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9,948,689 | 11 | 14 | 11. At least one non-transitory, computer readable storage medium having instructions stored thereon, the instructions when executed on a machine cause the machine to: collect information from at least one online community; collect profile information for users of the at least one online community; automatically detect and classify social roles of users of the at least one online community utilizing the collected information; automatically detect the stated and manifested interests of community members; map manifested topics of interest for a user to stated topics of interest; recommend to the user to add to their profile the manifested topics of interest currently not in their preferred stated topics of interest; identify live conversations within the online community and corresponding social roles of users corresponding to the live conversations; send at least one suggestion to the user of the at least one online community, wherein the at least one suggestion includes a suggestion of an online conversation for the user to join, based on an assumed social role of the user and/or a social roles identified as needed for the online community; and send behavioral alerts to users. | 11. At least one non-transitory, computer readable storage medium having instructions stored thereon, the instructions when executed on a machine cause the machine to: collect information from at least one online community; collect profile information for users of the at least one online community; automatically detect and classify social roles of users of the at least one online community utilizing the collected information; automatically detect the stated and manifested interests of community members; map manifested topics of interest for a user to stated topics of interest; recommend to the user to add to their profile the manifested topics of interest currently not in their preferred stated topics of interest; identify live conversations within the online community and corresponding social roles of users corresponding to the live conversations; send at least one suggestion to the user of the at least one online community, wherein the at least one suggestion includes a suggestion of an online conversation for the user to join, based on an assumed social role of the user and/or a social roles identified as needed for the online community; and send behavioral alerts to users. 14. The non-transitory, medium as recited in claim 11 , further comprising instructions to: provide an interactive visual representation of at least one user's online persona; and present data which contributes to the online persona. | 0.77553 |
9,461,945 | 9 | 15 | 9. An apparatus to automate message responses comprising: a message parsing module configured to parse a textual message to determine whether the message comprises a question, the textual message received on a device from a sender, wherein parsing the textual message further comprises determining one or more sentence boundaries of the message and identifying one or more question identifiers; a question determination module configured to determine a question type for the question; and a response presentation module configured to: select, automatically, one of a plurality of graphical response interfaces based on the determined question type; present the selected response interface, the selected response interface comprising a plurality of selectable responses to the question and a custom-response interface for entering a custom response, wherein the selectable responses are associated with the determined question type, the determined question type comprising: a date/time question, wherein the plurality of selectable responses comprises one or more of a date response and a time response based on the one or more question identifiers; a location question, wherein the plurality of selectable responses comprises one or more of an address, a location on a map, and a geographic coordinate based on the one or more question identifiers; and a contact question, wherein the plurality of selectable responses comprises a set of one or more contacts based on the one or more question identifiers; receive user input from the response interface to create a response selection comprising one or more of the selectable response and the customizable response; and send the response selection to the sender using the device. | 9. An apparatus to automate message responses comprising: a message parsing module configured to parse a textual message to determine whether the message comprises a question, the textual message received on a device from a sender, wherein parsing the textual message further comprises determining one or more sentence boundaries of the message and identifying one or more question identifiers; a question determination module configured to determine a question type for the question; and a response presentation module configured to: select, automatically, one of a plurality of graphical response interfaces based on the determined question type; present the selected response interface, the selected response interface comprising a plurality of selectable responses to the question and a custom-response interface for entering a custom response, wherein the selectable responses are associated with the determined question type, the determined question type comprising: a date/time question, wherein the plurality of selectable responses comprises one or more of a date response and a time response based on the one or more question identifiers; a location question, wherein the plurality of selectable responses comprises one or more of an address, a location on a map, and a geographic coordinate based on the one or more question identifiers; and a contact question, wherein the plurality of selectable responses comprises a set of one or more contacts based on the one or more question identifiers; receive user input from the response interface to create a response selection comprising one or more of the selectable response and the customizable response; and send the response selection to the sender using the device. 15. The apparatus of claim 9 , wherein the one or more selectable responses comprise one or more user-configured responses defined for the question type by a user. | 0.639381 |
8,700,300 | 1 | 20 | 1. A computer-implemented method, comprising: receiving, at a computer server system and as having been sent from a computing device that is remote from the server system, a search query; determining, from particular ones of a group of resources and before receiving the search query, geographical indicators for the particular ones of the resources by parsing textual information from the particular ones of the resources; identifying, by the computer server system and in response to receiving the search query, set of search results that correspond to resources of the group of resources from which geographic indicators have been identified; transmitting, by the computer server system and to the computing device, information that characterizes the set of search results for presentation to a user of the computing device; receiving, by the computer server system and as having been sent from the computing device, an indication of a selection that corresponds to a particular result in the set of search results; and providing, by the computer server system, data that is formatted for use by a navigational application to provide directions that have a destination at the specific geographical indicator that corresponds to the particular result. | 1. A computer-implemented method, comprising: receiving, at a computer server system and as having been sent from a computing device that is remote from the server system, a search query; determining, from particular ones of a group of resources and before receiving the search query, geographical indicators for the particular ones of the resources by parsing textual information from the particular ones of the resources; identifying, by the computer server system and in response to receiving the search query, set of search results that correspond to resources of the group of resources from which geographic indicators have been identified; transmitting, by the computer server system and to the computing device, information that characterizes the set of search results for presentation to a user of the computing device; receiving, by the computer server system and as having been sent from the computing device, an indication of a selection that corresponds to a particular result in the set of search results; and providing, by the computer server system, data that is formatted for use by a navigational application to provide directions that have a destination at the specific geographical indicator that corresponds to the particular result. 20. The method of claim 1 , wherein at least one of the particular ones of the resources is a web page. | 0.893154 |
8,577,818 | 1 | 12 | 1. A method comprising: performing on a processor, evaluating log data; determining at least one discrepancy between the log data and a system model; generating a candidate model based on the discrepancy and a model template; and updating the system model based on the candidate model. | 1. A method comprising: performing on a processor, evaluating log data; determining at least one discrepancy between the log data and a system model; generating a candidate model based on the discrepancy and a model template; and updating the system model based on the candidate model. 12. The method according to claim 1 , wherein the model template includes decision threshold definitions. | 0.708333 |
8,176,418 | 1 | 2 | 1. A system for generating a summary of a plurality of documents comprising: a computer processor; a computer readable document collection containing a plurality of related documents stored in electronic form therein; a plurality of forms of multiple document summarization engines including a single event engine, a biography engine and a multi-event engine operating on the computer processor; and a router, the router determining a temporal relationship of at least a subset of the documents in the collection and selecting one of the plurality of forms of multiple document summarization engines for generating a summary of the subset of documents based on the temporal relationship, wherein the router selects the biography engine if the documents in the collection are not generated within a predetermined time period and the number of capitalized words and the number of personal pronouns each exceed a predetermined threshold value. | 1. A system for generating a summary of a plurality of documents comprising: a computer processor; a computer readable document collection containing a plurality of related documents stored in electronic form therein; a plurality of forms of multiple document summarization engines including a single event engine, a biography engine and a multi-event engine operating on the computer processor; and a router, the router determining a temporal relationship of at least a subset of the documents in the collection and selecting one of the plurality of forms of multiple document summarization engines for generating a summary of the subset of documents based on the temporal relationship, wherein the router selects the biography engine if the documents in the collection are not generated within a predetermined time period and the number of capitalized words and the number of personal pronouns each exceed a predetermined threshold value. 2. The system for generating a summary of a plurality of documents of claim 1 , wherein the router selects the single event engine if a predetermined number of documents in the subset of the collection are generated within a predetermined time period. | 0.568729 |
8,074,176 | 1 | 2 | 1. A method for an electronic communications dialog between a plurality of users using digital images via a web portal, comprising the steps of: selecting a template for entering a plurality of words and associated images that constitute an initial electronic message; entering a plurality of words into the template corresponding to the initial electronic message; selecting a plurality of images from a visual dictionary associated with a user of the plurality of users, each of the plurality of images having a direct correspondence with the plurality of words entered into the template such that the plurality of images are configured to convey a message represented by the plurality of words to one or more of the plurality of users, and each of the plurality of images is associated with a definition provided by the user such that each of the plurality of images conveys one or more words based on the definition; inserting each image into the template in a sequence corresponding to the initial electronic message; and sending the initial electronic message containing the sequenced images to at least one other user via the web portal. | 1. A method for an electronic communications dialog between a plurality of users using digital images via a web portal, comprising the steps of: selecting a template for entering a plurality of words and associated images that constitute an initial electronic message; entering a plurality of words into the template corresponding to the initial electronic message; selecting a plurality of images from a visual dictionary associated with a user of the plurality of users, each of the plurality of images having a direct correspondence with the plurality of words entered into the template such that the plurality of images are configured to convey a message represented by the plurality of words to one or more of the plurality of users, and each of the plurality of images is associated with a definition provided by the user such that each of the plurality of images conveys one or more words based on the definition; inserting each image into the template in a sequence corresponding to the initial electronic message; and sending the initial electronic message containing the sequenced images to at least one other user via the web portal. 2. The method for an electronic communications dialog of claim 1 further comprising receiving the initial electronic message containing the sequenced images in lieu of the plurality of words by the at least one user via the web portal. | 0.774904 |
8,775,365 | 1 | 4 | 1. A computer implemented method, comprising an implementation using a portion or whole capacity of one or more non-transitory computer readable media with a set of instructions thereon, executable by one or more processing devices, configured, while being or is executed, for providing an interactive knowledge discovery session to a client comprising: providing, using one or more data processing or computing devices, an interactive environment to obtain the client's input, said input is useable to indicate a body of knowledge composed of ontological subjects and a form of response from a plurality of forms of responses; accessing or building a first one or more data structures corresponding to at least one participation matrix representing participation of a plurality of ontological subjects of a first predefined order into a plurality of partitions or ontological subjects of a second predefined order of said body of knowledge; accessing, or building in real time, a second one or more data structures corresponding to association strengths between a plurality of ontological subjects of a predefined order; wherein said association strength is a function of: i. probability of occurrences of some of the ontological subjects of the first order in partitions or ontological subjects of a predefined order of the body of knowledge, and ii. co-occurrences of some ontological subjects of the first order in some of partitions or ontological subjects of a predefined order; accessing evaluated, or evaluating in real time, value significances for one or more partitions or one or more ontological subjects of the body of knowledge, based on data of one or more of said first and second one or more data structures and in respect to at least one significance aspect of the one or more partitions or one or more ontological subjects of the body of knowledge; providing, using one or more data processing or computing devices, at least one output using one or more partitions and/or one or more ontological subjects of the body of knowledge in response to the client's input, based on the evaluated value significances of the one or more partitions and/or one or more ontological subjects of the body of knowledge and the form of response, and being responsive to further inputs. | 1. A computer implemented method, comprising an implementation using a portion or whole capacity of one or more non-transitory computer readable media with a set of instructions thereon, executable by one or more processing devices, configured, while being or is executed, for providing an interactive knowledge discovery session to a client comprising: providing, using one or more data processing or computing devices, an interactive environment to obtain the client's input, said input is useable to indicate a body of knowledge composed of ontological subjects and a form of response from a plurality of forms of responses; accessing or building a first one or more data structures corresponding to at least one participation matrix representing participation of a plurality of ontological subjects of a first predefined order into a plurality of partitions or ontological subjects of a second predefined order of said body of knowledge; accessing, or building in real time, a second one or more data structures corresponding to association strengths between a plurality of ontological subjects of a predefined order; wherein said association strength is a function of: i. probability of occurrences of some of the ontological subjects of the first order in partitions or ontological subjects of a predefined order of the body of knowledge, and ii. co-occurrences of some ontological subjects of the first order in some of partitions or ontological subjects of a predefined order; accessing evaluated, or evaluating in real time, value significances for one or more partitions or one or more ontological subjects of the body of knowledge, based on data of one or more of said first and second one or more data structures and in respect to at least one significance aspect of the one or more partitions or one or more ontological subjects of the body of knowledge; providing, using one or more data processing or computing devices, at least one output using one or more partitions and/or one or more ontological subjects of the body of knowledge in response to the client's input, based on the evaluated value significances of the one or more partitions and/or one or more ontological subjects of the body of knowledge and the form of response, and being responsive to further inputs. 4. The computer implemented method of claim 1 , wherein the body of knowledge includes the client's input. | 0.956271 |
8,460,103 | 9 | 12 | 9. A mobile hand-held device for use in a casino gaming network, comprising: a gaming controller; memory; a first display; at least one interface configured to communicate with at least one other device in the gaming network; a first gesture input interface device configured to detect movements associated with one or more persons; and a first gesture interpretation component configured to identify selected movements detected by the first gesture input interface device, and configured to generate gesture interpretation information relating to interpretation of the selected movements; wherein the hand-held device is configured to: control a wager-based game provided by the hand-held device, determine a current location of the hand-held device, select a hand-held device operating mode from a plurality of operating modes corresponding to different types of gaming activities provided in different locations based on the current location of the hand-held device, detect a first gesture by a first player participating in a first game session with the hand-held device, interpret the first gesture based on the selected operating mode and with respect to a first set of criteria, identify at least one first action to be initiated in response to the first gesture interpretation, initiate the at least one first action, and present a game interface on the first display, wherein the game interface is configured to facilitate interaction with the wager-based game by the first player. | 9. A mobile hand-held device for use in a casino gaming network, comprising: a gaming controller; memory; a first display; at least one interface configured to communicate with at least one other device in the gaming network; a first gesture input interface device configured to detect movements associated with one or more persons; and a first gesture interpretation component configured to identify selected movements detected by the first gesture input interface device, and configured to generate gesture interpretation information relating to interpretation of the selected movements; wherein the hand-held device is configured to: control a wager-based game provided by the hand-held device, determine a current location of the hand-held device, select a hand-held device operating mode from a plurality of operating modes corresponding to different types of gaming activities provided in different locations based on the current location of the hand-held device, detect a first gesture by a first player participating in a first game session with the hand-held device, interpret the first gesture based on the selected operating mode and with respect to a first set of criteria, identify at least one first action to be initiated in response to the first gesture interpretation, initiate the at least one first action, and present a game interface on the first display, wherein the game interface is configured to facilitate interaction with the wager-based game by the first player. 12. The hand-held device of claim 9 , wherein the hand-held device is further configured to: determine a current location of the hand-held device, and interpret the first gesture based on the current location of the hand-held device. | 0.815372 |
9,720,899 | 27 | 29 | 27. The method of claim 15 , wherein the defined and selected communication goal data structure is the evaluate status communication goal data structure, and wherein the narrative analytics model for the content block data structure associated therewith specifies data and algorithms for comparing the value for the subject metric against the reference. | 27. The method of claim 15 , wherein the defined and selected communication goal data structure is the evaluate status communication goal data structure, and wherein the narrative analytics model for the content block data structure associated therewith specifies data and algorithms for comparing the value for the subject metric against the reference. 29. The method of claim 27 wherein the reference is a threshold or the subject metric of a peer. | 0.756345 |
8,769,695 | 1 | 10 | 1. A system comprising: a processor for execution of a threat detection application for determining the probability that a current website link is associated with fraudulent activity; a communication device associated with the processor for receiving a website link; and a database associated with the processor, the database comprising: a plurality of different keyword combinations that have been identified in previously received website links received at a time prior to a time the current website link was received, where each of the keyword combinations comprises at least two distinct keywords; and for each of the different keyword combinations, a total count number representing a number of instances a previously received website link, received at a time prior to a time the current website link was received and containing the respective keyword combination, has been received by the system, a threat number representing a number of instances the previously received website link, received at a time prior to a time the current website link was received and containing the respective keyword combination, was associated with fraudulent activity, and a non-threat number representing a number of instances the previously received website link, received at a time prior to a time the current website link was received and not containing the respective keyword combination, was not associated with fraudulent activity; wherein the threat detection application executed by the processor is configured to: receive at least one current website link; review each current website link received by the system to determine that none of the plurality of keyword combinations exactly match words included in the current website link under review; in response to determining that none of the plurality of the keyword combinations exactly match words included in the current website link, review each previously received website link to identify each of the pluralities of the keyword combinations, from the database, that include at least one keyword that matches at least one word in the current website link, thereby indicating keyword combinations that partially match the current website link; for each of the keyword combinations that partially matches the current website link, retrieve, from the database, the plurality of threat numbers and/or for each of the keyword combinations that does not match the current website link, retrieve, from the database, and the plurality of non-threat numbers, update the threat numbers and/or the non-threat numbers by an increment of one; retrieve, from the database, the plurality of total count numbers from each of the different keyword combinations, update the total count numbers by an increment of one; divide the total threat number by the total count number from each of the different keyword combination, thereby resulting in a probability of threat of the current website link; and/or divide the total non-threat number by the total count number, thereby resulting in a probability of non-threat of the current website link; compare the probability of threat to a first threshold and/or compare the probability of non-threat to a second threshold; and based on the comparison, determine that the current website link is a threat if the probability is equaled or greater than the first threshold, non-threat if the probability is equaled or less than the second threshold. | 1. A system comprising: a processor for execution of a threat detection application for determining the probability that a current website link is associated with fraudulent activity; a communication device associated with the processor for receiving a website link; and a database associated with the processor, the database comprising: a plurality of different keyword combinations that have been identified in previously received website links received at a time prior to a time the current website link was received, where each of the keyword combinations comprises at least two distinct keywords; and for each of the different keyword combinations, a total count number representing a number of instances a previously received website link, received at a time prior to a time the current website link was received and containing the respective keyword combination, has been received by the system, a threat number representing a number of instances the previously received website link, received at a time prior to a time the current website link was received and containing the respective keyword combination, was associated with fraudulent activity, and a non-threat number representing a number of instances the previously received website link, received at a time prior to a time the current website link was received and not containing the respective keyword combination, was not associated with fraudulent activity; wherein the threat detection application executed by the processor is configured to: receive at least one current website link; review each current website link received by the system to determine that none of the plurality of keyword combinations exactly match words included in the current website link under review; in response to determining that none of the plurality of the keyword combinations exactly match words included in the current website link, review each previously received website link to identify each of the pluralities of the keyword combinations, from the database, that include at least one keyword that matches at least one word in the current website link, thereby indicating keyword combinations that partially match the current website link; for each of the keyword combinations that partially matches the current website link, retrieve, from the database, the plurality of threat numbers and/or for each of the keyword combinations that does not match the current website link, retrieve, from the database, and the plurality of non-threat numbers, update the threat numbers and/or the non-threat numbers by an increment of one; retrieve, from the database, the plurality of total count numbers from each of the different keyword combinations, update the total count numbers by an increment of one; divide the total threat number by the total count number from each of the different keyword combination, thereby resulting in a probability of threat of the current website link; and/or divide the total non-threat number by the total count number, thereby resulting in a probability of non-threat of the current website link; compare the probability of threat to a first threshold and/or compare the probability of non-threat to a second threshold; and based on the comparison, determine that the current website link is a threat if the probability is equaled or greater than the first threshold, non-threat if the probability is equaled or less than the second threshold. 10. The system of claim 1 , wherein the threat score is the probability that a website link is associated with fraudulent activity. | 0.5 |
