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4,694,405 | 10 | 11 |
10. The laser printer controller system of claim 9 wherein said old data word is all zeros if said new data word is the first word of the dot line of the character pattern and wherein said new data word is all zeros if said old data word is the last word of the dot line of the character pattern.
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10. The laser printer controller system of claim 9 wherein said old data word is all zeros if said new data word is the first word of the dot line of the character pattern and wherein said new data word is all zeros if said old data word is the last word of the dot line of the character pattern. 11. The laser printer controller of claim 10 wherein said reformating means includes partitioning means for holding the most significant data bits of the old data word in an intermediate element with the most significant bits of the old data word in the most significant bit positions of the intermediate element and the least significant data bits of the new data word in said intermediate element with the least significant bits of the new data word in the least significant bit positions of the intermediate element whereby an intermediate full word is stored and rotate means for translating the bit sequence of the bits of the old data word from the most significant bit positions to the least significant bit positions and substantially simultaneously the bit sequence of the bits from the new data word from the least significant bit positions to the most significant bit positions for the composite data word in the second orientation for the storage in the page bit map of the raster memory means.
| 0.5 |
9,791,999 | 1 | 2 |
1. A method comprising: displaying, by a processor, a touch phrase button in a first state; receiving, by the processor, a first input associated with the touch phrase button in the first state; in response to the first input associated with the touch phrase button, displaying, by the processor, a plurality of option buttons associated with the touch phrase button, wherein a first text is displayed within each of the option buttons; receiving, by the processor, a second input associated with at least one of the plurality of option buttons; and in response to the second input associated with at least one of the plurality of option buttons, displaying, by the processor, the touch phrase button in a second state, wherein displaying the touch phrase button in the second state comprises automatically associating a second text with the touch phrase button without user input of the second text, wherein the second text is displayed within the touch phrase button, and wherein the second text is related to the second input, and wherein the first text is different than the second text.
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1. A method comprising: displaying, by a processor, a touch phrase button in a first state; receiving, by the processor, a first input associated with the touch phrase button in the first state; in response to the first input associated with the touch phrase button, displaying, by the processor, a plurality of option buttons associated with the touch phrase button, wherein a first text is displayed within each of the option buttons; receiving, by the processor, a second input associated with at least one of the plurality of option buttons; and in response to the second input associated with at least one of the plurality of option buttons, displaying, by the processor, the touch phrase button in a second state, wherein displaying the touch phrase button in the second state comprises automatically associating a second text with the touch phrase button without user input of the second text, wherein the second text is displayed within the touch phrase button, and wherein the second text is related to the second input, and wherein the first text is different than the second text. 2. The method of claim 1 , wherein during the displaying of the plurality of option buttons the touch phrase button is not displayed.
| 0.879964 |
8,504,507 | 14 | 16 |
14. A computer-implemented method for performing a sentiment analysis based on an estimated actual age, the method comprising: identifying, by a computer, a set of related members for a first member, wherein the first member and each member in the set of related members are members of a social networking website, and wherein each member in the set of related members is connected to the first member in the social network website; examining, by the computer, age information associated with one or more members in the set of related members in the set of related members; when a threshold number of members in the set of related members have an estimated actual age within a certain age range, estimating, by the computer, an actual age of the first member based on the estimated actual age of the members in the set of related members; and using, by the computer, the member's estimated actual age as an input to a sentiment analysis application for determining sentiments for a demographic that includes the member's age range.
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14. A computer-implemented method for performing a sentiment analysis based on an estimated actual age, the method comprising: identifying, by a computer, a set of related members for a first member, wherein the first member and each member in the set of related members are members of a social networking website, and wherein each member in the set of related members is connected to the first member in the social network website; examining, by the computer, age information associated with one or more members in the set of related members in the set of related members; when a threshold number of members in the set of related members have an estimated actual age within a certain age range, estimating, by the computer, an actual age of the first member based on the estimated actual age of the members in the set of related members; and using, by the computer, the member's estimated actual age as an input to a sentiment analysis application for determining sentiments for a demographic that includes the member's age range. 16. The method of claim 14 , further comprising: providing content to the first member based at least in part on the results from the sentiment analysis application.
| 0.634956 |
9,910,924 | 9 | 10 |
9. A non-transitory computer readable storage medium impressed with computer program instructions to search online social profiles of real-world entities on an online social network, which instructions, when executed on a processor, implement a method comprising: specifying one or more core entity attributes as a first search attribute set for use in searching an online social network; electronically receiving, responsive to searching the online social network based on the first search attribute set, entity reflections that include supplemental entity attributes for real-world entities; and using a combination of the core entity attributes and one or more supplemental entity attributes to electronically receive more entity reflections that include meta entity attributes for the real-world entities.
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9. A non-transitory computer readable storage medium impressed with computer program instructions to search online social profiles of real-world entities on an online social network, which instructions, when executed on a processor, implement a method comprising: specifying one or more core entity attributes as a first search attribute set for use in searching an online social network; electronically receiving, responsive to searching the online social network based on the first search attribute set, entity reflections that include supplemental entity attributes for real-world entities; and using a combination of the core entity attributes and one or more supplemental entity attributes to electronically receive more entity reflections that include meta entity attributes for the real-world entities. 10. The non-transitory computer readable storage medium of claim 9 , wherein at least some of the supplemental entity attributes are shared by the real-world entities.
| 0.721667 |
7,941,426 | 1 | 5 |
1. A computer-implemented method, comprising: receiving a database query; generating, by operation of one or more computer processors, a plurality of query plans for executing the database query; estimating one or more characteristics of energy consumption for executing each query plan; estimating one or more characteristics of time for executing each query plan; and selecting one of the plurality of query plans for executing the database query, based at least on (i) the one or more characteristics of energy consumption, (ii) the one or more characteristics of time, and (iii) a relative priority between the characteristics of energy consumption and the characteristics of time.
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1. A computer-implemented method, comprising: receiving a database query; generating, by operation of one or more computer processors, a plurality of query plans for executing the database query; estimating one or more characteristics of energy consumption for executing each query plan; estimating one or more characteristics of time for executing each query plan; and selecting one of the plurality of query plans for executing the database query, based at least on (i) the one or more characteristics of energy consumption, (ii) the one or more characteristics of time, and (iii) a relative priority between the characteristics of energy consumption and the characteristics of time. 5. The computer-implemented method of claim 1 , wherein the one or more characteristics of energy consumption comprise the electrical energy required to cool one or more hard-disk drives required to execute each query plan.
| 0.5 |
7,661,071 | 1 | 3 |
1. A method for authoring an interactive, three-dimensional user interface comprising: creating a three-dimensional object having a texture definition property; defining animation properties for the three-dimensional object; creating a two-dimensional texture using a two-dimensional graphic design application; defining an interactive behavior of the two-dimensional texture in a two-dimensional resource image file stored on a computer, wherein the two-dimensional texture comprises one or more image assets, and the interactive behavior is defined by navigation instructions for selecting and activating the one or more image assets in response to user input; assigning the two-dimensional resource image file as the texture definition property of the three-dimensional object; mapping the two-dimensional resource image file to the three-dimensional object by distorting the two-dimensional texture onto the three-dimensional object and applying the interactive behavior of the two-dimensional texture to the three-dimensional object in a three-dimensional space to form a three-dimensional user interface having interactive behavior within the distorted two-dimensional texture on the three-dimensional object; and coordinating a behavior of the two-dimensional texture and the three-dimensional object in the three-dimensional space.
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1. A method for authoring an interactive, three-dimensional user interface comprising: creating a three-dimensional object having a texture definition property; defining animation properties for the three-dimensional object; creating a two-dimensional texture using a two-dimensional graphic design application; defining an interactive behavior of the two-dimensional texture in a two-dimensional resource image file stored on a computer, wherein the two-dimensional texture comprises one or more image assets, and the interactive behavior is defined by navigation instructions for selecting and activating the one or more image assets in response to user input; assigning the two-dimensional resource image file as the texture definition property of the three-dimensional object; mapping the two-dimensional resource image file to the three-dimensional object by distorting the two-dimensional texture onto the three-dimensional object and applying the interactive behavior of the two-dimensional texture to the three-dimensional object in a three-dimensional space to form a three-dimensional user interface having interactive behavior within the distorted two-dimensional texture on the three-dimensional object; and coordinating a behavior of the two-dimensional texture and the three-dimensional object in the three-dimensional space. 3. The method of claim 1 , wherein the one or more image assets comprise one or more of a static text element, an updated text element, a control button, a control slider, an advertising window, a video feed window, a logo window, a graphic, a link to a user interface screen, and a background.
| 0.5 |
8,285,744 | 2 | 3 |
2. The system of claim 1 , the computer-executable components further comprising: a master indexing component configured to derive an overall index via aggregation of the at least the portion of the searchable sub-indices.
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2. The system of claim 1 , the computer-executable components further comprising: a master indexing component configured to derive an overall index via aggregation of the at least the portion of the searchable sub-indices. 3. The system of claim 2 , wherein the manufacturing process search engine is further configured to employ the overall index to facilitate in responding to a manufacturing process information search query.
| 0.5 |
9,501,791 | 16 | 22 |
16. A method of facilitating online transactions involving seller financing and notifying users of time limited offers in an online marketplace, using at least one computing device, the method comprising: generating and storing trust profiles for buyer users and seller users, using the at least one computing device, the trust profiles configured to allow both the buyer users and the seller users to evaluate trustworthiness of each other prior to entering into online transactions involving seller financing, wherein the trust profiles include reputation data including: reputational factors, including: at least one rating of at least one of the user's prior transactions, from another user; historical data about the user's conformance to terms of the user's prior transactions; and information about a verification level of the user; and a trust score computed based on at least some of the reputational factors, including a number of the user's prior transactions; and receiving descriptions of a plurality of transaction offerings from a plurality of seller users of the online marketplace, using the at least one computing device, wherein the transaction offerings are available for purchase from the seller users over time for at least two payments; generating a user interface presenting a plurality of listings and the trust profiles using the at least one computing device, each of the listings including one of the descriptions of the plurality of transactions offerings, wherein the plurality of listings are associated with transaction offerings across a plurality of different transaction offering categories; presenting at least some of the plurality of listings to buyer users through the user interface, using the at least one computing device; and facilitating, using the at least one computing device and through the user interface, negotiation of binding contracts between the buyer users and the seller users for transfer of the transaction offerings from the seller users to the buyer users, wherein the binding contracts define payment terms, and wherein the payment terms include prices and seller-financing terms including at least two payments made by the buyer users to the seller users over a period of time, comprising: receiving an offer from a first user of the buyer users and the seller users for one of the transaction offerings, the offer including offer details and a time limit generating an offer alert from the offer that includes the offer details, the time limit, and a customized link, which is selectable by a second user of the buyer users and the seller users to view the offer on the online marketplace; formatting the offer alert according to a preferred offer communication method for the second user; transmitting the formatted offer alert to the second user over a wireless communication network, wherein the formatted offer alert upon receipt instantaneously activates an application on a remote computing device to display the formatted offer alert and enable connection via the customized link to the online marketplace over the Internet upon connection of the remote computing device via the customized link, generating for display on the remote computing device to the second user: a listing for the one of the transaction offerings; the offer including the offer details; the trust profile for the first user; and an option to accept the offer; and receiving an acceptance from the second user.
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16. A method of facilitating online transactions involving seller financing and notifying users of time limited offers in an online marketplace, using at least one computing device, the method comprising: generating and storing trust profiles for buyer users and seller users, using the at least one computing device, the trust profiles configured to allow both the buyer users and the seller users to evaluate trustworthiness of each other prior to entering into online transactions involving seller financing, wherein the trust profiles include reputation data including: reputational factors, including: at least one rating of at least one of the user's prior transactions, from another user; historical data about the user's conformance to terms of the user's prior transactions; and information about a verification level of the user; and a trust score computed based on at least some of the reputational factors, including a number of the user's prior transactions; and receiving descriptions of a plurality of transaction offerings from a plurality of seller users of the online marketplace, using the at least one computing device, wherein the transaction offerings are available for purchase from the seller users over time for at least two payments; generating a user interface presenting a plurality of listings and the trust profiles using the at least one computing device, each of the listings including one of the descriptions of the plurality of transactions offerings, wherein the plurality of listings are associated with transaction offerings across a plurality of different transaction offering categories; presenting at least some of the plurality of listings to buyer users through the user interface, using the at least one computing device; and facilitating, using the at least one computing device and through the user interface, negotiation of binding contracts between the buyer users and the seller users for transfer of the transaction offerings from the seller users to the buyer users, wherein the binding contracts define payment terms, and wherein the payment terms include prices and seller-financing terms including at least two payments made by the buyer users to the seller users over a period of time, comprising: receiving an offer from a first user of the buyer users and the seller users for one of the transaction offerings, the offer including offer details and a time limit generating an offer alert from the offer that includes the offer details, the time limit, and a customized link, which is selectable by a second user of the buyer users and the seller users to view the offer on the online marketplace; formatting the offer alert according to a preferred offer communication method for the second user; transmitting the formatted offer alert to the second user over a wireless communication network, wherein the formatted offer alert upon receipt instantaneously activates an application on a remote computing device to display the formatted offer alert and enable connection via the customized link to the online marketplace over the Internet upon connection of the remote computing device via the customized link, generating for display on the remote computing device to the second user: a listing for the one of the transaction offerings; the offer including the offer details; the trust profile for the first user; and an option to accept the offer; and receiving an acceptance from the second user. 22. The method of claim 16 , further comprising communicating contact information between a buyer user and a seller user only after a binding contract has been formed.
| 0.759366 |
9,552,439 | 10 | 15 |
10. An article of manufacture including a non-transitory computer-readable medium, having stored thereon program instructions that, upon execution by a client device, cause the client device to perform operations comprising: rendering a web page for display on the client device, wherein the rendered web page includes a first document and a first advertisement that is based on the first document; determining that a first scroll position of the rendered web page has a first characteristic; responsive to determining that the first scroll position of the rendered web page has the first characteristic, (i) requesting and receiving a second document from a content server device, and (ii) based on the second document, requesting and receiving a second advertisement from an advertisement server device; and re-rendering the web page for display on the client device, wherein the re-rendered web page includes content from the first document, content from the second document, the first advertisement, and the second advertisement, wherein not all content from the first document and second document is displayed on the re-rendered web page, wherein the first advertisement is based on non-displayed parts of the first document, and wherein the second advertisement is based on non-displayed parts of the second document.
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10. An article of manufacture including a non-transitory computer-readable medium, having stored thereon program instructions that, upon execution by a client device, cause the client device to perform operations comprising: rendering a web page for display on the client device, wherein the rendered web page includes a first document and a first advertisement that is based on the first document; determining that a first scroll position of the rendered web page has a first characteristic; responsive to determining that the first scroll position of the rendered web page has the first characteristic, (i) requesting and receiving a second document from a content server device, and (ii) based on the second document, requesting and receiving a second advertisement from an advertisement server device; and re-rendering the web page for display on the client device, wherein the re-rendered web page includes content from the first document, content from the second document, the first advertisement, and the second advertisement, wherein not all content from the first document and second document is displayed on the re-rendered web page, wherein the first advertisement is based on non-displayed parts of the first document, and wherein the second advertisement is based on non-displayed parts of the second document. 15. The article of manufacture of claim 10 , wherein determining that the first scroll position of the rendered web page has the first characteristic comprises determining that the first scroll position of the rendered web page is above a first threshold scroll position, and wherein re-rendering the web page for display on the client device comprises re-rendering the web page to represent the second document followed by the first document.
| 0.711589 |
9,081,853 | 20 | 27 |
20. A computer implemented method for processing information files characterized by containing or pertaining to targets of analysis, said method comprising: using at least one processor with accessible input/output and at least one data store to perform the following: storing information files and associated metadata in computer readable storage, the metadata including targets indicating information about the associated information files, said targets being typed-attributes usable by logic to process the information files; storing hierarchically organized profile data structures in a database including a plurality of individually addressable user records, each including named interest nodes which are user-tunable channels, each named interest node data structure being logically connected with at least one target data structure, each target data structure being logically connected with at least one typed-attribute which can be logically connected by the user to any of said plural user-tunable channels at the user's option; filtering the information files and metadata using said at least one target in a selected named interest node to produce a filtered set of information files, by executing a procedure on a data processing system in communication with the storage and the database, said meta data being produced by a person or an analyze engine performing analysis, extraction or classification on the associated information files; composing, using the data processing system, a first executable document for rendition of a graphical user interface at a user terminal including display to the user of the interest node names, including a representation of the filtered set of information files with user selectable mark-up identifying typed-attributes represented in the filtered set of information files and a representation of the profile data structure; sending said first executable document on a data network across a data network from the data processing system to the user terminal; modifying, using the data processing system, the selected named interest node which is a user-tunable channel in the profile data structure in response to an indication of a selected mark-up by adding the identified target; composing, using the data processing system, a second executable document for rendition of the graphical user interface using said modified named interest node; and sending said second executable document across the data network from the data processing system to the user terminal.
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20. A computer implemented method for processing information files characterized by containing or pertaining to targets of analysis, said method comprising: using at least one processor with accessible input/output and at least one data store to perform the following: storing information files and associated metadata in computer readable storage, the metadata including targets indicating information about the associated information files, said targets being typed-attributes usable by logic to process the information files; storing hierarchically organized profile data structures in a database including a plurality of individually addressable user records, each including named interest nodes which are user-tunable channels, each named interest node data structure being logically connected with at least one target data structure, each target data structure being logically connected with at least one typed-attribute which can be logically connected by the user to any of said plural user-tunable channels at the user's option; filtering the information files and metadata using said at least one target in a selected named interest node to produce a filtered set of information files, by executing a procedure on a data processing system in communication with the storage and the database, said meta data being produced by a person or an analyze engine performing analysis, extraction or classification on the associated information files; composing, using the data processing system, a first executable document for rendition of a graphical user interface at a user terminal including display to the user of the interest node names, including a representation of the filtered set of information files with user selectable mark-up identifying typed-attributes represented in the filtered set of information files and a representation of the profile data structure; sending said first executable document on a data network across a data network from the data processing system to the user terminal; modifying, using the data processing system, the selected named interest node which is a user-tunable channel in the profile data structure in response to an indication of a selected mark-up by adding the identified target; composing, using the data processing system, a second executable document for rendition of the graphical user interface using said modified named interest node; and sending said second executable document across the data network from the data processing system to the user terminal. 27. The method of claim 20 , wherein said targets comprise typed-attributes including topic type attributes identifying topics from a taxonomy addressed in the associated information files.
| 0.805155 |
7,665,063 | 68 | 69 |
68. The method of claim 67 , further comprising characterizing said one or more declarative rules by a DAG dependency network.
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68. The method of claim 67 , further comprising characterizing said one or more declarative rules by a DAG dependency network. 69. The method of claim 68 , wherein said step of updating said one or more other data comprises performing a forward search of said DAG dependency network.
| 0.5 |
8,943,465 | 16 | 20 |
16. The software design system according to claim 15 , wherein the verified implementation specification generator is arranged to process the received verified specifications to create formal implementation specifications; to generate from the formal implementation specifications mathematical models representing run-time implementation behavior of the software design system; to analyse the mathematical models representing the run-time implementation behavior to determine if the mathematical models representing the run-time implementation behavior have required run-time implementation behavior; to adjust the formal implementation specifications until the required run-time implementation behavior is achieved; and to derive required verified component implementation specifications from the mathematical models representing the run-time implementation behavior.
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16. The software design system according to claim 15 , wherein the verified implementation specification generator is arranged to process the received verified specifications to create formal implementation specifications; to generate from the formal implementation specifications mathematical models representing run-time implementation behavior of the software design system; to analyse the mathematical models representing the run-time implementation behavior to determine if the mathematical models representing the run-time implementation behavior have required run-time implementation behavior; to adjust the formal implementation specifications until the required run-time implementation behavior is achieved; and to derive required verified component implementation specifications from the mathematical models representing the run-time implementation behavior. 20. The software design system according to claim 16 , wherein the verified implementation specification generator is arranged compare the verified component implementation specifications against the verified component design specifications and to detect and remove any errors found.
| 0.609116 |
7,921,414 | 7 | 8 |
7. The compiler of claim 6 , wherein at least one of insert and delete operation can be performed on the grammar analyzer.
