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4,495,566 | 17 | 18 | 17. Means according to claim 13 wherein the means for processing comprises: means for merging the textual block identifiers in the groups corresponding to the equivalent words in the sets of equivalent words into a further group of textual block identifiers, one of said further groups of textual block identifiers being formed for each set of equivalent words without duplicating therein any of the same textual block identifiers; and means for further processing each said further group of textual block identifers to thereby form said representation of a score. | 17. Means according to claim 13 wherein the means for processing comprises: means for merging the textual block identifiers in the groups corresponding to the equivalent words in the sets of equivalent words into a further group of textual block identifiers, one of said further groups of textual block identifiers being formed for each set of equivalent words without duplicating therein any of the same textual block identifiers; and means for further processing each said further group of textual block identifers to thereby form said representation of a score. 18. Means according to claim 17 wherein said means for further processing comprises: means for merging the textual block identifiers taken from different ones of said further groups of textual block identifiers without duplicating therein any of the same textual block identifiers; and the means for processing comprises means for forming a representation of a score for each a plurality of the textual blocks, each said representation of a score indicating the number of further groups which contain at least one of the textual block identifiers corresponding to such textual block. | 0.5 |
8,630,859 | 1 | 5 | 1. A method comprising: selecting a recursive transition network top level flow controller to yield a selected recursive transition network top level flow controller; selecting available reusable subdialogs below the selected recursive transition network top level flow controller to yield a selected reusable subdialogs; developing a subdialog for each application part not having an available subdialog, to yield developed subdialogs; and testing and deploying (1) a spoken dialog service using the selected recursive transition network top level flow controller, (2) the selected reusable subdialogs, and (3) the developed subdialogs. | 1. A method comprising: selecting a recursive transition network top level flow controller to yield a selected recursive transition network top level flow controller; selecting available reusable subdialogs below the selected recursive transition network top level flow controller to yield a selected reusable subdialogs; developing a subdialog for each application part not having an available subdialog, to yield developed subdialogs; and testing and deploying (1) a spoken dialog service using the selected recursive transition network top level flow controller, (2) the selected reusable subdialogs, and (3) the developed subdialogs. 5. The method of claim 1 , wherein the reusable subdialogs manage mixed-initiative conversations with a user. | 0.742925 |
7,840,546 | 13 | 18 | 13. A system for optimizing data queries for related records in a reliable fashion, having a first computing device communicatively coupled with a second and a third computing device, and communicatively coupled to a first database that stores real-world entity data, having said second computing device communicatively coupled with said first and said third computing device, and communicatively coupled to a second database that stores real-world entity data, having said third computing device communicatively coupled with said first and said second computing device, and communicatively coupled to a third database that stores real-world entity data, a first end-user interface communicatively coupled to said first database, a second end-user interface communicatively coupled to said second database, and a third end-user interface communicatively coupled to said third database, comprising: a hierarchical system of Consolidation Strings for said first database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said first database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said first database, acting as a first data-source node in the overall system, by periodically communicating its Consolidation Strings to external data-source nodes; a hierarchical system of Consolidation Strings for said second database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said second database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said second database, acting as a second data-source node in the overall system, by periodically communicating its Consolidation Strings to external data-source nodes; a hierarchical system of Consolidation Strings for said third database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said third database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said third database, acting as a third data-source node in the overall system, by periodically communicating its Consolidation Strings to external data-source nodes; the capability of said first end-user interface to allow a first end-user to query said first data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said second and third data-source nodes, wherein said first data-source node communicates consolidation information to said second and third external data-source nodes, wherein said consolidation information is applied against a consolidation algorithm in each said second and third data-source nodes, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view; the capability of said second end-user interface to allow a second end-user to query said second data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said first and third data-source nodes, wherein said second data-source node communicates consolidation information to said first and third data-source nodes, wherein said consolidation information is applied against a consolidation algorithm in each said first and third data-source nodes, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view; and the capability of said third end-user interface to allow a third end-user to query said third data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said first and second data-source nodes, wherein said third data-source node communicates consolidation information to said first and second data-source nodes, wherein said consolidation information is applied against a consolidation algorithm in each said first and second data-source nodes, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view. | 13. A system for optimizing data queries for related records in a reliable fashion, having a first computing device communicatively coupled with a second and a third computing device, and communicatively coupled to a first database that stores real-world entity data, having said second computing device communicatively coupled with said first and said third computing device, and communicatively coupled to a second database that stores real-world entity data, having said third computing device communicatively coupled with said first and said second computing device, and communicatively coupled to a third database that stores real-world entity data, a first end-user interface communicatively coupled to said first database, a second end-user interface communicatively coupled to said second database, and a third end-user interface communicatively coupled to said third database, comprising: a hierarchical system of Consolidation Strings for said first database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said first database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said first database, acting as a first data-source node in the overall system, by periodically communicating its Consolidation Strings to external data-source nodes; a hierarchical system of Consolidation Strings for said second database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said second database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said second database, acting as a second data-source node in the overall system, by periodically communicating its Consolidation Strings to external data-source nodes; a hierarchical system of Consolidation Strings for said third database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said third database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said third database, acting as a third data-source node in the overall system, by periodically communicating its Consolidation Strings to external data-source nodes; the capability of said first end-user interface to allow a first end-user to query said first data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said second and third data-source nodes, wherein said first data-source node communicates consolidation information to said second and third external data-source nodes, wherein said consolidation information is applied against a consolidation algorithm in each said second and third data-source nodes, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view; the capability of said second end-user interface to allow a second end-user to query said second data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said first and third data-source nodes, wherein said second data-source node communicates consolidation information to said first and third data-source nodes, wherein said consolidation information is applied against a consolidation algorithm in each said first and third data-source nodes, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view; and the capability of said third end-user interface to allow a third end-user to query said third data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said first and second data-source nodes, wherein said third data-source node communicates consolidation information to said first and second data-source nodes, wherein said consolidation information is applied against a consolidation algorithm in each said first and second data-source nodes, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view. 18. The system for optimizing data queries in claim 13 , wherein said periodic communication of Consolidated Strings to other data-source nodes consists of all of the communication-originating data-source node's Consolidated Strings and source-record identifiers, wherein a data-source node is allowed to deconsolidate if there are changes in the communication-originating data-source node, and a data-source node can query back to querying data-source nodes to get more information. | 0.5 |
9,223,785 | 6 | 7 | 6. The mobile terminal of claim 1 , wherein a check box selectable by a touch input through the touchscreen is included in a thumbnail corresponding to each of the found at least one candidate image and wherein the controller is adapted to determine a candidate image selected via the check box as the selected image. | 6. The mobile terminal of claim 1 , wherein a check box selectable by a touch input through the touchscreen is included in a thumbnail corresponding to each of the found at least one candidate image and wherein the controller is adapted to determine a candidate image selected via the check box as the selected image. 7. The mobile terminal of claim 6 , wherein if a plurality of candidate images are selected through the check boxes, respectively, the controller is adapted to change the selected image in a manner of circulating a plurality of the selected candidate images in each predetermined time interval. | 0.5 |
8,583,087 | 16 | 20 | 16. A computer program product including a non-transitory computer-storage medium having instructions stored thereon for processing data information, such that the instructions, when carried out by a processing device, cause the processing device to perform the operations of: receiving one or more ambiguous characters via a reduced-entry keypad of a wireless phone, the one or more ambiguous characters received as a sequence of numbers input through the reduced-entry keypad, each respective ambiguous character being a number that represents one of at least two disambiguated letters; exchanging at least one of the ambiguous characters with a host by transmitting the sequence of numbers to the host across a wireless network, exchanging the at least one of the ambiguous characters including exchanging the sequence of numbers upon receiving an amount of numbers in the sequence that meets an initial predetermined threshold amount of numbers, and exchanging subsequently received numbers, received as part of the sequence of numbers; receiving, from the host, results that represent disambiguated terms corresponding to the ambiguous characters exchanged with the host; rendering the results in a display of the wireless phone in a manner that enables identification of which of the disambiguated terms will be used upon a received selection of a displayed result; rendering advertisements in the display of the wireless phone, the advertisements responsive to the received sequence of ambiguous characters; receiving, from the host, updated results that represent disambiguated terms corresponding to the subsequently received numbers exchanged with the host; rendering the updated results in the display of the wireless phone; and in response to receiving a selection of one of the disambiguated terms, displaying information corresponding to the selection. | 16. A computer program product including a non-transitory computer-storage medium having instructions stored thereon for processing data information, such that the instructions, when carried out by a processing device, cause the processing device to perform the operations of: receiving one or more ambiguous characters via a reduced-entry keypad of a wireless phone, the one or more ambiguous characters received as a sequence of numbers input through the reduced-entry keypad, each respective ambiguous character being a number that represents one of at least two disambiguated letters; exchanging at least one of the ambiguous characters with a host by transmitting the sequence of numbers to the host across a wireless network, exchanging the at least one of the ambiguous characters including exchanging the sequence of numbers upon receiving an amount of numbers in the sequence that meets an initial predetermined threshold amount of numbers, and exchanging subsequently received numbers, received as part of the sequence of numbers; receiving, from the host, results that represent disambiguated terms corresponding to the ambiguous characters exchanged with the host; rendering the results in a display of the wireless phone in a manner that enables identification of which of the disambiguated terms will be used upon a received selection of a displayed result; rendering advertisements in the display of the wireless phone, the advertisements responsive to the received sequence of ambiguous characters; receiving, from the host, updated results that represent disambiguated terms corresponding to the subsequently received numbers exchanged with the host; rendering the updated results in the display of the wireless phone; and in response to receiving a selection of one of the disambiguated terms, displaying information corresponding to the selection. 20. The computer program product of claim 16 , further comprising rendering updated advertisements in the display of the wireless phone after rendering the updated results, the updated advertisements responsive to the received sequence of ambiguous characters. | 0.802131 |
9,405,797 | 4 | 6 | 4. The method of claim 1 , wherein the improved query includes a reference to a denormalized table, wherein the denormalized table comprises data accessible by the group. | 4. The method of claim 1 , wherein the improved query includes a reference to a denormalized table, wherein the denormalized table comprises data accessible by the group. 6. The method of claim 4 , wherein the denormalized table comprises at least one index on a custom data field associated with the group. | 0.5 |
7,774,353 | 2 | 3 | 2. The method of claim 1 , wherein searching the data store using one or more of the remaining microsearches is performed until a predetermined condition is satisfied. | 2. The method of claim 1 , wherein searching the data store using one or more of the remaining microsearches is performed until a predetermined condition is satisfied. 3. The method of claim 2 , wherein the predetermined condition comprises finding a prespecified number of records that satisfy the query. | 0.5 |
9,940,390 | 12 | 13 | 12. One or more computing devices, comprising: a processor; and storage storing computer-executable instructions which, when executed by the processor, cause the processor to: receive a message provided by a particular user; determine whether the message provided by the particular user includes a selection control command specifying a target media item to be played by media playback equipment, or a non-selection control command; where the message is determined to contain the selection control command: send the message as an input query to a search system, with instruction that the search system is to perform a domain-specific search, receive a query response to the input query from the search system, the query response identifying a top-ranked media item that corresponds to the target media item, and control the media playback equipment to play the top-ranked media item; and where the message is determined to contain the non-selection control command, control the media playback equipment based at least on the non-selection control without interacting with the search system. | 12. One or more computing devices, comprising: a processor; and storage storing computer-executable instructions which, when executed by the processor, cause the processor to: receive a message provided by a particular user; determine whether the message provided by the particular user includes a selection control command specifying a target media item to be played by media playback equipment, or a non-selection control command; where the message is determined to contain the selection control command: send the message as an input query to a search system, with instruction that the search system is to perform a domain-specific search, receive a query response to the input query from the search system, the query response identifying a top-ranked media item that corresponds to the target media item, and control the media playback equipment to play the top-ranked media item; and where the message is determined to contain the non-selection control command, control the media playback equipment based at least on the non-selection control without interacting with the search system. 13. The one or more computing devices of claim 12 , wherein the computer-executable instructions further cause the processor to: provide one or more instances of a collaborative user interface presentation for use by respective users in a group of users, including the particular user. | 0.5 |
9,710,431 | 1 | 13 | 1. A method for transforming narrative content into structured output that defines where individual information resides within the output, the method comprising the steps of: receiving narrative content; scanning the narrative content using a natural language processing engine to identify at least one section and at least one clinical assertion within that section; extracting information from the narrative content, wherein the extracted information includes clinical assertions and contextual information; and identifying one or more clinical assertion elements which define a clinical assertion and assigning a clinical assertion element label to at least one clinical assertion element of the one or more clinical assertion elements based on a clinical model, wherein the label assigned to the at least one clinical assertion element is selected from a predetermined list, wherein the list is predetermined based on a clinical assertion type. | 1. A method for transforming narrative content into structured output that defines where individual information resides within the output, the method comprising the steps of: receiving narrative content; scanning the narrative content using a natural language processing engine to identify at least one section and at least one clinical assertion within that section; extracting information from the narrative content, wherein the extracted information includes clinical assertions and contextual information; and identifying one or more clinical assertion elements which define a clinical assertion and assigning a clinical assertion element label to at least one clinical assertion element of the one or more clinical assertion elements based on a clinical model, wherein the label assigned to the at least one clinical assertion element is selected from a predetermined list, wherein the list is predetermined based on a clinical assertion type. 13. The method of claim 1 , wherein property groups assigned to a clinical assertion are determined by a clinical assertion type. | 0.756604 |
8,027,438 | 28 | 32 | 28. A non-transitory computer-readable storage medium storing a computer program for translating electronic messages sent from a first party to a second different party, the computer program, when executed by a computer processor, performing: receiving an electronic message from the first party in a source language; determining whether the source language of the electronic message that has been received is similar to a preferred destination language; translating the electronic message that has been received into the preferred destination language when the source language is not similar to the preferred destination language, wherein translating includes determining the preferred destination language, wherein determining the preferred destination language includes determining a preferred operating system language of a computing device of the second different party; providing an option to the second different party to translate the electronic message that has been received from the preferred destination language into a different language, the different language being different than the source language and the preferred destination language, and sending at the destination location a reply electronic message in the preferred destination language to the first party; wherein the electronic message from the first party received at the destination location is translated; further comprising: including an indication that the received message has been translated; wherein the indication is one of a label, a symbol, a color of text, and a background of the message. | 28. A non-transitory computer-readable storage medium storing a computer program for translating electronic messages sent from a first party to a second different party, the computer program, when executed by a computer processor, performing: receiving an electronic message from the first party in a source language; determining whether the source language of the electronic message that has been received is similar to a preferred destination language; translating the electronic message that has been received into the preferred destination language when the source language is not similar to the preferred destination language, wherein translating includes determining the preferred destination language, wherein determining the preferred destination language includes determining a preferred operating system language of a computing device of the second different party; providing an option to the second different party to translate the electronic message that has been received from the preferred destination language into a different language, the different language being different than the source language and the preferred destination language, and sending at the destination location a reply electronic message in the preferred destination language to the first party; wherein the electronic message from the first party received at the destination location is translated; further comprising: including an indication that the received message has been translated; wherein the indication is one of a label, a symbol, a color of text, and a background of the message. 32. The non-transitory computer-readable medium of claim 28 , wherein the translating the electronic message occurs before the message is sent. | 0.787202 |
9,319,444 | 1 | 2 | 1. A method of font data streaming in relation to font data transmissions, the method comprising steps as follows: subdividing a portion of a media stream into data segments, the media stream including character data and font data; analyzing, by a server and independent of a first receiving device, text content of a data segment to determine any required fonts and an initial character set coverage for that data segment; for each required font, generating and storing into memory of the server a font subset that comprises only glyphs necessary for the initial character set coverage; after initiating transmission of the media stream to the first receiving device, transmitting from the server the font subset of the respective data segment to the first receiving device; and initiating transmission of a subsequent font subset that comprises additional glyphs for character coverage of a subsequent data segment that has not been previously sent, wherein the subsequent font subset is determined by comparing character set coverage for the subsequent data segment to any previously sent font subset; wherein said steps reduce redundancy in font data transmissions through reducing total number of glyphs provided in one or more subsequent font subsets determined for subsequent data segments of the media stream being transmitted to said first receiving device. | 1. A method of font data streaming in relation to font data transmissions, the method comprising steps as follows: subdividing a portion of a media stream into data segments, the media stream including character data and font data; analyzing, by a server and independent of a first receiving device, text content of a data segment to determine any required fonts and an initial character set coverage for that data segment; for each required font, generating and storing into memory of the server a font subset that comprises only glyphs necessary for the initial character set coverage; after initiating transmission of the media stream to the first receiving device, transmitting from the server the font subset of the respective data segment to the first receiving device; and initiating transmission of a subsequent font subset that comprises additional glyphs for character coverage of a subsequent data segment that has not been previously sent, wherein the subsequent font subset is determined by comparing character set coverage for the subsequent data segment to any previously sent font subset; wherein said steps reduce redundancy in font data transmissions through reducing total number of glyphs provided in one or more subsequent font subsets determined for subsequent data segments of the media stream being transmitted to said first receiving device. 2. The method of claim 1 , wherein each data segment represents a unit of data or a collection of multiple different units of data including video, audio, subtitles, and fonts. | 0.886305 |
8,938,508 | 8 | 12 | 8. A non-transitory computer-readable storage medium storing executable computer program instructions for detecting spam email messages, the computer program instructions comprising instructions for: collecting attributes of a web site to which an email address was submitted; collecting attributes of an email message sent to the email address; identifying a degree of correlation between at least one of the collected attributes of the web site and at least one of the collected attributes of the email message, the identifying comprising using a classifier to analyze the at least one collected attribute of the web site and the at least one collected attribute of the email message, wherein the analysis is based at least in part on a plurality of weights describing different values that represent the relative importances of the collected attributes of the web site and email message, wherein the classifier is generated by training on training data describing attributes of training web sites to which email addresses were submitted and legitimate emails received responsive to the submissions of the email addresses to the training web sites, generating the classifier comprising: generating feature vectors from the training data, the feature vectors having features describing the attributes of the training web sites and having features describing the attributes of the legitimate emails received responsive to the submissions of the email addresses to the training web sites; and training the classifier using the feature vectors, the training causing the classifier to learn weights describing relative importances of the features in recognizing when email messages are received in response to email addresses submitted to web sites; and determining whether the email message is spam responsive at least in part to the degree of correlation, a stronger correlation indicating a decreased likelihood that the email message is spam. | 8. A non-transitory computer-readable storage medium storing executable computer program instructions for detecting spam email messages, the computer program instructions comprising instructions for: collecting attributes of a web site to which an email address was submitted; collecting attributes of an email message sent to the email address; identifying a degree of correlation between at least one of the collected attributes of the web site and at least one of the collected attributes of the email message, the identifying comprising using a classifier to analyze the at least one collected attribute of the web site and the at least one collected attribute of the email message, wherein the analysis is based at least in part on a plurality of weights describing different values that represent the relative importances of the collected attributes of the web site and email message, wherein the classifier is generated by training on training data describing attributes of training web sites to which email addresses were submitted and legitimate emails received responsive to the submissions of the email addresses to the training web sites, generating the classifier comprising: generating feature vectors from the training data, the feature vectors having features describing the attributes of the training web sites and having features describing the attributes of the legitimate emails received responsive to the submissions of the email addresses to the training web sites; and training the classifier using the feature vectors, the training causing the classifier to learn weights describing relative importances of the features in recognizing when email messages are received in response to email addresses submitted to web sites; and determining whether the email message is spam responsive at least in part to the degree of correlation, a stronger correlation indicating a decreased likelihood that the email message is spam. 12. The computer-readable storage medium of claim 8 , wherein the computer program instructions for collecting attributes of an email message sent to the email address comprise instructions for: collecting one or more primary attributes describing the email message; and collecting one or more secondary attributes derived from the primary attributes. | 0.505634 |
