time section are defined in separate sections, and wherein the coding of the document constitutes an hierarchical structured application; defining a style section in the hierarchical structured format which includes style rules specifying properties of one or more document elements selected from the structure section, the time constraint acts upon a style rule of the style section, the linking including linking the time section, style section, and the structure section to establish structural, style, and temporal coding of the document, wherein the document elements in the structure section which are acted upon by the time constraint are selected by a CSS (Cascading Style Sheets) selector syntax; and at least one of (i) presenting the coded document on a presentation apparatus and (ii) storing the coded document for subsequent presentation. 6. The method of presenting a coded document, which is coded in accordance with the method claimed in claim 1 , comprising applying a time constraint of the time section to the document elements of the structure section which the time constraints acts upon. | 0.645485 |
12. The method of claim 3 , wherein said highlighting of one or more identifiable segments comprises the steps of: (h1) identifying as Segment of Interest a segment of said data file which contains at least one sub-segment to be highlighted; (h2) receiving a datum associated with the Segment of Interest; (h3) receiving the instructions to compute by machine the boundaries of said Segment of Interest using said datum; (h4) saving in a database the boundaries of said Segment of Interest computed by machine; (h5) highlighting one or more sub-segments within said Segment of Interest. | 12. The method of claim 3 , wherein said highlighting of one or more identifiable segments comprises the steps of: (h1) identifying as Segment of Interest a segment of said data file which contains at least one sub-segment to be highlighted; (h2) receiving a datum associated with the Segment of Interest; (h3) receiving the instructions to compute by machine the boundaries of said Segment of Interest using said datum; (h4) saving in a database the boundaries of said Segment of Interest computed by machine; (h5) highlighting one or more sub-segments within said Segment of Interest. 15. The method of claim 12 wherein said data file is a video file, and said instructions are used to compute as visual part of the Segment of Interest a box contained in the visual images of the video file. | 0.841213 |
20. A non-transitory machine-readable storage medium having stored thereon instructions which when executed cause a processor to perform a method for aggregating an information stream of content from a content sharing service, the method, comprising: determining the interests of a user from online activity of the user with respect to the content sharing service; identifying meanings or context surrounding content to be presented among the information stream for the user; using the meanings or the context surrounding the content in relation to the interests of the user, to increase or decrease visibility of the content among other pieces of content in the information stream to be presented to the user; wherein, the visibility of the content is increased or decreased for presentation in a user interface component of a third-party platform independent from the content sharing service; wherein, the interests of the user is also determined by the platform; and wherein, the meanings or the context surrounding the content is also determined by the third-party platform. | 20. A non-transitory machine-readable storage medium having stored thereon instructions which when executed cause a processor to perform a method for aggregating an information stream of content from a content sharing service, the method, comprising: determining the interests of a user from online activity of the user with respect to the content sharing service; identifying meanings or context surrounding content to be presented among the information stream for the user; using the meanings or the context surrounding the content in relation to the interests of the user, to increase or decrease visibility of the content among other pieces of content in the information stream to be presented to the user; wherein, the visibility of the content is increased or decreased for presentation in a user interface component of a third-party platform independent from the content sharing service; wherein, the interests of the user is also determined by the platform; and wherein, the meanings or the context surrounding the content is also determined by the third-party platform. 23. The method of claim 20 , wherein, the online activity is further determined from activity of the user on other content sharing services. | 0.563137 |
41. The method of claim 37 including the steps of: generating a list of words from said text and tabulation typesetting data; and combining said word list for retaining as index data in said master memory. | 41. The method of claim 37 including the steps of: generating a list of words from said text and tabulation typesetting data; and combining said word list for retaining as index data in said master memory. 43. The method of claim 41 including the step of associating each said word of said word list with a select field associated therewith to provide a unique word list for retention as index data in said master memory. | 0.943603 |
5. A computerized device comprising: a processor; and a user interface operatively connected to said processor, said user interface receiving a question comprising question terms into, said processor automatically searching sources of data containing passages using a processor of said computerized device to produce candidate answers to said question, said searching being based on said question terms, and said searching identifying sources of evidence that support each of said candidate answers based on scoring features that indicate whether said candidate answers are correct answers to said question, said sources of evidence comprising passages, said processor automatically creating a scoring feature-specific matrix for each scoring feature of said scoring features, each said scoring feature-specific matrix specifying all different combinations of said passages, said candidate answers, and said question terms and comprising score fields for score values each specific question term with respect to a specific passage and a specific candidate answer, each score field containing a score value indicating how a passage term of said specific passage aligns with said specific question term to support said specific candidate answer as being a correct answer to said question, and multiple ones of said different combinations of said passages, said candidate answers and said question terms forming vectors, said processor automatically combining said vectors to produce a collapsed score for each of said question terms, said processor automatically combining collapsed scores to produce a combined score for each of said candidate answers, and said processor automatically ranking said candidate answers based on said combined score. | 5. A computerized device comprising: a processor; and a user interface operatively connected to said processor, said user interface receiving a question comprising question terms into, said processor automatically searching sources of data containing passages using a processor of said computerized device to produce candidate answers to said question, said searching being based on said question terms, and said searching identifying sources of evidence that support each of said candidate answers based on scoring features that indicate whether said candidate answers are correct answers to said question, said sources of evidence comprising passages, said processor automatically creating a scoring feature-specific matrix for each scoring feature of said scoring features, each said scoring feature-specific matrix specifying all different combinations of said passages, said candidate answers, and said question terms and comprising score fields for score values each specific question term with respect to a specific passage and a specific candidate answer, each score field containing a score value indicating how a passage term of said specific passage aligns with said specific question term to support said specific candidate answer as being a correct answer to said question, and multiple ones of said different combinations of said passages, said candidate answers and said question terms forming vectors, said processor automatically combining said vectors to produce a collapsed score for each of said question terms, said processor automatically combining collapsed scores to produce a combined score for each of said candidate answers, and said processor automatically ranking said candidate answers based on said combined score. 7. The computerized device according to claim 5 , said passages comprising text passages. | 0.566894 |
10. A computer program product tangibly embodied in a machine-readable storage device for correcting an XML electronic document, the XML electronic document having a structure, the product comprising instructions operable to cause one or more data processing apparatus to perform operations comprising: identifying a validation error in the XML electronic document structure, the validation error being an aspect of the XML electronic document structure that fails to conform to rules of an XML document type definition or an XML schema, the rules being associated with the XML electronic document, the validation error being of a particular kind, wherein identifying the validation error comprises building a deterministic finite automaton from a content model defined in a document type definition of the XML electronic document and identifying the validation error using the deterministic finite automaton; selecting a suggestion template from among multiple suggestion templates according to the particular kind of the validation error, and using the selected suggestion template to suggest to a user suggested corrections that are predefined in the template for the particular kind of validation error, the selected suggestion template including logic necessary for modifying the XML electronic document structure in conformance with the rules of the XML document type definition or the XML schema, wherein modifying the XML electronic document structure comprises retagging an element in the XML electronic document structure and moving an element from a current location to a new location in the XML electronic document structure; receiving an input selecting one of the suggested corrections; and using the logic in the selected suggestion template to apply the correction selected by the input to the XML electronic document. | 10. A computer program product tangibly embodied in a machine-readable storage device for correcting an XML electronic document, the XML electronic document having a structure, the product comprising instructions operable to cause one or more data processing apparatus to perform operations comprising: identifying a validation error in the XML electronic document structure, the validation error being an aspect of the XML electronic document structure that fails to conform to rules of an XML document type definition or an XML schema, the rules being associated with the XML electronic document, the validation error being of a particular kind, wherein identifying the validation error comprises building a deterministic finite automaton from a content model defined in a document type definition of the XML electronic document and identifying the validation error using the deterministic finite automaton; selecting a suggestion template from among multiple suggestion templates according to the particular kind of the validation error, and using the selected suggestion template to suggest to a user suggested corrections that are predefined in the template for the particular kind of validation error, the selected suggestion template including logic necessary for modifying the XML electronic document structure in conformance with the rules of the XML document type definition or the XML schema, wherein modifying the XML electronic document structure comprises retagging an element in the XML electronic document structure and moving an element from a current location to a new location in the XML electronic document structure; receiving an input selecting one of the suggested corrections; and using the logic in the selected suggestion template to apply the correction selected by the input to the XML electronic document. 15. The computer program product of claim 10 , wherein: the template is implemented as a list of commands. | 0.824667 |
15. A system according to claim 14 wherein said model checker engine includes means determining whether a model checker-based trace is a reproduction of said ICUT-based trace. | 15. A system according to claim 14 wherein said model checker engine includes means determining whether a model checker-based trace is a reproduction of said ICUT-based trace. 17. A system according to claim 15 wherein said model checker engine includes means responsive to said determination, for generating a new assertion, and for applying said new assertion to said Controller, and wherein said Controller includes means responsive to said applied new assertion for generating a new configuration signals and for applying said new configuration signals to said DL region of said ICUT. | 0.928571 |
1. A method comprising: placing an object in a web page, the web page displayed to a user on a client device with a processor having access to a network, the web page is an affiliate web page, the object is an executable code component configured to execute a network communication when the web page is accessed; invoking a keyword extraction service at a host site via a network access in response to activation of the object in the web page when the web page is accessed by the user; obtaining information related to user activity on the client device, the information obtained in response to activation of the object in the web page when the web page is accessed by the user, the information related to user activity on the client device including impressions viewed by the user and user click-throughs received, wherein the information related to user activity on the client device is based on information selected from the group: user behavior on a web site, frequency of user queries, listings availability, post-search user activity, and catalog data; using the keyword extraction service to extract relevant keywords from content of the web page, the information related to user activity on the client device used to determine relevancy of the extracted keywords; identifying items relevant to the extracted keywords, the relevancy of the extracted keywords to the items is based on information from the group consisting of: measures of item popularity, measures of web site popularity, aggregate user behavior on the web site; user feedback, listings availability, and catalog data; and ranking the relevant items. | 1. A method comprising: placing an object in a web page, the web page displayed to a user on a client device with a processor having access to a network, the web page is an affiliate web page, the object is an executable code component configured to execute a network communication when the web page is accessed; invoking a keyword extraction service at a host site via a network access in response to activation of the object in the web page when the web page is accessed by the user; obtaining information related to user activity on the client device, the information obtained in response to activation of the object in the web page when the web page is accessed by the user, the information related to user activity on the client device including impressions viewed by the user and user click-throughs received, wherein the information related to user activity on the client device is based on information selected from the group: user behavior on a web site, frequency of user queries, listings availability, post-search user activity, and catalog data; using the keyword extraction service to extract relevant keywords from content of the web page, the information related to user activity on the client device used to determine relevancy of the extracted keywords; identifying items relevant to the extracted keywords, the relevancy of the extracted keywords to the items is based on information from the group consisting of: measures of item popularity, measures of web site popularity, aggregate user behavior on the web site; user feedback, listings availability, and catalog data; and ranking the relevant items. 10. The method as claimed in claim 1 further including using the extracted keywords to automatically initiate a re-fetch of content of the web page. | 0.770769 |
1. A method for summarizing a document, the method comprising: receiving, by one or more processors, a reading speed of a reader, wherein the reader is a human reader, wherein the reading speed is based on a first source; determining, by one or more processors, a summary length of a summary of the document based on the received reading speed of the reader, wherein the document is a second source that is a different source from the first source, wherein a first reading speed is faster than a second reading speed, wherein the first reading speed results in a first summary length of the summary and the second reading speed results in a second summary length of the summary, and wherein the first summary length is longer than the second summary length; generating, by one or more processors, a summary of the document having the determined summary length; identifying, by one or more processors, an interest of the reader; modifying, by one or more processors, the summary of the document according to the interest of the reader in order to include, in the summary of the document, content from the document that is of interest to the reader, wherein the reader has multiple interests; weighting, by one or more processors, each interest from the multiple interests based on a reading history of the reader, wherein each interest is assigned a weight based on a percentage of the reading history of the reader that is devoted to said each interest; generating, by one or more processors, a weight ratio of interests of the reader from the multiple interests based on the percentage of the reading history of the reader that is devoted to said each interest; generating, by one or more processors, components of the summary based on the weight ratio of interests of the reader; and modifying, by one or more processors, the summary of the document to match the weight ratio such that a ratio of lengths of the components of the summary matches the weight ratio of the interests of the reader. | 1. A method for summarizing a document, the method comprising: receiving, by one or more processors, a reading speed of a reader, wherein the reader is a human reader, wherein the reading speed is based on a first source; determining, by one or more processors, a summary length of a summary of the document based on the received reading speed of the reader, wherein the document is a second source that is a different source from the first source, wherein a first reading speed is faster than a second reading speed, wherein the first reading speed results in a first summary length of the summary and the second reading speed results in a second summary length of the summary, and wherein the first summary length is longer than the second summary length; generating, by one or more processors, a summary of the document having the determined summary length; identifying, by one or more processors, an interest of the reader; modifying, by one or more processors, the summary of the document according to the interest of the reader in order to include, in the summary of the document, content from the document that is of interest to the reader, wherein the reader has multiple interests; weighting, by one or more processors, each interest from the multiple interests based on a reading history of the reader, wherein each interest is assigned a weight based on a percentage of the reading history of the reader that is devoted to said each interest; generating, by one or more processors, a weight ratio of interests of the reader from the multiple interests based on the percentage of the reading history of the reader that is devoted to said each interest; generating, by one or more processors, components of the summary based on the weight ratio of interests of the reader; and modifying, by one or more processors, the summary of the document to match the weight ratio such that a ratio of lengths of the components of the summary matches the weight ratio of the interests of the reader. 13. The method of claim 1 , further comprising: determining, by one or more processors, the reading speed of the reader based on a length of time that the reader stays on a first webpage having a known number of words before switching to a second webpage. | 0.5 |