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7. The compiler of claim 6 , wherein at least one of insert and delete operation can be performed on the grammar analyzer. 8. The compiler of claim 7 , wherein the at least one of insert and delete operation can be performed to the lookup map in response to the at least one of insert and delete operation performed on the grammar analyzer.
| 0.5 |
9,552,417 | 14 | 15 |
14. The system according to claim 13 , wherein the entity database includes a domain-specific Hidden Markov Model.
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14. The system according to claim 13 , wherein the entity database includes a domain-specific Hidden Markov Model. 15. The system according to claim 14 , wherein the domain-specific Hidden Markov Model is domain-specific to inmate speech.
| 0.5 |
8,827,712 | 9 | 10 |
9. The method of claim 7 , further comprising publishing the user profile of the first user on a searchable location of the communication network, the published user profile comprising at least: a normal speed audio the and a slow speed audio file of at least one of the call-me-this names of the first user; the do-not-call-me name of the first user; and the language spoken by the first user.
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9. The method of claim 7 , further comprising publishing the user profile of the first user on a searchable location of the communication network, the published user profile comprising at least: a normal speed audio the and a slow speed audio file of at least one of the call-me-this names of the first user; the do-not-call-me name of the first user; and the language spoken by the first user. 10. The method of claim 9 , further comprising: receiving a practice audio file from the second user via the communication network, the practice audio file representing the second user's pronunciation of the searched name; analyzing the practice audio file to determine whether the second user's pronunciation of the searched name is correct or not; and providing a feedback to the second user as to whether the second user's pronunciation of the searched name is correct or not via the communication network.
| 0.5 |
6,138,087 | 8 | 14 |
8. A method of processing natural language, which comprises steps providing electronically encoded data which is representative of said natural language, providing a dictionary data base wherein said dictionary data base contains a plurality of entries which are comprised of one or more of syntax usage data, associated word sense numbers having associated state representation data, and/or function codes having associated functions, lexically processing said electronically encoded data to access said dictionary data base, utilizing said syntax usage data and said function codes which are from entries of said dictionary data base and which are associated with words of said natural language to access said functions.
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8. A method of processing natural language, which comprises steps providing electronically encoded data which is representative of said natural language, providing a dictionary data base wherein said dictionary data base contains a plurality of entries which are comprised of one or more of syntax usage data, associated word sense numbers having associated state representation data, and/or function codes having associated functions, lexically processing said electronically encoded data to access said dictionary data base, utilizing said syntax usage data and said function codes which are from entries of said dictionary data base and which are associated with words of said natural language to access said functions. 14. A method of processing as defined in claim 8, which comprises steps providing storage, accessing said function such that said function stores all or part of said state representation data of said word sense number in said storage.
| 0.590909 |
7,933,864 | 15 | 17 |
15. One or more computer-readable media storing computer-executable instructions that, when executed on one or more processors, configure a computer to perform operations comprising: creating variations of a search string, each variation having a weight corresponding to a similarity between the variation and the search string; aggregating respective weights of each variation of the variations to create an aggregate weight associated with the variation; determining when the aggregate weight reaches a threshold value based on the aggregating; creating a search forum for the variation that has the aggregate weight that reaches the threshold based on the determining; and causing a display of the search forum.
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15. One or more computer-readable media storing computer-executable instructions that, when executed on one or more processors, configure a computer to perform operations comprising: creating variations of a search string, each variation having a weight corresponding to a similarity between the variation and the search string; aggregating respective weights of each variation of the variations to create an aggregate weight associated with the variation; determining when the aggregate weight reaches a threshold value based on the aggregating; creating a search forum for the variation that has the aggregate weight that reaches the threshold based on the determining; and causing a display of the search forum. 17. The one or more computer-readable media as recited in claim 15 , the operations further comprising: associating the variation with at least one of a tag having a tag forum or a category having a category forum; creating a related forum for each of the associated tag forum and the associated category forums; and causing the display of the related forum proximate the search forum.
| 0.5 |
7,769,904 | 17 | 22 |
17. A system for receiving data formatted in an extensible markup language (XML), comprising: a parser configured to convert to an extensible markup language (XML) representation that is compatible with standard XML from a single data stream binary representation by providing binary data representations for element start tags and data values within the XML representation and by not providing binary data representations for element end tags within the XML representation; wherein the binary data representations are each formed using X-bit bytes; and wherein consistent extensible encoding is provided for the binary data representations by using a most-significant-bit of each X-bit byte as a termination indicator bit where a first logic level indicates the byte is a termination byte and a second logic level indicates that more bytes are included in a multi-byte data word, and the XML representation and the binary representation being defined according to a document type definition (DTD); and a communication interface coupled to the parser and configured to receive the single data stream binary representation from an external system through a network; wherein the element start tags are represented using positive integer binary data representations; and wherein the data values are represented using binary data representations selected from a group comprising a string, an integer, a floating point number, an enumerated value, a pattern, and a packed component.
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17. A system for receiving data formatted in an extensible markup language (XML), comprising: a parser configured to convert to an extensible markup language (XML) representation that is compatible with standard XML from a single data stream binary representation by providing binary data representations for element start tags and data values within the XML representation and by not providing binary data representations for element end tags within the XML representation; wherein the binary data representations are each formed using X-bit bytes; and wherein consistent extensible encoding is provided for the binary data representations by using a most-significant-bit of each X-bit byte as a termination indicator bit where a first logic level indicates the byte is a termination byte and a second logic level indicates that more bytes are included in a multi-byte data word, and the XML representation and the binary representation being defined according to a document type definition (DTD); and a communication interface coupled to the parser and configured to receive the single data stream binary representation from an external system through a network; wherein the element start tags are represented using positive integer binary data representations; and wherein the data values are represented using binary data representations selected from a group comprising a string, an integer, a floating point number, an enumerated value, a pattern, and a packed component. 22. The system of claim 17 , wherein the network comprises a communication channel having a bandwidth of less than or equal to about 9600 baud.
| 0.70332 |
8,721,340 | 5 | 7 |
5. A computer system, comprising: at least one specialize computer machine, comprising: a non-transient memory having at least one region for storing particular computer executable program code; and at least one processor for executing the particular program code stored in the memory, wherein the particular program code is configured to at least perform the following operations: generating a plurality of position specific surveys; wherein each position specific survey comprises a plurality of survey questions specific to competency skills related to performance of at least one position; wherein each survey question of the plurality of survey questions seeks a response in a form of a number on a numerical extent scale; wherein each position specific survey is configured for calculating an average score in each competency skills group of the competency skills by averaging numbers of the numerical extent scale across responses received from reference providers to the plurality of survey questions so that the responses from each of reference providers are confidential from employers and job candidates; receiving, through at least one first computer programmed interface, from at least one first employer, at least the following information: i) job information, wherein the job information is related to at least one first position, ii) an identity of each job candidate applying to be interviewed, and iii) a selection identifying, from the plurality of position specific surveys, at least one first position specific survey related to at least one first position; wherein the at least one first employer requires references from a plurality of reference providers to be received for each job candidate before the at least one first employer decides whether or not to conduct a job interview; wherein the at least one computer system is independent from each job candidate and the at least one first employer; wherein the job information at least identifies whether the at least one first position involves managing others; receiving, through at least one second computer programmed interface, from a first job candidate from a plurality of job candidates applying to be interviewed, first contact information identifying the plurality of reference providers, automatically assigning a first unique identifier to a first reference provider of the plurality of reference providers; automatically assigning a second unique identifier to a second reference provider of the plurality of reference providers; automatically assigning a third unique identifier to a third reference provider of the plurality of reference providers; automatically transmitting at least one first personalized request to complete the at least one first position specific survey to the first reference provider, wherein the at least one first personalized request comprises: i) a first URL link to access the at least one first position specific survey, and ii) the first unique identifier, and iii) information informing that responses obtained in response to the at least one first position specific survey are kept confidential from the at least one first employer and the first job candidate; automatically transmitting at least one second personalized request to complete the at least one first position specific survey to the second reference provider, wherein the at least one second personalized request comprises: i) a second URL link to access the at least one first position specific survey, and ii) the second unique identifier, and iii) the information informing that the responses obtained in response to the at least one first position specific survey are kept confidential from the at least one first employer and the first job candidate; automatically transmitting at least one third personalized request to complete the at least one first position specific survey to the third reference provider, wherein the at least one third personalized request comprises: i) a third URL link to access the at least one first position specific survey, and ii) the third unique identifier, and iii) the information informing that the responses obtained in response to the at least one first position specific survey are kept confidential from the at least one first employer and the first job candidate; causing to display, through at least one second computer interface, the at least one first position specific survey to the first, the second and the third reference providers in response to: i) the first, the second and the third URL links being activated respectively and ii) the first, the second and the third unique identifiers being supplied respectively; receiving, from the first, the second and the third reference providers, the responses to the at least one first position specific survey; calculating each average score of the first job candidate in each competency skills group of the competency skills based on the responses in each competency skills group of the first, the second and the third reference providers; generating, for the at least one first employer, at least one reference report related to the first job candidate, wherein the at least one reference report comprises average scores of the first job candidate in the competency skills groups of the at least one first position specific survey, calculated based on the responses of the first, the second and the third reference providers so as to maintain the confidentiality of the responses of the plurality of reference providers from the at least one first employer and the first job candidate; wherein the average scores of the first job candidate are benchmarked against average scores of other job candidates who applied to a specific position that is at least similar to the at least one first position; and wherein the at least one reference report is configured to allow the at least one first employer to decide whether or not to conduct the job interview with the first job candidate who has applied to be interviewed.
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5. A computer system, comprising: at least one specialize computer machine, comprising: a non-transient memory having at least one region for storing particular computer executable program code; and at least one processor for executing the particular program code stored in the memory, wherein the particular program code is configured to at least perform the following operations: generating a plurality of position specific surveys; wherein each position specific survey comprises a plurality of survey questions specific to competency skills related to performance of at least one position; wherein each survey question of the plurality of survey questions seeks a response in a form of a number on a numerical extent scale; wherein each position specific survey is configured for calculating an average score in each competency skills group of the competency skills by averaging numbers of the numerical extent scale across responses received from reference providers to the plurality of survey questions so that the responses from each of reference providers are confidential from employers and job candidates; receiving, through at least one first computer programmed interface, from at least one first employer, at least the following information: i) job information, wherein the job information is related to at least one first position, ii) an identity of each job candidate applying to be interviewed, and iii) a selection identifying, from the plurality of position specific surveys, at least one first position specific survey related to at least one first position; wherein the at least one first employer requires references from a plurality of reference providers to be received for each job candidate before the at least one first employer decides whether or not to conduct a job interview; wherein the at least one computer system is independent from each job candidate and the at least one first employer; wherein the job information at least identifies whether the at least one first position involves managing others; receiving, through at least one second computer programmed interface, from a first job candidate from a plurality of job candidates applying to be interviewed, first contact information identifying the plurality of reference providers, automatically assigning a first unique identifier to a first reference provider of the plurality of reference providers; automatically assigning a second unique identifier to a second reference provider of the plurality of reference providers; automatically assigning a third unique identifier to a third reference provider of the plurality of reference providers; automatically transmitting at least one first personalized request to complete the at least one first position specific survey to the first reference provider, wherein the at least one first personalized request comprises: i) a first URL link to access the at least one first position specific survey, and ii) the first unique identifier, and iii) information informing that responses obtained in response to the at least one first position specific survey are kept confidential from the at least one first employer and the first job candidate; automatically transmitting at least one second personalized request to complete the at least one first position specific survey to the second reference provider, wherein the at least one second personalized request comprises: i) a second URL link to access the at least one first position specific survey, and ii) the second unique identifier, and iii) the information informing that the responses obtained in response to the at least one first position specific survey are kept confidential from the at least one first employer and the first job candidate; automatically transmitting at least one third personalized request to complete the at least one first position specific survey to the third reference provider, wherein the at least one third personalized request comprises: i) a third URL link to access the at least one first position specific survey, and ii) the third unique identifier, and iii) the information informing that the responses obtained in response to the at least one first position specific survey are kept confidential from the at least one first employer and the first job candidate; causing to display, through at least one second computer interface, the at least one first position specific survey to the first, the second and the third reference providers in response to: i) the first, the second and the third URL links being activated respectively and ii) the first, the second and the third unique identifiers being supplied respectively; receiving, from the first, the second and the third reference providers, the responses to the at least one first position specific survey; calculating each average score of the first job candidate in each competency skills group of the competency skills based on the responses in each competency skills group of the first, the second and the third reference providers; generating, for the at least one first employer, at least one reference report related to the first job candidate, wherein the at least one reference report comprises average scores of the first job candidate in the competency skills groups of the at least one first position specific survey, calculated based on the responses of the first, the second and the third reference providers so as to maintain the confidentiality of the responses of the plurality of reference providers from the at least one first employer and the first job candidate; wherein the average scores of the first job candidate are benchmarked against average scores of other job candidates who applied to a specific position that is at least similar to the at least one first position; and wherein the at least one reference report is configured to allow the at least one first employer to decide whether or not to conduct the job interview with the first job candidate who has applied to be interviewed. 7. The computer system of claim 5 , wherein the average scores of the first job candidate are benchmarked on an industry-wide basis.
| 0.95262 |
9,256,366 | 1 | 4 |
1. A method comprising: providing, by an electronic device and for display in a seek area of a touch-sensitive display, a subset from a full range of a set of symbolic elements, wherein the subset has fewer symbolic elements than the full range; receiving, by the electronic device and in the seek area of the touch-sensitive display, a first user input specifying a first target range of the set of symbolic elements, wherein the first target range comprises a first alphabetized range between at least two symbolic elements of the subset that are presented in the seek area of the touch-sensitive display, and wherein the first target range includes the at least two symbolic elements; based on the first user input, providing, by the electronic device and for display in a selection area of the touch-sensitive display that is distinct from the seek area, individual symbolic elements from the first target range, wherein the individual symbolic elements from the first target range include the at least two symbolic elements of the first target range that are presented in the seek area of the touch-sensitive display, wherein the individual symbolic elements from the first target range further include at least one symbolic element of the first target range that is not included in the subset presented in the seek area of the touch-sensitive display, and wherein symbolic elements presented in the selection area are larger in size than symbolic elements presented in the seek area; receiving, by the electronic device, a second user input specifying a second target range of the set of symbolic elements that is different from the first target range, wherein the second target range comprises a second alphabetized range of the subset that is presented in the seek area of the touch-sensitive display; responsive to receiving the second user input: removing, by the electronic device and from the selection area of the touch-sensitive display, at least one of the individual symbolic elements from the first target range; and providing, by the electronic device and for display in the selection area of the touch-sensitive display, individual symbolic elements from the second target range, wherein the individual symbolic elements from the second target range include at least one symbolic element of the second target range that is not included in the subset presented in the seek area, and wherein the second target range includes at least one symbolic element that is also included in the first target range; receiving, by the electronic device and in the selection area of the touch-sensitive display, a third user input indicating a selected symbolic element from the individual symbolic elements from the second target range; and based on the third user input, inserting, by the electronic device, the selected symbolic element in a data object.
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1. A method comprising: providing, by an electronic device and for display in a seek area of a touch-sensitive display, a subset from a full range of a set of symbolic elements, wherein the subset has fewer symbolic elements than the full range; receiving, by the electronic device and in the seek area of the touch-sensitive display, a first user input specifying a first target range of the set of symbolic elements, wherein the first target range comprises a first alphabetized range between at least two symbolic elements of the subset that are presented in the seek area of the touch-sensitive display, and wherein the first target range includes the at least two symbolic elements; based on the first user input, providing, by the electronic device and for display in a selection area of the touch-sensitive display that is distinct from the seek area, individual symbolic elements from the first target range, wherein the individual symbolic elements from the first target range include the at least two symbolic elements of the first target range that are presented in the seek area of the touch-sensitive display, wherein the individual symbolic elements from the first target range further include at least one symbolic element of the first target range that is not included in the subset presented in the seek area of the touch-sensitive display, and wherein symbolic elements presented in the selection area are larger in size than symbolic elements presented in the seek area; receiving, by the electronic device, a second user input specifying a second target range of the set of symbolic elements that is different from the first target range, wherein the second target range comprises a second alphabetized range of the subset that is presented in the seek area of the touch-sensitive display; responsive to receiving the second user input: removing, by the electronic device and from the selection area of the touch-sensitive display, at least one of the individual symbolic elements from the first target range; and providing, by the electronic device and for display in the selection area of the touch-sensitive display, individual symbolic elements from the second target range, wherein the individual symbolic elements from the second target range include at least one symbolic element of the second target range that is not included in the subset presented in the seek area, and wherein the second target range includes at least one symbolic element that is also included in the first target range; receiving, by the electronic device and in the selection area of the touch-sensitive display, a third user input indicating a selected symbolic element from the individual symbolic elements from the second target range; and based on the third user input, inserting, by the electronic device, the selected symbolic element in a data object. 4. The method of claim 1 , wherein providing the subset from the full range of the set of symbolic elements in the seek area comprises: providing variably-separated symbolic elements in an ordered arrangement.
| 0.834913 |
8,510,285 | 30 | 31 |
30. The non-transitory computer storage medium of claim 23 , wherein the determining the confidence score comprises determining the confidence score based on a time of day or day of the week of the particular time.
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30. The non-transitory computer storage medium of claim 23 , wherein the determining the confidence score comprises determining the confidence score based on a time of day or day of the week of the particular time. 31. The non-transitory computer storage medium of claim 30 , wherein determining the confidence score associated with the topic comprises determining the confidence score based on a degree of correlation between the topic and actions of the particular user occurring on previous days at a time of day of the particular time.
| 0.5 |
8,560,479 | 1 | 8 |
1. A method for processing risk factors for a user, comprising: receiving protocol data for creating a risk factor coaching engine by an application stored and executed at a computing device, the risk factor coaching engine stored in memory and executable by a processor to process a first set of stored user health data for a user, wherein the protocol data includes a rule and one or more health attribute values, the rule and the one or more health attribute values each including a computer programming expression editable by a user through a graphical interface, the graphical interface including a first menu for editing the programmable expressions and a second menu for entering the user health data; determining a user health score through execution of the risk factor coaching engine by the processor and based on the user health data, wherein determining the user health score includes evaluating the expressions of the one or more health attribute values by inputting the user health data to calculate one or more calculated health attribute values, and then evaluating the expression of the rule by inputting the one or more calculated health attribute values to calculate the user health score; performing a first action through execution of the risk factor coaching engine by the processor and based on the user health score, the first action including reporting information to the user about the presence of the health risk; and storing updated user health data in memory based on the performed first action, the updated user health data including the user health score.
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1. A method for processing risk factors for a user, comprising: receiving protocol data for creating a risk factor coaching engine by an application stored and executed at a computing device, the risk factor coaching engine stored in memory and executable by a processor to process a first set of stored user health data for a user, wherein the protocol data includes a rule and one or more health attribute values, the rule and the one or more health attribute values each including a computer programming expression editable by a user through a graphical interface, the graphical interface including a first menu for editing the programmable expressions and a second menu for entering the user health data; determining a user health score through execution of the risk factor coaching engine by the processor and based on the user health data, wherein determining the user health score includes evaluating the expressions of the one or more health attribute values by inputting the user health data to calculate one or more calculated health attribute values, and then evaluating the expression of the rule by inputting the one or more calculated health attribute values to calculate the user health score; performing a first action through execution of the risk factor coaching engine by the processor and based on the user health score, the first action including reporting information to the user about the presence of the health risk; and storing updated user health data in memory based on the performed first action, the updated user health data including the user health score. 8. The method of claim 1 , wherein the user health score is associated with a user expected life span.
| 0.902111 |
7,707,221 | 1 | 7 |
1. A method comprising: receiving, at a computing device, a metadata request, which comprises a plurality of numeric values retrieved from a media item, as metadata corresponding to the media item; in response to the metadata request, first querying first and second metadata sources using the received metadata, so as to retrieve at least one primary record; transmitting the at least one primary record in response to the metadata request; in response to the metadata request and to extracting no metadata from one of the metadata sources queried using the first query, performing a second query of the queried metadata source, the second query formed using metadata extracted from the at least one primary record as other metadata corresponding to the media item, so as to retrieve, using the second query and the other metadata, at least one secondary record from the queried metadata source; transmitting the at least one secondary record in response to the metadata request; creating, at the computing device, a linking record associating the other metadata extracted from the primary record with the metadata received with the metadata request; and storing the linking record in a linking database that is in communication with the computing device.