8,670,978 | 8 | 13 | 8. A topic transition analysis system comprising: a statement trigger string determination unit receiving a primary media stream and one or a plurality of language communication streams (hereinafter, language streams) executed in parallel with the media stream and determining whether or not a certain statement on the one or plurality of language streams has been made newly in response to contents of the media stream; and one or a plurality of topic similarity calculation unit calculating a topic similarity between the statement and a media stream at and around the time when the statement is made and a topic similarity between the statement and a group of statements made immediately before the statement, wherein the statement trigger string determination unit determines a string having a higher topic similarity to be a string that has triggered the statement. | 8. A topic transition analysis system comprising: a statement trigger string determination unit receiving a primary media stream and one or a plurality of language communication streams (hereinafter, language streams) executed in parallel with the media stream and determining whether or not a certain statement on the one or plurality of language streams has been made newly in response to contents of the media stream; and one or a plurality of topic similarity calculation unit calculating a topic similarity between the statement and a media stream at and around the time when the statement is made and a topic similarity between the statement and a group of statements made immediately before the statement, wherein the statement trigger string determination unit determines a string having a higher topic similarity to be a string that has triggered the statement. 13. The topic transition analysis system according to claim 8 , further comprising: a topic group storage unit classifying a plurality of statements appearing on the language stream into topic groups according to topic similarity and storing the plurality of statements according to the topic groups, wherein the topic similarity calculation unit calculates a topic similarity between the statement and each of the groups accumulated in the topic group storage unit, and wherein the statement trigger string determination unit determines a string having a higher topic similarity to be a string that has triggered the statement. | 0.688183 |
8,463,808 | 1 | 2 | 1. A method comprising: generating a query conceptual graph for a search query, the query conceptual graph comprising: a plurality of graph terms, a graph term representing a concept type; a plurality of conceptual relation nodes that each comprise text describing a relationship between two or more of the plurality of graph terms; and a plurality of arcs that each indicate a direction of the relationship described by the text of a corresponding conceptual relation node of the plurality of conceptual relation nodes; identifying at least one set of conceptually similar terms for at least one graph term of the query conceptual graph, the at least one set of conceptually similar terms mapped to the corresponding concept type represented by the respective at least one graph term; searching a plurality of documents in accordance with a search query based at least in part on the query conceptual graph and on the set of conceptually similar terms; selecting a document from the plurality of documents as a potential match to the search query if, when the query conceptual graph is compared to a document conceptual graph for the document, there is at least one corresponding term associated with the query conceptual graph that matches at least one corresponding term associated with the document conceptual graph, wherein the corresponding term associated with each respective conceptual graph comprises at least one or more of: terms representing a concept type, and terms that are conceptually similar to the terms representing concept types; accessing one or more onomasticons, each onomasticon comprising a list of one or more mappings, each mapping comprising a mapping of a predetermined concept type to a corresponding set of conceptually similar terms; and validating that the potential match is a valid match if a set of conceptually similar terms of the query conceptual graph, and a set of conceptually similar terms of the document conceptual graph that is associated with the potentially matching document, map to the same concept type in one or more onomasticons. | 1. A method comprising: generating a query conceptual graph for a search query, the query conceptual graph comprising: a plurality of graph terms, a graph term representing a concept type; a plurality of conceptual relation nodes that each comprise text describing a relationship between two or more of the plurality of graph terms; and a plurality of arcs that each indicate a direction of the relationship described by the text of a corresponding conceptual relation node of the plurality of conceptual relation nodes; identifying at least one set of conceptually similar terms for at least one graph term of the query conceptual graph, the at least one set of conceptually similar terms mapped to the corresponding concept type represented by the respective at least one graph term; searching a plurality of documents in accordance with a search query based at least in part on the query conceptual graph and on the set of conceptually similar terms; selecting a document from the plurality of documents as a potential match to the search query if, when the query conceptual graph is compared to a document conceptual graph for the document, there is at least one corresponding term associated with the query conceptual graph that matches at least one corresponding term associated with the document conceptual graph, wherein the corresponding term associated with each respective conceptual graph comprises at least one or more of: terms representing a concept type, and terms that are conceptually similar to the terms representing concept types; accessing one or more onomasticons, each onomasticon comprising a list of one or more mappings, each mapping comprising a mapping of a predetermined concept type to a corresponding set of conceptually similar terms; and validating that the potential match is a valid match if a set of conceptually similar terms of the query conceptual graph, and a set of conceptually similar terms of the document conceptual graph that is associated with the potentially matching document, map to the same concept type in one or more onomasticons. 2. The method of claim 1 , the generating the query conceptual graph for the search query further comprising: generating the query conceptual graph in accordance with one or more query terms of the search query. | 0.745169 |
9,530,229 | 9 | 12 | 9. A system for presenting facts, comprising: one or more processors; and memory storing one or more programs to be executed by the one or more processors, the one or more programs comprising instructions for: receiving responsive objects from a fact repository responsive to a search query submitted to the fact repository by a user, wherein a respective responsive object has associated facts, wherein a respective fact includes an attribute field indicating an attribute, a value field describing the indicated attribute; presenting the responsive objects to an end-user in a first user interface, wherein the first user interface displays each responsive object with one or more representative facts, the representative facts selected based on a metric that includes an importance score and a confidence score; saving a subset of the responsive objects as a user-identified collection responsive to selection of the objects in the subset by the user for inclusion in the user-identified collection; presenting the subset of the responsive objects to the end-user in a second user-interface, the second user interface including initial facts for the subset of the responsive objects, the initial facts being attributes most common among the subset of the responsive objects; receiving an end-user-selection of a first attribute of the initial facts displayed in the second user interface, the selection indicating an intent from the end-user to graph values of facts having the first attribute for responsive objects; automatically, without end-user interaction, determining a type of graph showing the values for the first attribute that best facilitates interpretation of the values by the end-user; automatically, without end-user interaction, generating the determined type of graph for objects in the user-identified collection; and presenting via the user interface the determined type of graph. | 9. A system for presenting facts, comprising: one or more processors; and memory storing one or more programs to be executed by the one or more processors, the one or more programs comprising instructions for: receiving responsive objects from a fact repository responsive to a search query submitted to the fact repository by a user, wherein a respective responsive object has associated facts, wherein a respective fact includes an attribute field indicating an attribute, a value field describing the indicated attribute; presenting the responsive objects to an end-user in a first user interface, wherein the first user interface displays each responsive object with one or more representative facts, the representative facts selected based on a metric that includes an importance score and a confidence score; saving a subset of the responsive objects as a user-identified collection responsive to selection of the objects in the subset by the user for inclusion in the user-identified collection; presenting the subset of the responsive objects to the end-user in a second user-interface, the second user interface including initial facts for the subset of the responsive objects, the initial facts being attributes most common among the subset of the responsive objects; receiving an end-user-selection of a first attribute of the initial facts displayed in the second user interface, the selection indicating an intent from the end-user to graph values of facts having the first attribute for responsive objects; automatically, without end-user interaction, determining a type of graph showing the values for the first attribute that best facilitates interpretation of the values by the end-user; automatically, without end-user interaction, generating the determined type of graph for objects in the user-identified collection; and presenting via the user interface the determined type of graph. 12. The system of claim 9 , wherein a meaning of a fact being graphed is one consideration in automatically determining of the type of graph that best facilitates interpretation of the facts by the end-user. | 0.523041 |
8,930,305 | 1 | 7 | 1. An adaptive information processing system for updating product documentation and an associated knowledge base specific to multiple automotive vehicular product lines, the system comprising: an adaptive service system interactively and iteratively receiving original data from a data source, the data source including the following: a product documentation source, a field data processing source, a warranty analysis source and a logistics source and disseminating integrated data to the product documentation source, field data source, warranty analysis source and logistics source, the integrated data including the original data therein; a processor associated with the adaptive service system configured to integrate the original data from the product documentation source, the field data processing source, the warranty analysis source and the logistics source without manual input, and to produce integrated data and update the associated knowledge base, wherein the integrated data is communicated to the product documentation source, the field data processing source, the logistics source and the warranty analysis source, wherein the original data is correlated to at least one time factor in a data warehouse resident in the processor; and wherein the integrated data communicated to the product documentation source is included in adaptive documentation and reporting, and the integrated data communicated to the field data processing source is included in automated search tools and in dynamic guidance for trouble-shooting, integrated data communicated to the logistic source is included in parts order information and parts management systems, and the integrated data communicated to the warranty analysis source is included in root-cause identification and early warning forecasts. | 1. An adaptive information processing system for updating product documentation and an associated knowledge base specific to multiple automotive vehicular product lines, the system comprising: an adaptive service system interactively and iteratively receiving original data from a data source, the data source including the following: a product documentation source, a field data processing source, a warranty analysis source and a logistics source and disseminating integrated data to the product documentation source, field data source, warranty analysis source and logistics source, the integrated data including the original data therein; a processor associated with the adaptive service system configured to integrate the original data from the product documentation source, the field data processing source, the warranty analysis source and the logistics source without manual input, and to produce integrated data and update the associated knowledge base, wherein the integrated data is communicated to the product documentation source, the field data processing source, the logistics source and the warranty analysis source, wherein the original data is correlated to at least one time factor in a data warehouse resident in the processor; and wherein the integrated data communicated to the product documentation source is included in adaptive documentation and reporting, and the integrated data communicated to the field data processing source is included in automated search tools and in dynamic guidance for trouble-shooting, integrated data communicated to the logistic source is included in parts order information and parts management systems, and the integrated data communicated to the warranty analysis source is included in root-cause identification and early warning forecasts. 7. The system of claim 1 , wherein the original data is associated with product parts management or product parts order. | 0.89882 |
8,374,850 | 1 | 2 | 1. An apparatus comprising a processor and a memory storing a computer program, the memory and computer program being configured to, with the processor, cause the apparatus to at least: receive text input data; cause the text input data to be displayed; cause a precursor to be defined as one or more words; reference a dictionary containing a plurality of entries, each said entry including an index, and a candidate word; select a list of n-number of candidate words from said dictionary whose index matches the precursor, where n≧1; either: in an instance in which m>n and the precursor comprises two or more words: cause n-number of candidate words from said list of candidate words to be displayed, cause the precursor to be shortened by causing one or more words to be deleted from the precursor, select a supplemental list of candidate words from said dictionary whose index matches the shortened precursor, and cause m−n number or less of said supplemental candidate words to be displayed; or, in an instance in which n>m: cause the precursor to be lengthened by causing one or more words to be added to the precursor, select an alternate list of candidate words from said dictionary whose index matches the lengthened precursor, and cause m-number or less of candidate words from the alternate list to be displayed; and cause a prompt to be displayed, the prompt enabling a user to either select one of the displayed candidate words or enter a desired word; wherein m comprises a maximum number of candidate words capable of being caused to be displayed. | 1. An apparatus comprising a processor and a memory storing a computer program, the memory and computer program being configured to, with the processor, cause the apparatus to at least: receive text input data; cause the text input data to be displayed; cause a precursor to be defined as one or more words; reference a dictionary containing a plurality of entries, each said entry including an index, and a candidate word; select a list of n-number of candidate words from said dictionary whose index matches the precursor, where n≧1; either: in an instance in which m>n and the precursor comprises two or more words: cause n-number of candidate words from said list of candidate words to be displayed, cause the precursor to be shortened by causing one or more words to be deleted from the precursor, select a supplemental list of candidate words from said dictionary whose index matches the shortened precursor, and cause m−n number or less of said supplemental candidate words to be displayed; or, in an instance in which n>m: cause the precursor to be lengthened by causing one or more words to be added to the precursor, select an alternate list of candidate words from said dictionary whose index matches the lengthened precursor, and cause m-number or less of candidate words from the alternate list to be displayed; and cause a prompt to be displayed, the prompt enabling a user to either select one of the displayed candidate words or enter a desired word; wherein m comprises a maximum number of candidate words capable of being caused to be displayed. 2. The apparatus according to claim 1 , wherein said apparatus is caused to, in an initial state, before receiving any text entry, causing the precursor to be initialized by defining the precursor as a predefined word. | 0.793951 |
9,842,194 | 10 | 11 | 10. The system according to claim 9 , wherein the parameter model function is represented by y ( t ) = [ v ( T ) ∫ e { - k 2 ( t - T ) } dt ] [ f v ( 1 - f v ) K 1 ] , wherein y(t) is the image data, v(t) is a spillover activity, and k2 is an efflux value. | 10. The system according to claim 9 , wherein the parameter model function is represented by y ( t ) = [ v ( T ) ∫ e { - k 2 ( t - T ) } dt ] [ f v ( 1 - f v ) K 1 ] , wherein y(t) is the image data, v(t) is a spillover activity, and k2 is an efflux value. 11. The system according to claim 10 , wherein the one or more non-linear terms of the derived model function include values of k2. | 0.5 |
9,594,837 | 2 | 3 | 2. The method of claim 1 , wherein the objective function is further based on relevance of the search results to one or more of the related queries. | 2. The method of claim 1 , wherein the objective function is further based on relevance of the search results to one or more of the related queries. 3. The method of claim 2 , wherein the objective function is further based on relevance of the search results to the query. | 0.5 |
9,798,806 | 10 | 11 | 10. A system comprising: a processor; a storage medium for tangibly storing thereon program logic for execution by the processor, the stored program logic comprising: document identifying logic executed by the processor for identifying documents relating to a search category; document analyzing logic executed by the processor for analyzing the documents to determine internal statistical content; interestingness tracking logic executed by the processor for tracking users' interestingness data for the documents, where the tracking of the users' interestingness data comprises tracking user interaction with each document clicked through from a search result page, the tracking of the user interaction with each document comprising determining a user interaction data group including one or more of measuring how fast a user reads the each document based on page scroll speed and average reading time based on length of the each document, whether the user chose to cut and paste a portion of the document for further reading, whether the user bookmarked the each document, or combinations thereof; first query term identifying logic executed by the processor for identifying first query terms from the documents; second query term tracking logic executed by the processor for tracking second query terms specified by the users; interest tracking logic executed by the processor for tracking users' indication of interest in pairs of query terms; query suggestion tracking logic executed by the processor for tracking a query suggestion selected from a plurality of query suggestions and obtained from the first query terms, the second query terms, and the users' indication of interest in pairs of query terms; search results web page generating logic executed by the processor for generating the search results page from the interaction with the each document and documents comprising a search result in the identified documents, ordered in a determined order, wherein the search results page comprises the plurality of query suggestions. | 10. A system comprising: a processor; a storage medium for tangibly storing thereon program logic for execution by the processor, the stored program logic comprising: document identifying logic executed by the processor for identifying documents relating to a search category; document analyzing logic executed by the processor for analyzing the documents to determine internal statistical content; interestingness tracking logic executed by the processor for tracking users' interestingness data for the documents, where the tracking of the users' interestingness data comprises tracking user interaction with each document clicked through from a search result page, the tracking of the user interaction with each document comprising determining a user interaction data group including one or more of measuring how fast a user reads the each document based on page scroll speed and average reading time based on length of the each document, whether the user chose to cut and paste a portion of the document for further reading, whether the user bookmarked the each document, or combinations thereof; first query term identifying logic executed by the processor for identifying first query terms from the documents; second query term tracking logic executed by the processor for tracking second query terms specified by the users; interest tracking logic executed by the processor for tracking users' indication of interest in pairs of query terms; query suggestion tracking logic executed by the processor for tracking a query suggestion selected from a plurality of query suggestions and obtained from the first query terms, the second query terms, and the users' indication of interest in pairs of query terms; search results web page generating logic executed by the processor for generating the search results page from the interaction with the each document and documents comprising a search result in the identified documents, ordered in a determined order, wherein the search results page comprises the plurality of query suggestions. 11. The system of claim 10 , further comprising logic operable to combine the internal statistical content and users interestingness data to select documents of relevance and order of presentation of the selected documents in response to receiving the current query. | 0.5625 |
10,146,829 | 10 | 11 | 10. A computer implemented method, comprising: receiving, from a user device, an indication of a user event that includes data indicating a context of the user device, wherein: the user event comprises an indication that the user is accessing a search engine input in a user interface, and the user has not provided to the user interface a query input; and the context is independent of a query input at the user device and describes circumstances of the of the user device at the time of the user event; accessing the data describing context clusters and context cluster probabilities, wherein each context cluster includes query inputs based, in part, on the input context for each of the query inputs and the content described by each query input, and each context cluster probability is indicative of a probability that at least one query input that belongs to the context cluster and provided for an input context of the context cluster will be selected by the user; selecting as a selected context cluster, based on the context cluster probabilities for each of the context clusters and the context of the user device, a context cluster for selection input by the user device; and in response to the selection, providing, to the user device, data that causes the user device to display a context cluster selection input that indicates the selected context cluster for user selection. | 10. A computer implemented method, comprising: receiving, from a user device, an indication of a user event that includes data indicating a context of the user device, wherein: the user event comprises an indication that the user is accessing a search engine input in a user interface, and the user has not provided to the user interface a query input; and the context is independent of a query input at the user device and describes circumstances of the of the user device at the time of the user event; accessing the data describing context clusters and context cluster probabilities, wherein each context cluster includes query inputs based, in part, on the input context for each of the query inputs and the content described by each query input, and each context cluster probability is indicative of a probability that at least one query input that belongs to the context cluster and provided for an input context of the context cluster will be selected by the user; selecting as a selected context cluster, based on the context cluster probabilities for each of the context clusters and the context of the user device, a context cluster for selection input by the user device; and in response to the selection, providing, to the user device, data that causes the user device to display a context cluster selection input that indicates the selected context cluster for user selection. 11. The computer implemented method of claim 10 , wherein each context cluster probability is based on respective probabilities of entry of the query inputs that belong to the context cluster. | 0.748691 |
8,949,250 | 1 | 12 | 1. A method comprising, by a computing device: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a relationship between the two nodes and establishing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; generating a plurality of cards, each card comprising a suggested query referencing a query-domain associated with the online social network and one or more query-filters, wherein each query-filter references one or more nodes of the plurality of nodes or one or more edges of the plurality of edges of the social graph, each card further comprising one or more search results corresponding to the suggested query, each search result referencing a second node of the plurality of second nodes matching the suggested query of the card; calculating a user-engagement score for each card based on one or more user-engagement factors, the user-engagement score for each card measuring a probability the first user will engage with the card; and sending each card having a user-engagement score greater than a user-engagement threshold score to the first user for display on a page currently accessed by the first user. | 1. A method comprising, by a computing device: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a relationship between the two nodes and establishing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; generating a plurality of cards, each card comprising a suggested query referencing a query-domain associated with the online social network and one or more query-filters, wherein each query-filter references one or more nodes of the plurality of nodes or one or more edges of the plurality of edges of the social graph, each card further comprising one or more search results corresponding to the suggested query, each search result referencing a second node of the plurality of second nodes matching the suggested query of the card; calculating a user-engagement score for each card based on one or more user-engagement factors, the user-engagement score for each card measuring a probability the first user will engage with the card; and sending each card having a user-engagement score greater than a user-engagement threshold score to the first user for display on a page currently accessed by the first user. 12. The method of claim 1 , further comprising determining whether the first user is a tourist with respect to a current location of the first user based on a comparison of the current location with demographic information of the first user. | 0.628086 |