7,869,996 | 11 | 12 | 11. The method of claim 10 , wherein (E)(5) further comprises displaying the transcript to a user only after completion of (E)(4). | 11. The method of claim 10 , wherein (E)(5) further comprises displaying the transcript to a user only after completion of (E)(4). 12. The method of claim 11 , wherein (E)(4) comprises: (E)(4)(a) identifying a word pause within the effective dictation at a time that is within a predetermined threshold of the second time of the second partial audio stream; and (E)(4)(b) writing the second partial audio stream into the effective dictation at the time identified in (E)(4)(a). | 0.5 |
9,953,329 | 1 | 6 | 1. A method comprising: providing search results in a first dedicated screen space of a user interface and associated with a first collection based on at least one search term, and which excludes search results associated with any of one or more second collections; providing a separate customizable preview of search results based on the at least one search term in a separate pane located in a second dedicated screen space of the user interface and associated with at least one second collection which is different from the first collection; and providing options to a user to customize the second dedicated space and the separate pane through an editing settings link in the user interface that is configured to provide customization controls which: allow the user to remove the separate pane in the second dedicated space; order the separate pane with at least one other customizable preview pane in the second dedicated space; and allow the user to add another pane in the second dedicated space which includes the at least one second collection to be any web site that the user inputs through a text editable box in an add sidebar module, wherein the first collection is a first category of information for the at least one search term and the at least one second collection includes a second category of information for the at least one search term which is different from the first category of information. | 1. A method comprising: providing search results in a first dedicated screen space of a user interface and associated with a first collection based on at least one search term, and which excludes search results associated with any of one or more second collections; providing a separate customizable preview of search results based on the at least one search term in a separate pane located in a second dedicated screen space of the user interface and associated with at least one second collection which is different from the first collection; and providing options to a user to customize the second dedicated space and the separate pane through an editing settings link in the user interface that is configured to provide customization controls which: allow the user to remove the separate pane in the second dedicated space; order the separate pane with at least one other customizable preview pane in the second dedicated space; and allow the user to add another pane in the second dedicated space which includes the at least one second collection to be any web site that the user inputs through a text editable box in an add sidebar module, wherein the first collection is a first category of information for the at least one search term and the at least one second collection includes a second category of information for the at least one search term which is different from the first category of information. 6. The method of claim 1 , wherein a service provider at least one of supports, maintains, deploys and creates a computer infrastructure operable to perform the steps of claim 1 . | 0.841593 |
7,831,582 | 65 | 68 | 65. The system as recited in claim 64 , wherein each keyword associated with said particular online content source includes a respective keyword weight corresponding to said particular online content source, wherein said respective keyword weight indicates a strength of association of a corresponding keyword to said particular online content source. | 65. The system as recited in claim 64 , wherein each keyword associated with said particular online content source includes a respective keyword weight corresponding to said particular online content source, wherein said respective keyword weight indicates a strength of association of a corresponding keyword to said particular online content source. 68. The system as recited in claim 65 , wherein for each online content source included in said given aggregate path, said search engine is further configured to determine a respective content source search rank weight as a function of those keyword weights associated with said included online content source that correspond to respective keywords included in said keyword query. | 0.615385 |
8,781,863 | 19 | 20 | 19. A computerized vehicle insurance auditing system comprising: a processor coupled to a nontransitory computer readable storage medium having stored therein software instructions that, when executed by the processor, cause the processor to perform a series of operations including: receiving, via the processor, a data file comprising one or more auditable items, each auditable item being a line item from an insurance claim file, each auditable item comprising a word string having one or more words; translating, using the processor, each word string for each auditable item using one or more translation steps into a translated item description; associating, using the processor, each translated item description with an item identifier; and using the processor, automatically determining whether to accept or reject each auditable item based on the item identifier and one or more rules associated with the data file. | 19. A computerized vehicle insurance auditing system comprising: a processor coupled to a nontransitory computer readable storage medium having stored therein software instructions that, when executed by the processor, cause the processor to perform a series of operations including: receiving, via the processor, a data file comprising one or more auditable items, each auditable item being a line item from an insurance claim file, each auditable item comprising a word string having one or more words; translating, using the processor, each word string for each auditable item using one or more translation steps into a translated item description; associating, using the processor, each translated item description with an item identifier; and using the processor, automatically determining whether to accept or reject each auditable item based on the item identifier and one or more rules associated with the data file. 20. The system of claim 19 , wherein the insurance claim file includes a demand for subrogation. | 0.5 |
8,572,511 | 1 | 9 | 1. A non-transitory computer readable medium including a sequence of instructions stored thereon for causing a computer to execute a method, comprising: generating a search term entry area operable to allow a user to enter text as a search term; generating a hierarchical tree area operable to display data elements in a multi-level hierarchical tree structure, wherein the data elements are representative of searchable data in a database; generating a search result area operable to display a result of a search query; and generating a search criteria tree area operable to allow a user to enter a new search query of the searchable data in response to the user's selection of one or more of the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area, wherein the search criteria tree area enables the user to select the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area for the new search query, and wherein the search term entry area, hierarchical tree area, search results area, and search criteria tree area are displayed together in a single window on a graphical user interface. | 1. A non-transitory computer readable medium including a sequence of instructions stored thereon for causing a computer to execute a method, comprising: generating a search term entry area operable to allow a user to enter text as a search term; generating a hierarchical tree area operable to display data elements in a multi-level hierarchical tree structure, wherein the data elements are representative of searchable data in a database; generating a search result area operable to display a result of a search query; and generating a search criteria tree area operable to allow a user to enter a new search query of the searchable data in response to the user's selection of one or more of the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area, wherein the search criteria tree area enables the user to select the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area for the new search query, and wherein the search term entry area, hierarchical tree area, search results area, and search criteria tree area are displayed together in a single window on a graphical user interface. 9. The non-transitory computer readable medium of claim 1 , wherein the method further comprises generating a second window that appears in response to a user's selection of one of the data elements from the hierarchical tree area and the result from the search results area, wherein the second window displays additional information about the one of the data elements and the result. | 0.582609 |
6,065,295 | 1 | 2 | 1. A cryogenic refrigerator for producing temperatures within a given low temperature range, said refrigerator including a single-stage cold head and a regenerator operatively connected to said cold head, said regenerator having at least two layers of different materials through which a working fluid is circulated, said materials being selected so that the cold head has an optimum refrigerating capacity between 15K and 80K, wherein said regenerator contains a first layer of bronze mesh material on the warm side of the regenerator and a second layer of lead material on the cold side of the regenerator. | 1. A cryogenic refrigerator for producing temperatures within a given low temperature range, said refrigerator including a single-stage cold head and a regenerator operatively connected to said cold head, said regenerator having at least two layers of different materials through which a working fluid is circulated, said materials being selected so that the cold head has an optimum refrigerating capacity between 15K and 80K, wherein said regenerator contains a first layer of bronze mesh material on the warm side of the regenerator and a second layer of lead material on the cold side of the regenerator. 2. The refrigerator of claim 1 wherein said regenerator has three layers of differing materials that include a first layer of bronze mesh located on the warm side of the regenerator extending along about two to three sevenths of the regenerators total length, a second layer adjacent the first layer of bronze mesh having a mesh size that is smaller than that of said first layer extending along about two to three sevenths of the regenerators total length and a third layer of lead spheres or sintered lead material extending along about one to two sevenths of the regenerators total length. | 0.566618 |
9,689,682 | 14 | 20 | 14. A system for automatically ascertaining a geographic location, the system comprising: a digital camera configured to capture an image of at least a portion of sky visible upward from the geographic location; a memory storing a plurality of digital sky light scattering models, each sky light scattering model characterizing light, as the light would appear from a corresponding candidate geographic location after the light was emitted by at least one light source disposed proximate the candidate geographic location and subsequently scattered by particulates disposed in an atmosphere proximate the at least one light source, wherein each sky light scattering model is associated with the corresponding candidate geographic location; a search engine executed by a processor and configured to search the plurality of sky light scattering models in the memory for a matching sky light scattering model that matches the image within a match criterion; and a port configured to automatically, to at least one of: a display panel, a map selector, a guidance system, a navigation system and/or a control system, the candidate geographic location associated with the matching sky light scattering model as the ascertained geographic location as a result of the searching, the matching sky light scattering model is found. | 14. A system for automatically ascertaining a geographic location, the system comprising: a digital camera configured to capture an image of at least a portion of sky visible upward from the geographic location; a memory storing a plurality of digital sky light scattering models, each sky light scattering model characterizing light, as the light would appear from a corresponding candidate geographic location after the light was emitted by at least one light source disposed proximate the candidate geographic location and subsequently scattered by particulates disposed in an atmosphere proximate the at least one light source, wherein each sky light scattering model is associated with the corresponding candidate geographic location; a search engine executed by a processor and configured to search the plurality of sky light scattering models in the memory for a matching sky light scattering model that matches the image within a match criterion; and a port configured to automatically, to at least one of: a display panel, a map selector, a guidance system, a navigation system and/or a control system, the candidate geographic location associated with the matching sky light scattering model as the ascertained geographic location as a result of the searching, the matching sky light scattering model is found. 20. The system according to claim 14 , further comprising: a compass, wherein the search engine is configured to automatically adjust the image or at least some of the plurality of sky light scattering models according to a reading from the compass. | 0.77847 |
9,633,483 | 17 | 19 | 17. A computer program product for filtering, segmenting and recognizing objects, the computer program product comprising: a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions by one or more processors, the one or more processors perform operations of: down sampling a three-dimensional (3D) point cloud having a plurality of data points in 3D space to generate a down-sampled 3D point cloud P with reduced data points in the 3D space; identifying and removing a ground plane in the down-sampled 3D point cloud to leave non-ground data points in the down-sampled 3D point cloud; generating a set of 3D candidate blobs by clustering the non-ground data points to generate a plurality of 3D blobs, each of the 3D blobs having a cluster size; extracting features from each 3D candidate blob, the features being vectors that represent morphological characteristics of each 3D candidate blob; and classifying at least one of the 3D candidate blobs as a pre-defined object class based on the extracted features by assigning a semantic meaning to a segmented real-world individual object. | 17. A computer program product for filtering, segmenting and recognizing objects, the computer program product comprising: a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions by one or more processors, the one or more processors perform operations of: down sampling a three-dimensional (3D) point cloud having a plurality of data points in 3D space to generate a down-sampled 3D point cloud P with reduced data points in the 3D space; identifying and removing a ground plane in the down-sampled 3D point cloud to leave non-ground data points in the down-sampled 3D point cloud; generating a set of 3D candidate blobs by clustering the non-ground data points to generate a plurality of 3D blobs, each of the 3D blobs having a cluster size; extracting features from each 3D candidate blob, the features being vectors that represent morphological characteristics of each 3D candidate blob; and classifying at least one of the 3D candidate blobs as a pre-defined object class based on the extracted features by assigning a semantic meaning to a segmented real-world individual object. 19. The computer program product as set forth in claim 17 , wherein the 3D point cloud is down sampled using a 3D voxel grid having a plurality of voxels, where the 3D voxel grid is positioned over the 3D point cloud such that all the data points in each voxel are down-sampled to a centroid for each voxel. | 0.81326 |
9,043,339 | 3 | 5 | 3. The computer-implemented system according to claim 1 , wherein: the first extraction unit uses the first text processing information to extract the noun word from the document data by performing a morphological analysis on the document data to extract noun words (Ki (i=1, 2, . . . , n)); and the first extract unit further assigns, to each of the extracted noun words Ki, a weight corresponding to at least one of a position and a proportion of the noun word Ki in the document data. | 3. The computer-implemented system according to claim 1 , wherein: the first extraction unit uses the first text processing information to extract the noun word from the document data by performing a morphological analysis on the document data to extract noun words (Ki (i=1, 2, . . . , n)); and the first extract unit further assigns, to each of the extracted noun words Ki, a weight corresponding to at least one of a position and a proportion of the noun word Ki in the document data. 5. The computer-implemented system according to claim 3 , wherein: when the position of the noun word Ki is not in a sentence, a determination is made as to whether or not the noun word Ki takes up the entire text segment; when the noun word Ki takes up the entire text segment, a score W is assigned to the noun word Ki; when the noun word Ki does not take up the entire text segment, a score Y is assigned to the noun word Ki; when the position of the noun word Ki is in a sentence, a determination is made as to whether or not the noun word Ki is in a parenthesis in the sentence and takes up the entire character string in the parenthesis; when the noun word Ki is in the parenthesis and takes up the entire character string in the parenthesis, a score X is assigned to the noun word Ki; and when the noun word Ki is not in a parenthesis or does not take up the entire character string, a score Z is assigned to the noun word Ki, wherein score W is greater than score X, score X is greater than score Y, and score Y is greater than score Z. | 0.5 |
9,690,446 | 34 | 35 | 34. The non-transitory computer readable storage medium of claim 32 , wherein the second gesture is a swipe gesture. | 34. The non-transitory computer readable storage medium of claim 32 , wherein the second gesture is a swipe gesture. 35. The non-transitory computer readable storage medium of claim 34 , wherein the second gesture is an upward swipe gesture and the scroll is a one-dimensional vertical scroll. | 0.677656 |
9,098,493 | 5 | 7 | 5. The computer implemented method of claim 4 wherein the step of detecting further includes detecting a third sign after the second sign and further including comparing the first sign and the third sign to the second sign to determine the accuracy of the second sign to the second gesture. | 5. The computer implemented method of claim 4 wherein the step of detecting further includes detecting a third sign after the second sign and further including comparing the first sign and the third sign to the second sign to determine the accuracy of the second sign to the second gesture. 7. The computer implemented method of claim 5 further including acquiring user demographic information and further including comparing each match with the user demographic information to verify the accuracy of the match. | 0.5 |
9,720,984 | 15 | 16 | 15. One or more non-transitory computer readable storage media embodying logic that is operable when executed by one or more processors to: receive a visualization request relating to information stored in an ontology; parse the visualization request to generate a search query; submit the search query to the ontology, wherein the ontology is dynamically created to store retrieved data that is collected from a data source; perform data mitigation to process the retrieved data to detect and resolve conflicts among classified tokens provided by data agent, wherein the data mitigation uses quality score, trust score, and rate of decay for the data source; receive, in response to the query, a result comprising a plurality of instances associated with the classified tokens and a plurality of relationships between the instances; and generate a visual representation of the result using visualization rules stored in a memory, the visualization rules comprising level of detail rules, reduction rules, and rewriting rules, wherein generating the visual representation of the result using the visualization rules comprises: identifying a relationship between a first instance and a second instance from the plurality of instances within the result; removing the relationship between the first instance and the second instance from the results; and removing the first instance from the results when the first instance has no relationships with any other instances from the plurality of instances. | 15. One or more non-transitory computer readable storage media embodying logic that is operable when executed by one or more processors to: receive a visualization request relating to information stored in an ontology; parse the visualization request to generate a search query; submit the search query to the ontology, wherein the ontology is dynamically created to store retrieved data that is collected from a data source; perform data mitigation to process the retrieved data to detect and resolve conflicts among classified tokens provided by data agent, wherein the data mitigation uses quality score, trust score, and rate of decay for the data source; receive, in response to the query, a result comprising a plurality of instances associated with the classified tokens and a plurality of relationships between the instances; and generate a visual representation of the result using visualization rules stored in a memory, the visualization rules comprising level of detail rules, reduction rules, and rewriting rules, wherein generating the visual representation of the result using the visualization rules comprises: identifying a relationship between a first instance and a second instance from the plurality of instances within the result; removing the relationship between the first instance and the second instance from the results; and removing the first instance from the results when the first instance has no relationships with any other instances from the plurality of instances. 16. The storage media of claim 15 , wherein parsing the visualization request to generate the search query comprises reducing the scope of the search query based on the visualization rules. | 0.677474 |
7,801,912 | 25 | 26 | 25. The system as recited in claim 1 , wherein the plurality of nodes is distributed among two or more data centers. | 25. The system as recited in claim 1 , wherein the plurality of nodes is distributed among two or more data centers. 26. The system as recited in claim 25 , wherein the data centers are geographically dispersed. | 0.921273 |
9,305,278 | 5 | 6 | 5. A method of operating an access computing system under control of a first entity comprising: configuring a first access server computing system and a first database coupled to said first access server under control of said first entity; using said first access computing system to access a set of records maintained by a target computing system in a second database over an internet based network, said second database being configured and controlled by a second entity to respond to a user query for said records over said network using a first query protocol presented in a first browser interface which restricts access to no more than one record at one time in response to a single query parameter specified by a user; wherein said first access computing system accesses said target computing system through an Internet browser interface based on emulating a user providing said user query, including by automatically passing a plurality of single locator identifier parameters to said first query protocol sequentially in time to retrieve a corresponding plurality of records in said set of records; automatically generating a prioritized schedule with said first access computing system identifying an ordering for accessing said set of records, which prioritized schedule is based in part on both the following operations: a) processing and identifying a likelihood of new data appearing within said set of records based on historical analysis of data change patterns in said records in said database including computed correlations of occurrence and timing between distinct successive events in such records; b) processing and identifying a likelihood of user interest in selected ones of said set of records based on historical analysis of user access, including other users of the access computing system, to such set of records; wherein said plurality of records are retrieved one at a time automatically by said first access computing system in accordance with said prioritized schedule; storing said set of records in said first database; providing a second query protocol presented in a second browser interface to make said set of records accessible at said first access server computing system; wherein said second query protocol permits multiple records to be retrieved and presented in response to a single query presented to said first access server computing system; automatically updating said first database in response to changes in said second database in accordance with said priority schedule on a periodic basis. | 5. A method of operating an access computing system under control of a first entity comprising: configuring a first access server computing system and a first database coupled to said first access server under control of said first entity; using said first access computing system to access a set of records maintained by a target computing system in a second database over an internet based network, said second database being configured and controlled by a second entity to respond to a user query for said records over said network using a first query protocol presented in a first browser interface which restricts access to no more than one record at one time in response to a single query parameter specified by a user; wherein said first access computing system accesses said target computing system through an Internet browser interface based on emulating a user providing said user query, including by automatically passing a plurality of single locator identifier parameters to said first query protocol sequentially in time to retrieve a corresponding plurality of records in said set of records; automatically generating a prioritized schedule with said first access computing system identifying an ordering for accessing said set of records, which prioritized schedule is based in part on both the following operations: a) processing and identifying a likelihood of new data appearing within said set of records based on historical analysis of data change patterns in said records in said database including computed correlations of occurrence and timing between distinct successive events in such records; b) processing and identifying a likelihood of user interest in selected ones of said set of records based on historical analysis of user access, including other users of the access computing system, to such set of records; wherein said plurality of records are retrieved one at a time automatically by said first access computing system in accordance with said prioritized schedule; storing said set of records in said first database; providing a second query protocol presented in a second browser interface to make said set of records accessible at said first access server computing system; wherein said second query protocol permits multiple records to be retrieved and presented in response to a single query presented to said first access server computing system; automatically updating said first database in response to changes in said second database in accordance with said priority schedule on a periodic basis. 6. The method of claim 5 wherein said periodic basis is at least daily and said updating occurs in periods during which said target computing system is determined to have a lesser processing load. | 0.70303 |