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1. A method comprising: receiving, at a computing device, a metadata request, which comprises a plurality of numeric values retrieved from a media item, as metadata corresponding to the media item; in response to the metadata request, first querying first and second metadata sources using the received metadata, so as to retrieve at least one primary record; transmitting the at least one primary record in response to the metadata request; in response to the metadata request and to extracting no metadata from one of the metadata sources queried using the first query, performing a second query of the queried metadata source, the second query formed using metadata extracted from the at least one primary record as other metadata corresponding to the media item, so as to retrieve, using the second query and the other metadata, at least one secondary record from the queried metadata source; transmitting the at least one secondary record in response to the metadata request; creating, at the computing device, a linking record associating the other metadata extracted from the primary record with the metadata received with the metadata request; and storing the linking record in a linking database that is in communication with the computing device. 7. The method of claim 1 , wherein the computing device is a server.
| 0.869231 |
7,844,957 | 48 | 49 |
48. The system of claim 47 , wherein the data object is then serialized by said serializer component, for transmitting parsed message data to another system.
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48. The system of claim 47 , wherein the data object is then serialized by said serializer component, for transmitting parsed message data to another system. 49. The system of claim 48 , wherein the data object is itself not specific to a particular wire format.
| 0.5 |
8,060,575 | 17 | 26 |
17. A computer-based system for transmitting an electronic document, comprising: an computer that is remote from a device sending a message, the computer including a memory storing instructions; and a processor configured to: execute the instructions to receive the message, the message including a document including metadata, execute the instructions to automatically create a cleansed version of the document by removing at least a portion of the metadata from the document, execute the instructions to replace the document received with the message with the cleansed version of the document, and execute the instructions to transmit the message with the cleansed version of the document.
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17. A computer-based system for transmitting an electronic document, comprising: an computer that is remote from a device sending a message, the computer including a memory storing instructions; and a processor configured to: execute the instructions to receive the message, the message including a document including metadata, execute the instructions to automatically create a cleansed version of the document by removing at least a portion of the metadata from the document, execute the instructions to replace the document received with the message with the cleansed version of the document, and execute the instructions to transmit the message with the cleansed version of the document. 26. The system of claim 17 , wherein the processor is further configured to execute the instructions to save an entry in a log to indicate the message had the document replaced by the cleansed version of the document.
| 0.567729 |
9,544,402 | 10 | 11 |
10. The method of claim 1 further comprising, given a key matching rule having at least one dimension, storing in the memory a value associated with the at least one dimension, the value being stored as dimension data of the multi-rule.
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10. The method of claim 1 further comprising, given a key matching rule having at least one dimension, storing in the memory a value associated with the at least one dimension, the value being stored as dimension data of the multi-rule. 11. The method of claim 10 wherein storing the dimension data of the multi-rule further includes for a given key matching rule of the chunk, storing a priority value at the end of the dimension data stored for the rule in the multi-rule.
| 0.701511 |
9,373,031 | 9 | 14 |
9. A system comprising: a document processor, comprising a processor, that receives a first template document, wherein the first template document comprises a first plurality of text objects, receives a reference document, wherein the reference document comprises second a plurality of text objects, wherein at least one of the first template document and the reference document are misaligned or upside down during the following: identify the first plurality of text objects in the first template document, identify the second plurality of text objects in the reference document, identify a plurality of common identical text objects between the first template document and the reference document, identify locations of the plurality of common identical text objects in the first template document, identify two or more distances between the locations of the plurality of common identical text objects in the first template document, identifying locations of the plurality of common identical text objects in the reference document, identify two or more distances between the locations of the plurality of common identical text objects in the reference document, and determining that the two or more distances between the plurality of common identical text objects in the first template document are within a given percentage of variance as the two or more distances between the plurality of common text objects in the reference document, wherein an endpoint of a first one of the two or more distances between the plurality of common identical text objects in the first template document is used as a starting point for a second one of the two or more distances between the plurality of common identical text objects in the first template document and wherein an endpoint of a first one of the two or more distances between the plurality of common identical text objects in the reference document is used as a starting point for a second one of the two or more distances between the plurality of common identical text objects in the reference document; and a document classifier configured to group the first template document and the reference document as common documents in response to determining that the two or more distances between the plurality of common identical text objects in the first template document are within the given percentage of variance as the two or more distances between the plurality of common identical text objects in the reference document.
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9. A system comprising: a document processor, comprising a processor, that receives a first template document, wherein the first template document comprises a first plurality of text objects, receives a reference document, wherein the reference document comprises second a plurality of text objects, wherein at least one of the first template document and the reference document are misaligned or upside down during the following: identify the first plurality of text objects in the first template document, identify the second plurality of text objects in the reference document, identify a plurality of common identical text objects between the first template document and the reference document, identify locations of the plurality of common identical text objects in the first template document, identify two or more distances between the locations of the plurality of common identical text objects in the first template document, identifying locations of the plurality of common identical text objects in the reference document, identify two or more distances between the locations of the plurality of common identical text objects in the reference document, and determining that the two or more distances between the plurality of common identical text objects in the first template document are within a given percentage of variance as the two or more distances between the plurality of common text objects in the reference document, wherein an endpoint of a first one of the two or more distances between the plurality of common identical text objects in the first template document is used as a starting point for a second one of the two or more distances between the plurality of common identical text objects in the first template document and wherein an endpoint of a first one of the two or more distances between the plurality of common identical text objects in the reference document is used as a starting point for a second one of the two or more distances between the plurality of common identical text objects in the reference document; and a document classifier configured to group the first template document and the reference document as common documents in response to determining that the two or more distances between the plurality of common identical text objects in the first template document are within the given percentage of variance as the two or more distances between the plurality of common identical text objects in the reference document. 14. The system of claim 9 , wherein determining that the first template document and the reference document are within the given percentage of variance further comprises: comparing at least one of a height, a width, a font, and a Dots Per Inch (DPI) of a common identical text object in the template document.
| 0.911765 |
9,495,467 | 9 | 10 |
9. A method of providing headlines for articles, comprising: preprocessing an electronic article for which a text headline is to be provided by generating metadata related to content of the article and by extracting one or more tickers from the article; providing a plurality of tools related to at least one of creating the text headline and editing the text headline, and a user interface for providing access to one or more of the plurality of tools, the user interface including a display that includes the text headline and one or more of the plurality of tools; and using the one or more of the plurality of tools to supply the text headline; wherein at least one of the plurality of tools uses at least some of the metadata generated by the preprocessing in order to specify that the text headline includes a corporation name that is associated with a ticker selected from the one or more tickers using the user interface.
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9. A method of providing headlines for articles, comprising: preprocessing an electronic article for which a text headline is to be provided by generating metadata related to content of the article and by extracting one or more tickers from the article; providing a plurality of tools related to at least one of creating the text headline and editing the text headline, and a user interface for providing access to one or more of the plurality of tools, the user interface including a display that includes the text headline and one or more of the plurality of tools; and using the one or more of the plurality of tools to supply the text headline; wherein at least one of the plurality of tools uses at least some of the metadata generated by the preprocessing in order to specify that the text headline includes a corporation name that is associated with a ticker selected from the one or more tickers using the user interface. 10. The method of claim 9 , wherein the preprocessing of the electronic article comprises a recordation of one or more metadata selected from a group consisting of an article number, a time stamp, a news wire service provider, the text headline, the ticker, a corporation's market capitalization, and a subject matter classification.
| 0.5 |
9,576,188 | 1 | 17 |
1. A method, comprising: establishing at least one substantially three dimensional learning model of at least one learning subject; establishing at least one substantially three dimensional gallery model for at least one gallery subject; establishing at least one substantially three dimensional query model of a query subject; determining a transform of at least one parent gallery model from among said at least one gallery model in combination with at least one active learning model from among said at least one learning model so as to yield at least one transformed gallery model, wherein said transformed gallery model approaches correspondence with at least one of said at least one query model in at least one model property as compared with said parent gallery model; applying said transform; and comparing at least one substantially two dimensional transformed gallery image at least substantially corresponding with said at least one transformed gallery model against at least one substantially two dimensional query image at least substantially corresponding with said at least one query model, so as to determine whether said at least one query subject is said at least one gallery subject.
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1. A method, comprising: establishing at least one substantially three dimensional learning model of at least one learning subject; establishing at least one substantially three dimensional gallery model for at least one gallery subject; establishing at least one substantially three dimensional query model of a query subject; determining a transform of at least one parent gallery model from among said at least one gallery model in combination with at least one active learning model from among said at least one learning model so as to yield at least one transformed gallery model, wherein said transformed gallery model approaches correspondence with at least one of said at least one query model in at least one model property as compared with said parent gallery model; applying said transform; and comparing at least one substantially two dimensional transformed gallery image at least substantially corresponding with said at least one transformed gallery model against at least one substantially two dimensional query image at least substantially corresponding with said at least one query model, so as to determine whether said at least one query subject is said at least one gallery subject. 17. The method of claim 1 , comprising: establishing at least one substantially two dimensional query image of said at least one query subject; and determining said at least one query model therefrom.
| 0.827883 |
7,925,673 | 1 | 12 |
1. A method for providing an interactive knowledge based community solution, the community comprising multiple users, each of the multiple users belonging to a user type, the user types comprising participant, mentor, and subject matter expert, the method comprising the steps of: (a) associating a user profile with at least one of the multiple users; (b) matching a participant user with a mentor user based on user profiles of the participant user and the mentor user; (c) matching a participant user with at least one subject matter expert user based on the user profile of the participant user including at least one of an industry identifier and an occupation identifier, and based on the user profile of the at least one subject matter expert user including at least one of an industry identifier and an occupation identifier; and (d) providing a computerized terminal interface for allowing at least one user to interact with at least one other user; wherein the computerized terminal interface displays personalized content to each participant user, and the displayed personalized content is selected on the basis of at least one of (i) a match between the participant user and a mentor user, and (ii) a match between the participant user and at least one subject matter expert user; and wherein each mentor user and subject matter expert user differs from one another.
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1. A method for providing an interactive knowledge based community solution, the community comprising multiple users, each of the multiple users belonging to a user type, the user types comprising participant, mentor, and subject matter expert, the method comprising the steps of: (a) associating a user profile with at least one of the multiple users; (b) matching a participant user with a mentor user based on user profiles of the participant user and the mentor user; (c) matching a participant user with at least one subject matter expert user based on the user profile of the participant user including at least one of an industry identifier and an occupation identifier, and based on the user profile of the at least one subject matter expert user including at least one of an industry identifier and an occupation identifier; and (d) providing a computerized terminal interface for allowing at least one user to interact with at least one other user; wherein the computerized terminal interface displays personalized content to each participant user, and the displayed personalized content is selected on the basis of at least one of (i) a match between the participant user and a mentor user, and (ii) a match between the participant user and at least one subject matter expert user; and wherein each mentor user and subject matter expert user differs from one another. 12. The method of claim 1 , wherein the interface further displays content including at least one of (i) career-related information and (ii) job-related information, that is selected on the basis of the user profile of the participant user.
| 0.568345 |
7,860,811 | 1 | 3 |
1. A computer-based recommendation method comprising: generating an affinity vector between a first user of a computer-based system and a plurality of computer-based objects based, at least in part, on the first user's behaviors; generating a similarity metric between the first user and a second user of the computer-based system based, at least in part, on the affinity vector of the first user and an affinity vector of the second user; generating a recommendation for delivery to the first user based, at least in part, on the affinity vector of the first user and the similarity metric; and generating an explanation for the recommendation comprising one or more phrases, wherein the selection of the one or more phrases is based, at least in part, on a plurality of user behaviors and in accordance with a computer-implemented syntactical structure.
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1. A computer-based recommendation method comprising: generating an affinity vector between a first user of a computer-based system and a plurality of computer-based objects based, at least in part, on the first user's behaviors; generating a similarity metric between the first user and a second user of the computer-based system based, at least in part, on the affinity vector of the first user and an affinity vector of the second user; generating a recommendation for delivery to the first user based, at least in part, on the affinity vector of the first user and the similarity metric; and generating an explanation for the recommendation comprising one or more phrases, wherein the selection of the one or more phrases is based, at least in part, on a plurality of user behaviors and in accordance with a computer-implemented syntactical structure. 3. The method of claim 1 wherein generating a recommendation for delivery to the first user based, at least in part, on the affinity vector of the first user and the similarity metric comprises: recommending the second user to the first user.
| 0.716628 |
9,697,300 | 6 | 7 |
6. A graph syntax validation system, comprising: a processor configured to receive (i) an input graph that contains one or more input graph nodes, the input graph is checked for use of valid syntax or invalid syntax, (ii) transformation rules, and (iii) a minimal valid graph, wherein the input graph nodes indicate, in a graph notation, types of nodes, wherein the types of the nodes include functions, events, and gateways, wherein a syntax is defined by the transformation rules; transform, in response to receiving the input graph, the input graph toward the minimal valid graph using the transformation rules, each of the transformation rules includes a source pattern and a target pattern; source pattern-match by comparing the input graph with the source patterns of the transformation rules and determining whether the input graph matches the source pattern of one or more transformation rules; and rule-execute, by replacing the input graph nodes that are determined to match with the source pattern of one or more transformation rules with the target patterns for the one or more transformation rules, wherein the processor recurrently transforms until either the input graph has been determined to be reduced to the minimal valid graph indicating that the input graph uses the valid syntax, or until it is determined that none of the transformation rules match the input graph indicating that the input graph uses an invalid syntax; and output, after transforming, a result indicating either that the input graph is determined to use the valid syntax or the input graph is determined to use the invalid syntax.
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6. A graph syntax validation system, comprising: a processor configured to receive (i) an input graph that contains one or more input graph nodes, the input graph is checked for use of valid syntax or invalid syntax, (ii) transformation rules, and (iii) a minimal valid graph, wherein the input graph nodes indicate, in a graph notation, types of nodes, wherein the types of the nodes include functions, events, and gateways, wherein a syntax is defined by the transformation rules; transform, in response to receiving the input graph, the input graph toward the minimal valid graph using the transformation rules, each of the transformation rules includes a source pattern and a target pattern; source pattern-match by comparing the input graph with the source patterns of the transformation rules and determining whether the input graph matches the source pattern of one or more transformation rules; and rule-execute, by replacing the input graph nodes that are determined to match with the source pattern of one or more transformation rules with the target patterns for the one or more transformation rules, wherein the processor recurrently transforms until either the input graph has been determined to be reduced to the minimal valid graph indicating that the input graph uses the valid syntax, or until it is determined that none of the transformation rules match the input graph indicating that the input graph uses an invalid syntax; and output, after transforming, a result indicating either that the input graph is determined to use the valid syntax or the input graph is determined to use the invalid syntax. 7. The system of claim 6 , wherein the processor is further configured to result-visualize the transformation result.
| 0.596552 |
8,209,333 | 23 | 26 |
23. A method for providing contextually related content to a user, the method comprising: detecting an occurrence of a key phrase on a page of a site; transforming the occurrence of the key phrase on the page, as loaded by a browser on a user computing device, into a user-selectable display element that is selectable by a user to initiate a display of contextually related content, wherein the key phrase is transformed into the user-selectable display element based on a score generated for said key phrase, said score based at least partly on view counts of social media content items associated with the key phrase; and responding to user selection of the display element by displaying contextually related content in a panel on the page, said contextually related content including an advertisement associated with the key phrase and further including non-advertisement social media content associated with the key phrase, said panel generated on the page by execution by the browser of a browser-executable component loaded by the browser.
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23. A method for providing contextually related content to a user, the method comprising: detecting an occurrence of a key phrase on a page of a site; transforming the occurrence of the key phrase on the page, as loaded by a browser on a user computing device, into a user-selectable display element that is selectable by a user to initiate a display of contextually related content, wherein the key phrase is transformed into the user-selectable display element based on a score generated for said key phrase, said score based at least partly on view counts of social media content items associated with the key phrase; and responding to user selection of the display element by displaying contextually related content in a panel on the page, said contextually related content including an advertisement associated with the key phrase and further including non-advertisement social media content associated with the key phrase, said panel generated on the page by execution by the browser of a browser-executable component loaded by the browser. 26. The method of claim 23 , wherein the user selection of the display element is a mouse-over event in which a mouse cursor is hovered over the display element.
| 0.754573 |
7,877,815 | 1 | 10 |
1. A method for battery authentication in a wireless communication device with an attached battery, comprising the steps of: (a) the wireless communication device entering a low power mode, wherein the low power mode prevents the wireless communication device from initiating and receiving calls; (b) the wireless communication device sending, in the low power mode, a pre-stored plain text to the attached battery, wherein the pre-stored plain text is generated by a tool external to the wireless communication device, wherein the pre-stored plain text is stored in a memory of the wireless communication device during provisioning; (c) waiting, in the low power mode, for a first time period after the step of sending to receive encrypted text from the attached battery; (d) if encrypted text is not received within the first time period, then repeating, in the low power mode, the steps of (a) and (b) up to a pre-defined number of attempts, (e) if the encrypted text is not received within the first time period, and the pre-defined number of attempts is exhausted, then entering, in the low power mode, a battery authentication failure event procedure; (f) if encrypted text is received within the first time period, then comparing, in the low power mode, the encrypted text received by the wireless communication device with a pre-stored encrypted text that is associated with the pre-stored plain text; (g) if the encrypted text received by the wireless communication device matches the pre-stored encrypted text, then identifying the attached battery as an authentic battery and entering an operational mode, wherein the operational mode enables the wireless communication device to proceed with normal operations; and (h) if the encrypted text received by the wireless communication device does not match the pre-stored encrypted text, then entering the battery authentication failure event procedure.
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1. A method for battery authentication in a wireless communication device with an attached battery, comprising the steps of: (a) the wireless communication device entering a low power mode, wherein the low power mode prevents the wireless communication device from initiating and receiving calls; (b) the wireless communication device sending, in the low power mode, a pre-stored plain text to the attached battery, wherein the pre-stored plain text is generated by a tool external to the wireless communication device, wherein the pre-stored plain text is stored in a memory of the wireless communication device during provisioning; (c) waiting, in the low power mode, for a first time period after the step of sending to receive encrypted text from the attached battery; (d) if encrypted text is not received within the first time period, then repeating, in the low power mode, the steps of (a) and (b) up to a pre-defined number of attempts, (e) if the encrypted text is not received within the first time period, and the pre-defined number of attempts is exhausted, then entering, in the low power mode, a battery authentication failure event procedure; (f) if encrypted text is received within the first time period, then comparing, in the low power mode, the encrypted text received by the wireless communication device with a pre-stored encrypted text that is associated with the pre-stored plain text; (g) if the encrypted text received by the wireless communication device matches the pre-stored encrypted text, then identifying the attached battery as an authentic battery and entering an operational mode, wherein the operational mode enables the wireless communication device to proceed with normal operations; and (h) if the encrypted text received by the wireless communication device does not match the pre-stored encrypted text, then entering the battery authentication failure event procedure. 10. The method of claim 1 , wherein a battery authentication security level is “low” and wherein the battery authentication failure event procedure comprises the steps of: displaying a message in a pop-up window to indicate that the attached battery is not authentic; receiving a message acknowledgement; conducting normal battery operations; and conducting normal battery charging operations.
| 0.618447 |
9,313,722 | 13 | 17 |
13. A machine-implemented method, comprising: receiving a first set of scan data that includes information regarding wireless access points available to each device of the first group; computing a set of statistics for each of multiple subsets of devices of the first group based on the first set of scan data; classifying each of the subsets of devices in one of multiple proximity classes; training a model to classify the subsets of devices in the respective proximity classes based on the respective sets of statistics; receiving a second set of scan data that includes information regarding wireless access points available to each device of a second group; computing the set of statistics for the second group of devices based on the second set of scan data; and classifying the second group of devices in one of the proximity classes based on the set of statistics of the second group and the model.
