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8,352,388 | 8 | 9 | 8. The system of claim 2 , further wherein hierarchies of association are constructed across a state space of term usage compatible for interpolation of mapping functions between sets of terms. | 8. The system of claim 2 , further wherein hierarchies of association are constructed across a state space of term usage compatible for interpolation of mapping functions between sets of terms. 9. The system of claim 8 , further wherein said mapping functions include one or more of fuzzy-type, weighted-type, or other types of mapping functions. | 0.940718 |
7,487,469 | 1 | 20 | 1. A computer readable storage medium having stored thereon an information processing program for causing a computer, connected to display means, coordinate set input means for inputting a coordinate set input instruction from a user, entry word data storage means for storing entry word data including a plurality of entry words, and explanation data storage means for storing explanation data associated with each of the plurality of entry words, to function as: first display control means for displaying, in an entry word candidate display area, a part of the plurality of entry words included in the entry word data; entry word change operation detection means for determining at least one of (a) whether or not a slide operation has been performed in the entry word candidate display area and (b) whether or not a long push operation has been performed in the entry word candidate display area, based on an output signal from the coordinate set input means, and detecting an entry word change operation by the user based on the determination result; second display control means for, when the entry word change operation by the user is detected by the entry word change operation detection means, erasing at least one entry word displayed in the entry word candidate display area and displaying a new entry word; and third display control means for, when the coordinate set input instruction is terminated on an entry word displayed in the entry word candidate display area based on an output signal from the coordinate set input means, reading the explanation data corresponding to the entry word and displaying an explanation of the entry word on the display means under a condition that no new entry word has been displayed by the second display control means at least in a time period from a start of the coordinate set input instruction until a termination thereof. | 1. A computer readable storage medium having stored thereon an information processing program for causing a computer, connected to display means, coordinate set input means for inputting a coordinate set input instruction from a user, entry word data storage means for storing entry word data including a plurality of entry words, and explanation data storage means for storing explanation data associated with each of the plurality of entry words, to function as: first display control means for displaying, in an entry word candidate display area, a part of the plurality of entry words included in the entry word data; entry word change operation detection means for determining at least one of (a) whether or not a slide operation has been performed in the entry word candidate display area and (b) whether or not a long push operation has been performed in the entry word candidate display area, based on an output signal from the coordinate set input means, and detecting an entry word change operation by the user based on the determination result; second display control means for, when the entry word change operation by the user is detected by the entry word change operation detection means, erasing at least one entry word displayed in the entry word candidate display area and displaying a new entry word; and third display control means for, when the coordinate set input instruction is terminated on an entry word displayed in the entry word candidate display area based on an output signal from the coordinate set input means, reading the explanation data corresponding to the entry word and displaying an explanation of the entry word on the display means under a condition that no new entry word has been displayed by the second display control means at least in a time period from a start of the coordinate set input instruction until a termination thereof. 20. A computer readable storage medium according to claim 1 , wherein the second display control means executes entry word change processing repeatedly while the user keeps the coordinate set input instruction after the long push operation is detected by the entry word change operation detection means. | 0.759524 |
8,457,347 | 16 | 18 | 16. The method, as in claim 15 , further comprising the step of: determining text data content of the text data. | 16. The method, as in claim 15 , further comprising the step of: determining text data content of the text data. 18. The method, as in claim 16 , further comprising the step of: reporting the text data content based upon the text data content. | 0.925029 |
8,126,712 | 1 | 12 | 1. An information communication terminal configured to exchange at least speech information with a plurality of information communication terminals, comprising: a speech recognition module configured to recognize the speech information to identify a plurality of words based on the recognized speech information; a storage medium configured to store keyword extraction condition setting data in which conditions for extracting keywords are set; a keyword extraction module configured to read the keyword extraction condition setting data to extract a plurality of keywords from the plurality of words; a subject extraction processing module configured to: associate the plurality of words read by the keyword extraction module with knowledge network data in which the plurality of keywords and a route among the plurality of keywords are described in a network form, generate a plurality of word pairs in a predetermined order from the plurality of keywords, extract the shortest route connecting words in each word pair from the knowledge network data, give point values to each word on each of the shortest routes, count the point values given to the respective words, and extract a word having a relatively high point value as a subject word; a related information acquisition module configured to acquire related information related to the plurality of keywords; and a related information output module configured to provide the related information to a monitor. | 1. An information communication terminal configured to exchange at least speech information with a plurality of information communication terminals, comprising: a speech recognition module configured to recognize the speech information to identify a plurality of words based on the recognized speech information; a storage medium configured to store keyword extraction condition setting data in which conditions for extracting keywords are set; a keyword extraction module configured to read the keyword extraction condition setting data to extract a plurality of keywords from the plurality of words; a subject extraction processing module configured to: associate the plurality of words read by the keyword extraction module with knowledge network data in which the plurality of keywords and a route among the plurality of keywords are described in a network form, generate a plurality of word pairs in a predetermined order from the plurality of keywords, extract the shortest route connecting words in each word pair from the knowledge network data, give point values to each word on each of the shortest routes, count the point values given to the respective words, and extract a word having a relatively high point value as a subject word; a related information acquisition module configured to acquire related information related to the plurality of keywords; and a related information output module configured to provide the related information to a monitor. 12. The information communication terminal according to claim 1 , wherein the subject extraction processing module gives, when the words have therebetween a plurality of the shortest routes, points to words existing on the plurality of the shortest routes. | 0.841975 |
8,965,922 | 14 | 17 | 14. An apparatus for generating one or more context-sensitive content recommendations, the apparatus comprising: a memory; and at least one processor, coupled to the memory, operative to: detect information needs of a user; retrieve one or more content-recommendation templates that substantially match the detected information needs; and instantiate the retrieved templates with one or more parameter values to generate one or more recommended contents. | 14. An apparatus for generating one or more context-sensitive content recommendations, the apparatus comprising: a memory; and at least one processor, coupled to the memory, operative to: detect information needs of a user; retrieve one or more content-recommendation templates that substantially match the detected information needs; and instantiate the retrieved templates with one or more parameter values to generate one or more recommended contents. 17. The apparatus of claim 14 , wherein said processor is further configured to instantiate said retrieved templates by: formulating queries for retrieving information from external sources; sending the queries to one or more external information sources and collecting the retrieval results; extracting one or more relevant information pieces to generate candidate template parameter values; instantiating the parameters of the retrieved templates; and ranking and filtering the instantiated templates. | 0.730728 |
8,117,225 | 17 | 20 | 17. The computer program product of claim 15 , further comprising code for receiving a request to access a digital entity associated with at least one of the different online applications. | 17. The computer program product of claim 15 , further comprising code for receiving a request to access a digital entity associated with at least one of the different online applications. 20. The computer program product of claim 17 , wherein the digital entity includes a file. | 0.991818 |
9,910,829 | 12 | 16 | 12. In a computer-based system, a method for automatically separating documents represented within a plurality of images by delineating document boundaries and identifying document types in accordance with classification rules, the method comprising: automatically generating classification rules that predict a document type or subdocument type for each of the plurality of images based on textual information and/or graphical information represented in each respective one of the plurality of images, wherein the classification rules are generated based on analyzing textual information and/or graphical information of a plurality of training images using one or more of: a probabilistic network; relational algebra; and machine learning techniques; obtaining the plurality of images; automatically categorizing a plurality of subdocument images into a plurality of predetermined categories based on analyzing textual infoiniation and/or image characteristics of each of the plurality of document images using the classification rules, wherein said step of automatically categorizing comprises: producing an output score for each subdocument image based on the analysis thereof using the classification rules, wherein each output score represents an estimated document type probability or a subdocument type probability; and using a graph search algorithm to determine an optimum categorization sequence from a plurality of possible categorization sequences for said plurality of subdocument images based on said output scores; automatically generating at least one identifier for identifying which of said plurality of subdocument images belongs to which of said plurality of predetermined categories; and separating subdocuments within the plurality of subdocument images from one another by either: electronically associating at least one computer-generated label with at least some of the plurality of subdocument images, each label corresponding to a different one of the plurality of categories and comprising one of the one or more identifiers generated for identifying which of the plurality of subdocument images belongs to which of the plurality of predetermined categories; or inserting one or more computer-generated separation pages between at least some of the plurality of subdocument images to delineate images belonging to different ones of the plurality of categories, each separation page comprising one of the one or more identifiers generated for identifying which of the plurality of subdocument images belongs to which of the plurality of predetermined categories; or both electronically associating the at least one computer-generated label with at least some of the plurality of subdocument images and inserting the one or more computer-generated separation pages between at least some of the plurality of subdocument images. | 12. In a computer-based system, a method for automatically separating documents represented within a plurality of images by delineating document boundaries and identifying document types in accordance with classification rules, the method comprising: automatically generating classification rules that predict a document type or subdocument type for each of the plurality of images based on textual information and/or graphical information represented in each respective one of the plurality of images, wherein the classification rules are generated based on analyzing textual information and/or graphical information of a plurality of training images using one or more of: a probabilistic network; relational algebra; and machine learning techniques; obtaining the plurality of images; automatically categorizing a plurality of subdocument images into a plurality of predetermined categories based on analyzing textual infoiniation and/or image characteristics of each of the plurality of document images using the classification rules, wherein said step of automatically categorizing comprises: producing an output score for each subdocument image based on the analysis thereof using the classification rules, wherein each output score represents an estimated document type probability or a subdocument type probability; and using a graph search algorithm to determine an optimum categorization sequence from a plurality of possible categorization sequences for said plurality of subdocument images based on said output scores; automatically generating at least one identifier for identifying which of said plurality of subdocument images belongs to which of said plurality of predetermined categories; and separating subdocuments within the plurality of subdocument images from one another by either: electronically associating at least one computer-generated label with at least some of the plurality of subdocument images, each label corresponding to a different one of the plurality of categories and comprising one of the one or more identifiers generated for identifying which of the plurality of subdocument images belongs to which of the plurality of predetermined categories; or inserting one or more computer-generated separation pages between at least some of the plurality of subdocument images to delineate images belonging to different ones of the plurality of categories, each separation page comprising one of the one or more identifiers generated for identifying which of the plurality of subdocument images belongs to which of the plurality of predetermined categories; or both electronically associating the at least one computer-generated label with at least some of the plurality of subdocument images and inserting the one or more computer-generated separation pages between at least some of the plurality of subdocument images. 16. The method of claim 12 , wherein said one or more identifiers comprise the at least one computer-generated label. | 0.838398 |
9,275,341 | 5 | 6 | 5. A computer system, comprising: at least one data input, the at least one data input for providing a data stream from at least one of a sensor, a data output from another computer, a computer program and a message containing encoded intelligible human language; at least one processor for processing each data stream for creating software objects corresponding to discrete informational elements present in the data stream; a first model comprising an object structure in which objects therein represent real world entities; a context model, dynamically updated by processing of the data stream; and a mapping function which communicates with the at least one processor and the context model and which associates the software objects with corresponding objects within the first model which causes computer code attached to the software objects of the first model to be executed and causes an alteration of the context model and depending on a result of the alteration providing at least one output which is an action dependent upon a state of the dynamically updated context model. | 5. A computer system, comprising: at least one data input, the at least one data input for providing a data stream from at least one of a sensor, a data output from another computer, a computer program and a message containing encoded intelligible human language; at least one processor for processing each data stream for creating software objects corresponding to discrete informational elements present in the data stream; a first model comprising an object structure in which objects therein represent real world entities; a context model, dynamically updated by processing of the data stream; and a mapping function which communicates with the at least one processor and the context model and which associates the software objects with corresponding objects within the first model which causes computer code attached to the software objects of the first model to be executed and causes an alteration of the context model and depending on a result of the alteration providing at least one output which is an action dependent upon a state of the dynamically updated context model. 6. A computer system in accordance with claim 5 comprising: a module which communicates with the first model for controlling an action in response to an internal utility function. | 0.801991 |
9,544,402 | 1 | 4 | 1. A method for encoding a plurality of key matching rules grouped in a chunk, each of the key matching rules beginning with a header and having at least one dimension, the method comprising: in a rule encoding engine, communicatively coupled to memory and provided with a chunk of key matching rules, building a multi-rule corresponding to the chunk comprising: storing in the memory a multi-rule header of the multi-rule, the multi-rule header representing, collectively, a plurality of headers stored one after the other, the multi-rule header being decoded by a rule matching engine in a single decode operation to extract the plurality of headers of the key matching rules, wherein the plurality of headers include values which control the rule matching engine processing of the key matching rules, including dimensions, the rule matching engine formats the key matching rules based on a key and matches the key matching rules against the key to find a match based on the values stored in the plurality of headers. | 1. A method for encoding a plurality of key matching rules grouped in a chunk, each of the key matching rules beginning with a header and having at least one dimension, the method comprising: in a rule encoding engine, communicatively coupled to memory and provided with a chunk of key matching rules, building a multi-rule corresponding to the chunk comprising: storing in the memory a multi-rule header of the multi-rule, the multi-rule header representing, collectively, a plurality of headers stored one after the other, the multi-rule header being decoded by a rule matching engine in a single decode operation to extract the plurality of headers of the key matching rules, wherein the plurality of headers include values which control the rule matching engine processing of the key matching rules, including dimensions, the rule matching engine formats the key matching rules based on a key and matches the key matching rules against the key to find a match based on the values stored in the plurality of headers. 4. The method of claim 1 wherein storing the multi-rule header of the multi-rule further includes, given key matching rules each having at least one dimension, storing, consecutively, an enable value for each dimension in which storing a first value for the enable value corresponding to a subject dimension enables matching of the subject dimension, while storing a second value instead of the first value disables matching of the subject dimension. | 0.505495 |
8,751,636 | 1 | 10 | 1. A computer-implemented method comprising: identifying third-party content objects associated with a user of the social networking system; establishing, by a computer, for each of a plurality of time periods of a day, a maximum rate at which to provide notifications of third-party content objects to the user, where the maximum rate is a maximum number of notifications that can be sent to the user during a particular time period; providing a first set of notifications of third-party content objects to a user device of the user within the maximum rate for each of the plurality of time periods; identifying user interactions with the first set of notifications; identifying patterns in the user interactions describing characteristics of the user's interactions with the first set of notifications; adjusting the maximum rate for each of the plurality of time periods based at least in part on the identified patterns; and providing a second set of notifications of third-party content objects to the user device within the adjusted maximum rate for each of the plurality of time periods. | 1. A computer-implemented method comprising: identifying third-party content objects associated with a user of the social networking system; establishing, by a computer, for each of a plurality of time periods of a day, a maximum rate at which to provide notifications of third-party content objects to the user, where the maximum rate is a maximum number of notifications that can be sent to the user during a particular time period; providing a first set of notifications of third-party content objects to a user device of the user within the maximum rate for each of the plurality of time periods; identifying user interactions with the first set of notifications; identifying patterns in the user interactions describing characteristics of the user's interactions with the first set of notifications; adjusting the maximum rate for each of the plurality of time periods based at least in part on the identified patterns; and providing a second set of notifications of third-party content objects to the user device within the adjusted maximum rate for each of the plurality of time periods. 10. The computer-implemented method of claim 1 , wherein identifying the patterns in the user interactions describing characteristics of the user's interactions with the first set of notifications comprises: identifying a geographic location of the user in which the user most frequently interacted with the first set of notifications; and increasing the maximum rate in which to provide notifications of third-party content objects when the user is located at the geographic location. | 0.578993 |