6,061,652 | 16 | 18 | 16. The speech recognition apparatus according to claim 11, wherein, when the membership degree vector corresponding to a frame t of the input pattern is defined as a.sub.t =(a.sub.t1, . . . ,a.sub.tM), the membership degree vector corresponding to a frame j of the reference pattern is defined as b.sub.j =(b.sub.j1, . . . ,b.sub.jM), a k-th (t,j) coordinate on the matching path is defined as x(k)=(t(k),j(k)) and a weighting coefficient at x(k) is defined as w(x(k)), the similarity degree calculating means for calculating the distance or the similarity degree specifies the similarity degree of a.sub.t(k) and b.sub.j(k) as follows, ##EQU81## and the similarity degree of vector series a.sub.t(1), . . . ,a.sub.t(K) and b.sub.j(1), . . . ,b.sub.j(K) along the path is specified as follows, ##EQU82## where for 1.ltoreq.n.ltoreq.k-1, if j(k)-j(k-n)=1, w(x(k-n+1))+ . . .+w(x(k))=1. | 16. The speech recognition apparatus according to claim 11, wherein, when the membership degree vector corresponding to a frame t of the input pattern is defined as a.sub.t =(a.sub.t1, . . . ,a.sub.tM), the membership degree vector corresponding to a frame j of the reference pattern is defined as b.sub.j =(b.sub.j1, . . . ,b.sub.jM), a k-th (t,j) coordinate on the matching path is defined as x(k)=(t(k),j(k)) and a weighting coefficient at x(k) is defined as w(x(k)), the similarity degree calculating means for calculating the distance or the similarity degree specifies the similarity degree of a.sub.t(k) and b.sub.j(k) as follows, ##EQU81## and the similarity degree of vector series a.sub.t(1), . . . ,a.sub.t(K) and b.sub.j(1), . . . ,b.sub.j(K) along the path is specified as follows, ##EQU82## where for 1.ltoreq.n.ltoreq.k-1, if j(k)-j(k-n)=1, w(x(k-n+1))+ . . .+w(x(k))=1. 18. The speech recognition apparatus according to claim 16, wherein for x(k)=(t,j), k-1.gtoreq.n.gtoreq.1, the matching path includes either of (1) x(k-1)=(t-n,j-1) or x(k-1)=(t,j-1), (2) x(k-1)=(t-1,j-1) or x(k-1)=(t,j-1), x(k-m)=(t-m,k-1) for m=2, . . . ,n, (3) x(k-m)=(t-m,j),x(k-n)=(t-n,j-1) for m=, . . . ,n-1, (4) x(k-m)=(t-m,j), x(k-n)=(t-n,j-1) for m=1, . . . ,n-1 and (5) x(k-1)=(t-1,j-1) or x(k-1)=(t,j-1), x(k-m)=(t-m,j-1) for m=2, . . . ,n and w(x(k))=1 for the path(1), w(x(k))=1, w(x(k-m+1))=0 for the path(2), w(x(k-m+1))=0, w(x(k-n+1))=1 for the path(3) and w(x(k-m+1))=1/n for the paths (4) and (5). | 0.5 |
8,345,966 | 8 | 10 | 8. The method of claim 4 , wherein the labeling produces a label for the each pixel, and the smoothing further comprises: obtaining the label for the each pixel in the image; and using the label for the each pixel in determining a smoothing filter to be used for the each pixel in the image. | 8. The method of claim 4 , wherein the labeling produces a label for the each pixel, and the smoothing further comprises: obtaining the label for the each pixel in the image; and using the label for the each pixel in determining a smoothing filter to be used for the each pixel in the image. 10. The method of claim 8 , wherein the support of a smoothing filter is largest for pixels labeled uniform and smallest for pixels labeled coarse texture. | 0.562147 |
9,304,657 | 19 | 25 | 19. A storage device having instructions stored thereon that, when executed by a data processing apparatus, cause the data processing apparatus to perform operations comprising: obtaining an audio message associated with one or more image files, wherein the obtaining comprises detecting that a first image file is being displayed on a device associated with a user, determining a first period of time when the first image file is displayed on the device associated with the user, and time stamping the obtained audio message; processing the audio message using speech recognition technology to detect a text component of the audio message; determining one or more textual tags for the one or more image files based on the detected text component, wherein the determining comprises determining a first portion of the detected text component corresponding to the first period of time using the time stamps of the obtained audio message and identifying a first set of the one or more textual tags that were determined based on the first portion of the detected text component; and assigning the one or more textual tags to the one or more image files, wherein the assigning comprises assigning one or more of the textual tags from the first set of the one or more textual tags to the first image file. | 19. A storage device having instructions stored thereon that, when executed by a data processing apparatus, cause the data processing apparatus to perform operations comprising: obtaining an audio message associated with one or more image files, wherein the obtaining comprises detecting that a first image file is being displayed on a device associated with a user, determining a first period of time when the first image file is displayed on the device associated with the user, and time stamping the obtained audio message; processing the audio message using speech recognition technology to detect a text component of the audio message; determining one or more textual tags for the one or more image files based on the detected text component, wherein the determining comprises determining a first portion of the detected text component corresponding to the first period of time using the time stamps of the obtained audio message and identifying a first set of the one or more textual tags that were determined based on the first portion of the detected text component; and assigning the one or more textual tags to the one or more image files, wherein the assigning comprises assigning one or more of the textual tags from the first set of the one or more textual tags to the first image file. 25. The storage device of claim 19 , wherein the one or more image files are digital video files. | 0.875641 |
7,711,573 | 333 | 394 | 333. A method for using a computer to improve a precision ratio when searching a resume database, comprising: receiving a resume in a memory device resident in the computer; parsing the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute, by the computer, a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; storing the resume in the resume database; associating at least one of said at least one skill or experience-related phrase located in the resume with at least one implied skill or experience-related phrase, wherein a term of experience for each said at least one implied skill or experience-related phrase is the term of experience computed for said at least one of said at least one skill or experience-related phrase, and wherein said at least one skill or experience-related phrase and said at least one implied skill or experience-related phrase are searchable phrases in the resume; creating a parsed resume based on the resume, the parsed resume including each searchable phrase in the resume, the term of experience for each searchable phrase, and a relationship between the term of experience and each searchable phrase; storing the parsed resume in the resume database; sending a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and receiving a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. | 333. A method for using a computer to improve a precision ratio when searching a resume database, comprising: receiving a resume in a memory device resident in the computer; parsing the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute, by the computer, a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; storing the resume in the resume database; associating at least one of said at least one skill or experience-related phrase located in the resume with at least one implied skill or experience-related phrase, wherein a term of experience for each said at least one implied skill or experience-related phrase is the term of experience computed for said at least one of said at least one skill or experience-related phrase, and wherein said at least one skill or experience-related phrase and said at least one implied skill or experience-related phrase are searchable phrases in the resume; creating a parsed resume based on the resume, the parsed resume including each searchable phrase in the resume, the term of experience for each searchable phrase, and a relationship between the term of experience and each searchable phrase; storing the parsed resume in the resume database; sending a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and receiving a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. 394. The method of claim 333 , wherein the job description further includes a required salary range comprising a minimum required salary and a maximum required salary, the method further comprising: storing the job description; and sending a portion of the result set, wherein the result set includes at least one matching resume from the resume database, each said at least one matching resume satisfying the job description. | 0.563525 |
9,760,607 | 1 | 2 | 1. A method comprising: receiving, by a server computing device from a client computing device over a network, a network request for a network page; associating, by the server computing device, one of a plurality of user accounts with the network request; retrieving, by the server computing device over the network, the network page from a network page server; calculating, by the server computing device, a plurality of component scores for the network page including a readability score, a word count, and a timeliness score; determining, by the server computing device, a plurality of weights specified by configuration data associated with the user account, each of the plurality of user accounts associated with configuration data; generating, by the server computing device, a quality score for the network page by multiplying the plurality of weights specified by the configuration data associated with the user account to the plurality of component scores; calculating, by the server computing device, a dynamic threshold value as a function of aggregate values of quality scores of a plurality of other network pages; responsive to the quality score falling below the dynamic threshold value, determining, by the server computing device, at least one suggested modification to the network page to improve the quality score based on the plurality of weights specified by the configuration data associated with the user account; encoding, by the server computing device, for rendering by the client computing device a report embodying at least the quality score or the at least one suggested modification; and generating, by the server computing device, search results comprising a list of network pages, wherein the list of network pages is sorted according to respective quality scores associated with the network pages in the list. | 1. A method comprising: receiving, by a server computing device from a client computing device over a network, a network request for a network page; associating, by the server computing device, one of a plurality of user accounts with the network request; retrieving, by the server computing device over the network, the network page from a network page server; calculating, by the server computing device, a plurality of component scores for the network page including a readability score, a word count, and a timeliness score; determining, by the server computing device, a plurality of weights specified by configuration data associated with the user account, each of the plurality of user accounts associated with configuration data; generating, by the server computing device, a quality score for the network page by multiplying the plurality of weights specified by the configuration data associated with the user account to the plurality of component scores; calculating, by the server computing device, a dynamic threshold value as a function of aggregate values of quality scores of a plurality of other network pages; responsive to the quality score falling below the dynamic threshold value, determining, by the server computing device, at least one suggested modification to the network page to improve the quality score based on the plurality of weights specified by the configuration data associated with the user account; encoding, by the server computing device, for rendering by the client computing device a report embodying at least the quality score or the at least one suggested modification; and generating, by the server computing device, search results comprising a list of network pages, wherein the list of network pages is sorted according to respective quality scores associated with the network pages in the list. 2. The method of claim 1 , wherein the configuration data associated with the user account specifies a weight to be applied for a particular language of the network page. | 0.685185 |
8,682,913 | 15 | 20 | 15. A computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: identifying a plurality of source documents including facts associated with a common subject; identifying, from the plurality of source documents, one or more attribute-value pairs associated with the common subject; corroborating a fact, comprising a respective attribute-value pair of the one or more attribute-value pairs associated with the common subject, by determining that the respective attribute-value pair meets one or more predefined corroboration requirements; and in response to corroboration of the fact, updating a status of the respective attribute value pair in a fact repository; wherein corroborating the fact includes: determining that a respective attribute of the respective attribute-value pair meets a first corroboration requirement; and determining that the respective attribute-value pair meets a second corroboration requirement. | 15. A computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: identifying a plurality of source documents including facts associated with a common subject; identifying, from the plurality of source documents, one or more attribute-value pairs associated with the common subject; corroborating a fact, comprising a respective attribute-value pair of the one or more attribute-value pairs associated with the common subject, by determining that the respective attribute-value pair meets one or more predefined corroboration requirements; and in response to corroboration of the fact, updating a status of the respective attribute value pair in a fact repository; wherein corroborating the fact includes: determining that a respective attribute of the respective attribute-value pair meets a first corroboration requirement; and determining that the respective attribute-value pair meets a second corroboration requirement. 20. The computer program product of claim 15 , further comprising reducing the second corroboration requirement with respect to a first attribute-value pair in a source document, when the source document includes at least a second predefined number of other attribute-value pairs meeting the second corroboration requirement. | 0.514925 |
8,457,347 | 13 | 14 | 13. The method, as in claim 10 , further comprising the step of: archiving at least a portion of the event content. | 13. The method, as in claim 10 , further comprising the step of: archiving at least a portion of the event content. 14. The method, as in claim 13 , wherein the step of archiving at least a portion of the event content is initiated based upon the event content. | 0.5 |
9,519,716 | 1 | 3 | 1. A method comprising: receiving, by a computing device, a search query including one or more search terms from a user; generating, based upon the one or more search terms and from tracked user search behavior, by the computing device, a user profile for the user in a data store comprising a plurality of user profiles; establishing, by the computing device, a contextual relationship between the one or more search terms and user profile characteristics associated with each user profile of the plurality of user profiles; parsing, by the computing device, the search query into categorical verticals; determining, by the computing device, search refinement data relative to the categorical verticals, the search refinement data including at least one of: profile information, environmental data relative to the search query and historical behavior data relating to other search queries; accessing, by the computing device, a database of aggregated search data based on the search refinement data, the search data comprising a plurality of query terms and the plurality of user profiles; determining, by the computing device, alternative query terms in the plurality of query terms, the alternative query terms relevant to a set of user profiles in the plurality other than a user's primary profile selected by the user; determining, by the computing device, a most relevant search query from the plurality of search queries and the alternative query terms and a most relevant user profile from the plurality of user profiles, the most relevant user profile based on a plurality of sponsor-purchased public user profiles and both the most relevant search query and the most relevant user profile based on the aggregated search data; refining, by the computing device, the search query based on the most relevant search query and most relevant user profile; and generating, by the computing device, an output display including a search result set based on the refined search query. | 1. A method comprising: receiving, by a computing device, a search query including one or more search terms from a user; generating, based upon the one or more search terms and from tracked user search behavior, by the computing device, a user profile for the user in a data store comprising a plurality of user profiles; establishing, by the computing device, a contextual relationship between the one or more search terms and user profile characteristics associated with each user profile of the plurality of user profiles; parsing, by the computing device, the search query into categorical verticals; determining, by the computing device, search refinement data relative to the categorical verticals, the search refinement data including at least one of: profile information, environmental data relative to the search query and historical behavior data relating to other search queries; accessing, by the computing device, a database of aggregated search data based on the search refinement data, the search data comprising a plurality of query terms and the plurality of user profiles; determining, by the computing device, alternative query terms in the plurality of query terms, the alternative query terms relevant to a set of user profiles in the plurality other than a user's primary profile selected by the user; determining, by the computing device, a most relevant search query from the plurality of search queries and the alternative query terms and a most relevant user profile from the plurality of user profiles, the most relevant user profile based on a plurality of sponsor-purchased public user profiles and both the most relevant search query and the most relevant user profile based on the aggregated search data; refining, by the computing device, the search query based on the most relevant search query and most relevant user profile; and generating, by the computing device, an output display including a search result set based on the refined search query. 3. The method of claim 1 further comprising: conducting a search operation based on the search query; and refining the search query by sorting and selecting the most relevant search results based on the most relevant search query and most relevant user profile. | 0.623919 |
8,930,376 | 18 | 20 | 18. The medium of claim 16 , wherein the step of enabling the processing unit to select one or more fragments from the series of fragments of the web page comprises: enabling the processing unit to determine the measure of similarity between the plurality of bookmarking tags and each fragment in the series of fragments of the web page, wherein the plurality of bookmarking tags is a plurality of social bookmarking tags; enabling the processing unit to calculate a score for each fragment in the series of fragments of the web page based at least in part on the measure of similarity between the plurality of social bookmarking tags and the fragment; and enabling the processing unit to select one or more fragments from the series of fragments of the web page based at least in part on the score associated with each fragment in the series of fragments of the web page. | 18. The medium of claim 16 , wherein the step of enabling the processing unit to select one or more fragments from the series of fragments of the web page comprises: enabling the processing unit to determine the measure of similarity between the plurality of bookmarking tags and each fragment in the series of fragments of the web page, wherein the plurality of bookmarking tags is a plurality of social bookmarking tags; enabling the processing unit to calculate a score for each fragment in the series of fragments of the web page based at least in part on the measure of similarity between the plurality of social bookmarking tags and the fragment; and enabling the processing unit to select one or more fragments from the series of fragments of the web page based at least in part on the score associated with each fragment in the series of fragments of the web page. 20. The medium of claim 18 , wherein the step of enabling the processing unit to determine a measure of similarity between the plurality of social bookmarking tags and each fragment in the series of fragments of the web page comprises: enabling the processing unit to determine a measure of similarity between the plurality of social bookmarking tags associated with the web page and a fragment, wherein each social bookmarking tag in the plurality of social bookmarking tags comprises a text descriptor assigned by one or more users to the web page. | 0.702381 |
8,699,794 | 17 | 19 | 17. The storage medium of claim 16 , the method further comprising: obtaining at least one image of handwritten text; and identifying a plurality of glyph representations of each glyph, as depicted in said at least one image of handwritten text. | 17. The storage medium of claim 16 , the method further comprising: obtaining at least one image of handwritten text; and identifying a plurality of glyph representations of each glyph, as depicted in said at least one image of handwritten text. 19. The storage medium of claim 17 , wherein said at least one geometric variation function is determined based at least in part on said plurality of glyph representations. | 0.836812 |
6,092,035 | 17 | 18 | 17. A server device comprising: a source text input unit for inputting source text data in a predetermined language; a source text analyzing unit that analyzes the source text data by meaning and grammatical significance, the source text analyzing unit generating a plurality of candidates when vagueness in the source text data enables more than one interpretation of the source text data; and an analysis result display unit that automatically displays the plurality of candidates generated by the source text analyzing unit. | 17. A server device comprising: a source text input unit for inputting source text data in a predetermined language; a source text analyzing unit that analyzes the source text data by meaning and grammatical significance, the source text analyzing unit generating a plurality of candidates when vagueness in the source text data enables more than one interpretation of the source text data; and an analysis result display unit that automatically displays the plurality of candidates generated by the source text analyzing unit. 18. A server device an claimed in claim 17, further comprising an analysis result selection unit for selecting a specific one of the plurality of candidates displayed by the analysis result display unit and designating the specific one of the plurality of candidates an an analysis result. | 0.5 |
8,108,370 | 11 | 13 | 11. A system comprising: a memory to store a plurality of classified data patterns for personal identifiers, the plurality of classified data patterns corresponding to variations of personal identifier formats, the personal identifiers including confidential information of a plurality of entities; a processor, coupled to the memory, to: search a text document for data expressed in a format that matches any of the plurality of classified data patterns corresponding to the variations of personal identifier formats, find, in the text document, one or more personal identifier candidates matching any of the plurality of classified data patterns, and validate each of the personal identifier candidates using one or more personal identifier validators to provide accurate detection of the confidential information in the text document. | 11. A system comprising: a memory to store a plurality of classified data patterns for personal identifiers, the plurality of classified data patterns corresponding to variations of personal identifier formats, the personal identifiers including confidential information of a plurality of entities; a processor, coupled to the memory, to: search a text document for data expressed in a format that matches any of the plurality of classified data patterns corresponding to the variations of personal identifier formats, find, in the text document, one or more personal identifier candidates matching any of the plurality of classified data patterns, and validate each of the personal identifier candidates using one or more personal identifier validators to provide accurate detection of the confidential information in the text document. 13. The system of claim 11 wherein the search engine is to perform a search for the plurality of classified data patterns in parallel using a single finite state machine (FSM) and a set of bitmasks, the set of bitmasks comprising bitmasks associated with the plurality of classified data patterns, bitmasks associated with a plurality of transition links of the FSM, the bitmasks identifying classified data patterns that share a relevant transition link, and bitmasks associated with a plurality of nodes of the FSM, each bitmask identifying data patterns exiting at a relevant node. | 0.584046 |
7,487,448 | 11 | 14 | 11. The system of claim 1 , wherein at least some of said additional elements comprise one or more elements that describe how drawing is performed and at least a grouping element that groups other elements. | 11. The system of claim 1 , wherein at least some of said additional elements comprise one or more elements that describe how drawing is performed and at least a grouping element that groups other elements. 14. The system of claim 11 , wherein the grouping element has properties that can be expressed multiple ways. | 0.846045 |
7,797,157 | 2 | 3 | 2. The method of claim 1 wherein forming the statistically derived mapping comprises: accepting a plurality of utterances; measuring statistics from a portion of each of the plurality of utterances; and forming the statistically derived mapping based on a relationship between inputs that each comprise measured statistics from a portion of a single one of the plurality of utterances and outputs that each comprise feature normalization parameters calculated from multiple ones of the plurality of utterances. | 2. The method of claim 1 wherein forming the statistically derived mapping comprises: accepting a plurality of utterances; measuring statistics from a portion of each of the plurality of utterances; and forming the statistically derived mapping based on a relationship between inputs that each comprise measured statistics from a portion of a single one of the plurality of utterances and outputs that each comprise feature normalization parameters calculated from multiple ones of the plurality of utterances. 3. The method of claim 2 wherein the portion of each of the plurality of utterances comprises an initial portion of each of the utterances. | 0.624324 |
9,003,381 | 5 | 6 | 5. The computing device of claim 1 wherein, the browsing context comprises one or more objects adapted for use in a user interface media display. | 5. The computing device of claim 1 wherein, the browsing context comprises one or more objects adapted for use in a user interface media display. 6. The computing device of claim 5 wherein, at least one of the one or more objects comprises a document object model tree. | 0.5 |
5,553,084 | 8 | 11 | 8. An apparatus for decoding a machine-readable symbol representing encoded information, the symbol having symbol characters, a series of repeating characters, and error correction characters derived from the symbol and repeating characters, the apparatus comprising: a sensor that receives light reflected by the symbol and produces an output signal therefore; a receiver that receives the output signal and produces a data signal indicative of at least some of the symbol characters, repeating characters and error correction characters, but which fails to accurately indicate at least some of the symbol and repeating characters; and a processor for processing the data signal and producing a signal indicative of the information encoded in the symbol, the processor being programmed to (i) attempt to decode the symbol, (ii) determine if the symbol has any repeating characters if the symbol cannot be decoded, (iii) locate at least two repeating characters in the symbol, (iv) replace the repeating characters that failed to be accurately indicated in the data signal with accurately indicated repeating characters, and (v) attempt to decode the symbol again alter replacing the repeating character with accurately indicated repeating characters that failed to be indicated in the data signal. | 8. An apparatus for decoding a machine-readable symbol representing encoded information, the symbol having symbol characters, a series of repeating characters, and error correction characters derived from the symbol and repeating characters, the apparatus comprising: a sensor that receives light reflected by the symbol and produces an output signal therefore; a receiver that receives the output signal and produces a data signal indicative of at least some of the symbol characters, repeating characters and error correction characters, but which fails to accurately indicate at least some of the symbol and repeating characters; and a processor for processing the data signal and producing a signal indicative of the information encoded in the symbol, the processor being programmed to (i) attempt to decode the symbol, (ii) determine if the symbol has any repeating characters if the symbol cannot be decoded, (iii) locate at least two repeating characters in the symbol, (iv) replace the repeating characters that failed to be accurately indicated in the data signal with accurately indicated repeating characters, and (v) attempt to decode the symbol again alter replacing the repeating character with accurately indicated repeating characters that failed to be indicated in the data signal. 11. The apparatus of claim 8 wherein the sensor is a movable one-dimensional CCD. | 0.939006 |