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13. A machine-implemented method, comprising: receiving a first set of scan data that includes information regarding wireless access points available to each device of the first group; computing a set of statistics for each of multiple subsets of devices of the first group based on the first set of scan data; classifying each of the subsets of devices in one of multiple proximity classes; training a model to classify the subsets of devices in the respective proximity classes based on the respective sets of statistics; receiving a second set of scan data that includes information regarding wireless access points available to each device of a second group; computing the set of statistics for the second group of devices based on the second set of scan data; and classifying the second group of devices in one of the proximity classes based on the set of statistics of the second group and the model. 17. The machine-implemented method of claim 13 , further including: performing the receiving a first set of scan data, the computing a set of statistics, the classifying each of the subsets, the training, and the outputting on a server system; and performing the receiving a second set of scan data, the computing the set of statistics for the second group of devices, and the classifying the second group of devices on a device of the second group; wherein the receiving a second set of scan data further includes exchanging scan data with the second device.
| 0.716531 |
9,530,415 | 13 | 17 |
13. The system of claim 12 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, cause the processor to perform operations comprising, upon a second indication from a user, processing the transcription in the specific field.
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13. The system of claim 12 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, cause the processor to perform operations comprising, upon a second indication from a user, processing the transcription in the specific field. 17. The system of claim 13 , wherein processing the text in the specific field is performed as though the user typed the text in the specific field.
| 0.5 |
7,769,904 | 10 | 15 |
10. A system for transmitting data formatted in an extensible markup language (XML), comprising: a parser configured to convert from an extensible markup language (XML) representation that is compatible with standard XML to a single data stream binary representation by providing binary data representations for element start tags and data values within the XML representation and by not providing binary data representations for element end tags within the XML representation; wherein the binary data representations are each formed using X-bit bytes; and wherein consistent extensible encoding is provided for each binary data representation by using a most-significant-bit of each X-bit byte as a termination indicator bit where a first logic level indicates the byte is a termination byte and a second logic level indicates that more bytes are included in a multi-byte data word, and the XML representation and the binary representation being defined according to document type definition (DTD); and a communication interface coupled to the parser and configured to transmit the single data stream binary representation to an external system through a network; wherein the element start tags are represented using positive integer binary data representations; and wherein the data values are represented using binary data representations selected from a group comprising a string, an integer, a floating point number, an enumerated value, a pattern, and a packed component.
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10. A system for transmitting data formatted in an extensible markup language (XML), comprising: a parser configured to convert from an extensible markup language (XML) representation that is compatible with standard XML to a single data stream binary representation by providing binary data representations for element start tags and data values within the XML representation and by not providing binary data representations for element end tags within the XML representation; wherein the binary data representations are each formed using X-bit bytes; and wherein consistent extensible encoding is provided for each binary data representation by using a most-significant-bit of each X-bit byte as a termination indicator bit where a first logic level indicates the byte is a termination byte and a second logic level indicates that more bytes are included in a multi-byte data word, and the XML representation and the binary representation being defined according to document type definition (DTD); and a communication interface coupled to the parser and configured to transmit the single data stream binary representation to an external system through a network; wherein the element start tags are represented using positive integer binary data representations; and wherein the data values are represented using binary data representations selected from a group comprising a string, an integer, a floating point number, an enumerated value, a pattern, and a packed component. 15. The system of claim 10 , wherein the network comprises a communication channel having a bandwidth of less than or equal to about 9600 baud.
| 0.70332 |
9,305,051 | 1 | 6 |
1. A computer-implemented method, comprising: extracting query reformulations from search logs, each of the query reformulations including an initial query and a query qualifier not specified in the initial query; clustering the extracted query reformulations into clusters using modified star clustering such that a set of query aspects is identified, the set of query aspects including query qualifiers of the query reformulations, wherein clustering includes generating star-shaped subgraphs using the query qualifiers, wherein clustering is performed without using the query reformulations or corresponding queries; receiving a search query; identifying query aspects for the search query from the set of query aspects such that a similarity measure is maximized; and presenting the identified query aspects along with results of the search query, wherein the identified query aspects are presented as options for refinement of the search query.
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1. A computer-implemented method, comprising: extracting query reformulations from search logs, each of the query reformulations including an initial query and a query qualifier not specified in the initial query; clustering the extracted query reformulations into clusters using modified star clustering such that a set of query aspects is identified, the set of query aspects including query qualifiers of the query reformulations, wherein clustering includes generating star-shaped subgraphs using the query qualifiers, wherein clustering is performed without using the query reformulations or corresponding queries; receiving a search query; identifying query aspects for the search query from the set of query aspects such that a similarity measure is maximized; and presenting the identified query aspects along with results of the search query, wherein the identified query aspects are presented as options for refinement of the search query. 6. The method of claim 1 , wherein clustering comprises k means clustering.
| 0.884259 |
8,850,372 | 2 | 3 |
2. The computer-implemented method of claim 1 , wherein executing the proof algorithm comprises: establishing the specified resource limit to enable less than a complete run of the proof algorithm on the design model, wherein a pre-specified resource limit is selected from among a time limit, a depth limit, and a hardware resource usage limit; and executing the proof algorithm for only a preset limit, wherein the proof algorithm iterates over a series of timesteps corresponding to states extending from an initial state (t0) to a subsequent state (tk) at which a proof condition holds true over a first k timesteps for a set of bounded invariants identified at the respective states, wherein said set of bounded invariants hold true for a particular state from the initial state and wherein the invariants each refer to one or more components of said design.
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2. The computer-implemented method of claim 1 , wherein executing the proof algorithm comprises: establishing the specified resource limit to enable less than a complete run of the proof algorithm on the design model, wherein a pre-specified resource limit is selected from among a time limit, a depth limit, and a hardware resource usage limit; and executing the proof algorithm for only a preset limit, wherein the proof algorithm iterates over a series of timesteps corresponding to states extending from an initial state (t0) to a subsequent state (tk) at which a proof condition holds true over a first k timesteps for a set of bounded invariants identified at the respective states, wherein said set of bounded invariants hold true for a particular state from the initial state and wherein the invariants each refer to one or more components of said design. 3. The computer-implemented method of claim 2 , further comprising: incrementally refining and extending a sequence of sets of invariants representing bounded invariants and determining a relevance of the one or more design components referenced in the invariant clauses by: evaluating, for each invariant, whether the invariant is an unbounded invariant that is first introduced at a specific timestep between the initial and the kth timestep; deterministically assigning relative priorities to one or more design components referenced in the invariant based on the specific timestep at which the unbounded invariant is introduced; determining for each design component referenced by an invariant, if the design component has a priority that is equal to a highest priority assigned among the design components; and in response to the design component not having a priority equal to the highest priority assigned, identifying the design component as a cutpoint and replacing the design component with the cutpoint within the abstracted design.
| 0.5 |
9,128,986 | 30 | 31 |
30. The computer program product of claim 26 , wherein the computer program code further comprises program instructions for caching a plurality of objects corresponding to data present in the XML file, wherein the data corresponds to one or more commands associated with the table.
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30. The computer program product of claim 26 , wherein the computer program code further comprises program instructions for caching a plurality of objects corresponding to data present in the XML file, wherein the data corresponds to one or more commands associated with the table. 31. The computer program product of claim 30 , wherein the computer program code further comprises program instructions for retrieving a table object from the plurality of objects, the table object comprising a screen object and one or more parameters corresponding to the table.
| 0.5 |
9,886,703 | 5 | 8 |
5. The method of claim 4 , wherein the plurality of dynamic centroids include a dynamic IP centroid derived from a third plurality of ad requests made within a predetermined time duration.
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5. The method of claim 4 , wherein the plurality of dynamic centroids include a dynamic IP centroid derived from a third plurality of ad requests made within a predetermined time duration. 8. The method of claim 5 , wherein each of the third plurality of requests does not include an IP address, and wherein the third plurality of requests includes geographic coordinates within a predefined range of each other.
| 0.5 |
10,133,621 | 10 | 13 |
10. A method comprising: accessing, from a machine-readable storage device, a data object representing an investigative issue; causing presentation, on a display of a device, of a user interface configured to receive user search queries and present search results for each received search query; causing presentation of a set of search results within the user interface in response to receiving a search query; receiving a user selection of one or more filters; filtering the search results in accordance with the one or more filters; receiving a user selection of text included in a particular search result of the set of search results; generating a token that includes the text; identifying additional instances of the token in a remainder of the set of search results; upon receiving a request to present one of the remainder of the set of search results, visually distinguishing the additional instances of the token in the one of the remainder of the set of search results; tracking user activity that includes one or more user actions performed as part of an investigation of the investigatory issue, the one or more user actions including user interactions with the user interface; creating, by one or more processors, a record of the user activity involving the investigatory issue, the record including the one or more user actions; and linking the record of the user activity with the data object representing the investigative issue, the linking of the record of user activity with the data object including modifying the data object to include the record of user activity.
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10. A method comprising: accessing, from a machine-readable storage device, a data object representing an investigative issue; causing presentation, on a display of a device, of a user interface configured to receive user search queries and present search results for each received search query; causing presentation of a set of search results within the user interface in response to receiving a search query; receiving a user selection of one or more filters; filtering the search results in accordance with the one or more filters; receiving a user selection of text included in a particular search result of the set of search results; generating a token that includes the text; identifying additional instances of the token in a remainder of the set of search results; upon receiving a request to present one of the remainder of the set of search results, visually distinguishing the additional instances of the token in the one of the remainder of the set of search results; tracking user activity that includes one or more user actions performed as part of an investigation of the investigatory issue, the one or more user actions including user interactions with the user interface; creating, by one or more processors, a record of the user activity involving the investigatory issue, the record including the one or more user actions; and linking the record of the user activity with the data object representing the investigative issue, the linking of the record of user activity with the data object including modifying the data object to include the record of user activity. 13. The method of claim 10 , wherein the one or more user actions include at least one of: a search query input by the user, a search result accessed by the user, a linkage between two or more data objects generated by the user, a token created by the user, or a note created by the user.
| 0.616 |
9,501,549 | 8 | 14 |
8. A system comprising: a data store for storing primary scores and auxiliary scores for a set of criteria; and one or more processors configured to interact with the data store, the one or more processors being further configured to perform operations comprising: identifying a primary ranking signal and a set of auxiliary ranking signals for ranking the set of criteria for a content item, wherein the primary ranking signal defines a first attribute for one of the criteria in the set of criteria and each auxiliary ranking signal in the set of auxiliary ranking signals a) defines a second attribute for one of the criteria in the set of criteria and b) is different than the primary ranking signal; for each particular criterion in the set of criteria: identifying a primary score representing a value of the primary ranking signal for the particular criterion; identifying a set of auxiliary scores for the particular criterion, each auxiliary score representing a value of an auxiliary ranking signal of the set of auxiliary ranking signals for the particular criterion; adjusting each auxiliary score in the set of auxiliary scores to generate adjusted auxiliary scores, the adjusting comprising applying, to at least a portion of the auxiliary scores, a transformation function that reduces an amount of skewness among the auxiliary scores that are associated with a particular auxiliary ranking signal from the set of auxiliary ranking signals; and determining a ranking score for the particular criterion based on a function of the primary score for the particular criterion and the adjusted auxiliary scores, the function suppressing effects of adjusted auxiliary scores for the particular criterion that do not satisfy a specified value and boosting the ranking score using adjusted auxiliary scores for the particular criterion that satisfy the specified value; selecting one or more criteria in the set of criteria for which to associate the content item based on the ranking score for each particular criterion; and providing the content item in response to receiving data specifying one or more of the selected criteria.
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8. A system comprising: a data store for storing primary scores and auxiliary scores for a set of criteria; and one or more processors configured to interact with the data store, the one or more processors being further configured to perform operations comprising: identifying a primary ranking signal and a set of auxiliary ranking signals for ranking the set of criteria for a content item, wherein the primary ranking signal defines a first attribute for one of the criteria in the set of criteria and each auxiliary ranking signal in the set of auxiliary ranking signals a) defines a second attribute for one of the criteria in the set of criteria and b) is different than the primary ranking signal; for each particular criterion in the set of criteria: identifying a primary score representing a value of the primary ranking signal for the particular criterion; identifying a set of auxiliary scores for the particular criterion, each auxiliary score representing a value of an auxiliary ranking signal of the set of auxiliary ranking signals for the particular criterion; adjusting each auxiliary score in the set of auxiliary scores to generate adjusted auxiliary scores, the adjusting comprising applying, to at least a portion of the auxiliary scores, a transformation function that reduces an amount of skewness among the auxiliary scores that are associated with a particular auxiliary ranking signal from the set of auxiliary ranking signals; and determining a ranking score for the particular criterion based on a function of the primary score for the particular criterion and the adjusted auxiliary scores, the function suppressing effects of adjusted auxiliary scores for the particular criterion that do not satisfy a specified value and boosting the ranking score using adjusted auxiliary scores for the particular criterion that satisfy the specified value; selecting one or more criteria in the set of criteria for which to associate the content item based on the ranking score for each particular criterion; and providing the content item in response to receiving data specifying one or more of the selected criteria. 14. The system of claim 8 , wherein the one or more processors are further configured to perform further operations comprising normalizing auxiliary scores for each auxiliary ranking signal.
| 0.877419 |
10,133,727 | 10 | 11 |
10. A computer system comprising: a computer processor operatively coupled to an interactive display; a database in communication with the computer processor, the database comprising memory for storing clinical documentation; a natural language engine executing on the computer processor, the natural language engine configured to: input narrative text from the clinical documentation, the narrative text comprising sections of words; segment the sections of words based on boundaries defined between the sections of words in the documentation; map the segmented sections of words to semantic objects in an ontology, the ontology defining classes of the semantic objects based on axes of a multi-axial coding scheme for coding the clinical documentation and based on concepts of a conceptual data resource, wherein the classes of semantic objects define a hierarchical structure in the ontology, the hierarchical structure defining conditions on and relationships between the semantic objects; convert the semantic objects into characters; position the characters into slots in a procedural or a diagnostic medical code, wherein positions of the slots are defined by the multi-axial coding scheme and wherein in the multi-axial coding system each position of a character within the procedural or diagnostic medical code corresponds to a semi-independent axis of classification of a procedure or diagnosis; output the characters to the user interface; output, to the user interface, trace data that includes linking information to map characters in a selected slot in the procedural or the diagnostic medical code to particular locations in the narrative text of the clinical documentation from which the characters in the selected slot in the medical code are derived; and infer a character in at least one of the slots in the procedural or the diagnostic medical code, wherein the inferred character is associated with a semantic object that is not mapped to sequenced words in the segmented text, the sematic object being inferred from one or more other semantic objects that are mapped to sequenced words in the segmented text.
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10. A computer system comprising: a computer processor operatively coupled to an interactive display; a database in communication with the computer processor, the database comprising memory for storing clinical documentation; a natural language engine executing on the computer processor, the natural language engine configured to: input narrative text from the clinical documentation, the narrative text comprising sections of words; segment the sections of words based on boundaries defined between the sections of words in the documentation; map the segmented sections of words to semantic objects in an ontology, the ontology defining classes of the semantic objects based on axes of a multi-axial coding scheme for coding the clinical documentation and based on concepts of a conceptual data resource, wherein the classes of semantic objects define a hierarchical structure in the ontology, the hierarchical structure defining conditions on and relationships between the semantic objects; convert the semantic objects into characters; position the characters into slots in a procedural or a diagnostic medical code, wherein positions of the slots are defined by the multi-axial coding scheme and wherein in the multi-axial coding system each position of a character within the procedural or diagnostic medical code corresponds to a semi-independent axis of classification of a procedure or diagnosis; output the characters to the user interface; output, to the user interface, trace data that includes linking information to map characters in a selected slot in the procedural or the diagnostic medical code to particular locations in the narrative text of the clinical documentation from which the characters in the selected slot in the medical code are derived; and infer a character in at least one of the slots in the procedural or the diagnostic medical code, wherein the inferred character is associated with a semantic object that is not mapped to sequenced words in the segmented text, the sematic object being inferred from one or more other semantic objects that are mapped to sequenced words in the segmented text. 11. The computer system of claim 10 , wherein the user interface is configured for a user to accept or reject the code based on the trace data.
| 0.750871 |
8,190,684 | 1 | 10 |
1. A method of intelligently distributing, in a networked environment, an object that represents an offering, the method comprising: receiving a request from a user initiated at a computing device to create the object to represent the offering; creating the object to represent the offering to be made available for access in the networked environment, the object being created to include metadata specifying criteria of target recipients of the offering; wherein, the criteria of target recipients are received in the networked environment from the user that requested creation of the object, matching the criteria specified in the metadata of the object to users in the networked environment, to find recipients who satisfy the criteria; automatically sending the offering represented by the object to the recipients who satisfy the criteria specified in the metadata; automatically generating multiple versions of the object to represent the offering based on an example object specified by the user; test-posting the multiple versions to compute price-performance attributes of each of the multiple versions.
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1. A method of intelligently distributing, in a networked environment, an object that represents an offering, the method comprising: receiving a request from a user initiated at a computing device to create the object to represent the offering; creating the object to represent the offering to be made available for access in the networked environment, the object being created to include metadata specifying criteria of target recipients of the offering; wherein, the criteria of target recipients are received in the networked environment from the user that requested creation of the object, matching the criteria specified in the metadata of the object to users in the networked environment, to find recipients who satisfy the criteria; automatically sending the offering represented by the object to the recipients who satisfy the criteria specified in the metadata; automatically generating multiple versions of the object to represent the offering based on an example object specified by the user; test-posting the multiple versions to compute price-performance attributes of each of the multiple versions. 10. The method of claim 1 , further comprising, creating a second object to represent a request for the offering.
| 0.797491 |
8,233,712 | 14 | 17 |
14. A method of segmenting an image comprising the steps of: (a) performing a preliminary segmentation; (b) providing initial input segmentation parameters; (c) using a fuzzy logic inference system using the initial input segmentation parameters and object features to evaluate new segmentation parameters; and (d) performing segmentation of the image using the new parameters.
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14. A method of segmenting an image comprising the steps of: (a) performing a preliminary segmentation; (b) providing initial input segmentation parameters; (c) using a fuzzy logic inference system using the initial input segmentation parameters and object features to evaluate new segmentation parameters; and (d) performing segmentation of the image using the new parameters. 17. A non-transitory computer readable memory having recorded thereon statements and instructions for execution by a computer to carry out the method of claim 14 .
| 0.5 |
10,049,416 | 12 | 16 |
12. The non-transitory computer-readable storage medium of claim 10 , the computer program instructions further comprising instructions for: serving the job recall material to the user; and storing a response to the job recall material received from the user as a job recall activity completed by the user.