8,285,702 | 22 | 24 | 22. The method as claimed in claim 21 , further including: performing a top-k dominant competitor analysis by determining any web-page in the domain, not belonging to said web-site, that is ranked higher than all said web-site for at least k important terms, where k is an integer. | 22. The method as claimed in claim 21 , further including: performing a top-k dominant competitor analysis by determining any web-page in the domain, not belonging to said web-site, that is ranked higher than all said web-site for at least k important terms, where k is an integer. 24. The method as claimed in claim 22 , further comprising: modifying said web-site's content based on said ranked results; simulating said modified web-site's findability; and determining from said simulating whether said modified web-site's findability has improved. | 0.769759 |
7,599,917 | 1 | 2 | 1. A computer readable storage medium having stored thereon computer-executable instructions for ranking a plurality of documents in a network, wherein said computer-executable instructions when executed by the computer perform a method of generating search results in response to a search query, the method comprising: storing document information in memory, the document information identifying the plurality of documents in the network, the plurality of documents including authoritative documents and non-authoritative documents, the authoritative documents including at least a first authoritative document and a second authoritative document, and the non-authoritative documents including at least a first non-authoritative document; storing link information in the memory, the link information identifying links among the plurality of documents; computing click distance values for each of the non-authoritative documents to the authoritative documents, the click distance values including at least a first click distance value that is a function of a number of links that need to be followed to create a path from the first non-authoritative document to the first authoritative document and a second click distance value that is a function of a number of links that need to be followed to create a path from the first non-authoritative document to the second authoritative document; computing biased click distance values for each of the non-authoritative documents in the network to the authoritative documents, wherein the biased click distance values include at least a first biased click distance value that is a function of a lesser of the first and second click distances; receiving the search query including at least one search term; executing the search query to generate a list of the plurality of documents that include the at least one search term, the list of the plurality of documents including an identifier of the first non-authoritative document; ranking the list of the plurality of documents that include the at least one search term using a ranking function that comprises one or more query-independent components, wherein at least one query-independent component includes a biased click distance parameter that takes into account the biased click distance values, including the first biased click distance value; and outputting the ranked search results according to the ranking. | 1. A computer readable storage medium having stored thereon computer-executable instructions for ranking a plurality of documents in a network, wherein said computer-executable instructions when executed by the computer perform a method of generating search results in response to a search query, the method comprising: storing document information in memory, the document information identifying the plurality of documents in the network, the plurality of documents including authoritative documents and non-authoritative documents, the authoritative documents including at least a first authoritative document and a second authoritative document, and the non-authoritative documents including at least a first non-authoritative document; storing link information in the memory, the link information identifying links among the plurality of documents; computing click distance values for each of the non-authoritative documents to the authoritative documents, the click distance values including at least a first click distance value that is a function of a number of links that need to be followed to create a path from the first non-authoritative document to the first authoritative document and a second click distance value that is a function of a number of links that need to be followed to create a path from the first non-authoritative document to the second authoritative document; computing biased click distance values for each of the non-authoritative documents in the network to the authoritative documents, wherein the biased click distance values include at least a first biased click distance value that is a function of a lesser of the first and second click distances; receiving the search query including at least one search term; executing the search query to generate a list of the plurality of documents that include the at least one search term, the list of the plurality of documents including an identifier of the first non-authoritative document; ranking the list of the plurality of documents that include the at least one search term using a ranking function that comprises one or more query-independent components, wherein at least one query-independent component includes a biased click distance parameter that takes into account the biased click distance values, including the first biased click distance value; and outputting the ranked search results according to the ranking. 2. The computer readable storage medium of claim 1 , wherein the method further comprises assigning assigned biased click distance values to the authoritative documents. | 0.724756 |
8,458,179 | 1 | 6 | 1. A computer-executed method for augmenting a privacy policy, the method comprising: obtaining a set of training documents and a seed keyword associated with the privacy policy; extracting a candidate keyword from the training documents; issuing at least one query comprising the candidate keyword to a corpus; receiving a set of result documents; evaluating an inference strength between the candidate keyword and a respective seed keyword, wherein evaluating the inference strength comprises evaluating a ratio between the number of search hits from a query containing both the candidate keyword and the respective seed keyword, and the number of search hits from a query containing only the candidate keyword; determining that the evaluated inference strength is greater than a predetermined threshold ratio; responsive to the evaluated inference strength being greater than the predetermined threshold ratio, augmenting the privacy policy by associating the candidate keyword with the privacy policy; and applying the augmented privacy policy to a subject document to determine whether the subject document triggers the privacy policy, wherein applying the augmented privacy policy comprises searching the subject document for occurrences of any of the candidate keywords associated with the augmented privacy policy. | 1. A computer-executed method for augmenting a privacy policy, the method comprising: obtaining a set of training documents and a seed keyword associated with the privacy policy; extracting a candidate keyword from the training documents; issuing at least one query comprising the candidate keyword to a corpus; receiving a set of result documents; evaluating an inference strength between the candidate keyword and a respective seed keyword, wherein evaluating the inference strength comprises evaluating a ratio between the number of search hits from a query containing both the candidate keyword and the respective seed keyword, and the number of search hits from a query containing only the candidate keyword; determining that the evaluated inference strength is greater than a predetermined threshold ratio; responsive to the evaluated inference strength being greater than the predetermined threshold ratio, augmenting the privacy policy by associating the candidate keyword with the privacy policy; and applying the augmented privacy policy to a subject document to determine whether the subject document triggers the privacy policy, wherein applying the augmented privacy policy comprises searching the subject document for occurrences of any of the candidate keywords associated with the augmented privacy policy. 6. The method of claim 1 , wherein obtaining the set of training documents comprises: issuing an initial query to a corpus, wherein the initial query includes the seed keyword associated with the privacy policy; and selecting a predetermined number of top-ranking search results of the initial query. | 0.5 |
8,065,116 | 1 | 6 | 1. A method of proofing a design for an apparatus, the method being performed with a computer system having a processor and memory, the method comprising: receiving a CAD object of the apparatus; prompting for a type of casting process for the apparatus to be manufactured with; receiving a response specifying the type of casting process; determining a nominal dimension and a related tolerance from the CAD object; obtaining a first data value from the memory, the first obtained data value being based on the specified type of casting process; obtaining a second data value from the memory, the second obtained data value being based on the specified type of casting process; obtaining a function having a variable; determining a first threshold based on the function, the first obtained data value, and the nominal dimension, the first threshold corresponding to a commercial tolerance threshold; determining a second threshold based on the function, the second obtained data value, and the nominal dimension, the second threshold corresponding to a minimum tolerance threshold; comparing the tolerance with the threshold; comparing the tolerance with the second threshold; and tagging the CAD object based on the comparisons. | 1. A method of proofing a design for an apparatus, the method being performed with a computer system having a processor and memory, the method comprising: receiving a CAD object of the apparatus; prompting for a type of casting process for the apparatus to be manufactured with; receiving a response specifying the type of casting process; determining a nominal dimension and a related tolerance from the CAD object; obtaining a first data value from the memory, the first obtained data value being based on the specified type of casting process; obtaining a second data value from the memory, the second obtained data value being based on the specified type of casting process; obtaining a function having a variable; determining a first threshold based on the function, the first obtained data value, and the nominal dimension, the first threshold corresponding to a commercial tolerance threshold; determining a second threshold based on the function, the second obtained data value, and the nominal dimension, the second threshold corresponding to a minimum tolerance threshold; comparing the tolerance with the threshold; comparing the tolerance with the second threshold; and tagging the CAD object based on the comparisons. 6. The method of claim 1 , further comprising generating a replacement tolerance, and replacing the tolerance with the replacement tolerance. | 0.808424 |
8,713,041 | 6 | 7 | 6. A non-transitory computer readable storage medium comprising a program product which, when executed, is configured to perform an operation for retrieving query results, comprising: receiving a first abstract query comprising at least two logical fields defined by a first data abstraction model comprising a plurality of first logical field definitions mapped to physical fields of a first database in a first device, wherein one or more of the first logical fields definitions associate respective first logical fields to respective concepts of a predefined set of concepts, the concepts being standardized metadata; for each of the at least two logical fields of the first abstract query, determining whether a second data abstraction model comprises a logical field associated with a concept associated with the respective logical field of the abstract query, wherein the second data abstraction model comprises a plurality of second logical field definitions mapping the second logical fields to physical fields of a second database in a second device, wherein one or more of the second logical fields definitions associate respective second logical fields to respective concepts of the predefined set of concepts; and upon determining that the second data abstraction model does not comprise the logical field associated with the concept associated with the respective logical field of the abstract query, modifying the first abstract query to remove the respective logical field from the first abstract query such that the modified first abstract query includes only the at least two logical fields less the removed logical field. | 6. A non-transitory computer readable storage medium comprising a program product which, when executed, is configured to perform an operation for retrieving query results, comprising: receiving a first abstract query comprising at least two logical fields defined by a first data abstraction model comprising a plurality of first logical field definitions mapped to physical fields of a first database in a first device, wherein one or more of the first logical fields definitions associate respective first logical fields to respective concepts of a predefined set of concepts, the concepts being standardized metadata; for each of the at least two logical fields of the first abstract query, determining whether a second data abstraction model comprises a logical field associated with a concept associated with the respective logical field of the abstract query, wherein the second data abstraction model comprises a plurality of second logical field definitions mapping the second logical fields to physical fields of a second database in a second device, wherein one or more of the second logical fields definitions associate respective second logical fields to respective concepts of the predefined set of concepts; and upon determining that the second data abstraction model does not comprise the logical field associated with the concept associated with the respective logical field of the abstract query, modifying the first abstract query to remove the respective logical field from the first abstract query such that the modified first abstract query includes only the at least two logical fields less the removed logical field. 7. The non-transitory computer readable storage medium of claim 6 , wherein the operation further comprises generating a second abstract query based on the first abstract query, wherein the second abstract query comprises one or more of the second logical field definitions of the second data abstraction model. | 0.5 |
8,429,174 | 1 | 2 | 1. A method for searching, comprising: receiving a three dimensional object; searching one or more data stores with the three dimensional object as a first search query; presenting results from the search, wherein the results include an answer set; dynamically receiving modifications for one or more items in the answer set; and re-searching the one or more data stores with the modifications associated with the one or more items as a second search query. | 1. A method for searching, comprising: receiving a three dimensional object; searching one or more data stores with the three dimensional object as a first search query; presenting results from the search, wherein the results include an answer set; dynamically receiving modifications for one or more items in the answer set; and re-searching the one or more data stores with the modifications associated with the one or more items as a second search query. 2. The method of claim 1 further comprising, converting the three dimensional object into a graph skeleton defining a graph data structure, wherein the graph data structure is the first search query. | 0.631481 |
8,627,195 | 8 | 14 | 8. A computer-implemented method for summarizing the differences between network resources, the method comprising: under the control of a network computing component executing on one or more physical computing components of a network computing provider, the physical computing components configured to execute specific instructions, obtaining data regarding a measurement of differences between a plurality of versions of a plurality of network resources, wherein the plurality of network resources are related, and wherein the differences are differences between versions of a single network resource; causing the display of a plurality of objects, each object corresponding to one of the plurality of network resources, wherein each object represents the measurement of differences between the plurality of versions of the corresponding network resource; and causing the display of a plurality of connections, each connection graphically associating two or more objects with each other, wherein each connection represents a shared property of the network resources represented by each of the associated objects. | 8. A computer-implemented method for summarizing the differences between network resources, the method comprising: under the control of a network computing component executing on one or more physical computing components of a network computing provider, the physical computing components configured to execute specific instructions, obtaining data regarding a measurement of differences between a plurality of versions of a plurality of network resources, wherein the plurality of network resources are related, and wherein the differences are differences between versions of a single network resource; causing the display of a plurality of objects, each object corresponding to one of the plurality of network resources, wherein each object represents the measurement of differences between the plurality of versions of the corresponding network resource; and causing the display of a plurality of connections, each connection graphically associating two or more objects with each other, wherein each connection represents a shared property of the network resources represented by each of the associated objects. 14. The computer-implemented method of claim 8 , wherein the shared property comprises one of the subject matter of the content of the network resources, the source of the network resources, the creation date of the network resources, or the edit date of the network resources. | 0.5 |
9,142,219 | 6 | 10 | 6. The method of claim 1 further comprising: determining a set of classifications based on the speaker-specific information; classifying portions of the acoustic input signal into different classifications in the set of classifications; selecting a classification in the set of classifications based on a criterion associated with the classification; and using the classification to determine the set of potential responses. | 6. The method of claim 1 further comprising: determining a set of classifications based on the speaker-specific information; classifying portions of the acoustic input signal into different classifications in the set of classifications; selecting a classification in the set of classifications based on a criterion associated with the classification; and using the classification to determine the set of potential responses. 10. The method of claim 6 wherein classifying portions of the acoustic input signal is not performed until receiving a trigger phrase to activate the speech recognizer. | 0.66129 |
7,743,360 | 1 | 2 | 1. One or more computer-readable storage media having computer-executable instructions for performing a method comprising: in a first pane for a node, presenting a representation of the node and one or more links from the node to other nodes adjacent to the node in a graph data structure; and responsive to activation of one of the links presented in the first pane from the node to a selected node, presenting in a second pane adjacent to the first pane, a representation of the node for the activated link and one or more links from the node for the activated link to other nodes adjacent to the node for the activated link in the graph data structure; wherein in the second pane, the one or more links from the node for the activated link to other nodes comprise a link back to the node of the first pane; and wherein each of the first pane and the second pane further comprises a title of a node the pane represents and an additional description of a node the pane represents. | 1. One or more computer-readable storage media having computer-executable instructions for performing a method comprising: in a first pane for a node, presenting a representation of the node and one or more links from the node to other nodes adjacent to the node in a graph data structure; and responsive to activation of one of the links presented in the first pane from the node to a selected node, presenting in a second pane adjacent to the first pane, a representation of the node for the activated link and one or more links from the node for the activated link to other nodes adjacent to the node for the activated link in the graph data structure; wherein in the second pane, the one or more links from the node for the activated link to other nodes comprise a link back to the node of the first pane; and wherein each of the first pane and the second pane further comprises a title of a node the pane represents and an additional description of a node the pane represents. 2. The one or more computer-readable storage media of claim 1 wherein: the graph data structure represents software items. | 0.67027 |
8,078,453 | 36 | 48 | 36. A method of computer analysis of at least one communication originated from a person, comprising: receiving with a computer the at least one communication with each communication being comprised of a group of words originated by the person; processing a text of the received group of words in each of the received at least one communication with a computer to determine risk posed by the person from an attitude represented by the text of the group of words in each of the at least one communication; and in response to the determined risk posed by the person from the attitude generating with a computer an output communication pertaining to the risk posed by the person from the attitude of the at least one communication. | 36. A method of computer analysis of at least one communication originated from a person, comprising: receiving with a computer the at least one communication with each communication being comprised of a group of words originated by the person; processing a text of the received group of words in each of the received at least one communication with a computer to determine risk posed by the person from an attitude represented by the text of the group of words in each of the at least one communication; and in response to the determined risk posed by the person from the attitude generating with a computer an output communication pertaining to the risk posed by the person from the attitude of the at least one communication. 48. A method in accordance with claim 36 wherein the at least one communication is chat from a chat room. | 0.711538 |
9,336,194 | 1 | 3 | 1. A method comprising: receiving an input string; receiving a regular expression; converting, by a system comprising a hardware processor, the regular expression into a plurality of automata to extract submatches of substrings in the input string, wherein the extracting comprises: using a first automaton of the plurality of automata to determine whether the input string is in a language described by the regular expression, and to process the input string; and using states of the first automaton in a second automaton of the plurality of automata to extract the submatches; and identifying, by the system, a source of an issue in a network in response to the submatches. | 1. A method comprising: receiving an input string; receiving a regular expression; converting, by a system comprising a hardware processor, the regular expression into a plurality of automata to extract submatches of substrings in the input string, wherein the extracting comprises: using a first automaton of the plurality of automata to determine whether the input string is in a language described by the regular expression, and to process the input string; and using states of the first automaton in a second automaton of the plurality of automata to extract the submatches; and identifying, by the system, a source of an issue in a network in response to the submatches. 3. The method of claim 1 , further comprising: implementing the method in a parser. | 0.762857 |
9,152,948 | 1 | 3 | 1. A computer-implemented method of providing a structured topic drift for a displayed set of user comments on an article, the method comprising: determining, using at least one processor, an ordered sequence of topical recommendations based on one or more properties of the displayed set of user comments and user characteristics using a sequential recommendation model, wherein each topical recommendation contains a plurality of user comments; sampling, using the at least one processor, each of the topical recommendations in the ordered sequence to produce a first set of one or more user comments for each of the topical recommendations; appending, using the at least one processor, one by one, the user comments from the first set of one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments; and updating, using the at least one processor, the sequential recommendation model based on a user response to the first set of one or more user comments for each of the topical recommendations; determining, using at least one processor, a second ordered sequence of topical recommendations using the sequential recommendation model; sampling, using the at least one processor, each of the topical recommendations in the second ordered sequence to produce a second set of one or more user comments for each of the topical recommendations; and appending, using the at least one processor, one by one, the second set of one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments. | 1. A computer-implemented method of providing a structured topic drift for a displayed set of user comments on an article, the method comprising: determining, using at least one processor, an ordered sequence of topical recommendations based on one or more properties of the displayed set of user comments and user characteristics using a sequential recommendation model, wherein each topical recommendation contains a plurality of user comments; sampling, using the at least one processor, each of the topical recommendations in the ordered sequence to produce a first set of one or more user comments for each of the topical recommendations; appending, using the at least one processor, one by one, the user comments from the first set of one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments; and updating, using the at least one processor, the sequential recommendation model based on a user response to the first set of one or more user comments for each of the topical recommendations; determining, using at least one processor, a second ordered sequence of topical recommendations using the sequential recommendation model; sampling, using the at least one processor, each of the topical recommendations in the second ordered sequence to produce a second set of one or more user comments for each of the topical recommendations; and appending, using the at least one processor, one by one, the second set of one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments. 3. The method as claimed in claim 1 , wherein determining the ordered sequence of topical recommendations further comprises determining one or more features associated with the structured topic drift using a prediction function in the sequential recommendation model; determining, using the sequential recommendation model, an initial internal state based on the one or more features, wherein the initial internal state is related to the user characteristics and is used to determine the ordered sequence of topical recommendations. | 0.5 |
5,519,867 | 49 | 51 | 49. The apparatus of claim 48, wherein said fault classes comprise a first object-oriented class defining a generic fault, said first class having virtual methods for setting a processor computer program logic and a fault computer program logic to thereby identify said generic fault, said first class representing an abstract base class. | 49. The apparatus of claim 48, wherein said fault classes comprise a first object-oriented class defining a generic fault, said first class having virtual methods for setting a processor computer program logic and a fault computer program logic to thereby identify said generic fault, said first class representing an abstract base class. 51. The apparatus of claim 49, wherein said fault classes comprise an object-oriented class encapsulating information identifying a destination port, a fault message format, and fault types, said object-oriented class comprising methods for enabling said application to specify said destination port, said fault message format, and said fault types, and for enabling said application to instruct said operating system to send messages in said specified fault message format to the specified destination port when said specified fault types occur. | 0.5 |