8,239,186 | 10 | 12 | 10. A computer-readable storage device having stored thereon instructions, which, when executed by a data processing apparatus, cause the data processing apparatus to perform operations comprising: receiving, at a computing device, one or more words in a first language to be translated to a second language; obtaining, at the computing device, translated text in the second language based on the one or more words, a translation model, and a language model, the translated text being a translation of the one or more words; providing, from the computing device, a graphical user interface (GUI) for display at a display device, the GUI including the one or more words in the first language and the translated text; receiving, at the computing device, user input indicating an alternate translation of the one or more words; analyzing, at the computing device, the user input to determine whether the user input is SPAM; when the user input is not SPAM, updating, at the computing device, the language model and the translation model based on the user input; and when the user input is SPAM, discarding the user input. | 10. A computer-readable storage device having stored thereon instructions, which, when executed by a data processing apparatus, cause the data processing apparatus to perform operations comprising: receiving, at a computing device, one or more words in a first language to be translated to a second language; obtaining, at the computing device, translated text in the second language based on the one or more words, a translation model, and a language model, the translated text being a translation of the one or more words; providing, from the computing device, a graphical user interface (GUI) for display at a display device, the GUI including the one or more words in the first language and the translated text; receiving, at the computing device, user input indicating an alternate translation of the one or more words; analyzing, at the computing device, the user input to determine whether the user input is SPAM; when the user input is not SPAM, updating, at the computing device, the language model and the translation model based on the user input; and when the user input is SPAM, discarding the user input. 12. The computer-readable storage device of claim 10 , wherein analyzing further comprises determining whether the user input contains no text, the user input being SPAM when the user input contains no text. | 0.84824 |
10,120,968 | 12 | 13 | 12. The system of claim 10 , wherein the at least one processor is further configured to generate a library catalog with information acquired during the identification of the one or more undefined references from within the first group and the identification of the one or more undefined references from within the second group. | 12. The system of claim 10 , wherein the at least one processor is further configured to generate a library catalog with information acquired during the identification of the one or more undefined references from within the first group and the identification of the one or more undefined references from within the second group. 13. The system of claim 12 , wherein the at least one processor is further configured to identify the one or more references from within a subset of the one or more groups based upon, at least in part, the information within the library catalog. | 0.5 |
6,119,086 | 20 | 32 | 20. A speech coding method responsive to an input speech signal provided by a system user, the method comprising the steps of: (a) recognizing words in the input speech signal in accordance with a speech recognition vocabulary to generate a first transcription comprising at least one phonetic token representative of the input speech signal; (b) generating a second transcription comprising at least one phonetic token representative of a word in the input speech signal that is not associated with the speech recognition vocabulary; (c) one of transmitting and storing at least one of the phonetic tokens; and (d) generating a synthesized speech signal which is representative of the input speech signal provided by the system user using at least one of a plurality of pre-enrolled phonetic tokens that substantially matches at least one of the phonetic tokens. | 20. A speech coding method responsive to an input speech signal provided by a system user, the method comprising the steps of: (a) recognizing words in the input speech signal in accordance with a speech recognition vocabulary to generate a first transcription comprising at least one phonetic token representative of the input speech signal; (b) generating a second transcription comprising at least one phonetic token representative of a word in the input speech signal that is not associated with the speech recognition vocabulary; (c) one of transmitting and storing at least one of the phonetic tokens; and (d) generating a synthesized speech signal which is representative of the input speech signal provided by the system user using at least one of a plurality of pre-enrolled phonetic tokens that substantially matches at least one of the phonetic tokens. 32. The speech coding method of claim 20, wherein step (d) further comprises the steps of: selecting the pre-enrolled phonetic tokens that substantially match the phonetic tokens; associating pre-stored waveforms to the pre-enrolled phonetic tokens; adjusting the pre-stored waveforms in accordance with acoustic parameters associated with voice characteristics of the system user; and linking the pre-stored waveforms to form the synthesized speech signal. | 0.5 |
9,069,583 | 2 | 3 | 2. The method of claim 1 , wherein creating a control that includes the one or more designers comprises creating a control that includes a tab element for each of the one or more designers, the tab element operable to receive a command to switch to a designer associated with the tab element. | 2. The method of claim 1 , wherein creating a control that includes the one or more designers comprises creating a control that includes a tab element for each of the one or more designers, the tab element operable to receive a command to switch to a designer associated with the tab element. 3. The method of claim 2 , wherein creating the control that includes the one or more designers further comprises creating a control that includes an additional tab element, the additional tab element associated with a markup language editor included in the control, the additional tab element operable to receive a command to switch to the markup language editor. | 0.5 |
8,539,359 | 85 | 90 | 85. A machine system configured for performing prespecified operations wherein at least a portion of the machine system includes a data processing machine configured to perform at least part of the prespecified operations of the machine system, the machine system comprising: a user monitoring subsystem configured to automatically repeatedly monitor at least one of machine usage activities of, states of and surroundings of a corresponding first user of the machine system and to automatically repeatedly record report records corresponding to the monitored activities, states and/or surroundings of the first user, wherein the automatically repeated monitorings are carried out transparently by the user monitoring subsystem without need for diverting focused attention of the first user to aiding the monitorings; and an invitations presenting subsystem configured to automatically present to the first user, immediately acceptable invitations to join in on system-identified telecommunications-mediated information exchange forums that are each a forum having at least one other user co-invited to it or already participating in the forum, where the invitations are based on automatically repeated determinations by the machine system of likely recent focusings of attention or likely recent co-compatibilities of the first user to join in on said forums and where the automatically repeated determinations are based on at least some of the recorded report records corresponding to the monitored activities, states and/or surroundings of the first user, wherein said likely recent focusings of attention of the first user or said likely recent co-compatibilities of the first user occurred no more than at least one of: 3 hours prior to said presentation to the first user of the respective invitations; and a determined time duration prior to said presentation to the first user of the respective invitations, the determined time duration being determined based on a currently active profile characterizing the first user. | 85. A machine system configured for performing prespecified operations wherein at least a portion of the machine system includes a data processing machine configured to perform at least part of the prespecified operations of the machine system, the machine system comprising: a user monitoring subsystem configured to automatically repeatedly monitor at least one of machine usage activities of, states of and surroundings of a corresponding first user of the machine system and to automatically repeatedly record report records corresponding to the monitored activities, states and/or surroundings of the first user, wherein the automatically repeated monitorings are carried out transparently by the user monitoring subsystem without need for diverting focused attention of the first user to aiding the monitorings; and an invitations presenting subsystem configured to automatically present to the first user, immediately acceptable invitations to join in on system-identified telecommunications-mediated information exchange forums that are each a forum having at least one other user co-invited to it or already participating in the forum, where the invitations are based on automatically repeated determinations by the machine system of likely recent focusings of attention or likely recent co-compatibilities of the first user to join in on said forums and where the automatically repeated determinations are based on at least some of the recorded report records corresponding to the monitored activities, states and/or surroundings of the first user, wherein said likely recent focusings of attention of the first user or said likely recent co-compatibilities of the first user occurred no more than at least one of: 3 hours prior to said presentation to the first user of the respective invitations; and a determined time duration prior to said presentation to the first user of the respective invitations, the determined time duration being determined based on a currently active profile characterizing the first user. 90. The machine system of claim 85 wherein the invitations presenting subsystem is configured to automatically repeatedly present the invitations as progressively more up to date invitations. | 0.91016 |
6,105,036 | 28 | 31 | 28. A method of displaying on a computer display a source code file, the source code file including an ordered arrangement of program statements and at least one set of data interposed therein, the method comprising: (a) displaying the ordered arrangement of program statements on the computer display; and (b) in response to user input, selectively displaying a shorthand notation of the set of data on the computer display at the relative location thereof in the ordered arrangement of program statements. | 28. A method of displaying on a computer display a source code file, the source code file including an ordered arrangement of program statements and at least one set of data interposed therein, the method comprising: (a) displaying the ordered arrangement of program statements on the computer display; and (b) in response to user input, selectively displaying a shorthand notation of the set of data on the computer display at the relative location thereof in the ordered arrangement of program statements. 31. The method of claim 28, wherein selectively displaying the shorthand notation includes displaying ellipses. | 0.723881 |
7,979,442 | 5 | 6 | 5. The method of claim 4 further comprising: determining a compatibility rating between the user and the other users based on the similar attributes between the arrangement and the other arrangements; and enabling each user of the server device to view mark-up language files of the other users. | 5. The method of claim 4 further comprising: determining a compatibility rating between the user and the other users based on the similar attributes between the arrangement and the other arrangements; and enabling each user of the server device to view mark-up language files of the other users. 6. The method of claim 5 further comprising registering a particular one of the other users when the particular one of the other users responds to a hook data in a communication between the user and the other users. | 0.5 |
8,612,853 | 3 | 4 | 3. A method as set forth in claim 2 further comprising the steps of: recognizing ( 130 , 230 ) a third element designated by the common noun preceded by a third combination of adjectives including one of the primary adjectives identifying one of the first and second elements combined with the secondary adjective identifying the other one of the first and second elements, associating ( 132 , 232 ) a third reference numeral with the common noun preceded by the third combination of adjectives, automatically inserting ( 148 , 248 ) the third reference numeral following the common noun in response to each recitation of the common noun preceded solely by the third combination of adjectives ( 150 , 250 ) to reference the third element throughout said at least one section of the patent application, further characterized by automatically inserting ( 166 , 264 ) the first and third reference numerals following the common noun in response to each recitation of the common noun modified solely by the one of the primary and secondary adjective shared between the first and third elements ( 166 , 266 ) and automatically inserting ( 160 , 260 ) the second and third reference numerals following the common noun in response to each recitation of the common noun modified solely by the one of the primary and secondary adjectives shared between the second and third elements ( 162 , 262 ), and automatically inserting ( 172 ) the first reference numeral and the second reference numeral and the third reference numeral following the common noun in response to each recitation of the common noun unmodified by an adjective ( 174 ) to reference the first element and the second element and the third element throughout said at least one section of the patent application. | 3. A method as set forth in claim 2 further comprising the steps of: recognizing ( 130 , 230 ) a third element designated by the common noun preceded by a third combination of adjectives including one of the primary adjectives identifying one of the first and second elements combined with the secondary adjective identifying the other one of the first and second elements, associating ( 132 , 232 ) a third reference numeral with the common noun preceded by the third combination of adjectives, automatically inserting ( 148 , 248 ) the third reference numeral following the common noun in response to each recitation of the common noun preceded solely by the third combination of adjectives ( 150 , 250 ) to reference the third element throughout said at least one section of the patent application, further characterized by automatically inserting ( 166 , 264 ) the first and third reference numerals following the common noun in response to each recitation of the common noun modified solely by the one of the primary and secondary adjective shared between the first and third elements ( 166 , 266 ) and automatically inserting ( 160 , 260 ) the second and third reference numerals following the common noun in response to each recitation of the common noun modified solely by the one of the primary and secondary adjectives shared between the second and third elements ( 162 , 262 ), and automatically inserting ( 172 ) the first reference numeral and the second reference numeral and the third reference numeral following the common noun in response to each recitation of the common noun unmodified by an adjective ( 174 ) to reference the first element and the second element and the third element throughout said at least one section of the patent application. 4. A method as set forth in claim 3 further comprising the steps of: recognizing a fourth element ( 234 ) designated by the common noun preceded by a fourth combination including the other primary adjective from the primary adjective of the third combination combined with the other secondary adjective from the secondary adjective of the third combination, associating ( 236 ) a fourth reference numeral with the common noun preceded by the fourth combination of adjectives to reference the fourth element, automatically ( 252 ) inserting the fourth reference numeral following the common noun in response to each recitation of the common noun preceded by the fourth combination of adjectives ( 254 ) to reference the fourth element throughout said at least one section the patent application, further characterized by automatically inserting ( 256 ) the first and fourth reference numerals following the common noun in response to each recitation of the common noun modified solely by the one of the primary and secondary adjective shared between the first and fourth elements ( 258 ) and automatically inserting ( 268 ) the second and fourth reference numerals following the common noun in response to each recitation of the common noun modified solely by the one of the primary and secondary adjectives shared between the second and fourth reference numerals ( 270 ), and automatically inserting ( 272 ) the first reference numeral and the second reference numeral and the third reference numeral and the fourth reference numeral following the common noun in response to each recitation of the common noun unmodified by an adjective ( 274 ) to reference the first element and the second element and the third element and the fourth element throughout said at least one section the patent application. | 0.5 |
8,312,032 | 31 | 33 | 31. A server system for processing query information, comprising: one or more processors; and memory to store data and one or more programs to be executed by the one or more processors, the one or more programs including instructions for: prior to a user of a client device signaling completion of a search query: receiving from a search requestor a partial search query, the search requestor located remotely from the server system; predicting from the partial search query a set of predicted complete queries relevant to the partial search query, where the predicted complete queries comprise previously submitted complete queries submitted by a community of users, wherein the partial search query and the set of predicted complete queries are in a first language; subsequent to the predicting, obtaining translations of at least a subset of the set of predicted complete queries, wherein the translations are in a second language different from the first language, and the subset comprises multiple predicted complete queries, wherein the first and second languages are predicted based, at least in part, on the partial search query; and conveying both the set of predicted complete queries and the corresponding translations to the search requestor for concurrent display. | 31. A server system for processing query information, comprising: one or more processors; and memory to store data and one or more programs to be executed by the one or more processors, the one or more programs including instructions for: prior to a user of a client device signaling completion of a search query: receiving from a search requestor a partial search query, the search requestor located remotely from the server system; predicting from the partial search query a set of predicted complete queries relevant to the partial search query, where the predicted complete queries comprise previously submitted complete queries submitted by a community of users, wherein the partial search query and the set of predicted complete queries are in a first language; subsequent to the predicting, obtaining translations of at least a subset of the set of predicted complete queries, wherein the translations are in a second language different from the first language, and the subset comprises multiple predicted complete queries, wherein the first and second languages are predicted based, at least in part, on the partial search query; and conveying both the set of predicted complete queries and the corresponding translations to the search requestor for concurrent display. 33. The server system of claim 31 , wherein at least one of the predicted complete queries does not include the entire partial search query. | 0.837209 |
8,285,734 | 1 | 16 | 1. A method for comparing a first document to one or more second documents, a given document comprising one or more elements and one or more values for each of the one or more elements, the method comprising the steps of: assigning at least one weight to at least one of the one or more elements in the first document; generating a weighted template in accordance with the at least one assigned weight; computing one or more comparison scores for each of the one or more second documents, wherein the one or more comparison scores for a given second document are computed by comparing the one or more values for at least a given element in the first document to one or more values for each of one or more elements in the given second document in accordance with one or more comparison rules, wherein the one or more comparison rules determine at least one technique used for comparing the given element in the first document and a given element in the given second document based on whether the values of the elements being compared are textual or numeric values, wherein the at least one technique determined by the one or more comparison rules comprises using at least one or more language hierarchies to compare textual values; and generating one or more similarity scores for each of the one or more second documents in accordance with the generated weighted template and the one or more computed comparison scores. | 1. A method for comparing a first document to one or more second documents, a given document comprising one or more elements and one or more values for each of the one or more elements, the method comprising the steps of: assigning at least one weight to at least one of the one or more elements in the first document; generating a weighted template in accordance with the at least one assigned weight; computing one or more comparison scores for each of the one or more second documents, wherein the one or more comparison scores for a given second document are computed by comparing the one or more values for at least a given element in the first document to one or more values for each of one or more elements in the given second document in accordance with one or more comparison rules, wherein the one or more comparison rules determine at least one technique used for comparing the given element in the first document and a given element in the given second document based on whether the values of the elements being compared are textual or numeric values, wherein the at least one technique determined by the one or more comparison rules comprises using at least one or more language hierarchies to compare textual values; and generating one or more similarity scores for each of the one or more second documents in accordance with the generated weighted template and the one or more computed comparison scores. 16. The method of claim 1 , wherein the weighted template is generated such that the at least one weight assigned to the at least one of the one or more elements in the first document is applied to at least one of the one or more elements in each of the one or more second documents. | 0.5 |
9,037,593 | 1 | 4 | 1. A computer-readable, non-transitory medium storing a program which, when executed by a computer, causes the computer to perform a process comprising: splitting a first character string and a second character string into words; acquiring information including a semantic attribute that represents a semantic nature of each of the words and a conceptual code that semantically identifies said each of the words, from a storage device; identifying a pair of the words having a common semantic attribute between the first character string and the second character string; comparing the conceptual codes of the specified pair of the words between the first character string and the second character string; and generating a comparison result between the first character string and the second character string based upon a comparison result of the conceptual codes, wherein the first character string is split into a first set of words and the second character string is split into a second set of words, wherein a first conceptual structure that represents a relationship among the first set of the words is generated from the first character string using a first set of conceptual codes, on the basis of the semantic attribute and a grammatical configuration of each of the first set of the words, and a second conceptual structure that represents a relationship among the second set of the words is generated from the second character string using a second set of conceptual codes, on the basis of the semantic attribute and a grammatical configuration of each of the second set of the words, and wherein a pair of the conceptual codes having a common semantic attribute and a common among-the-words relationship between the first character string and the second character string are identified. | 1. A computer-readable, non-transitory medium storing a program which, when executed by a computer, causes the computer to perform a process comprising: splitting a first character string and a second character string into words; acquiring information including a semantic attribute that represents a semantic nature of each of the words and a conceptual code that semantically identifies said each of the words, from a storage device; identifying a pair of the words having a common semantic attribute between the first character string and the second character string; comparing the conceptual codes of the specified pair of the words between the first character string and the second character string; and generating a comparison result between the first character string and the second character string based upon a comparison result of the conceptual codes, wherein the first character string is split into a first set of words and the second character string is split into a second set of words, wherein a first conceptual structure that represents a relationship among the first set of the words is generated from the first character string using a first set of conceptual codes, on the basis of the semantic attribute and a grammatical configuration of each of the first set of the words, and a second conceptual structure that represents a relationship among the second set of the words is generated from the second character string using a second set of conceptual codes, on the basis of the semantic attribute and a grammatical configuration of each of the second set of the words, and wherein a pair of the conceptual codes having a common semantic attribute and a common among-the-words relationship between the first character string and the second character string are identified. 4. The computer-readable, non-transitory medium according to claim 1 , wherein the process further includes: determining a comparison value representing the comparison result of the conceptual codes for each of multiple conceptual code pairs between the first character string and the second character string; and calculating an evaluation value by summing the comparison values of the multiple conceptual code pairs, and wherein the generation of the comparison result includes generating the comparison result between the first character string and the second character string by comparing the evaluation value and a determination threshold value. | 0.683415 |
9,367,807 | 6 | 8 | 6. The logic-programming-based computer system of claim 5 wherein each fact-rule pair of the set of fact-rule pairs comprises: a IDX fact; and a ID rule. | 6. The logic-programming-based computer system of claim 5 wherein each fact-rule pair of the set of fact-rule pairs comprises: a IDX fact; and a ID rule. 8. The logic-programming-based computer system of claim 6 wherein each ID rule includes: a head predicate with a name identical to the predicate name of a final argument of a corresponding IDX fact and with a number of variable arguments equal to the number of variable arguments of a rule implemented by the gateway rule and the set of fact-rule pairs; and a body corresponding to the body of the rule implemented by the gateway rule and the set of fact-rule pairs. | 0.589789 |