9,747,331 | 8 | 13 | 8. A computer program product for accessing data within a database object based on a query with a predicate including a plurality of conditional expressions, wherein an element of the database object is stored among a plurality of different storage regions with each storage region being associated with first and second range values indicating a value range for element values within that storage region, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising computer readable program code configured to: apply each conditional expression of the query predicate to at least one of the first and second range values for each of the storage regions to produce evaluation results of that conditional expression for the storage regions, wherein each storage region comprises units of column data, and applying each conditional expression further comprises: inserting mock data into units of column data of a storage region that are determined not to be scanned based on application of that conditional expression; combine the evaluation result of each conditional expression for a corresponding storage region to produce aggregated results for each of the storage regions, wherein the aggregated result for a corresponding storage region indicates at least one of a presence of data satisfying the conditional expressions within that storage region, an absence of data satisfying the conditional expressions within that storage region, and insufficient information to determine the presence of data satisfying the conditional expressions within that storage region, and wherein the aggregated result for at least one storage region indicates insufficient information; provide information to evaluate one or more conditional expressions for a storage region in response to the aggregated result for that storage region indicating insufficient information, wherein the provided information indicates one or more columns within that storage region; and scan one or more corresponding individual storage regions based on the aggregated results for those storage regions and the provided information. | 8. A computer program product for accessing data within a database object based on a query with a predicate including a plurality of conditional expressions, wherein an element of the database object is stored among a plurality of different storage regions with each storage region being associated with first and second range values indicating a value range for element values within that storage region, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising computer readable program code configured to: apply each conditional expression of the query predicate to at least one of the first and second range values for each of the storage regions to produce evaluation results of that conditional expression for the storage regions, wherein each storage region comprises units of column data, and applying each conditional expression further comprises: inserting mock data into units of column data of a storage region that are determined not to be scanned based on application of that conditional expression; combine the evaluation result of each conditional expression for a corresponding storage region to produce aggregated results for each of the storage regions, wherein the aggregated result for a corresponding storage region indicates at least one of a presence of data satisfying the conditional expressions within that storage region, an absence of data satisfying the conditional expressions within that storage region, and insufficient information to determine the presence of data satisfying the conditional expressions within that storage region, and wherein the aggregated result for at least one storage region indicates insufficient information; provide information to evaluate one or more conditional expressions for a storage region in response to the aggregated result for that storage region indicating insufficient information, wherein the provided information indicates one or more columns within that storage region; and scan one or more corresponding individual storage regions based on the aggregated results for those storage regions and the provided information. 13. The computer program product of claim 8 , wherein the database object includes a database table, and the information provided includes database table columns providing the information to evaluate the conditional expressions. | 0.784906 |
10,095,696 | 2 | 5 | 2. The system of claim 1 , wherein the one or more temporal attributes and/or spatial attributes include one or more of a geolocation attribute, a device attribute, and/or a content attribute. | 2. The system of claim 1 , wherein the one or more temporal attributes and/or spatial attributes include one or more of a geolocation attribute, a device attribute, and/or a content attribute. 5. The system of claim 2 , wherein the content attribute includes one or more of an action depicted within the digital media content, an activity depicted within the digital media content, and/or one or more objects depicted within the digital media content. | 0.941918 |
9,990,564 | 8 | 13 | 8. A system for optical character recognition, the system comprising: at least one processor; and a non-transitory computer-readable medium storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising: detecting a presence of a character in an image data; providing the image data to a plurality of customized machine learning algorithms for character recognition, wherein each of the plurality of customized machine learning algorithms is configured to recognize a pre-defined character; in response to a negative character recognition, presenting one or more suggestions for the character to the user, wherein the one or more suggestions comprises characters corresponding to one or more of the plurality of customized machine learning algorithms whose outputs meet a pre-defined threshold criteria for suggestion but does not meet a pre-defined threshold criteria for recognition; in response to the one or more suggestions being rejected by the user, prompting the user to identify the character; determining a presence of the character in a set of pre-defined characters; in response to a positive presence, training a customized machine learning algorithm corresponding to the character; and in response to a negative presence, adding the character in the set of pre-defined characters and dynamically creating a customized machine learning algorithm corresponding to the character; and in response to one of the one or more suggestions being identified by the user, training a customized machine learning algorithm corresponding to the character. | 8. A system for optical character recognition, the system comprising: at least one processor; and a non-transitory computer-readable medium storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising: detecting a presence of a character in an image data; providing the image data to a plurality of customized machine learning algorithms for character recognition, wherein each of the plurality of customized machine learning algorithms is configured to recognize a pre-defined character; in response to a negative character recognition, presenting one or more suggestions for the character to the user, wherein the one or more suggestions comprises characters corresponding to one or more of the plurality of customized machine learning algorithms whose outputs meet a pre-defined threshold criteria for suggestion but does not meet a pre-defined threshold criteria for recognition; in response to the one or more suggestions being rejected by the user, prompting the user to identify the character; determining a presence of the character in a set of pre-defined characters; in response to a positive presence, training a customized machine learning algorithm corresponding to the character; and in response to a negative presence, adding the character in the set of pre-defined characters and dynamically creating a customized machine learning algorithm corresponding to the character; and in response to one of the one or more suggestions being identified by the user, training a customized machine learning algorithm corresponding to the character. 13. The system of claim 8 , wherein dynamically creating the customized machine learning algorithm corresponding to the character comprises learning the character by deep learning mechanism. | 0.815534 |
9,152,324 | 1 | 6 | 1. A computer-implemented method, comprising: displaying a document containing two or more hyperlinks, wherein at least two of the hyperlinks are initially non-highlighted; following the initial display, receiving a request, based on non-alphanumeric character input, to navigate to one of the at least two non-highlighted hyperlinks that are included as part of the document, wherein one of the plurality of hyperlinks appears as a graphical image; determining which of the at least two non-highlighted hyperlinks to navigate to, the determination based on identifying the next hyperlink in an index of hyperlinks, the index comprised of sequential list of each hyperlink in the document; responsive to receiving the non-alphanumeric character based request, providing a first focus shape to the one non-highlighted hyperlink, without providing the focus shape to any other hyperlinks included as part of the document; and wherein the hyperlink to which the focus shape has been provided is activated after receiving an activation request. | 1. A computer-implemented method, comprising: displaying a document containing two or more hyperlinks, wherein at least two of the hyperlinks are initially non-highlighted; following the initial display, receiving a request, based on non-alphanumeric character input, to navigate to one of the at least two non-highlighted hyperlinks that are included as part of the document, wherein one of the plurality of hyperlinks appears as a graphical image; determining which of the at least two non-highlighted hyperlinks to navigate to, the determination based on identifying the next hyperlink in an index of hyperlinks, the index comprised of sequential list of each hyperlink in the document; responsive to receiving the non-alphanumeric character based request, providing a first focus shape to the one non-highlighted hyperlink, without providing the focus shape to any other hyperlinks included as part of the document; and wherein the hyperlink to which the focus shape has been provided is activated after receiving an activation request. 6. The computer-implemented method of claim 1 , wherein the non-highlighted hyperlink and the one or more other hyperlinks are part of an image map that is configured to be displayed as at least a portion of the document. | 0.869385 |
8,799,276 | 11 | 20 | 11. One or more non-transitory machine-readable media storing instructions that are executable by one or more processing devices to perform operations comprising: receiving an input query for a subject having a web site; determining that the input query is a navigational query, the navigational query comprising a query to locate the web site of the subject; and in response to determining that the input query is a navigational query: identifying a first page on a social network, the first page being a page specific to the subject within the social network; obtaining content from the first page; obtaining search results corresponding to the input query; identifying a second page for the subject from among the search results, the second page comprising a page of the web site and being represented in the search results by a snippet of content associated with the second page; combining the content from the first page with the snippet to thereby produce combined content; and outputting data corresponding to the combined content to display the combined content in search results. | 11. One or more non-transitory machine-readable media storing instructions that are executable by one or more processing devices to perform operations comprising: receiving an input query for a subject having a web site; determining that the input query is a navigational query, the navigational query comprising a query to locate the web site of the subject; and in response to determining that the input query is a navigational query: identifying a first page on a social network, the first page being a page specific to the subject within the social network; obtaining content from the first page; obtaining search results corresponding to the input query; identifying a second page for the subject from among the search results, the second page comprising a page of the web site and being represented in the search results by a snippet of content associated with the second page; combining the content from the first page with the snippet to thereby produce combined content; and outputting data corresponding to the combined content to display the combined content in search results. 20. The one or more non-transitory machine-readable media of claim 11 , wherein obtaining content from the first page comprises obtaining the content based on popularity of the content. | 0.787844 |
8,515,751 | 12 | 13 | 12. A system, comprising: an interface configured to receive an input signal comprising data that corresponds to one or more words; an interface configured to pass the input signal to a text recognition system that generates a recognized text string based on the input signal; an interface configured to receive the recognized text string from the text recognition system; an interface configured to present the recognized text string to a user; an interface configured to receiving a corrected text string based on input from the user; means for checking if an edit distance between the corrected text string and the recognized text string is below a threshold, wherein the threshold depends on a length of the corrected text string; and an interface configured to, if the edit distance is below the threshold, pass the corrected text string to the text recognition system. | 12. A system, comprising: an interface configured to receive an input signal comprising data that corresponds to one or more words; an interface configured to pass the input signal to a text recognition system that generates a recognized text string based on the input signal; an interface configured to receive the recognized text string from the text recognition system; an interface configured to present the recognized text string to a user; an interface configured to receiving a corrected text string based on input from the user; means for checking if an edit distance between the corrected text string and the recognized text string is below a threshold, wherein the threshold depends on a length of the corrected text string; and an interface configured to, if the edit distance is below the threshold, pass the corrected text string to the text recognition system. 13. The system of claim 12 , wherein the edit distance represents the minimum number of single character insertion, deletion, or substitution operations required to transform the recognized text string into the corrected text string. | 0.728438 |
9,747,377 | 10 | 11 | 10. A system comprising a processor in electronic communication with computer-readable storage media, the computer readable-storage media storing instructions that, when executed, perform a method, the method comprising: receiving a search query; responsive to receiving the query: obtaining a set of search results corresponding to the query; and displaying at least a portion of the set of search results within a main search engine results view; obtaining a set of related content corresponding to the query, the set of related content determined by narrowing the query; receiving a semantic zoom command associated with the main search engine results view; and in response to receiving the semantic zoom command, transitioning the search interface from the main search engine results view to a related content view. | 10. A system comprising a processor in electronic communication with computer-readable storage media, the computer readable-storage media storing instructions that, when executed, perform a method, the method comprising: receiving a search query; responsive to receiving the query: obtaining a set of search results corresponding to the query; and displaying at least a portion of the set of search results within a main search engine results view; obtaining a set of related content corresponding to the query, the set of related content determined by narrowing the query; receiving a semantic zoom command associated with the main search engine results view; and in response to receiving the semantic zoom command, transitioning the search interface from the main search engine results view to a related content view. 11. The system of claim 10 , the obtaining a set of related content comprising: obtaining the link to the application. | 0.672222 |
8,965,904 | 6 | 7 | 6. The method according to claim 5 , wherein at least one of said plurality of scores is calculated based on said number of unique matched query-keywords, said number of matched keyword, said total number of distances that are less than a threshold distance within the file and a distance calculated from said plurality of distances. | 6. The method according to claim 5 , wherein at least one of said plurality of scores is calculated based on said number of unique matched query-keywords, said number of matched keyword, said total number of distances that are less than a threshold distance within the file and a distance calculated from said plurality of distances. 7. The method according to claim 6 , wherein said calculated distance is at least one of: a distance between a first matched keyword and a last matched keyword, a shortest distance between two adjacent matched keywords, a largest distance between two adjacent matched keywords, or a square root of sum of square of distances between any two adjacent matched keywords. | 0.909739 |
9,704,483 | 1 | 9 | 1. A computer-implemented method comprising: receiving, by a term pre-processor module of a server-based automated speech recognition system that includes (a) the term pre-processor module, (b) a user similarity determiner module, (c) a vocabulary generator module, (d) a language model biaser module, and (e) an automated speech recognizer, and from a device associated with a target user, (i) data including a set of terms associated with the target user that includes terms from one or more queries previously submitted by the target user, and, (ii) from each of multiple other users, data including a set of terms associated with the other user; selecting, by the user similarity determiner module of the server-based automated speech recognition system, a particular other user based at least on comparing the set of terms associated with the target user to the sets of terms associated with the other users; selecting, by the vocabulary generator module of the server-based automated speech recognition system, one or more terms from the set of terms that is associated with the particular other user; obtaining, by the language model biaser module of the server-based automated speech recognition system and based on the selected terms that are associated with the particular other user, a biased language model; using, by the automated speech recognizer of the server-based automated speech recognition system, the biased language model generate a speech recognition output; and providing, by the server-based automated speech recognition system, the speech recognition output to the device associated with the target user. | 1. A computer-implemented method comprising: receiving, by a term pre-processor module of a server-based automated speech recognition system that includes (a) the term pre-processor module, (b) a user similarity determiner module, (c) a vocabulary generator module, (d) a language model biaser module, and (e) an automated speech recognizer, and from a device associated with a target user, (i) data including a set of terms associated with the target user that includes terms from one or more queries previously submitted by the target user, and, (ii) from each of multiple other users, data including a set of terms associated with the other user; selecting, by the user similarity determiner module of the server-based automated speech recognition system, a particular other user based at least on comparing the set of terms associated with the target user to the sets of terms associated with the other users; selecting, by the vocabulary generator module of the server-based automated speech recognition system, one or more terms from the set of terms that is associated with the particular other user; obtaining, by the language model biaser module of the server-based automated speech recognition system and based on the selected terms that are associated with the particular other user, a biased language model; using, by the automated speech recognizer of the server-based automated speech recognition system, the biased language model generate a speech recognition output; and providing, by the server-based automated speech recognition system, the speech recognition output to the device associated with the target user. 9. The method of claim 1 , further comprising: receiving, from the device associated with the target user, a subsequent query of the target user; using, by the automated speech recognizer, the biased language model to generate an output responsive to the subsequent query of the target user; and providing the output to the device associated with the target user. | 0.798557 |
8,903,719 | 8 | 9 | 8. One or more non-transitory computer-readable media having computer-executable instructions embodied thereon that, when executed by a computing device, facilitate a method of providing context-sensitive writing assistance, the method comprising: determining a context of a textual communication that a user is composing, wherein the context of the textual communication comprises a specific recipient of the textual communication and a specific communication medium in which the textual communication is being composed; selecting one or more dictionaries from a plurality of dictionaries, wherein the one or more dictionaries include words that are consistent with a communication style used in previous textual communications in the specific communication medium that are addressed to the specific recipient or written by the specific recipient; and providing, by way of the computing device, writing assistance that utilizes the one or more dictionaries, thereby tuning the writing assistance to match the communication style, wherein the writing assistance comprises a text slang to proper English conversion function that is activated only when a text-slang dictionary is not one of the one or more dictionaries, wherein the writing assistance is provided while the textual communication is being composed. | 8. One or more non-transitory computer-readable media having computer-executable instructions embodied thereon that, when executed by a computing device, facilitate a method of providing context-sensitive writing assistance, the method comprising: determining a context of a textual communication that a user is composing, wherein the context of the textual communication comprises a specific recipient of the textual communication and a specific communication medium in which the textual communication is being composed; selecting one or more dictionaries from a plurality of dictionaries, wherein the one or more dictionaries include words that are consistent with a communication style used in previous textual communications in the specific communication medium that are addressed to the specific recipient or written by the specific recipient; and providing, by way of the computing device, writing assistance that utilizes the one or more dictionaries, thereby tuning the writing assistance to match the communication style, wherein the writing assistance comprises a text slang to proper English conversion function that is activated only when a text-slang dictionary is not one of the one or more dictionaries, wherein the writing assistance is provided while the textual communication is being composed. 9. The media of claim 8 , wherein the one or more dictionaries are selected using a communication profile for the specific recipient that maintains the communication style for the specific recipient on a per-communication-medium basis. | 0.502119 |