9,495,376 | 6 | 7 | 6. The method of claim 1 , where extracting from the profile information further comprises: parsing the profile information. | 6. The method of claim 1 , where extracting from the profile information further comprises: parsing the profile information. 7. The method of claim 6 , where parsing the profile information further comprises: utilizing a profile engine to parse the profile information; and utilizing at least one handler to extract the file identification information from the source system. | 0.5 |
7,620,494 | 17 | 24 | 17. An apparatus for displaying driving directions, the apparatus being configured to: access data that describes at least one maneuver to be executed to traverse a route from an origin to a destination; select a portion of the accessed data that describes a particular maneuver, the maneuver including an action and a road; determine a road symbol to associate with the particular maneuver, the road symbol having substantially the same appearance as a road sign used to mark the road involved in the particular maneuver; determine an action symbol to associate with the particular maneuver, the action symbol having substantially the same appearance as a road sign used to identify the action to be performed to execute the particular maneuver; and present both the road symbol and the action symbol to describe the particular maneuver, such that the road symbol and the action symbol describe the particular maneuver. | 17. An apparatus for displaying driving directions, the apparatus being configured to: access data that describes at least one maneuver to be executed to traverse a route from an origin to a destination; select a portion of the accessed data that describes a particular maneuver, the maneuver including an action and a road; determine a road symbol to associate with the particular maneuver, the road symbol having substantially the same appearance as a road sign used to mark the road involved in the particular maneuver; determine an action symbol to associate with the particular maneuver, the action symbol having substantially the same appearance as a road sign used to identify the action to be performed to execute the particular maneuver; and present both the road symbol and the action symbol to describe the particular maneuver, such that the road symbol and the action symbol describe the particular maneuver. 24. The apparatus of claim 17 wherein the action symbol indicates a turn angle involved in the particular maneuver. | 0.744444 |
8,386,465 | 33 | 37 | 33. A method for decreasing the perceived end user latency while interacting with a database, the method comprising: aggregating metadata associated with media in the database, the database stored provided by a digital media server; displaying on a user interface of an endpoint device, a first set of query results, wherein each query result in the displayed first set of query results representing a user selectable object that navigates to another set of query results displayable by the user interface and wherein the endpoint device communicates with the digital media server via at least one of multiple connections between the endpoint device and the digital media server, wherein endpoint device and the digital media server negotiate a number of objects to be presented; performing at least one first predictive background query of the database based on the displayed first set of query results and prior to a user invoking any action within the user interface; receiving and storing the another set of query results for each of the query results in the displayed first set of query results from the at least one first predictive background query; receiving user input at the user interface; generating at least one query based on the user input; comparing the at least one generated query to the at least one first predictive background query; and displaying the another set of query results received from the at least one first predictive background query that correspond to the generated query in response to the at least one first predictive background query encompassing the at least one generated query. | 33. A method for decreasing the perceived end user latency while interacting with a database, the method comprising: aggregating metadata associated with media in the database, the database stored provided by a digital media server; displaying on a user interface of an endpoint device, a first set of query results, wherein each query result in the displayed first set of query results representing a user selectable object that navigates to another set of query results displayable by the user interface and wherein the endpoint device communicates with the digital media server via at least one of multiple connections between the endpoint device and the digital media server, wherein endpoint device and the digital media server negotiate a number of objects to be presented; performing at least one first predictive background query of the database based on the displayed first set of query results and prior to a user invoking any action within the user interface; receiving and storing the another set of query results for each of the query results in the displayed first set of query results from the at least one first predictive background query; receiving user input at the user interface; generating at least one query based on the user input; comparing the at least one generated query to the at least one first predictive background query; and displaying the another set of query results received from the at least one first predictive background query that correspond to the generated query in response to the at least one first predictive background query encompassing the at least one generated query. 37. The method of claim 33 further comprising receiving and storing the result of the at least one generated query of the database and presenting the stored result of the at least one generated background query via the user interface. | 0.746753 |
9,535,883 | 15 | 18 | 15. A non-transitory computer-readable medium, comprising instructions executable on a processor, the instructions causing the processor to perform steps of: receiving a request from a client device for a preview of a native document, the preview representing the native document in a file format other than the file format of the native document; inserting, by a document mapping module in the native document prior to rendering a preview, a set of unique links comprising a uniform resource locator (URL) and each unique link associated with a different word in the native document, the native object comprising a renderable portion of the native document; rendering, by a document rendering module, the native document into a preview of the native document and thereby generating a bounding area for each of the unique links in the set of unique links, the bounding area mapping a page and pixel location on the preview to the native object associated with the unique link; and providing the preview to the client device for display. | 15. A non-transitory computer-readable medium, comprising instructions executable on a processor, the instructions causing the processor to perform steps of: receiving a request from a client device for a preview of a native document, the preview representing the native document in a file format other than the file format of the native document; inserting, by a document mapping module in the native document prior to rendering a preview, a set of unique links comprising a uniform resource locator (URL) and each unique link associated with a different word in the native document, the native object comprising a renderable portion of the native document; rendering, by a document rendering module, the native document into a preview of the native document and thereby generating a bounding area for each of the unique links in the set of unique links, the bounding area mapping a page and pixel location on the preview to the native object associated with the unique link; and providing the preview to the client device for display. 18. The non-transitory computer-readable medium of claim 15 , wherein the unique links are hyperlinks. | 0.910683 |
9,990,420 | 17 | 19 | 17. An apparatus comprising: a processor and a non-transitory computer readable storage medium comprising instructions executable by the processor to: extract text and contextual data from a first screen element selected by a user action, the first screen element being part of a plurality of screen elements that are displayed by an application, wherein the plurality of screen elements correspond to different contextual information and the contextual data extracted from the first screen element including operating system data indicating a type of screen element from which the text is extracted; obtain a plurality of strings of different text data types from the extracted text via a series of analyses; determine a plurality of search types for the plurality of strings based at least on contextual information of the first screen element and the series of analyses, wherein the determined search types are selected from a plurality of different search types that are mapped to respective contextual information of the different contextual information corresponding to the plurality of screen elements; automatically append the determined search types with respective strings from the plurality of strings; automatically generate a relevant search string by combining the determined search types with the respective strings via Boolean logic; and search a database with the relevant search string. | 17. An apparatus comprising: a processor and a non-transitory computer readable storage medium comprising instructions executable by the processor to: extract text and contextual data from a first screen element selected by a user action, the first screen element being part of a plurality of screen elements that are displayed by an application, wherein the plurality of screen elements correspond to different contextual information and the contextual data extracted from the first screen element including operating system data indicating a type of screen element from which the text is extracted; obtain a plurality of strings of different text data types from the extracted text via a series of analyses; determine a plurality of search types for the plurality of strings based at least on contextual information of the first screen element and the series of analyses, wherein the determined search types are selected from a plurality of different search types that are mapped to respective contextual information of the different contextual information corresponding to the plurality of screen elements; automatically append the determined search types with respective strings from the plurality of strings; automatically generate a relevant search string by combining the determined search types with the respective strings via Boolean logic; and search a database with the relevant search string. 19. The apparatus of claim 17 , wherein the non-transitory computer readable storage medium comprising further instructions executable by the processor to: determine if other contextual mapping data for the application associated with the first screen element is mapped to one or more of the plurality of different search types if no search types could be determined for the first screen element from the mappings of the plurality of different search types; and use the mapping associated with the other contextual data of the application if it is determined that mapping exists for the other contextual data. | 0.5 |
9,990,223 | 1 | 4 | 1. A method of improving parallel functional processing, the method including: performing data transformations in a functional processing pipeline running on multiple processors using at least one instance or composition combining each of categorical functions in a group including PairMaker, FreeMonoidReduce, PairABtoAFMB, ReducePairs, and MonoidReduce, wherein: the PairMaker categorical function transforms a free monoid over strings into a free monoid over tuples including at least one key-value pair in each tuple; the FreeMonoidReduce categorical function merges a nested free monoid over tuples into one free monoid over tuples, thereby reducing a nesting depth of the nested free monoid over tuples; the PairABtoAFMB categorical function transforms one element in each tuple of the one free monoid over tuples into list of one element in a free monoid over tuples with an embedded list element; the ReducePairs categorical function merges consecutive tuples of the free monoid over tuples with the embedded list element; and the MonoidReduce categorical function transforms a plurality of list values into a single value based on a parameterized operation. | 1. A method of improving parallel functional processing, the method including: performing data transformations in a functional processing pipeline running on multiple processors using at least one instance or composition combining each of categorical functions in a group including PairMaker, FreeMonoidReduce, PairABtoAFMB, ReducePairs, and MonoidReduce, wherein: the PairMaker categorical function transforms a free monoid over strings into a free monoid over tuples including at least one key-value pair in each tuple; the FreeMonoidReduce categorical function merges a nested free monoid over tuples into one free monoid over tuples, thereby reducing a nesting depth of the nested free monoid over tuples; the PairABtoAFMB categorical function transforms one element in each tuple of the one free monoid over tuples into list of one element in a free monoid over tuples with an embedded list element; the ReducePairs categorical function merges consecutive tuples of the free monoid over tuples with the embedded list element; and the MonoidReduce categorical function transforms a plurality of list values into a single value based on a parameterized operation. 4. The method of claim 1 , wherein the PairMaker creates at least part of the tuples by combining consecutive elements of the free monoid over strings into the tuples. | 0.877566 |
7,676,373 | 1 | 8 | 1. A setting apparatus comprising a caption setting unit for setting a timing of displaying text of speech in synchronization with reproduction of said speech, the text of said speech being predetermined, said caption setting unit comprising: a scenario data obtaining unit for obtaining scenario data representing content of said speech; a speech recognition unit for dividing textual data resulting from recognition of said speech being reproduced to generate a plurality of pieces of recognition data; a character string detection unit for detecting in said scenario data a character string that matches each of said plurality of pieces of recognition data; a character detection unit for detecting a character string that matches the recognition data from said scenario data by detecting a character contained in the recognition data for each recognition data with which said character string detection unit has detected no matching characters string; a display setting unit for setting the display timing of displaying each of the character strings contained in said scenario data to the timing at which speech recognized as a piece of recognition data that matches said character string is reproduce; and a reliability calculating unit for calculating a reliability factor that represents a likelihood that each of the plurality of pieces of recognition data matches one character string, wherein said display setting unit generates a setting that, if the calculated reliability factor associated with a first character string to be displayed in two successive character strings among the plurality of character strings in the scenario data is higher than the calculated reliability factor associated with a second character string to be displayed in the two successive character strings, causes a concatenated character string comprising said first character string with said second character string appended to said first character string to be displayed at a time point at which said first character string should be displayed. | 1. A setting apparatus comprising a caption setting unit for setting a timing of displaying text of speech in synchronization with reproduction of said speech, the text of said speech being predetermined, said caption setting unit comprising: a scenario data obtaining unit for obtaining scenario data representing content of said speech; a speech recognition unit for dividing textual data resulting from recognition of said speech being reproduced to generate a plurality of pieces of recognition data; a character string detection unit for detecting in said scenario data a character string that matches each of said plurality of pieces of recognition data; a character detection unit for detecting a character string that matches the recognition data from said scenario data by detecting a character contained in the recognition data for each recognition data with which said character string detection unit has detected no matching characters string; a display setting unit for setting the display timing of displaying each of the character strings contained in said scenario data to the timing at which speech recognized as a piece of recognition data that matches said character string is reproduce; and a reliability calculating unit for calculating a reliability factor that represents a likelihood that each of the plurality of pieces of recognition data matches one character string, wherein said display setting unit generates a setting that, if the calculated reliability factor associated with a first character string to be displayed in two successive character strings among the plurality of character strings in the scenario data is higher than the calculated reliability factor associated with a second character string to be displayed in the two successive character strings, causes a concatenated character string comprising said first character string with said second character string appended to said first character string to be displayed at a time point at which said first character string should be displayed. 8. The setting apparatus according to claim 1 , further comprising a phoneme detection unit for detecting in a phonetic representation of said scenario data a phoneme that matches a phoneme contained in a character in said recognition data for which no matching character has been detected by said character detection unit, wherein said character detection unit detects in said scenario data, as a character that matches a character in said recognition data for which a matching phoneme has been detected by said phoneme detection unit, a character containing said phoneme; and said reliability calculating unit produces a lower reliability for a piece of recognition data containing a character for which a matching phoneme has been detected by said phoneme detection unit than the reliability of a piece of recognition data containing a character for which no matching phoneme has been detected by said phoneme detection unit but for which a matching character has been detected by said character detection unit. | 0.5 |
9,990,652 | 23 | 26 | 23. A computer program product comprising a non-transitory computer readable storage medium having instructions encoded thereon that, when executed by a processor, cause the processor to perform steps comprising: receiving a plurality of advertisement requests, each advertising request comprising advertising content and an identification of one or more objects in a social networking system; identifying a viewing user to receive advertising; identifying one or more other users who are connected to the viewing user in the social networking system; identifying a plurality of objects in the social networking system with which the identified one or more other users have interacted; identifying one or more candidate advertisements based on the advertisement requests, where each candidate advertisement is associated with an advertisement request that identified at least one of the identified objects with which the identified one or more other users have interacted; selecting a candidate advertisement for display to the viewing user; generating by a processor a social advertisement that comprises (1) the advertising content for the advertisement request associated with the selected candidate advertisement and (2) a social story that describes an interaction between a user who is connected with the viewing user and an object in the social networking system; and sending the social advertisement for display to the viewing user. | 23. A computer program product comprising a non-transitory computer readable storage medium having instructions encoded thereon that, when executed by a processor, cause the processor to perform steps comprising: receiving a plurality of advertisement requests, each advertising request comprising advertising content and an identification of one or more objects in a social networking system; identifying a viewing user to receive advertising; identifying one or more other users who are connected to the viewing user in the social networking system; identifying a plurality of objects in the social networking system with which the identified one or more other users have interacted; identifying one or more candidate advertisements based on the advertisement requests, where each candidate advertisement is associated with an advertisement request that identified at least one of the identified objects with which the identified one or more other users have interacted; selecting a candidate advertisement for display to the viewing user; generating by a processor a social advertisement that comprises (1) the advertising content for the advertisement request associated with the selected candidate advertisement and (2) a social story that describes an interaction between a user who is connected with the viewing user and an object in the social networking system; and sending the social advertisement for display to the viewing user. 26. The computer program product of claim 23 , wherein at least one of the advertising requests inherently identifies one or more objects in a social networking system, and wherein the method further comprises identifying one or more objects in the social networking system based on the advertising content. | 0.631894 |
7,945,662 | 1 | 6 | 1. A computerized method for optimizing a domain name page, the method comprising: receiving a first group of at least one request for a domain name page originating from a first group of at least one device responding to a first group of at least one user; displaying content on the requested domain name page to each of the first group of users, the domain name page including a plurality of keywords and at least one interactive region, each interactive region including a page position identifier and being associated with at least a position weight; tracking user interactions of each of the first group of users with the displayed domain name page, the tracking including identifying one or more of the interactive regions in which the user interactions occur for each of the keywords, and determining a frequency of the user interactions in the corresponding interactive region for each of the keywords; for each of the first group of users, storing the tracked information for at least one particular interaction including the associated position identifier identifying the interactive region on the domain name page in which each of the stored user interactions occurred; receiving at least one request for the domain name page from a second group of at least one user device; and, displaying an updated domain name page on each of the second group of at least one user device, the updated domain name page being updated based on the tracked user interactions, the updating including computing a keyword point for each of the keywords as a function of the frequency of the user interactions for the corresponding keyword for each of the at least one of the interactive regions, and the weight assigned to the corresponding interactive region. | 1. A computerized method for optimizing a domain name page, the method comprising: receiving a first group of at least one request for a domain name page originating from a first group of at least one device responding to a first group of at least one user; displaying content on the requested domain name page to each of the first group of users, the domain name page including a plurality of keywords and at least one interactive region, each interactive region including a page position identifier and being associated with at least a position weight; tracking user interactions of each of the first group of users with the displayed domain name page, the tracking including identifying one or more of the interactive regions in which the user interactions occur for each of the keywords, and determining a frequency of the user interactions in the corresponding interactive region for each of the keywords; for each of the first group of users, storing the tracked information for at least one particular interaction including the associated position identifier identifying the interactive region on the domain name page in which each of the stored user interactions occurred; receiving at least one request for the domain name page from a second group of at least one user device; and, displaying an updated domain name page on each of the second group of at least one user device, the updated domain name page being updated based on the tracked user interactions, the updating including computing a keyword point for each of the keywords as a function of the frequency of the user interactions for the corresponding keyword for each of the at least one of the interactive regions, and the weight assigned to the corresponding interactive region. 6. The method of claim 1 , wherein the frequency of the user interactions is a search frequency indicative of a number of searches conducted based on the particular keyword at the interactive region identified by the position identifier, and the tracking of the user interactions include, for each of the first group of users: storing the search frequency in association with the particular keyword and the associated position identifier. | 0.5 |
7,949,646 | 11 | 20 | 11. An apparatus for extracting elements of information from a website comprising a plurality of web pages, the apparatus comprising: means for identifying a structure associated with the plurality of web pages; means for extracting a plurality of blocks of information from the web pages as a function of the structure, the means for extracting comprising means for examining a number of web pages associated with the website and means for following a number of hyperlinks; means for assigning each block of information in the plurality of blocks of information to a category in a plurality of categories, one of the categories being a task complexity, the information being assigned to the category of task complexity including the number of web pages associated with the website and the number of hyperlinks followed; and means for identifying a plurality of elements of information in each block of information. | 11. An apparatus for extracting elements of information from a website comprising a plurality of web pages, the apparatus comprising: means for identifying a structure associated with the plurality of web pages; means for extracting a plurality of blocks of information from the web pages as a function of the structure, the means for extracting comprising means for examining a number of web pages associated with the website and means for following a number of hyperlinks; means for assigning each block of information in the plurality of blocks of information to a category in a plurality of categories, one of the categories being a task complexity, the information being assigned to the category of task complexity including the number of web pages associated with the website and the number of hyperlinks followed; and means for identifying a plurality of elements of information in each block of information. 20. The apparatus of claim 11 wherein the elements of information comprise contact information. | 0.717262 |
9,898,527 | 12 | 13 | 12. The device as set forth in claim 9 wherein the processor is configured to execute programmed instructions stored in the memory further comprising: parsing the received query to identify one or more new property conditions. | 12. The device as set forth in claim 9 wherein the processor is configured to execute programmed instructions stored in the memory further comprising: parsing the received query to identify one or more new property conditions. 13. The device as set forth in claim 12 wherein the processor is further configured to execute programmed instructions stored in the memory further comprising: determining when one or more of the ontology entities match the at least one of the new property conditions identified in the received query when the identified subject of interest has not been determined to be identified by the parsing; and identifying the one or more of the ontology entities that match the at least one of the new property conditions when the determining indicates the one or more of the ontology entities match the at least one of the new property conditions. | 0.5 |