7,849,148 | 1 | 67 | 1. In a computer system, a computer-implemented method comprising: displaying at least one window in connection with a website; displaying, utilizing the at least one window, a stock-related field; receiving a plurality of characters of text from a user as the user is typing the text utilizing the stock-related field; after the user types each character in the received text, dynamically determining whether the characters typed so far match any of n text strings in one of a plurality of n-tuples including n>1 text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; if it is determined that the characters typed so far match any of the n text strings in the one of the plurality of n-tuples, indicating to the user that a match has been found, utilizing the at least one window; displaying, utilizing the at least one window, a first set of representations of a first set of hyperlinks; receiving first input from the user indicating a selection of one of the first set of hyperlink representations; in response to receiving the first input, displaying a second set of representations of a second set of hyperlinks, utilizing the at least one window; receiving second input from the user indicating a selection of one of the second set of hyperlink representations; and in response to receiving the second input, navigating to a destination specified by the selected one of the second set of hyperlink representations. | 1. In a computer system, a computer-implemented method comprising: displaying at least one window in connection with a website; displaying, utilizing the at least one window, a stock-related field; receiving a plurality of characters of text from a user as the user is typing the text utilizing the stock-related field; after the user types each character in the received text, dynamically determining whether the characters typed so far match any of n text strings in one of a plurality of n-tuples including n>1 text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; if it is determined that the characters typed so far match any of the n text strings in the one of the plurality of n-tuples, indicating to the user that a match has been found, utilizing the at least one window; displaying, utilizing the at least one window, a first set of representations of a first set of hyperlinks; receiving first input from the user indicating a selection of one of the first set of hyperlink representations; in response to receiving the first input, displaying a second set of representations of a second set of hyperlinks, utilizing the at least one window; receiving second input from the user indicating a selection of one of the second set of hyperlink representations; and in response to receiving the second input, navigating to a destination specified by the selected one of the second set of hyperlink representations. 67. The method of claim 1 , wherein the second set of representations is specified by the user before displaying the second set of representations. | 0.821168 |
9,767,255 | 14 | 16 | 14. The medical system of claim 13 , wherein the steps further comprise: generating a list of popular data entries; saving the list of popular data entries in an electronic memory storage; and selecting at least a subset of the list of popular data entries to be displayed as the plurality of predefined suggestions. | 14. The medical system of claim 13 , wherein the steps further comprise: generating a list of popular data entries; saving the list of popular data entries in an electronic memory storage; and selecting at least a subset of the list of popular data entries to be displayed as the plurality of predefined suggestions. 16. The medical system of claim 14 , wherein the steps further comprise: analyzing popular data entries stored on other portable electronic devices, wherein the generating the list of popular data entries comprises selecting at least a subset of popular data entries stored on the other portable electronic devices. | 0.5 |
8,224,816 | 44 | 46 | 44. The computer implemented system of claim 40 , including a tracking overlay, said tracking overlay comprised of a rating panel, including a plurality of rating factors, and a selecting panel, including a plurality of commands, sorting of said correlated content to said response and generating a correlated content. | 44. The computer implemented system of claim 40 , including a tracking overlay, said tracking overlay comprised of a rating panel, including a plurality of rating factors, and a selecting panel, including a plurality of commands, sorting of said correlated content to said response and generating a correlated content. 46. The computer implemented system of claim 44 , wherein in said sorting of correlated content, optionally, disposes said correlated content from said displaying of correlated content, including a opposite correlated content. | 0.5 |
7,933,863 | 11 | 18 | 11. A method of managing a database storing a plurality of entities related to each other by a plurality of relations, the database associated with a user interface, comprising: storing a plurality of entities representing a situation, in which the user has been involved, as at least one artificial intelligence frame, the at least one artificial intelligence frame describing at least one object and action involved in the situation in which the user has been involved and their relationship to each other; and modeling a context representation of a current situation using the at least one artificial intelligence frame, so that when the context representation is applied to the database, operation of the database is adapted according to the situation. | 11. A method of managing a database storing a plurality of entities related to each other by a plurality of relations, the database associated with a user interface, comprising: storing a plurality of entities representing a situation, in which the user has been involved, as at least one artificial intelligence frame, the at least one artificial intelligence frame describing at least one object and action involved in the situation in which the user has been involved and their relationship to each other; and modeling a context representation of a current situation using the at least one artificial intelligence frame, so that when the context representation is applied to the database, operation of the database is adapted according to the situation. 18. The method according to claim 11 , further comprising: assigning a value to at least one entity in at least one of the slots indicating the reliability of the relation of the entity in the slot with respect to another entity in a related slot. | 0.635693 |
9,092,478 | 44 | 45 | 44. The system of claim 31 , wherein providing representations of the data items and the identified metadata in response to receiving the search query further comprises: providing a value that represents the data items and the identified metadata; and providing additional values that are related to the value. | 44. The system of claim 31 , wherein providing representations of the data items and the identified metadata in response to receiving the search query further comprises: providing a value that represents the data items and the identified metadata; and providing additional values that are related to the value. 45. The system of claim 44 , wherein the additional values include top values associated with the data items and the identified metadata. | 0.5 |
9,716,686 | 27 | 29 | 27. The electronic device of claim 15 , wherein the responding device is configured to detect when a location about the responding device is occupied. | 27. The electronic device of claim 15 , wherein the responding device is configured to detect when a location about the responding device is occupied. 29. The electronic device of claim 27 , wherein the processor is configured to identify particular occupants or objects when the processor detects that the location about the responding device is occupied. | 0.730263 |
8,392,454 | 6 | 10 | 6. A computer-implemented method comprising: providing an electronic document via a computer comprising text and concordance data, wherein said concordance data identifies locations where said text appears on hyperlinked pages, such as web pages; performing a computerized search of said electronic document via said computer based on a multi-term inclusive query to produce preliminary search results comprising search term matches, where each search term match only includes a single term, and wherein said search term matches identify page locations within said hyperlinked pages where individual terms within said multi-term inclusive query appear; determining whether terms within said search term matches are within predetermined proximities of other terms in said multi-term inclusive query via said computer, wherein said predetermined proximities comprise said term within said search term match being within adjacent hyperlink pages of at least one of said other terms in said multi-term inclusive query, wherein said adjacent hyperlink pages each have hyperlinks that directly link to each other; eliminating said search term matches via said computer that do not comprise terms that appear within said predetermined proximities from said preliminary search results to produce final search results; and reporting said final search results via said computer. | 6. A computer-implemented method comprising: providing an electronic document via a computer comprising text and concordance data, wherein said concordance data identifies locations where said text appears on hyperlinked pages, such as web pages; performing a computerized search of said electronic document via said computer based on a multi-term inclusive query to produce preliminary search results comprising search term matches, where each search term match only includes a single term, and wherein said search term matches identify page locations within said hyperlinked pages where individual terms within said multi-term inclusive query appear; determining whether terms within said search term matches are within predetermined proximities of other terms in said multi-term inclusive query via said computer, wherein said predetermined proximities comprise said term within said search term match being within adjacent hyperlink pages of at least one of said other terms in said multi-term inclusive query, wherein said adjacent hyperlink pages each have hyperlinks that directly link to each other; eliminating said search term matches via said computer that do not comprise terms that appear within said predetermined proximities from said preliminary search results to produce final search results; and reporting said final search results via said computer. 10. The method according to claim 6 , wherein said hyperlinked pages comprise a hyperlink comprising a graphical item a user activates with a single user input action to move between adjacent hyperlinked pages in one of network documents and web pages. | 0.5 |
8,572,075 | 23 | 25 | 23. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform actions comprising: receiving a plurality of queries sequentially, each query being received from a respective user; and performing the following operations with respect to each query and respective user: selecting a pair of candidate scoring functions from a group of at least three candidate scoring functions, the pair including a first candidate scoring function and a second candidate scoring function, the selecting being based at least in part on a ranking of the candidate scoring functions in the group; presenting search results, which are responsive to the query, ordered according to scores from the first candidate scoring function, to the respective user; presenting the search results, which are responsive to the query, ordered according to scores from the second candidate scoring function, to the respective user; receiving user input, from the respective user, selecting one of the first and second candidate scoring functions over the other; and using the user input to update the ranking of the candidate scoring functions in the group. | 23. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform actions comprising: receiving a plurality of queries sequentially, each query being received from a respective user; and performing the following operations with respect to each query and respective user: selecting a pair of candidate scoring functions from a group of at least three candidate scoring functions, the pair including a first candidate scoring function and a second candidate scoring function, the selecting being based at least in part on a ranking of the candidate scoring functions in the group; presenting search results, which are responsive to the query, ordered according to scores from the first candidate scoring function, to the respective user; presenting the search results, which are responsive to the query, ordered according to scores from the second candidate scoring function, to the respective user; receiving user input, from the respective user, selecting one of the first and second candidate scoring functions over the other; and using the user input to update the ranking of the candidate scoring functions in the group. 25. The system of claim 23 , wherein selecting a pair of candidate scoring functions from a group of at least three candidate scoring functions comprises: determining a diversity score between the first candidate scoring function and the second candidate scoring function, wherein the diversity score is based at least in part on a comparison of respective search result sets ordered according to the first candidate scoring function and the second candidate scoring function; and determining that the diversity score between the first scoring function and the second scoring function satisfies a threshold. | 0.5 |
7,801,354 | 9 | 10 | 9. The learning device according to claim 2 , wherein the recognizer generating means provides a threshold value for the learning correlation feature quantity to perform screening of the learning correlation feature quantity on the basis of the threshold value. | 9. The learning device according to claim 2 , wherein the recognizer generating means provides a threshold value for the learning correlation feature quantity to perform screening of the learning correlation feature quantity on the basis of the threshold value. 10. The learning device according to claim 9 , wherein the recognizer generating means generates the recognizer and performs screening of the learning correlation feature quantity in accordance with a boosting algorithm. | 0.5 |
9,275,079 | 1 | 2 | 1. A computer-implemented method, comprising: receiving, at a server computer system, digital image data captured by a mobile device; performing image recognition analysis on an object within the digital image data to identify the object; receiving, at the server computer system, sensor data that describes a change in orientation executed by the user device; determining based on the identity of the object, the image analysis, and the sensor data, a gesture associated with the object; querying a semantic associations database based on the determined gesture and the object to determine a secondary meaning associated with the gesture and the object, wherein the secondary meaning is a non-literal meaning associated with the determined identity of the object based on the gesture, wherein the non-literal meaning is inferred from descriptions associated with a plurality of images located on a computer network that depict objects with the determined identity, wherein the descriptions each include one or more references to the non-literal meaning associated with the gesture; in response to the determination of the secondary meaning, requesting augmentation data from a remote service based on the secondary meaning; receiving the augmentation data from the remote service in response to the request, wherein the augmentation data is relevant to the secondary meaning associated with the identified object, and wherein the augmentation data is to be rendered over the identified object in the digital image data when displayed by the mobile device; and transmitting augmentation data to the mobile device that is semantically relevant to the object based on the secondary meaning. | 1. A computer-implemented method, comprising: receiving, at a server computer system, digital image data captured by a mobile device; performing image recognition analysis on an object within the digital image data to identify the object; receiving, at the server computer system, sensor data that describes a change in orientation executed by the user device; determining based on the identity of the object, the image analysis, and the sensor data, a gesture associated with the object; querying a semantic associations database based on the determined gesture and the object to determine a secondary meaning associated with the gesture and the object, wherein the secondary meaning is a non-literal meaning associated with the determined identity of the object based on the gesture, wherein the non-literal meaning is inferred from descriptions associated with a plurality of images located on a computer network that depict objects with the determined identity, wherein the descriptions each include one or more references to the non-literal meaning associated with the gesture; in response to the determination of the secondary meaning, requesting augmentation data from a remote service based on the secondary meaning; receiving the augmentation data from the remote service in response to the request, wherein the augmentation data is relevant to the secondary meaning associated with the identified object, and wherein the augmentation data is to be rendered over the identified object in the digital image data when displayed by the mobile device; and transmitting augmentation data to the mobile device that is semantically relevant to the object based on the secondary meaning. 2. The computer-implemented method of claim 1 , further comprising: receiving metadata with the digital image data, the metadata captured by one or more sensors of the mobile device; including the received metadata in the request of the remote system, the metadata to provide a context for the request. | 0.5 |
8,122,033 | 1 | 8 | 1. In a computer system having a relational database system, a method comprising: creating a number of materialized query tables (MQTs) within the database system; defining one or more database table specifications, including a primary key of a table for a number of tables; receiving an incoming query at the database system; in response to the incoming query referencing a first subset of a set of tables, identifying an MQT with a definition query that references the set of tables, wherein said first subset includes one of: (a) a number of fact tables and a group of dimension tables; (b) a number of source tables and a group of dependent tables; and (c) a number of referencing tables and a group of referenced tables; determining when the MQT is a candidate match for the incoming query; identifying one or more candidate MQTs; selecting an optimal MQT from among the one or more candidate MQTs; and when (a) a definition query of the MQT uses a corresponding group-by column list to reference a first number of columns from a set of tables and (b) the incoming query references a second number of columns from the same set of tables, determining one or more of the following: (1) whether one or more of the first number of columns is identical to one or more of the second number of columns; (2) whether one or more of the first number of columns is not contained within the second number of columns; (3) whether one or more of the second number of columns is not contained within the first number of columns; and (4) whether the first number of columns functionally determines the second number of columns. | 1. In a computer system having a relational database system, a method comprising: creating a number of materialized query tables (MQTs) within the database system; defining one or more database table specifications, including a primary key of a table for a number of tables; receiving an incoming query at the database system; in response to the incoming query referencing a first subset of a set of tables, identifying an MQT with a definition query that references the set of tables, wherein said first subset includes one of: (a) a number of fact tables and a group of dimension tables; (b) a number of source tables and a group of dependent tables; and (c) a number of referencing tables and a group of referenced tables; determining when the MQT is a candidate match for the incoming query; identifying one or more candidate MQTs; selecting an optimal MQT from among the one or more candidate MQTs; and when (a) a definition query of the MQT uses a corresponding group-by column list to reference a first number of columns from a set of tables and (b) the incoming query references a second number of columns from the same set of tables, determining one or more of the following: (1) whether one or more of the first number of columns is identical to one or more of the second number of columns; (2) whether one or more of the first number of columns is not contained within the second number of columns; (3) whether one or more of the second number of columns is not contained within the first number of columns; and (4) whether the first number of columns functionally determines the second number of columns. 8. The method of claim 1 , further comprising: when the matched group exists and the non-empty first unmatched group and the second unmatched group are identified: (1) determining whether the matched group functionally determines the non-empty first unmatched group and the second unmatched group; and (2) identifying the MQT as a candidate match when (a) the matched group exists and is identified, (b) the matched group functionally determines the non-empty first and second unmatched group(s), and (c) one or more of the qualifying conditions are satisfied; when the matched group does not exist or the matched group exists but does not functionally determine the non-empty first and second unmatched group(s): (1) determining whether the incoming query is based on measures which are exclusively additive; and (2) identifying the MQT as a candidate match when (a) the incoming query is based on measures which are exclusively additive, (b) the number of columns in the said first set functionally determines the number of columns in the said second set, and (c) one or more of the qualifying conditions are satisfied. | 0.635566 |
8,762,369 | 18 | 19 | 18. The continuous query result estimator according to claim 3 , wherein the control module is configured to trigger the classification of the received set of data items by the classification module when one of a number and a proportion of expected data values determined to be missing from the received set of data items is one of at and below a threshold value. | 18. The continuous query result estimator according to claim 3 , wherein the control module is configured to trigger the classification of the received set of data items by the classification module when one of a number and a proportion of expected data values determined to be missing from the received set of data items is one of at and below a threshold value. 19. The continuous query result estimator according to claim 18 , wherein the classification module is configured to: classify the received set of data items by calculating for each of the input data groups a respective value of a similarity measure using the received set of data items, and select an input data group on the basis of the calculated similarity measure values. | 0.5 |
8,073,741 | 19 | 20 | 19. A computer program product for locating a relevant product, the computer program product comprising: a storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: receiving a search topic from a user; receiving one or more attributes associated with the topic; assigning a rating to at least one of the attributes; locating at one or more information locations at least two separate instances of the topic; locating at least two information fields, each field related to one of the instances of the topic; associating content in each of at least two of the information fields with at least one of the attributes; comparing the content in each of the at least two information fields associated with an attribute against each other; assigning a score to the content of each compared instance of content based on the comparing; prioritizing the attributes; and ranking the located instances of the topic based on the prioritizing and the score of content associated with the topic. | 19. A computer program product for locating a relevant product, the computer program product comprising: a storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: receiving a search topic from a user; receiving one or more attributes associated with the topic; assigning a rating to at least one of the attributes; locating at one or more information locations at least two separate instances of the topic; locating at least two information fields, each field related to one of the instances of the topic; associating content in each of at least two of the information fields with at least one of the attributes; comparing the content in each of the at least two information fields associated with an attribute against each other; assigning a score to the content of each compared instance of content based on the comparing; prioritizing the attributes; and ranking the located instances of the topic based on the prioritizing and the score of content associated with the topic. 20. The computer program product according to claim 19 , which further comprises carrying out the attribute step by at least one of: receiving inputs from a user; searching data stored during the user's previous session; searching a database of user attributes; and assigning default values. | 0.5 |
9,348,811 | 19 | 25 | 19. A system of one or more computers configured to perform operations comprising: accessing a set of related electronic documents; analyzing markup language of an electronic document of the set of related electronic documents to identify markup language tags of the electronic document; analyzing, using a page recognition module, the markup language tags to identify the electronic document as a product page, the page recognition model generated based on a first machine learning algorithm, and the product page comprising a plurality of terms; filtering the plurality of terms into a first set of terms and a second set of terms, the first set of terms and the second set of terms including different terms of the plurality of terms, each term in the first set of terms identified as potentially being associated with a product name, and each term in the second set of terms identified as not being associated with a product name; for each term of the first set of terms, identifying a noun phrase that includes the term and determining one or more features of each of the noun phrase and the term; for each feature of the one or more features: determining, for each term of the first of terms, a first feature value of the noun phrase and a second feature value of the term, and determining, for each term of the first set of terms, an overall feature value for the term based on the first feature value and the second feature value; identifying each term in the first set of terms as being associated with a product name or not being associated with a product name with a name recognition model, the name recognition model generated based on the overall feature value for each feature of the term; and providing for display on a graphical user interface, one or more of the first set of terms that are identified as being associated with a product name. | 19. A system of one or more computers configured to perform operations comprising: accessing a set of related electronic documents; analyzing markup language of an electronic document of the set of related electronic documents to identify markup language tags of the electronic document; analyzing, using a page recognition module, the markup language tags to identify the electronic document as a product page, the page recognition model generated based on a first machine learning algorithm, and the product page comprising a plurality of terms; filtering the plurality of terms into a first set of terms and a second set of terms, the first set of terms and the second set of terms including different terms of the plurality of terms, each term in the first set of terms identified as potentially being associated with a product name, and each term in the second set of terms identified as not being associated with a product name; for each term of the first set of terms, identifying a noun phrase that includes the term and determining one or more features of each of the noun phrase and the term; for each feature of the one or more features: determining, for each term of the first of terms, a first feature value of the noun phrase and a second feature value of the term, and determining, for each term of the first set of terms, an overall feature value for the term based on the first feature value and the second feature value; identifying each term in the first set of terms as being associated with a product name or not being associated with a product name with a name recognition model, the name recognition model generated based on the overall feature value for each feature of the term; and providing for display on a graphical user interface, one or more of the first set of terms that are identified as being associated with a product name. 25. The system of claim 19 , wherein filtering the plurality of terms into a first set of terms and a second set of terms comprises: parsing text in the product page into the plurality of terms; for each of the plurality of terms, determining a type of the term; and identifying the term as belonging in the first set of terms or the second set of terms based on the type of the term. | 0.639098 |