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12. The non-transitory computer-readable storage medium of claim 10 , the computer program instructions further comprising instructions for: serving the job recall material to the user; and storing a response to the job recall material received from the user as a job recall activity completed by the user. 16. The non-transitory computer-readable storage medium of claim 12 , wherein the online education platform stores a plurality of job classes, each job class associated with one or more job recall materials and one or more job listings, and wherein recommending the job recall material to the user comprises: identifying a recall gap between job recall activities completed by the user and job recall materials associated with one or more of the job classes, the recall gap comprising one or more uncompleted job recall activities; and recommending the uncompleted job recall activities to the user.
| 0.5 |
7,765,477 | 1 | 9 |
1. A computer-implemented method for searching an electronic document that includes a non-coded representation of characters of text, the method comprising: receiving text coding information identifying each of a plurality of characters of text represented by the non-coded representation; based on the text coding information, generating a coded representation that: specifies, for each of the plurality of characters of text represented by the non-coded representation, a respective code value based on a character encoding, the code value selected to represent the respective character of text, and associates a particular glyph from a collection of glyphs with each of the code values specified for the plurality of characters of text, the particular glyph selected independently of any relation to the respective character of text, the collection of glyphs being insufficient to semantically represent the plurality of characters of text; associating the coded representation with the non-coded representation, wherein a code value of one of the plurality of characters of text is associated with one or more positions in a visual representation of the non-coded representation; displaying the visual representation of the non-coded representation; searching the coded representation to find a coded character sequence that includes one or more characters at a location in the coded representation; and highlighting, in the displayed visual representation of the non-coded representation, the portion of the non-coded visual representation associated with the coded character sequence at the location in the coded representation.
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1. A computer-implemented method for searching an electronic document that includes a non-coded representation of characters of text, the method comprising: receiving text coding information identifying each of a plurality of characters of text represented by the non-coded representation; based on the text coding information, generating a coded representation that: specifies, for each of the plurality of characters of text represented by the non-coded representation, a respective code value based on a character encoding, the code value selected to represent the respective character of text, and associates a particular glyph from a collection of glyphs with each of the code values specified for the plurality of characters of text, the particular glyph selected independently of any relation to the respective character of text, the collection of glyphs being insufficient to semantically represent the plurality of characters of text; associating the coded representation with the non-coded representation, wherein a code value of one of the plurality of characters of text is associated with one or more positions in a visual representation of the non-coded representation; displaying the visual representation of the non-coded representation; searching the coded representation to find a coded character sequence that includes one or more characters at a location in the coded representation; and highlighting, in the displayed visual representation of the non-coded representation, the portion of the non-coded visual representation associated with the coded character sequence at the location in the coded representation. 9. The method of claim 1 , further comprising: storing the coded representation in a first document; and storing the non-coded representation in a second document; wherein associating the coded representation with the non-coded representation includes associating the first document with the second document.
| 0.549708 |
9,594,747 | 15 | 20 |
15. A method, comprising: identifying, by a device, main concepts and attributes in listing corpora; clustering, by the device, words, in the listing corpora, based on at least one of the main concepts or the attributes according to one or more rules, the one or more rules including one or more of: a first rule preventing clustering of words based on a frequency of appearance of words in a same listing corpora, a second rule preventing clustering of a quantitative attribute word with a qualitative attribute word, or a third rule indicating clustering of two words when characters of a first word, of the two words, are included in a second word of the two words; and providing, by the device, after clustering the words, the main concept words and the attribute words as at least a portion of a semantic model, the semantic model being used for subsequent clustering.
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15. A method, comprising: identifying, by a device, main concepts and attributes in listing corpora; clustering, by the device, words, in the listing corpora, based on at least one of the main concepts or the attributes according to one or more rules, the one or more rules including one or more of: a first rule preventing clustering of words based on a frequency of appearance of words in a same listing corpora, a second rule preventing clustering of a quantitative attribute word with a qualitative attribute word, or a third rule indicating clustering of two words when characters of a first word, of the two words, are included in a second word of the two words; and providing, by the device, after clustering the words, the main concept words and the attribute words as at least a portion of a semantic model, the semantic model being used for subsequent clustering. 20. The method of claim 15 , where the device is a semantic model generation device.
| 0.895522 |
8,595,235 | 9 | 10 |
9. A method implemented by a computer comprising at least one processor for creating classes for classifying digitized documents comprising: generating a plurality of word pairs, each word pair comprising a word from a first digitized document, and a corresponding word from a second digitized document; computing for each word pair first location information for the word that indicates a location of the word in the first digitized document relative to other words in the first digitized document; computing for each word pair second location information for the corresponding word that indicates a location of the corresponding word in the second digitized document relative to other words in the second digitized document; comparing the first and second location information; and creating one or more classes responsive to the comparison to classify digitized documents similar to the first digitized document, and to classify digitized documents similar to the second digitized document.
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9. A method implemented by a computer comprising at least one processor for creating classes for classifying digitized documents comprising: generating a plurality of word pairs, each word pair comprising a word from a first digitized document, and a corresponding word from a second digitized document; computing for each word pair first location information for the word that indicates a location of the word in the first digitized document relative to other words in the first digitized document; computing for each word pair second location information for the corresponding word that indicates a location of the corresponding word in the second digitized document relative to other words in the second digitized document; comparing the first and second location information; and creating one or more classes responsive to the comparison to classify digitized documents similar to the first digitized document, and to classify digitized documents similar to the second digitized document. 10. The method of claim 9 comprising: if the comparison indicates locations of words in the first digitized document are the same as locations of corresponding words in the second digitized document, determining that the first and second digitized documents should be in a same class; and upon the determination that the first and second digitized documents should be in the same class, creating a class to classify documents similar to the first and second digitized documents.
| 0.645401 |
7,743,082 | 1 | 11 |
1. A computer system comprising: at least one processor for executing computer-executable instructions; and at least one computer-readable storage medium storing computer-executable instructions, which when executed by the at least one processor, cause the computing system to perform steps, comprising: receiving a document for storing in association with a selected document library file system folder, the selected document library file system folder is associated with a selected document library from among a plurality of document libraries, each document library among the plurality of document libraries comprising a document library database, a document library file system folder, and documents included within the document library file system folder, wherein each document library of the plurality of document libraries has a corresponding set of properties that apply to the type of documents that are associated with that document library; associating the set of properties corresponding to the selected document library with the document such that the document is associated with a consistent set of properties applied to all documents stored in association with the selected document library, and such that each document in the selected document library has the consistent set of properties that make such documents specific to only the selected document library; writing property value information for at least some of the properties in the set to the document library database of the selected document library that includes an entry for the document to relate the property value information to the document; and storing the document in the selected document library file system folder of the selected document library, such that the document and all other document stored in the selected document library file system folder have consistent properties making such documents specific to the selected document library in which the documents are all stored.
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1. A computer system comprising: at least one processor for executing computer-executable instructions; and at least one computer-readable storage medium storing computer-executable instructions, which when executed by the at least one processor, cause the computing system to perform steps, comprising: receiving a document for storing in association with a selected document library file system folder, the selected document library file system folder is associated with a selected document library from among a plurality of document libraries, each document library among the plurality of document libraries comprising a document library database, a document library file system folder, and documents included within the document library file system folder, wherein each document library of the plurality of document libraries has a corresponding set of properties that apply to the type of documents that are associated with that document library; associating the set of properties corresponding to the selected document library with the document such that the document is associated with a consistent set of properties applied to all documents stored in association with the selected document library, and such that each document in the selected document library has the consistent set of properties that make such documents specific to only the selected document library; writing property value information for at least some of the properties in the set to the document library database of the selected document library that includes an entry for the document to relate the property value information to the document; and storing the document in the selected document library file system folder of the selected document library, such that the document and all other document stored in the selected document library file system folder have consistent properties making such documents specific to the selected document library in which the documents are all stored. 11. The computer system of claim 1 having further computer-executable instructions comprising, displaying at least some of the property value information on a view page based upon the entry for the document.
| 0.566946 |
8,468,012 | 1 | 9 |
1. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving an audio signal that corresponds to an utterance recorded by a mobile device, determining a geographic location associated with the mobile device, determining a geographic location type associated with the geographic location, selecting a subset of geotagged audio signals based on the geographic location type associated with the geographic location of the mobile device, and based on context data associated with the utterance, wherein the context data comprises data that references a time or a date when the utterance was recorded by the mobile device, data that references a speed or an amount of motion measured by the mobile device when the utterance was recorded, data that references settings of the mobile device or data that references a type of the mobile device; adapting one or more acoustic models for the geographic location type, and performing speech recognition on the audio signal using the one or more acoustic models that are adapted for the geographic location type.
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1. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving an audio signal that corresponds to an utterance recorded by a mobile device, determining a geographic location associated with the mobile device, determining a geographic location type associated with the geographic location, selecting a subset of geotagged audio signals based on the geographic location type associated with the geographic location of the mobile device, and based on context data associated with the utterance, wherein the context data comprises data that references a time or a date when the utterance was recorded by the mobile device, data that references a speed or an amount of motion measured by the mobile device when the utterance was recorded, data that references settings of the mobile device or data that references a type of the mobile device; adapting one or more acoustic models for the geographic location type, and performing speech recognition on the audio signal using the one or more acoustic models that are adapted for the geographic location type. 9. The system of claim 1 , wherein adapting one or more acoustic models for the geographic location type further comprises: selecting, from among multiple acoustic models that have been generated for multiple geographic location types, the one or more acoustic models generated for the geographic location type associated with the geographic location of the mobile device.
| 0.643678 |
8,868,509 | 10 | 15 |
10. A computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code to modify the application to register a servlet; computer readable program code to publish the application to the cloud computing environment; during execution of the application, computer readable program code to use the servlet to: detect annotated entities created in the code of the application by parsing user codes; find out properties and property types of the annotated entities; generate a plurality of structured query language (SQL) statements to query out data to be backed up in accordance with the annotated entities; and publish the backed up data.
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10. A computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code to modify the application to register a servlet; computer readable program code to publish the application to the cloud computing environment; during execution of the application, computer readable program code to use the servlet to: detect annotated entities created in the code of the application by parsing user codes; find out properties and property types of the annotated entities; generate a plurality of structured query language (SQL) statements to query out data to be backed up in accordance with the annotated entities; and publish the backed up data. 15. The computer readable storage medium according to claim 10 , further comprising computer readable program code to add a library to the application.
| 0.690574 |
8,700,641 | 11 | 15 |
11. A system, comprising: a processor, communicatively coupled to a memory that stores computer-executable instructions, that executes or facilitates execution of the computer-executable instructions to perform operations comprising: a social application server: determine a first match M h between a first audio descriptor representing a first recording at a first time step in an environment and a first reference descriptor, the first match M h having-a first confidence score C h indicative of a confidence of the first match, the first time step having a time step length l; determine a second match M 0 between a second audio descriptor representing a second recording at a second time step in the environment and a second reference descriptor, the second match M 0 having a second confidence score C 0 indicative of a confidence of the second match, the second time step having the time step length l, wherein the first time step is temporally prior to the second time step, and the first match M h and the second match M 0 are non-identity matches determined using a direct or locality sensitive hashing function and a validation process to select a most accurate match out of a plurality of candidate matches, wherein the first confidence score C h and the second confidence score C 0 are based upon a log-likelihood function given by an audio fingerprinting process; discount the first confidence score C h by a discount value l/L to generate a discounted first confidence score C h −l/L, where L is an expected dwell time between a channel change; in response to the discounted first confidence score C h −l/L being greater than the second confidence score C 0 , employ the first reference descriptor associated with the first match M h for selecting related content; and in response to the discounted first confidence score C h −l/L not being greater than the second confidence score C 0 , employ the second reference descriptor associated with the second match M 0 for selecting the related content.
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11. A system, comprising: a processor, communicatively coupled to a memory that stores computer-executable instructions, that executes or facilitates execution of the computer-executable instructions to perform operations comprising: a social application server: determine a first match M h between a first audio descriptor representing a first recording at a first time step in an environment and a first reference descriptor, the first match M h having-a first confidence score C h indicative of a confidence of the first match, the first time step having a time step length l; determine a second match M 0 between a second audio descriptor representing a second recording at a second time step in the environment and a second reference descriptor, the second match M 0 having a second confidence score C 0 indicative of a confidence of the second match, the second time step having the time step length l, wherein the first time step is temporally prior to the second time step, and the first match M h and the second match M 0 are non-identity matches determined using a direct or locality sensitive hashing function and a validation process to select a most accurate match out of a plurality of candidate matches, wherein the first confidence score C h and the second confidence score C 0 are based upon a log-likelihood function given by an audio fingerprinting process; discount the first confidence score C h by a discount value l/L to generate a discounted first confidence score C h −l/L, where L is an expected dwell time between a channel change; in response to the discounted first confidence score C h −l/L being greater than the second confidence score C 0 , employ the first reference descriptor associated with the first match M h for selecting related content; and in response to the discounted first confidence score C h −l/L not being greater than the second confidence score C 0 , employ the second reference descriptor associated with the second match M 0 for selecting the related content. 15. The system of claim 11 , wherein the first reference descriptor has a highest confidence score of a plurality of reference descriptors that match the first audio descriptor.
| 0.721698 |
8,417,651 | 18 | 20 |
18. A computer based method of matching a text description to one of a set of structured records of products in a database, the structured records individually having a plurality of attributes associated with corresponding values, the method comprising: parsing a text description related to a product into a plurality of text segments; for each of at least some of the structured records in the database, individually associating the text segments with one of the attributes of the structured record; generating a similarity vector having one or more elements individually representing a similarity of the values of attributes in the text description and those in the corresponding structured record; calculating a probability of match between the text description and the structured record based on the generated similarity vector; and selecting one of the structured record as a match for the text description based on the calculated probabilities.
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18. A computer based method of matching a text description to one of a set of structured records of products in a database, the structured records individually having a plurality of attributes associated with corresponding values, the method comprising: parsing a text description related to a product into a plurality of text segments; for each of at least some of the structured records in the database, individually associating the text segments with one of the attributes of the structured record; generating a similarity vector having one or more elements individually representing a similarity of the values of attributes in the text description and those in the corresponding structured record; calculating a probability of match between the text description and the structured record based on the generated similarity vector; and selecting one of the structured record as a match for the text description based on the calculated probabilities. 20. The method of claim 18 , further comprising: generating a subset of the structured records as candidate records using inverted indices of the attributes, wherein for each of at least some of the structured records in the database includes: for each of the subset of the structured records in the database, individually associating the text segments with one of the attributes of the product corresponding to the structured record; generating a similarity vector having one or more elements individually representing a similarity of the values of corresponding attributes in the text description and in the structured record; and calculating a probability of match between the text description and the structured record based on the generated similarity vector.
| 0.5 |
9,318,110 | 12 | 17 |
12. A method for correcting errors in an audio transcription comprising: recording an analog audio transmission with an analog audio recorder; converting the analog format to a digital format with a transcription generator including an analog-to-digital audio converter; generating a transcription of said audio transmission; storing said audio recording; generating a collection of link data; storing the text of said transcription; playing the recorded audio transmission; cross linking said stored text with said recorded audio transmission; editing said text using a cursor; dragging a slider on a playback controller located on the text editor screen to jump to any part of the recording; and jumping the text cursor to a corresponding playback position by a first button, disabling a text tracking function of the audio transcription by a second button, and optionally controlling speed of a playback by a third button.
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12. A method for correcting errors in an audio transcription comprising: recording an analog audio transmission with an analog audio recorder; converting the analog format to a digital format with a transcription generator including an analog-to-digital audio converter; generating a transcription of said audio transmission; storing said audio recording; generating a collection of link data; storing the text of said transcription; playing the recorded audio transmission; cross linking said stored text with said recorded audio transmission; editing said text using a cursor; dragging a slider on a playback controller located on the text editor screen to jump to any part of the recording; and jumping the text cursor to a corresponding playback position by a first button, disabling a text tracking function of the audio transcription by a second button, and optionally controlling speed of a playback by a third button. 17. The method for correcting errors in an audio transcription of claim 12 , further comprising: providing feedback from the step of editing to the step of generating a transcription.
| 0.635458 |
7,596,576 | 16 | 18 |
16. The computer system of claim 11 , wherein the class defining the structure and methods of the user-defined type further comprises an attribute that specifies that serialized binary representations of instances of the user-defined type will be binary ordered.
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16. The computer system of claim 11 , wherein the class defining the structure and methods of the user-defined type further comprises an attribute that specifies that serialized binary representations of instances of the user-defined type will be binary ordered. 18. The computer system recited in claim 16 , wherein the database server creates a table in a database store in which a type of a column of the table is defined as the user-defined type, and wherein the database server creates an index on the column.
| 0.790134 |
7,580,836 | 29 | 30 |
29. An article of manufacture comprising: a computer-readable storage medium having executable instructions thereon which when executed cause a processor to perform operations comprising: (a) recognizing utterances through converting the utterances into a recognized phone string; (b) comparing the recognized string with a reference string to determine errors; (c) calculating estimated weights for sections of the utterances; (d) marking the errors in the utterances and providing corresponding estimated weights to form adaptation enrollment data; and (e) using the adaptation enrollment data to convert a speaker independent model to a speaker dependent model; wherein an average likelihood difference per frame is used to calculate the estimated weights and is calculated according to the equation (1) as follows: Ln = H L n H e n - H b n - R L n R e n - R b n , ( 1 ) where H L n is a log likelihood of hypothesis word n, H b n is a beginning frame index (in time), and H e n is an end frame index, and R L n , R b n and R e n are counter parts for the reference string, and a weight for misrecognized words of a particular speaker “i” is calculated according to equation (2) as follows: W i = 1 m * ∑ n = 1 m Ln , ( 2 ) wherein m is a number of misrecognized words.
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29. An article of manufacture comprising: a computer-readable storage medium having executable instructions thereon which when executed cause a processor to perform operations comprising: (a) recognizing utterances through converting the utterances into a recognized phone string; (b) comparing the recognized string with a reference string to determine errors; (c) calculating estimated weights for sections of the utterances; (d) marking the errors in the utterances and providing corresponding estimated weights to form adaptation enrollment data; and (e) using the adaptation enrollment data to convert a speaker independent model to a speaker dependent model; wherein an average likelihood difference per frame is used to calculate the estimated weights and is calculated according to the equation (1) as follows: Ln = H L n H e n - H b n - R L n R e n - R b n , ( 1 ) where H L n is a log likelihood of hypothesis word n, H b n is a beginning frame index (in time), and H e n is an end frame index, and R L n , R b n and R e n are counter parts for the reference string, and a weight for misrecognized words of a particular speaker “i” is calculated according to equation (2) as follows: W i = 1 m * ∑ n = 1 m Ln , ( 2 ) wherein m is a number of misrecognized words. 30. The article of manufacture of claim 29 wherein the executable instructions causing the processor to perform calculating estimated weights comprises executable instructions thereon which when executed cause the processor to perform operations comprising: running a force alignment program on the reference string to obtain statistics of references; decoding the utterances to obtain statistics of 1-best hypothesis; and aligning the 1-best hypothesis with the reference string to obtain the error words.
| 0.5 |
8,219,396 | 2 | 4 |
2. The apparatus of claim 1 , wherein the speech recognizer comprises: a speech recognition unit configured to detect speech sections of the reproduced audio signals and performing the speech recognition on the detected speech sections; and a storage unit configured to store the speech recognition results and the detected speech sections of the reproduced audio signals.
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2. The apparatus of claim 1 , wherein the speech recognizer comprises: a speech recognition unit configured to detect speech sections of the reproduced audio signals and performing the speech recognition on the detected speech sections; and a storage unit configured to store the speech recognition results and the detected speech sections of the reproduced audio signals. 4. The apparatus of claim 2 , wherein the speech recognition unit uses an end-point detection function to detect the speech sections of the reproduced audio signals.
| 0.691011 |
9,043,257 | 1 | 15 |
1. An application server for matching a plurality of users within a domain, said application server configured to: (A) implement a social network having a plurality of users; (B) observe network behaviors of at least some of said plurality of users of said social network; (C) develop profiles of at least some of said plurality of users within at least one of a plurality of domains using a profile function, wherein (i) said profile function defines a level of relevance of network behaviors for said domain, (ii) said profile function maps said observed network behaviors to said profiles for said domain and (iii) each of said profiles stores a descriptor representing one of said plurality of users for said domain; and (D) compute matches of two or more of said plurality of users with respect to one of said domains, wherein said matches are based on a relation of common descriptors of said profiles for said domain.