7,684,068 | 7 | 8 | 7. An email server for performing automatic capture archiving of electronic documents in a network environment, said email server operatively disposed to: generate a copy of each email document transmitted over the network environment, the email document being transmitted in response to a single user input command configured to transmit the email document to a destination; and forward each copy to a document management device, the forwarding of each copy causing the document management device to generate electronic image data for each copy of an email document, the electronic image data being generated in a compressed image format, the forwarding of each copy further causing the generated electronic image data to be stored in the at least one database to perform the capture archiving, the capture archiving being performed without further input from the user notwithstanding the single user input command for transmitting the email document to a destination, the storing of said image data in the at least one database being separate from the transmission of the email document to the destination and transparent to the user, the capture archiving for each email document occurring at substantially a time that the email document is transferred over the network. | 7. An email server for performing automatic capture archiving of electronic documents in a network environment, said email server operatively disposed to: generate a copy of each email document transmitted over the network environment, the email document being transmitted in response to a single user input command configured to transmit the email document to a destination; and forward each copy to a document management device, the forwarding of each copy causing the document management device to generate electronic image data for each copy of an email document, the electronic image data being generated in a compressed image format, the forwarding of each copy further causing the generated electronic image data to be stored in the at least one database to perform the capture archiving, the capture archiving being performed without further input from the user notwithstanding the single user input command for transmitting the email document to a destination, the storing of said image data in the at least one database being separate from the transmission of the email document to the destination and transparent to the user, the capture archiving for each email document occurring at substantially a time that the email document is transferred over the network. 8. The email server of claim 7 , wherein the destination comprises a destination client system. | 0.775943 |
9,589,561 | 10 | 17 | 10. A display apparatus comprising: an input unit configured to receive an uttered voice of a user; a display configured to display a voice recognition result of the uttered voice; a voice processor configured to extract voice information from the uttered voice, compare the voice information to information associated with words in a pronunciation dictionary, and, based on reliabilities associated with the comparing, determine similar words which are similar to words in the uttered voice; and a controller configured to set, as a target word with respect to the uttered voice, a word satisfying a predetermined condition, control the display to display one or both of the target word and a similar word list including one or more of the similar words other than the target word, set an execution command, and adjust a critical value assigned to the similar word set as the execution command from among the plurality of similar words including the target word, wherein, in response to an execution command not being received for a predetermined critical time or in response to a selection command with respect to the target word being received, setting the execution command comprises setting the target word as the execution command. | 10. A display apparatus comprising: an input unit configured to receive an uttered voice of a user; a display configured to display a voice recognition result of the uttered voice; a voice processor configured to extract voice information from the uttered voice, compare the voice information to information associated with words in a pronunciation dictionary, and, based on reliabilities associated with the comparing, determine similar words which are similar to words in the uttered voice; and a controller configured to set, as a target word with respect to the uttered voice, a word satisfying a predetermined condition, control the display to display one or both of the target word and a similar word list including one or more of the similar words other than the target word, set an execution command, and adjust a critical value assigned to the similar word set as the execution command from among the plurality of similar words including the target word, wherein, in response to an execution command not being received for a predetermined critical time or in response to a selection command with respect to the target word being received, setting the execution command comprises setting the target word as the execution command. 17. The apparatus as claimed in claim 10 , wherein the controller is configured to group the plurality of similar words into a similar word group in response to the plurality of similar words which are similar to the uttered voice being determined. | 0.681234 |
7,873,616 | 1 | 13 | 1. A computer-readable medium having stored thereon a set of instructions which when executed perform a method for recommending an item to a user, the method, comprising: defining an ontology as nodes in a graph, the nodes including a scored node and an unscored node, the nodes in the graph representing concepts; wherein, the scored node has an associated score based on a preference of the user for a concept represented by the scored node; using a propagating function and the associated score of the scored node, to determine, for the user, a personalized score of the unscored node in the ontology; wherein, the propagation function determines the personalized score of the unscored node based on a relationship of the unscored node and the scored node in the graph representing the ontology; identifying, for the user, a qualifying concept from the concepts in the ontology for which the personalized scores have been computed, wherein, the qualifying concept that is identified from the concepts, is one that is associated a qualifying score among the personalized scores that have been computed for the concepts at the nodes of the ontology; and selecting the item which is an instance of the qualifying concept to be recommended to the user. | 1. A computer-readable medium having stored thereon a set of instructions which when executed perform a method for recommending an item to a user, the method, comprising: defining an ontology as nodes in a graph, the nodes including a scored node and an unscored node, the nodes in the graph representing concepts; wherein, the scored node has an associated score based on a preference of the user for a concept represented by the scored node; using a propagating function and the associated score of the scored node, to determine, for the user, a personalized score of the unscored node in the ontology; wherein, the propagation function determines the personalized score of the unscored node based on a relationship of the unscored node and the scored node in the graph representing the ontology; identifying, for the user, a qualifying concept from the concepts in the ontology for which the personalized scores have been computed, wherein, the qualifying concept that is identified from the concepts, is one that is associated a qualifying score among the personalized scores that have been computed for the concepts at the nodes of the ontology; and selecting the item which is an instance of the qualifying concept to be recommended to the user. 13. The method of claim 1 further comprising, using upward inference to determine the preference of the user for an unscored concept represented by the unscored node using the scored node using by S(y|x)=αS(x); wherein a is a coefficient of generalization for the scored node, if the unscored node represents a more general concept than the concept represented by the scored node. | 0.535452 |
8,520,812 | 9 | 12 | 9. A computer system for serializing asynchronous communications that are received and played over a plurality of telephone interfaces of users participating in a telephone conference, comprising: a memory storing computer-executable instructions that: receives from a first user first audio as a first audio segment; stores in a queue the first audio segment; plays live for a second user the first audio as the first audio is received; while the first audio is being received, receives from a third user second audio as a second audio segment; stores at the end of at the end of the queue the second audio segment; after the second audio segment is stored at the end of the queue, terminates the first audio segment; after terminating the first audio segment, plays for the first user and the second user the second audio of the second audio segment; and after playing the second audio, receives from the first user third audio as a third audio segment as a resumption of audio of the first user; stores in the queue the third audio segment; wherein the queue contains a serialization of audio segments that are received asynchronously; and a processor that executes the computer-executable instructions stored in the memory. | 9. A computer system for serializing asynchronous communications that are received and played over a plurality of telephone interfaces of users participating in a telephone conference, comprising: a memory storing computer-executable instructions that: receives from a first user first audio as a first audio segment; stores in a queue the first audio segment; plays live for a second user the first audio as the first audio is received; while the first audio is being received, receives from a third user second audio as a second audio segment; stores at the end of at the end of the queue the second audio segment; after the second audio segment is stored at the end of the queue, terminates the first audio segment; after terminating the first audio segment, plays for the first user and the second user the second audio of the second audio segment; and after playing the second audio, receives from the first user third audio as a third audio segment as a resumption of audio of the first user; stores in the queue the third audio segment; wherein the queue contains a serialization of audio segments that are received asynchronously; and a processor that executes the computer-executable instructions stored in the memory. 12. The computer system of claim 9 including instructions that store multiple audio segments in the queue between the first audio segment and the second audio segment and skip over the multiple audio segment to play the second audio segment after the first audio segment is terminated. | 0.5 |
8,073,851 | 1 | 7 | 1. A content searching device which searches content from a content database with a use of a related keyword which is related to a keyword describing content, the content database storing the content for each content attribute showing a classification of the content, and said content searching device comprising: a dictionary database which stores a degree of relevance, among a plurality of keywords, for each related segment indicating a time segment, the plurality of keywords each describing the content which (i) belongs to the classification indicated by the content attribute, and (ii) is included in the related segment; a related segment calculating unit configured to calculate, for each content attribute, a related segment which is defined in order for first content and second content to be included in a same time segment, the related segment being calculated based on whether or not a degree of difference, for each content attribute, calculated out of a plurality of first keywords and a plurality of second keywords meets a predetermined reference value, and the plurality of the first keywords each describing the first content to be stored in said database, and the plurality of the second keywords each describing the second content having been stored in said content database; a dictionary updating unit configured to update the degree of relevance, stored in said dictionary database, regarding the content included in the related segment calculated by said related segment calculating unit, the degree of relevance being updated with a use of the related segment, and the degree of relevance, among the plurality of keywords, being calculated for each content attribute; and an output generating unit configured to generate output information used for outputting, for each related segment, the related keyword relating to a keyword entered by a user, the output information being generated based on the degree of relevance stored in said dictionary database, wherein said related segment calculating unit is configured to calculate (i) a related segment defined by a time segment corresponding to the first content in the case where the degree of difference exceeds the predetermined reference value, and (ii) a related segment defined by a time segment which is a sum of a latest related segment stored in said dictionary database and the time segment corresponding to the first content in the case where the degree of difference is equal to the predetermined reference value or below. | 1. A content searching device which searches content from a content database with a use of a related keyword which is related to a keyword describing content, the content database storing the content for each content attribute showing a classification of the content, and said content searching device comprising: a dictionary database which stores a degree of relevance, among a plurality of keywords, for each related segment indicating a time segment, the plurality of keywords each describing the content which (i) belongs to the classification indicated by the content attribute, and (ii) is included in the related segment; a related segment calculating unit configured to calculate, for each content attribute, a related segment which is defined in order for first content and second content to be included in a same time segment, the related segment being calculated based on whether or not a degree of difference, for each content attribute, calculated out of a plurality of first keywords and a plurality of second keywords meets a predetermined reference value, and the plurality of the first keywords each describing the first content to be stored in said database, and the plurality of the second keywords each describing the second content having been stored in said content database; a dictionary updating unit configured to update the degree of relevance, stored in said dictionary database, regarding the content included in the related segment calculated by said related segment calculating unit, the degree of relevance being updated with a use of the related segment, and the degree of relevance, among the plurality of keywords, being calculated for each content attribute; and an output generating unit configured to generate output information used for outputting, for each related segment, the related keyword relating to a keyword entered by a user, the output information being generated based on the degree of relevance stored in said dictionary database, wherein said related segment calculating unit is configured to calculate (i) a related segment defined by a time segment corresponding to the first content in the case where the degree of difference exceeds the predetermined reference value, and (ii) a related segment defined by a time segment which is a sum of a latest related segment stored in said dictionary database and the time segment corresponding to the first content in the case where the degree of difference is equal to the predetermined reference value or below. 7. The content searching device according to claim 1 , wherein said related segment calculating unit is configured to calculate the related segment according to whether or not a degree of difference meets a predetermined reference value, the degree of difference representing a value where the number of keywords, out of the plurality of the first keywords, which do not overlap with the plurality of the second keywords is divided by the number of the plurality of the second keywords. | 0.629008 |
7,894,596 | 15 | 21 | 15. A system for providing language interpretation, comprising: an incoming call telephonic module that receives an incoming telephone call from a caller speaking a first language, wherein a language interpretation number can be used to place the incoming telephone call to a language interpretation for language interpretation, the incoming call telephonic module being associated with a language interpretation provider, the caller being greeted in the first language by an interpreter associated with the language interpretation provider; and an outgoing call telephonic module that permits the interpreter to telephonically engage an agent representing a first business entity, wherein the first business entity is selected over a second business entity from a group of business entities, wherein the first business entity is a subscriber for a subscription fee to the language interpretation provider for language interpretation for the first business entity, wherein second business entity is not a subscriber for a subscription fee to the language interpretation provider for language interpretation for the second business entity, wherein the agent speaks a second language and the interpreter interprets a conversation between the caller and the agent. | 15. A system for providing language interpretation, comprising: an incoming call telephonic module that receives an incoming telephone call from a caller speaking a first language, wherein a language interpretation number can be used to place the incoming telephone call to a language interpretation for language interpretation, the incoming call telephonic module being associated with a language interpretation provider, the caller being greeted in the first language by an interpreter associated with the language interpretation provider; and an outgoing call telephonic module that permits the interpreter to telephonically engage an agent representing a first business entity, wherein the first business entity is selected over a second business entity from a group of business entities, wherein the first business entity is a subscriber for a subscription fee to the language interpretation provider for language interpretation for the first business entity, wherein second business entity is not a subscriber for a subscription fee to the language interpretation provider for language interpretation for the second business entity, wherein the agent speaks a second language and the interpreter interprets a conversation between the caller and the agent. 21. The system of claim 15 , further comprising an accounting module that establishes a billing that accounts a time count accruing from a time at which the language interpretation telephone call starts until a time at which the interpreter is engaged. | 0.560976 |
8,621,394 | 15 | 17 | 15. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program instructions stored therein, the computer-readable program instructions comprising program instructions configured to cause an apparatus to perform a method comprising: receiving an input indicating a search criteria; determining, by a processor, at least one search result position related to the search criteria; determining a relationship between the at least one search result position and a multi-level map; and causing, based at least in part on the relationship, a level of the map and the at least one search result position to be displayed as a search result position indicator, wherein the displayed search result position indicator is presented in a different manner based at least in part on whether the search result position is on the level of the map that is displayed or is on another level of the map. | 15. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program instructions stored therein, the computer-readable program instructions comprising program instructions configured to cause an apparatus to perform a method comprising: receiving an input indicating a search criteria; determining, by a processor, at least one search result position related to the search criteria; determining a relationship between the at least one search result position and a multi-level map; and causing, based at least in part on the relationship, a level of the map and the at least one search result position to be displayed as a search result position indicator, wherein the displayed search result position indicator is presented in a different manner based at least in part on whether the search result position is on the level of the map that is displayed or is on another level of the map. 17. The computer program product of claim 15 configured to cause an apparatus to perform a method wherein causing the at least one search result position to be displayed further comprises causing the at least one search result position indicator to be displayed in an instance in which the at least one search result position is located within the portion of the map that is displayed. | 0.511421 |
8,248,667 | 12 | 13 | 12. A document management method comprising: storing, in a document storage unit, pieces of document data; storing, in a relationship-information storage unit, relationship information indicating a parent-child relationship between the pieces of document data stored in the document storage unit; selecting a piece of document data from among the pieces of document data stored in the document storage unit as a selected piece of document data; searching for related-document information that is relationship information pertaining to the selected piece of document data; stopping the searching when an upper limit for the relationship information is reached; and creating, from the related-document information retrieved at the searching, a list that indicates a hierarchical relationship between the selected piece of document data and other pieces of document data stored in the document storage unit. | 12. A document management method comprising: storing, in a document storage unit, pieces of document data; storing, in a relationship-information storage unit, relationship information indicating a parent-child relationship between the pieces of document data stored in the document storage unit; selecting a piece of document data from among the pieces of document data stored in the document storage unit as a selected piece of document data; searching for related-document information that is relationship information pertaining to the selected piece of document data; stopping the searching when an upper limit for the relationship information is reached; and creating, from the related-document information retrieved at the searching, a list that indicates a hierarchical relationship between the selected piece of document data and other pieces of document data stored in the document storage unit. 13. The document management method according to claim 12 , further comprising displaying the pieces of document data that are related to the selected piece of document data on a single screen based on the list. | 0.5 |
9,160,548 | 10 | 18 | 10. A system of matching users to user communities, the system comprising: memory for storing event data representing user-generated events that reflect user affinities for particular items represented in the electronic catalog and for storing information about a plurality of user communities, each of which corresponds to a respective subset of the plurality of users and comprises multiple users; and at least one computing device including a processor in communication with the memory, the at least one computing device operative to: identify a first plurality of items that characterize item preferences of a first user community of the plurality of user communities; calculate a degree to which the first plurality of items are related to a set of items in the electronic catalog identified by the first user; and based at least in part on the degree, determine whether to suggest the first user community to the first user. | 10. A system of matching users to user communities, the system comprising: memory for storing event data representing user-generated events that reflect user affinities for particular items represented in the electronic catalog and for storing information about a plurality of user communities, each of which corresponds to a respective subset of the plurality of users and comprises multiple users; and at least one computing device including a processor in communication with the memory, the at least one computing device operative to: identify a first plurality of items that characterize item preferences of a first user community of the plurality of user communities; calculate a degree to which the first plurality of items are related to a set of items in the electronic catalog identified by the first user; and based at least in part on the degree, determine whether to suggest the first user community to the first user. 18. The system of claim 10 , wherein the first user community comprises users having email addresses associated with a particular organization. | 0.846895 |
9,823,824 | 2 | 10 | 2. A method of placing text and/or graphic elements in a digital image product comprising: providing a context and content sensitive adaptable user interface for the text and/or graphic element placement in a digital image product; analyzing the context and content of the digital image product and recognizing a plurality of objects within the digital image product; allowing a user to link the text and/or graphic elements with at least one of the recognized objects within the digital image product; in response to dragging the text and/or graphic elements within a predetermined distance to any of the plurality of recognized objects, dynamically suggesting to the user modifications to at least one attribute of a color, font, size, shape, surround, or background of the text and/or graphic elements in the digital image product based on the analysis of the context and content of the digital image product by the user interface; and as the user drags the text and/or graphic elements, dynamically indicating by the user interface to the user via visual, haptic, or audio feedback text placement options that are available on any given area of the digital image product, wherein the image product areas includes recognized objects and open spaces including template surround areas for composite images, collages, or album pages, or folds, gutters, or borders for post printing converting, folding, trimming, and binding operations. | 2. A method of placing text and/or graphic elements in a digital image product comprising: providing a context and content sensitive adaptable user interface for the text and/or graphic element placement in a digital image product; analyzing the context and content of the digital image product and recognizing a plurality of objects within the digital image product; allowing a user to link the text and/or graphic elements with at least one of the recognized objects within the digital image product; in response to dragging the text and/or graphic elements within a predetermined distance to any of the plurality of recognized objects, dynamically suggesting to the user modifications to at least one attribute of a color, font, size, shape, surround, or background of the text and/or graphic elements in the digital image product based on the analysis of the context and content of the digital image product by the user interface; and as the user drags the text and/or graphic elements, dynamically indicating by the user interface to the user via visual, haptic, or audio feedback text placement options that are available on any given area of the digital image product, wherein the image product areas includes recognized objects and open spaces including template surround areas for composite images, collages, or album pages, or folds, gutters, or borders for post printing converting, folding, trimming, and binding operations. 10. The method of claim 2 wherein a visual or audio linking of the text with image content comprises linking with detected faces, animals, objects, clipart, or graphic design elements. | 0.637795 |
7,793,211 | 9 | 10 | 9. A computer system having recordable media including computer instructions for carrying out a method for delivering targeted web advertising to users via a network capable of annotating a data object, the computer system comprising: computer program code for accessing a data object with a selectable view-thru option; computer program code for displaying a visible portion of the data object as a display image; computer program code for making alterations to the data object, wherein at least one alteration includes a rating of the data object; means for storing and caching the data object and the alterations, the data object and the alterations comprising inputs; computer program code for searching and organizing the inputs; computer program code for displaying a result to the user without migrating to another display image wherein the result displayed includes an advertisement. | 9. A computer system having recordable media including computer instructions for carrying out a method for delivering targeted web advertising to users via a network capable of annotating a data object, the computer system comprising: computer program code for accessing a data object with a selectable view-thru option; computer program code for displaying a visible portion of the data object as a display image; computer program code for making alterations to the data object, wherein at least one alteration includes a rating of the data object; means for storing and caching the data object and the alterations, the data object and the alterations comprising inputs; computer program code for searching and organizing the inputs; computer program code for displaying a result to the user without migrating to another display image wherein the result displayed includes an advertisement. 10. The computer system of claim 9 , wherein the data object is web page. | 0.731618 |