9,990,589 | 11 | 12 | 11. The computer-implemented method of claim 10 , wherein the plurality of search refinement options is determined based on a non-absolute interpretation and an absolute interpretation of the previously received indications of approval and disapproval. | 11. The computer-implemented method of claim 10 , wherein the plurality of search refinement options is determined based on a non-absolute interpretation and an absolute interpretation of the previously received indications of approval and disapproval. 12. The computer-implemented method of claim 11 , wherein a degree of the non-absolute interpretation of the previously received indications of both approval and disapproval is based on a number of approvals and disapprovals for search refinement options in a same search refinement category. | 0.5 |
9,779,187 | 15 | 16 | 15. A non-transitory computer program product storing instructions, which when executed by at least one data processor of at least one computing system, implement a method, the method comprising: accessing, using at least one data processor and from at least one database, data from a plurality of disparate data sources; automatically building, by a model building engine using at least one data processor and the data obtained from the accessed data sources, a plurality of test models, each test model having predetermined predictive variables and each test model built from one or more of the plurality of disparate data sources; determining, by a variable selector and using at least one data processor, a final set of predictive variables from the predetermined predictive variables in the plurality of test models by comparing the predictive power of the predictive variables across the plurality of test models, the final set of predictive variables being the most predictive of the predetermined predictive variables; generating, using at least one data processor, a master dataset comprising data selected from the disparate data sources and corresponding to the determined final set of predictive variables; and building, using at least one data processor and from the master dataset, a master model that combines the final set of predictive variables from the plurality of disparate data sources, the master model characterizing a quantitative estimate of the probability that an entity will display a defined behavior. | 15. A non-transitory computer program product storing instructions, which when executed by at least one data processor of at least one computing system, implement a method, the method comprising: accessing, using at least one data processor and from at least one database, data from a plurality of disparate data sources; automatically building, by a model building engine using at least one data processor and the data obtained from the accessed data sources, a plurality of test models, each test model having predetermined predictive variables and each test model built from one or more of the plurality of disparate data sources; determining, by a variable selector and using at least one data processor, a final set of predictive variables from the predetermined predictive variables in the plurality of test models by comparing the predictive power of the predictive variables across the plurality of test models, the final set of predictive variables being the most predictive of the predetermined predictive variables; generating, using at least one data processor, a master dataset comprising data selected from the disparate data sources and corresponding to the determined final set of predictive variables; and building, using at least one data processor and from the master dataset, a master model that combines the final set of predictive variables from the plurality of disparate data sources, the master model characterizing a quantitative estimate of the probability that an entity will display a defined behavior. 16. The computer program product of claim 15 , the method further comprising iteratively building test models and determining an interim set of predictive variables until the test models or the interim set of predictive variables satisfy a predetermined criterion. | 0.65445 |
8,165,985 | 13 | 14 | 13. A method for performing discovery of digital information in a subject area, comprising: designating through a user interface of a computer a corpus comprising electronically-stored digital information, which are maintained in a storage device; selecting one or more topics and training material for the selected topics comprising on topic information and off topic information; building candidate topic models on the computer comprising: selecting seed words for each of the selected topics; and generating patterns from the seed words for each topic as candidate topic models for that topic; evaluating the candidate topic models for each selected topic against the training material comprising: matching the patterns in each candidate topic model to the training material; rating each candidate topic model for the selected topic comprising: assigning a higher score to each candidate topic model that matches the on topic information for the selected topic; assigning a lower score to each candidate topic model that does not match the on topic information for the selected topic; assigning a higher score to each candidate topic model that does not match the off topic information for the selected topic; and assigning a lower score to each candidate topic model that matches the off topic information for the selected topic; and building an evergreen index comprising topic models for each of the selected topics by pairing each topic to the candidate topic model that has the best overall score. | 13. A method for performing discovery of digital information in a subject area, comprising: designating through a user interface of a computer a corpus comprising electronically-stored digital information, which are maintained in a storage device; selecting one or more topics and training material for the selected topics comprising on topic information and off topic information; building candidate topic models on the computer comprising: selecting seed words for each of the selected topics; and generating patterns from the seed words for each topic as candidate topic models for that topic; evaluating the candidate topic models for each selected topic against the training material comprising: matching the patterns in each candidate topic model to the training material; rating each candidate topic model for the selected topic comprising: assigning a higher score to each candidate topic model that matches the on topic information for the selected topic; assigning a lower score to each candidate topic model that does not match the on topic information for the selected topic; assigning a higher score to each candidate topic model that does not match the off topic information for the selected topic; and assigning a lower score to each candidate topic model that matches the off topic information for the selected topic; and building an evergreen index comprising topic models for each of the selected topics by pairing each topic to the candidate topic model that has the best overall score. 14. A method according to claim 13 , further comprising: favoring the candidate topic models for the selected topic based on how well each candidate topic model performs by assigning a higher score to those candidate topic models, which match all of the on topic information for the selected topic and do not match all of the off topic information for the selected topic. | 0.5 |
8,793,653 | 19 | 20 | 19. A method for deploying a system for program code library selection in a networked computing environment, comprising: providing a computer infrastructure being operable to: receive a search results file in a library selection integrated development environment (IDE) from a library searching IDE, the search results file comprising at least one method and at least one class from a first program code file in the library searching IDE, and the search results file having a set of attributes; determine whether to perform a micro-benchmarking on the at least one method and the at least one class of the search results file, the determining being based on at least one of: a configuration of a second program code file in the library selection IDE, or a detected code pattern of the second program code file; perform, responsive to the determination, the micro-benchmarking on the at least one method and the at least one class, and store an associated micro-benchmark time and an invocation timestamp in a computer storage device; calculate a set of code style similarity scores that indicated a similarity between the at least one method and the at least one class with the methods and classes of the second program code file based on code syntax similarity; and provide an ordered list of the methods and classes of the second program code file based on the set of code style similarity scores, the micro-benchmarking, and the set of attributes. | 19. A method for deploying a system for program code library selection in a networked computing environment, comprising: providing a computer infrastructure being operable to: receive a search results file in a library selection integrated development environment (IDE) from a library searching IDE, the search results file comprising at least one method and at least one class from a first program code file in the library searching IDE, and the search results file having a set of attributes; determine whether to perform a micro-benchmarking on the at least one method and the at least one class of the search results file, the determining being based on at least one of: a configuration of a second program code file in the library selection IDE, or a detected code pattern of the second program code file; perform, responsive to the determination, the micro-benchmarking on the at least one method and the at least one class, and store an associated micro-benchmark time and an invocation timestamp in a computer storage device; calculate a set of code style similarity scores that indicated a similarity between the at least one method and the at least one class with the methods and classes of the second program code file based on code syntax similarity; and provide an ordered list of the methods and classes of the second program code file based on the set of code style similarity scores, the micro-benchmarking, and the set of attributes. 20. The method of claim 19 , the computer infrastructure being further operable to select a program code library based on the ordered list. | 0.5 |
9,053,466 | 12 | 18 | 12. The computer readable medium of claim 3 , wherein each calendar publication definition further comprises one or more transformation rules for transforming the data contained in fields of the qualified calendar events from the calendar database, wherein processing each calendar publication definition by the publication agent further comprises applying the respective one or more transformation rules to the qualified calendar events so that field values of the qualified calendar events are transformed before inclusion in the calendar publication. | 12. The computer readable medium of claim 3 , wherein each calendar publication definition further comprises one or more transformation rules for transforming the data contained in fields of the qualified calendar events from the calendar database, wherein processing each calendar publication definition by the publication agent further comprises applying the respective one or more transformation rules to the qualified calendar events so that field values of the qualified calendar events are transformed before inclusion in the calendar publication. 18. The computer readable medium of claim 12 , where the calendar publication definition further comprises one or more transformation criteria for determining whether or not the transformation rules should be applied to a qualified calendar event from the calendar database, wherein the publication agent, for each calendar publication definition, evaluates the one or more transformation criteria for each qualified calendar event before conditionally applying the relative transformation rules to be qualified calendar events that meet the required transformation criteria. | 0.5 |
9,773,252 | 7 | 9 | 7. The server of claim 6 wherein the server is further caused to select the pattern recognition algorithm based on recognizing source-specific data representation patterns in an instance in which the published content is unstructured content. | 7. The server of claim 6 wherein the server is further caused to select the pattern recognition algorithm based on recognizing source-specific data representation patterns in an instance in which the published content is unstructured content. 9. The server of claim 7 , wherein the pattern recognition algorithm is a trainable function generated using machine learning. | 0.772563 |
8,462,394 | 5 | 6 | 5. The method of claim 3 , wherein the document page is classified as one of a word processing document or a spreadsheet document when the page orientation is not landscape or the text size is classified as normal text. | 5. The method of claim 3 , wherein the document page is classified as one of a word processing document or a spreadsheet document when the page orientation is not landscape or the text size is classified as normal text. 6. The method of claim 5 , wherein text is classified as normal text when it is less than or equal to a predetermined text size, and classified as large text when it is larger than the predetermined text size. | 0.50939 |
7,478,047 | 41 | 42 | 41. The computer readable medium of claim 38 wherein said mental state further comprises a defined emotional state. | 41. The computer readable medium of claim 38 wherein said mental state further comprises a defined emotional state. 42. The computer readable medium of claim 41 wherein said modification of pitch or duration is based at least in part on the degree of intensity of said defined emotional state. | 0.508333 |
7,634,474 | 18 | 23 | 18. One or more computer-readable media having computer-executable instructions embodied thereon so that, when executed, performs a method for facilitating improvement in the quality of search results, the method comprising: obtaining a result of a search query initiated by a searching entity; storing in a physical memory data pertinent to the result of a search query; returning, by a searching component, a list of search results from a search query; obtaining, by a rating component from the searching entity, a pertinence rating of at least one of the results returned from the search query, the pertinence rating indicates at least one of multiple a degrees of relevancy of the rated results; examining, by a connectivity analysis component, connections between the rated results and unrated results of the search query and constructs a connectivity graph between the rated results and the unrated results, the connectivity graph provides a set of connectivity distances between the rated results and one or more of the unrated results, wherein the connectivity distance is based on the number of hops or links between the rated results and the unrated results; re-ranking, by a ranking component, the rated object and a subset of the other results based in part on the pertinence rating and a subset of the connectivity distances; truncating, by the ranking component, the initial list of search results to exclude non-relevant objects from display in a re-ranked search result list; wherein the rated results link to one or more unrated results directly, or through a series of links or hops; wherein if a rated search result has a pertinence rating that indicates that the rated search result is relevant, then all pages the rated search result links to within a given number (m) of links will be included in the truncated search results; and wherein the number m is a number that is greater than or equal to 2. | 18. One or more computer-readable media having computer-executable instructions embodied thereon so that, when executed, performs a method for facilitating improvement in the quality of search results, the method comprising: obtaining a result of a search query initiated by a searching entity; storing in a physical memory data pertinent to the result of a search query; returning, by a searching component, a list of search results from a search query; obtaining, by a rating component from the searching entity, a pertinence rating of at least one of the results returned from the search query, the pertinence rating indicates at least one of multiple a degrees of relevancy of the rated results; examining, by a connectivity analysis component, connections between the rated results and unrated results of the search query and constructs a connectivity graph between the rated results and the unrated results, the connectivity graph provides a set of connectivity distances between the rated results and one or more of the unrated results, wherein the connectivity distance is based on the number of hops or links between the rated results and the unrated results; re-ranking, by a ranking component, the rated object and a subset of the other results based in part on the pertinence rating and a subset of the connectivity distances; truncating, by the ranking component, the initial list of search results to exclude non-relevant objects from display in a re-ranked search result list; wherein the rated results link to one or more unrated results directly, or through a series of links or hops; wherein if a rated search result has a pertinence rating that indicates that the rated search result is relevant, then all pages the rated search result links to within a given number (m) of links will be included in the truncated search results; and wherein the number m is a number that is greater than or equal to 2. 23. One or more computer-readable media of claim 18 , the method further comprising outputting, by the rating component, a request to obtain a rating for a most-linked object of the result of the search query. | 0.601145 |
9,305,545 | 20 | 21 | 20. A non-transitory computer-readable medium having instructions which when executed on a computer perform a method comprising: performing a first speech recognition process for converting a plurality of speech signals into a plurality of words; receiving classification criteria for a primary application; classifying the plurality of words to identify a vocabulary application group that the plurality of words belongs to by performing a first classification process based on using a confidence score for each one of the plurality of words and the classification criteria; upon determining that one or more words are unrecognized based on the classifying, receiving additional classification criteria for one or more unrecognized words for multiple secondary vocabulary applications, wherein the multiple secondary vocabulary applications comprise application specific vocabularies; classifying the one or more unrecognized words to identify a vocabulary application group that the one or more unrecognized words belong to by performing a second classification process based on using a plurality of confidence scores for each unrecognized word and the additional received classification criteria; and upon determining a match for the one or more unrecognized words, performing a second speech recognition process for converting at least a portion of the plurality of speech signals to a plurality of recognized words. | 20. A non-transitory computer-readable medium having instructions which when executed on a computer perform a method comprising: performing a first speech recognition process for converting a plurality of speech signals into a plurality of words; receiving classification criteria for a primary application; classifying the plurality of words to identify a vocabulary application group that the plurality of words belongs to by performing a first classification process based on using a confidence score for each one of the plurality of words and the classification criteria; upon determining that one or more words are unrecognized based on the classifying, receiving additional classification criteria for one or more unrecognized words for multiple secondary vocabulary applications, wherein the multiple secondary vocabulary applications comprise application specific vocabularies; classifying the one or more unrecognized words to identify a vocabulary application group that the one or more unrecognized words belong to by performing a second classification process based on using a plurality of confidence scores for each unrecognized word and the additional received classification criteria; and upon determining a match for the one or more unrecognized words, performing a second speech recognition process for converting at least a portion of the plurality of speech signals to a plurality of recognized words. 21. The medium of claim 20 , further comprising: receiving the plurality of speech signals using an electronic device, wherein a primary vocabulary application is used for converting the plurality of speech signals into the plurality of words; and receiving the additional classification criteria for multiple secondary vocabulary applications for the one or more unrecognized words. | 0.5 |
9,208,324 | 17 | 18 | 17. The one or more non-transitory computer readable storage mediums of claim 16 , further comprising, performing a correlation of one or more tasks results with said one or more scan attack templates to generate a subsequent set of tasks. | 17. The one or more non-transitory computer readable storage mediums of claim 16 , further comprising, performing a correlation of one or more tasks results with said one or more scan attack templates to generate a subsequent set of tasks. 18. The one or more non-transitory computer readable storage mediums of claim 17 , further comprising assigning said subsequent set of tasks to said user based on said one or more steps. | 0.5 |
8,572,021 | 1 | 8 | 1. A method comprising: receiving a plurality of medical documents, the plurality of medical documents including a first set of medical documents in a first format and a second set of medical documents in a second format, wherein the first format is an image-based format and the second format is in a structured data format, and wherein the structured data format is in a non-image text data organized by fields and respective values; determining a schema, the schema including a plurality of categories determined based on an expected structural content in the first set of medical documents or second set of medical documents; determining indices from the plurality of categories to be used for tagging the first set of medical documents and the second set of medical documents when converted into the image-based format based on a review of an organizing principle to which a common set of descriptors can be identified to tag and organize images of the first set of medical documents and the second set of medical documents; converting the non-image text data of the second set of medical documents into images in the image-based format based on the determined indices, wherein the second format is removed in the conversion and content included in each image is determined based on the determined indices applying to the fields and respective values; indexing images of the first medical documents and the images of the second medical documents in the image-based format by associating the determined indices based on the schema with content determined from the first and second medical documents; and storing the images of the first set of medical documents and the images of the second set of medical documents in the image-based format with the indices to allow searching of both the first set of medical documents and the second set of medical documents together based on a search query. | 1. A method comprising: receiving a plurality of medical documents, the plurality of medical documents including a first set of medical documents in a first format and a second set of medical documents in a second format, wherein the first format is an image-based format and the second format is in a structured data format, and wherein the structured data format is in a non-image text data organized by fields and respective values; determining a schema, the schema including a plurality of categories determined based on an expected structural content in the first set of medical documents or second set of medical documents; determining indices from the plurality of categories to be used for tagging the first set of medical documents and the second set of medical documents when converted into the image-based format based on a review of an organizing principle to which a common set of descriptors can be identified to tag and organize images of the first set of medical documents and the second set of medical documents; converting the non-image text data of the second set of medical documents into images in the image-based format based on the determined indices, wherein the second format is removed in the conversion and content included in each image is determined based on the determined indices applying to the fields and respective values; indexing images of the first medical documents and the images of the second medical documents in the image-based format by associating the determined indices based on the schema with content determined from the first and second medical documents; and storing the images of the first set of medical documents and the images of the second set of medical documents in the image-based format with the indices to allow searching of both the first set of medical documents and the second set of medical documents together based on a search query. 8. The method of claim 1 , further comprising storing the second set of medical documents with an active link to view specific data in the structured data format in the second set of medical documents for enabling access to the structured data. | 0.709524 |
8,321,224 | 2 | 3 | 2. The method of claim 1 , further including: using results of the similarity tests to map at least part of the second language phonemes to sets of phonemes of the first language by: assigning respective scores to results of the similarity tests; and mapping one or more of the second language phonemes to a set of mapping phonemes of the first language, the set of mapping phonemes being selected from the candidate mapping phonemes as a function of the scores; and including the first language sets of phonemes resulting from the mapping in a stream of phonemes of the first language representative of the text to produce a resulting stream of phonemes that are used to generate a speech signal. | 2. The method of claim 1 , further including: using results of the similarity tests to map at least part of the second language phonemes to sets of phonemes of the first language by: assigning respective scores to results of the similarity tests; and mapping one or more of the second language phonemes to a set of mapping phonemes of the first language, the set of mapping phonemes being selected from the candidate mapping phonemes as a function of the scores; and including the first language sets of phonemes resulting from the mapping in a stream of phonemes of the first language representative of the text to produce a resulting stream of phonemes that are used to generate a speech signal. 3. The method of claim 2 , wherein the phoneme of the second language, which is mapped to a set of mapping phonemes of the first language, is selected from: a set of phonemes of the first language including three, two, or one phonemes of the first language, or an empty set, whereby no phoneme is included in the resulting stream for the phoneme in the second language. | 0.578767 |