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1. An application server for matching a plurality of users within a domain, said application server configured to: (A) implement a social network having a plurality of users; (B) observe network behaviors of at least some of said plurality of users of said social network; (C) develop profiles of at least some of said plurality of users within at least one of a plurality of domains using a profile function, wherein (i) said profile function defines a level of relevance of network behaviors for said domain, (ii) said profile function maps said observed network behaviors to said profiles for said domain and (iii) each of said profiles stores a descriptor representing one of said plurality of users for said domain; and (D) compute matches of two or more of said plurality of users with respect to one of said domains, wherein said matches are based on a relation of common descriptors of said profiles for said domain. 15. The application server according to claim 1 , wherein content is (i) recommended in a first mode and (ii) presented in a second mode based on said profile and said domain.
| 0.773316 |
7,603,272 | 1 | 13 |
1. A system for generating a block diagonal matrix from a lattice, the system comprising: (1) a processor; (2) a module configured to control the processor to compute posterior probability of all transitions T in a graph, if a lattice having transitions T is weighted; (3) a module configured to control the processor to extract a pivot baseline path from the lattice; and (4) a module configured to control the processor to align the transitions T in the lattice with the transitions in the pivot baseline path.
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1. A system for generating a block diagonal matrix from a lattice, the system comprising: (1) a processor; (2) a module configured to control the processor to compute posterior probability of all transitions T in a graph, if a lattice having transitions T is weighted; (3) a module configured to control the processor to extract a pivot baseline path from the lattice; and (4) a module configured to control the processor to align the transitions T in the lattice with the transitions in the pivot baseline path. 13. The system of claim 1 , wherein the block diagonal matrix preserves the accuracy of the lattice.
| 0.801587 |
8,406,382 | 1 | 3 |
1. A method comprising: receiving a call from a party at a voice response system; capturing verbal communication spoken by the party; creating a voice model associated with the party, the voice model being created by processing the captured verbal communication spoken by the party; storing the created voice model in a memory; verifying the identity of the party; and updating a previously stored voice model of the party, the previously stored voice model of the party having been registered during a previous call received from the party, wherein the creating of the voice model is imperceptible to the party.
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1. A method comprising: receiving a call from a party at a voice response system; capturing verbal communication spoken by the party; creating a voice model associated with the party, the voice model being created by processing the captured verbal communication spoken by the party; storing the created voice model in a memory; verifying the identity of the party; and updating a previously stored voice model of the party, the previously stored voice model of the party having been registered during a previous call received from the party, wherein the creating of the voice model is imperceptible to the party. 3. The method according to claim 1 , further comprising prompting the party for information when the party requests access to account information.
| 0.755853 |
8,533,208 | 17 | 18 |
17. A non-transitory computer-readable medium to identify topics among a group of documents, comprising a set of instructions which, when implemented by one or more computing devices, cause the one or more machines to perform the following operations to: search a set of documents to identify a key phrase, the identifying comprising clarifying a term found in at least one of the set of documents by extracting log data related to the term from a corresponding session log of a user interaction with a service or product, the clarifying relating the term to the key phrase; select a first subset of documents from the set of documents, based on each document in the first subset of documents including the key phrase; build a syntactic tree of a sentence within a document from the first subset of documents, the syntactic tree identifying a relationship between parts of the sentence; build a lexical pattern including a plurality of tokens, the plurality of tokens including a key phrase token, a polarity token, and a special token that indicates a relationship between the key phrase token and the polarity token, the special token being separate and distinct from the key phrase token and the polarity token; and determine that the document conveys an opinion by matching the lexical pattern including the plurality of tokens to the syntactic tree.
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17. A non-transitory computer-readable medium to identify topics among a group of documents, comprising a set of instructions which, when implemented by one or more computing devices, cause the one or more machines to perform the following operations to: search a set of documents to identify a key phrase, the identifying comprising clarifying a term found in at least one of the set of documents by extracting log data related to the term from a corresponding session log of a user interaction with a service or product, the clarifying relating the term to the key phrase; select a first subset of documents from the set of documents, based on each document in the first subset of documents including the key phrase; build a syntactic tree of a sentence within a document from the first subset of documents, the syntactic tree identifying a relationship between parts of the sentence; build a lexical pattern including a plurality of tokens, the plurality of tokens including a key phrase token, a polarity token, and a special token that indicates a relationship between the key phrase token and the polarity token, the special token being separate and distinct from the key phrase token and the polarity token; and determine that the document conveys an opinion by matching the lexical pattern including the plurality of tokens to the syntactic tree. 18. The computer-readable medium of claim 17 , wherein the set of documents are from an electronic community forum related to a product available through an electronic commerce system.
| 0.775061 |
9,009,131 | 8 | 9 |
8. A system comprising: (a) server connected to a network, the server including: (a) at least one processor; and, (b) a memory operatively coupled to said at least one processor, the memory storing program instructions that when executed by the at least one processor, cause the at least one processor to: (i) initiate a search of word-indexed database, one word at a time; (ii) pass the results of the first-word search through a duplicate document elimination module in order to eliminate duplicate documents; (iii) store the results of the first word search in a smaller more relevant database organized in said memory of said server; (iv) search every document in said smaller more relevant database associated with the first of the multiplicity of key words, by means of searching the remaining key words through each document and noting in which document each key word appears, without regard to frequency of appearance; resulting in all combinations of key words in any document being identified and each document assigned a number indicating the number of key word appearances; (v) calculate a document relevancy factor as the percentage of key words appearing in each document as the number of key words found in the document disregarding word appearance frequency, divided by the number of key words employed in the search, time one hundred; (vi) calculate a ranking number for each document that is the resultant of the total cumulative word count for all key words in the document multiplied by the documents relevancy factor, with higher numbers taking precedence over lower numbers; (vii) repeat steps (i) through (vi) for the remaining words of said query; and, (viii) sending these results back to the user.
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8. A system comprising: (a) server connected to a network, the server including: (a) at least one processor; and, (b) a memory operatively coupled to said at least one processor, the memory storing program instructions that when executed by the at least one processor, cause the at least one processor to: (i) initiate a search of word-indexed database, one word at a time; (ii) pass the results of the first-word search through a duplicate document elimination module in order to eliminate duplicate documents; (iii) store the results of the first word search in a smaller more relevant database organized in said memory of said server; (iv) search every document in said smaller more relevant database associated with the first of the multiplicity of key words, by means of searching the remaining key words through each document and noting in which document each key word appears, without regard to frequency of appearance; resulting in all combinations of key words in any document being identified and each document assigned a number indicating the number of key word appearances; (v) calculate a document relevancy factor as the percentage of key words appearing in each document as the number of key words found in the document disregarding word appearance frequency, divided by the number of key words employed in the search, time one hundred; (vi) calculate a ranking number for each document that is the resultant of the total cumulative word count for all key words in the document multiplied by the documents relevancy factor, with higher numbers taking precedence over lower numbers; (vii) repeat steps (i) through (vi) for the remaining words of said query; and, (viii) sending these results back to the user. 9. The system of claim 8 wherein said processor simultaneously performing steps (vii) continuously as the server processes step (i) for the next succeeding word of the multiplicity of key words of the query.
| 0.738636 |
7,979,417 | 1 | 10 |
1. A computer-implemented method of processing documents, comprising: receiving a document in a search engine crawler, the document having a first link tag embedded in the document, the first link tag including a location value and one or more information pairs that are distinct from the location value, wherein a respective information pair has a respective parameter and a corresponding parameter value; selecting a method of processing content, wherein the content is specified by the location value of the first link tag and the selected method of processing is in accordance with one or more of the one or more information pairs of the first link tag; retrieving the content specified by the location value of the first link tag; and processing the retrieved content specified by the first link tag in accordance with the selected method to add information to one or more databases used by a search engine.
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1. A computer-implemented method of processing documents, comprising: receiving a document in a search engine crawler, the document having a first link tag embedded in the document, the first link tag including a location value and one or more information pairs that are distinct from the location value, wherein a respective information pair has a respective parameter and a corresponding parameter value; selecting a method of processing content, wherein the content is specified by the location value of the first link tag and the selected method of processing is in accordance with one or more of the one or more information pairs of the first link tag; retrieving the content specified by the location value of the first link tag; and processing the retrieved content specified by the first link tag in accordance with the selected method to add information to one or more databases used by a search engine. 10. The method of claim 1 , wherein the first link tag is XML compatible.
| 0.924431 |
9,697,830 | 12 | 13 |
12. The computer program product according to claim 1 , wherein the method further comprises eliminating all hits containing consecutive time pairs that are not ordered.
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12. The computer program product according to claim 1 , wherein the method further comprises eliminating all hits containing consecutive time pairs that are not ordered. 13. The computer program product according to claim 12 , wherein two time pairs (s i ,e i ) and (s i+1 ,e i+1 ) are ordered if s i <s i+1 and s i+1 −e i <thresh, where thresh is empirically determined.
| 0.5 |
7,725,346 | 9 | 10 |
9. A computer program product having a plurality of executable instruction codes that are stored on a computer-readable medium, which, when executed by a computer, predict an increase in sales from a plurality of online public discussions, comprising: a first set of instruction codes stored on a computer-readable medium for receiving a product information input for defining a product for which sales are predicted; a second set of instruction codes stored on a computer-readable medium for receiving a temporally defined input based on a number of times the product receives a mention from the plurality of online public discussions, wherein the temporally defined input is derived from on line chatter containing a time stamp; a third set of instruction codes stored on a computer-readable medium for generating a restriction that can automatically change between a plurality of levels of disambiguation employing queries based on domain-specific keywords, wherein the restriction is applied to the temporally defined input; a fourth set of instruction codes stored on a computer-readable medium for filtering out false results of the temporally defined input with the restriction; a fifth set of instruction codes stored on a computer-readable medium for generating a signal quantifying the number of times the product is mentioned, wherein an amplitude of the signal is based on the number of times the product is mentioned in the temporally defined input; a sixth set of instruction codes stored on a computer-readable medium for identifying one or more spikes in the number of times the product is mentioned being present in the signal, wherein the one or more spikes are based on a rate of change in the amplitude exceeding a threshold value between two points in time in the temporally defined input; a seventh set of instruction codes stored on a computer-readable medium for identifying a largest spike among the one or more spikes, wherein the largest spike includes a highest amplitude of the generated signal among a selected number of the one or more spikes with respective amplitudes exceeding the threshold value; an eighth set of instruction codes stored on a computer-readable medium for generating a correlation value between the temporally defined input and a sales rank time series of said product, wherein the sales rank time series represents measured sales of the product, and using the correlation value as a comparison between measured sales of the product and the temporally defined input, determining an optimum lag value for values where the correlation value is a maximum, wherein negative values for the optimum lag value are considered leading and non-negative values for the optimum lag value are considered trailing; and a ninth set of instruction codes stored on a computer-readable medium for predicting the increase in sales of the product from the identified largest spike of the generated signal, where the predicting comprises: a spikes-predictor algorithm that categorizes a prediction as one of the categories selected from the group consisting of leading, trailing, inside, and incorrect; wherein the leading category indicates the identified largest spike occurs after a time t but within a predetermined elapsed time; wherein the trailing category indicates the identified largest spike has already occurred within the predetermined elapsed time; wherein the inside category indicates the identified largest spike is currently occurring; and wherein the incorrect category indicates the identified largest spike does not occur within the predetermined elapsed time; and a prediction algorithm that predicts the increase in sales of the product from the added spike of the signal if the correlation value is at least 0.5, the optimum lag is leading and there is a sudden increase in the temporally defined input, wherein the prediction algorithm includes feature quantizing that maps differences in elements of the sales rank times series to predict if the tomorrow value differs from a current value by more than a predetermined value, wherein the prediction algorithm alters the level of disambiguation if the optimum lag is not leading or the correlation value is less than 0.5.
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9. A computer program product having a plurality of executable instruction codes that are stored on a computer-readable medium, which, when executed by a computer, predict an increase in sales from a plurality of online public discussions, comprising: a first set of instruction codes stored on a computer-readable medium for receiving a product information input for defining a product for which sales are predicted; a second set of instruction codes stored on a computer-readable medium for receiving a temporally defined input based on a number of times the product receives a mention from the plurality of online public discussions, wherein the temporally defined input is derived from on line chatter containing a time stamp; a third set of instruction codes stored on a computer-readable medium for generating a restriction that can automatically change between a plurality of levels of disambiguation employing queries based on domain-specific keywords, wherein the restriction is applied to the temporally defined input; a fourth set of instruction codes stored on a computer-readable medium for filtering out false results of the temporally defined input with the restriction; a fifth set of instruction codes stored on a computer-readable medium for generating a signal quantifying the number of times the product is mentioned, wherein an amplitude of the signal is based on the number of times the product is mentioned in the temporally defined input; a sixth set of instruction codes stored on a computer-readable medium for identifying one or more spikes in the number of times the product is mentioned being present in the signal, wherein the one or more spikes are based on a rate of change in the amplitude exceeding a threshold value between two points in time in the temporally defined input; a seventh set of instruction codes stored on a computer-readable medium for identifying a largest spike among the one or more spikes, wherein the largest spike includes a highest amplitude of the generated signal among a selected number of the one or more spikes with respective amplitudes exceeding the threshold value; an eighth set of instruction codes stored on a computer-readable medium for generating a correlation value between the temporally defined input and a sales rank time series of said product, wherein the sales rank time series represents measured sales of the product, and using the correlation value as a comparison between measured sales of the product and the temporally defined input, determining an optimum lag value for values where the correlation value is a maximum, wherein negative values for the optimum lag value are considered leading and non-negative values for the optimum lag value are considered trailing; and a ninth set of instruction codes stored on a computer-readable medium for predicting the increase in sales of the product from the identified largest spike of the generated signal, where the predicting comprises: a spikes-predictor algorithm that categorizes a prediction as one of the categories selected from the group consisting of leading, trailing, inside, and incorrect; wherein the leading category indicates the identified largest spike occurs after a time t but within a predetermined elapsed time; wherein the trailing category indicates the identified largest spike has already occurred within the predetermined elapsed time; wherein the inside category indicates the identified largest spike is currently occurring; and wherein the incorrect category indicates the identified largest spike does not occur within the predetermined elapsed time; and a prediction algorithm that predicts the increase in sales of the product from the added spike of the signal if the correlation value is at least 0.5, the optimum lag is leading and there is a sudden increase in the temporally defined input, wherein the prediction algorithm includes feature quantizing that maps differences in elements of the sales rank times series to predict if the tomorrow value differs from a current value by more than a predetermined value, wherein the prediction algorithm alters the level of disambiguation if the optimum lag is not leading or the correlation value is less than 0.5. 10. The computer program product of claim 9 wherein the predetermined elapsed time is two weeks.
| 0.883777 |
8,024,715 | 1 | 5 |
1. A method for transforming code to detect transient faults, comprising: translating binary code to an intermediate language code; identifying an instruction of interest in the intermediate language code; inserting reliability instructions in the intermediate language code to validate register values in memory accessed by the instruction of interest; and translating the intermediate language code to binary code.
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1. A method for transforming code to detect transient faults, comprising: translating binary code to an intermediate language code; identifying an instruction of interest in the intermediate language code; inserting reliability instructions in the intermediate language code to validate register values in memory accessed by the instruction of interest; and translating the intermediate language code to binary code. 5. The method of claim 1 , wherein identifying an instruction of interest comprises identifying a timestamp counter read instruction.
| 0.5625 |
7,777,125 | 21 | 22 |
21. The system of claim 20 further wherein the global classes of links of the sparse graph of media object similarities include one or more of music artists, music albums, and music tracks.
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21. The system of claim 20 further wherein the global classes of links of the sparse graph of media object similarities include one or more of music artists, music albums, and music tracks. 22. The system of claim 21 further comprising performing a simplex optimization for automatically optimizing one or more of the weighted global classes of links for maximally matching one or more predefined data sets.
| 0.5 |
8,938,461 | 9 | 10 |
9. The computer implemented method of claim 8 , further comprising: creating an association between nodes that are associated with documents found to near-duplicate to each other.
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9. The computer implemented method of claim 8 , further comprising: creating an association between nodes that are associated with documents found to near-duplicate to each other. 10. The computer implemented method of claim 9 , further comprising: enabling a user to define a degree of similarity between documents for documents to be considered near-duplicating.
| 0.5 |
8,583,628 | 19 | 20 |
19. A computer-readable memory having stored therein a set of instructions which, when executed by a processor, causes the processor to retrieve information from a database of relationally linked documents by: receiving search parameters from a user; locating an entry point document responsive to said search parameters, the entry point document comprising a root document in a hierarchy of a plurality of related documents; returning a search result including said entry point document and one or more manual relational links and one or more learned relational links between said entry point document and one or more related documents in the plurality of related documents, wherein the manual relational links comprise relational links between documents within the hierarchy manually encoded in the documents and wherein the learned relational links comprise dynamic links between documents within the hierarchy that are not manually encoded in the documents, that are not known at a time of creation of the documents, and that are generated automatically based on text of the documents; initiating one of said learned relational links in response to at least one user link selection; returning the document from the plurality of related documents that corresponds to said learned initiated relational link; updating a connection strength rating to said learned initiated relational link based on the user link selection and indicating navigation of the user through the hierarchy; associating said learned initiated relational link with said search parameters; storing in said database said learned relationally linked documents, said updated connection strength and said learned initiated relational link with said parameters; returning additional documents from the plurality of related documents; and recursively associating initiated relational links with said search parameters, wherein at least one of said returning steps include using a clustering algorithm on the hierarchy of the plurality of related documents.
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19. A computer-readable memory having stored therein a set of instructions which, when executed by a processor, causes the processor to retrieve information from a database of relationally linked documents by: receiving search parameters from a user; locating an entry point document responsive to said search parameters, the entry point document comprising a root document in a hierarchy of a plurality of related documents; returning a search result including said entry point document and one or more manual relational links and one or more learned relational links between said entry point document and one or more related documents in the plurality of related documents, wherein the manual relational links comprise relational links between documents within the hierarchy manually encoded in the documents and wherein the learned relational links comprise dynamic links between documents within the hierarchy that are not manually encoded in the documents, that are not known at a time of creation of the documents, and that are generated automatically based on text of the documents; initiating one of said learned relational links in response to at least one user link selection; returning the document from the plurality of related documents that corresponds to said learned initiated relational link; updating a connection strength rating to said learned initiated relational link based on the user link selection and indicating navigation of the user through the hierarchy; associating said learned initiated relational link with said search parameters; storing in said database said learned relationally linked documents, said updated connection strength and said learned initiated relational link with said parameters; returning additional documents from the plurality of related documents; and recursively associating initiated relational links with said search parameters, wherein at least one of said returning steps include using a clustering algorithm on the hierarchy of the plurality of related documents. 20. The computer-readable memory according to claim 19 wherein assigning a connection strength rating further comprises adjusting said connection strength rating according to the skill level of said user.
| 0.680251 |
9,700,276 | 11 | 12 |
11. An article of manufacture for tracking one or more catheter objects in a sequence of images, the article of manufacture comprising a computer-readable, non-transitory medium holding computer-executable instructions for performing the method comprising: determining a foreground portion of the first image comprising portions of the first image corresponding to one or more catheter electrode locations; determining a background portion of the first image which excludes the foreground portion; applying a steerable filter or a pre-processing method to the background portion of the first image to create a non-catheter structures mask which excludes ridge-like structures in the background portion of the first image; generating a dictionary based on catheter object locations in the first image, wherein sparse coding is used to represent the non-catheter structures mask as a plurality of basis vectors in the dictionary; identifying one or more catheter object landmark candidates in the sequence of images; generating a plurality of tracking hypothesis for the catheter object landmark candidates; generating a voting score for the catheter object landmark candidates based on a voting contribution of each of a plurality of image patches used to localize the catheter object locations in the first image; and selecting a first tracking hypothesis from the plurality of tracking hypothesis based on the dictionary and the voting score.