5. The method of claim 1 , further comprising: determining whether data representing the online source is stored in a source search index; and in an instance in which the data representing the online source is not stored in the source search index, updating the source search index by storing the data representing the online source in the source search index. | 5. The method of claim 1 , further comprising: determining whether data representing the online source is stored in a source search index; and in an instance in which the data representing the online source is not stored in the source search index, updating the source search index by storing the data representing the online source in the source search index. 6. The method of claim 5 , further comprising: determining whether the analysis of the content data includes a source-specific pattern analysis algorithm; in an instance in which the analysis includes the source-specific pattern analysis algorithm, generating a source-specific representation of the new business reference that is included in the content data; and updating the source-specific pattern analysis algorithm using the source-specific representation. | 0.846232 |
14. A computer server-implemented method for personalization of network search results and search result rankings, the method comprising: using the computer server, receiving at least one query from a respondent or co-respondent via the network; in response to the at least one query, using the computer server, accessing at least one data storage device and selecting a plurality of return queries; using the computer server, transmitting the plurality of return queries to the respondent or co-respondent via the network; using the computer server, receiving a plurality of responses to the return queries from the respondent or co-respondent via the network; using the computer server, generating a digital filter from each plurality of responses to the return queries to form a plurality of digital filters; using the computer server, searching the at least one data storage device for corresponding pluralities of responses to the return queries from one or more co-respondents or respondents, respectively; using the computer server, comparatively pair-wise scoring the plurality of responses to the return queries against the corresponding pluralities of responses to the return queries by using a variance determination or a difference determination to compare a selected combination of respondent and co-respondent digital filters, of the plurality of digital filters, to generate a pair-wise alignment score for the selected respondent and co-respondent combination to form a plurality of pair-wise alignment scores for a plurality of respondent and co-respondent combinations; using the computer server, sorting and ranking the plurality of respondent and co-respondent combinations according to the plurality of pair-wise alignment scores; and using the computer server, outputting a listing of the sorted and ranked respondents or co-respondents to form the personalized network search results and search result rankings. | 14. A computer server-implemented method for personalization of network search results and search result rankings, the method comprising: using the computer server, receiving at least one query from a respondent or co-respondent via the network; in response to the at least one query, using the computer server, accessing at least one data storage device and selecting a plurality of return queries; using the computer server, transmitting the plurality of return queries to the respondent or co-respondent via the network; using the computer server, receiving a plurality of responses to the return queries from the respondent or co-respondent via the network; using the computer server, generating a digital filter from each plurality of responses to the return queries to form a plurality of digital filters; using the computer server, searching the at least one data storage device for corresponding pluralities of responses to the return queries from one or more co-respondents or respondents, respectively; using the computer server, comparatively pair-wise scoring the plurality of responses to the return queries against the corresponding pluralities of responses to the return queries by using a variance determination or a difference determination to compare a selected combination of respondent and co-respondent digital filters, of the plurality of digital filters, to generate a pair-wise alignment score for the selected respondent and co-respondent combination to form a plurality of pair-wise alignment scores for a plurality of respondent and co-respondent combinations; using the computer server, sorting and ranking the plurality of respondent and co-respondent combinations according to the plurality of pair-wise alignment scores; and using the computer server, outputting a listing of the sorted and ranked respondents or co-respondents to form the personalized network search results and search result rankings. 26. The computer server-implemented method of claim 14 , further comprising: using the computer server, using the plurality of digital filters to provide a two-stage filtering of potential search results through both a respondent digital filter of a selected respondent and a co-respondent digital filter of a selected co-respondent, of the plurality of digital filters, to generate the personalized network search results and search result rankings for the selected respondent or the selected co-respondent. | 0.570179 |
1. A method comprising: automatically retrieving extended content from other users that are a predetermined number of hops away from a user in an extended network of the user; obtaining engaging content for the user from a network service to increase the user's engagement with a content stream by identifying the engaging content having a score over a predefined threshold for likelihood of user engagement based upon one or more of quality of posts, trends of posts, and strength of a relationship between the user and a poster, the obtaining engaging content including generating a message with an action button for the user to take an action in a social network; combining the engaging content and the extended content to create a combined list of content; ranking the combined content by relevance to the user; and providing one or more of the ranked content. | 1. A method comprising: automatically retrieving extended content from other users that are a predetermined number of hops away from a user in an extended network of the user; obtaining engaging content for the user from a network service to increase the user's engagement with a content stream by identifying the engaging content having a score over a predefined threshold for likelihood of user engagement based upon one or more of quality of posts, trends of posts, and strength of a relationship between the user and a poster, the obtaining engaging content including generating a message with an action button for the user to take an action in a social network; combining the engaging content and the extended content to create a combined list of content; ranking the combined content by relevance to the user; and providing one or more of the ranked content. 3. The method of claim 1 , wherein ranking the combined content includes ranking the extended content by a vicinity of an author of content to the user. | 0.744681 |
9. A computer program product comprising: a computer usable medium having computer usable program code for executing creating normalized data from markup language data, the computer program medium comprising: computer usable program code for receiving user defined parameters for retrieving event data, wherein the parameters define a type of event and a subset of attributes for the type of event; computer usable program code, responsive to receiving the parameters, for configuring a process using the type of event and the subset of attributes for the type of event to form a configured process; and computer usable program code for processing a set of records using the configured process, wherein the configured process places data corresponding to each attribute in the subset of attributes for the type of event from the set of records into a table to form the normalized data. | 9. A computer program product comprising: a computer usable medium having computer usable program code for executing creating normalized data from markup language data, the computer program medium comprising: computer usable program code for receiving user defined parameters for retrieving event data, wherein the parameters define a type of event and a subset of attributes for the type of event; computer usable program code, responsive to receiving the parameters, for configuring a process using the type of event and the subset of attributes for the type of event to form a configured process; and computer usable program code for processing a set of records using the configured process, wherein the configured process places data corresponding to each attribute in the subset of attributes for the type of event from the set of records into a table to form the normalized data. 16. The computer program product of claim 9 , wherein the process comprises a shredder, wherein the shredder uses a table class and a column class to place data corresponding to each attribute in the subset of attributes for the event type from the set of records into the table. | 0.648537 |
16. The method as recited in claim 15 , wherein said discriminant reduction includes carrying out a Support Vector Machine (SVM) process mutually k-wise comparing the distinct sources in adaptive decomposition to selectively determine one of said at least one optimal combination of atoms for each said k-wise comparison. | 16. The method as recited in claim 15 , wherein said discriminant reduction includes carrying out a Support Vector Machine (SVM) process mutually k-wise comparing the distinct sources in adaptive decomposition to selectively determine one of said at least one optimal combination of atoms for each said k-wise comparison. 24. The method as recited in claim 16 at least partially implemented as an application for a mobile communication device for execution thereon to identify and classify said input signal captured thereby. | 0.947996 |
6. The computer-implemented method of claim 1 further comprising, filtering the candidate alternates. | 6. The computer-implemented method of claim 1 further comprising, filtering the candidate alternates. 7. The computer-implemented method of claim 6 wherein filtering the candidate alternates comprises performing automated synonym filtering. | 0.939035 |
1. A method for training dyslexic students on improving reading skills using a computer-based system that is capable of displaying at least text from a training data set, the method comprising: receiving the training data set as a sequence of symbols representing one or more words from the text of the training data set; parsing the sequence of symbols into a set of segments, the segments representing one or more of words, syllables or letters; generating a tree graph data structure, in a computer-readable medium, representing a tree graph having a plurality of spatial levels, each level including nodes, wherein child nodes in the tree graph correspond to segments of the set of segments, with nodes of a particular level corresponding to words, syllables or letters; mapping attributes from a set of attributes to nodes of the tree graph, such that the sum of an entropy of the graph and an entropy of the set of attributes is a constant times an entropy of the one or more words; and displaying, to a dyslexic student, using a display device of the computer-based system, a representation of the sequence of symbols with the attributes visually represented, thereby providing additional display information beyond just the sequence of symbols usable to training on improving reading skills. | 1. A method for training dyslexic students on improving reading skills using a computer-based system that is capable of displaying at least text from a training data set, the method comprising: receiving the training data set as a sequence of symbols representing one or more words from the text of the training data set; parsing the sequence of symbols into a set of segments, the segments representing one or more of words, syllables or letters; generating a tree graph data structure, in a computer-readable medium, representing a tree graph having a plurality of spatial levels, each level including nodes, wherein child nodes in the tree graph correspond to segments of the set of segments, with nodes of a particular level corresponding to words, syllables or letters; mapping attributes from a set of attributes to nodes of the tree graph, such that the sum of an entropy of the graph and an entropy of the set of attributes is a constant times an entropy of the one or more words; and displaying, to a dyslexic student, using a display device of the computer-based system, a representation of the sequence of symbols with the attributes visually represented, thereby providing additional display information beyond just the sequence of symbols usable to training on improving reading skills. 15. The method of claim 1 , wherein values of appearance attributes maximize a minimum perceptual distance in some space of appearance attributes. | 0.563087 |
9. A computer-executed method for determining social interest in time-based media events, the method comprising: selecting a plurality of events in a time-based medium; accessing from a social networking system a plurality of candidate social media content items authored by users of the social networking system that are potentially relevant to the events in the time based medium; for each social media content item, determining a confidence score for the social media content item with respect to at least one of the plurality of events, the confidence score indicating a probability that the social media content item is relevant to the at least one event; and for each of the plurality of events: aligning with the event, based on their respective confidence scores, a subset of the plurality of the social media content items; aggregating the confidence scores of the social media content items having a confidence score for the event; and determining a level of social interest for in the event based on the aggregate score. | 9. A computer-executed method for determining social interest in time-based media events, the method comprising: selecting a plurality of events in a time-based medium; accessing from a social networking system a plurality of candidate social media content items authored by users of the social networking system that are potentially relevant to the events in the time based medium; for each social media content item, determining a confidence score for the social media content item with respect to at least one of the plurality of events, the confidence score indicating a probability that the social media content item is relevant to the at least one event; and for each of the plurality of events: aligning with the event, based on their respective confidence scores, a subset of the plurality of the social media content items; aggregating the confidence scores of the social media content items having a confidence score for the event; and determining a level of social interest for in the event based on the aggregate score. 10. The computer-executed method of claim 9 , further comprising collecting in a data store the alignments between the event and the subset of the plurality of the social media content items. | 0.636749 |
1. A computer-implemented method performed by a computerized device, comprising: obtaining a proof of a property with respect to a bounded model having a bounded number of cycles, wherein the bounded model comprising an initial axiom and a transition relation axiom, wherein the proof of the property is a Directed Acyclic Graph (DAG), wherein each non-leaf node of the DAG is deducible from its child nodes, wherein a root of the DAG is the property, and wherein leaves of the DAG are associated with an axiom of the bounded model; selecting a set of candidate invariants comprising at least one intermediate node of the DAG; determining, without using the proof and using a Boolean satisfiability problem solver, a subset of the set of candidates, wherein the subset comprises invariants which are held in an unbounded model during each cycle after the bound, wherein the unbounded model is an unbounded version of the bounded model; and utilizing the subset for model checking of the unbounded model. | 1. A computer-implemented method performed by a computerized device, comprising: obtaining a proof of a property with respect to a bounded model having a bounded number of cycles, wherein the bounded model comprising an initial axiom and a transition relation axiom, wherein the proof of the property is a Directed Acyclic Graph (DAG), wherein each non-leaf node of the DAG is deducible from its child nodes, wherein a root of the DAG is the property, and wherein leaves of the DAG are associated with an axiom of the bounded model; selecting a set of candidate invariants comprising at least one intermediate node of the DAG; determining, without using the proof and using a Boolean satisfiability problem solver, a subset of the set of candidates, wherein the subset comprises invariants which are held in an unbounded model during each cycle after the bound, wherein the unbounded model is an unbounded version of the bounded model; and utilizing the subset for model checking of the unbounded model. 5. The computer-implemented method of claim 1 , wherein said utilizing the subset comprises: adding the invariants to the unbounded model; and model checking the modified unbounded model. | 0.727193 |
25. An article, comprising: a machine-readable medium having stored thereon instructions that, if executed, direct a computing platform to: receive a query expression specifying a set of information to be retrieved; check for the presence of a cache file related to a database file, the database file including at least the specified set of information, wherein the cache file comprises one or more subsets of information from the database file and one or more query expressions, wherein each one of the one or more subsets of information is stored in the cache file in association with a different one of the one or more query expressions, and wherein each one of the one or more subsets of information is a result of parsing the database file according to a corresponding one of the one or query expressions; in response to determining that the cache file is present: determine whether the specified set of information is present in the cache file; in response to determining that the specified set of information is present in the cache file: determine whether the cache file is valid, wherein said determining whether the cache file is valid comprises examining a currency token stored in association with the cache file, wherein the currency token indicates whether the cache file is current, wherein the currency token includes an attribute of the database file, and wherein the attribute describes the database file at a time when the database file was parsed according to the one or more query expressions that are stored in the cache file; in response to determining that the cache file is valid: retrieve the specified set of information from an entry in the cache file, wherein the entry is associated with one of the one or more query expressions which matches the retrieved query expression. | 25. An article, comprising: a machine-readable medium having stored thereon instructions that, if executed, direct a computing platform to: receive a query expression specifying a set of information to be retrieved; check for the presence of a cache file related to a database file, the database file including at least the specified set of information, wherein the cache file comprises one or more subsets of information from the database file and one or more query expressions, wherein each one of the one or more subsets of information is stored in the cache file in association with a different one of the one or more query expressions, and wherein each one of the one or more subsets of information is a result of parsing the database file according to a corresponding one of the one or query expressions; in response to determining that the cache file is present: determine whether the specified set of information is present in the cache file; in response to determining that the specified set of information is present in the cache file: determine whether the cache file is valid, wherein said determining whether the cache file is valid comprises examining a currency token stored in association with the cache file, wherein the currency token indicates whether the cache file is current, wherein the currency token includes an attribute of the database file, and wherein the attribute describes the database file at a time when the database file was parsed according to the one or more query expressions that are stored in the cache file; in response to determining that the cache file is valid: retrieve the specified set of information from an entry in the cache file, wherein the entry is associated with one of the one or more query expressions which matches the retrieved query expression. 29. The article of claim 25 , wherein the machine-readable medium has stored thereon further instructions that, if executed, further direct the computing platform to retrieve the specified set of information from the database file if the specified set of information is not present in the cache file. | 0.511216 |