9,626,081 | 1 | 7 | 1. A system, comprising: a processing device; and a memory device in communication with the processing device, the memory device storing instructions that when executed by the processing device result in: receiving a geographic location indicator associated with a plurality of geographic location-based rules stored in a database; monitoring a user input interface of an interactive user display for a user input string comprising a minimum number of characters; generating a suggestion request to retrieve a data set from the plurality of geographic location-based rules stored in the database that match the geographic location indicator and the user input string based on determining that the user input string includes at least the minimum number of characters, the geographic location-based rules constraining a plurality of numeric classification codes and corresponding descriptions based on the geographic location indicator, and a same numeric classification code having a different corresponding description defined by the geographic location-based rules; receiving the data set in response to the suggestion request; formatting the data set as a list comprising one or more entries, each of the entries comprising one of the numeric classification codes and one of the corresponding descriptions based on the geographic location indicator; and outputting the list on the interactive user display as one or more user selectable instances of the one or more entries. | 1. A system, comprising: a processing device; and a memory device in communication with the processing device, the memory device storing instructions that when executed by the processing device result in: receiving a geographic location indicator associated with a plurality of geographic location-based rules stored in a database; monitoring a user input interface of an interactive user display for a user input string comprising a minimum number of characters; generating a suggestion request to retrieve a data set from the plurality of geographic location-based rules stored in the database that match the geographic location indicator and the user input string based on determining that the user input string includes at least the minimum number of characters, the geographic location-based rules constraining a plurality of numeric classification codes and corresponding descriptions based on the geographic location indicator, and a same numeric classification code having a different corresponding description defined by the geographic location-based rules; receiving the data set in response to the suggestion request; formatting the data set as a list comprising one or more entries, each of the entries comprising one of the numeric classification codes and one of the corresponding descriptions based on the geographic location indicator; and outputting the list on the interactive user display as one or more user selectable instances of the one or more entries. 7. The system of claim 1 , wherein the data set received in response to the suggestion request further comprises a synonym match of the user input string. | 0.866087 |
6,092,036 | 7 | 8 | 7. The system of claim 1 further including a translation master table, responsive to said computer software, said translation master table including a locality identifier and translation data for at least said target language identified by said locality setting. | 7. The system of claim 1 further including a translation master table, responsive to said computer software, said translation master table including a locality identifier and translation data for at least said target language identified by said locality setting. 8. The system of claim 7 wherein said translation data in said translation master table includes character and font data for said target language identified by said locality setting. | 0.959321 |
9,405,652 | 3 | 4 | 3. The system of claim 1 , wherein the translator module compiles the probe script by translating the input source code into a second source code language, and compiling the second source code language to a kernel module. | 3. The system of claim 1 , wherein the translator module compiles the probe script by translating the input source code into a second source code language, and compiling the second source code language to a kernel module. 4. The system of claim 3 , wherein the second source code language is C. | 0.985099 |
8,645,346 | 14 | 20 | 14. A computer-readable storage memory comprising computer program instructions for processing a complex user query, the program instructions executable by one or more processors to perform actions including: a) receiving the user query; b) generating a logical operator graph representative of the user query, the logical operator graph representing a composable SQL query that includes a plurality of sub-queries; c) generating the composable SQL query based on the logical operator graph and a capability set corresponding to a data source, the composable SQL query being remotable to the data source and including a plurality of SQL aggregations or manipulations; d) sending the composable SQL query to the data source; e) receiving a response set from the data source; and f) sending the response set to a client; wherein the logical operator graph is processed so that each data source returns a minimum number of columns that are sufficient to answer the complex user query. | 14. A computer-readable storage memory comprising computer program instructions for processing a complex user query, the program instructions executable by one or more processors to perform actions including: a) receiving the user query; b) generating a logical operator graph representative of the user query, the logical operator graph representing a composable SQL query that includes a plurality of sub-queries; c) generating the composable SQL query based on the logical operator graph and a capability set corresponding to a data source, the composable SQL query being remotable to the data source and including a plurality of SQL aggregations or manipulations; d) sending the composable SQL query to the data source; e) receiving a response set from the data source; and f) sending the response set to a client; wherein the logical operator graph is processed so that each data source returns a minimum number of columns that are sufficient to answer the complex user query. 20. The computer-readable storage memory of claim 14 , the actions further including if a logical operator has a free column that is an output column of a child node logical operator, inserting a filter operator to cause the output column to be equivalent to the free column. | 0.66545 |
8,086,600 | 25 | 33 | 25. A computer-readable storage device having stored thereon instructions that, when executed by a computer, cause the computer to perform operations comprising: receiving a plurality of first search results in a first presentation format, the first search results received from a first search engine, the first search results identified for a search query directed to the first search engine, the first search results having an associated order indicative of respective first quality scores that are used to rank the first search results; receiving one or more second search results in a second presentation format different from the first presentation format, the second search results received from a second search engine, the second search results identified for the search query directed to the second search engine, wherein the first search engine searches a first corpus of first resources, wherein the second search engine searches a second corpus of second resources, and wherein the first search engine and the second search engines are distinct from each other; obtaining a respective first quality score for a plurality of the first search results, the respective first quality score determined in relation to the corpus of first resources and obtaining a respective second quality score for each of the one or more second search results, each respective second quality score determined in relation to the corpus of second resources; and inserting one or more of the second search results into the order including decreasing one or more of the respective first quality scores by reducing a contribution of a scoring feature unique to the first search results and distinct from scoring features of the second search results so that the inserted second search results occur within a number of top-ranked search results in the order. | 25. A computer-readable storage device having stored thereon instructions that, when executed by a computer, cause the computer to perform operations comprising: receiving a plurality of first search results in a first presentation format, the first search results received from a first search engine, the first search results identified for a search query directed to the first search engine, the first search results having an associated order indicative of respective first quality scores that are used to rank the first search results; receiving one or more second search results in a second presentation format different from the first presentation format, the second search results received from a second search engine, the second search results identified for the search query directed to the second search engine, wherein the first search engine searches a first corpus of first resources, wherein the second search engine searches a second corpus of second resources, and wherein the first search engine and the second search engines are distinct from each other; obtaining a respective first quality score for a plurality of the first search results, the respective first quality score determined in relation to the corpus of first resources and obtaining a respective second quality score for each of the one or more second search results, each respective second quality score determined in relation to the corpus of second resources; and inserting one or more of the second search results into the order including decreasing one or more of the respective first quality scores by reducing a contribution of a scoring feature unique to the first search results and distinct from scoring features of the second search results so that the inserted second search results occur within a number of top-ranked search results in the order. 33. The storage device of claim 25 , wherein: the first resources are generic web pages and the second resources are image resources. | 0.85911 |
8,368,924 | 1 | 2 | 1. A method of printing a document having a printed copy detection pattern, comprising: receiving at an intermediate electronic device printer control commands from a computing device, said printer control commands including: (i) commands for printing based on document data, and (ii) an identification of a determined portion of the document data that is to be used in generating said printed copy detection pattern; generating in said intermediate electronic device copy detection pattern data using said determined portion of the document data and a cryptographic key stored in the intermediate electronic device; generating in said intermediate electronic device modified printer control commands, said modified printer control commands including commands for printing a first document portion based on the document data and a second document portion including said printed copy detection pattern based on said copy detection pattern data; and sending said modified printer control commands to a printing device for printing said first document portion and said second document portion. | 1. A method of printing a document having a printed copy detection pattern, comprising: receiving at an intermediate electronic device printer control commands from a computing device, said printer control commands including: (i) commands for printing based on document data, and (ii) an identification of a determined portion of the document data that is to be used in generating said printed copy detection pattern; generating in said intermediate electronic device copy detection pattern data using said determined portion of the document data and a cryptographic key stored in the intermediate electronic device; generating in said intermediate electronic device modified printer control commands, said modified printer control commands including commands for printing a first document portion based on the document data and a second document portion including said printed copy detection pattern based on said copy detection pattern data; and sending said modified printer control commands to a printing device for printing said first document portion and said second document portion. 2. The method according to claim 1 , wherein said printer control commands and said modified printer control commands are PCL commands. | 0.894696 |
10,133,776 | 13 | 21 | 13. One or more non-transitory computer-readable storage media storing sequences of instructions that, when executed by one or more computing devices, cause: receiving a first query comprising an outer query that: includes one or more set operators; instantiates a particular data object using a first name; references a first instance of the particular data object using said first name; wherein at least a particular set operator of the one or more set operators includes a particular subquery that: instantiates the particular data object using a second name; references a second instance of the particular data object using said second name; based at least in part on the first query, transforming the first query to a second query that does not contain at least the particular subquery or the particular set operator; wherein the second query comprises an added predicate that is based at least in part on the particular subquery; wherein the added predicate references the first instance of the particular data object using said first name without referencing the second instance of the particular data object using said second name; and wherein the second query is semantically equivalent to the first query; generating an execution plan for executing the second query; causing execution of the second query instead of the first query based on the execution plan for executing the second query. | 13. One or more non-transitory computer-readable storage media storing sequences of instructions that, when executed by one or more computing devices, cause: receiving a first query comprising an outer query that: includes one or more set operators; instantiates a particular data object using a first name; references a first instance of the particular data object using said first name; wherein at least a particular set operator of the one or more set operators includes a particular subquery that: instantiates the particular data object using a second name; references a second instance of the particular data object using said second name; based at least in part on the first query, transforming the first query to a second query that does not contain at least the particular subquery or the particular set operator; wherein the second query comprises an added predicate that is based at least in part on the particular subquery; wherein the added predicate references the first instance of the particular data object using said first name without referencing the second instance of the particular data object using said second name; and wherein the second query is semantically equivalent to the first query; generating an execution plan for executing the second query; causing execution of the second query instead of the first query based on the execution plan for executing the second query. 21. The one or more non-transitory computer-readable storage media of claim 13 , wherein the sequences of instructions include instructions that, when executed by said one or more computing devices, cause: determining that the particular subquery does not reference any instances of any data objects other than the particular data object and that a single predicate of the particular subquery references the second instance of the particular data object; based at least in part on determining that the particular subquery does not reference any instances of any data objects other than the particular data object and that the single predicate of the particular subquery references the second instance of the particular data object, eliminating the particular subquery and generating the added predicate. | 0.536374 |
8,290,953 | 8 | 12 | 8. A system, comprising: a memory that stores resource names; and a processor programmed to: identify rule attributes for each of a plurality of prioritized naming rules, where a combination of the rule attributes represents a plurality of identifiers that uniquely identify resources via one or more of the plurality of prioritized naming rules; determine a naming context that makes the combination of the rule attributes for each of the plurality of prioritized naming rules unique; correlate the resource names for a plurality of resources generated by a plurality of management products within a single management domain based upon the plurality of prioritized naming rules comprising being programmed to correlate the resource names for the plurality of resources using the determined naming context and the identified rule attributes for each of the plurality of prioritized naming rules; determine whether each of the plurality of resources has more than one valid name within the single management domain based upon the correlated resource names for the plurality of resources; and select, for each resource determined to have more than one valid name within the single management domain, one of the valid names as a master name for the resource using the plurality of prioritized naming rules. | 8. A system, comprising: a memory that stores resource names; and a processor programmed to: identify rule attributes for each of a plurality of prioritized naming rules, where a combination of the rule attributes represents a plurality of identifiers that uniquely identify resources via one or more of the plurality of prioritized naming rules; determine a naming context that makes the combination of the rule attributes for each of the plurality of prioritized naming rules unique; correlate the resource names for a plurality of resources generated by a plurality of management products within a single management domain based upon the plurality of prioritized naming rules comprising being programmed to correlate the resource names for the plurality of resources using the determined naming context and the identified rule attributes for each of the plurality of prioritized naming rules; determine whether each of the plurality of resources has more than one valid name within the single management domain based upon the correlated resource names for the plurality of resources; and select, for each resource determined to have more than one valid name within the single management domain, one of the valid names as a master name for the resource using the plurality of prioritized naming rules. 12. The system of claim 8 , where the plurality of prioritized naming rules comprises prioritized naming rules for software resources and prioritized naming rules for hardware resources, and where: the rule attributes for each of the prioritized naming rules for software resources comprise at least one of an operating system (OS) type, an OS version, a host name of a computer system in which software is running, total memory used by the software, and total physically attached storage that is available to the software; and the rule attributes for each of the prioritized naming rules for hardware resources comprise at least one of a dedicated role of a hardware resource, a processor family used by the hardware resource, a manufacturer of the hardware resource, a model of the hardware resource, a machine type, and a serial number. | 0.591529 |
9,852,729 | 8 | 11 | 8. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, generating a first score based at least partly on a likelihood that a frame, of a window of sequential frames of audio data, comprises audio data corresponding to a keyword, wherein the window comprises the frame and an equal quantity of (1) frames before the frame and (2) frames after the frame; generating a second score based at least partly on a likelihood that the frame comprises audio data corresponding to background audio; determining a difference between the first score and the second score; and determining that the frame corresponds to an end of the keyword based at least partly on the difference being greater than differences determined for the frames before the frame, and differences determined for the frames after the frame. | 8. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, generating a first score based at least partly on a likelihood that a frame, of a window of sequential frames of audio data, comprises audio data corresponding to a keyword, wherein the window comprises the frame and an equal quantity of (1) frames before the frame and (2) frames after the frame; generating a second score based at least partly on a likelihood that the frame comprises audio data corresponding to background audio; determining a difference between the first score and the second score; and determining that the frame corresponds to an end of the keyword based at least partly on the difference being greater than differences determined for the frames before the frame, and differences determined for the frames after the frame. 11. The computer-implemented method of claim 8 , further comprising suppressing, for a period of time, determining that a second frame, different than the frame, corresponds to an end of the keyword. | 0.876551 |
8,433,123 | 47 | 48 | 47. The method of claim 43 , wherein the data file includes deposit information, the deposit information at least including a declared deposit amount associated with the deposit transaction. | 47. The method of claim 43 , wherein the data file includes deposit information, the deposit information at least including a declared deposit amount associated with the deposit transaction. 48. The method of claim 47 , further comprising in response to the determination of the suspect record, determining a credit amount, the credit amount being a percentage of the declared deposit amount minus the value included in the suspect record. | 0.932682 |
8,150,830 | 24 | 25 | 24. A computer program product, tangibly embodied on a machine readable medium, the computer program product comprising instructions that, when read by a machine, operate to cause data processing apparatus to: provide an association of a term and a primary resource identifier, the association input by a user; receive a search query input from a user; determine whether the search query matches the term; if the search query matches the term, present the primary resource identifier without initiating a search; and if the search query does not match the term, initiate a search and present a search result based on the search query. | 24. A computer program product, tangibly embodied on a machine readable medium, the computer program product comprising instructions that, when read by a machine, operate to cause data processing apparatus to: provide an association of a term and a primary resource identifier, the association input by a user; receive a search query input from a user; determine whether the search query matches the term; if the search query matches the term, present the primary resource identifier without initiating a search; and if the search query does not match the term, initiate a search and present a search result based on the search query. 25. The computer program product of claim 24 , wherein the primary resource identifier is in a form of a Uniform Resource Locator (URL). | 0.866405 |
9,208,255 | 4 | 5 | 4. The method according to claim 1 , wherein the designing the source XML document comprises: defining a source XML document that includes a preset structure and preset source data by using the user-defined tags; and duplicating the source XML document and then creating a duplicated XML document including a structure and source data which are identical to those of the source XML document. | 4. The method according to claim 1 , wherein the designing the source XML document comprises: defining a source XML document that includes a preset structure and preset source data by using the user-defined tags; and duplicating the source XML document and then creating a duplicated XML document including a structure and source data which are identical to those of the source XML document. 5. The method according to claim 4 , wherein at the defining the source XML document, the source XML document stores an absolute path of the user-defined tags as user-defined tag values using an XML tree structure. | 0.95991 |