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11. An article of manufacture for tracking one or more catheter objects in a sequence of images, the article of manufacture comprising a computer-readable, non-transitory medium holding computer-executable instructions for performing the method comprising: determining a foreground portion of the first image comprising portions of the first image corresponding to one or more catheter electrode locations; determining a background portion of the first image which excludes the foreground portion; applying a steerable filter or a pre-processing method to the background portion of the first image to create a non-catheter structures mask which excludes ridge-like structures in the background portion of the first image; generating a dictionary based on catheter object locations in the first image, wherein sparse coding is used to represent the non-catheter structures mask as a plurality of basis vectors in the dictionary; identifying one or more catheter object landmark candidates in the sequence of images; generating a plurality of tracking hypothesis for the catheter object landmark candidates; generating a voting score for the catheter object landmark candidates based on a voting contribution of each of a plurality of image patches used to localize the catheter object locations in the first image; and selecting a first tracking hypothesis from the plurality of tracking hypothesis based on the dictionary and the voting score. 12. The article of manufacture claim 11 , wherein the selecting the first tracking hypothesis from the plurality of tracking hypothesis based on the dictionary comprises: determining a confidence score for each of tracking hypothesis included in the plurality of tracking hypothesis; and selecting the tracking hypothesis with the highest confidence score as the first tracking hypothesis.
| 0.734652 |
7,822,742 | 12 | 17 |
12. The system of claim 11 , wherein the search-result item is a web page.
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12. The system of claim 11 , wherein the search-result item is a web page. 17. The system of claim 12 , wherein the rank modifier determines that the search-result item includes two search terms of the user query that are adjacent to one another.
| 0.69788 |
8,836,729 | 7 | 9 |
7. A computer program product, tangibly stored on a non-transitory computer-readable storage device, for reflowing a page, comprising instructions operable to cause a programmable processor to: receive a page represented in a page description language, the page including a plurality of page objects that include one or more textual elements and one or more graphical elements; and change at least one of i) a size of the page and ii) a size of the page objects, wherein changing includes: creating one or more new pages, creating a map containing positions of the page objects in the page, and adding to the map updated positions of the page objects in the one or more new pages to produce a relationship for each page object between the position of the page object in the page and the updated position of the page object in the one or more new pages, adding the page objects to the one or more new pages according to the updated positions in the map, including adding a particular graphical element to the one or more new pages based on updated positions of one or more particular textual elements in the one or more new pages as listed in the map, the particular graphical element being anchored to the one or more particular textual elements; and scaling the particular graphical element based on a difference between a distance between two particular textual elements in the page and a corresponding distance between the particular two textual elements in the one or more new pages.
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7. A computer program product, tangibly stored on a non-transitory computer-readable storage device, for reflowing a page, comprising instructions operable to cause a programmable processor to: receive a page represented in a page description language, the page including a plurality of page objects that include one or more textual elements and one or more graphical elements; and change at least one of i) a size of the page and ii) a size of the page objects, wherein changing includes: creating one or more new pages, creating a map containing positions of the page objects in the page, and adding to the map updated positions of the page objects in the one or more new pages to produce a relationship for each page object between the position of the page object in the page and the updated position of the page object in the one or more new pages, adding the page objects to the one or more new pages according to the updated positions in the map, including adding a particular graphical element to the one or more new pages based on updated positions of one or more particular textual elements in the one or more new pages as listed in the map, the particular graphical element being anchored to the one or more particular textual elements; and scaling the particular graphical element based on a difference between a distance between two particular textual elements in the page and a corresponding distance between the particular two textual elements in the one or more new pages. 9. The computer program product of claim 7 further comprising instructions to scale the page objects prior to adding to the one or more new pages.
| 0.857977 |
8,458,276 | 18 | 20 |
18. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: evaluate a plurality of messages, each message associated with an author; log, for each message, information associated with the author, information associated with one or more designated recipients of the message, and time information associated with the message; determine correlation values for one or more sets of the designated recipients based on at least a portion of the logged information; and determine an association amongst a plurality of users over time, the determining being based on the correlation values, at least one of the plurality of users comprising at least one of the designated recipients.
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18. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: evaluate a plurality of messages, each message associated with an author; log, for each message, information associated with the author, information associated with one or more designated recipients of the message, and time information associated with the message; determine correlation values for one or more sets of the designated recipients based on at least a portion of the logged information; and determine an association amongst a plurality of users over time, the determining being based on the correlation values, at least one of the plurality of users comprising at least one of the designated recipients. 20. The system of claim 18 , the processors being further operable to: determine, based on the correlation values, a trend over time regarding messages related to a particular topic.
| 0.804301 |
9,430,531 | 89 | 92 |
89. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information, and the personally identifiable information comprises e-mail addresses; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender.
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89. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information, and the personally identifiable information comprises e-mail addresses; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender. 92. The method of claim 89 wherein the social graph comprises a plurality of activity information, each activity information represented in the social graph by an edge coupling at two nodes of the social graph.
| 0.790837 |
9,477,749 | 33 | 49 |
33. A non-transitory computer readable storage medium comprising instructions that if executed enables a computing system to: access unstructured data from one or more sources of text; process text from the unstructured data to extract features from the unstructured data; receive an instruction to execute a report from a user; receive an instruction to determine the one or more causal factors associated with an observation selected by the user; determine a baseline for comparison with the selected observation, the baseline being determined by the user as either data comprising one or more features in which the observation is not present or the data originating in a particular time period comprising one or more features in which the observation is present; determine the one or more causal factors associated with the selected observation by calculating an impact of one or more of the features of the unstructured data on the observation selected by the user using the baseline for comparison with the observation selected, at least one of the one or more causal factors comprising one or more of the features, and the impact on a measurable characteristic of the observation selected being calculated based on a comparison of one or more of the features of the unstructured data associated with the presence of the observation and features of the unstructured data associated with the baseline, the measurable characteristic being a volume-based metric, a sentiment metric, a satisfaction metric, or another user-defined metric; rank the one or more causal factors based on a measure of statistical association to the selected observation; and present results to the user.
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33. A non-transitory computer readable storage medium comprising instructions that if executed enables a computing system to: access unstructured data from one or more sources of text; process text from the unstructured data to extract features from the unstructured data; receive an instruction to execute a report from a user; receive an instruction to determine the one or more causal factors associated with an observation selected by the user; determine a baseline for comparison with the selected observation, the baseline being determined by the user as either data comprising one or more features in which the observation is not present or the data originating in a particular time period comprising one or more features in which the observation is present; determine the one or more causal factors associated with the selected observation by calculating an impact of one or more of the features of the unstructured data on the observation selected by the user using the baseline for comparison with the observation selected, at least one of the one or more causal factors comprising one or more of the features, and the impact on a measurable characteristic of the observation selected being calculated based on a comparison of one or more of the features of the unstructured data associated with the presence of the observation and features of the unstructured data associated with the baseline, the measurable characteristic being a volume-based metric, a sentiment metric, a satisfaction metric, or another user-defined metric; rank the one or more causal factors based on a measure of statistical association to the selected observation; and present results to the user. 49. The non-transitory computer readable storage medium of claim 33 , further comprising instructions that if executed enable the computing system to: present a trended report by displaying a measure trending over a time scale; and wherein the instructions for receiving an instruction to determine the one or more causal factors associated with the observation selected by the user further comprise instructions that if executed enable the computing system to: allow the user to select a specific data point on the time scale as the observation for investigating causal factors that drove the tracked measure to rise or fall when compared to the prior data point on the time scale.
| 0.536054 |
9,858,385 | 5 | 7 |
5. A computer program product for identifying errors in medical data, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instruction executable by a processor to cause the processor to perform a method comprising: receiving medical data comprising a report and an image; analyzing the report using natural language processing (NLP) to identify a condition and a criterion, wherein the condition is a medical condition, and wherein the criterion includes diagnostic information corresponding to the condition; generating an image analysis by analyzing the image using an image processing model; and determining whether the report has a potential problem by comparing the criterion to the image analysis.
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5. A computer program product for identifying errors in medical data, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instruction executable by a processor to cause the processor to perform a method comprising: receiving medical data comprising a report and an image; analyzing the report using natural language processing (NLP) to identify a condition and a criterion, wherein the condition is a medical condition, and wherein the criterion includes diagnostic information corresponding to the condition; generating an image analysis by analyzing the image using an image processing model; and determining whether the report has a potential problem by comparing the criterion to the image analysis. 7. The computer program product of claim 5 , the method performed by the processor further comprising: providing, in response to determining that the report has a potential problem, a notification indicating the potential problem.
| 0.833815 |
4,751,737 | 10 | 13 |
10. In a speech recognition system, wherein speech is represented by data in frames of equal time intervals, a method for generating a final word template from a plurality of tokens, comprising the steps of: (a) forming an interim template representative of at least one token; (b) generating a time alignment path between said interim template and an additional token; (c) weighting the data representing said interim template proportional to the number of tokens said interim template represents; and (d) combining frames from said interim template with frames from said additional token, dependent upon the number of tokens which the interim template represents, to produce output frames representative of the final word template.
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10. In a speech recognition system, wherein speech is represented by data in frames of equal time intervals, a method for generating a final word template from a plurality of tokens, comprising the steps of: (a) forming an interim template representative of at least one token; (b) generating a time alignment path between said interim template and an additional token; (c) weighting the data representing said interim template proportional to the number of tokens said interim template represents; and (d) combining frames from said interim template with frames from said additional token, dependent upon the number of tokens which the interim template represents, to produce output frames representative of the final word template. 13. A method for generating a final word template, according to claim 10, including the steps of comparing the data between the interim template and the additional token to produce a distance measure and comparing said distance measure to a predetermined distance measure.
| 0.682984 |
7,970,808 | 1 | 4 |
1. A method of classifying entities, the method comprising: using a processor to perform acts comprising: recognizing occurrences of an entity in a plurality of documents; identifying a plurality of features in contexts of said occurrences, a first one of the features being derived from a first context of a first one of the occurrences in a first one of the documents, and a second one of the features being derived from a second context of a second one of the occurrences in a second one of the documents; calculating a sum of a plurality of weights, wherein each of the features is associated with one of the weights; making a first determination that said sum exceeds a first threshold; making a second determination that a label applies to said entity based on said first determination; and storing or communicating a fact that said label applies to said entity, wherein said features comprise membership in a list, and wherein said acts further comprise: choosing a subset of members of said members of said list based on members in said subset being estimated to occur more frequently in said documents than other members of said list; and comparing a string that occurs in at least one of said contexts with members of said subset; and making a third determination that said string represents a member of said list, said third determination being made (a) based on said string's being among said subset, and (b) without use of a filter that accepts all strings that are members of said list and accepts at least one string that is not a member of said list.
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1. A method of classifying entities, the method comprising: using a processor to perform acts comprising: recognizing occurrences of an entity in a plurality of documents; identifying a plurality of features in contexts of said occurrences, a first one of the features being derived from a first context of a first one of the occurrences in a first one of the documents, and a second one of the features being derived from a second context of a second one of the occurrences in a second one of the documents; calculating a sum of a plurality of weights, wherein each of the features is associated with one of the weights; making a first determination that said sum exceeds a first threshold; making a second determination that a label applies to said entity based on said first determination; and storing or communicating a fact that said label applies to said entity, wherein said features comprise membership in a list, and wherein said acts further comprise: choosing a subset of members of said members of said list based on members in said subset being estimated to occur more frequently in said documents than other members of said list; and comparing a string that occurs in at least one of said contexts with members of said subset; and making a third determination that said string represents a member of said list, said third determination being made (a) based on said string's being among said subset, and (b) without use of a filter that accepts all strings that are members of said list and accepts at least one string that is not a member of said list. 4. The method of claim 1 , wherein said acts further comprise: storing a pair that comprises said entity and one of said features in either a first store or a second store; and choosing whether to store said pair in said first store or said second store based on an estimate of a frequency of said pair in said documents.
| 0.618765 |
8,117,242 | 6 | 8 |
6. The computer program product of claim 2 , wherein the computer program product is configured to cooperate with at least one mobile application configured to access at least one of the different online applications utilizing a mobile device, the computer program product further configured to allow the at least one mobile application to provide at least a portion of a functionality of the at least one of the different online applications.
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6. The computer program product of claim 2 , wherein the computer program product is configured to cooperate with at least one mobile application configured to access at least one of the different online applications utilizing a mobile device, the computer program product further configured to allow the at least one mobile application to provide at least a portion of a functionality of the at least one of the different online applications. 8. The computer program product of claim 6 , wherein the computer program product is configured such that the portion of the functionality is performed by a network browser plug-in installed on the mobile device.
| 0.625442 |
10,002,131 | 1 | 7 |
1. A non-transitory computer readable storage medium storing instructions that, in response to being executed by a computing device, cause the computing device to perform operations for building a user language model that indicates one or more natural languages for a user associated with a user identifier, the operations comprising: operations for receiving an indication of a set of one or more characteristics associated with the user identifier, wherein at least some of the received characteristics correspond to a specified likelihood that the user is facile with a particular language; operations for combining the specified likelihoods to generate a baseline language prediction; operations for receiving indications of one or more user actions, wherein each user action corresponds to a specified expectation that the user is facile with a particular language; and operations for updating the baseline language prediction to form a current language prediction indicating one or more languages the user is facile with, the updating based on a modification of the baseline language prediction using the specified expectations; wherein, for a selected language of the one or more of the languages which the current language prediction indicates the user is facile with, the language model includes at least a first identifier indicating whether the user can read in the selected language and at least a second identifier, different from the first identifier, indicating whether the user can write in the selected language; and wherein the operations for updating of the baseline language prediction comprise operations for associating one or more user actions with a weight value based on an observed intensity or frequency of the user action.
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1. A non-transitory computer readable storage medium storing instructions that, in response to being executed by a computing device, cause the computing device to perform operations for building a user language model that indicates one or more natural languages for a user associated with a user identifier, the operations comprising: operations for receiving an indication of a set of one or more characteristics associated with the user identifier, wherein at least some of the received characteristics correspond to a specified likelihood that the user is facile with a particular language; operations for combining the specified likelihoods to generate a baseline language prediction; operations for receiving indications of one or more user actions, wherein each user action corresponds to a specified expectation that the user is facile with a particular language; and operations for updating the baseline language prediction to form a current language prediction indicating one or more languages the user is facile with, the updating based on a modification of the baseline language prediction using the specified expectations; wherein, for a selected language of the one or more of the languages which the current language prediction indicates the user is facile with, the language model includes at least a first identifier indicating whether the user can read in the selected language and at least a second identifier, different from the first identifier, indicating whether the user can write in the selected language; and wherein the operations for updating of the baseline language prediction comprise operations for associating one or more user actions with a weight value based on an observed intensity or frequency of the user action. 7. The non-transitory computer readable storage medium of claim 1 , wherein, one or more of the user actions are actions taken by a user other than the user for which the language model is built.
| 0.819778 |
8,862,661 | 1 | 2 |
1. A client computer to process content in a plurality of languages comprising: an embedded database for storage and retrieval of content in a plurality languages, the content configuring user interface elements of an application program executing on the client computer, the user interface elements each associated with an identifier for associating the content, wherein first content is the content in a first language and second content is the content in a second language translated from the first language; and a content management module stored as instructions on a non-transitory computer-readable medium and executable by a processor to: establish a bind relationship between the content in the embedded database and a content database on a server computer, the bind relationship allowing the server computer to notify the client computer of any occurrences of changes to the content; generate by the application program at the client computer a request to the server computer for the first content, if the first content is not stored in the embedded database, and automatically receive from the server computer updated first content, if there is a change in the second content, store the first content in the embedded database at the client computer; retrieve the first content from the embedded database at the client computer; display the first content on a window of the application program at the client computer; and overlay the displayed first content with the updated first content.
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1. A client computer to process content in a plurality of languages comprising: an embedded database for storage and retrieval of content in a plurality languages, the content configuring user interface elements of an application program executing on the client computer, the user interface elements each associated with an identifier for associating the content, wherein first content is the content in a first language and second content is the content in a second language translated from the first language; and a content management module stored as instructions on a non-transitory computer-readable medium and executable by a processor to: establish a bind relationship between the content in the embedded database and a content database on a server computer, the bind relationship allowing the server computer to notify the client computer of any occurrences of changes to the content; generate by the application program at the client computer a request to the server computer for the first content, if the first content is not stored in the embedded database, and automatically receive from the server computer updated first content, if there is a change in the second content, store the first content in the embedded database at the client computer; retrieve the first content from the embedded database at the client computer; display the first content on a window of the application program at the client computer; and overlay the displayed first content with the updated first content. 2. The client computer of claim 1 further comprising instructions to: display a first portion of the first content on a first window of the application program at the client computer; receive a request to display a second portion of the first content on a second window of the application program; and generate, by the application program at the client computer, a request to the server computer for the second portion of the first content, if the second portion is not stored in the embedded database of the client computer.
| 0.5 |
7,650,286 | 56 | 59 |
56. The method of claim 55 , wherein said at least one attribute includes a name, a residence or business address, a telephone number, an electronic mail address, education data, past employer data, or salary data.
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56. The method of claim 55 , wherein said at least one attribute includes a name, a residence or business address, a telephone number, an electronic mail address, education data, past employer data, or salary data. 59. The method of claim 56 , wherein the past employer data includes an employer name, a last title, and a period of employment.
| 0.536232 |
8,935,192 | 5 | 6 |
5. The method of claim 1 , further comprising: receiving a question from an asker; receiving an answer for the question from an answerer; identifying an entity in the answer; determining an interactive link to a resource, of an affiliate, from which the entity can be obtained; and providing to the asker the interactive link with the answer.
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5. The method of claim 1 , further comprising: receiving a question from an asker; receiving an answer for the question from an answerer; identifying an entity in the answer; determining an interactive link to a resource, of an affiliate, from which the entity can be obtained; and providing to the asker the interactive link with the answer. 6. The method of claim 5 , wherein identifying the entity in the answer further comprises using a trained classifier to determine if the answer refers to an entity.
| 0.5 |
8,386,410 | 1 | 8 |
1. An enterprise administration system comprising: a user interface module that uses a hardware processor for entering administration query terms or selecting a predetermined script of administration query terms; a knowledge base that stores system information; a meta information module that uses the system information to store entity-objective indexes that comprise meta information for at least one entity, wherein an entity comprises one or more of a logical device and a physical device; and a workflow mapping module that maps the administration query terms to system information extraction tasks to extract relevant entities and objectives and applies a rule to the extracted entities and objectives for presenting the extracted entities and objectives in a ranked order, wherein the workflow mapping module further creates an abstract dependency tree for logical and physical entities that are relevant to the administration query terms, and applies a degraded recipe on each of the entities in the abstract dependency tree.
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1. An enterprise administration system comprising: a user interface module that uses a hardware processor for entering administration query terms or selecting a predetermined script of administration query terms; a knowledge base that stores system information; a meta information module that uses the system information to store entity-objective indexes that comprise meta information for at least one entity, wherein an entity comprises one or more of a logical device and a physical device; and a workflow mapping module that maps the administration query terms to system information extraction tasks to extract relevant entities and objectives and applies a rule to the extracted entities and objectives for presenting the extracted entities and objectives in a ranked order, wherein the workflow mapping module further creates an abstract dependency tree for logical and physical entities that are relevant to the administration query terms, and applies a degraded recipe on each of the entities in the abstract dependency tree. 8. The system of claim 1 , wherein the ranked order is based on relevancy of the extracted entities and objectives.
| 0.776265 |
8,384,917 | 24 | 25 |
24. The system as claimed in claim 15 , wherein the extraction mechanism includes an optical character recognition system with a confidence measure of a character recognition.
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24. The system as claimed in claim 15 , wherein the extraction mechanism includes an optical character recognition system with a confidence measure of a character recognition. 25. The system as claimed in claim 24 , wherein the optical character recognition system includes a user interface for user input to confirm a character recognition.
| 0.5 |
7,945,563 | 5 | 6 |
5. The method of claim 4 wherein identifying embedded code further comprises: retrieving an identifier associated with the embedded code.