1. A method for virtually integrating a bot with an online search service, the method comprising the steps of: surfacing bot content for indexing by a search engine associated with the search service, the surfaced bot content being includable in a link contained in a results page returned by the search engine to a user of the online search service responsively to a query; responsively to the link being activated by the user, launching the bot to engage in a conversation with the user, enabling the user to converse with the bot using a natural language interface; and receiving at least a portion of the query from the search engine to enable the bot to begin the conversation with the user using bot content that has relevance to the query by identifying the user with a unique identifier that is shared with the bot so that the bot may utilize the unique identifier to pull a last known query input by the user. | 1. A method for virtually integrating a bot with an online search service, the method comprising the steps of: surfacing bot content for indexing by a search engine associated with the search service, the surfaced bot content being includable in a link contained in a results page returned by the search engine to a user of the online search service responsively to a query; responsively to the link being activated by the user, launching the bot to engage in a conversation with the user, enabling the user to converse with the bot using a natural language interface; and receiving at least a portion of the query from the search engine to enable the bot to begin the conversation with the user using bot content that has relevance to the query by identifying the user with a unique identifier that is shared with the bot so that the bot may utilize the unique identifier to pull a last known query input by the user. 7. The method of claim 1 in which the surfacing comprises exposing one or more sources of the bot content through an API on a hosted platform on which the bot runs. | 0.530644 |
29. The method defined in claim 28 , further comprising: identifying those of the reference video streams for which the at least one characteristic of the best matching snippet's associated segment for the respective reference video stream meets pre-determined criteria; and outputting an indication that the query video stream is deemed to include at least a portion of the identified reference video stream or streams. | 29. The method defined in claim 28 , further comprising: identifying those of the reference video streams for which the at least one characteristic of the best matching snippet's associated segment for the respective reference video stream meets pre-determined criteria; and outputting an indication that the query video stream is deemed to include at least a portion of the identified reference video stream or streams. 32. The method defined in claim 29 , wherein the characteristic comprises a ratio of matches within the segment and wherein the pre-determined criteria comprises the ratio exceeding a pre-determined ratio. | 0.827126 |
16. A user device comprising: a processor apparatus comprising a processor and a memory in electronic communication with one another, the memory having stored therein a plurality of objects comprising a plurality of language objects and a plurality of linguistic elements, at least some of the language objects each comprising a number of the linguistic elements; and an interface apparatus having a plurality of keys; the memory further having stored therein a number of routines which, when executed on the processor, cause the user device to perform operations comprising: detecting an input comprising a number of key selections including a current key selection; identifying linguistic elements corresponding to the key selections; identifying a language object having at least an initial portion that corresponds with the linguistic elements of the input; identifying in the language object a predictive linguistic element that is positioned in the language object at a location adjacent and subsequent to a current linguistic element corresponding to the current key selection; and highlighting the predictive linguistic element on a key. | 16. A user device comprising: a processor apparatus comprising a processor and a memory in electronic communication with one another, the memory having stored therein a plurality of objects comprising a plurality of language objects and a plurality of linguistic elements, at least some of the language objects each comprising a number of the linguistic elements; and an interface apparatus having a plurality of keys; the memory further having stored therein a number of routines which, when executed on the processor, cause the user device to perform operations comprising: detecting an input comprising a number of key selections including a current key selection; identifying linguistic elements corresponding to the key selections; identifying a language object having at least an initial portion that corresponds with the linguistic elements of the input; identifying in the language object a predictive linguistic element that is positioned in the language object at a location adjacent and subsequent to a current linguistic element corresponding to the current key selection; and highlighting the predictive linguistic element on a key. 19. The user electronic device of claim 16 wherein the operations further comprise determining that the input corresponds with two language objects each having a quantity of linguistic elements equal to the quantity of key selections in the input and, responsive thereto, providing another highlight. | 0.618998 |
6. The method of claim 1 , wherein comparative and summary statistics are presented in the calendar-based display. | 6. The method of claim 1 , wherein comparative and summary statistics are presented in the calendar-based display. 12. The method of claim 6 , wherein one of the comparative statistics is a parallel period comparison statistic, a consecutive period comparison statistic, or a relative contribution analysis statistic; wherein one of the summary statistics is a year-to-date total and year-to-date average; a quarter-to-date total and quarter-to-date average; a month-to-date total and month-to-date average; a week-to-date total and week-to-date average; an opening period statistic that represents a value at a beginning of the time period; or a closing period statistic that represents a value at an end of the time period. | 0.825876 |
16. A computer system comprising one or more computers, said computer system programmed, via executable code stored in computer storage, to perform a method that comprises: storing, in an electronic data repository, user activity data associated with each of a plurality of users of an interactive system that provides access to an electronic catalog, said user activity data reflecting user-generated events associated with particular items represented in the electronic catalog; identifying, among the plurality of users, a subset of users whose email addresses are associated with a particular organization; analyzing the user activity data associated with the plurality of users, including the subset of users, to identify, among the items represented in the electronic catalog, a set of items that have experienced significantly higher levels of user activity among the subset of users than among the plurality of users; and storing, in computer storage, association data that associates the organization with the identified set of items. | 16. A computer system comprising one or more computers, said computer system programmed, via executable code stored in computer storage, to perform a method that comprises: storing, in an electronic data repository, user activity data associated with each of a plurality of users of an interactive system that provides access to an electronic catalog, said user activity data reflecting user-generated events associated with particular items represented in the electronic catalog; identifying, among the plurality of users, a subset of users whose email addresses are associated with a particular organization; analyzing the user activity data associated with the plurality of users, including the subset of users, to identify, among the items represented in the electronic catalog, a set of items that have experienced significantly higher levels of user activity among the subset of users than among the plurality of users; and storing, in computer storage, association data that associates the organization with the identified set of items. 22. The computer system of claim 16 , wherein analyzing the user activity data comprises using a bootstrap method to evaluate whether a set of items associated with the organization is a result of group preferences that differ from preferences of the plurality of users. | 0.5 |
1. In a computer system comprising at least one hardware processor and at least one tangible storage medium, a method of identifying elemental facet attribute relationships in a domain of information comprising a plurality of concepts, wherein the method comprises: identifying a plurality of concept relationships between pairs of concepts in the plurality of concepts; identifying at least one facet attribute in each of at least some of the pairs of concepts; based, at least in part, on the identified plurality of concept relationships, identifying a set of candidate facet attribute relationships between the facet attributes in the at least some of the pairs of concepts; and determining whether to include a candidate facet attribute relationship from the set of candidate facet attribute relationships in a modified set of candidate facet attribute relationships based, at least in part, on the pervasiveness of the candidate facet attribute relationship. | 1. In a computer system comprising at least one hardware processor and at least one tangible storage medium, a method of identifying elemental facet attribute relationships in a domain of information comprising a plurality of concepts, wherein the method comprises: identifying a plurality of concept relationships between pairs of concepts in the plurality of concepts; identifying at least one facet attribute in each of at least some of the pairs of concepts; based, at least in part, on the identified plurality of concept relationships, identifying a set of candidate facet attribute relationships between the facet attributes in the at least some of the pairs of concepts; and determining whether to include a candidate facet attribute relationship from the set of candidate facet attribute relationships in a modified set of candidate facet attribute relationships based, at least in part, on the pervasiveness of the candidate facet attribute relationship. 7. The method of claim 1 , wherein the act of identifying at least one facet attribute in each of at least some of the pairs of concepts further comprises: identifying a plurality of keywords in the at least some of the pairs of concepts; and identifying the plurality of facet attributes in the plurality of keywords. | 0.569739 |
6. One or more tangible non-transitory computer-readable media as in claim 1 , further comprising: utilizing probability smoothing to assign additional probability values to other keyboard patterns for other password strings not found in said plurality of password strings. | 6. One or more tangible non-transitory computer-readable media as in claim 1 , further comprising: utilizing probability smoothing to assign additional probability values to other keyboard patterns for other password strings not found in said plurality of password strings. 7. One or more tangible non-transitory computer-readable media as in claim 6 , wherein said step of utilizing probability smoothing is achieved by an equation Prob ( p ) = Prob ( s ) N i + α ∑ N i + C α where Prob(s) is the probability of a keyboard shape s given the length of the keyboard pattern, Ni is the number of times an ith keyboard pattern of a shape s was found, α is a smoothing value, ΣN i is a sum of counts of the keyboard patterns found for the shape s, and C is a total number of unique patterns for the shape s. | 0.887907 |
6. The method of claim 1 , wherein the act (B) comprises establishing the rejection threshold in an underlying multivariate Gaussian distribution within an acoustic model of the speech recognition system. | 6. The method of claim 1 , wherein the act (B) comprises establishing the rejection threshold in an underlying multivariate Gaussian distribution within an acoustic model of the speech recognition system. 7. The method of claim 6 , wherein if the quality of the input signal is determined in the act (A) to be low, then the act (B) comprises increasing skirts of the underlying multivariate Gaussian distribution, and if the quality of the input signal is determined in the act (A) to be high, then the act (B) comprises reducing skirts of the underlying multivariate Gaussian distribution. | 0.777393 |
12. At a computer system including a multi-touch input display surface, a method for recognizing a region for selecting items displayed on the multi-touch input display surface, the method comprising: an act of receiving input contact data indicating simultaneous contact on an area of the multi-touch input display surface; an act of calculating a selection region on the multi-touch input surface based on the area of simultaneous contact; an act of identifying selected items displayed on the multi-touch input surface that are selected by the calculated selection region; an act of providing region visual feedback data to the multi-touch input surface to display the calculated selection region on the multi-touch input surface; and an act of providing item visual feedback data to the multi-touch input surface to visually indicate the selected items. | 12. At a computer system including a multi-touch input display surface, a method for recognizing a region for selecting items displayed on the multi-touch input display surface, the method comprising: an act of receiving input contact data indicating simultaneous contact on an area of the multi-touch input display surface; an act of calculating a selection region on the multi-touch input surface based on the area of simultaneous contact; an act of identifying selected items displayed on the multi-touch input surface that are selected by the calculated selection region; an act of providing region visual feedback data to the multi-touch input surface to display the calculated selection region on the multi-touch input surface; and an act of providing item visual feedback data to the multi-touch input surface to visually indicate the selected items. 13. The method as recited in claim 12 , wherein the act of receiving input contact data indicating simultaneous contact on an area of the multi-touch input display surface comprises an act of receiving input contact data indicating simultaneous contact between a portion of a hand and the multi-touch input display surface. | 0.807176 |
1. A computer-implemented method comprising: (a) generating, using a data federation computer system, electronic configuration triple data structures for each of a plurality of data sources by performing the following steps for each of the plurality of data sources: i. identifying, using a data federation computer system, the respective data source; ii. identifying, using the data federation computer system, respective access data used to access the respective data source; iii. converting, by the data federation computer system, the respective access data to corresponding electronic configuration triple data structures based at least in part upon a common configuration ontology; and iv. storing in non-transitory computer-readable memory comprising at least one triplestore database, by the data federation computer system, the electronic configuration triple data structures; (b) generating, using the data federation computer system, a generated metadata ontology for each of the plurality of data sources by performing the following steps for each of the plurality of data sources: i. accessing, by the data federation computer system, the respective data source using the respective access data identified by the respective electronic configuration triple data structures; ii. extracting, by the data federation computer system, respective metadata from the respective data source, wherein the respective metadata identifies respective data specified in respective data structures; iii. converting, by the data federation computer system, the extracted respective metadata to corresponding respective electronic metadata triple data structures based at least in part upon a common metadata ontology; and iv. storing in the non-transitory computer-readable memory, by the data federation computer system, the respective electronic metadata triple data structures to form a respective generated metadata ontology for each respective data source; (c) generating, using the data federation computer system, a domain ontology corresponding to a first target data environment, wherein the first target data environment comprises a respective lexicon for specifying queries of the plurality of data sources; (d) storing, using the data federation computer system, the domain ontology; (e) for each of the plurality of data sources, generating, using the data federation computer system, a bridge ontology comprising an electronic mapping between the generated metadata ontology for the respective data source and the domain ontology; (f) determining, by the data federation computer system, a subset of the plurality of data sources that cannot be queried in place; (g) generating, by the data federation computer system, a re-hosted data ontology for each of the subset of the plurality of data sources by performing the following steps for each of the subset of the plurality of data sources: i. extracting, by the data federation computer system, respective data from the respective data source; ii. converting, by the data federation computer system, the respective extracted data to corresponding electronic data triple data structures based upon the respective bridge ontology; and iii. storing in the non-transitory computer-readable memory, by the data federation computer system, the electronic data triple data structures to form a re-hosted data ontology; and (h) correlating, by the data federation computer system, a query expressed in the domain ontology to the data from the plurality of data sources using the re-hosted data ontologies for each of the subset of the plurality of data sources and using the bridge ontologies for the remaining data sources. | 1. A computer-implemented method comprising: (a) generating, using a data federation computer system, electronic configuration triple data structures for each of a plurality of data sources by performing the following steps for each of the plurality of data sources: i. identifying, using a data federation computer system, the respective data source; ii. identifying, using the data federation computer system, respective access data used to access the respective data source; iii. converting, by the data federation computer system, the respective access data to corresponding electronic configuration triple data structures based at least in part upon a common configuration ontology; and iv. storing in non-transitory computer-readable memory comprising at least one triplestore database, by the data federation computer system, the electronic configuration triple data structures; (b) generating, using the data federation computer system, a generated metadata ontology for each of the plurality of data sources by performing the following steps for each of the plurality of data sources: i. accessing, by the data federation computer system, the respective data source using the respective access data identified by the respective electronic configuration triple data structures; ii. extracting, by the data federation computer system, respective metadata from the respective data source, wherein the respective metadata identifies respective data specified in respective data structures; iii. converting, by the data federation computer system, the extracted respective metadata to corresponding respective electronic metadata triple data structures based at least in part upon a common metadata ontology; and iv. storing in the non-transitory computer-readable memory, by the data federation computer system, the respective electronic metadata triple data structures to form a respective generated metadata ontology for each respective data source; (c) generating, using the data federation computer system, a domain ontology corresponding to a first target data environment, wherein the first target data environment comprises a respective lexicon for specifying queries of the plurality of data sources; (d) storing, using the data federation computer system, the domain ontology; (e) for each of the plurality of data sources, generating, using the data federation computer system, a bridge ontology comprising an electronic mapping between the generated metadata ontology for the respective data source and the domain ontology; (f) determining, by the data federation computer system, a subset of the plurality of data sources that cannot be queried in place; (g) generating, by the data federation computer system, a re-hosted data ontology for each of the subset of the plurality of data sources by performing the following steps for each of the subset of the plurality of data sources: i. extracting, by the data federation computer system, respective data from the respective data source; ii. converting, by the data federation computer system, the respective extracted data to corresponding electronic data triple data structures based upon the respective bridge ontology; and iii. storing in the non-transitory computer-readable memory, by the data federation computer system, the electronic data triple data structures to form a re-hosted data ontology; and (h) correlating, by the data federation computer system, a query expressed in the domain ontology to the data from the plurality of data sources using the re-hosted data ontologies for each of the subset of the plurality of data sources and using the bridge ontologies for the remaining data sources. 8. The computer-implemented method of claim 1 , wherein at least one of the plurality of data sources is a web service. | 0.536524 |