4,092,493 | 3 | 4 | 3. A speech recognizer for identifying an unknown speech segment in a continuous speech signal as one of a plurality of identified speech segments comprising means responsive to repetitions of strings of identified speech segments for generating a set of reference signals for each identified speech segment representative of the means and variances of the linear prediction characterstics of the average voiced intervals of said identified speech segment; means responsive to a string of unknown speech segments for partitioning said string into said unknown speech segments; means responsive to each partitioned unknown speech segment for generating a set of test signals representative of the linear prediction characteristics of the voiced intervals of said partitioned unknown speech segment; means for time aligning said set of test signals to the average voiced intervals of each identified speech segment; means for forming a first correspondence signal representative of the correspondence between said aligned voiced interval test signals and said voiced interval reference signals for each identified speech segment; means for selecting the identified speech segment having the least first correspondence signal; means for generating a signal representative of the classification of the beginning of said unknown speech segment as one of voiced, unvoiced and silence; means jointly responsive to said classification signal, said selected identified speech segment identity and said first correspondence signals for generating a first signal when said classification signal is consistent with said selected identity and a second signal when said classification signal is inconsistent with said selected identity; means responsive to said first signal for identifying said unknown speech segment as said selected identified speech segment; means responsive to said second signal for forming a second correspondence signal from said aligned voiced interval test signals and said voiced interval reference signals for each identified speech segment; and means responsive to the second correspondence signals for identifying said unknown speech segment as the identified speech segment having the least second correspondence signal. | 3. A speech recognizer for identifying an unknown speech segment in a continuous speech signal as one of a plurality of identified speech segments comprising means responsive to repetitions of strings of identified speech segments for generating a set of reference signals for each identified speech segment representative of the means and variances of the linear prediction characterstics of the average voiced intervals of said identified speech segment; means responsive to a string of unknown speech segments for partitioning said string into said unknown speech segments; means responsive to each partitioned unknown speech segment for generating a set of test signals representative of the linear prediction characteristics of the voiced intervals of said partitioned unknown speech segment; means for time aligning said set of test signals to the average voiced intervals of each identified speech segment; means for forming a first correspondence signal representative of the correspondence between said aligned voiced interval test signals and said voiced interval reference signals for each identified speech segment; means for selecting the identified speech segment having the least first correspondence signal; means for generating a signal representative of the classification of the beginning of said unknown speech segment as one of voiced, unvoiced and silence; means jointly responsive to said classification signal, said selected identified speech segment identity and said first correspondence signals for generating a first signal when said classification signal is consistent with said selected identity and a second signal when said classification signal is inconsistent with said selected identity; means responsive to said first signal for identifying said unknown speech segment as said selected identified speech segment; means responsive to said second signal for forming a second correspondence signal from said aligned voiced interval test signals and said voiced interval reference signals for each identified speech segment; and means responsive to the second correspondence signals for identifying said unknown speech segment as the identified speech segment having the least second correspondence signal. 4. A speech recognizer for identifying an unknown speech segment in a continuous speech signal as one of a plurality of identified speech segments according to claim 3 wherein said unknown speech segment is an unknown spoken digit and each identified speech segment is an identified spoken digit. | 0.885891 |
7,725,307 | 20 | 21 | 20. The method of claim 18 , wherein steps (b) and (c) overlap in time. | 20. The method of claim 18 , wherein steps (b) and (c) overlap in time. 21. The method of claim 20 , wherein step (c) includes two sub-steps, including a step (c)′ wherein a preliminary query is generated based on said recognized text, and a step (c)″ wherein a final query is generated based on said preliminary query and said search predicates. | 0.919079 |
9,942,518 | 15 | 20 | 15. A non-transitory processor readable medium storing instructions that, when executed by a processor, cause the processor to: detect a plurality of participants within a field of view of a video camera of a video conference endpoint; calculate a proximity of each participant with respect to one or more other participants; group the participants into one or more groups based on the proximity such that the one or more groups include more than one participant; detect a first participant of a first group of the one or more groups as an active speaker; and alter a framing of a video output of the video conference endpoint to frame the first group. | 15. A non-transitory processor readable medium storing instructions that, when executed by a processor, cause the processor to: detect a plurality of participants within a field of view of a video camera of a video conference endpoint; calculate a proximity of each participant with respect to one or more other participants; group the participants into one or more groups based on the proximity such that the one or more groups include more than one participant; detect a first participant of a first group of the one or more groups as an active speaker; and alter a framing of a video output of the video conference endpoint to frame the first group. 20. The non-transitory processor readable medium of claim 15 , further comprising instructions that, when executed by the processor, cause the processor to: detect if the active speaker is conducting a discussion with a second participant; determine if the proximity between the active speaker and second participant is within a predetermined threshold; and if the proximity between the active speaker and the second participant is within the predetermined threshold, alter the framing of the video output of the video conference endpoint to frame the active speaker and the second participant. | 0.50084 |
9,081,849 | 2 | 3 | 2. A computer-implemented method of processing a multidimensional (MD) data set produced from an execution of a multidimensional query on a MD data source, the MD data set comprising data for a report described by the report specification based on an entity/relationship (ER) schema, the method comprising: producing a result set description matching the semantics of the report specification based on the ER schema from a MD data set description describing the semantics of the MD data set using result processing information; and converting MD data set into a collection of rows of data to generate a result set of the report output as a tabular result set when the ER report specification conforms to a tabular report, wherein converting the MD data set into a collection of rows of data includes, producing respective full stacks of members, each full stack representing a row of data available for inclusion in the collection of rows of data, wherein producing given full stack of members comprises: pushing a highest-level member of a dimension onto a stack, traversing parent/child relationships within a dimension along an edge to push each member at each level onto the stack, popping a top member off the stack, and pushing all siblings of the top member onto the stack; and converting the MD data set into a cross tabulated result set when the report specification conforms to a cross-tabulated report. | 2. A computer-implemented method of processing a multidimensional (MD) data set produced from an execution of a multidimensional query on a MD data source, the MD data set comprising data for a report described by the report specification based on an entity/relationship (ER) schema, the method comprising: producing a result set description matching the semantics of the report specification based on the ER schema from a MD data set description describing the semantics of the MD data set using result processing information; and converting MD data set into a collection of rows of data to generate a result set of the report output as a tabular result set when the ER report specification conforms to a tabular report, wherein converting the MD data set into a collection of rows of data includes, producing respective full stacks of members, each full stack representing a row of data available for inclusion in the collection of rows of data, wherein producing given full stack of members comprises: pushing a highest-level member of a dimension onto a stack, traversing parent/child relationships within a dimension along an edge to push each member at each level onto the stack, popping a top member off the stack, and pushing all siblings of the top member onto the stack; and converting the MD data set into a cross tabulated result set when the report specification conforms to a cross-tabulated report. 3. The method as claimed in claim 2 , further comprising creating a header row, including: setting a state of header to header nested; performing a check header nested; performing a check header current; performing a check header done; performing a check children; performing a check nested; performing a check current; performing a check sibling; and performing a check ancestor. | 0.761905 |
4,658,370 | 1 | 4 | 1. A knowledge engineering tool comprising a computer having a stored program and memory for storing a knowledge base, said knowledge base including factual knowledge and judgmental knowledge, said judgmental knowledge including judgmental rules having premises for limiting the conditions in which the rules are applicable and conclusions for indicating the actions to perform when the rules are successfully applied, said factual knowledge including definitions of attributes that can take on values, said judgmental rules including rules having premises referring to attributes and rules concluding values for attributes, means for executing a built-in control procedure including means for interpreting the knowledge base, means for invoking and chaining said rules, and means for terminating the knowledge base search for a value, said knowledge base also including control knowledge supplied by a knowledge engineer to modify the built-in control procedure, and a language interpreter for executing the control knowledge to modify the built-in control procedure, whereby the control knowledge can be separated from the factual knowledge and judgmental knowledge and stored as a distinct portion of the knowledge base. | 1. A knowledge engineering tool comprising a computer having a stored program and memory for storing a knowledge base, said knowledge base including factual knowledge and judgmental knowledge, said judgmental knowledge including judgmental rules having premises for limiting the conditions in which the rules are applicable and conclusions for indicating the actions to perform when the rules are successfully applied, said factual knowledge including definitions of attributes that can take on values, said judgmental rules including rules having premises referring to attributes and rules concluding values for attributes, means for executing a built-in control procedure including means for interpreting the knowledge base, means for invoking and chaining said rules, and means for terminating the knowledge base search for a value, said knowledge base also including control knowledge supplied by a knowledge engineer to modify the built-in control procedure, and a language interpreter for executing the control knowledge to modify the built-in control procedure, whereby the control knowledge can be separated from the factual knowledge and judgmental knowledge and stored as a distinct portion of the knowledge base. 4. A knowledge engineering tool as set forth in claim 1 which includes interface means with predefined commands for a user to load said knowledge base, start said consultation, end said consultation, and save the results of said consultation. | 0.95592 |
9,437,186 | 16 | 18 | 16. A system, comprising: at least one processor coupled to a memory, the memory including instructions operable to be executed by the at least one processor to perform a set of actions, configuring the at least one processor: to receive audio input data including speech; to perform automatic speech recognition (ASR) processing on the audio input data to obtain a speech recognition output; to determine, based at least in part on the speech recognition output, a likelihood that the speech recognition output includes a complete user command; to determine, based at least in part on the likelihood, a threshold length of non-speech that is processed before indicating an ending of the speech; to determine an ending of an utterance in the audio input data after the threshold length of non-speech is detected in the audio input data; and to, after determining the ending, initiate an action to be executed on a first device based at least in part on the speech recognition output and the ending. | 16. A system, comprising: at least one processor coupled to a memory, the memory including instructions operable to be executed by the at least one processor to perform a set of actions, configuring the at least one processor: to receive audio input data including speech; to perform automatic speech recognition (ASR) processing on the audio input data to obtain a speech recognition output; to determine, based at least in part on the speech recognition output, a likelihood that the speech recognition output includes a complete user command; to determine, based at least in part on the likelihood, a threshold length of non-speech that is processed before indicating an ending of the speech; to determine an ending of an utterance in the audio input data after the threshold length of non-speech is detected in the audio input data; and to, after determining the ending, initiate an action to be executed on a first device based at least in part on the speech recognition output and the ending. 18. The system of claim 16 , wherein the at least one processor is further configured to perform natural language processing on the speech following the determining of the ending. | 0.910768 |
7,801,712 | 1 | 2 | 1. A system comprising: one or more computer-readable media; a plurality of management packs embodied on the one or more computer-readable media, wherein each individual management pack comprises: a model declaration that represents an abstract model that describes components of the management pack, properties associated with the components, and relationships between the components, the components representing objects in a subsystem of a modeled system; discovery rules that describe how to find entities in a particular environment and relationships between the entities, the entities being instantiations of the objects; a monitoring policy that comprises a state machine that describes states and transitions associated with each entity of the entities; and a causality model that uses the discovery rules and the monitoring policy to express causality across the subsystem of the modeled system, wherein the causality model further: expresses causality in a manner that does not require specific knowledge of an instance of remaining management packs; and expresses multiple different reasons for an observable fault, with at least one reason being associated with a different entity in a different management pack than an entity for which causality is expressed; and a root cause analysis engine to access and utilize data generated by the causality model to determine a root cause of the observable fault based at least in part on the at least one reason expressed by the causality model. | 1. A system comprising: one or more computer-readable media; a plurality of management packs embodied on the one or more computer-readable media, wherein each individual management pack comprises: a model declaration that represents an abstract model that describes components of the management pack, properties associated with the components, and relationships between the components, the components representing objects in a subsystem of a modeled system; discovery rules that describe how to find entities in a particular environment and relationships between the entities, the entities being instantiations of the objects; a monitoring policy that comprises a state machine that describes states and transitions associated with each entity of the entities; and a causality model that uses the discovery rules and the monitoring policy to express causality across the subsystem of the modeled system, wherein the causality model further: expresses causality in a manner that does not require specific knowledge of an instance of remaining management packs; and expresses multiple different reasons for an observable fault, with at least one reason being associated with a different entity in a different management pack than an entity for which causality is expressed; and a root cause analysis engine to access and utilize data generated by the causality model to determine a root cause of the observable fault based at least in part on the at least one reason expressed by the causality model. 2. The system of claim 1 , wherein the causality model declares dependencies on other management packs. | 0.854108 |
5,587,918 | 24 | 25 | 24. A circuit pattern comparison apparatus according to claim 1, wherein said search pattern editing means includes means for schematically designating an omissible pattern in said designated predetermined search pattern. | 24. A circuit pattern comparison apparatus according to claim 1, wherein said search pattern editing means includes means for schematically designating an omissible pattern in said designated predetermined search pattern. 25. A circuit pattern comparison apparatus according to claim 24, wherein said search code synthesizing means includes means for converting the omissible pattern to a search code contained as an omissible comparison block, and said comparing means includes means for determining that comparison succeeds irrespective of whether or not a matched pattern is found relative to the omissible block. | 0.87323 |
9,342,608 | 17 | 18 | 17. The computer program product of claim 1 , further comprising calculating a frequency of occurrence of each of the differentiating factors in the plurality of differentiating factors in the evidence passages of the at least two candidate answers, wherein selecting the subset of differentiating factors comprises selecting the subset of differentiating factors based on the frequencies of occurrence associated with each of the differentiating factors. | 17. The computer program product of claim 1 , further comprising calculating a frequency of occurrence of each of the differentiating factors in the plurality of differentiating factors in the evidence passages of the at least two candidate answers, wherein selecting the subset of differentiating factors comprises selecting the subset of differentiating factors based on the frequencies of occurrence associated with each of the differentiating factors. 18. The computer program product of claim 17 , wherein selecting the subset of differentiating factors based on the frequencies of occurrence associated with each of the differentiating factors comprises selecting differentiating factors from the plurality of differentiating factors, for inclusion in the subset of differentiating factors, that have associated frequencies of occurrence equal to or above a threshold value. | 0.886083 |
8,214,366 | 13 | 16 | 13. A method for enabling natural language communication with a computer, the method comprising: receiving a text expression comprising (n) operands and (n−1) operators; combining sub-concepts in the text expression into higher order sub-concepts, according to precedence defined by the operators, until the higher order sub-concepts join to form a concept that represents the entire text expression, associating each of the concept and sub-concepts with a concept identifier, and storing the concept, sub-concepts, and associated concept identifiers in a database. | 13. A method for enabling natural language communication with a computer, the method comprising: receiving a text expression comprising (n) operands and (n−1) operators; combining sub-concepts in the text expression into higher order sub-concepts, according to precedence defined by the operators, until the higher order sub-concepts join to form a concept that represents the entire text expression, associating each of the concept and sub-concepts with a concept identifier, and storing the concept, sub-concepts, and associated concept identifiers in a database. 16. The method of claim 13 , wherein the associated concept identifiers comprise one or more of numeric identifiers, alphanumeric identifiers, random numbers, acronyms, words, or letters. | 0.919466 |
8,407,169 | 16 | 17 | 16. The system according to claim 15 wherein said group of location attribute types further comprise at least one general location attribute type, and at least one specific location attribute type. | 16. The system according to claim 15 wherein said group of location attribute types further comprise at least one general location attribute type, and at least one specific location attribute type. 17. The system according to claim 16 wherein said at least one general location attribute type together with said at least one specific location attribute type is further configured for full description and unique identification of said problem domain object. | 0.895733 |
8,990,083 | 1 | 3 | 1. A method, comprising: receiving data propagating in a network environment at a streaming database feeder; ignoring Joint Photographic Experts Group (JPEG) documents in the data; updating tags for each user in the network environment using a user-sub stream created for the user by the streaming database feeder, wherein each user-sub stream includes at least a portion of the data propagating in the network environment, wherein the tags are words and phrases that are associated with each user, wherein the data includes documents and, for at least a portion of the documents in the data, each original document is copied to create an anonymous document and a document that contains selected words within the data based on a whitelist, wherein the whitelist includes a plurality of designated words to be tagged, wherein documents that include data in a blacklist are dropped, and wherein the anonymous documents contain a concept field and some of the data in the anonymous documents is selected for the whitelist, and wherein the document that contains selected words does not include the concept field; assigning a weight to the selected words based on at least one characteristic associated with the data; associating the selected words to an individual, wherein the weight for a selected word is higher if the individual propagates the data; and generating a resultant composite of the selected words that are tagged. | 1. A method, comprising: receiving data propagating in a network environment at a streaming database feeder; ignoring Joint Photographic Experts Group (JPEG) documents in the data; updating tags for each user in the network environment using a user-sub stream created for the user by the streaming database feeder, wherein each user-sub stream includes at least a portion of the data propagating in the network environment, wherein the tags are words and phrases that are associated with each user, wherein the data includes documents and, for at least a portion of the documents in the data, each original document is copied to create an anonymous document and a document that contains selected words within the data based on a whitelist, wherein the whitelist includes a plurality of designated words to be tagged, wherein documents that include data in a blacklist are dropped, and wherein the anonymous documents contain a concept field and some of the data in the anonymous documents is selected for the whitelist, and wherein the document that contains selected words does not include the concept field; assigning a weight to the selected words based on at least one characteristic associated with the data; associating the selected words to an individual, wherein the weight for a selected word is higher if the individual propagates the data; and generating a resultant composite of the selected words that are tagged. 3. The method of claim 1 , further comprising: determining whether a threshold weight value associated with the selected words has been met, wherein if the threshold has been met, then the selected words are included in the resultant composite. | 0.837333 |