8,782,613 | 11 | 12 | 11. A system comprising: memory operable to store a catalog of generic code statements that have each been determined to be an inefficiently coded statement, each generic code statement being a particular source code statement; one or more data processing apparatuses operable to interact with the memory and to perform operations comprising: receiving actual source code for a computer program, the actual source code comprising a plurality of code statements; without executing the computer program, matching the generic code statements against the actual source code to identify first code statements of the code statements of the actual source code that are each one of the generic code statements and that may potentially cause performance issues when the computer program is executed; executing the computer program; while the computer program is being executed, monitoring execution of a compiled version of the specific code statements to identify code statements of the actual source code that are actually causing performance issues, as second code statements, the second code statements identified without consideration of and not taking into account the first code statements that are identified, such that at least one second code statement is not a first code statement; after the computer program has been executed, matching the first code statements that may potentially cause performance issues that are identical to the second code statements that actually caused performance issues, as third code statements, such that at least one first code statement and at least one second code statement are not third code statements; and indicating to a user just the third code statements within the computer program as candidate code statements of the specific code statements of the computer program for optimization, such that the first code statements and the second code statements that are not third code statements are not indicated to the user, wherein the catalog of generic code statements comprises: a statement that increases execution time of a given computer program; a statement that increases processor utilization when the given computer program is executed; a statement that decreases system stability when the given computer program is executed; a statement that decreases system availability when the given computer program is executed; and a statement that decreases system response time when the given computer program is executed. | 11. A system comprising: memory operable to store a catalog of generic code statements that have each been determined to be an inefficiently coded statement, each generic code statement being a particular source code statement; one or more data processing apparatuses operable to interact with the memory and to perform operations comprising: receiving actual source code for a computer program, the actual source code comprising a plurality of code statements; without executing the computer program, matching the generic code statements against the actual source code to identify first code statements of the code statements of the actual source code that are each one of the generic code statements and that may potentially cause performance issues when the computer program is executed; executing the computer program; while the computer program is being executed, monitoring execution of a compiled version of the specific code statements to identify code statements of the actual source code that are actually causing performance issues, as second code statements, the second code statements identified without consideration of and not taking into account the first code statements that are identified, such that at least one second code statement is not a first code statement; after the computer program has been executed, matching the first code statements that may potentially cause performance issues that are identical to the second code statements that actually caused performance issues, as third code statements, such that at least one first code statement and at least one second code statement are not third code statements; and indicating to a user just the third code statements within the computer program as candidate code statements of the specific code statements of the computer program for optimization, such that the first code statements and the second code statements that are not third code statements are not indicated to the user, wherein the catalog of generic code statements comprises: a statement that increases execution time of a given computer program; a statement that increases processor utilization when the given computer program is executed; a statement that decreases system stability when the given computer program is executed; a statement that decreases system availability when the given computer program is executed; and a statement that decreases system response time when the given computer program is executed. 12. The system of claim 11 , wherein the operations further comprise: receiving optimization instructions for the third code statements as to how to rectify the performance issues caused by the third code statements; modifying the actual source code for the computer program in accordance with the optimization instructions; and validating the actual source code as has been modified. | 0.5 |
8,626,753 | 9 | 10 | 9. A method comprising: receiving at least one search criteria from a first user; identifying multiple portions of indexed content, each respective portion of indexed content related to at least one characteristic of the search criteria, each respective portion of indexed content referencing metadata; determining a relevance of each respective portion of indexed content to the first user who provided the search criteria, the relevance based on second user feedback associated with an online version of the portion of indexed content comprising: identifying a first rating of the second user providing the first user with second user feedback associated with an online version of a first portion of the multiple portions of the indexed content wherein the first rating is indicative of a degree to which a third user agrees with the second user feedback; ranking the multiple portions of indexed content according to their respective relevance to the search criteria of the first user; and creating a search result based on ranking the multiple portions of indexed content. | 9. A method comprising: receiving at least one search criteria from a first user; identifying multiple portions of indexed content, each respective portion of indexed content related to at least one characteristic of the search criteria, each respective portion of indexed content referencing metadata; determining a relevance of each respective portion of indexed content to the first user who provided the search criteria, the relevance based on second user feedback associated with an online version of the portion of indexed content comprising: identifying a first rating of the second user providing the first user with second user feedback associated with an online version of a first portion of the multiple portions of the indexed content wherein the first rating is indicative of a degree to which a third user agrees with the second user feedback; ranking the multiple portions of indexed content according to their respective relevance to the search criteria of the first user; and creating a search result based on ranking the multiple portions of indexed content. 10. The method as in claim 9 , wherein determining the relevance of each respective portion of indexed content to the search criteria of first user further comprises identifying a second rating of the second user providing the second user feedback associated with an online version of the first portion of the multiple portions of indexed content wherein the second rating is indicative of a degree to which the third user agrees with the second user feedback. | 0.5 |
9,332,380 | 16 | 20 | 16. One or more computer-readable media storing computer-executable instructions that, when executed by one or more processors, instruct the one or more processors to perform acts comprising: receiving, from a user device, a first string including one or more characters; determining a geographic area associated with the user device; identifying a geographic word database corresponding to the geographic area; matching the first string with a second string of the geographic word database corresponding to the geographic area; and determining, based on the geographic word database, a phrase corresponding to the second string, wherein the phrase includes one or more words, and the phrase is different than the second string. | 16. One or more computer-readable media storing computer-executable instructions that, when executed by one or more processors, instruct the one or more processors to perform acts comprising: receiving, from a user device, a first string including one or more characters; determining a geographic area associated with the user device; identifying a geographic word database corresponding to the geographic area; matching the first string with a second string of the geographic word database corresponding to the geographic area; and determining, based on the geographic word database, a phrase corresponding to the second string, wherein the phrase includes one or more words, and the phrase is different than the second string. 20. The one or more computer-readable media of claim 16 , wherein the acts further comprise presenting the phrase. | 0.81962 |
9,069,916 | 1 | 4 | 1. A computer-implemented method for model selection, the computer-implemented method comprising: (a) providing an ensemble of reservoir models for a reservoir that define an input uncertainty space; (b) inputting a target number of representative models and one or more target percentiles of output variables that the representative models are to approximate; (c) selecting the representative models from the ensemble of reservoir models that match the one or more target percentiles of output variables while maximizing the spread between the selected representative models in the input uncertainty space, wherein selecting the representative models from the ensemble of reservoir models comprises solving a single constrained minimax optimization problem, and wherein the single constrained minimax optimization problem is represented mathematically as: for i = 1: nTrials for j = 1: P X j = arg rand X j ∈ C { ( max k min l y k j - y _ k l y _ k l ) < ɛ } ∀ k = 1, . . . , M: l = 1, . . . , P − j + 1 sub to: ∀ q = j − 1, . . . , 1 nnz(prctile(Y j ) == prctile(Y q )) = 0 end end; and (d) modeling a behavior of the reservoir using the selected representative models. | 1. A computer-implemented method for model selection, the computer-implemented method comprising: (a) providing an ensemble of reservoir models for a reservoir that define an input uncertainty space; (b) inputting a target number of representative models and one or more target percentiles of output variables that the representative models are to approximate; (c) selecting the representative models from the ensemble of reservoir models that match the one or more target percentiles of output variables while maximizing the spread between the selected representative models in the input uncertainty space, wherein selecting the representative models from the ensemble of reservoir models comprises solving a single constrained minimax optimization problem, and wherein the single constrained minimax optimization problem is represented mathematically as: for i = 1: nTrials for j = 1: P X j = arg rand X j ∈ C { ( max k min l y k j - y _ k l y _ k l ) < ɛ } ∀ k = 1, . . . , M: l = 1, . . . , P − j + 1 sub to: ∀ q = j − 1, . . . , 1 nnz(prctile(Y j ) == prctile(Y q )) = 0 end end; and (d) modeling a behavior of the reservoir using the selected representative models. 4. The computer-implemented method of claim 1 , wherein the single constrained minimax optimization problem is solved using a greedy method with randomization. | 0.600503 |
10,163,074 | 5 | 8 | 5. A computer-implemented method comprising: analyzing a digital communication to or from a user; identifying, via a processor, text in a body text of the digital communication corresponding to a schedulable event, by comparison of words in the text to predefined words designated as identifying schedulable events; determining if the schedulable event conflicts with already scheduled events in a user calendar; and responsive to a determination that no conflict exists, scheduling schedulable event in the user calendar. | 5. A computer-implemented method comprising: analyzing a digital communication to or from a user; identifying, via a processor, text in a body text of the digital communication corresponding to a schedulable event, by comparison of words in the text to predefined words designated as identifying schedulable events; determining if the schedulable event conflicts with already scheduled events in a user calendar; and responsive to a determination that no conflict exists, scheduling schedulable event in the user calendar. 8. The method of claim 5 wherein the communication is a social networking message. | 0.775956 |
8,629,940 | 1 | 2 | 1. A method for setting media device operation preferences in a media device, the method comprising: receiving streamed program content at the media device having a program of interest therein, wherein the program of interest includes at least a video portion, a native language audio portion and a foreign language audio portion; detecting, at a remote control signal detector residing in the media device, a remote control communication signal transmitted from a remote control, wherein the remote control communication signal includes a unique identifier that identifies the transmitting remote control; identifying, at the media device, the remote control based on the unique identifier in the detected remote control communication signal; determining a language preference that is associated with the identified transmitting remote control based on the unique identifier; and selecting, at the media device, one of the native language audio portion and the foreign language audio portion based on the determined language preference. | 1. A method for setting media device operation preferences in a media device, the method comprising: receiving streamed program content at the media device having a program of interest therein, wherein the program of interest includes at least a video portion, a native language audio portion and a foreign language audio portion; detecting, at a remote control signal detector residing in the media device, a remote control communication signal transmitted from a remote control, wherein the remote control communication signal includes a unique identifier that identifies the transmitting remote control; identifying, at the media device, the remote control based on the unique identifier in the detected remote control communication signal; determining a language preference that is associated with the identified transmitting remote control based on the unique identifier; and selecting, at the media device, one of the native language audio portion and the foreign language audio portion based on the determined language preference. 2. The method of claim 1 , further comprising: presenting the selected one of the native language audio portion and the foreign language audio portion in response to receiving the remote control communication signal from the transmitting remote control and based on the determined language preference; and concurrently presenting the video portion with the selected one of the native language audio portion and the foreign language audio portion. | 0.688112 |
10,120,911 | 17 | 20 | 17. A non-transitory computer-readable medium having program code recorded thereon for analyzing data, the program code being executed by a processor and comprising: program code to generate, by an entity, a query based at least in part on a topic of interest; program code to execute the query on a plurality of data sources, at least one of the plurality of data sources comprising at least one of customer information, health related information, or a combination thereof; program code to select, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; program code to monitor, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; program code to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; program code to determine an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; program code to determine a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; program code to dynamically adjust the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; program code to analyze, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; program code to establish a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; program code to transmit, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and program code to receive, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. | 17. A non-transitory computer-readable medium having program code recorded thereon for analyzing data, the program code being executed by a processor and comprising: program code to generate, by an entity, a query based at least in part on a topic of interest; program code to execute the query on a plurality of data sources, at least one of the plurality of data sources comprising at least one of customer information, health related information, or a combination thereof; program code to select, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; program code to monitor, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; program code to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; program code to determine an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; program code to determine a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; program code to dynamically adjust the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; program code to analyze, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; program code to establish a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; program code to transmit, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and program code to receive, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. 20. The non-transitory computer-readable medium of claim 17 , in which the two-way communication channel comprises at least one of short message service (SMS), click-to-voice, interactive voice response (IVR), e-mail, phone, Internet protocol, message board, social media, digital communication, or a combination thereof. | 0.503096 |
9,811,584 | 13 | 16 | 13. A non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code executable to cause a processor to perform a method for operating an information retrieval system, the method comprising: receiving, via a processor, a search query from a user, wherein the search query comprises a plurality of keywords; calculating, via the processor, relevance to a plurality of documents on the basis of the plurality of keywords and an influence set for each keyword, wherein the relevance is calculated a mathematical product of: a number of keywords in a search query in a document; a frequency of a keyword appearing in the document; a proportion of documents containing the keyword; a weight of the keyword; and a weight for a date indicative of when a search index was created; displaying, via the processor, on a display device documents in the order of relevance; displaying on the display device, via the processor, an influence set for each keyword; receiving, via the processor, changes to the displayed influence by the user; and recalculating the relevance, via the processor, on the basis of a change to the influence and displaying on the display device documents in the order of relevance. | 13. A non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code executable to cause a processor to perform a method for operating an information retrieval system, the method comprising: receiving, via a processor, a search query from a user, wherein the search query comprises a plurality of keywords; calculating, via the processor, relevance to a plurality of documents on the basis of the plurality of keywords and an influence set for each keyword, wherein the relevance is calculated a mathematical product of: a number of keywords in a search query in a document; a frequency of a keyword appearing in the document; a proportion of documents containing the keyword; a weight of the keyword; and a weight for a date indicative of when a search index was created; displaying, via the processor, on a display device documents in the order of relevance; displaying on the display device, via the processor, an influence set for each keyword; receiving, via the processor, changes to the displayed influence by the user; and recalculating the relevance, via the processor, on the basis of a change to the influence and displaying on the display device documents in the order of relevance. 16. The computer program product of claim 13 , further comprising displaying on the display device the influence of each keyword in each retrieved document. | 0.670886 |
8,924,419 | 6 | 13 | 6. A method of determining an authoritative author on a subject, the method comprising: receiving a set of documents for each of a plurality of authors, each document having a semantic footprint; receiving user usage data for each of the documents; assigning a rating to each of the documents using the respective semantic footprint and user usage data for each document; determining, when one of the plurality of authors has a plurality of highly rated documents, an intersecting semantic footprint of the plurality of highly rated documents to establish that the one of the plurality of authors is an authoritative author of a subject, determining which documents are highly rated documents is based upon the usage data associated with each of the plurality of documents; receiving a query from a user; determining a semantic footprint of the query; determining that the semantic footprint of the query intersects with the intersecting semantic footprint of the plurality of highly rated documents; determining an extent of the intersection between the semantic footprint of the query and the intersecting semantic footprint associated with the author based upon a ratio of a union of the semantic footprint of the query and the intersecting semantic footprint associated with the author; and providing the user with contact information for the authoritative author based on a determination that the semantic footprint of the query intersects with the semantic footprint of the plurality of highly rated documents, wherein each semantic footprint is a multi-dimensional coordinate based on one or more keywords, entities and annotations, and wherein the intersecting semantic footprint is determined based upon a volume of overlapping areas of the respective multi-dimensional coordinates. | 6. A method of determining an authoritative author on a subject, the method comprising: receiving a set of documents for each of a plurality of authors, each document having a semantic footprint; receiving user usage data for each of the documents; assigning a rating to each of the documents using the respective semantic footprint and user usage data for each document; determining, when one of the plurality of authors has a plurality of highly rated documents, an intersecting semantic footprint of the plurality of highly rated documents to establish that the one of the plurality of authors is an authoritative author of a subject, determining which documents are highly rated documents is based upon the usage data associated with each of the plurality of documents; receiving a query from a user; determining a semantic footprint of the query; determining that the semantic footprint of the query intersects with the intersecting semantic footprint of the plurality of highly rated documents; determining an extent of the intersection between the semantic footprint of the query and the intersecting semantic footprint associated with the author based upon a ratio of a union of the semantic footprint of the query and the intersecting semantic footprint associated with the author; and providing the user with contact information for the authoritative author based on a determination that the semantic footprint of the query intersects with the semantic footprint of the plurality of highly rated documents, wherein each semantic footprint is a multi-dimensional coordinate based on one or more keywords, entities and annotations, and wherein the intersecting semantic footprint is determined based upon a volume of overlapping areas of the respective multi-dimensional coordinates. 13. The method of claim 6 , wherein the query is an active query and the method further comprises: analyzing the active query for its semantic footprint in real time; and refreshing the name of the authoritative author in real time as the user is entering the active query. | 0.5 |
9,704,069 | 1 | 4 | 1. An image processing method for classifying each of a plurality of regions in an image to one of a plurality of predefined classes using classification confidences, the method comprising: a confidence generation step for generating, for each of a plurality of regions of the image, a set of classification confidences, each classification confidence corresponding to one of a plurality of predefined classes and representing the probability of the respective region belonging to the predefined class; and a classification step for classifying the regions in the image wherein for each of the regions for which an obvious match with one of the predefined classes exists based on the classification confidences associated with the region, classifying the region to the respective predefined class based on the classification confidences associated with the region, the method further comprising: a fuzzy region extraction step for extracting and designating as fuzzy regions one or more regions of the plurality of regions, which do not have an obvious match with one of the plurality of predefined classes based on their set of associated classification confidences; and a confidence update step for updating the classification confidence for each such fuzzy region based on the sets of classification confidences associated with adjacent regions thereof, wherein the classification step further classifies the fuzzy regions to respective predefined classes based on the updated classification confidences. | 1. An image processing method for classifying each of a plurality of regions in an image to one of a plurality of predefined classes using classification confidences, the method comprising: a confidence generation step for generating, for each of a plurality of regions of the image, a set of classification confidences, each classification confidence corresponding to one of a plurality of predefined classes and representing the probability of the respective region belonging to the predefined class; and a classification step for classifying the regions in the image wherein for each of the regions for which an obvious match with one of the predefined classes exists based on the classification confidences associated with the region, classifying the region to the respective predefined class based on the classification confidences associated with the region, the method further comprising: a fuzzy region extraction step for extracting and designating as fuzzy regions one or more regions of the plurality of regions, which do not have an obvious match with one of the plurality of predefined classes based on their set of associated classification confidences; and a confidence update step for updating the classification confidence for each such fuzzy region based on the sets of classification confidences associated with adjacent regions thereof, wherein the classification step further classifies the fuzzy regions to respective predefined classes based on the updated classification confidences. 4. The image processing method according to claim 1 , wherein the fuzzy region extraction step comprises: a confidence map generation step for creating a confidence map for each predefined class based on the classification confidence of each region; a region segmentation step for segmenting each confidence map into foreground and background regions of each predefined class based on the confidence maps and predefined thresholds; and a fuzzy region judgment step for judging a region, which is not segmented into the foreground region of one and only one predefined class, to be a fuzzy region. | 0.5 |
8,117,024 | 1 | 3 | 1. A method of processing candidate resumes and job specifications to match candidates with job specifications, comprising providing a database of elements, each element expressed in natural language and at least some of which are associated with a corresponding set of synonymous words or phrases, the elements and the synonymous words or phrases each having a corresponding usage counter; a server receiving candidate resumes and job specifications in electronic form and expressed in natural language, such that candidates skills and experiences are expressed in words and phrases; a server analyzing the natural language expression of the candidate resumes and job specifications to extract elements expressed in candidate resumes and job specifications; a server comparing the extracted elements to the database and updating the usage counters corresponding to the extracted elements such that the relative frequency of the words or phrases expressing skills and experiences is tracked; a server for each extracted element, determining which of the extracted element or the corresponding set of synonymous words or phrases has the highest usage and using the word, phrase or element with the highest usage as a common form for the extracted element and; a server matching a set of candidate resumes with a corresponding job specification by comparing the set of elements expressed in common form for the candidate resumes with the set of elements expressed in common form for the job specification. | 1. A method of processing candidate resumes and job specifications to match candidates with job specifications, comprising providing a database of elements, each element expressed in natural language and at least some of which are associated with a corresponding set of synonymous words or phrases, the elements and the synonymous words or phrases each having a corresponding usage counter; a server receiving candidate resumes and job specifications in electronic form and expressed in natural language, such that candidates skills and experiences are expressed in words and phrases; a server analyzing the natural language expression of the candidate resumes and job specifications to extract elements expressed in candidate resumes and job specifications; a server comparing the extracted elements to the database and updating the usage counters corresponding to the extracted elements such that the relative frequency of the words or phrases expressing skills and experiences is tracked; a server for each extracted element, determining which of the extracted element or the corresponding set of synonymous words or phrases has the highest usage and using the word, phrase or element with the highest usage as a common form for the extracted element and; a server matching a set of candidate resumes with a corresponding job specification by comparing the set of elements expressed in common form for the candidate resumes with the set of elements expressed in common form for the job specification. 3. The method of claim 1 wherein the received candidate resumes are in disparate formats. | 0.865964 |