19. A computer system, comprising: a processor configured to receive one or more search criteria and an indication that a search result based content associated with the search criteria is to be included in a web page; and generate automatically for the web page a computer script or code configured to enable the search result based content to be retrieved in accordance with the search criteria; wherein the search result based content includes content from pages that: 1) satisfy the search criteria, 2) are associated with a natural language with which the web page is associated, and 3) match a life cycle state of the web page, wherein the life cycle state describes a stage in a content management system approval process; wherein the natural language comprises a primary natural language associated with the web page; wherein to generate automatically includes inserting in the search result based content a specific content from a specific page that satisfies: 1) the search criteria and 2) is associated with a secondary or default natural language associated with the web page, in the event a corresponding page associated with the primary natural language is not found; and a storage configured to store one or more of the search criteria and the computer script or code. | 19. A computer system, comprising: a processor configured to receive one or more search criteria and an indication that a search result based content associated with the search criteria is to be included in a web page; and generate automatically for the web page a computer script or code configured to enable the search result based content to be retrieved in accordance with the search criteria; wherein the search result based content includes content from pages that: 1) satisfy the search criteria, 2) are associated with a natural language with which the web page is associated, and 3) match a life cycle state of the web page, wherein the life cycle state describes a stage in a content management system approval process; wherein the natural language comprises a primary natural language associated with the web page; wherein to generate automatically includes inserting in the search result based content a specific content from a specific page that satisfies: 1) the search criteria and 2) is associated with a secondary or default natural language associated with the web page, in the event a corresponding page associated with the primary natural language is not found; and a storage configured to store one or more of the search criteria and the computer script or code. 20. A computer system as recited in claim 19 , wherein the indication comprises an update indication that a time or the end of an update interval specified by the schedule associated with the web page has arrived. | 0.537442 |
17. A method comprising the steps of receiving a computer programming language database system query; generating at least one relational algebraic expression in response to said query by employing at least one of a collection of equivalence rules involving the multiset version of the relational algebraic theta-semijoin operator; selecting at least one of said relational algebraic expressions; and accessing said computer programming language database based on said selected expression, said multiset version defined as ##EQU52## where R1 and R2 denote relations, and .theta.(t.sub.2) denotes the predicate .theta. with attributes of R.sub.2 replaced by their values from tuple t.sub.2. | 17. A method comprising the steps of receiving a computer programming language database system query; generating at least one relational algebraic expression in response to said query by employing at least one of a collection of equivalence rules involving the multiset version of the relational algebraic theta-semijoin operator; selecting at least one of said relational algebraic expressions; and accessing said computer programming language database based on said selected expression, said multiset version defined as ##EQU52## where R1 and R2 denote relations, and .theta.(t.sub.2) denotes the predicate .theta. with attributes of R.sub.2 replaced by their values from tuple t.sub.2. 18. The method of claim 17 wherein said collection includes equivalence rule ##EQU53## where E (with or without subscripts) denotes relational expressions, .theta. (with or without subscripts) denotes predicates,.sub..theta. denotes the .theta.-join operator, and .sub..theta. denotes the .theta.-semijoin operator. | 0.557197 |
16. A non-transitory computer-readable storage having instructions stored thereon for executing a method, the method comprising: labeling one or more portions of a content item with a system-generated label; analyzing the one or more labeled portions and the content item for sentiment and assigning a sentiment score to a first labeled portion of the one or more labeled portions and to the content item; causing a graphical user interface to display the content item; receiving, via the graphical user interface, a user-specified label for a user-selected portion of the content item and a user-specified sentiment for the user-specified label; responsive to receiving the user-specified label and user-specified sentiment, searching a data store comprising a plurality of content items to identify content items comprising the user-specified label; re-analyzing the identified content items to update their sentiment scores based on the user-specified sentiment score; and causing the graphical user interface to display the updated sentiment score of the content item. | 16. A non-transitory computer-readable storage having instructions stored thereon for executing a method, the method comprising: labeling one or more portions of a content item with a system-generated label; analyzing the one or more labeled portions and the content item for sentiment and assigning a sentiment score to a first labeled portion of the one or more labeled portions and to the content item; causing a graphical user interface to display the content item; receiving, via the graphical user interface, a user-specified label for a user-selected portion of the content item and a user-specified sentiment for the user-specified label; responsive to receiving the user-specified label and user-specified sentiment, searching a data store comprising a plurality of content items to identify content items comprising the user-specified label; re-analyzing the identified content items to update their sentiment scores based on the user-specified sentiment score; and causing the graphical user interface to display the updated sentiment score of the content item. 19. The non-transitory computer-readable storage of claim 16 , further comprising assigning a first weight to a first portion of the one or more portions labeled with the system-generated label and a second weight to the user-selected portion, wherein the second weight is greater than the first weight such that the sentiment score for the first portion labeled with the system-generated label is decreased relative to the sentiment score for the user-selected portion. | 0.689955 |
5. Method according to claim 4, comprising the steps of: generating error signals out of results of the evaluating operations and out of results of the checking of said block error detection code; and generating control signals out of said error signals for controlling operations subsequently carried out on said data words. | 5. Method according to claim 4, comprising the steps of: generating error signals out of results of the evaluating operations and out of results of the checking of said block error detection code; and generating control signals out of said error signals for controlling operations subsequently carried out on said data words. 11. Method according to claim 5, whereas digital data words and correction words in said first sequence are recorded on a plurality of tracks on a recording medium, comprising the steps of: generating error signals related to data words and correction words from each of said tracks; generating an error pattern out of the error signals from all tracks; and generating control signals taking into account said error signals from said plurality of tracks. | 0.837787 |
26. A non-semantical method for numerically representing objects in a computer database and for computerized searching of the numerically represented objects in the database, wherein direct and indirect relationships exist between objects in the database, comprising: marking objects in the database so that each marked object may be individually identified by a computerized search; creating a first numerical representation for each identified object in the database based upon the object's direct relationship with other objects in the database; storing the first numerical representations for use in computerized searching; analyzing the first numerical representations for indirect relationships existing between or among objects in the database; generating a second numerical representation of each object based on the analysis of the first numerical representation; storing the second numerical representation for use in computerized searching; and searching the objects in the database using a computer and the stored second numerical representations, wherein the search identifies one or more of the objects in the database. | 26. A non-semantical method for numerically representing objects in a computer database and for computerized searching of the numerically represented objects in the database, wherein direct and indirect relationships exist between objects in the database, comprising: marking objects in the database so that each marked object may be individually identified by a computerized search; creating a first numerical representation for each identified object in the database based upon the object's direct relationship with other objects in the database; storing the first numerical representations for use in computerized searching; analyzing the first numerical representations for indirect relationships existing between or among objects in the database; generating a second numerical representation of each object based on the analysis of the first numerical representation; storing the second numerical representation for use in computerized searching; and searching the objects in the database using a computer and the stored second numerical representations, wherein the search identifies one or more of the objects in the database. 27. The non-semantical method of claim 26, wherein the objects in the database include words, and semantic indexing techniques are used in combination with the non-semantical method, the method further comprising the step of creating and storing a boolean word index for the words of the objects in the database. | 0.610592 |
9. The system of claim 7 , wherein the user-specified behavior requirement includes a semantic tag that specifies at least one of: a proper name, a phone number, an address, an email address, an internet protocol address, and a web address; and the speech recognition platform further configured to: encode the user-specified behavior requirement into the speech recognition grammar specification for the speech recognition platform; and transform the recognized word sequence according to the user-specified behavior requirement. | 9. The system of claim 7 , wherein the user-specified behavior requirement includes a semantic tag that specifies at least one of: a proper name, a phone number, an address, an email address, an internet protocol address, and a web address; and the speech recognition platform further configured to: encode the user-specified behavior requirement into the speech recognition grammar specification for the speech recognition platform; and transform the recognized word sequence according to the user-specified behavior requirement. 11. The system of claim 9 , the speech recognition platform further configured to: determine which transformations to apply to a sub-segment of the recognized speech according to a semantic tag associated with the sub-segment. | 0.835455 |
10. A method according to claim 9 , wherein the input stroke is preprocessed, wherein the preprocessing includes at least the normalization and smoothing of the input stroke. | 10. A method according to claim 9 , wherein the input stroke is preprocessed, wherein the preprocessing includes at least the normalization and smoothing of the input stroke. 12. A method according to claim 10 , wherein the assigning of a recognition score comprises a feature extraction stage and a classification of features extracted by neural networks. | 0.924481 |
1. A computer-implemented method for identifying an on-line bank account utilized for business purposes, the method being performed by a computer and comprising: the computer parsing data of an on-line bank account into a plurality of segments; the computer applying a first set of rules to individual segments and a second set of rules to groups of multiple segments; and the computer determining whether the on-line bank account is a business account or utilized for business purposes based at least in part upon respective scores generated by application of respective first and second sets of rules. | 1. A computer-implemented method for identifying an on-line bank account utilized for business purposes, the method being performed by a computer and comprising: the computer parsing data of an on-line bank account into a plurality of segments; the computer applying a first set of rules to individual segments and a second set of rules to groups of multiple segments; and the computer determining whether the on-line bank account is a business account or utilized for business purposes based at least in part upon respective scores generated by application of respective first and second sets of rules. 20. The method of claim 1 , applying the second set of rules resulting in assigning respective scores to respective groups of segments, the computer determining whether the on-line bank account is a business account or utilized for business purposes based at least in part upon the respective scores for respective groups of segments. | 0.547671 |
1. A method to facilitate user productivity in visualizing and reviewing a set of document search results, the method comprising: receiving a query request comprising two or more search terms as a computer machine input, wherein each search term from the one or more search terms is assigned a graphical indicator; searching a corpora of electronically stored content for a set of at least two documents relevant to the query request; scoring a set of paragraphs associated with the set of at least two documents; ranking the set of paragraphs based on the scoring; and displaying at least one boxed abacus icon that indicates whether the two or more search terms in the query request are present in a subset of the set of paragraphs, wherein: the subset comprises a preset number of paragraphs receiving higher scores determined in the ranking step than a set of paragraphs not included in the subset, each paragraph in the subset is assigned to a vertical line in a set of vertical lines, and the at least one boxed abacus icon comprises a depiction of the graphical indicators on each vertical line corresponding to a presence of the search term in the paragraph. | 1. A method to facilitate user productivity in visualizing and reviewing a set of document search results, the method comprising: receiving a query request comprising two or more search terms as a computer machine input, wherein each search term from the one or more search terms is assigned a graphical indicator; searching a corpora of electronically stored content for a set of at least two documents relevant to the query request; scoring a set of paragraphs associated with the set of at least two documents; ranking the set of paragraphs based on the scoring; and displaying at least one boxed abacus icon that indicates whether the two or more search terms in the query request are present in a subset of the set of paragraphs, wherein: the subset comprises a preset number of paragraphs receiving higher scores determined in the ranking step than a set of paragraphs not included in the subset, each paragraph in the subset is assigned to a vertical line in a set of vertical lines, and the at least one boxed abacus icon comprises a depiction of the graphical indicators on each vertical line corresponding to a presence of the search term in the paragraph. 5. The method of claim 1 , wherein the subset of the set of paragraphs has a greater term density and is scored higher than remaining paragraphs of the set of paragraphs having a lower term density. | 0.837152 |