10,089,582 | 9 | 14 | 9. A computing device, comprising: means for receiving from a server computing device a full classifier model and sigmoid parameters; means for determining a normalized confidence value based on the received sigmoid parameters; and means for classifying a device behavior of the computing device based on a combination of: an analysis result generated by applying a behavior vector information structure to a lean classifier model; and the normalized confidence value determined based on the received sigmoid parameters. | 9. A computing device, comprising: means for receiving from a server computing device a full classifier model and sigmoid parameters; means for determining a normalized confidence value based on the received sigmoid parameters; and means for classifying a device behavior of the computing device based on a combination of: an analysis result generated by applying a behavior vector information structure to a lean classifier model; and the normalized confidence value determined based on the received sigmoid parameters. 14. The computing device of claim 9 , further comprising: means for generating an updated sigmoid parameter based on the normalized confidence value; and means for sending the updated sigmoid parameter to the server computing device. | 0.896444 |
8,484,198 | 9 | 13 | 9. The method of claim 7 , wherein the metric is a presence or absence of a unifying signal found in the set of the granular locations. | 9. The method of claim 7 , wherein the metric is a presence or absence of a unifying signal found in the set of the granular locations. 13. The method of claim 9 , further comprising determining if a threshold number of distinguishable signals associated with a given one of the geographic features exists, and if not, subdividing the given one of the geographic features. | 0.935974 |
9,696,969 | 1 | 6 | 1. A method, comprising: inferring, by an editing device including a processor, a first industrial programming language of a plurality of industrial programming languages to employ for programming an industrial controller and a second industrial programming language of the plurality of industrial programming languages to employ in combination with the first industrial programming language for programming the industrial controller to create a new programming language that is optimal for programming the industrial controller based upon at least one criteria comprising a code function to be implemented in the industrial controller, wherein the at least one criteria further comprises user tendencies associated with respective industrial programming languages of the industrial programming languages; and integrating, by the editing device, at least a portion of the first industrial programming language with at least another portion of the second industrial programming language to produce the new programming language for programming the industrial controller, wherein the first industrial programming language, the second industrial programming language and the new programming language are different. | 1. A method, comprising: inferring, by an editing device including a processor, a first industrial programming language of a plurality of industrial programming languages to employ for programming an industrial controller and a second industrial programming language of the plurality of industrial programming languages to employ in combination with the first industrial programming language for programming the industrial controller to create a new programming language that is optimal for programming the industrial controller based upon at least one criteria comprising a code function to be implemented in the industrial controller, wherein the at least one criteria further comprises user tendencies associated with respective industrial programming languages of the industrial programming languages; and integrating, by the editing device, at least a portion of the first industrial programming language with at least another portion of the second industrial programming language to produce the new programming language for programming the industrial controller, wherein the first industrial programming language, the second industrial programming language and the new programming language are different. 6. The method of claim 1 , wherein the first industrial programming language is a textual programming language and the second industrial programming language is a graphical programming language. | 0.8083 |
8,458,196 | 14 | 16 | 14. A non-transitory computer storage medium having computer executable instructions which when executed by a computer cause the computer to perform operations comprising: receiving topic information for a document, the information including at least one topic and a weight for each topic, where the topic relates to content of the document, and the weight represents how strongly the topic is associated with the document; receiving authorship information for the document, the information including, for each topic in the document, at least one author and an authorship percentage for each author; updating an authority signature value for a first author of a first topic based on a product of the authorship percentage for the first author of the first topic and the weight of the first topic in the document, where the first topic is included in the received topic information; receiving topic information for a second document, the information including at least one topic and a weight for each topic; receiving authorship information for the second document, the information including, for each topic in the second document, at least one author and an authorship percentage for each author; and updating the authority signature value for the first author of the first topic based on a product of the second document first topic authorship percentage for the first author and the weight of the first topic in the second document. | 14. A non-transitory computer storage medium having computer executable instructions which when executed by a computer cause the computer to perform operations comprising: receiving topic information for a document, the information including at least one topic and a weight for each topic, where the topic relates to content of the document, and the weight represents how strongly the topic is associated with the document; receiving authorship information for the document, the information including, for each topic in the document, at least one author and an authorship percentage for each author; updating an authority signature value for a first author of a first topic based on a product of the authorship percentage for the first author of the first topic and the weight of the first topic in the document, where the first topic is included in the received topic information; receiving topic information for a second document, the information including at least one topic and a weight for each topic; receiving authorship information for the second document, the information including, for each topic in the second document, at least one author and an authorship percentage for each author; and updating the authority signature value for the first author of the first topic based on a product of the second document first topic authorship percentage for the first author and the weight of the first topic in the second document. 16. The non-transitory computer storage medium of claim 14 , which further causes the computer to perform further operations comprising: storing a plurality of authority signature values in a database; and retrieving and displaying information regarding one or more authors from the database having a predetermined rank or authority signature value for a query topic in response to a request regarding the query topic. | 0.501193 |
9,711,141 | 24 | 26 | 24. A non-transitory computer-readable storage medium comprising instructions for causing one or more processors to: receive, from a user, a speech input containing a heteronym and one or more additional words; process the speech input using an automatic speech recognition system to determine a text string corresponding to the speech input, wherein processing the speech input includes determining at least one of: a phonemic string corresponding to the heteronym as pronounced by the user in the speech input; and a frequency of occurrence of an n-gram with respect to a corpus, wherein the n-gram includes the heteronym and the one or more additional words; determine an actionable intent based on the text string; determine a correct pronunciation of the heteronym based on at least one of the phonemic string, the frequency of occurrence of the n-gram, and the actionable intent; generate a dialogue response to the speech input, wherein the dialogue response includes the heteronym; and output the dialogue response as a speech output, wherein the heteronym in the dialogue response is pronounced in the speech output according to the determined correct pronunciation. | 24. A non-transitory computer-readable storage medium comprising instructions for causing one or more processors to: receive, from a user, a speech input containing a heteronym and one or more additional words; process the speech input using an automatic speech recognition system to determine a text string corresponding to the speech input, wherein processing the speech input includes determining at least one of: a phonemic string corresponding to the heteronym as pronounced by the user in the speech input; and a frequency of occurrence of an n-gram with respect to a corpus, wherein the n-gram includes the heteronym and the one or more additional words; determine an actionable intent based on the text string; determine a correct pronunciation of the heteronym based on at least one of the phonemic string, the frequency of occurrence of the n-gram, and the actionable intent; generate a dialogue response to the speech input, wherein the dialogue response includes the heteronym; and output the dialogue response as a speech output, wherein the heteronym in the dialogue response is pronounced in the speech output according to the determined correct pronunciation. 26. The computer-readable storage medium of claim 24 , wherein processing the speech input using the automatic speech recognition system includes determining a text string corresponding to the speech input, and further comprising instructions for causing the one or more processors to: determine an actionable intent based on the text string, wherein the correct pronunciation of the heteronym is determined based on at least one of the phonemic string, the frequency of occurrence of the n-gram, and the actionable intent. | 0.655921 |
4,139,310 | 1 | 12 | 1. A dividing and encoding apparatus comprising: first dividing and encoding switching means comprising a number of electrically conducting first slide means, means for electrically contacting said first slide means and insulatedly supporting said first slide means for movement back and forth between a normal position and an excursion position, dividend input means comprising amount left-in-a-line measuring means for measuring the amount left in a line, and first solenoid means responsive to said amount left-in-a-line measuring means, first means for coupling said first slide means to said first solenoid means for moving the first slide means to an excursion position, second dividing and encoding switching means comprising second slide means arranged in a number of group assemblies, each of said group assemblies comprising a number of electrically conducting dividing and encoding slide plates, means for insulatedly and movably supporting said dividing and encoding slide plates, whereby each of said slide plates is insulated from any other one of said slide plates and whereby each of said group of said assemblies of slide plates is movable back and forth between a normal position and an excursion position, divisor input means comprising word space counter means, second solenoid means and third solenoid means responsive to said word space counter means, second means for coupling the second solenoid means to respective ones of said group assemblies for selecting any one of said group assemblies in response to said word space counter means, and third means for couplng said third solenoid means to the group assemblies for moving a selected one of said group assemblies of said slide plates from its normal position to an excursion position also in response to said word space counter means, a source of current connected to said first slide means, and output circuit means comprising a plurality of sationary contact bars and means for insulatedly supporting said contact bars which are arranged to be contacted in a code channel relationship by said slide plates in their excursion positions whereby coded output signals are produced at said output circuit means which said output signals represent an appropriate quotient and remainder. | 1. A dividing and encoding apparatus comprising: first dividing and encoding switching means comprising a number of electrically conducting first slide means, means for electrically contacting said first slide means and insulatedly supporting said first slide means for movement back and forth between a normal position and an excursion position, dividend input means comprising amount left-in-a-line measuring means for measuring the amount left in a line, and first solenoid means responsive to said amount left-in-a-line measuring means, first means for coupling said first slide means to said first solenoid means for moving the first slide means to an excursion position, second dividing and encoding switching means comprising second slide means arranged in a number of group assemblies, each of said group assemblies comprising a number of electrically conducting dividing and encoding slide plates, means for insulatedly and movably supporting said dividing and encoding slide plates, whereby each of said slide plates is insulated from any other one of said slide plates and whereby each of said group of said assemblies of slide plates is movable back and forth between a normal position and an excursion position, divisor input means comprising word space counter means, second solenoid means and third solenoid means responsive to said word space counter means, second means for coupling the second solenoid means to respective ones of said group assemblies for selecting any one of said group assemblies in response to said word space counter means, and third means for couplng said third solenoid means to the group assemblies for moving a selected one of said group assemblies of said slide plates from its normal position to an excursion position also in response to said word space counter means, a source of current connected to said first slide means, and output circuit means comprising a plurality of sationary contact bars and means for insulatedly supporting said contact bars which are arranged to be contacted in a code channel relationship by said slide plates in their excursion positions whereby coded output signals are produced at said output circuit means which said output signals represent an appropriate quotient and remainder. 12. The dividing and encoding apparatus according to claim 1, wherein said output circuit means comprise a first set of wires, means for connecting said first set of wires to certain ones of said stationary contact bars, a second set of wires and means for connecting said second set of wires to other ones of said stationary contact bars whereby one set of wires provides quotient output signals and the other set of wires provides remainder output signals. | 0.802586 |
9,536,524 | 2 | 3 | 2. The method of claim 1 , wherein the parameterizable speech recognition model is speaker independent. | 2. The method of claim 1 , wherein the parameterizable speech recognition model is speaker independent. 3. The method of claim 2 , wherein generating of the user identifier occurs after receiving a unique user code in the voice request. | 0.940541 |
8,417,854 | 10 | 16 | 10. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, causes the one or more computers to perform operations comprising: receiving, at an integration layer, a connection request from an auto-id component to be connected to an auto-id node, the connection request specifying one or more communication parameters of the auto-id component, instantiating a generic adaptor class for effecting communication between the auto-id node and the auto-id component, the generic adaptor implementing functionality common to multiple different, specific adaptor classes stored in a class repository of the integration layer, instantiating a generic communicator class for effecting a data transport aspect of the communication between the auto-id node and the auto-id component, the generic communicator class implementing functionality common to multiple different, specific communicator classes stored in the class repository, and the generic communicator class being a component of the generic adaptor class, instantiating a generic converter class for effecting a data conversion aspect of the communication between the auto-id node and the auto-id component, the generic converter class implementing functionality common to multiple different, specific converter classes stored in the class repository, and the generic converter class being a component of the generic adaptor class, identifying, from among the multiple different adaptor, communicator, and converter classes stored in the class repository, a specific adaptor, a specific communicator class, and a specific converter class, respectively, based on the specified communication parameters, instantiating the identified specific adaptor, communicator, and converter classes, adding the identified specific adaptor, communicator class, and converter classes to an instance list, and effecting the communication between the auto-id component and the auto-id node using the instantiated generic adaptor, communicator, and converter classes and the instantiated specific adaptor, communicator, and converter classes. | 10. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, causes the one or more computers to perform operations comprising: receiving, at an integration layer, a connection request from an auto-id component to be connected to an auto-id node, the connection request specifying one or more communication parameters of the auto-id component, instantiating a generic adaptor class for effecting communication between the auto-id node and the auto-id component, the generic adaptor implementing functionality common to multiple different, specific adaptor classes stored in a class repository of the integration layer, instantiating a generic communicator class for effecting a data transport aspect of the communication between the auto-id node and the auto-id component, the generic communicator class implementing functionality common to multiple different, specific communicator classes stored in the class repository, and the generic communicator class being a component of the generic adaptor class, instantiating a generic converter class for effecting a data conversion aspect of the communication between the auto-id node and the auto-id component, the generic converter class implementing functionality common to multiple different, specific converter classes stored in the class repository, and the generic converter class being a component of the generic adaptor class, identifying, from among the multiple different adaptor, communicator, and converter classes stored in the class repository, a specific adaptor, a specific communicator class, and a specific converter class, respectively, based on the specified communication parameters, instantiating the identified specific adaptor, communicator, and converter classes, adding the identified specific adaptor, communicator class, and converter classes to an instance list, and effecting the communication between the auto-id component and the auto-id node using the instantiated generic adaptor, communicator, and converter classes and the instantiated specific adaptor, communicator, and converter classes. 16. The system of claim 10 , wherein the specific adaptor class further comprises a SOAP (Simple Object Access Protocol) or a JSP (Java Server Pages) adaptor class. | 0.722034 |
8,676,578 | 1 | 4 | 1. A meeting support apparatus comprising: a storage unit configured to store storage information for each of words, the storage information indicating a word of the words, pronunciation information on the word, and pronunciation recognition frequency which represents number of times that same pronunciation corresponding to the word is spoken; a determination unit configured to generate emphasis determination information including an emphasis level that represents whether or not a first word of the words is highlighted and represents a degree of highlighting determined in accordance with a pronunciation recognition frequency of a second word of the words when the first word is highlighted, the generating the emphasis determination information being based on whether or not the storage information includes a second set corresponding to a first set and based on the pronunciation recognition frequency of the second word when the second set is included in the storage information, the first set representing a combination between the first word and pronunciation information on the first word, the second set representing a combination between the second word and pronunciation information on the second word and being pre-stored in the storage unit; and a generation unit configured to generate an emphasis character string based on the emphasis determination information when the first word is highlighted, the emphasis character string being obtained by combining a symbol to the first word, the symbol representing that the degree of highlighting is increased in accordance with an increase in the emphasis level. | 1. A meeting support apparatus comprising: a storage unit configured to store storage information for each of words, the storage information indicating a word of the words, pronunciation information on the word, and pronunciation recognition frequency which represents number of times that same pronunciation corresponding to the word is spoken; a determination unit configured to generate emphasis determination information including an emphasis level that represents whether or not a first word of the words is highlighted and represents a degree of highlighting determined in accordance with a pronunciation recognition frequency of a second word of the words when the first word is highlighted, the generating the emphasis determination information being based on whether or not the storage information includes a second set corresponding to a first set and based on the pronunciation recognition frequency of the second word when the second set is included in the storage information, the first set representing a combination between the first word and pronunciation information on the first word, the second set representing a combination between the second word and pronunciation information on the second word and being pre-stored in the storage unit; and a generation unit configured to generate an emphasis character string based on the emphasis determination information when the first word is highlighted, the emphasis character string being obtained by combining a symbol to the first word, the symbol representing that the degree of highlighting is increased in accordance with an increase in the emphasis level. 4. The apparatus according to claim 1 , wherein: if the second set is not included in the storage information, the determination unit determines the emphasis level to be high; if the second set is included in the storage information and a ratio of a number of pronunciation recognition frequencies of the second set to a total number of pronunciation recognition frequencies of all pronunciation information corresponding to second words is less than a first threshold, the determination unit determines the emphasis level to be high in accordance with an decrease in the ratio, and if the second set is included in the storage information and the ratio is not less than the first threshold, the determination unit determines that the first word fails to be highlighted. | 0.500649 |