9,460,164 | 1 | 10 | 1. A non-transitory computer readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method to view documents with legal categories, the method comprising: providing example documents representative of specified legal criteria defining a legal category; categorizing documents based on the specified legal criteria exemplified by the example documents; assigning confidence levels to legal categorizations of at least one of the categorized documents; loading categorized documents consistent with the legal category into a queue; assigning template buttons to the categorized documents, the template buttons having a pre-populated coding schema; transmitting to display a categorized document from the queue; and in response to a single input action, accepting one or more classifications associated with the legal category of the categorized document and with the single input action invoking a subsequent categorized document from the queue for viewing. | 1. A non-transitory computer readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method to view documents with legal categories, the method comprising: providing example documents representative of specified legal criteria defining a legal category; categorizing documents based on the specified legal criteria exemplified by the example documents; assigning confidence levels to legal categorizations of at least one of the categorized documents; loading categorized documents consistent with the legal category into a queue; assigning template buttons to the categorized documents, the template buttons having a pre-populated coding schema; transmitting to display a categorized document from the queue; and in response to a single input action, accepting one or more classifications associated with the legal category of the categorized document and with the single input action invoking a subsequent categorized document from the queue for viewing. 10. The non-transitory computer readable storage medium of claim 1 , wherein the step of loading categorized documents consistent with the legal category into a queue further comprises loading commonly categorized documents adjacent to one another in the queue. | 0.696512 |
7,523,423 | 19 | 20 | 19. The method of claim 15 , wherein the step of producing a first multiplexer further comprises the following step: constructing a first ITE expression from the first set of output elements. | 19. The method of claim 15 , wherein the step of producing a first multiplexer further comprises the following step: constructing a first ITE expression from the first set of output elements. 20. The method of claim 19 , further comprising the following step: converting the first ITE expression into a first multi-terminal binary decision diagram. | 0.5 |
8,552,992 | 20 | 22 | 20. A computer-readable medium comprising instructions executable to specify textual input for a computing device using a multi-directional input device, the instructions being executable to: display a first matrix comprising a plurality of rows and a plurality of columns of predicted text; display a second matrix comprising a plurality of rows and a plurality of columns that include groups of characters; determine a swipe angle of a directional swipe received at a multi-directional input device; identify the associated angle closest to the swipe angle; move a first highlighted region within the first matrix to highlight a first predicted text from the plurality of predicted text, the first highlighted region moving in a direction of the associated angle; while moving the first highlighted region, move a second highlighted region within the second matrix to highlight a first group of characters from the groups of characters, the second highlighted region moving in the direction of the associated angle; in response to determining that the first predicted text is selected, sending the first predictive text to a text submission area; in response to sending the first predictive text to the text submission area: move the first highlighted region to a centered predicted text of the plurality of predicted text; and move the second highlighted region to a centered group of characters of the groups of characters while moving the first highlighted region to the centered predicted text. | 20. A computer-readable medium comprising instructions executable to specify textual input for a computing device using a multi-directional input device, the instructions being executable to: display a first matrix comprising a plurality of rows and a plurality of columns of predicted text; display a second matrix comprising a plurality of rows and a plurality of columns that include groups of characters; determine a swipe angle of a directional swipe received at a multi-directional input device; identify the associated angle closest to the swipe angle; move a first highlighted region within the first matrix to highlight a first predicted text from the plurality of predicted text, the first highlighted region moving in a direction of the associated angle; while moving the first highlighted region, move a second highlighted region within the second matrix to highlight a first group of characters from the groups of characters, the second highlighted region moving in the direction of the associated angle; in response to determining that the first predicted text is selected, sending the first predictive text to a text submission area; in response to sending the first predictive text to the text submission area: move the first highlighted region to a centered predicted text of the plurality of predicted text; and move the second highlighted region to a centered group of characters of the groups of characters while moving the first highlighted region to the centered predicted text. 22. The computer-readable medium of claim 20 , wherein the second highlighted region displays visual indicia on the display screen to distinguish the first group of characters from other groups of characters. | 0.724868 |
8,099,313 | 28 | 29 | 28. The system of claim 27 , wherein a modifying term reduces the scope of another term. | 28. The system of claim 27 , wherein a modifying term reduces the scope of another term. 29. The system of claim 28 , wherein the user interface device displays said terms that represent the task suggestions, and in selecting task suggestions, allows the user to select terms to modify other terms such that the user selected task suggestions can be performed by the available devices. | 0.5 |
10,096,317 | 2 | 6 | 2. A computer-implemented method, comprising: accessing a literal speech recognition corpus comprising a plurality of expressions, an expression comprising a sequence of word tokens; accessing a concept tagging module for identifying instances of a plurality of concepts within an expression and for replacing expressions with placeholders that indicate classes associated with concepts; generating a parameterized speech recognition corpus by using the concept tagging module to identify, within the expressions of the literal speech recognition corpus, portions of the expressions that are instances of the concepts and to replace the identified portions of the expressions with placeholders; and generating a parameterized statistical model based on the parameterized speech recognition corpus receiving, over a computer network, an utterance of a user, the utterance having been accepted from the user at a client device as spoken input; and generating a text interpretation of the utterance using the parameterized statistical model together with a language sub-model corresponding to one of the plurality of concepts. | 2. A computer-implemented method, comprising: accessing a literal speech recognition corpus comprising a plurality of expressions, an expression comprising a sequence of word tokens; accessing a concept tagging module for identifying instances of a plurality of concepts within an expression and for replacing expressions with placeholders that indicate classes associated with concepts; generating a parameterized speech recognition corpus by using the concept tagging module to identify, within the expressions of the literal speech recognition corpus, portions of the expressions that are instances of the concepts and to replace the identified portions of the expressions with placeholders; and generating a parameterized statistical model based on the parameterized speech recognition corpus receiving, over a computer network, an utterance of a user, the utterance having been accepted from the user at a client device as spoken input; and generating a text interpretation of the utterance using the parameterized statistical model together with a language sub-model corresponding to one of the plurality of concepts. 6. The computer-implemented method of claim 2 , wherein the parameterized statistical model indicates a plurality of probability scores for a corresponding plurality of n-grams, some of the plurality of n-grams including a placeholder indicating one of the plurality of concepts. | 0.515625 |
8,396,878 | 20 | 22 | 20. A computer-implemented method of generating automated tags for a video file, the method comprising: receiving one or more manually generated tags associated with a video file; based at least in part on the one or more manually entered tags, determining a preliminary category for the video file; based on the preliminary category, generating a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generating an ontology of the plurality of words based on the targeted transcript; ranking the plurality of words in the ontology based on a plurality of scoring factors; based on the ranking of the plurality of words, generating one or more automated tags associated with the video file; establishing a top concepts threshold value; determining that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associating information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file, wherein the plurality of scoring factors consists of two or more of: distribution of words throughout the targeted transcript of the video file, words related to the plurality of words throughout the targeted transcript of the video file, occurrence age of the related words, information associated with the one or more manually entered tags, vernacular meaning of the plurality of words, or colloquial considerations of the meaning of the plurality of words. | 20. A computer-implemented method of generating automated tags for a video file, the method comprising: receiving one or more manually generated tags associated with a video file; based at least in part on the one or more manually entered tags, determining a preliminary category for the video file; based on the preliminary category, generating a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generating an ontology of the plurality of words based on the targeted transcript; ranking the plurality of words in the ontology based on a plurality of scoring factors; based on the ranking of the plurality of words, generating one or more automated tags associated with the video file; establishing a top concepts threshold value; determining that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associating information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file, wherein the plurality of scoring factors consists of two or more of: distribution of words throughout the targeted transcript of the video file, words related to the plurality of words throughout the targeted transcript of the video file, occurrence age of the related words, information associated with the one or more manually entered tags, vernacular meaning of the plurality of words, or colloquial considerations of the meaning of the plurality of words. 22. The computer-implemented method of generating automated tags for the video file as in claim 20 , further comprising: determining if the rankings for each of the plurality of words exceed a threshold ranking value; and excluding any of the plurality of words that have a ranking value lower than the threshold value. | 0.84439 |
7,840,590 | 15 | 18 | 15. The one or more storage media of claim 14 , wherein the content of a resource of the multiple resources includes at least one of the following: system properties of the resource, user-defined properties of the resource, and the data of the resource. | 15. The one or more storage media of claim 14 , wherein the content of a resource of the multiple resources includes at least one of the following: system properties of the resource, user-defined properties of the resource, and the data of the resource. 18. The one or more storage media of claim 15 , wherein: the content includes the data of the resource; and a subset of the data does not conform to a particular XML schema. | 0.603211 |
8,612,489 | 9 | 10 | 9. A computer program product for transforming an extensible business reporting language (XBRL) instance into a structured extensible markup language (XML) data model instance the computer program product comprising: a computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising a computer usable program code configured to: for each of a plurality of concepts indicated in an XBRL schema associated with the XBRL instance, determine concept relationship information for the concept from the XBRL schema, context information indicated in the XBRL instance, and at least one of a plurality of files that constitute a taxonomy set for the XBRL instance; determine attribute information for the concept based, at least in part, on the XBRL schema and at least one of the files that constitute the taxonomy set; generate an XML document with XML elements structured in accordance with the concept relationship information, wherein the XML elements correspond to the plurality of concepts and have attributes set based, at least in part, on the attribute information; populate each of the XML elements with corresponding ones of XBRL facts to yield the structured XML data model instance, wherein the XBRL instance indicates the XBRL facts and the XML data model instance comprises at least the XML document; retrieve an XBRL dimension document via a second reference indicated in the taxonomy set, the XBRL dimension document including at least one hypercube having a plurality of dimensions; add a parent element to an XML dimension mapping document, the parent element corresponding to the hypercube; add to the XML dimension document one or more child elements of the parent element, the one or more child elements representing one or more dimensions in the hypercube. | 9. A computer program product for transforming an extensible business reporting language (XBRL) instance into a structured extensible markup language (XML) data model instance the computer program product comprising: a computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising a computer usable program code configured to: for each of a plurality of concepts indicated in an XBRL schema associated with the XBRL instance, determine concept relationship information for the concept from the XBRL schema, context information indicated in the XBRL instance, and at least one of a plurality of files that constitute a taxonomy set for the XBRL instance; determine attribute information for the concept based, at least in part, on the XBRL schema and at least one of the files that constitute the taxonomy set; generate an XML document with XML elements structured in accordance with the concept relationship information, wherein the XML elements correspond to the plurality of concepts and have attributes set based, at least in part, on the attribute information; populate each of the XML elements with corresponding ones of XBRL facts to yield the structured XML data model instance, wherein the XBRL instance indicates the XBRL facts and the XML data model instance comprises at least the XML document; retrieve an XBRL dimension document via a second reference indicated in the taxonomy set, the XBRL dimension document including at least one hypercube having a plurality of dimensions; add a parent element to an XML dimension mapping document, the parent element corresponding to the hypercube; add to the XML dimension document one or more child elements of the parent element, the one or more child elements representing one or more dimensions in the hypercube. 10. The computer program product of claim 9 , wherein the computer usable program code is further configured to: retrieve an XBRL dimension document via a second reference indicated in the taxonomy set; generate XBRL dimensional metadata from the XBRL dimension document; and generate an XML dimension mapping document with the XBRL dimensional metadata and dimension constraints indicated in the context information. | 0.5 |
7,954,084 | 6 | 7 | 6. The non-transitory computer-readable medium encoded with instructions according to claim 2 , wherein said two adapters having to handle the dependency are chosen following assignment rules associating, for the orientation of the dependency of said two object classes, an adapter corresponding to each of the code generators translating said two object classes, said assignment rules being modifiable. | 6. The non-transitory computer-readable medium encoded with instructions according to claim 2 , wherein said two adapters having to handle the dependency are chosen following assignment rules associating, for the orientation of the dependency of said two object classes, an adapter corresponding to each of the code generators translating said two object classes, said assignment rules being modifiable. 7. The non-transitory computer-readable medium encoded with instructions according to the claim 6 , said instructions, when executed by the computer, cause the computer to generate said computer code from said description made in a language organized in object classes, in which said language enables to define first classes giving access to technical or functional services to be provided by a hardware and software computer platform receiving the computer application, said services being not definable by said language, and the other classes of said language cannot have access to any one of said services except through said first classes and wherein said instructions cause the computer to split said description in dependencies between said object classes from dependencies between said first classes or other classes of said language. | 0.688749 |
9,563,646 | 15 | 17 | 15. A computer-implemented system, comprising: an input device enabled to generate an idea-image association that associates an image with an idea based on data that indicates user interaction with the image in a presentation of search results that correspond to a first search query, wherein the idea is determined to be related to the first search query; a database enabled to store the idea-image association and other idea-image associations; and a processor enabled to provide the image for display in a presentation of search results that correspond to a different, second search query, wherein the processor is enabled to select the image for display in the presentation of search results that correspond to the second search query based on (i) determining that the second search query relates to the idea and (ii) identifying from the stored idea-image association that a match exists between the idea that the second search query relates to and the idea to which the image is associated. | 15. A computer-implemented system, comprising: an input device enabled to generate an idea-image association that associates an image with an idea based on data that indicates user interaction with the image in a presentation of search results that correspond to a first search query, wherein the idea is determined to be related to the first search query; a database enabled to store the idea-image association and other idea-image associations; and a processor enabled to provide the image for display in a presentation of search results that correspond to a different, second search query, wherein the processor is enabled to select the image for display in the presentation of search results that correspond to the second search query based on (i) determining that the second search query relates to the idea and (ii) identifying from the stored idea-image association that a match exists between the idea that the second search query relates to and the idea to which the image is associated. 17. The system of claim 15 , wherein the system is further enabled to provide the image in the presentation of search results based at least on a determined relevance of a textual description of the image to the first search query. | 0.687838 |
9,348,919 | 1 | 9 | 1. A computerized method of presenting web pages to an end user comprising: a) using a web crawler operating on a digital computer to identify in a quoting web page a quotation of a quoted text portion; b) using the web crawler to identify the quoted text portion in a quoted web page and to identify a location of the quoted text portion within the quoted web page; c) storing in a database accessible by a server computer information concerning the quoted text portion, the quoted web page, and the quoting web page, including the location of the quoted text portion within the quoted web page; d) receiving at the server computer a request from a user computer concerning the quoted web page; e) querying the database for the existence of quoted text portions in the quoted web page; and f) generating, using information within the database concerning the location of the quoted text portion within the quoted web page, a new version of the quoted web page visually distinguishing the quoted text portion and providing a first link to the quoting document. | 1. A computerized method of presenting web pages to an end user comprising: a) using a web crawler operating on a digital computer to identify in a quoting web page a quotation of a quoted text portion; b) using the web crawler to identify the quoted text portion in a quoted web page and to identify a location of the quoted text portion within the quoted web page; c) storing in a database accessible by a server computer information concerning the quoted text portion, the quoted web page, and the quoting web page, including the location of the quoted text portion within the quoted web page; d) receiving at the server computer a request from a user computer concerning the quoted web page; e) querying the database for the existence of quoted text portions in the quoted web page; and f) generating, using information within the database concerning the location of the quoted text portion within the quoted web page, a new version of the quoted web page visually distinguishing the quoted text portion and providing a first link to the quoting document. 9. The computerized method of claim 1 , wherein the new version of the quoted web page is generated before receiving the request from the user computer. | 0.737024 |
8,554,756 | 1 | 16 | 1. A method of generating personalized search results for a search query generated by a selected user of a social network, steps of the method being variously performed by at least one computing device, and the method comprising: for respective topics, detecting an interest trend in the topic among the users of the social network who are associated with the selected user; applying the search query on a search engine indexing content items outside of the social network to generate a search result set comprising at least one search result that is not referenced by the users of the social network who are associated with the selected user; identifying at least one topic associated with the search query; selecting, within the social network of the user, at least one social data item that is referenced by the users of the social network who are associated with the selected user, associated with at least one topic associated with the search query, and exhibiting a positive interest trend among the users of the social network who are associated with the selected user; and providing for display to the selected user the at least one social data item integrated with the search result set. | 1. A method of generating personalized search results for a search query generated by a selected user of a social network, steps of the method being variously performed by at least one computing device, and the method comprising: for respective topics, detecting an interest trend in the topic among the users of the social network who are associated with the selected user; applying the search query on a search engine indexing content items outside of the social network to generate a search result set comprising at least one search result that is not referenced by the users of the social network who are associated with the selected user; identifying at least one topic associated with the search query; selecting, within the social network of the user, at least one social data item that is referenced by the users of the social network who are associated with the selected user, associated with at least one topic associated with the search query, and exhibiting a positive interest trend among the users of the social network who are associated with the selected user; and providing for display to the selected user the at least one social data item integrated with the search result set. 16. The method of claim 1 : at least one topic associated with the product; method further comprising: identifying a current price of the product offered by at least one product vendor, and evaluating the current price of the product to generate a product purchase recommendation for the product; and presenting to the selected user the at least one social data item and the search result set comprising: presenting to the selected user the product purchase recommendation for the product at the current price. | 0.635193 |
9,811,547 | 1 | 7 | 1. A client computer for updating a database stored on a server via a network, the client computer comprising: a network interconnect to communicate with the server via the network to update the database, wherein the database comprises first data items and suffix items, each one of the suffix items describes a suffix of at least one first data item of the first data items, and for each suffix item a first referential connection exists in the database assigning said suffix item to the at least one first data item of the first data items that comprises the suffix of said suffix item, each suffix item is encrypted with a suffix cryptographic key in the database, each first data item is encrypted with a first cryptographic key in the database; a microprocessor to execute an application program stored at a non-transitory processor-readable medium, the application program configured to: a) receive an update first data item, the update first data item comprising a set of successional symbols, b) creating create an update suffix item by removing a number of the set of successional symbols from the left side of the update first data item, the update suffix item being the residual part of the update first data item without the removed symbols, c) encrypt the update suffix item with the suffix cryptographic key for obtaining an encrypted update suffix item and encrypting the update first data item with the first cryptographic key for obtaining an encrypted update first data item, d) provide a storage request to the database, the storage request comprising instructions to store in the database the encrypted update suffix item, the encrypted update first data item and the first referential connection assigning said encrypted update suffix item to the encrypted update first data item, e) repeat steps b)-d) with different numbers of the successional removed symbols, the numbers being in between a minimum and a maximum, wherein the maximum is given by the total number of symbols of the update first data item minus a predefined minimal word length. | 1. A client computer for updating a database stored on a server via a network, the client computer comprising: a network interconnect to communicate with the server via the network to update the database, wherein the database comprises first data items and suffix items, each one of the suffix items describes a suffix of at least one first data item of the first data items, and for each suffix item a first referential connection exists in the database assigning said suffix item to the at least one first data item of the first data items that comprises the suffix of said suffix item, each suffix item is encrypted with a suffix cryptographic key in the database, each first data item is encrypted with a first cryptographic key in the database; a microprocessor to execute an application program stored at a non-transitory processor-readable medium, the application program configured to: a) receive an update first data item, the update first data item comprising a set of successional symbols, b) creating create an update suffix item by removing a number of the set of successional symbols from the left side of the update first data item, the update suffix item being the residual part of the update first data item without the removed symbols, c) encrypt the update suffix item with the suffix cryptographic key for obtaining an encrypted update suffix item and encrypting the update first data item with the first cryptographic key for obtaining an encrypted update first data item, d) provide a storage request to the database, the storage request comprising instructions to store in the database the encrypted update suffix item, the encrypted update first data item and the first referential connection assigning said encrypted update suffix item to the encrypted update first data item, e) repeat steps b)-d) with different numbers of the successional removed symbols, the numbers being in between a minimum and a maximum, wherein the maximum is given by the total number of symbols of the update first data item minus a predefined minimal word length. 7. The client computer of claim 1 , wherein a data item is given by the update first data item or the update suffix item, wherein the application program is further operational to determine for each data item the respective cryptographic key required for encrypting said data item by generating a seed value and combining the seed value with a symmetric key common for all of the data items, wherein the storage request comprises instructions to store in the database the data item with the seed value being appended to the encrypted data item, wherein the seed value being appended to the encrypted data item forms a storable encrypted data item, wherein the seed value is appended to the data suffix item in a predefined manner common for all data items. | 0.683417 |