1. In a speech recognition system, an apparatus for storing speech parameters, said apparatus comprising: transducer means responsive to acoustic energy for transforming said acoustic energy into analog electrical signals, wherein said acoustic energy comprises voiced speech, unvoiced speech and background noise; signal processing means for converting said analog signals to substantially equivalent forms of speech parameters and for sampling said speech parameters at a predetermined sampling rate; first storage means coupled to said signal processing means for temporarily storing a plurality of samples of said speech parameters from said signal processing means; a binary adder coupled to said signal processing means for computing the average signal level of samples of said speech parameters from said signal processing means during predetermined periods of time; a digital magnitude comparator coupled to said binary adder, said comparator generating a control signal when the computed average signal level exceeds a predetermined signal level, said predetermined signal level representative of said background noise; second storage means coupled to said first storage means for storing speech parameters transferred from said first storage means; and means responsive to said control signal for conveying information stored in said first storage means to said second storage means, wherein said conveyed information includes speech parameters stored in said first storage means prior to the generation of said control signal. | 1. In a speech recognition system, an apparatus for storing speech parameters, said apparatus comprising: transducer means responsive to acoustic energy for transforming said acoustic energy into analog electrical signals, wherein said acoustic energy comprises voiced speech, unvoiced speech and background noise; signal processing means for converting said analog signals to substantially equivalent forms of speech parameters and for sampling said speech parameters at a predetermined sampling rate; first storage means coupled to said signal processing means for temporarily storing a plurality of samples of said speech parameters from said signal processing means; a binary adder coupled to said signal processing means for computing the average signal level of samples of said speech parameters from said signal processing means during predetermined periods of time; a digital magnitude comparator coupled to said binary adder, said comparator generating a control signal when the computed average signal level exceeds a predetermined signal level, said predetermined signal level representative of said background noise; second storage means coupled to said first storage means for storing speech parameters transferred from said first storage means; and means responsive to said control signal for conveying information stored in said first storage means to said second storage means, wherein said conveyed information includes speech parameters stored in said first storage means prior to the generation of said control signal. 3. The apparatus according to claim 1 wherein said second storage means is a random access memory (RAM). | 0.920404 |
2. The computing device of claim 1 , wherein the one or more processors are further configured to: automatically detect an intent to read the message, wherein the intent includes one or more of a read selection to read the message and a read command to read the message; and automatically identify the reading mode as the presentation mode. | 2. The computing device of claim 1 , wherein the one or more processors are further configured to: automatically detect an intent to read the message, wherein the intent includes one or more of a read selection to read the message and a read command to read the message; and automatically identify the reading mode as the presentation mode. 3. The computing device of claim 2 , wherein the one or more processors are further configured to: automatically place the reading mode commands on the toolbar UI to present the toolbar UI as the command UI, wherein the reading mode commands include one or more of a reply command, a reply to all command, a forward command, and a delete command. | 0.834237 |
12. The article of claim 11 , wherein the first visual indicators include plural different colors representing different user sentiments, including a positive sentiment, a neutral sentiment, and a negative sentiment. | 12. The article of claim 11 , wherein the first visual indicators include plural different colors representing different user sentiments, including a positive sentiment, a neutral sentiment, and a negative sentiment. 20. The article of claim 12 , wherein the second visual indicators include different heights of the graphical elements to represent different levels of uncertainty. | 0.944026 |
16. The computer program product of claim 12 wherein the computer program instructions are further operable when executed by at least one computing device to accumulate statistics for a subset of the keywords representing a conversion rate for each. | 16. The computer program product of claim 12 wherein the computer program instructions are further operable when executed by at least one computing device to accumulate statistics for a subset of the keywords representing a conversion rate for each. 17. The computer program product of claim 16 wherein the computer program instructions are further operable when executed by at least one computing device to derive the utility for each of the subset of keywords with reference to the corresponding conversion rate and the associated bid. | 0.819495 |
1. A system for selectively delivering an article, comprising: a communications interface configured to: receive a user preference; and receive a document; a processor configured to: identify a plurality of entity pairs each comprising a concept included in a concept taxonomy and a textual representation relating to the concept included in the document, each concept having a corresponding category vector including a plurality of adjacent nodes of the concept in a taxonomy; compute a document vector (dv) for the document as a sum of the category vectors for the plurality of entity pairs; select a subset of concepts from the plurality of entity pairs according to a comparison of the document vector and the category vectors of the concepts of the plurality of entity pairs by: calculating a similarity score ds for each concept according to ds=dv·cv, where dv is the document vector and cv is a concept vector; selecting the subset of concepts as concepts having similarity scores ds with respect to the document vector hi her than a threshold; categorize the document based at least in part on the selected subset of concepts; and determine that the selected subset of concepts corresponds to the user preference; in response to determining that the selected subset of concepts corresponds to the user preference, notify a user associated with the user preference of the document; and a memory coupled to the processor and configured to provide the processor with instructions. | 1. A system for selectively delivering an article, comprising: a communications interface configured to: receive a user preference; and receive a document; a processor configured to: identify a plurality of entity pairs each comprising a concept included in a concept taxonomy and a textual representation relating to the concept included in the document, each concept having a corresponding category vector including a plurality of adjacent nodes of the concept in a taxonomy; compute a document vector (dv) for the document as a sum of the category vectors for the plurality of entity pairs; select a subset of concepts from the plurality of entity pairs according to a comparison of the document vector and the category vectors of the concepts of the plurality of entity pairs by: calculating a similarity score ds for each concept according to ds=dv·cv, where dv is the document vector and cv is a concept vector; selecting the subset of concepts as concepts having similarity scores ds with respect to the document vector hi her than a threshold; categorize the document based at least in part on the selected subset of concepts; and determine that the selected subset of concepts corresponds to the user preference; in response to determining that the selected subset of concepts corresponds to the user preference, notify a user associated with the user preference of the document; and a memory coupled to the processor and configured to provide the processor with instructions. 10. The system of claim 1 , further comprising pruning concepts according to ambiguity resolution further comprises comparing similarity scores ds for ambiguous entity pairs of the plurality of entity pairs. | 0.52669 |
38. The computer-readable computer memory medium of claim 26 wherein the method further comprises: rendering the search snapshot history comprising a plurality of search snapshots using the search result snapshot history data structure including displaying a history of relationships between the search result snapshot objects. | 38. The computer-readable computer memory medium of claim 26 wherein the method further comprises: rendering the search snapshot history comprising a plurality of search snapshots using the search result snapshot history data structure including displaying a history of relationships between the search result snapshot objects. 39. The computer-readable computer memory medium of claim 38 , wherein the method further comprises: filtering the rendered search snapshot history. | 0.941046 |
13. The method according to claim 12 , in which P ℑ (ƒ i |z k ) is determined by maximization of the log-likelihood function: log ∏ i = 1 N P ( f i ❘ Z ) u i = ∑ i = 1 N u i log ( ∑ k = 1 K P z ( z k ) p ( f i ❘ z k ) ) where u i is the number of annotation words for image ƒ i , and P z (z k ) and P V (w j |z k ) are determined by maximization of the log-likelihood function: = log P ( F , V ) = ∑ i = 1 N ∑ j = 1 M n ( w i j ) log P ( f i , w j ) where n (w i j ) denotes the weight of annotation word w j , i.e., occurrence frequency, for image ƒ i ; and the model is resolved by applying the expectation-maximization (EM) technique, comprising: (i) an expectation (E) step where the posterior probabilities are computed for the hidden variable z k based on the current estimates of the parameters; and (ii) an maximization (M) step, where parameters are updated to maximize the expectation of the complete-data likelihood log P (F,V,Z) given the posterior probabilities computed in the preceding E-step, whereby the probabilities can be iteratively determined by fitting the model to the training image database and the associated annotations. | 13. The method according to claim 12 , in which P ℑ (ƒ i |z k ) is determined by maximization of the log-likelihood function: log ∏ i = 1 N P ( f i ❘ Z ) u i = ∑ i = 1 N u i log ( ∑ k = 1 K P z ( z k ) p ( f i ❘ z k ) ) where u i is the number of annotation words for image ƒ i , and P z (z k ) and P V (w j |z k ) are determined by maximization of the log-likelihood function: = log P ( F , V ) = ∑ i = 1 N ∑ j = 1 M n ( w i j ) log P ( f i , w j ) where n (w i j ) denotes the weight of annotation word w j , i.e., occurrence frequency, for image ƒ i ; and the model is resolved by applying the expectation-maximization (EM) technique, comprising: (i) an expectation (E) step where the posterior probabilities are computed for the hidden variable z k based on the current estimates of the parameters; and (ii) an maximization (M) step, where parameters are updated to maximize the expectation of the complete-data likelihood log P (F,V,Z) given the posterior probabilities computed in the preceding E-step, whereby the probabilities can be iteratively determined by fitting the model to the training image database and the associated annotations. 18. The Bayesian model according to claim 13 , wherein images are retrieved for word queries by determining the conditional probability P(ƒ i |w j ) P ( f i ❘ w j ) = ∫ P ( f i ❘ z ) P ( z ❘ w j ) ⅆ z = ∫ P V ( w j ❘ z ) p ( f i ❘ z ) P ( z ) P ( w j ) ⅆ z = E z { P V ( w j ❘ z ) p ( f i ❘ z ) P ( w j ) } in which the expectation is estimated as follows: P ( f i ❘ w j ) ≈ ∑ k = 1 K P V ( w j ❘ z k ) p ( f i ❘ z k ) ∑ h = 1 K P V ( w j ❘ z h ) = ∑ k = 1 K p ( f i ❘ z k ) y k where y k = P V ( w j ❘ z k ) ∑ h P V ( w j ❘ z h ) , and wherein the images in the database with the top highest P(ƒ i |w j ) are returned as the retrieval result for each query word. | 0.809037 |
17. The system of claim 16 wherein the set of descriptors comprise: annotation descriptors that annotate content elements found in the POD in order to identify basic pieces of information that constitute the attributes of the objects to extract; and object descriptors comprising object schemas that define which attributes defined by at least one of the annotation descriptors and other object descriptors, compose each of the objects to extract, and a set of semantic and spatial constraints and preferences that define expected spatial arrangement of the attributes defined in the object descriptors. | 17. The system of claim 16 wherein the set of descriptors comprise: annotation descriptors that annotate content elements found in the POD in order to identify basic pieces of information that constitute the attributes of the objects to extract; and object descriptors comprising object schemas that define which attributes defined by at least one of the annotation descriptors and other object descriptors, compose each of the objects to extract, and a set of semantic and spatial constraints and preferences that define expected spatial arrangement of the attributes defined in the object descriptors. 22. The system of claim 17 , wherein the object instances are created by searching for annotated content elements in the SSDM that compose given objects as defined by the object descriptors. | 0.852116 |
1. An electronic book, comprising: a screen for displaying an electronic book content; at least one first component with at least one underlying link, wherein, upon selection of the at least one first component, the at least one first component links to at least an Internet web site for providing a plurality of streaming video, audio and text data when connected to the electronic book, wherein location information for each of the plurality of streaming video, audio and text data is provided in at least one hidden links table and the at least one hidden links table is provided in conjunction with downloading the content of the electronic book from a remote provider, and each of the at least one hidden links table is associated with the at least one first component with the at least one underlying link, and wherein the location information provides access to the plurality of streaming video, audio and text data, and wherein the at least one first component is a part of a content of the electronic book; and a control function wherein the control function allows selection of one or more of the plurality of streaming video, audio and text data while displaying the content of the electronic book, and wherein the selected data is displayed on the screen of the electronic book, wherein the hidden links table is updatable from a most current links table using information transmitted via the Internet web site from the remote provider, wherein the most current links table is downloaded to the electronic book either periodically by the remote provider, or when a new electronic book content is downloaded to the electronic book by the remote provider, and wherein the control function includes an on-screen show links button, upon selection of which a link menu is displayed on the screen of the electronic book along with the content of the electronic book, wherein the link menu shows all of the first components with the underlying links contained in the content of the electronic book displayed on the screen of the electronic book, and shows linked materials including a number of links, link numbers and descriptions of the linked materials that each of the first components with the underlying links is able to be linked to, such that, by choosing one of the links, a user is able to link to one of the linked materials. | 1. An electronic book, comprising: a screen for displaying an electronic book content; at least one first component with at least one underlying link, wherein, upon selection of the at least one first component, the at least one first component links to at least an Internet web site for providing a plurality of streaming video, audio and text data when connected to the electronic book, wherein location information for each of the plurality of streaming video, audio and text data is provided in at least one hidden links table and the at least one hidden links table is provided in conjunction with downloading the content of the electronic book from a remote provider, and each of the at least one hidden links table is associated with the at least one first component with the at least one underlying link, and wherein the location information provides access to the plurality of streaming video, audio and text data, and wherein the at least one first component is a part of a content of the electronic book; and a control function wherein the control function allows selection of one or more of the plurality of streaming video, audio and text data while displaying the content of the electronic book, and wherein the selected data is displayed on the screen of the electronic book, wherein the hidden links table is updatable from a most current links table using information transmitted via the Internet web site from the remote provider, wherein the most current links table is downloaded to the electronic book either periodically by the remote provider, or when a new electronic book content is downloaded to the electronic book by the remote provider, and wherein the control function includes an on-screen show links button, upon selection of which a link menu is displayed on the screen of the electronic book along with the content of the electronic book, wherein the link menu shows all of the first components with the underlying links contained in the content of the electronic book displayed on the screen of the electronic book, and shows linked materials including a number of links, link numbers and descriptions of the linked materials that each of the first components with the underlying links is able to be linked to, such that, by choosing one of the links, a user is able to link to one of the linked materials. 21. The electronic book of claim 1 , wherein the hidden links table is updated when a new electronic book is purchased. | 0.549579 |
11. The one or more non-transitory machine-readable media of claim 7 , wherein the operations comprise: receiving language options on the mobile device; and outputting one or more selections from among the language options; wherein at least one of the initial language and the target language are based on the one or more selections. | 11. The one or more non-transitory machine-readable media of claim 7 , wherein the operations comprise: receiving language options on the mobile device; and outputting one or more selections from among the language options; wherein at least one of the initial language and the target language are based on the one or more selections. 12. The one or more non-transitory machine-readable media of claim 11 , wherein outputting is performed via a voice command. | 0.948529 |
1. A system for testing software, the system generating a multi-level test case from a unified modeling language (UML) sequence diagram (SD), the multi-level test case being based on a multiple condition control flow graph (MCCFG), the system comprising: at least one processor and a memory unit; a unified modeling language (UML) sequence diagram (SD) metamodel storing unit which stores a unified modeling language (UML) sequence diagram (SD) metamodel therein; a multiple condition control flow graph (MCCFG) metamodel storing unit which stores a multiple condition control flow graph (MCCFG) metamodel; a model converting unit which converts the unified modeling language (UML) sequence diagram (SD) according to the unified modeling language (UML) sequence diagram (SD) metamodel and the multiple condition control flow graph (MCCFG) metamodel and generates the multiple condition control flow graph (MCCFG); and a coverage criteria unit which converts the multiple condition control flow graph (MCCFG) into a plurality of test cases. | 1. A system for testing software, the system generating a multi-level test case from a unified modeling language (UML) sequence diagram (SD), the multi-level test case being based on a multiple condition control flow graph (MCCFG), the system comprising: at least one processor and a memory unit; a unified modeling language (UML) sequence diagram (SD) metamodel storing unit which stores a unified modeling language (UML) sequence diagram (SD) metamodel therein; a multiple condition control flow graph (MCCFG) metamodel storing unit which stores a multiple condition control flow graph (MCCFG) metamodel; a model converting unit which converts the unified modeling language (UML) sequence diagram (SD) according to the unified modeling language (UML) sequence diagram (SD) metamodel and the multiple condition control flow graph (MCCFG) metamodel and generates the multiple condition control flow graph (MCCFG); and a coverage criteria unit which converts the multiple condition control flow graph (MCCFG) into a plurality of test cases. 2. The apparatus of claim 1 , wherein the unified modeling language (UML) sequence diagram (SD) metamodel storing unit stores a unified modeling language (UML) sequence diagram (SD) metamodel extracted from a unified modeling language (UML) specification therein. | 0.543709 |