8,270,733 | 14 | 18 | 14. A system, comprising: a video input source configured to provide image data; a processor; and a memory containing a program, which, when executed on the processor is configured to perform an operation that identifies anomaly object types during classification of image data captured by a video camera, the operation comprising: receiving a micro-feature vector including multiple micro-feature values, each micro-feature value based on at least one pixel-level characteristic of a foreground patch that depicts a foreground object within the image data; classifying the foreground object as depicting a first object type corresponding to a first object type cluster of the object type clusters based on the micro-feature vector; computing a probability density function for the object type clusters; computing a probability density value for the micro-feature vector; evaluating a rareness measure of the micro-feature vector, wherein the rareness measure estimates a likelihood of observing the micro-feature vector, based on the probability density function and the probability density value, and identifying the foreground object as an anomaly object type when the rareness measure is below a specified threshold. | 14. A system, comprising: a video input source configured to provide image data; a processor; and a memory containing a program, which, when executed on the processor is configured to perform an operation that identifies anomaly object types during classification of image data captured by a video camera, the operation comprising: receiving a micro-feature vector including multiple micro-feature values, each micro-feature value based on at least one pixel-level characteristic of a foreground patch that depicts a foreground object within the image data; classifying the foreground object as depicting a first object type corresponding to a first object type cluster of the object type clusters based on the micro-feature vector; computing a probability density function for the object type clusters; computing a probability density value for the micro-feature vector; evaluating a rareness measure of the micro-feature vector, wherein the rareness measure estimates a likelihood of observing the micro-feature vector, based on the probability density function and the probability density value, and identifying the foreground object as an anomaly object type when the rareness measure is below a specified threshold. 18. The system of claim 14 , further comprising merging the first object type cluster with a second object type cluster of the object type clusters for the image data when the first object type cluster overlaps the second object type cluster by a specified amount. | 0.501887 |
9,037,469 | 9 | 14 | 9. A system comprising: a mobile device having a plurality of applications and configured to receive a first, second, and third input of user's speech; a voice recognition module configured to respectively convert the first, second, and third input of user's speech to a first, second, and third text; and a processor configured to: identify a first, second, and third command respectively from the first, second and third text; access a first quantity of information based on the first command identified from the first text; access a second quantity of information from a database source remote from the mobile device and based on the second command identified from the second text; access a third quantity of information based on the third command identified from third text; and provide the accessed information based on at least one the first command, the second command, and the third command to a user via at least one application of the plurality of applications. | 9. A system comprising: a mobile device having a plurality of applications and configured to receive a first, second, and third input of user's speech; a voice recognition module configured to respectively convert the first, second, and third input of user's speech to a first, second, and third text; and a processor configured to: identify a first, second, and third command respectively from the first, second and third text; access a first quantity of information based on the first command identified from the first text; access a second quantity of information from a database source remote from the mobile device and based on the second command identified from the second text; access a third quantity of information based on the third command identified from third text; and provide the accessed information based on at least one the first command, the second command, and the third command to a user via at least one application of the plurality of applications. 14. The system as recited in claim 9 , wherein the provided information is text information and the at least one application is one of a messaging application and an email application. | 0.861237 |
7,668,865 | 13 | 17 | 13. A computer implemented method of formatting a document comprising: a) providing a database comprising: (i) a plurality of document element classes; (ii) a set of clause formatting rules for each document element class; and (iii) a set of document elements for each document element class; and in a computer system comprising at least one processor operatively associated with the database: b) obtaining an electronic document; c) identifying a clause within the electronic document; d) identifying one or more of said document elements within said clause; e) for one or more of the document elements identified within the clause: (i) classifying the respective identified document element into one of the document element classes; (ii) determining the clause formatting rules associated with the classified document element class; (iii) determining whether said clause is formatted in accordance with the clause formatting rules of the classified document element class; and (iv) where the said clause is not formatted in accordance with the clause formatting rules of the classified document element class, selecting one or more of the clause formatting rules of the classified document element class and applying the selected one or more clause formatting rules to said clause to re-format said clause to a re-formatted clause that accords with the selected one or more clause formatting rules; and f) displaying a re-formatted version of the electronic document including one or more of the re-formatted clauses. | 13. A computer implemented method of formatting a document comprising: a) providing a database comprising: (i) a plurality of document element classes; (ii) a set of clause formatting rules for each document element class; and (iii) a set of document elements for each document element class; and in a computer system comprising at least one processor operatively associated with the database: b) obtaining an electronic document; c) identifying a clause within the electronic document; d) identifying one or more of said document elements within said clause; e) for one or more of the document elements identified within the clause: (i) classifying the respective identified document element into one of the document element classes; (ii) determining the clause formatting rules associated with the classified document element class; (iii) determining whether said clause is formatted in accordance with the clause formatting rules of the classified document element class; and (iv) where the said clause is not formatted in accordance with the clause formatting rules of the classified document element class, selecting one or more of the clause formatting rules of the classified document element class and applying the selected one or more clause formatting rules to said clause to re-format said clause to a re-formatted clause that accords with the selected one or more clause formatting rules; and f) displaying a re-formatted version of the electronic document including one or more of the re-formatted clauses. 17. A computer implemented method according to claim 13 wherein steps (d) and (e)(i) to (e)(iv) are repeated for each clause identified within said electronic document. | 0.901408 |
10,055,874 | 19 | 20 | 19. A computer-readable memory storing a plurality of instructions executable by one or more processors for transferring facial expressions from a subject to a computer-generated character, the plurality of instructions comprising: instructions that cause the one or more processors to receive positional information from a motion capture session of the subject representing a performance having facial expressions to be transferred to the computer-generated character; instructions that cause the one or more processors to receive a first animation model that represents the subject and a second animation model that represents the computer-generated character, each of the first and second animation models including a plurality of adjustable controls that define geometries of the animation model and that can be adjusted to represent different facial expressions on the model, wherein setting the same values for corresponding sets of adjustable controls in the models generates similar facial poses on the models; instructions that cause the one or more processors to determine a solution that matches the animation model to the positional information to reproduce the facial expressions from the performance to an first animation model that represents the subject using the positional information and animation model, the solution including values for at least some of the plurality of controls; instructions that cause the one or more processors to retarget the facial expressions from the performance to the second animation model using the solution; and instructions that cause the one or more processors to synchronize lip movement of the creature with lip movement from the first animation model after the facial expressions are retargeted from the performance to the second animation model. | 19. A computer-readable memory storing a plurality of instructions executable by one or more processors for transferring facial expressions from a subject to a computer-generated character, the plurality of instructions comprising: instructions that cause the one or more processors to receive positional information from a motion capture session of the subject representing a performance having facial expressions to be transferred to the computer-generated character; instructions that cause the one or more processors to receive a first animation model that represents the subject and a second animation model that represents the computer-generated character, each of the first and second animation models including a plurality of adjustable controls that define geometries of the animation model and that can be adjusted to represent different facial expressions on the model, wherein setting the same values for corresponding sets of adjustable controls in the models generates similar facial poses on the models; instructions that cause the one or more processors to determine a solution that matches the animation model to the positional information to reproduce the facial expressions from the performance to an first animation model that represents the subject using the positional information and animation model, the solution including values for at least some of the plurality of controls; instructions that cause the one or more processors to retarget the facial expressions from the performance to the second animation model using the solution; and instructions that cause the one or more processors to synchronize lip movement of the creature with lip movement from the first animation model after the facial expressions are retargeted from the performance to the second animation model. 20. The computer-readable memory of claim 19 wherein the instructions that cause the one or more processors to synchronize lip movement of the creature with lip movement from the first animation model after the facial expressions are retargeted from the performance to the second animation model comprise: instructions that determine a jaw opening of the first animation model, determine a jaw opening for the second animation model, and determine if the jaw opening of the second animation model matches the jaw opening of the first animation model, and if not, adjust the jaw opening of the second animation model to more closely match the jaw opening of the first animation model; and instructions that, after adjusting the jaw opening of the second animation model, determine a visible percentage of teeth for the first animation model, determine a visible percentage of teeth for the second animation model, and determine if the visible percentage of teeth for the second animation model matches the visible percentage of teeth for the first animation model, and if not, adjust the visible percentage of teeth in the second animation model to more closely match the percentage in the first animation model. | 0.500413 |
8,209,672 | 24 | 25 | 24. The system according to claim 21 , wherein the programming constructs are objects corresponding to an execution language description notation. | 24. The system according to claim 21 , wherein the programming constructs are objects corresponding to an execution language description notation. 25. The system according to claim 24 , wherein the objects corresponding to the execution language description notation comprise business process execution language (BPEL) code. | 0.934831 |
9,703,779 | 1 | 6 | 1. A method of finding and presenting content items based on input received from a user in which the search query used to match content items of potential interest is formed based on matching the input with a catalog of metacontent items and keywords associated with the metacontent items, the method comprising: providing, on a local device, a local collection of content items and associated metacontent, the metacontent associated with each content item describing informational content of the corresponding content item; providing, on a remote server system, a remote catalog of metacontent items and keywords associated with the metacontent items; receiving, on the local device during a range of time of a sequence of ranges of times, input from the user for finding at least one desired content item, wherein the sequence of ranges of times repeats cyclically after all ranges of times in the sequence of ranges of times have lapsed; receiving a plurality of magnitudes of user interaction, wherein each respective magnitude of the plurality of magnitudes corresponds to an amount of user interaction of the user with a respective dataspace of a plurality of dataspaces of the remote catalog during the range of time; identifying, based on the plurality of magnitudes, a dataspace of the plurality of dataspaces that corresponds to the respective magnitude having a greatest magnitude of user interaction of the plurality of magnitudes of user interaction; selecting at least one keyword that has a different word stem than the received input from keywords included within a subset of the remote catalog corresponding to the dataspace, based at least in part on matching the received input from the user with metacontent items that are included within the subset of the remote catalog; adding, on the local device, the at least one keyword to the received input from the user to form a search query; determining, on the local device, a subset of content items of the local collection associated with metacontent that at least partially matches both of the at least one keyword and the received input from the user of the search query; and presenting, on the local device, the subset of content items of the local collection on a display device based at least in part on at least one ranking criterion, wherein the ranking criterion includes learned preferences of the user for content items of the local collection and local attribute values associated with the content items of the local collection, each local attribute value being based on interactions of the user with at least one content item of the local collection corresponding to the local attribute value. | 1. A method of finding and presenting content items based on input received from a user in which the search query used to match content items of potential interest is formed based on matching the input with a catalog of metacontent items and keywords associated with the metacontent items, the method comprising: providing, on a local device, a local collection of content items and associated metacontent, the metacontent associated with each content item describing informational content of the corresponding content item; providing, on a remote server system, a remote catalog of metacontent items and keywords associated with the metacontent items; receiving, on the local device during a range of time of a sequence of ranges of times, input from the user for finding at least one desired content item, wherein the sequence of ranges of times repeats cyclically after all ranges of times in the sequence of ranges of times have lapsed; receiving a plurality of magnitudes of user interaction, wherein each respective magnitude of the plurality of magnitudes corresponds to an amount of user interaction of the user with a respective dataspace of a plurality of dataspaces of the remote catalog during the range of time; identifying, based on the plurality of magnitudes, a dataspace of the plurality of dataspaces that corresponds to the respective magnitude having a greatest magnitude of user interaction of the plurality of magnitudes of user interaction; selecting at least one keyword that has a different word stem than the received input from keywords included within a subset of the remote catalog corresponding to the dataspace, based at least in part on matching the received input from the user with metacontent items that are included within the subset of the remote catalog; adding, on the local device, the at least one keyword to the received input from the user to form a search query; determining, on the local device, a subset of content items of the local collection associated with metacontent that at least partially matches both of the at least one keyword and the received input from the user of the search query; and presenting, on the local device, the subset of content items of the local collection on a display device based at least in part on at least one ranking criterion, wherein the ranking criterion includes learned preferences of the user for content items of the local collection and local attribute values associated with the content items of the local collection, each local attribute value being based on interactions of the user with at least one content item of the local collection corresponding to the local attribute value. 6. The method of claim 1 , wherein the content items of the local collection include application store items and the associated metacontent includes at least one of application name, keywords associated with the application, application price, and application categories. | 0.812067 |
7,855,799 | 22 | 23 | 22. A method of controlling automated printing of electronic documents implemented at least in part on a computing system, comprising: identifying a plurality of electronic files, each electronic file having a unique file name comprising a plurality of fields, each field comprising at least one alpha-numeric character and separated from an adjacent field by a field separation character; displaying the file name for each of the plurality of electronic files; receiving an input identifying the character separator employed to delineate between the plurality of fields in each of the file names of the plurality of electronic files; for each of the plurality of electronic files, parsing the file name to identify each of the plurality of fields, identifying the at least one alpha-numeric character comprised in each of the plurality of fields, and displaying the alpha-numeric strings comprised in each field; receiving an input identifying a first printing parameter to be controlled by the value of the at least one alpha-numeric character comprised in a first field of each file name; receiving an input identifying a second printing parameter to be controlled by the value of the alpha-numeric character string assigned to a second field; and generating instructions for printing the plurality of files, wherein for each of the plurality of files, the value of the at least one alpha-numeric character in the first field is used to determine instructions relating to the first printing parameter and the value of the at least one alpha-numeric character in the second field is used to determine instructions relating to the second printing parameter. | 22. A method of controlling automated printing of electronic documents implemented at least in part on a computing system, comprising: identifying a plurality of electronic files, each electronic file having a unique file name comprising a plurality of fields, each field comprising at least one alpha-numeric character and separated from an adjacent field by a field separation character; displaying the file name for each of the plurality of electronic files; receiving an input identifying the character separator employed to delineate between the plurality of fields in each of the file names of the plurality of electronic files; for each of the plurality of electronic files, parsing the file name to identify each of the plurality of fields, identifying the at least one alpha-numeric character comprised in each of the plurality of fields, and displaying the alpha-numeric strings comprised in each field; receiving an input identifying a first printing parameter to be controlled by the value of the at least one alpha-numeric character comprised in a first field of each file name; receiving an input identifying a second printing parameter to be controlled by the value of the alpha-numeric character string assigned to a second field; and generating instructions for printing the plurality of files, wherein for each of the plurality of files, the value of the at least one alpha-numeric character in the first field is used to determine instructions relating to the first printing parameter and the value of the at least one alpha-numeric character in the second field is used to determine instructions relating to the second printing parameter. 23. The method of claim 22 , wherein receiving an input identifying a field separator used in the file name for each of the plurality of files to separate portions of the file names comprises receiving an input identifying at least one of a space, a hyphen, a colon, a comma, a period, underscore, and a semicolon. | 0.857273 |
8,671,104 | 11 | 13 | 11. A computer-implemented method for providing orientation into digital information, comprising: maintaining a plurality of evergreen indexes on a server for topically-limited subject areas, each of the subject areas comprising electronically-stored digital information and, for each of the evergreen indexes, comprising: specifying a hierarchy of topics; and pairing a topic model to each of the topics in the topic hierarchy, each of the topic models comprising a pattern evaluable against the digital information, wherein the pattern identifies such digital information matching the topic model's topic; receiving a user interest in the digital information for the subject area of at least one of the evergreen indexes; evaluating each of the patterns for the identified topic models against the digital information; providing access through a visual display to the digital information organized according to each of the topics in the subject area; receiving a query comprising topic search terms and matching the topic search terms to the topics in the topic hierarchy; designating at least one of the chosen topics and the topic search terms as characteristic words; examining all of the evergreen indexes; and identifying those evergreen indexes in the visual display that comprise the characteristic words. | 11. A computer-implemented method for providing orientation into digital information, comprising: maintaining a plurality of evergreen indexes on a server for topically-limited subject areas, each of the subject areas comprising electronically-stored digital information and, for each of the evergreen indexes, comprising: specifying a hierarchy of topics; and pairing a topic model to each of the topics in the topic hierarchy, each of the topic models comprising a pattern evaluable against the digital information, wherein the pattern identifies such digital information matching the topic model's topic; receiving a user interest in the digital information for the subject area of at least one of the evergreen indexes; evaluating each of the patterns for the identified topic models against the digital information; providing access through a visual display to the digital information organized according to each of the topics in the subject area; receiving a query comprising topic search terms and matching the topic search terms to the topics in the topic hierarchy; designating at least one of the chosen topics and the topic search terms as characteristic words; examining all of the evergreen indexes; and identifying those evergreen indexes in the visual display that comprise the characteristic words. 13. A method according to claim 11 , further comprising: associating a ranking with each of the topics in the subject area of the at least one evergreen index as assigned by the online community; identifying the topics corresponding to the topic models identified and ranking the at least one evergreen index based upon the rankings associated with the topics identified; and biasing the topics provided in the visual display based on the ranking of their respective evergreen indexes. | 0.683833 |