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5. The method of claim 4 wherein identifying embedded code further comprises: retrieving an identifier associated with the embedded code. 6. The method of claim 5 wherein the identifier is a URL of the embedded code.
| 0.5 |
8,024,191 | 15 | 18 |
15. A non-transitory computer-readable medium storing instructions for controlling a computing device to process speech, the instructions comprising: receiving, via a processor, an input speech having at least one pre-vocalic consonant or at least one post-vocalic consonant; generating at least one output lattice that calculates a first score by comparing the input speech to a training model to provide a result; distinguishing between the at least one pre-vocalic consonant and the at least one post-vocalic consonant in the input speech; calculating a second score by measuring a similarity between the at least one pre-vocalic consonant or the at least one post-vocalic consonant in the input speech and the first score; determining at least one category for at least one pre-vocalic match or mismatch or at least one post-vocalic match or mismatch by using the second score; and refining the results of the an automated speech recognition system by using the at least one category for at least one pre-vocalic match or mismatch or at least one post-vocalic match or mismatch.
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15. A non-transitory computer-readable medium storing instructions for controlling a computing device to process speech, the instructions comprising: receiving, via a processor, an input speech having at least one pre-vocalic consonant or at least one post-vocalic consonant; generating at least one output lattice that calculates a first score by comparing the input speech to a training model to provide a result; distinguishing between the at least one pre-vocalic consonant and the at least one post-vocalic consonant in the input speech; calculating a second score by measuring a similarity between the at least one pre-vocalic consonant or the at least one post-vocalic consonant in the input speech and the first score; determining at least one category for at least one pre-vocalic match or mismatch or at least one post-vocalic match or mismatch by using the second score; and refining the results of the an automated speech recognition system by using the at least one category for at least one pre-vocalic match or mismatch or at least one post-vocalic match or mismatch. 18. The non-transitory computer-readable medium of claim 15 , wherein if there is a mismatch between the second output lattice and the second score, a word probability is decreased.
| 0.686851 |
9,920,855 | 1 | 2 |
1. A system, comprising: a process line comprising a valve assembly; 4-20 analog instrumentation wiring coupled to the valve assembly to exchange signals; a computing device coupled with the 4-20 analog instrumentation wiring, the computing device generating signals to manage operation of the valve assembly; a network coupled with the computing device; and a terminal coupled with the network, the terminal having a display with a Web-based user interface, wherein the computing device comprises, a processor; a memory coupled with the processor, the memory having executable instructions stored thereon that are configured to be accessed and executed by the processor, the executable instructions comprising instructions for implementing an architecture comprising a first architecture layer and a second architecture layer, which is different from the first architecture layer, wherein the first architecture layer is configured to exchange data in a first format that allows communication between the computing device and the valve assembly, the data relating to an operating variable for the valve assembly on the process line, wherein the second architecture layer is configured to exchange data in a second format with the network, wherein the second format is different from the first format, and wherein the second format utilizes a JavaScript Object Notation (JSON) format, and wherein the data in JSON format transits the network to change the Web-based user interface on the display to correspond with real-time operation of the valve assembly.
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1. A system, comprising: a process line comprising a valve assembly; 4-20 analog instrumentation wiring coupled to the valve assembly to exchange signals; a computing device coupled with the 4-20 analog instrumentation wiring, the computing device generating signals to manage operation of the valve assembly; a network coupled with the computing device; and a terminal coupled with the network, the terminal having a display with a Web-based user interface, wherein the computing device comprises, a processor; a memory coupled with the processor, the memory having executable instructions stored thereon that are configured to be accessed and executed by the processor, the executable instructions comprising instructions for implementing an architecture comprising a first architecture layer and a second architecture layer, which is different from the first architecture layer, wherein the first architecture layer is configured to exchange data in a first format that allows communication between the computing device and the valve assembly, the data relating to an operating variable for the valve assembly on the process line, wherein the second architecture layer is configured to exchange data in a second format with the network, wherein the second format is different from the first format, and wherein the second format utilizes a JavaScript Object Notation (JSON) format, and wherein the data in JSON format transits the network to change the Web-based user interface on the display to correspond with real-time operation of the valve assembly. 2. The system of claim 1 , wherein the architecture is configured to exchange data using a representational state transfer protocol.
| 0.841346 |
10,007,882 | 10 | 12 |
10. The method of claim 9 , wherein said query document and said plurality of additional documents are each associated with a maximum number of most relevant concept vectors M such that the proximity of each document belonging to said plurality of additional documents to said query document is determined by the degree of overlapping of said maximum number of most relevant concept vectors M such that said output module enables displaying said at least a subset of said plurality of said additional documents based, at least in part, on said degree of overlapping.
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10. The method of claim 9 , wherein said query document and said plurality of additional documents are each associated with a maximum number of most relevant concept vectors M such that the proximity of each document belonging to said plurality of additional documents to said query document is determined by the degree of overlapping of said maximum number of most relevant concept vectors M such that said output module enables displaying said at least a subset of said plurality of said additional documents based, at least in part, on said degree of overlapping. 12. The method of claim 10 , wherein said maximum number of most relevant concept vectors M is one hundred.
| 0.836391 |
7,885,844 | 11 | 31 |
11. A computer-implemented method for facilitating performance by task performers of tasks from task requesters, the method comprising: receiving indications of multiple available tasks supplied by task requesters, each of the tasks being available for performance by one or more task performers; and for each of at least one of multiple task performers who are available to perform tasks, obtaining information about prior activities of the task performer that include performing one or more tasks supplied by one or more task requesters; automatically determining one or more attributes of tasks that are appropriate for the task performer based at least in part on the prior activities of the task performer, and identifying one or more of the multiple available tasks for the task performer based at least in part on the identified tasks each having at least one of the determined attributes, the automatic determining being performed by one or more configured computer processors and including weighting at least some of the obtained information about the prior activities of the task performer based on recency of the prior activities, such that a first prior activity of the task performer has a greater impact on the determining than does a second prior activity of the task performer if the first prior activity occurred more recently than the second prior activity; and providing one or more indications of the identified tasks to the task performer as recommendations.
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11. A computer-implemented method for facilitating performance by task performers of tasks from task requesters, the method comprising: receiving indications of multiple available tasks supplied by task requesters, each of the tasks being available for performance by one or more task performers; and for each of at least one of multiple task performers who are available to perform tasks, obtaining information about prior activities of the task performer that include performing one or more tasks supplied by one or more task requesters; automatically determining one or more attributes of tasks that are appropriate for the task performer based at least in part on the prior activities of the task performer, and identifying one or more of the multiple available tasks for the task performer based at least in part on the identified tasks each having at least one of the determined attributes, the automatic determining being performed by one or more configured computer processors and including weighting at least some of the obtained information about the prior activities of the task performer based on recency of the prior activities, such that a first prior activity of the task performer has a greater impact on the determining than does a second prior activity of the task performer if the first prior activity occurred more recently than the second prior activity; and providing one or more indications of the identified tasks to the task performer as recommendations. 31. The method of claim 11 wherein, for each of one or more of the at least one task performers, the providing of the one or more indications of the identified tasks to the task performer is performed in exchange for payment from the task performer and/or from at least one of the task requesters that supplied the identified tasks.
| 0.787179 |
8,849,798 | 7 | 8 |
7. The method of claim 1 , wherein, random sampling is used for sampling query data in the query keyword subset according to the sampled size.
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7. The method of claim 1 , wherein, random sampling is used for sampling query data in the query keyword subset according to the sampled size. 8. The method of claim 7 , wherein, random sampling includes generating a random number and selecting a query keyword in the query keyword subset that is associated with the random number.
| 0.5 |
9,928,555 | 12 | 15 |
12. A method programmed in a non-transitory memory of a device comprising: a. acquiring a plurality of activity feed stories from a game; b. matching the game of a user and additional users using an implementation to account for translation differences in a title of the game, wherein the implementation to account for translation differences comprises a look up table to match a first title in a first language with a second title in a second language; and c. condensing the plurality of activity feed stories into a single activity feed story to be displayed in an activity feed for a user while participating in an activity, wherein a property is set to identify how text appears for the single activity feed story.
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12. A method programmed in a non-transitory memory of a device comprising: a. acquiring a plurality of activity feed stories from a game; b. matching the game of a user and additional users using an implementation to account for translation differences in a title of the game, wherein the implementation to account for translation differences comprises a look up table to match a first title in a first language with a second title in a second language; and c. condensing the plurality of activity feed stories into a single activity feed story to be displayed in an activity feed for a user while participating in an activity, wherein a property is set to identify how text appears for the single activity feed story. 15. The method of claim 12 wherein condensing the plurality of activity feed stories enables a condensed tile space.
| 0.879418 |
8,538,842 | 4 | 5 |
4. The method of claim 3 further comprising the additional step of: calculating, using the at least one computing device, brand economic earnings by applying a charge to the branded profit for capital employed in creating, hosting and maintaining the domain name portfolio.
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4. The method of claim 3 further comprising the additional step of: calculating, using the at least one computing device, brand economic earnings by applying a charge to the branded profit for capital employed in creating, hosting and maintaining the domain name portfolio. 5. The method of claim 4 further comprising the additional step of: calculating, using the at least one computing device, brand earnings, wherein by applying the first role of brand index to the brand economic earnings.
| 0.508969 |
9,910,890 | 1 | 4 |
1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: generating a plurality of synthetic events based upon analyzing a plurality of parent/child hierarchies between a plurality of semi-structured items included in a semi-structured resource, wherein each of the one or more synthetic events corresponds to at least one of the plurality of parent/child hierarchies; creating a structured resource, based upon the plurality of synthetic events, that includes a plurality of structured resource entries, wherein at least one of the plurality of structured resource entries includes a first one of the plurality of semi-structured items, a second one of the plurality of semi-structured items, and at least a selected one of the plurality of synthetic events, wherein the selected synthetic event corresponds to a third one of the plurality of semi-structured items that is a parent entry of the second semi-structured item; and querying the structured resource based upon a question received from a user interface.
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1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: generating a plurality of synthetic events based upon analyzing a plurality of parent/child hierarchies between a plurality of semi-structured items included in a semi-structured resource, wherein each of the one or more synthetic events corresponds to at least one of the plurality of parent/child hierarchies; creating a structured resource, based upon the plurality of synthetic events, that includes a plurality of structured resource entries, wherein at least one of the plurality of structured resource entries includes a first one of the plurality of semi-structured items, a second one of the plurality of semi-structured items, and at least a selected one of the plurality of synthetic events, wherein the selected synthetic event corresponds to a third one of the plurality of semi-structured items that is a parent entry of the second semi-structured item; and querying the structured resource based upon a question received from a user interface. 4. The method of claim 1 wherein the semi-structure resource includes a plurality of lines, the method further comprising: identifying a first one of the plurality of lines that includes a first amount of indentations and the third semi-structured item; identifying a second one of the plurality of lines that includes a second amount of indentations and a fourth one of the plurality of semi-structured items, wherein the second amount of indentations is more than the first amount of indentations; identifying a third one of the plurality of lines that includes a third amount of indentations, the first semi-structured item, and the second semi-structured item, wherein the third amount of indentations is more than the second amount of indentations, and wherein the synthetic event links the third semi-structured item to the fourth semi-structured item; and wherein the at least one of the plurality of structured resource entries associates the third semi-structured resource to the first semi-structured resource.
| 0.5 |
8,694,555 | 1 | 3 |
1. A computer-assisted method of processing a drug information source, the drug information source comprising at least one instance of drug rule content, each instance of drug rule content comprising at least one drug rule, the method comprising: creating a drug rule syntax; detecting at least one instance of drug rule content from a drug information source; and parsing drug rule elements from at least one identified instance of drug rule content into the drug rule syntax, retaining associations between those drug rule elements that form a drug rule, whereby a subset of the drug information source is processed into syntax-parsed drug rules.
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1. A computer-assisted method of processing a drug information source, the drug information source comprising at least one instance of drug rule content, each instance of drug rule content comprising at least one drug rule, the method comprising: creating a drug rule syntax; detecting at least one instance of drug rule content from a drug information source; and parsing drug rule elements from at least one identified instance of drug rule content into the drug rule syntax, retaining associations between those drug rule elements that form a drug rule, whereby a subset of the drug information source is processed into syntax-parsed drug rules. 3. The method of claim 1 wherein the drug rule syntax comprises drug rule syntax elements, each drug rule syntax element corresponding to a subset of a logical proposition.
| 0.5 |
9,195,643 | 1 | 5 |
1. A method of managing data, comprising: generating a model file on a non-transitory computer readable medium containing descriptions of the data, wherein the descriptions of the data in the model file are formatted as a collection of dictionaries, wherein the descriptions of the data are divided into multiple groups that are associated with multiple hierarchical pages, wherein the multiple groups associated with the multiple hierarchical pages are listed in the model file in a flat structure, and wherein a first entry in a first of the multiple hierarchical pages shares an identifier with a second entry in a second of the multiple hierarchical pages; and generating a controller file on the non-transitory computer readable medium that, when executed by a processor, causes the processor to interpret the model file and present the data in the multiple hierarchical pages to a user, wherein the controller file refers to one of the multiple groups in the model file, wherein the controller file is re-used to interpret the multiple groups in the descriptions of the data and present the data in the multiple hierarchical pages, and wherein the controller file is configured to retrieve data associated with the second entry and display at least a portion of the data associated with the second entry on the first of the multiple hierarchical pages.
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1. A method of managing data, comprising: generating a model file on a non-transitory computer readable medium containing descriptions of the data, wherein the descriptions of the data in the model file are formatted as a collection of dictionaries, wherein the descriptions of the data are divided into multiple groups that are associated with multiple hierarchical pages, wherein the multiple groups associated with the multiple hierarchical pages are listed in the model file in a flat structure, and wherein a first entry in a first of the multiple hierarchical pages shares an identifier with a second entry in a second of the multiple hierarchical pages; and generating a controller file on the non-transitory computer readable medium that, when executed by a processor, causes the processor to interpret the model file and present the data in the multiple hierarchical pages to a user, wherein the controller file refers to one of the multiple groups in the model file, wherein the controller file is re-used to interpret the multiple groups in the descriptions of the data and present the data in the multiple hierarchical pages, and wherein the controller file is configured to retrieve data associated with the second entry and display at least a portion of the data associated with the second entry on the first of the multiple hierarchical pages. 5. The method of claim 1 , wherein the multiple hierarchical pages have at least two levels.
| 0.786047 |
8,849,707 | 1 | 6 |
1. A method for facilitating business-to-business personal connections by enhancing Internet search results, the method comprising the machine-implemented steps of: registering one or more selling entities by establishing a selling entity account for each of the one or more selling entities in a business-to-business connectivity service, wherein each of the one or more selling entities corresponds to a single individual associated with one or more companies and wherein each individual is associated with only one selling entity; registering one or more buying entities by establishing a buying entity account for each of the one or more buying entities in a business-to-business connectivity service, wherein each of the one or more buying entities corresponds to a single individual; receiving one or more search query terms from a searching user; determining, based on the one or more search query terms, a first set of search results generated by an Internet search engine that queries the World Wide Web, that are relevant relative to the search query terms; selecting, from the first set, a second set of one or more search results, wherein each search result in the second set is selected in response to a determination that it comprises a Uniform Resource Locator (URL) that has been previously registered in association with at least one selling entity account in the business-to-business connectivity service; ranking the one or more search results in the second set based on at least one of: one or more ratings that are based on input from one or more buying entities or, a filter score that is based on filter criteria specified by a submitter of the search query terms when the submitter of the search query terms is a buying entity; generating, for presentation, seller-specific information for each of the search results that are in the second set of search results, wherein seller-specific information comprises the name of a selling entity, the company associated with each selling entity, and one or both of a product or service that each selling entity is associated with; and presenting seller-specific information in connection with only those search results for which seller-specific information was generated.
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1. A method for facilitating business-to-business personal connections by enhancing Internet search results, the method comprising the machine-implemented steps of: registering one or more selling entities by establishing a selling entity account for each of the one or more selling entities in a business-to-business connectivity service, wherein each of the one or more selling entities corresponds to a single individual associated with one or more companies and wherein each individual is associated with only one selling entity; registering one or more buying entities by establishing a buying entity account for each of the one or more buying entities in a business-to-business connectivity service, wherein each of the one or more buying entities corresponds to a single individual; receiving one or more search query terms from a searching user; determining, based on the one or more search query terms, a first set of search results generated by an Internet search engine that queries the World Wide Web, that are relevant relative to the search query terms; selecting, from the first set, a second set of one or more search results, wherein each search result in the second set is selected in response to a determination that it comprises a Uniform Resource Locator (URL) that has been previously registered in association with at least one selling entity account in the business-to-business connectivity service; ranking the one or more search results in the second set based on at least one of: one or more ratings that are based on input from one or more buying entities or, a filter score that is based on filter criteria specified by a submitter of the search query terms when the submitter of the search query terms is a buying entity; generating, for presentation, seller-specific information for each of the search results that are in the second set of search results, wherein seller-specific information comprises the name of a selling entity, the company associated with each selling entity, and one or both of a product or service that each selling entity is associated with; and presenting seller-specific information in connection with only those search results for which seller-specific information was generated. 6. The method of claim 1 , wherein the step of selecting the second set further comprises: determining a maximum quantity of search results for which seller-specific information can be generated within a specified period of time; selecting, from the first set, no more than the maximum quantity of search results for inclusion in the second set.
| 0.795374 |
9,911,034 | 1 | 2 |
1. A system that transforms a document image into an electronic document, the system comprising: one or more processors; one or more electronic memories; and a hierarchically organized data structure, stored in one or more of the one or more electronic memories, the hierarchically organized data structure comprising a plurality of entries corresponding to one or more natural-language entities selected from among one or more morphemes, words, or phrases encoded as sequences of standard feature symbols, wherein the plurality of entries are associated with a plurality of scores; and computer instructions, digitally encoded and stored in one or more of the one or more electronic memories and executed on the one or more processors, that: receive an image comprising text of a language; identify a subimage within the image, the subimage corresponding to one or more of words and morphemes; identify a set of character-sequences that represent candidate character-sequence representations of the subimage, wherein a character-sequence of the set is identified by traversing a path of the hierarchically organized data structure and accumulating a value for the character-sequence based on the scores on the path, wherein the value for the character-sequence in the set satisfies a predetermined threshold; use the candidate character-sequence representations of the subimage as hypotheses regarding lexical identities of the subimage; construct a portion of an electronic document corresponding to the received image of text using the hypotheses regarding the lexical identities of the subimage; and store the constructed portion of the electronic document in one or more of the one or more electronic memories.
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1. A system that transforms a document image into an electronic document, the system comprising: one or more processors; one or more electronic memories; and a hierarchically organized data structure, stored in one or more of the one or more electronic memories, the hierarchically organized data structure comprising a plurality of entries corresponding to one or more natural-language entities selected from among one or more morphemes, words, or phrases encoded as sequences of standard feature symbols, wherein the plurality of entries are associated with a plurality of scores; and computer instructions, digitally encoded and stored in one or more of the one or more electronic memories and executed on the one or more processors, that: receive an image comprising text of a language; identify a subimage within the image, the subimage corresponding to one or more of words and morphemes; identify a set of character-sequences that represent candidate character-sequence representations of the subimage, wherein a character-sequence of the set is identified by traversing a path of the hierarchically organized data structure and accumulating a value for the character-sequence based on the scores on the path, wherein the value for the character-sequence in the set satisfies a predetermined threshold; use the candidate character-sequence representations of the subimage as hypotheses regarding lexical identities of the subimage; construct a portion of an electronic document corresponding to the received image of text using the hypotheses regarding the lexical identities of the subimage; and store the constructed portion of the electronic document in one or more of the one or more electronic memories. 2. The system of claim 1 wherein the language comprises at least one of Arabic, Persian, Pashto, Urdu, Devanagari, Hindi, Korean, or a Turkish language.
| 0.945007 |
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