11. A device comprising: a touchscreen display; one or more processors; and computer-readable storage media including instructions executable by the one or more processors to perform operations comprising: displaying, by the touchscreen display, an image that includes one or more words in a first language, wherein at least one word of the one or more words is displayed at a non-horizontal angle relative to an edge of the touchscreen display; receiving, by the touchscreen display, a swipe gesture selecting a first portion of the image that includes at least part of the at least one word, wherein the swipe gesture is performed at approximately the non-horizontal angle; identifying, using edge-based text detection, a second portion of the image based at least in part on the first portion of the image, the second portion of the image including the at least one word; sending the second portion of the image that includes the at least one word to a server; receiving, from the server, a translation comprising one or more translated words in a second language, the translation corresponding to the at least one word of the one or more words in the first language; and displaying the translation by the touchscreen display. | 11. A device comprising: a touchscreen display; one or more processors; and computer-readable storage media including instructions executable by the one or more processors to perform operations comprising: displaying, by the touchscreen display, an image that includes one or more words in a first language, wherein at least one word of the one or more words is displayed at a non-horizontal angle relative to an edge of the touchscreen display; receiving, by the touchscreen display, a swipe gesture selecting a first portion of the image that includes at least part of the at least one word, wherein the swipe gesture is performed at approximately the non-horizontal angle; identifying, using edge-based text detection, a second portion of the image based at least in part on the first portion of the image, the second portion of the image including the at least one word; sending the second portion of the image that includes the at least one word to a server; receiving, from the server, a translation comprising one or more translated words in a second language, the translation corresponding to the at least one word of the one or more words in the first language; and displaying the translation by the touchscreen display. 16. The device of claim 11 , the operations further comprising: displaying a callout window that includes the first portion of the image; receiving a corrective gesture; and adjusting at least one of a height or a width of the callout window based at least in part on the corrective gesture. | 0.514553 |
1. A computerized method comprising: receiving a plurality of search criteria from a plurality of users respectively, the plurality of search criteria including a first search criterion that is respectively received from at least two of the plurality of users, the plurality of search criteria to be applied to a common information repository; associating source information and category information with each of the plurality of search criteria, the category information identifying a category of a plurality of categories into which information in the common information repository is categorized, and the source information identifying a source of a plurality of sources via which the plurality of search criteria are received and communicated to enable the receiving of the plurality of search criteria; storing each of the plurality of search criteria in association with the source information and the category information, the storing done at least in part through the use of one or more processors; and maintaining a count of instances of the first search criterion received from the at least two of the plurality of users for each of a plurality of unique source and category information combinations. | 1. A computerized method comprising: receiving a plurality of search criteria from a plurality of users respectively, the plurality of search criteria including a first search criterion that is respectively received from at least two of the plurality of users, the plurality of search criteria to be applied to a common information repository; associating source information and category information with each of the plurality of search criteria, the category information identifying a category of a plurality of categories into which information in the common information repository is categorized, and the source information identifying a source of a plurality of sources via which the plurality of search criteria are received and communicated to enable the receiving of the plurality of search criteria; storing each of the plurality of search criteria in association with the source information and the category information, the storing done at least in part through the use of one or more processors; and maintaining a count of instances of the first search criterion received from the at least two of the plurality of users for each of a plurality of unique source and category information combinations. 5. The computerized method of claim 1 , wherein the count of the instances is maintained over a determinable time interval and wherein the determinable time interval is modified based on a rate at which instances of the first search criterion are received. | 0.621992 |
17. The method of claim 1 comprising extracting one or more items of metadata from the one or more VOB files maintained on the storage media item. | 17. The method of claim 1 comprising extracting one or more items of metadata from the one or more VOB files maintained on the storage media item. 18. The method of claim 17 wherein indexing comprises indexing the captions, subtitles, descriptions and corresponding video and audio content associated with the one or more segments of the one or more VOB files using the metadata associated with the VOB files. | 0.84375 |
5. The electronic device of claim 1 , wherein: the request to delete the first candidate character comprises a first swipe detected on the touch-sensitive surface of the device, and receiving the input to replace the first candidate character with a different candidate character from the first plurality of other candidate characters comprises receiving an indication of a second input that corresponds to selection of a respective one of the first plurality of other candidate characters; and the one or more programs further include instructions for: in response to the second input, updating the user interface to include the respective one of the first plurality of other candidate characters in the candidate character region. | 5. The electronic device of claim 1 , wherein: the request to delete the first candidate character comprises a first swipe detected on the touch-sensitive surface of the device, and receiving the input to replace the first candidate character with a different candidate character from the first plurality of other candidate characters comprises receiving an indication of a second input that corresponds to selection of a respective one of the first plurality of other candidate characters; and the one or more programs further include instructions for: in response to the second input, updating the user interface to include the respective one of the first plurality of other candidate characters in the candidate character region. 7. The electronic device of claim 5 , wherein the one or more programs further include instructions for: while displaying the respective one of the first plurality of other candidate characters in the candidate character region, receiving an indication of a second swipe detected on the touch-sensitive surface of the device; in accordance with a determination that the second swipe comprises a swipe having a same direction as the first swipe, updating the user interface by deleting the respective one of the first plurality of other candidate characters in the candidate character region; and in accordance with a determination that the second swipe comprises a swipe and hold, the swipe having a same direction as the first swipe, updating the user interface by deleting the respective one of the first plurality of other candidate characters in the candidate character region and other candidate characters in the candidate character region until a release of the hold is detected. | 0.678715 |
1. A computer-implemented method for building a user profile of a user, the method comprising: labeling and storing user registration information in a database as a set of demographic nouns; analyzing, with a computing device, author-generated classification information regarding at least one document of a set of documents and assigning a set of first taxonomic nouns to characterize the user based upon the author-generated classification information; examining, with a computing device, a user-generated tag from a client computer and characterizing the user of at least one document of the set of documents and assigning a set of second taxonomic nouns to characterize the user based upon the user-generated tag characterization; identifying, with a computing device, a method by which the user accessed at least one document of the set of documents from a content provider and assigning a set of third taxonomic nouns to characterize the user based upon the method of access; evaluating, with a computing device, attributes that are related to the method of access and assigning a set of fourth taxonomic nouns to characterize the user based upon the attributes related to the method of access; processing, with a computing device, at least one document of the set of documents to extract a set of fifth taxonomic nouns to characterize the user; aggregating, with a computing device, the set of first taxonomic nouns, the set of second taxonomic nouns, the set of third taxonomic nouns, the set of fourth taxonomic nouns, and the set of fifth taxonomic nouns into a composite set of taxonomic nouns; building, with a computing device, a user profile based upon the composite set of taxonomic nouns, the author-generated classification information, and at least one of the demographic nouns; comparing, with a computing device, the composite set of taxonomic nouns with taxonomic nouns associated with a plurality of other user profiles corresponding to a plurality of other users; and modifying, with a computing device, the user profile based on the comparison. | 1. A computer-implemented method for building a user profile of a user, the method comprising: labeling and storing user registration information in a database as a set of demographic nouns; analyzing, with a computing device, author-generated classification information regarding at least one document of a set of documents and assigning a set of first taxonomic nouns to characterize the user based upon the author-generated classification information; examining, with a computing device, a user-generated tag from a client computer and characterizing the user of at least one document of the set of documents and assigning a set of second taxonomic nouns to characterize the user based upon the user-generated tag characterization; identifying, with a computing device, a method by which the user accessed at least one document of the set of documents from a content provider and assigning a set of third taxonomic nouns to characterize the user based upon the method of access; evaluating, with a computing device, attributes that are related to the method of access and assigning a set of fourth taxonomic nouns to characterize the user based upon the attributes related to the method of access; processing, with a computing device, at least one document of the set of documents to extract a set of fifth taxonomic nouns to characterize the user; aggregating, with a computing device, the set of first taxonomic nouns, the set of second taxonomic nouns, the set of third taxonomic nouns, the set of fourth taxonomic nouns, and the set of fifth taxonomic nouns into a composite set of taxonomic nouns; building, with a computing device, a user profile based upon the composite set of taxonomic nouns, the author-generated classification information, and at least one of the demographic nouns; comparing, with a computing device, the composite set of taxonomic nouns with taxonomic nouns associated with a plurality of other user profiles corresponding to a plurality of other users; and modifying, with a computing device, the user profile based on the comparison. 9. The computer-implemented method for building a user profile of claim 1 , wherein the attributes related to the method of access include at least one of sharing the user's interests, clicking on a newsletter, participating in a discussion, reading or writing a blog, downloading a white paper, purchasing a product or a service, reviewing a product or service, sharing a document, posting to a social network, sending an email, and disclosing information about the user. | 0.564112 |
1. A method comprising: providing, on a user interface associated with an apparatus, a presentation of a menu of one or more topics from among a predetermined hierarchy of topics and subtopics to a user; receiving, via the user interface by the apparatus, a first input from the user specifying at least one of the one or more topics from among the predetermined hierarchy of topics and subtopics; retrieving, by the apparatus, one or more documents associated with the user; extracting, by the apparatus, noun tokens from the documents based, at least in part, on the specified topics; performing, by the apparatus, histogram processing of the extracted noun tokens to provide a list of pertinent tokens; comparing, by the apparatus, topic input information received from the user with the list of pertinent tokens to determine if there is a corresponding match; generating, by the apparatus, a topology of the matching tokens according to a probabilistic model, wherein the topology matches the matching pertinent tokens with the topics and subtopics of the hierarchy; providing, on the user interface by the apparatus, a presentation of top-level topics as topic icons on a tool bar on the user interface based, at least in part, on the topology of matching tokens; and in response to a second input from the user specifying one of the topic icons, providing, on the user interface by the apparatus, a presentation of one or more search results customized for the user using machine learning based on the topology. | 1. A method comprising: providing, on a user interface associated with an apparatus, a presentation of a menu of one or more topics from among a predetermined hierarchy of topics and subtopics to a user; receiving, via the user interface by the apparatus, a first input from the user specifying at least one of the one or more topics from among the predetermined hierarchy of topics and subtopics; retrieving, by the apparatus, one or more documents associated with the user; extracting, by the apparatus, noun tokens from the documents based, at least in part, on the specified topics; performing, by the apparatus, histogram processing of the extracted noun tokens to provide a list of pertinent tokens; comparing, by the apparatus, topic input information received from the user with the list of pertinent tokens to determine if there is a corresponding match; generating, by the apparatus, a topology of the matching tokens according to a probabilistic model, wherein the topology matches the matching pertinent tokens with the topics and subtopics of the hierarchy; providing, on the user interface by the apparatus, a presentation of top-level topics as topic icons on a tool bar on the user interface based, at least in part, on the topology of matching tokens; and in response to a second input from the user specifying one of the topic icons, providing, on the user interface by the apparatus, a presentation of one or more search results customized for the user using machine learning based on the topology. 2. A method of claim 1 , wherein the extracting of the noun tokens comprises: identifying substantially all noun tokens in the documents; selecting one of the identified noun tokens based, at least in part, on whether the one identified noun token is semantically related to the specified topics, wherein the extracted noun tokens include the selected one identified noun token; providing, on the user interface by the apparatus, a presentation of topics determined based on the topology; and receiving, via the user interface by the apparatus, a third input from the user specifying a subset of the topics, wherein the topic icons correspond to the subset of the topics. | 0.525465 |
11. The apparatus according to claim 10 , further comprising means for identifying information related to the one of the plurality of multiword expressions using the path number. | 11. The apparatus according to claim 10 , further comprising means for identifying information related to the one of the plurality of multiword expressions using the path number. 12. The apparatus according to claim 11 , wherein the information related to the one of the plurality of multiword expressions includes one of categorization information, frequency of use, style of use, pronunciation, nuances of use, a synonym, an antonym, and a translation. | 0.904501 |
1. A method comprising: selecting a first configuration item from a source dataset; failing to identify the first configuration item with configuration items in a target dataset of a configuration management database using identification rules without automatically modifiable acceptance criteria; evaluating a rule against the first configuration item and a second configuration item of the target dataset; marking the first configuration item as identified with the second configuration item upon successful evaluation of the rule if a threshold value for the rule exceeds a predetermined acceptance value; and automatically adjusting the threshold value responsive to the act of marking. | 1. A method comprising: selecting a first configuration item from a source dataset; failing to identify the first configuration item with configuration items in a target dataset of a configuration management database using identification rules without automatically modifiable acceptance criteria; evaluating a rule against the first configuration item and a second configuration item of the target dataset; marking the first configuration item as identified with the second configuration item upon successful evaluation of the rule if a threshold value for the rule exceeds a predetermined acceptance value; and automatically adjusting the threshold value responsive to the act of marking. 14. The method of claim 1 , wherein the rule is selected based on a class of the first configuration item and the acceptance value is for the class of the first configuration item. | 0.792008 |
13. An apparatus for controlling home electronic devices connected to a home network comprising: an action library which stores action data for controlling the home electronic devices connected to the home network; a voice recognition unit which receives a user voice command and recognizes the user voice command as a character command; a command interpretation unit which converts the character command into a logical command, wherein the command interpretation unit comprises: a command surface analysis unit which extracts actions and objects from the character command and stores semantic information related to the meaning of the extracted actions and semantic information related to the meaning of the extracted objects, and a command deep analysis unit which analyzes the stored semantic information to remove semantic ambiguity from the actions and objects based on the semantic information of the character command and outputs the logical command based on the analysis, wherein a time that the character command is received is used to interpret a meaning of an object; an action planning unit which generates an action list comprising a series of actions used to execute the logical command by searching the action library, wherein the generated action list is influenced by which electronic devices are currently connected to the home network and by state information of the electronic devices currently connected to the home network; and a home electronic device control unit which converts the series of actions contained in the action list into a control signal and controls the home electronic devices connected to the home network according to the control signal. | 13. An apparatus for controlling home electronic devices connected to a home network comprising: an action library which stores action data for controlling the home electronic devices connected to the home network; a voice recognition unit which receives a user voice command and recognizes the user voice command as a character command; a command interpretation unit which converts the character command into a logical command, wherein the command interpretation unit comprises: a command surface analysis unit which extracts actions and objects from the character command and stores semantic information related to the meaning of the extracted actions and semantic information related to the meaning of the extracted objects, and a command deep analysis unit which analyzes the stored semantic information to remove semantic ambiguity from the actions and objects based on the semantic information of the character command and outputs the logical command based on the analysis, wherein a time that the character command is received is used to interpret a meaning of an object; an action planning unit which generates an action list comprising a series of actions used to execute the logical command by searching the action library, wherein the generated action list is influenced by which electronic devices are currently connected to the home network and by state information of the electronic devices currently connected to the home network; and a home electronic device control unit which converts the series of actions contained in the action list into a control signal and controls the home electronic devices connected to the home network according to the control signal. 18. The apparatus of claim 13 , further comprising: a device monitoring unit which monitors states of home electronic devices which change according to control of the home electronic devices connected to the home network. | 0.5 |