7,734,357 | 19 | 20 | 19. A method for checking a selection of objects, where the objects respectively represent subunits in a technical installation and the subunits can be controlled and configured using configuration data, the selection of the objects producing or altering the configuration data associated with the represented subunit, which comprises the steps of: checking a consistency of selected objects in respect of already available objects using an association function; subsequently an admissible object selection in line with the association function prompts the configuration data associated with the represented subunit to be updated and the consistency of the updated configuration data for the selected subunit to be checked using admissible configurations of the technical installation; and an admissible selection in line with the association function prompts the process data elements associated with the represented subunit to be updated and the consistency of the then updated process data elements for the selected subunit to be checked using admissible operating states of the technical installation; and processing further the object selection, the updated configuration data and the updated process elements only if the object selection, the updated configuration data and the updated process elements are consistent. | 19. A method for checking a selection of objects, where the objects respectively represent subunits in a technical installation and the subunits can be controlled and configured using configuration data, the selection of the objects producing or altering the configuration data associated with the represented subunit, which comprises the steps of: checking a consistency of selected objects in respect of already available objects using an association function; subsequently an admissible object selection in line with the association function prompts the configuration data associated with the represented subunit to be updated and the consistency of the updated configuration data for the selected subunit to be checked using admissible configurations of the technical installation; and an admissible selection in line with the association function prompts the process data elements associated with the represented subunit to be updated and the consistency of the then updated process data elements for the selected subunit to be checked using admissible operating states of the technical installation; and processing further the object selection, the updated configuration data and the updated process elements only if the object selection, the updated configuration data and the updated process elements are consistent. 20. The method according to claim 19 , which further comprises providing an association table as the association function. | 0.504065 |
7,962,507 | 14 | 15 | 14. The method as recited in claim 13 wherein the filtering is performed by: an identity filter configured to discard any one of the snippet set that does not include the first sentence of the Chinese couplet and a returned second sentence; a neighbor filter configured to pass through the returned second sentence of the sentence pairs not discarded by the identity filter; a length filter configured to discard any one of the returned second sentences passed through by the neighbor filter and that does not have sentence length that corresponds to the first sentence of the Chinese couplet. | 14. The method as recited in claim 13 wherein the filtering is performed by: an identity filter configured to discard any one of the snippet set that does not include the first sentence of the Chinese couplet and a returned second sentence; a neighbor filter configured to pass through the returned second sentence of the sentence pairs not discarded by the identity filter; a length filter configured to discard any one of the returned second sentences passed through by the neighbor filter and that does not have sentence length that corresponds to the first sentence of the Chinese couplet. 15. The method as recited in claim 14 wherein the generating the at least one new sentence comprises training the support vector machine classifier with a set of manually labeled Chinese couplets resulting in a support vector machine classifier model. | 0.801109 |
4,783,761 | 2 | 4 | 2. A dictionary storage apparatus for use with a source of characters, the apparatus containing a list of correctly-spelled words for verifying the spelling order of character inputs, comprising: (a) word terminators in said list, one said terminator distinguishing each complete word therein, (b) input means for receiving character inputs in a first code format, (c) a first storage means for storing character information structured to sequentially check the spelling order of a first predetermined series of received character inputs, said character information in said first storage means being in said first code format and held in a plurality of bytes, one character per byte, and comprising a succession of character sequences having at least two characters therein, a first character selected from all characters of the alphabet and groups identified by a particular one of said first characters in combination with at least one other alphabetic character, at least some of said groups being less in number than the entire alphabet; (d) a second storage means extending from said first storage means and containing further character information structured to check the spelling order of a variable string of character inputs strung from said predetermined series to validate spelling of words, said further character information in said second storage means comprises a tree structure with a plurality of branches, each of said branches stemming from a discrete one of said sequences in said first storage means and at least one word remnant being associated with said discrete one sequence, said word remnant containing at least one character held in a second code format and being followed by said word terminator; (e) normally disabled means decoding said second code format into said first code format, said means for decoding being enabled at the end of each said discrete one sequence; (f) comparison means operable upon receipt of each said character input and effective to check agreement between the received one of said character inputs and ordinally corresponding ones of said character information as to words stored in said first storage means and in said second storage means, and (g) signal output means connected to said first and second storage means for generating a signal immediately in response to a received character input being out of spelling order as structured in said first and second storage means and determined by said comparison means. | 2. A dictionary storage apparatus for use with a source of characters, the apparatus containing a list of correctly-spelled words for verifying the spelling order of character inputs, comprising: (a) word terminators in said list, one said terminator distinguishing each complete word therein, (b) input means for receiving character inputs in a first code format, (c) a first storage means for storing character information structured to sequentially check the spelling order of a first predetermined series of received character inputs, said character information in said first storage means being in said first code format and held in a plurality of bytes, one character per byte, and comprising a succession of character sequences having at least two characters therein, a first character selected from all characters of the alphabet and groups identified by a particular one of said first characters in combination with at least one other alphabetic character, at least some of said groups being less in number than the entire alphabet; (d) a second storage means extending from said first storage means and containing further character information structured to check the spelling order of a variable string of character inputs strung from said predetermined series to validate spelling of words, said further character information in said second storage means comprises a tree structure with a plurality of branches, each of said branches stemming from a discrete one of said sequences in said first storage means and at least one word remnant being associated with said discrete one sequence, said word remnant containing at least one character held in a second code format and being followed by said word terminator; (e) normally disabled means decoding said second code format into said first code format, said means for decoding being enabled at the end of each said discrete one sequence; (f) comparison means operable upon receipt of each said character input and effective to check agreement between the received one of said character inputs and ordinally corresponding ones of said character information as to words stored in said first storage means and in said second storage means, and (g) signal output means connected to said first and second storage means for generating a signal immediately in response to a received character input being out of spelling order as structured in said first and second storage means and determined by said comparison means. 4. The dictionary storage apparatus of claim 2, wherein at least one said sequence includes a said word terminator, said second format is a compressed code format having variable numbers of bits for the different characters, some characters having a bit-length in excess of a byte, and said word terminator has a discrete code in said first format and said second format. | 0.631213 |
7,921,100 | 1 | 6 | 1. A method for calculating a similarity score of a query set comprising a query set of tokens and a first database set comprising a first database set of tokens, wherein the first database set is one of a plurality of database sets in a data collection set stored on a non-transitory computer readable medium, comprising the steps of: for each specific token in the query set, determining the number of database sets that contain the specific token; for each specific token in the query set, calculating an inverse document frequency (idf) weight, based at least in part on the number of database sets that contain the specific token and on the total number of database sets in the data collection set; calculating a normalized length of the first database set; calculating a normalized length of the query set; and, calculating a similarity score based at least in part on the normalized length of the first database set, the normalized length of the query set, and the idf weight of each of the tokens in the query set. | 1. A method for calculating a similarity score of a query set comprising a query set of tokens and a first database set comprising a first database set of tokens, wherein the first database set is one of a plurality of database sets in a data collection set stored on a non-transitory computer readable medium, comprising the steps of: for each specific token in the query set, determining the number of database sets that contain the specific token; for each specific token in the query set, calculating an inverse document frequency (idf) weight, based at least in part on the number of database sets that contain the specific token and on the total number of database sets in the data collection set; calculating a normalized length of the first database set; calculating a normalized length of the query set; and, calculating a similarity score based at least in part on the normalized length of the first database set, the normalized length of the query set, and the idf weight of each of the tokens in the query set. 6. The method of claim 1 further comprising the step of calculating the idf weight of a specific token according to the formula:
idf ( q i )=log 2 (1 +N/N ( q i )) wherein: q i represents the specific token; idf(q i ) represents the idf weight of the specific token; N represents the total number of database sets in the data collection set; and, N(q i ) represents the number of database sets that contain the token q i . | 0.657512 |
9,286,572 | 12 | 15 | 12. A method of managing an autonomous actor network, the method comprising: obtaining, by a network management computing system comprising computer hardware, metadata information associated with the autonomous actor network and autonomous actors included therein; associating, by the network management computing system, a self-assessment identifier with an autonomous actor, the self-assessment identifier indicative of: metadata elements stored by the autonomous actor, a quantity of metadata information for each metadata element stored by the autonomous actor, and a relationship between the metadata elements for the autonomous actor and the quantity of metadata information stored for each metadata element, wherein the relationship includes a threshold result; and generating, by the network management computing system, an assessment value for the autonomous actor based on the obtained information and the self-assessment identifier, wherein generating the assessment value includes comparing the threshold result to a combination of the metadata elements for the autonomous actor and the quantity of metadata information stored for each metadata element in accordance with an identified process. | 12. A method of managing an autonomous actor network, the method comprising: obtaining, by a network management computing system comprising computer hardware, metadata information associated with the autonomous actor network and autonomous actors included therein; associating, by the network management computing system, a self-assessment identifier with an autonomous actor, the self-assessment identifier indicative of: metadata elements stored by the autonomous actor, a quantity of metadata information for each metadata element stored by the autonomous actor, and a relationship between the metadata elements for the autonomous actor and the quantity of metadata information stored for each metadata element, wherein the relationship includes a threshold result; and generating, by the network management computing system, an assessment value for the autonomous actor based on the obtained information and the self-assessment identifier, wherein generating the assessment value includes comparing the threshold result to a combination of the metadata elements for the autonomous actor and the quantity of metadata information stored for each metadata element in accordance with an identified process. 15. The method of claim 12 , further comprising altering the self-assessment identifier for said autonomous actor based in part on the assessment value. | 0.803109 |
10,078,802 | 5 | 7 | 5. A system of discovering and analyzing structures of user groups in a microblog, which comprises a processor, characterized in that the processor is configured to perform the operations of: acquiring information on behavior data of microblog users of a target group; constructing a microblog user association network based on the information on behavior data of the microblog users of the target group; acquiring at least one maximal clique from the microblog user association network; acquiring at least one core clique based on the maximal clique; conducting behavior analysis on the user groups in the microblog based on the acquired maximal clique and/or the acquired core clique, wherein the operation of acquiring at least one maximal clique particularly comprises: acquiring all maximal cliques of the microblog user association network by utilizing a search-triangle based method operated with a certain pruning strategy, and wherein the operation of acquiring at least one core clique particularly comprises: based on the maximal cliques, analyzing a social relation circle of each microblog user and all other microblog users, and filtering out the core cliques of the microblog user association network based on an inclusion-consolidation strategy on the social relation circles, wherein if a social relation circle of one microblog user is not included by any of the other social relation circles, the social relation circle of the one microblog user is filtered out as one of the core cliques. | 5. A system of discovering and analyzing structures of user groups in a microblog, which comprises a processor, characterized in that the processor is configured to perform the operations of: acquiring information on behavior data of microblog users of a target group; constructing a microblog user association network based on the information on behavior data of the microblog users of the target group; acquiring at least one maximal clique from the microblog user association network; acquiring at least one core clique based on the maximal clique; conducting behavior analysis on the user groups in the microblog based on the acquired maximal clique and/or the acquired core clique, wherein the operation of acquiring at least one maximal clique particularly comprises: acquiring all maximal cliques of the microblog user association network by utilizing a search-triangle based method operated with a certain pruning strategy, and wherein the operation of acquiring at least one core clique particularly comprises: based on the maximal cliques, analyzing a social relation circle of each microblog user and all other microblog users, and filtering out the core cliques of the microblog user association network based on an inclusion-consolidation strategy on the social relation circles, wherein if a social relation circle of one microblog user is not included by any of the other social relation circles, the social relation circle of the one microblog user is filtered out as one of the core cliques. 7. The system of discovering and analyzing structures of user groups in a microblog according to claim 5 , characterized in that, the operation of acquiring at least one core clique further comprises: acquiring a common microblog user existing among the core cliques; re-partitioning the common microblog user into a corresponding core clique such that there is no common microblog user among respective core cliques. | 0.749097 |
8,015,129 | 8 | 14 | 8. The method of claim 1 , further comprising trading off semantic similarity with respect to nearness when rearranging the set of value-item lists. | 8. The method of claim 1 , further comprising trading off semantic similarity with respect to nearness when rearranging the set of value-item lists. 14. The method of claim 8 , further comprising performing a nearness test of the set of value-item lists with respect to centers of values for conditioning variables. | 0.934543 |
9,367,235 | 1 | 2 | 1. A method for receiving a confirming gesture formed on or about a sensor panel, comprising: detecting one or more images at a first time at the sensor panel; determining that the one or more images at the first time are arranged in a pattern corresponding to a predetermined OK gesture; determining a centering parameter from the one or more images; associating the OK gesture with a user interface (UI) element coincident with the centering parameter, the UI element accepting a confirming input; and providing the confirming input to the UI element. | 1. A method for receiving a confirming gesture formed on or about a sensor panel, comprising: detecting one or more images at a first time at the sensor panel; determining that the one or more images at the first time are arranged in a pattern corresponding to a predetermined OK gesture; determining a centering parameter from the one or more images; associating the OK gesture with a user interface (UI) element coincident with the centering parameter, the UI element accepting a confirming input; and providing the confirming input to the UI element. 2. The method of claim 1 , further comprising determining that the one or more images at the first time are arranged in a pattern corresponding to a predetermined OK gesture by: identifying one or more palm edge and pinky features; and identifying a thumb and finger feature. | 0.668675 |
9,727,577 | 13 | 25 | 13. A cloud storage system, comprising: a communication circuitry in communication with: a file database circuitry for storing a plurality of files and metadata associated with each of the plurality of files; and a user database circuitry for storing information associating at least one user with at least one file, wherein the communication circuitry is configured to: receive a request, from a user, to edit metadata associated with a file in the plurality of files; identify a first application generates the request; divide the metadata associated with the file into a first set of metadata categories and a second set of metadata categories, wherein the first set of metadata categories is associated with the first application and the second set of metadata categories is not associated with the first application; filter the first set of metadata categories to obtain filtered metadata containing metadata associated with the file; provide the filtered metadata to the first application; receive edits from the user to metadata associated with the first file, wherein the edited metadata is in a metadata category in the first set of metadata categories; and determine the category of metadata of the received edits and: in response to determining that the received edits belong to the first set of metadata categories, apply the edits to the metadata category, wherein the received edits belong to the first set of metadata categories; and in response to determining that the category of the metadata does not exist, generate a new metadata category associated only with the application in the first set of metadata categories. | 13. A cloud storage system, comprising: a communication circuitry in communication with: a file database circuitry for storing a plurality of files and metadata associated with each of the plurality of files; and a user database circuitry for storing information associating at least one user with at least one file, wherein the communication circuitry is configured to: receive a request, from a user, to edit metadata associated with a file in the plurality of files; identify a first application generates the request; divide the metadata associated with the file into a first set of metadata categories and a second set of metadata categories, wherein the first set of metadata categories is associated with the first application and the second set of metadata categories is not associated with the first application; filter the first set of metadata categories to obtain filtered metadata containing metadata associated with the file; provide the filtered metadata to the first application; receive edits from the user to metadata associated with the first file, wherein the edited metadata is in a metadata category in the first set of metadata categories; and determine the category of metadata of the received edits and: in response to determining that the received edits belong to the first set of metadata categories, apply the edits to the metadata category, wherein the received edits belong to the first set of metadata categories; and in response to determining that the category of the metadata does not exist, generate a new metadata category associated only with the application in the first set of metadata categories. 25. The system of claim 13 , wherein metadata includes a date and time. | 0.886943 |