9,749,267 | 1 | 3 | 1. A computer-implemented method of intelligent predictive messaging, the method comprising: obtaining, at a message prediction engine from a user device, message context data indicative of context of a conversation taking place between particular people during a messaging session; processing the message context data, at the message prediction engine, to determine, based on prior conversation patterns between those particular people, a predicted conversation pattern of the conversation that is taking place between the particular people; determining, at the message prediction engine based on the predicted conversation pattern, recommended text that indicates suggested language to be included in a message as part of the conversation to complete at least part of the message, wherein the suggested language corresponds to the message context data indicative of the context of the conversation, wherein the recommended text comprises: options for suggested language that are predicted to compete at least part of the message, wherein the suggested language to be included in the message comprises: a plurality of suggested entries for the messaging session, wherein each of the suggested entries comprises: a different recommended lines of text, wherein each of the different recommended lines of text indicates different suggested language for the message corresponding to the message context data; and displaying the recommended text within a message field. | 1. A computer-implemented method of intelligent predictive messaging, the method comprising: obtaining, at a message prediction engine from a user device, message context data indicative of context of a conversation taking place between particular people during a messaging session; processing the message context data, at the message prediction engine, to determine, based on prior conversation patterns between those particular people, a predicted conversation pattern of the conversation that is taking place between the particular people; determining, at the message prediction engine based on the predicted conversation pattern, recommended text that indicates suggested language to be included in a message as part of the conversation to complete at least part of the message, wherein the suggested language corresponds to the message context data indicative of the context of the conversation, wherein the recommended text comprises: options for suggested language that are predicted to compete at least part of the message, wherein the suggested language to be included in the message comprises: a plurality of suggested entries for the messaging session, wherein each of the suggested entries comprises: a different recommended lines of text, wherein each of the different recommended lines of text indicates different suggested language for the message corresponding to the message context data; and displaying the recommended text within a message field. 3. The method of claim 1 , wherein the message predication engine is implemented at a computing system that is communicatively coupled to the user device via a network. | 0.830645 |
8,688,728 | 7 | 10 | 7. A non-transitory computer readable storage medium having computer readable program instructions stored thereon for causing a computer system to perform instructions, the instructions comprising the steps of: creating a list of candidate probe words; for each candidate probe word, counting a number of application descriptions that contain the candidate probe word; choosing q probe words from the candidate probe words whose word count is closest to |D i |/(q+1), where D i is a set of remaining application descriptions for an ith repetition, and q is a number of probe words presented for user selection and is an integer greater than 1; presenting the q probe words for user selection; pruning the list of candidate probe words to eliminate application descriptions that include non-selected ones of the q probe words to create a pruned list of candidate probe words, wherein the pruned list of candidate probe words includes a probe word selected by the user from the q probe words; and repeating counting the number of application descriptions, choosing q probe words from the pruned list of candidate probe words, presenting the q probe words for selection and pruning the list of probe words until a final list of applications remain. | 7. A non-transitory computer readable storage medium having computer readable program instructions stored thereon for causing a computer system to perform instructions, the instructions comprising the steps of: creating a list of candidate probe words; for each candidate probe word, counting a number of application descriptions that contain the candidate probe word; choosing q probe words from the candidate probe words whose word count is closest to |D i |/(q+1), where D i is a set of remaining application descriptions for an ith repetition, and q is a number of probe words presented for user selection and is an integer greater than 1; presenting the q probe words for user selection; pruning the list of candidate probe words to eliminate application descriptions that include non-selected ones of the q probe words to create a pruned list of candidate probe words, wherein the pruned list of candidate probe words includes a probe word selected by the user from the q probe words; and repeating counting the number of application descriptions, choosing q probe words from the pruned list of candidate probe words, presenting the q probe words for selection and pruning the list of probe words until a final list of applications remain. 10. The non-transitory computer readable storage medium having computer readable program instructions recited in claim 7 , the instructions further comprising presenting the final list of applications for user selection. | 0.677419 |
7,921,106 | 1 | 2 | 1. A computer-implemented apparatus that enhances search result listings, comprising: a processor operatively coupled to a computer readable medium having stored thereon the following computer executable components: an attribute value ranking component comprising a search engine search result list sorted by search results rank, and further sorted by attribute value as a primary sort and rank as a secondary sort, wherein an attribute value rank is calculated for each of the attribute values; grouped search results comprising the search result list resorted by the calculated attribute value ranks, and further resorted by the attribute values, and still further resorted by the search results rank; a search result display component that provides search result groupings based on the group-by ranking for interaction with a user; and computer-readable storage medium comprising data structures and code for causing a computer to execute the attribute value ranking and search result display components, wherein the object oriented search result list references a plurality of information pages each comprising an object block representing an object classified as an object type having attributes for which the object block contains elements identified as attribute values, wherein the attribute pertains to a source of a respective information page. | 1. A computer-implemented apparatus that enhances search result listings, comprising: a processor operatively coupled to a computer readable medium having stored thereon the following computer executable components: an attribute value ranking component comprising a search engine search result list sorted by search results rank, and further sorted by attribute value as a primary sort and rank as a secondary sort, wherein an attribute value rank is calculated for each of the attribute values; grouped search results comprising the search result list resorted by the calculated attribute value ranks, and further resorted by the attribute values, and still further resorted by the search results rank; a search result display component that provides search result groupings based on the group-by ranking for interaction with a user; and computer-readable storage medium comprising data structures and code for causing a computer to execute the attribute value ranking and search result display components, wherein the object oriented search result list references a plurality of information pages each comprising an object block representing an object classified as an object type having attributes for which the object block contains elements identified as attribute values, wherein the attribute pertains to a source of a respective information page. 2. The computer-implemented apparatus of claim 1 , wherein the attribute value ranking component accepts user or system preferences for selecting attributes on which to base the group-by ranking. | 0.53125 |
7,587,359 | 18 | 19 | 18. The system of claim 15 , wherein the plurality of items are respectively associated with a plurality of completed transactions on the network-based transaction facility. | 18. The system of claim 15 , wherein the plurality of items are respectively associated with a plurality of completed transactions on the network-based transaction facility. 19. The system of claim 18 , wherein the plurality of completed transactions includes a first transaction in which a first user participated as a buyer and a second user participated as a seller. | 0.5 |
8,874,556 | 7 | 12 | 7. A system comprising: a memory comprising instructions executable by one or more processors; and the one or more processors coupled to the memory and operable to execute the instructions, the one or more processors being operable when executing the instructions to: receive a search query from a first user of a social-networking system, the social-networking system comprising a graph that comprises a plurality of nodes and edges connecting the nodes, at least one node in the graph corresponding to the first user; identify one or more web pages responsive to the search query, each web page being hosted by a third party application server that is external to the social-networking system; retrieve information associated with the first user to identify one or more second users of the social-networking system, for each of the second users at least one node in the graph corresponding to the second user, at least one of the nodes corresponding to the first user and at least one of the nodes corresponding to a second user being connected to each other by one or more edges; rank the identified web pages that are hosted by third party application servers that are external to the social-networking system based at least in part on interaction of the second users of the social-networking system with the web pages, the interaction of the second users being determined, for each of the web pages, from one or more databases indicating a number of times the web page has been accessed by the second users divided by a number of times the web page has been presented to the second users; and provide a link for each of the web pages for presentation to the first user as ranked. | 7. A system comprising: a memory comprising instructions executable by one or more processors; and the one or more processors coupled to the memory and operable to execute the instructions, the one or more processors being operable when executing the instructions to: receive a search query from a first user of a social-networking system, the social-networking system comprising a graph that comprises a plurality of nodes and edges connecting the nodes, at least one node in the graph corresponding to the first user; identify one or more web pages responsive to the search query, each web page being hosted by a third party application server that is external to the social-networking system; retrieve information associated with the first user to identify one or more second users of the social-networking system, for each of the second users at least one node in the graph corresponding to the second user, at least one of the nodes corresponding to the first user and at least one of the nodes corresponding to a second user being connected to each other by one or more edges; rank the identified web pages that are hosted by third party application servers that are external to the social-networking system based at least in part on interaction of the second users of the social-networking system with the web pages, the interaction of the second users being determined, for each of the web pages, from one or more databases indicating a number of times the web page has been accessed by the second users divided by a number of times the web page has been presented to the second users; and provide a link for each of the web pages for presentation to the first user as ranked. 12. The system of claim 7 : wherein the web pages comprise one or more sponsored links and one or more algorithmic search results; the one or more processors being further operable when executing the instructions to: rank the sponsored links further based at least in part on a-bids received with sponsored links; and rank the algorithmic search results further based at least in part on a degree of relevance of each algorithmic search result with respect to the search query. | 0.669209 |
8,965,129 | 1 | 21 | 1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: cropping a frame of the real-time video feed of one or more words of the first language to fit inside a bounding box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments while determining at least a shape score for at least one merged character segment; performing character recognition on the merged character segments by utilizing at least the shape score of the at least one merged character segment to produce a plurality of recognized characters with high scores; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language. | 1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: cropping a frame of the real-time video feed of one or more words of the first language to fit inside a bounding box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments while determining at least a shape score for at least one merged character segment; performing character recognition on the merged character segments by utilizing at least the shape score of the at least one merged character segment to produce a plurality of recognized characters with high scores; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language. 21. The method of claim 1 , wherein a translated line having a highest translation quality is selected for display, and wherein the translation quality is determined by how well the one or more words of the first language are translated. | 0.789894 |
8,335,794 | 1 | 9 | 1. A method using a graphical user interface (GUI) for tuning access middleware that provides an application with one or more connections to a database, the method comprising: using a computer to perform steps comprising: receiving a first response from a user specifying a type of a driver/provider for the database to be tuned; querying the user, based on the first response received from the user, regarding a functionality of the application, the functionality of the application including a functionality to use a prepared statement that is compiled for a connection and available to be executed for the connection, wherein the prepared statement is compiled once for the connection and available to be executed two or more times for the connection; receiving a second response from the user specifying the functionality of the application, the second response including data describing that the application uses the prepared statement; generating, based on the first response received from the user and the second response including the data describing that the application uses the prepared statement, a set of connection options and values configured to achieve optimal performance of the driver/provider; and providing the set of connection options and values to the user. | 1. A method using a graphical user interface (GUI) for tuning access middleware that provides an application with one or more connections to a database, the method comprising: using a computer to perform steps comprising: receiving a first response from a user specifying a type of a driver/provider for the database to be tuned; querying the user, based on the first response received from the user, regarding a functionality of the application, the functionality of the application including a functionality to use a prepared statement that is compiled for a connection and available to be executed for the connection, wherein the prepared statement is compiled once for the connection and available to be executed two or more times for the connection; receiving a second response from the user specifying the functionality of the application, the second response including data describing that the application uses the prepared statement; generating, based on the first response received from the user and the second response including the data describing that the application uses the prepared statement, a set of connection options and values configured to achieve optimal performance of the driver/provider; and providing the set of connection options and values to the user. 9. The method of claim 1 wherein providing the set of connection options and values to the user includes providing multiple output formats from which the user can choose. | 0.777487 |
8,898,163 | 4 | 5 | 4. The method as claimed in claim 2 , wherein the user input comprises at least one input associated with one or more of: an email, an instant message, a short message, a telephone call, and a browser. | 4. The method as claimed in claim 2 , wherein the user input comprises at least one input associated with one or more of: an email, an instant message, a short message, a telephone call, and a browser. 5. The method as claimed in claim 4 , wherein the user input is composed on a user device. | 0.5 |
8,301,514 | 5 | 7 | 5. A method of generating item recommendations, the method comprising: by a computer system comprising computer hardware: accessing a transaction phrase index comprising a plurality of transaction phrases mapped to items purchased using the transaction phrases; identifying a transaction phrase created by a target user; identifying candidate recommendations from the transaction phrase index based at least partly on the identified target user transaction phrase, the candidate recommendations comprising one or more of the purchased items contained in the transaction phrase index; and selecting one or more of the candidate recommendations to present to the target user as item recommendations. | 5. A method of generating item recommendations, the method comprising: by a computer system comprising computer hardware: accessing a transaction phrase index comprising a plurality of transaction phrases mapped to items purchased using the transaction phrases; identifying a transaction phrase created by a target user; identifying candidate recommendations from the transaction phrase index based at least partly on the identified target user transaction phrase, the candidate recommendations comprising one or more of the purchased items contained in the transaction phrase index; and selecting one or more of the candidate recommendations to present to the target user as item recommendations. 7. The method of claim 5 , wherein said identifying candidate recommendations comprises using a similar phrase that is similar to the target user transaction phrase to index into the transaction phrase index. | 0.5 |
8,677,262 | 4 | 17 | 4. A method, comprising: rendering, by a system including a processor, a visualization comprising a first display object and a second display object, wherein the first display object and the second display object are related to at least one hardware device; obtaining, by the system, context information for a user identity of an industrial automation system comprising a state of the at least one hardware device within an industrial automation system; determining, by the system, a first level of relevance of the first display object to the user identity based on the context information; determining, by the system, a second level of relevance of the second display object to the user identity based on the context information, wherein the first level of relevance is determined to be higher than the second level of relevance; initiating, by the system, an update of the visualization to render the first display object more prominently than the second display object based on the first level of relevance being higher than the second level of relevance. | 4. A method, comprising: rendering, by a system including a processor, a visualization comprising a first display object and a second display object, wherein the first display object and the second display object are related to at least one hardware device; obtaining, by the system, context information for a user identity of an industrial automation system comprising a state of the at least one hardware device within an industrial automation system; determining, by the system, a first level of relevance of the first display object to the user identity based on the context information; determining, by the system, a second level of relevance of the second display object to the user identity based on the context information, wherein the first level of relevance is determined to be higher than the second level of relevance; initiating, by the system, an update of the visualization to render the first display object more prominently than the second display object based on the first level of relevance being higher than the second level of relevance. 17. The method of claim 4 , wherein the context information is further based on a logical location of the device or a physical location of the at least one device. | 0.714035 |
8,296,126 | 4 | 5 | 4. The method of claim 1 comprising maintaining a store of portions of text and respective translations on said communications device; and using said store to determine the translation for the portion of text. | 4. The method of claim 1 comprising maintaining a store of portions of text and respective translations on said communications device; and using said store to determine the translation for the portion of text. 5. The method of claim 4 wherein the store of portions of text and respective translations is defined by prior translations. | 0.5 |
7,873,223 | 1 | 16 | 1. A method comprising: in a specification mode: specifying a class network having a class, wherein a membership function defines a likelihood that an object of a data network belongs to the class; specifying a process step having a domain and an algorithm, wherein the domain designates the class, and wherein the process step is part of a process hierarchy; specifying a link type that defines a relation between the class and the object; in an execution mode: acquiring table data values; and executing the class network and the process hierarchy on a computer that implements the data network by generating the object of the data network and by selectively linking selected table data values to the object according to the class network and the process hierarchy. | 1. A method comprising: in a specification mode: specifying a class network having a class, wherein a membership function defines a likelihood that an object of a data network belongs to the class; specifying a process step having a domain and an algorithm, wherein the domain designates the class, and wherein the process step is part of a process hierarchy; specifying a link type that defines a relation between the class and the object; in an execution mode: acquiring table data values; and executing the class network and the process hierarchy on a computer that implements the data network by generating the object of the data network and by selectively linking selected table data values to the object according to the class network and the process hierarchy. 16. The method of claim 1 , wherein the executing that implements the data network comprises: classifying whether each of a plurality of objects of the data network belongs to the class designated by the domain of the process step; performing the algorithm on each of the plurality of objects that belong to the class; automatically generating a second class that is part of the class network, wherein the domain designates the second class instead of the class; and performing the algorithm on each object of the plurality of objects that belong to the second class. | 0.590909 |
6,038,393 | 1 | 4 | 1. A computer system, including a repository, comprising: a.) first means for transforming a first distinctive representation of business model information into an OMG compliant UML representation of at least a portion of a business model and storing said representation in said repository in the form of a set of object classes, said first means for transforming including: 1) a representation of a business model between one of said distinctive representations and said UML representation of said business model; and 2) means for creating bi-directional mapping between elements of said method of representation of a business model by said one of the distinctive representations and the method of representation of said business model by said UML representation; b.) means for modifying said UML representation of said business model; c.) means for modifying a distinctive representation of said business model to reflect the modification in said UML representation of said business model; and d.)second means for transforming said UML representation into a second distinctive representation of at least a portion of said business model. | 1. A computer system, including a repository, comprising: a.) first means for transforming a first distinctive representation of business model information into an OMG compliant UML representation of at least a portion of a business model and storing said representation in said repository in the form of a set of object classes, said first means for transforming including: 1) a representation of a business model between one of said distinctive representations and said UML representation of said business model; and 2) means for creating bi-directional mapping between elements of said method of representation of a business model by said one of the distinctive representations and the method of representation of said business model by said UML representation; b.) means for modifying said UML representation of said business model; c.) means for modifying a distinctive representation of said business model to reflect the modification in said UML representation of said business model; and d.)second means for transforming said UML representation into a second distinctive representation of at least a portion of said business model. 4. The system of claim 1 wherein said first distinctive representation comprises a first distinctive representation of a plurality of objects and wherein said first means for transforming comprise means for transforming said first distinctive representation of a subset of said plurality of objects into an OMG compliant UML representation of said subset of said plurality of objects. | 0.5 |