7. A computer-implemented method for providing snapshots, comprising: displaying, at a mashup client computer via a display interface, a mashup or service, interacting with the user to input, at the client computer via a user input device interface, an indication to take a snapshot of the mashup or service being currently displayed via the display interface, and storing, at a mashup server computer, a snapshot artifact of live data from the mashup or service at the instant the snapshot is taken. | 7. A computer-implemented method for providing snapshots, comprising: displaying, at a mashup client computer via a display interface, a mashup or service, interacting with the user to input, at the client computer via a user input device interface, an indication to take a snapshot of the mashup or service being currently displayed via the display interface, and storing, at a mashup server computer, a snapshot artifact of live data from the mashup or service at the instant the snapshot is taken. 10. The method of claim 7 , further comprising interacting with the user so as to share the snapshot with another user. | 0.834711 |
1. A method of performing data loss prevention on content from a content source, the method comprising: generating, by processing circuitry, multiple variants from the content, the multiple variants including a set of variants for each parsed word of the content, each variant of the set (i) including multiple characters and (ii) differing from other variants of the set by at least one character; performing, by the processing circuitry, evaluation operations to determine whether any of the variants includes sensitive data; and in response to the evaluation operations, performing, by the processing circuitry, a control operation which (i) releases all of the parsed words of the content to a destination when none of the variants is determined to include sensitive data, and (ii) blocks at least one parsed word of the content from reaching the destination when at least one variant is determined to include sensitive data; wherein generating the multiple variants from the content includes: applying a set of predefined transformations from a transformation database to the content from the content source to form the multiple variants. | 1. A method of performing data loss prevention on content from a content source, the method comprising: generating, by processing circuitry, multiple variants from the content, the multiple variants including a set of variants for each parsed word of the content, each variant of the set (i) including multiple characters and (ii) differing from other variants of the set by at least one character; performing, by the processing circuitry, evaluation operations to determine whether any of the variants includes sensitive data; and in response to the evaluation operations, performing, by the processing circuitry, a control operation which (i) releases all of the parsed words of the content to a destination when none of the variants is determined to include sensitive data, and (ii) blocks at least one parsed word of the content from reaching the destination when at least one variant is determined to include sensitive data; wherein generating the multiple variants from the content includes: applying a set of predefined transformations from a transformation database to the content from the content source to form the multiple variants. 16. A method as in claim 1 wherein performing the evaluation operations includes: performing matching operations which compare both (i) the content from the content source as well as (ii) each variant formed from the content to a database of sensitive data and sensitive data patterns to determine whether any of the content and variants includes sensitive data. | 0.602783 |
1. A computer-implemented method of batch processing in a batch component model within a distributed object environment, the computer-implemented method comprising: instantiating a batch component by a processor of a data processing system, for use with a batch job within the distributed object environment; initializing the batch component with a set of deployment descriptors and an instance of a batch container to form a contractual relationship between the batch component and the batch container, wherein the set of deployment descriptors is a set of declarative policies for the batch component; wrapping the contractual relationship between the batch component and the batch container to form an adapter, wherein the adapter isolates the batch component from different implementations of the batch container; dynamically computing by the batch container, for each use of a checkpoint interval, a size of the checkpoint interval for the batch job based on the set of deployment descriptors and other processing workloads; managing operation of the batch component in the batch component model by the batch container in accordance with the set of deployment descriptors and the other processing workloads; and committing, by the batch container on the processor, at an end of the checkpoint interval, checkpoint cursors and data of the batch job that are updated during the batch processing to a storage of the data processing system, wherein context information, including the size of the checkpoint interval and resource dependencies, is persisted and passed to downstream batch containers. | 1. A computer-implemented method of batch processing in a batch component model within a distributed object environment, the computer-implemented method comprising: instantiating a batch component by a processor of a data processing system, for use with a batch job within the distributed object environment; initializing the batch component with a set of deployment descriptors and an instance of a batch container to form a contractual relationship between the batch component and the batch container, wherein the set of deployment descriptors is a set of declarative policies for the batch component; wrapping the contractual relationship between the batch component and the batch container to form an adapter, wherein the adapter isolates the batch component from different implementations of the batch container; dynamically computing by the batch container, for each use of a checkpoint interval, a size of the checkpoint interval for the batch job based on the set of deployment descriptors and other processing workloads; managing operation of the batch component in the batch component model by the batch container in accordance with the set of deployment descriptors and the other processing workloads; and committing, by the batch container on the processor, at an end of the checkpoint interval, checkpoint cursors and data of the batch job that are updated during the batch processing to a storage of the data processing system, wherein context information, including the size of the checkpoint interval and resource dependencies, is persisted and passed to downstream batch containers. 7. The computer-implemented method of claim 1 , wherein the set of deployment descriptors includes descriptors for identifying business function components, symbolic references resolved at deployment time, for conditioning a checkpoint interval and enumerating resource dependencies identify resources that are needed for the batch job. | 0.633347 |
14. The computer-based recommendation system of claim 1 , wherein the condition score further represents an estimated preference impact based on at least one status attribute that may affect the user's preference for the unique item. | 14. The computer-based recommendation system of claim 1 , wherein the condition score further represents an estimated preference impact based on at least one status attribute that may affect the user's preference for the unique item. 15. The computer-based recommendation system of claim 14 , wherein the at least one status attribute describes at least one of the following: a listing price, a geographic location, a type of seller. | 0.952358 |
18. A non-transitory computer-readable recording media recording a program for causing a computer to function as a symbol insertion apparatus for inserting a symbol in a word sequence transcribing voice information comprising: a symbol insertion likelihood calculation unit that obtains a symbol insertion likelihood of the word sequence for each of a plurality of symbol insertion models, the plurality of symbol insertion models being supplied for the word sequence to insert the symbol in for each speaking style feature; a speaking style feature similarity calculation unit that obtains a similarity between the speaking style feature of the word sequence and a plurality of speaking style feature models; and a symbol insertion evaluation unit that weights the symbol insertion likelihood obtained for the word sequence for each of the plurality of symbol insertion models according to the similarly between the speaking style feature of the word sequence and the plurality of speaking style feature models and a relevance between the symbol insertion model and the speaking style feature model, and perform symbol insertion evaluation to the word sequence. | 18. A non-transitory computer-readable recording media recording a program for causing a computer to function as a symbol insertion apparatus for inserting a symbol in a word sequence transcribing voice information comprising: a symbol insertion likelihood calculation unit that obtains a symbol insertion likelihood of the word sequence for each of a plurality of symbol insertion models, the plurality of symbol insertion models being supplied for the word sequence to insert the symbol in for each speaking style feature; a speaking style feature similarity calculation unit that obtains a similarity between the speaking style feature of the word sequence and a plurality of speaking style feature models; and a symbol insertion evaluation unit that weights the symbol insertion likelihood obtained for the word sequence for each of the plurality of symbol insertion models according to the similarly between the speaking style feature of the word sequence and the plurality of speaking style feature models and a relevance between the symbol insertion model and the speaking style feature model, and perform symbol insertion evaluation to the word sequence. 21. A non-transitory computer-readable recording media according to claim 18 , wherein the computer comprises a model relevance storage means that holds the relevance. | 0.695134 |
17. A computer-readable medium storing instructions that, when executed, cause the following to occur: identifying a textual item in a user interface; associating a plurality of different audio files with the textual item, wherein the plurality of different audio files comprise a corresponding plurality of different audio announcements of the textual item; receiving, by a computing device, a first selection of the textual item in the user interface; determining a first one of the plurality of different audio files to use for audibly announcing the textual item, wherein the determining is based on a rule governing audio announcement in response to repeated selection of the textual item; causing playback of the first one of the plurality of different audio files based on the determining and responsive to the first selection of the textual item; receiving, by the computing device, a second selection of the textual item in the user interface; determining whether the second selection is a repeated selection of the textual item; and in response to determining that the second selection is a repeated selection of the textual item, causing playback of a second one of the plurality of different audio files responsive to the repeated selection of the textual item, wherein the second one of the plurality of different audio files comprises a different amount of explanatory speech than the first one of the plurality of different audio files. | 17. A computer-readable medium storing instructions that, when executed, cause the following to occur: identifying a textual item in a user interface; associating a plurality of different audio files with the textual item, wherein the plurality of different audio files comprise a corresponding plurality of different audio announcements of the textual item; receiving, by a computing device, a first selection of the textual item in the user interface; determining a first one of the plurality of different audio files to use for audibly announcing the textual item, wherein the determining is based on a rule governing audio announcement in response to repeated selection of the textual item; causing playback of the first one of the plurality of different audio files based on the determining and responsive to the first selection of the textual item; receiving, by the computing device, a second selection of the textual item in the user interface; determining whether the second selection is a repeated selection of the textual item; and in response to determining that the second selection is a repeated selection of the textual item, causing playback of a second one of the plurality of different audio files responsive to the repeated selection of the textual item, wherein the second one of the plurality of different audio files comprises a different amount of explanatory speech than the first one of the plurality of different audio files. 30. The computer-readable medium of claim 17 , further storing instructions that, when executed, cause the following to occur: while a user is accessing the user interface, generating a new audio file to correspond with a new textual item in the user interface. | 0.566384 |
14. A computer implemented system for benchmarking a brand based on social media strength of said brand, comprising: a brand monitoring platform comprising at least one processor configured to execute modules of said brand monitoring platform for monitoring said brand in a virtual social media environment, said modules of said brand monitoring platform comprising: an information acquisition module that acquires input information on said brand; an industry identification module that identifies industries related to said brand and competing brands in said identified industries using said acquired input information on said brand; said information acquisition module that acquires social media information related to said brand and said competing brands in said identified industries from a plurality of social media sources in said virtual social media environment via a network; a category generation module that dynamically generates categories in one or more hierarchical levels in each of said identified industries based on an independent analysis of said acquired social media information related to said brand and said competing brands from each of said social media sources; a sorting module that sorts said acquired social media information related to said brand and said competing brands in said each of said identified industries into one or more of said dynamically generated categories in said one or more hierarchical levels using a sorting interface; a scoring module that determines an audience score for said brand and each of said competing brands by measuring an aggregate reach of said brand and said each of said competing brands in said virtual social media environment based on one or more of a plurality of weighted audience score metric parameters using said sorted social media information; said scoring module that determines an engagement score for said brand and said each of said competing brands by measuring interaction between said brand and said each of said competing brands and their followers based on one or more of a plurality of weighted engagement score metric parameters using said sorted social media information; said scoring module that generates an aggregate score for said brand and said each of said competing brands using said determined audience score and said determined engagement score; and said scoring module that determines said social media strength of said brand in comparison with said competing brands in said virtual social media environment by assigning a rank to said brand and said each of said competing brands based on said aggregate score for said benchmarking of said brand based on said social media strength of said brand in comparison with said competing brands in said virtual social media environment; whereby said generated aggregate score of said brand and said each of said competing brands benchmarks said brand based on said social media strength of said brand in comparison with said competing brands in said virtual social media environment. | 14. A computer implemented system for benchmarking a brand based on social media strength of said brand, comprising: a brand monitoring platform comprising at least one processor configured to execute modules of said brand monitoring platform for monitoring said brand in a virtual social media environment, said modules of said brand monitoring platform comprising: an information acquisition module that acquires input information on said brand; an industry identification module that identifies industries related to said brand and competing brands in said identified industries using said acquired input information on said brand; said information acquisition module that acquires social media information related to said brand and said competing brands in said identified industries from a plurality of social media sources in said virtual social media environment via a network; a category generation module that dynamically generates categories in one or more hierarchical levels in each of said identified industries based on an independent analysis of said acquired social media information related to said brand and said competing brands from each of said social media sources; a sorting module that sorts said acquired social media information related to said brand and said competing brands in said each of said identified industries into one or more of said dynamically generated categories in said one or more hierarchical levels using a sorting interface; a scoring module that determines an audience score for said brand and each of said competing brands by measuring an aggregate reach of said brand and said each of said competing brands in said virtual social media environment based on one or more of a plurality of weighted audience score metric parameters using said sorted social media information; said scoring module that determines an engagement score for said brand and said each of said competing brands by measuring interaction between said brand and said each of said competing brands and their followers based on one or more of a plurality of weighted engagement score metric parameters using said sorted social media information; said scoring module that generates an aggregate score for said brand and said each of said competing brands using said determined audience score and said determined engagement score; and said scoring module that determines said social media strength of said brand in comparison with said competing brands in said virtual social media environment by assigning a rank to said brand and said each of said competing brands based on said aggregate score for said benchmarking of said brand based on said social media strength of said brand in comparison with said competing brands in said virtual social media environment; whereby said generated aggregate score of said brand and said each of said competing brands benchmarks said brand based on said social media strength of said brand in comparison with said competing brands in said virtual social media environment. 16. The computer implemented system of claim 14 , wherein said scoring module generates said aggregate score for said brand and said each of said competing brands by determining a weighted average of said determined audience score and said determined engagement score. | 0.762151 |