6,070,176 | 28 | 31 | 28. A computer system according to claim 26, wherein the plurality of hypertext documents are referenced by a plurality of links, and wherein the plurality of hypertext documents comprises a plurality of World Wide Web pages. | 28. A computer system according to claim 26, wherein the plurality of hypertext documents are referenced by a plurality of links, and wherein the plurality of hypertext documents comprises a plurality of World Wide Web pages. 31. A computer system according to claim 28, wherein the instructions are executed by the processor in conjunction with execution of instructions for generating a Web browser. | 0.764785 |
8,914,420 | 6 | 8 | 6. A non-transitory computer readable medium storing one or more sequences of instructions for causing a system to populate a plurality of data structures of a software application written in a programming language, each of said plurality of data structures containing corresponding fields, wherein execution of said one or more sequences of instructions by one or more processors contained in said system causes said system to perform the actions of: receiving an input data, said input data being according to eXtensible Markup Language (XML), wherein said input data contains a plurality of elements, each element having an associated value; receiving a non-XML based schema, said non-XML based schema containing a plurality of schema structures according to said programming language of said software application, said plurality of schema structures specifying a mapping of each of said plurality of elements to respective fields of said plurality of data structures; and setting each of the fields of said plurality of data structures to values associated with an element specified by said mapping, wherein said plurality of data structures contains a first data structure with a first field, wherein said plurality of schema structures contains a first schema structure and a second schema structure, said first schema structure contains a mapping of a first tag text to said first data structure, said second schema structure contains a mapping of a second tag text to said first field, said first schema structure containing a link to said second schema structure to indicate that elements having said second tag text are disposed within elements having said first tag text, wherein said setting comprises: parsing said plurality of elements to identify a hierarchical element having said first tag text and a sub -element at a lower level, said sub-element being disposed within said hierarchical element and having said second tag text, said sub-element having a first value; and storing said first value in said first field of said first data structure, in response to said identifying. | 6. A non-transitory computer readable medium storing one or more sequences of instructions for causing a system to populate a plurality of data structures of a software application written in a programming language, each of said plurality of data structures containing corresponding fields, wherein execution of said one or more sequences of instructions by one or more processors contained in said system causes said system to perform the actions of: receiving an input data, said input data being according to eXtensible Markup Language (XML), wherein said input data contains a plurality of elements, each element having an associated value; receiving a non-XML based schema, said non-XML based schema containing a plurality of schema structures according to said programming language of said software application, said plurality of schema structures specifying a mapping of each of said plurality of elements to respective fields of said plurality of data structures; and setting each of the fields of said plurality of data structures to values associated with an element specified by said mapping, wherein said plurality of data structures contains a first data structure with a first field, wherein said plurality of schema structures contains a first schema structure and a second schema structure, said first schema structure contains a mapping of a first tag text to said first data structure, said second schema structure contains a mapping of a second tag text to said first field, said first schema structure containing a link to said second schema structure to indicate that elements having said second tag text are disposed within elements having said first tag text, wherein said setting comprises: parsing said plurality of elements to identify a hierarchical element having said first tag text and a sub -element at a lower level, said sub-element being disposed within said hierarchical element and having said second tag text, said sub-element having a first value; and storing said first value in said first field of said first data structure, in response to said identifying. 8. The non-transitory computer readable medium of claim 6 , wherein a third schema structure of said plurality of schema structures specifies a mapping of a first attribute text of an element in said plurality of elements to a second field in a second data structure of said plurality of data structures, wherein said parsing identifies a third value associated with said first attribute text in said element of said input data, wherein said storing stores said third value in said second field of said second data structure. | 0.658203 |
8,745,054 | 13 | 15 | 13. A memory device having instructions stored which, when executed on a computing device, cause the computing device to perform operations comprising: determining pairs of words, where each pair of words in the pairs of words comprises a first word and a second word, with both the first word and the second word occurring together in more than one text document of a plurality of text documents; determining, for the each pair of words in the pairs of words: a first word frequency based on appearances of the first word in the plurality of text-documents; a second word frequency based on appearances of the second word in the plurality of text-documents; and a co-occurrence frequency based on appearances of both the first word and the second word together in the plurality of documents; receiving, from a user, an input indicating a maximum number of edges and a maximum number of nodes to include in a graphic presentation; displaying, on a first tab, a statistical view portion of the graphical presentation, the statistical view comprising the first word frequency, the second word frequency, and the co-occurrence frequency; and displaying, on a second tab, an interactive view portion of the graphical presentation, the interactive view portion comprising the first word and the second word each having a color, a size, font, boldness, slant, and a thickness determined based on the first word frequency and the second word frequency, respectively, while edges connect the first word and the second word, the edges having the associated color and the thickness determined based on the co-occurrence frequency of the each pair of words. | 13. A memory device having instructions stored which, when executed on a computing device, cause the computing device to perform operations comprising: determining pairs of words, where each pair of words in the pairs of words comprises a first word and a second word, with both the first word and the second word occurring together in more than one text document of a plurality of text documents; determining, for the each pair of words in the pairs of words: a first word frequency based on appearances of the first word in the plurality of text-documents; a second word frequency based on appearances of the second word in the plurality of text-documents; and a co-occurrence frequency based on appearances of both the first word and the second word together in the plurality of documents; receiving, from a user, an input indicating a maximum number of edges and a maximum number of nodes to include in a graphic presentation; displaying, on a first tab, a statistical view portion of the graphical presentation, the statistical view comprising the first word frequency, the second word frequency, and the co-occurrence frequency; and displaying, on a second tab, an interactive view portion of the graphical presentation, the interactive view portion comprising the first word and the second word each having a color, a size, font, boldness, slant, and a thickness determined based on the first word frequency and the second word frequency, respectively, while edges connect the first word and the second word, the edges having the associated color and the thickness determined based on the co-occurrence frequency of the each pair of words. 15. A memory device of claim 13 , wherein determining the co-occurrence frequency further comprises: determining a measured frequency of the co-occurrence frequency and an expected frequency of the co-occurrence frequency, based the first word frequency and the second word frequency. | 0.5 |
7,778,864 | 1 | 3 | 1. A method for identifying sourcing event metrics for analyzing a supplier, comprising: a metric identification engine of a consumer computing device selecting a first previously created sourcing event, wherein two or more predefined metrics are associated with the previously created sourcing event; the metric identification engine of the consumer computing device providing a comment field and receiving comments related to a metric from the supplier; the metric identification engine of the consumer computing device populating a new sourcing event with the two or more predefined metrics, each predefined metric operable to trigger a response from a potential supplier; the metric identification engine of the consumer computing device further populating the new sourcing event with a second previously created sourcing event, wherein the second previously created sourcing event is used as a predefined metric of the first previously created sourcing event; the metric identification engine of the consumer computing device modifying one or more of the predefined metrics; the metric identification engine of the consumer computing device determining a weighting factor predefined for one or more of the predefined metrics; for each predefined metric having a fixed set of possible responses, the metric identification engine of the consumer computing device determining a points value predefined for one or more possible responses; the metric identification engine of the consumer computing device redefining a points value for one or more of the predefined metrics; for each predefined metric providing for a comment field, the metric identification engine of the consumer computing device assigning a points value to one or more keywords appearing in the comment field before receiving a response to the new sourcing event; a metric evaluation engine of the consumer computing device determining whether previously obtained data associated with the predefined metrics exists for each of a plurality of potential suppliers, and for each potential supplier: the metric evaluation engine of the consumer computing device pre-populating a response field associated with each of the predefined metrics where previously obtained data exists for that predefined metric, the metric evaluation engine of the consumer computing device querying the potential supplier for response data associated with the predefined metrics, the metric evaluation engine of the consumer computing device receiving a second set of response data in response to the query, the metric evaluation engine of the consumer computing device determining the points values earned for each of the predefined metrics based upon the second set of response data, the metric evaluation engine of the consumer computing device multiplying the points values for each of the predefined metrics by the weighting factor for the respective predefined metric to generate a weighted points value for each predefined metric, and the metric evaluation engine of the consumer computing device summing the weighted points values to generate an overall point total; and the metric evaluation engine of the consumer computing device ranking each supplier based on the overall point total and displaying the ranking to a user, whereby the user is able to select a supplier based on the ranking. | 1. A method for identifying sourcing event metrics for analyzing a supplier, comprising: a metric identification engine of a consumer computing device selecting a first previously created sourcing event, wherein two or more predefined metrics are associated with the previously created sourcing event; the metric identification engine of the consumer computing device providing a comment field and receiving comments related to a metric from the supplier; the metric identification engine of the consumer computing device populating a new sourcing event with the two or more predefined metrics, each predefined metric operable to trigger a response from a potential supplier; the metric identification engine of the consumer computing device further populating the new sourcing event with a second previously created sourcing event, wherein the second previously created sourcing event is used as a predefined metric of the first previously created sourcing event; the metric identification engine of the consumer computing device modifying one or more of the predefined metrics; the metric identification engine of the consumer computing device determining a weighting factor predefined for one or more of the predefined metrics; for each predefined metric having a fixed set of possible responses, the metric identification engine of the consumer computing device determining a points value predefined for one or more possible responses; the metric identification engine of the consumer computing device redefining a points value for one or more of the predefined metrics; for each predefined metric providing for a comment field, the metric identification engine of the consumer computing device assigning a points value to one or more keywords appearing in the comment field before receiving a response to the new sourcing event; a metric evaluation engine of the consumer computing device determining whether previously obtained data associated with the predefined metrics exists for each of a plurality of potential suppliers, and for each potential supplier: the metric evaluation engine of the consumer computing device pre-populating a response field associated with each of the predefined metrics where previously obtained data exists for that predefined metric, the metric evaluation engine of the consumer computing device querying the potential supplier for response data associated with the predefined metrics, the metric evaluation engine of the consumer computing device receiving a second set of response data in response to the query, the metric evaluation engine of the consumer computing device determining the points values earned for each of the predefined metrics based upon the second set of response data, the metric evaluation engine of the consumer computing device multiplying the points values for each of the predefined metrics by the weighting factor for the respective predefined metric to generate a weighted points value for each predefined metric, and the metric evaluation engine of the consumer computing device summing the weighted points values to generate an overall point total; and the metric evaluation engine of the consumer computing device ranking each supplier based on the overall point total and displaying the ranking to a user, whereby the user is able to select a supplier based on the ranking. 3. The method of claim 1 , further comprising: adding one or more ad hoc metrics to the new sourcing event; creating a query for each of the one or more ad hoc metrics; creating a points value for one or more potential responses for each of the one or more ad hoc metrics; and creating a weight for one or more of the ad hoc metrics. | 0.5 |
8,599,801 | 8 | 9 | 8. A mobile device for sharing information, comprising: a memory component for storing data; and a processing component for executing data that enables actions, comprising: creating a membership group to a spontaneous event of a gathering of people in a physical location; sharing, during the event, at least one of media content or text message to at least one other mobile device associated with a member of the group, wherein sharing or the media content further comprises enabling automatic posting of the media content to a website associated with the event independent of further actions by the mobile device; enabling a determination of an initial start time or an end time of the spontaneous event based on the sharing of the at least one media content or text message; and determining a revised start time as when a rate of sharing of messages exceeds a threshold during the spontaneous event, wherein the sharing of messages includes messages received from one member of the group that are distributed to other members of the group. | 8. A mobile device for sharing information, comprising: a memory component for storing data; and a processing component for executing data that enables actions, comprising: creating a membership group to a spontaneous event of a gathering of people in a physical location; sharing, during the event, at least one of media content or text message to at least one other mobile device associated with a member of the group, wherein sharing or the media content further comprises enabling automatic posting of the media content to a website associated with the event independent of further actions by the mobile device; enabling a determination of an initial start time or an end time of the spontaneous event based on the sharing of the at least one media content or text message; and determining a revised start time as when a rate of sharing of messages exceeds a threshold during the spontaneous event, wherein the sharing of messages includes messages received from one member of the group that are distributed to other members of the group. 9. The mobile device of claim 8 , wherein enabling a determination of an end time further comprises determining the end time based on a time associated with receiving a last message, wherein the last message is determined based on receiving no messages for a threshold period of time for the group. | 0.616967 |
8,682,648 | 19 | 20 | 19. The storage medium of claim 15 , wherein the threshold value defines a maximum difference of text quality scores for characters to be included in a given subset of characters. | 19. The storage medium of claim 15 , wherein the threshold value defines a maximum difference of text quality scores for characters to be included in a given subset of characters. 20. The storage medium of claim 19 , further comprising adding a neighboring character to the given subset of characters in response to determining that a difference between an average value of text quality scores associated with the characters included in the given subset and a text quality score associated with the neighboring character subset is less than the threshold value. | 0.5 |
10,120,858 | 5 | 11 | 5. A method for analyzing queries, the method comprising: receiving a query from a user; dissecting the query into a plurality of words; assigning an ontological threshold score to each of the plurality of words based on a predetermined ontology; discarding the words having an assigned ontological threshold score that is below a predetermined ontological threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a part of speech associated with the word, said part of speech determination being determined based on the content of the query; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a concept associated with the word, said concept determination being determined based on the content of the query; displaying, to the user, each word having an assigned ontological threshold score that is at or above the predetermined threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, displaying, adjacent to the word, and along a horizontal axis, the determined part of speech associated with the word, and the determined concept associated with the word; and enabling the user to change: each word having an assigned ontological threshold score that is at or above the predetermined threshold; each concept; and each part of speech. | 5. A method for analyzing queries, the method comprising: receiving a query from a user; dissecting the query into a plurality of words; assigning an ontological threshold score to each of the plurality of words based on a predetermined ontology; discarding the words having an assigned ontological threshold score that is below a predetermined ontological threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a part of speech associated with the word, said part of speech determination being determined based on the content of the query; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, determining a concept associated with the word, said concept determination being determined based on the content of the query; displaying, to the user, each word having an assigned ontological threshold score that is at or above the predetermined threshold; for each word having an assigned ontological threshold score that is at or above the predetermined ontological threshold, displaying, adjacent to the word, and along a horizontal axis, the determined part of speech associated with the word, and the determined concept associated with the word; and enabling the user to change: each word having an assigned ontological threshold score that is at or above the predetermined threshold; each concept; and each part of speech. 11. The method of claim 5 , wherein the receiving occurs in response to the user: typing the query into a text entry field; receiving query results; and depressing an analyze query button. | 0.749333 |
9,152,860 | 23 | 25 | 23. The machine-accessible device of claim 22 , further comprising instructions stored thereon that are configured when executed to cause a machine to at: record the image prior to identifying the graphical objects with an image; and normalize the image in relation to previously recorded images of card objects. | 23. The machine-accessible device of claim 22 , further comprising instructions stored thereon that are configured when executed to cause a machine to at: record the image prior to identifying the graphical objects with an image; and normalize the image in relation to previously recorded images of card objects. 25. The machine-accessible device of claim 23 , wherein normalizing includes applying an image transformation to the image including at least one of color adjustment, bit depth adjustment, resolution adjustment, hue adjustment, and saturation adjustment. | 0.5 |
8,082,498 | 1 | 8 | 1. A method for automatically spell-checking dynamically generated web pages, the method comprising: a. receiving, by a server computing device, a request from a client computing device for a web page associated with a workflow; b. generating dynamically, by the server computing device responsive to the received request, a web page containing at least some text; c. intercepting after dynamic generation of the web page by the server computing device and before transmission to the client computing device, by a process executing on the server computing device, the dynamically-generated web page; d. identifying, by the process executing on the server computing device, the at least some text contained in the web page; e. executing, by the process executing on the server computing device, a spelling check on the identified at least some text; and f. outputting, by the process executing on the server computing device, at least one word identified by the spelling check as misspelled. | 1. A method for automatically spell-checking dynamically generated web pages, the method comprising: a. receiving, by a server computing device, a request from a client computing device for a web page associated with a workflow; b. generating dynamically, by the server computing device responsive to the received request, a web page containing at least some text; c. intercepting after dynamic generation of the web page by the server computing device and before transmission to the client computing device, by a process executing on the server computing device, the dynamically-generated web page; d. identifying, by the process executing on the server computing device, the at least some text contained in the web page; e. executing, by the process executing on the server computing device, a spelling check on the identified at least some text; and f. outputting, by the process executing on the server computing device, at least one word identified by the spelling check as misspelled. 8. The method of claim 1 further comprising executing, by the process executing on the server computing device a grammar check on the at least some text. | 0.595238 |
8,891,871 | 1 | 5 | 1. A form recognition apparatus for recognizing a character string existing in an arbitrary table structure in a form, comprising: an image acquisition unit capable of obtaining a digitized form image of the form; a character string recognition unit capable of recognizing a character string existing in the form image obtained by the image acquisition unit; a character string extraction unit capable of extracting a headline wording consisting of a predetermined character string from character strings recognized by the character string recognition unit; a table structure determination unit capable of determining a table structure existing in the form image, on the basis of each of the headline wordings extracted by the character string extraction unit entirely from the form image and arrangement of each of the headline wordings in the form image, when the character string extraction unit extracted plurality of the headline wording; a correspondence relationship specification unit capable of specifying a correspondence relationship between the headline wording and a character string other than the headline wording recognized by the character string recognition unit, using a determination result of the table structure by the table structure determination unit; and a storage unit capable of storing a database in which headline wordings that may appear in a unit table structure being a unit for entering one or more pieces of related data in the form are defined in a hierarchical structure for each unit table structure, wherein the table structure determination unit determines the entire table structure existing in the form image, referring to the database stored in the storage unit. | 1. A form recognition apparatus for recognizing a character string existing in an arbitrary table structure in a form, comprising: an image acquisition unit capable of obtaining a digitized form image of the form; a character string recognition unit capable of recognizing a character string existing in the form image obtained by the image acquisition unit; a character string extraction unit capable of extracting a headline wording consisting of a predetermined character string from character strings recognized by the character string recognition unit; a table structure determination unit capable of determining a table structure existing in the form image, on the basis of each of the headline wordings extracted by the character string extraction unit entirely from the form image and arrangement of each of the headline wordings in the form image, when the character string extraction unit extracted plurality of the headline wording; a correspondence relationship specification unit capable of specifying a correspondence relationship between the headline wording and a character string other than the headline wording recognized by the character string recognition unit, using a determination result of the table structure by the table structure determination unit; and a storage unit capable of storing a database in which headline wordings that may appear in a unit table structure being a unit for entering one or more pieces of related data in the form are defined in a hierarchical structure for each unit table structure, wherein the table structure determination unit determines the entire table structure existing in the form image, referring to the database stored in the storage unit. 5. The form recognition apparatus according to claim 1 , wherein the correspondence relationship specification unit refers to accessory information of a symbol that may be attached to a character string existing as information of the headline wording, defined for each of the headline wordings and specifies the correspondence relationship. | 0.845735 |
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