7,587,667 | 1 | 11 | 1. A method comprising the computer-implemented steps of: after an XML processor, which is configured to send validated XML data to an application, starts performing a validation operation on an XML-based input stream, and before said XML processor completes performing said validation operation on said XML-based input stream, performing the steps of: after starting to validate a particular XML element in said XML-based input stream, and before completion of validating said particular XML element in said XML-based input stream, performing the computer-implemented step of said XML processor receiving one or more requests for particular information relating to said validation operation, wherein said one or more requests include at least one of: (a) a request for whether said particular XML element is defined in corresponding information that dictates the structure of said XML data in said XML-based input stream; (b) a request for the name of said particular XML element; (c) a request for the data type of said particular XML element; (d) a request for whether said particular XML element conforms to the corresponding information that dictates the structure of said XML data in said XML-based input stream; (e) a request for the current validation mode of said validation operation; (f) a request for the current state of said validation operation; or (g) a request for one or more annotations that are associated with said particular XML element; said XML processor generating one or more messages that include said particular information; and said XML processor responding to said one or more requests for said particular information by providing said one or more messages. | 1. A method comprising the computer-implemented steps of: after an XML processor, which is configured to send validated XML data to an application, starts performing a validation operation on an XML-based input stream, and before said XML processor completes performing said validation operation on said XML-based input stream, performing the steps of: after starting to validate a particular XML element in said XML-based input stream, and before completion of validating said particular XML element in said XML-based input stream, performing the computer-implemented step of said XML processor receiving one or more requests for particular information relating to said validation operation, wherein said one or more requests include at least one of: (a) a request for whether said particular XML element is defined in corresponding information that dictates the structure of said XML data in said XML-based input stream; (b) a request for the name of said particular XML element; (c) a request for the data type of said particular XML element; (d) a request for whether said particular XML element conforms to the corresponding information that dictates the structure of said XML data in said XML-based input stream; (e) a request for the current validation mode of said validation operation; (f) a request for the current state of said validation operation; or (g) a request for one or more annotations that are associated with said particular XML element; said XML processor generating one or more messages that include said particular information; and said XML processor responding to said one or more requests for said particular information by providing said one or more messages. 11. The method of claim 1 , wherein the step of said XML processor receiving said one or more requests for said particular information includes receiving a request regarding whether a data type of content of said particular XML element of said XML-based input stream conforms to a corresponding data type definition in information that dictates the structure of corresponding XML data. | 0.805752 |
8,504,664 | 6 | 10 | 6. The method of claim 1 wherein validating, using the at least one rule, a command for configuring the network entity includes: selecting the validation configuration file for processing; accessing the validation configuration file; and processing the validation configuration file for obtaining the at least one rule for validating commands for configuring the network entity. | 6. The method of claim 1 wherein validating, using the at least one rule, a command for configuring the network entity includes: selecting the validation configuration file for processing; accessing the validation configuration file; and processing the validation configuration file for obtaining the at least one rule for validating commands for configuring the network entity. 10. The method of claim 6 wherein at least one of selecting, accessing, and processing the validation configuration file occurs at least one of: prior to a request for validation of input; and in response to a request for validation of input. | 0.724374 |
8,069,410 | 4 | 5 | 4. The process of claim 1 , wherein said parsing further includes binary examination of said document. | 4. The process of claim 1 , wherein said parsing further includes binary examination of said document. 5. The process of claim 4 , wherein said binary examination further includes executing specific parsing rules according to a type associated with said document. | 0.5 |
9,817,564 | 1 | 7 | 1. A computer-implemented method of managing display of content, comprising: identifying a plurality of documents, for each document in the plurality of documents: determining a first topic associated with a first portion of the document based on extracting metadata associated with the document; determining a second, differing topic associated with a second, differing portion of the document based on textual content of the second portion; generating a first topic vector associated with the document based on the first and the second topics, the first topic vector indicating respective relations between the first and the second topics and the document; generating a second topic vector associated with one or more keywords associated with the user; determining a correlation between the document and one or more keywords based on a comparison of the first topic vector and the second topic vector; and determining a time weight for the document, the time weight indicating an amount of time to display a portion of the document to the user through a GUI based at least in part on the correlation; displaying a particular portion of a first document of the plurality of documents to the user through the GUI for the respective determined amount of time; during the display of the particular portion of the first document, identifying a user interaction with the particular portion of the first document, and a particular topic associated with the particular portion of the first document, the particular topic being one of the first topic and the second topic, the user interaction including an adjustment to the determined amount of time of display of the particular portion of the first document; generating a user interaction topic vector based on the user interaction; identifying a second, differing document of the plurality of documents; comparing the user interaction topic vector with a topic vector associated with the second document; based on the comparing the user interaction topic vector with the topic vector associated with the second document, updating a time weight for a portion of the second document that is associated with the particular topic; and after displaying the particular portion of the first document, displaying the second document of the plurality of documents to the user through the GUI for the updated time weight. | 1. A computer-implemented method of managing display of content, comprising: identifying a plurality of documents, for each document in the plurality of documents: determining a first topic associated with a first portion of the document based on extracting metadata associated with the document; determining a second, differing topic associated with a second, differing portion of the document based on textual content of the second portion; generating a first topic vector associated with the document based on the first and the second topics, the first topic vector indicating respective relations between the first and the second topics and the document; generating a second topic vector associated with one or more keywords associated with the user; determining a correlation between the document and one or more keywords based on a comparison of the first topic vector and the second topic vector; and determining a time weight for the document, the time weight indicating an amount of time to display a portion of the document to the user through a GUI based at least in part on the correlation; displaying a particular portion of a first document of the plurality of documents to the user through the GUI for the respective determined amount of time; during the display of the particular portion of the first document, identifying a user interaction with the particular portion of the first document, and a particular topic associated with the particular portion of the first document, the particular topic being one of the first topic and the second topic, the user interaction including an adjustment to the determined amount of time of display of the particular portion of the first document; generating a user interaction topic vector based on the user interaction; identifying a second, differing document of the plurality of documents; comparing the user interaction topic vector with a topic vector associated with the second document; based on the comparing the user interaction topic vector with the topic vector associated with the second document, updating a time weight for a portion of the second document that is associated with the particular topic; and after displaying the particular portion of the first document, displaying the second document of the plurality of documents to the user through the GUI for the updated time weight. 7. The computer-implemented method of claim 1 , wherein the particular portion of the first document comprises a page of the first document. | 0.87013 |
4,661,915 | 1 | 2 | 1. A speech recognition system comprising: means for analyzing digital speech data representative of an analog speech signal to generate perceived phonemes representative of component parts of said digital speech data; memory means having encoded digital speech data stored therein, said encoded digital speech data including phoneme codes representative of a plurality of respective reference phonemes, said memory means further having digital speech data stored therein representative of allophones analogous to said phoneme codes; means operably coupled to said analyzing means and to said memory means for selecting encoded digital speech data representative of a particular reference phoneme from said memory means as the closest match for each of said perceived phonemes of said digital speech data to provide a phoneme code at least approximating each of said perceived phonemes; and means operably coupled to said selecting means and said memory means for forming a phoneme code sequence of a plurality of said phoneme codes, said phoneme code sequence-formeing means being responsive to said phoneme codes as determined by said selecting means to access digital speech data from said memory means representative of analogous allophones corresponding to said phoneme codes. | 1. A speech recognition system comprising: means for analyzing digital speech data representative of an analog speech signal to generate perceived phonemes representative of component parts of said digital speech data; memory means having encoded digital speech data stored therein, said encoded digital speech data including phoneme codes representative of a plurality of respective reference phonemes, said memory means further having digital speech data stored therein representative of allophones analogous to said phoneme codes; means operably coupled to said analyzing means and to said memory means for selecting encoded digital speech data representative of a particular reference phoneme from said memory means as the closest match for each of said perceived phonemes of said digital speech data to provide a phoneme code at least approximating each of said perceived phonemes; and means operably coupled to said selecting means and said memory means for forming a phoneme code sequence of a plurality of said phoneme codes, said phoneme code sequence-formeing means being responsive to said phoneme codes as determined by said selecting means to access digital speech data from said memory means representative of analogous allophones corresponding to said phoneme codes. 2. A speech recognition system as set forth in claim 1, wherein the digital speech data operated upon by said analyzing means is representative of an analog speech signal normalized for pitch and speed such that the allophones represented by the digital speech data as accessed from said memory means by said phoneme code sequence-forming means more nearly approximate the original analog speech signal. | 0.5 |
6,047,286 | 13 | 14 | 13. A system according to claim 11, wherein processor is further configured to generate a metaword as part of the index entry. | 13. A system according to claim 11, wherein processor is further configured to generate a metaword as part of the index entry. 14. A system according to claim 13, wherein the processor is further configured to generate the metaword to be identical to the concatenation of adjacent portions of the information. | 0.5 |
8,125,922 | 29 | 30 | 29. The method of claim 28 wherein associating each of said web pages with co-ordinate data comprises associating web pages with co-ordinate data on the basis of textual analysis of data appearing in a webpage. | 29. The method of claim 28 wherein associating each of said web pages with co-ordinate data comprises associating web pages with co-ordinate data on the basis of textual analysis of data appearing in a webpage. 30. The method of claim 29 wherein said textual analysis is such to associate web pages relating to similar subjects with similar co-ordinate values. | 0.5 |
8,935,664 | 5 | 8 | 5. The method of claim 1 wherein each of the plurality of SOA operational rule categories respectively corresponds to an SOA component into which rules may be implemented. | 5. The method of claim 1 wherein each of the plurality of SOA operational rule categories respectively corresponds to an SOA component into which rules may be implemented. 8. The method of claim 5 wherein the questions of the plurality of questions include at least one question at each of the following levels: (i) security; (ii) maintenance frequency/usage demand; (iii) complexity; and (iv) rule type. | 0.628205 |
9,672,203 | 10 | 13 | 10. A computer-implemented method, comprising: determining at least a portion of a text string associated with an electronic book; determining one or more nouns in the text string; associating each of the one or more nouns with one or more characters so as to create a set of characters for the electronic book; determining one or more verbs in the text string, each of the one or more verbs representing an action between one of the characters of the set of characters and at least one other of the characters of the set of characters; generating a character graph that represents relationships between the one or more characters based at least in part upon the one or more verbs and the actions between the one or more characters, the one or more characters represented as nodes in the character graph; calculating a number of the nodes in the character graph; comparing the number of the nodes to a character threshold; and determining a maturity level of the electronic book based in part on the comparison of the character threshold with the number of the nodes in the character graph. | 10. A computer-implemented method, comprising: determining at least a portion of a text string associated with an electronic book; determining one or more nouns in the text string; associating each of the one or more nouns with one or more characters so as to create a set of characters for the electronic book; determining one or more verbs in the text string, each of the one or more verbs representing an action between one of the characters of the set of characters and at least one other of the characters of the set of characters; generating a character graph that represents relationships between the one or more characters based at least in part upon the one or more verbs and the actions between the one or more characters, the one or more characters represented as nodes in the character graph; calculating a number of the nodes in the character graph; comparing the number of the nodes to a character threshold; and determining a maturity level of the electronic book based in part on the comparison of the character threshold with the number of the nodes in the character graph. 13. The computer-implemented method of claim 10 , wherein the one or more verbs are associated with one or more weights, the one or more weights associated with a complexity of the one or more verbs, and wherein determining the maturity level of the electronic book comprises utilizing the one or more weights associated with the one or more verbs. | 0.756303 |
10,079,014 | 35 | 37 | 35. The system of claim 34 , wherein the set of one or more pronunciation guessers comprise pronunciation guessers for a plurality of locales, each locale having its own pronunciation guesser. | 35. The system of claim 34 , wherein the set of one or more pronunciation guessers comprise pronunciation guessers for a plurality of locales, each locale having its own pronunciation guesser. 37. The system of claim 35 , wherein the system executes the one or more programs for a plurality of users, and each user of the plurality of users has a dedicated extended phonetic dictionary that is unique to each user. | 0.833835 |
8,495,491 | 6 | 7 | 6. A computer system configured for locale and operating platform independent font selection comprising: an operating platform executing in a computing system and having an operating platform configuration and an associated locale; a font properties file disposed in the computing system, the font properties file comprising a plurality of entries, each of said entries defining a font and at least one of corresponding supported locale and a corresponding supported operating platform configuration; and, a locale and operating platform independent font selection processor executing in the computing system and programmed first to parse the font properties file, to identify within the font properties file whether a desired font referenced in said font properties file supports at least one of the operating platform configuration and the associated locale, and to utilize the desired font in the operating platform if it is indicated within the font properties file that the desired font supports the at least one of the operating platform configuration and the associated locale. | 6. A computer system configured for locale and operating platform independent font selection comprising: an operating platform executing in a computing system and having an operating platform configuration and an associated locale; a font properties file disposed in the computing system, the font properties file comprising a plurality of entries, each of said entries defining a font and at least one of corresponding supported locale and a corresponding supported operating platform configuration; and, a locale and operating platform independent font selection processor executing in the computing system and programmed first to parse the font properties file, to identify within the font properties file whether a desired font referenced in said font properties file supports at least one of the operating platform configuration and the associated locale, and to utilize the desired font in the operating platform if it is indicated within the font properties file that the desired font supports the at least one of the operating platform configuration and the associated locale. 7. The system of claim 6 , wherein each of said entries defines a font and a corresponding supported locale for which said font can support a display of non-Latin text. | 0.5 |
9,972,315 | 5 | 6 | 5. A speech processing device comprising: a reverberation suppression unit configured to generate dereverberated speech for each acoustic environment from acquired speech on the basis of reverberation component data of each acoustic environment; a feature quantity calculation unit configured to calculate a feature quantity of the dereverberated speech; and a speech recognition unit configured to calculate a likelihood of an utterance state string from the feature quantity for each acoustic environment and selects an utterance state string on the basis of the likelihood, wherein the reverberation component data is data indicating a contribution of a reverberation component given by correction reverberation characteristics obtained through predetermined filter processing for a predetermined reverberation characteristic, and a correction factor for use in the filter processing is set such that a likelihood which is calculated from a feature quantity of corrected speech obtained through the filter processing for the speech of each acoustic environment is higher than a likelihood calculated from a feature quantity of the speech of each acoustic environment. | 5. A speech processing device comprising: a reverberation suppression unit configured to generate dereverberated speech for each acoustic environment from acquired speech on the basis of reverberation component data of each acoustic environment; a feature quantity calculation unit configured to calculate a feature quantity of the dereverberated speech; and a speech recognition unit configured to calculate a likelihood of an utterance state string from the feature quantity for each acoustic environment and selects an utterance state string on the basis of the likelihood, wherein the reverberation component data is data indicating a contribution of a reverberation component given by correction reverberation characteristics obtained through predetermined filter processing for a predetermined reverberation characteristic, and a correction factor for use in the filter processing is set such that a likelihood which is calculated from a feature quantity of corrected speech obtained through the filter processing for the speech of each acoustic environment is higher than a likelihood calculated from a feature quantity of the speech of each acoustic environment. 6. The speech processing device according to claim 5 , wherein an acoustic model for use in calculating the likelihood is a model representing an appearance probability of an utterance state by a linear combination of a normal distribution of a feature quantity, and for calculating the correction factor, the correction factor is updated such that the likelihood is made higher using a gradient of the likelihood with respect to the correction factor. | 0.5 |
7,657,832 | 10 | 15 | 10. A computer program product tangibly embodied in a machine-readable storage device for correcting an XML electronic document, the XML electronic document having a structure, the product comprising instructions operable to cause one or more data processing apparatus to perform operations comprising: identifying a validation error in the XML electronic document structure, the validation error being an aspect of the XML electronic document structure that fails to conform to rules of an XML document type definition or an XML schema, the rules being associated with the XML electronic document, the validation error being of a particular kind, wherein identifying the validation error comprises building a deterministic finite automaton from a content model defined in a document type definition of the XML electronic document and identifying the validation error using the deterministic finite automaton; selecting a suggestion template from among multiple suggestion templates according to the particular kind of the validation error, and using the selected suggestion template to suggest to a user suggested corrections that are predefined in the template for the particular kind of validation error, the selected suggestion template including logic necessary for modifying the XML electronic document structure in conformance with the rules of the XML document type definition or the XML schema, wherein modifying the XML electronic document structure comprises retagging an element in the XML electronic document structure and moving an element from a current location to a new location in the XML electronic document structure; receiving an input selecting one of the suggested corrections; and using the logic in the selected suggestion template to apply the correction selected by the input to the XML electronic document. | 10. A computer program product tangibly embodied in a machine-readable storage device for correcting an XML electronic document, the XML electronic document having a structure, the product comprising instructions operable to cause one or more data processing apparatus to perform operations comprising: identifying a validation error in the XML electronic document structure, the validation error being an aspect of the XML electronic document structure that fails to conform to rules of an XML document type definition or an XML schema, the rules being associated with the XML electronic document, the validation error being of a particular kind, wherein identifying the validation error comprises building a deterministic finite automaton from a content model defined in a document type definition of the XML electronic document and identifying the validation error using the deterministic finite automaton; selecting a suggestion template from among multiple suggestion templates according to the particular kind of the validation error, and using the selected suggestion template to suggest to a user suggested corrections that are predefined in the template for the particular kind of validation error, the selected suggestion template including logic necessary for modifying the XML electronic document structure in conformance with the rules of the XML document type definition or the XML schema, wherein modifying the XML electronic document structure comprises retagging an element in the XML electronic document structure and moving an element from a current location to a new location in the XML electronic document structure; receiving an input selecting one of the suggested corrections; and using the logic in the selected suggestion template to apply the correction selected by the input to the XML electronic document. 15. The computer program product of claim 10 , wherein: the template is implemented as a list of commands. | 0.906526 |
8,793,265 | 26 | 27 | 26. The system of claim 25 , wherein characteristic information for each personalized search engine further includes characteristic information for said personalized search engine based on personalization information for each base search engine represented by said personalized search engine. | 26. The system of claim 25 , wherein characteristic information for each personalized search engine further includes characteristic information for said personalized search engine based on personalization information for each base search engine represented by said personalized search engine. 27. The system of claim 26 , wherein characteristic information for each personalized search engine further includes one or more characteristic keywords representing searching capabilities of each base search engine of said personalized search engine. | 0.5 |
9,477,925 | 1 | 7 | 1. A system comprising: one or more processors; and one or more computer storage media storing computer-executable instructions that are executable to cause the one or more processors to perform acts comprising: providing a pipelined algorithm to train deep neural networks (DNNs) for performing data analysis based on training data, the DNNs being one of context-dependent DNNs or context-independent DNNs; partitioning the training data into sample batches of a specific batch size based on rates of data transfers between the one or more processors for executing the pipelined algorithm and an execution speed of each of the one or more processors; and pipelining an execution of the pipelined algorithm on the DNNs through the one or more processors to train the DNNs using the sample batches. | 1. A system comprising: one or more processors; and one or more computer storage media storing computer-executable instructions that are executable to cause the one or more processors to perform acts comprising: providing a pipelined algorithm to train deep neural networks (DNNs) for performing data analysis based on training data, the DNNs being one of context-dependent DNNs or context-independent DNNs; partitioning the training data into sample batches of a specific batch size based on rates of data transfers between the one or more processors for executing the pipelined algorithm and an execution speed of each of the one or more processors; and pipelining an execution of the pipelined algorithm on the DNNs through the one or more processors to train the DNNs using the sample batches. 7. The system of claim 1 , wherein the pipelining includes executing a model update prior to an input data forward propagation in a computation iteration of the pipelined algorithm. | 0.832717 |
8,880,455 | 3 | 4 | 3. The medical decision making support apparatus according to claim 2 , wherein the presentation unit presents medical information included in a partial set for which a highest degree of denial is calculated by the calculation unit and medical information included in a partial set for which a highest degree of affirmation is calculated, as the negative information and the affirmative information, respectively. | 3. The medical decision making support apparatus according to claim 2 , wherein the presentation unit presents medical information included in a partial set for which a highest degree of denial is calculated by the calculation unit and medical information included in a partial set for which a highest degree of affirmation is calculated, as the negative information and the affirmative information, respectively. 4. The medical decision making support apparatus according to claim 3 , wherein the inference unit obtains an inference result by calculating a posteriori probability of each inference result based on the plurality of pieces of medical information in association with a plurality of inference results for which a plurality of priori probabilities are set. | 0.5 |
5,537,488 | 33 | 35 | 33. The method of claim 24 wherein the training operation includes computing for each category a category class contrast indicative of the degree to which a peak class of the category dominates the category. | 33. The method of claim 24 wherein the training operation includes computing for each category a category class contrast indicative of the degree to which a peak class of the category dominates the category. 35. The method of claim 33 wherein if the category class contrast is below a threshold, the category is labeled as unknown. | 0.523256 |
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