32. A system as claimed in claim 31 , including a sampler for randomly selecting from said example input phrases to provide said sets. | 32. A system as claimed in claim 31 , including a sampler for randomly selecting from said example input phrases to provide said sets. 33. A system as claimed in claim 32 , wherein said sampler is adapted to randomly selecting from example input phrases to provide a test set of input phrases, and wherein said relationship is determined on the basis of respective portions of said test set predicted by said grammars. | 0.881646 |
14. A system, comprising: a processor; and a memory containing a program which, when executed by the processor, is configured to perform an operation for magnifying content on a graphical display, the operation comprising: receiving user input specifying a selection area of the graphical display to be magnified; specifying a display area of the graphical display within which to output a magnified copy of the specified selection area; generating the magnified copy of the specified selection area; and outputting the magnified copy of the specified selection area within the specified display area, wherein the specified selection area remains at least partially visible on the graphical display separate from the specified display area wherein a predefined area selected from the selection area and display area is anchored to a display element of an application window, such that a position of predefined area relative to the display element remains fixed when the display element is moved within the graphical display. | 14. A system, comprising: a processor; and a memory containing a program which, when executed by the processor, is configured to perform an operation for magnifying content on a graphical display, the operation comprising: receiving user input specifying a selection area of the graphical display to be magnified; specifying a display area of the graphical display within which to output a magnified copy of the specified selection area; generating the magnified copy of the specified selection area; and outputting the magnified copy of the specified selection area within the specified display area, wherein the specified selection area remains at least partially visible on the graphical display separate from the specified display area wherein a predefined area selected from the selection area and display area is anchored to a display element of an application window, such that a position of predefined area relative to the display element remains fixed when the display element is moved within the graphical display. 19. The system of claim 14 , wherein the position is specified in terms of one of: (i) a number of pixels from a reference point and (ii) a percentage of pixels from a border relative to a length of the border in pixels. | 0.737882 |
22. A system that implements a cloud service for providing optimized web domains classification based on progressive crawling with clustering, comprising: a processor configured to: distribute a first Uniform Resource Locator (URL) content categorization data feed to a first plurality of subscribers, wherein the first URL content categorization data feed is collected using an optimized web domains classification based on progressive crawling with clustering to determine which category clusters to publish for each categorized web domain, and wherein the distributing of the first Uniform Resource Locator (URL) content categorization data feed to the first plurality of subscribers comprises: receive a request to classify content for a first web domain from a first security device; automatically classify the content for the first web domain, comprising: crawl a plurality of pages in the first web domain; determine a category for the plurality of pages in the first web domain; group more than one page having the same category into a first cluster; determine whether a number of the more than one page of the first cluster exceeds a first threshold; and in the event that the number of the more than one page of the first cluster does not exceed the first threshold, select a new page within the domain to crawl and classify; and send the classification for the content for the first web domain to the first security device; and distribute a second URL content categorization data feed to a second plurality of subscribers, wherein the second URL content categorization data feed is collected using an optimized web domains classification based on progressive crawling with clustering to determine which category clusters to publish for each categorized web domain; and a memory coupled to the processor and configured to provide the processor with instructions. | 22. A system that implements a cloud service for providing optimized web domains classification based on progressive crawling with clustering, comprising: a processor configured to: distribute a first Uniform Resource Locator (URL) content categorization data feed to a first plurality of subscribers, wherein the first URL content categorization data feed is collected using an optimized web domains classification based on progressive crawling with clustering to determine which category clusters to publish for each categorized web domain, and wherein the distributing of the first Uniform Resource Locator (URL) content categorization data feed to the first plurality of subscribers comprises: receive a request to classify content for a first web domain from a first security device; automatically classify the content for the first web domain, comprising: crawl a plurality of pages in the first web domain; determine a category for the plurality of pages in the first web domain; group more than one page having the same category into a first cluster; determine whether a number of the more than one page of the first cluster exceeds a first threshold; and in the event that the number of the more than one page of the first cluster does not exceed the first threshold, select a new page within the domain to crawl and classify; and send the classification for the content for the first web domain to the first security device; and distribute a second URL content categorization data feed to a second plurality of subscribers, wherein the second URL content categorization data feed is collected using an optimized web domains classification based on progressive crawling with clustering to determine which category clusters to publish for each categorized web domain; and a memory coupled to the processor and configured to provide the processor with instructions. 24. The system recited in claim 22 , wherein the processor is further configured to: receive a request to classify content for a second web domain from a second security device; automatically classify the content for the second web domain; and send the classification for the content for the second web domain to the second security device. | 0.565683 |
1. A method for generating a plurality of application programming interfaces (APIs) in a codeless manner, the method comprising: receiving a request for a plurality of APIs based on a description of a database schema; upon identifying the database schema description, generating a set of data graphs that identifies relationships between a set of data objects included in the description; generating the plurality of APIs based on the set of data graphs and providing the generated APIs to a user for selecting a subset of the plurality of APIs; and upon selection of an API, generating a JavaScript object notation based model (JSON-based model) associated with the selected API, the JSON-based model comprising a JSON file and a JavaScript (JS) file for an application to use to exchange data with the database. | 1. A method for generating a plurality of application programming interfaces (APIs) in a codeless manner, the method comprising: receiving a request for a plurality of APIs based on a description of a database schema; upon identifying the database schema description, generating a set of data graphs that identifies relationships between a set of data objects included in the description; generating the plurality of APIs based on the set of data graphs and providing the generated APIs to a user for selecting a subset of the plurality of APIs; and upon selection of an API, generating a JavaScript object notation based model (JSON-based model) associated with the selected API, the JSON-based model comprising a JSON file and a JavaScript (JS) file for an application to use to exchange data with the database. 7. The method of claim 1 , wherein the database comprises a relational database (RDB). | 0.659983 |
18. An auto-segmentation apparatus comprising: a processor configured to: perform atlas-based auto-segmentation on a plurality of points in a subject image using atlas images to generate first data representative of at least one structure in the subject image, wherein the processor is further configured to perform the atlas-based auto-segmentation by registering the subject image with a plurality of the atlas images to map point of the subject images to points of the atlas images, apply a plurality of points in the subject image to a trained classifier to generate second data representative of the a least one structure in the subject image, combine the first data with the second data to generate third data representative of the at least one structure in the subject image, and determine based on the data structure classification associated with the subject image. | 18. An auto-segmentation apparatus comprising: a processor configured to: perform atlas-based auto-segmentation on a plurality of points in a subject image using atlas images to generate first data representative of at least one structure in the subject image, wherein the processor is further configured to perform the atlas-based auto-segmentation by registering the subject image with a plurality of the atlas images to map point of the subject images to points of the atlas images, apply a plurality of points in the subject image to a trained classifier to generate second data representative of the a least one structure in the subject image, combine the first data with the second data to generate third data representative of the at least one structure in the subject image, and determine based on the data structure classification associated with the subject image. 19. The apparatus of claim 18 , wherein the processor is further configured to select a subset of the points in the subject image, and limit the points of the subject image that are applied to the trained classifier to the selected subset. | 0.746249 |
15. A non-transitory computer-readable medium having instructions stored therein that, when executed by at least one processor, cause the processor to: electronically translate, by the processor during an automated translation process, a first plurality of words in a source language so as to obtain a second plurality of words in a target language, wherein, to electronically translate, the processor is to: perform lexical-morphological analysis of the first plurality of words to generate a lexical-morphological structure of at least one sentence in the first plurality of words, perform syntactic analysis using the lexical-morphological structure of the at least one sentence to generate a language-independent semantic structure, perform syntactic synthesis based on the language-independent semantic structure to generate the second plurality of words, and identify first one or more likely erroneous words in the first plurality of words and corresponding second one or more likely erroneous words in the second plurality of words; display, on a display device, the first plurality of words in the source language; display, on the display device, the second plurality of words in the target language; automatically indicate, on the display device as part of the automated translation process, the first one or more likely erroneous words within the displayed first plurality of words in the source language; automatically indicate, on the display device as part of the automated translation process, the second one or more likely erroneous words within the displayed second plurality of words in the target language; receive a change to the first one or more likely erroneous words; and modify the second plurality of words to provide another translation in the target language based on the change in the first one or more likely erroneous words. | 15. A non-transitory computer-readable medium having instructions stored therein that, when executed by at least one processor, cause the processor to: electronically translate, by the processor during an automated translation process, a first plurality of words in a source language so as to obtain a second plurality of words in a target language, wherein, to electronically translate, the processor is to: perform lexical-morphological analysis of the first plurality of words to generate a lexical-morphological structure of at least one sentence in the first plurality of words, perform syntactic analysis using the lexical-morphological structure of the at least one sentence to generate a language-independent semantic structure, perform syntactic synthesis based on the language-independent semantic structure to generate the second plurality of words, and identify first one or more likely erroneous words in the first plurality of words and corresponding second one or more likely erroneous words in the second plurality of words; display, on a display device, the first plurality of words in the source language; display, on the display device, the second plurality of words in the target language; automatically indicate, on the display device as part of the automated translation process, the first one or more likely erroneous words within the displayed first plurality of words in the source language; automatically indicate, on the display device as part of the automated translation process, the second one or more likely erroneous words within the displayed second plurality of words in the target language; receive a change to the first one or more likely erroneous words; and modify the second plurality of words to provide another translation in the target language based on the change in the first one or more likely erroneous words. 18. The computer-readable medium of claim 15 , wherein, to automatically indicate the first one or more likely erroneous words, the processor is further to indicate different lexical errors or syntactical errors associated with the first one or more likely erroneous words by different distinctive display styles. | 0.512853 |
1. A method of processing documents, comprising: parsing, in connection with at least one processor, a document into a plurality constituent nodes, the document including a plurality of Document Object Model (DOM) objects representable in accordance with an object model; storing the parsed constituent nodes in a plurality of cacheable partitions, the cacheable partitions being located in a memory or a non-transitory backing store, wherein a first node of the parsed constituent nodes is stored in a first partition of the plurality of partitions and a second node of the parsed constituent nodes is stored in a second partition of the plurality of partitions, and each said cacheable partition having an associated commit level that initially is set to 0; storing, for each said cacheable partition, an identifier thereof in a partition table list, the identifier(s) in the partition table list collectively identifying the working contents of the document, the partition table list initially being designated as a current partition table list and initially being designated as having a current commit level of 0; handling a request from a user program for an object from the document by identifying the one or more partitions in which nodes corresponding to the requested object are located and instantiating only said requested objects from the identified partition(s) in accordance with the object model; in response to a request for an atomic update to the document: pushing onto a stack, configured to hold one or more previous partition table lists, a copy of the current partition table list; incrementing the current commit level; determining whether a given partition's contents are changed as a result of the atomic update and whether the commit level associated with the given partition does not match the current commit level; and when a given partition's contents are changed as a result of the atomic update and the commit level associated with the given partition does not match the current commit level, copying the given partition's contents to create a new partition with the changed contents and replace the identifier for the given partition in the current partition table list with an identifier for the new partition; and in response to an atomic update being completed: popping from the stack the uppermost partition table list, the popped partition table list being a candidate partition table list; determining partitions in the current partition table list that have associated commit levels that match the current commit level into the candidate partition table list; copying identifiers for any partitions in the current partition table list that have associated commit levels that match the current commit level into the candidate partition table list; replacing the current partition table list with the candidate list; and decrementing the current commit level. | 1. A method of processing documents, comprising: parsing, in connection with at least one processor, a document into a plurality constituent nodes, the document including a plurality of Document Object Model (DOM) objects representable in accordance with an object model; storing the parsed constituent nodes in a plurality of cacheable partitions, the cacheable partitions being located in a memory or a non-transitory backing store, wherein a first node of the parsed constituent nodes is stored in a first partition of the plurality of partitions and a second node of the parsed constituent nodes is stored in a second partition of the plurality of partitions, and each said cacheable partition having an associated commit level that initially is set to 0; storing, for each said cacheable partition, an identifier thereof in a partition table list, the identifier(s) in the partition table list collectively identifying the working contents of the document, the partition table list initially being designated as a current partition table list and initially being designated as having a current commit level of 0; handling a request from a user program for an object from the document by identifying the one or more partitions in which nodes corresponding to the requested object are located and instantiating only said requested objects from the identified partition(s) in accordance with the object model; in response to a request for an atomic update to the document: pushing onto a stack, configured to hold one or more previous partition table lists, a copy of the current partition table list; incrementing the current commit level; determining whether a given partition's contents are changed as a result of the atomic update and whether the commit level associated with the given partition does not match the current commit level; and when a given partition's contents are changed as a result of the atomic update and the commit level associated with the given partition does not match the current commit level, copying the given partition's contents to create a new partition with the changed contents and replace the identifier for the given partition in the current partition table list with an identifier for the new partition; and in response to an atomic update being completed: popping from the stack the uppermost partition table list, the popped partition table list being a candidate partition table list; determining partitions in the current partition table list that have associated commit levels that match the current commit level into the candidate partition table list; copying identifiers for any partitions in the current partition table list that have associated commit levels that match the current commit level into the candidate partition table list; replacing the current partition table list with the candidate list; and decrementing the current commit level. 7. The method of claim 1 , wherein the document is an XML document. | 0.569351 |
Subsets and Splits
No saved queries yet
Save your SQL queries to embed, download, and access them later. Queries will appear here once saved.