8,462,368 | 9 | 12 | 9. A computer program product in a non-transitory computer-readable storage medium for collecting and displaying information about printing device related objects on a network, comprising machine-readable code for causing a machine to perform the method steps of: providing a user with a graphic user interface of a main window of a device management application comprising a left pane tree and a central view pane; the user selecting in the left pane tree at least one topic of interest from at least one category of interest from a list of topics of interest which are hierarchically arranged by categories of interest, which left pane tree displays the list of topics of interest and the categories of interest, and which left pane tree does not display printing device related objects, wherein the list of topics provides a central point user interface comprising at least one root category of topics comprising the group consisting of device management, account management, queue management, queue user management, and combinations thereof to enable the user's selection from multiple levels of printing device related objects with circular associations to each other, which printing device related objects comprising traditional printing devices and non-traditional printing device related objects, which non-traditional printing device related objects comprise the group consisting of users, devices, alerts, hosts, queues, jobs, accounts, balances, and combinations thereof; the user specifying displaying in the central view pane of object property information associated with the selected at least one topic of interest about the printing device related objects; and causing displaying in the central view pane of object property information associated with the selected at least one topic of interest about the printing device related objects, while the left pane tree does not display printing device related objects wherein a list of devices can be displayed in the central view pane, and wherein displaying of the list of devices comprises: optionally expanding a Device Management category in order to select a List View topic of interest within the Device Management category; selecting the List View topic of interest within the Device Management category; and causing the list of devices to be displayed in the central view pane using a default object locator ALL, which locates all objects without any filtering, and the list of devices is never displayed in the left pane tree. | 9. A computer program product in a non-transitory computer-readable storage medium for collecting and displaying information about printing device related objects on a network, comprising machine-readable code for causing a machine to perform the method steps of: providing a user with a graphic user interface of a main window of a device management application comprising a left pane tree and a central view pane; the user selecting in the left pane tree at least one topic of interest from at least one category of interest from a list of topics of interest which are hierarchically arranged by categories of interest, which left pane tree displays the list of topics of interest and the categories of interest, and which left pane tree does not display printing device related objects, wherein the list of topics provides a central point user interface comprising at least one root category of topics comprising the group consisting of device management, account management, queue management, queue user management, and combinations thereof to enable the user's selection from multiple levels of printing device related objects with circular associations to each other, which printing device related objects comprising traditional printing devices and non-traditional printing device related objects, which non-traditional printing device related objects comprise the group consisting of users, devices, alerts, hosts, queues, jobs, accounts, balances, and combinations thereof; the user specifying displaying in the central view pane of object property information associated with the selected at least one topic of interest about the printing device related objects; and causing displaying in the central view pane of object property information associated with the selected at least one topic of interest about the printing device related objects, while the left pane tree does not display printing device related objects wherein a list of devices can be displayed in the central view pane, and wherein displaying of the list of devices comprises: optionally expanding a Device Management category in order to select a List View topic of interest within the Device Management category; selecting the List View topic of interest within the Device Management category; and causing the list of devices to be displayed in the central view pane using a default object locator ALL, which locates all objects without any filtering, and the list of devices is never displayed in the left pane tree. 12. The computer program product of claim 9 , wherein the selecting of the at least one topic of interest comprises selecting the at least one topic of interest in a first pane in a menu; wherein the displaying of the object property information associated with the selected topic of interest comprises displaying the object property information in a second pane in the menu; and the number of the at least one topic of interest in the first pane and the number of the object property information in the second pane stay constant while there is an increase in the number of printing devices on the network. | 0.65724 |
10,068,178 | 9 | 11 | 9. A method comprising: receiving, at a computing system, an item of content from a user, the item of content comprising one or more first annotations, wherein the one or more first annotations comprise at least one designated tag; identifying a probability distribution of the one or more first annotations over two or more geographic locations based, at least in part, on a language model; smoothing the probability distribution based, at least in part, on annotation-specific smoothing with the item of content based, at least in part on a smoothing coefficient, wherein the smoothing coefficient for a particular annotation is proportional to a spatial ambiguity of the annotation; receiving one or more second annotations; and wherein in response to receiving the one or more second annotations, determining one or more of the geographical locations corresponding to the one or more second annotations based, at least in part, on the smoothed probability distribution. | 9. A method comprising: receiving, at a computing system, an item of content from a user, the item of content comprising one or more first annotations, wherein the one or more first annotations comprise at least one designated tag; identifying a probability distribution of the one or more first annotations over two or more geographic locations based, at least in part, on a language model; smoothing the probability distribution based, at least in part, on annotation-specific smoothing with the item of content based, at least in part on a smoothing coefficient, wherein the smoothing coefficient for a particular annotation is proportional to a spatial ambiguity of the annotation; receiving one or more second annotations; and wherein in response to receiving the one or more second annotations, determining one or more of the geographical locations corresponding to the one or more second annotations based, at least in part, on the smoothed probability distribution. 11. The method of claim 9 , further comprising ranking the two or more geographical locations. | 0.92868 |
7,552,381 | 1 | 29 | 1. A computer-implemented method comprising: scanning a coversheet having an overview of a collection; receiving an image of the overview of the collection that comprises a first plurality of indication areas associated with a plurality of documents and a second plurality of indication areas associated with a plurality of actions, wherein the plurality of actions includes printing, faxing, sending by electronic mail, and grouping; identifying at least one action from the plurality of actions set forth in the image; identifying at least one document from the plurality of documents for the at least one action identified from the plurality of actions, wherein the identifying the at least one action from the plurality of actions set forth in the image is performed based on the second plurality of the indication areas in the image, the identifying the at least one document from the plurality of documents is performed based on the first plurality of the indication areas in the image, wherein the at least one action from the plurality of actions and the at least one document from the plurality of documents are identified by scanning the image; and performing the at least one action on the at least one document in response to the identifying the at least one action from the fourth plurality of actions set forth in the image and the identifying the at least one document from the third plurality of documents from the image. | 1. A computer-implemented method comprising: scanning a coversheet having an overview of a collection; receiving an image of the overview of the collection that comprises a first plurality of indication areas associated with a plurality of documents and a second plurality of indication areas associated with a plurality of actions, wherein the plurality of actions includes printing, faxing, sending by electronic mail, and grouping; identifying at least one action from the plurality of actions set forth in the image; identifying at least one document from the plurality of documents for the at least one action identified from the plurality of actions, wherein the identifying the at least one action from the plurality of actions set forth in the image is performed based on the second plurality of the indication areas in the image, the identifying the at least one document from the plurality of documents is performed based on the first plurality of the indication areas in the image, wherein the at least one action from the plurality of actions and the at least one document from the plurality of documents are identified by scanning the image; and performing the at least one action on the at least one document in response to the identifying the at least one action from the fourth plurality of actions set forth in the image and the identifying the at least one document from the third plurality of documents from the image. 29. The method of claim 1 , wherein receiving the image of a document index comprises receiving an e-mail message containing the image of the document index. | 0.841093 |
8,037,001 | 2 | 3 | 2. The method of claim 1 , further comprising determining a cost for each EFMPR. | 2. The method of claim 1 , further comprising determining a cost for each EFMPR. 3. The method of claim 2 , further comprising determining the overlap threshold based on the cost of the candidate EFMPR. | 0.956223 |
9,055,419 | 2 | 3 | 2. The method according to claim 1 , wherein the parsing history short messages of a user to generate data associated with contacts further comprises: acquiring identification information on the contacts of the history short messages; and acquiring a name entity list of the history short messages by performing name entity recognition on texts of the history short messages. | 2. The method according to claim 1 , wherein the parsing history short messages of a user to generate data associated with contacts further comprises: acquiring identification information on the contacts of the history short messages; and acquiring a name entity list of the history short messages by performing name entity recognition on texts of the history short messages. 3. The method according to claim 2 , wherein constructing the critical object association database by using the data comprises constructing a name entity association database by using the data. | 0.956765 |
9,886,525 | 3 | 4 | 3. The system of claim 1 , wherein the processor is configured to determine the probability associated with the geographic region based at least in part on one or more previous events associated with the geographic region. | 3. The system of claim 1 , wherein the processor is configured to determine the probability associated with the geographic region based at least in part on one or more previous events associated with the geographic region. 4. The system of claim 3 , wherein the processor configured to determine the probability associated with the geographic region is configured to: determine the probability associated with the geographic region based at least in part on a predicted change to a second attribute of individual data items within the plurality of data items. | 0.940043 |
7,958,123 | 7 | 9 | 7. A bundle database management method for generating, storing, and searching bundle data defining an association structure between individual words having relation to each other, the method comprising the steps of: (1) defining, with a processor, a core word, a relevant word connected to the core word, and another relevant word derived from the relevant word regarded as another core word, generating bundle data defining an nth connection relation between the core word and the relevant word as a graph hierarchy structure, and storing the generated bundle data; (2) storing description data in a memory, the description data corresponding to the core word and the relevant word; (3) receiving a search request including a specific search word input by a user; (4) generating, with a processor, a search result page including the bundle data having a search word as its core word and the description data relating to the core word; and (5) transmitting the search result page to a user terminal, wherein the step of (4) generating a search result page includes the step of including the bundle data in the search result page, the bundle data being in odd bundles (n =1, 3, 5, . . . ) represented in such a graphic structure that at least one relevant word for each core word are horizontally connects and in even bundles (n =2, 4, 6, . . . ) represented in such a graphic structure that at least one relevant word for each core word are vertically connected. | 7. A bundle database management method for generating, storing, and searching bundle data defining an association structure between individual words having relation to each other, the method comprising the steps of: (1) defining, with a processor, a core word, a relevant word connected to the core word, and another relevant word derived from the relevant word regarded as another core word, generating bundle data defining an nth connection relation between the core word and the relevant word as a graph hierarchy structure, and storing the generated bundle data; (2) storing description data in a memory, the description data corresponding to the core word and the relevant word; (3) receiving a search request including a specific search word input by a user; (4) generating, with a processor, a search result page including the bundle data having a search word as its core word and the description data relating to the core word; and (5) transmitting the search result page to a user terminal, wherein the step of (4) generating a search result page includes the step of including the bundle data in the search result page, the bundle data being in odd bundles (n =1, 3, 5, . . . ) represented in such a graphic structure that at least one relevant word for each core word are horizontally connects and in even bundles (n =2, 4, 6, . . . ) represented in such a graphic structure that at least one relevant word for each core word are vertically connected. 9. The bundle database management method of claim 7 , wherein the step of (2) storing description data includes storing description data corresponding to the core word and relevant word in a description data DB. | 0.931582 |
7,870,163 | 11 | 24 | 11. A non-transitory computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to modify an existing XML schema in a database without modifying existing data that conforms to the existing XML schema in the database by performing the steps of: storing data from a set of XML documents in base database structures in a database according to an XML schema, wherein the XML schema defines an XML structure for said set of XML documents; after storing the data from the set of XML documents in the base database structures, receiving a request to make one or more changes to the schema; determining that the schema, if modified by the one or more changes, would be compatible with the stored data; and wherein the step of determining that the schema, if modified by the one or more changes, would be compatible with the stored data comprises one or more of: (a) determining that the one or more changes comprise an addition of a new element to the schema, and determining that the data stored in the base database structures in the database would be compatible with the schema as modified to add the new element; (b) determining that the one or more changes comprise a removal of an element from the schema, and determining whether the data stored in the base database structures in the database would be compatible with the schema as modified to remove the element; or (c) determining that the one or more changes affect the ordering of elements within the schema, and determining whether the data stored in the base database structures in the database would be compatible with the schema as modified to affect the ordering of elements within the schema; and in response to determining that the schema, if modified by the one or more changes, would be compatible with the stored data, modifying the base database structures in the database to reflect the changes to the schema without modifying the data from the set of XML documents that is stored in the base database structures. | 11. A non-transitory computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to modify an existing XML schema in a database without modifying existing data that conforms to the existing XML schema in the database by performing the steps of: storing data from a set of XML documents in base database structures in a database according to an XML schema, wherein the XML schema defines an XML structure for said set of XML documents; after storing the data from the set of XML documents in the base database structures, receiving a request to make one or more changes to the schema; determining that the schema, if modified by the one or more changes, would be compatible with the stored data; and wherein the step of determining that the schema, if modified by the one or more changes, would be compatible with the stored data comprises one or more of: (a) determining that the one or more changes comprise an addition of a new element to the schema, and determining that the data stored in the base database structures in the database would be compatible with the schema as modified to add the new element; (b) determining that the one or more changes comprise a removal of an element from the schema, and determining whether the data stored in the base database structures in the database would be compatible with the schema as modified to remove the element; or (c) determining that the one or more changes affect the ordering of elements within the schema, and determining whether the data stored in the base database structures in the database would be compatible with the schema as modified to affect the ordering of elements within the schema; and in response to determining that the schema, if modified by the one or more changes, would be compatible with the stored data, modifying the base database structures in the database to reflect the changes to the schema without modifying the data from the set of XML documents that is stored in the base database structures. 24. The computer-readable storage medium of claim 11 , wherein the step of determining that the schema, if modified by the one or more changes, would be compatible with the stored data comprises (c) determining that the one or more changes affect the ordering of elements within the schema, and determining that the data stored in the base database structures in the database would be compatible with the schema as modified to affect the ordering of elements within the schema. | 0.597808 |
8,584,227 | 16 | 17 | 16. The computer-readable storage medium of claim 15 , wherein the policy store comprises at least one of a local policy store, a dynamic policy store, and/or a group policy store. | 16. The computer-readable storage medium of claim 15 , wherein the policy store comprises at least one of a local policy store, a dynamic policy store, and/or a group policy store. 17. The computer-readable storage medium of claim 16 , further comprising a network location awareness component, wherein the current network context is derived from information provided by the network location awareness component. | 0.927903 |
8,566,938 | 3 | 4 | 3. The method of claim 1 , wherein comparing the email characteristics of the received email message with stored email characteristics associated with the recipient/recipient organization and/or the sender/sender organization, comprises: obtaining a statistical distribution of each of the stored email characteristics associated with the recipient/recipient organization and/or sender/sender organization; and comparing the email characteristics of the received email message with the obtained statistical distribution of prior email characteristics associated with the recipient/recipient organization and/or sender/sender organization. | 3. The method of claim 1 , wherein comparing the email characteristics of the received email message with stored email characteristics associated with the recipient/recipient organization and/or the sender/sender organization, comprises: obtaining a statistical distribution of each of the stored email characteristics associated with the recipient/recipient organization and/or sender/sender organization; and comparing the email characteristics of the received email message with the obtained statistical distribution of prior email characteristics associated with the recipient/recipient organization and/or sender/sender organization. 4. The method of claim 3 , further comprising: determining degree of variance of each email characteristic when compared with the associated statistical distribution; establishing a score based on the determined degree of variance for each email characteristic; assigning weights for each established score based on the determined degree of variance; and obtaining a combined score by adding scores of all the email characteristics in the received email based on the assigned weights. | 0.943695 |
8,775,436 | 1 | 3 | 1. A method comprising: identifying, by one or more processors, a caption associated with an image included in a document in a cluster of documents; generating, by one or more processors, a first score for the image based on a size of the image; generating, by the one or more processors, a second score for the image based on a distance between the image and a title of the document; generating, by the one or more processors, a third score for the image based on the caption associated with the image; generating, by the one or more processors, an overall score for the image based on the first score, the second score, and the third score; identifying, by one or more processors, the image for being representative of the cluster based on the overall score; and associating, by one or more processors, the image with the cluster as being a representative image of the cluster. | 1. A method comprising: identifying, by one or more processors, a caption associated with an image included in a document in a cluster of documents; generating, by one or more processors, a first score for the image based on a size of the image; generating, by the one or more processors, a second score for the image based on a distance between the image and a title of the document; generating, by the one or more processors, a third score for the image based on the caption associated with the image; generating, by the one or more processors, an overall score for the image based on the first score, the second score, and the third score; identifying, by one or more processors, the image for being representative of the cluster based on the overall score; and associating, by one or more processors, the image with the cluster as being a representative image of the cluster. 3. The method of claim 1 , further comprising: receiving a search query; generating a list of search results based on the search query, the list of search results including information regarding documents in the cluster, and the documents including the document that includes the image; generating a search result document that includes the list of search results, the search result document presenting the representative image with the information regarding the documents in the cluster; and outputting the search result document. | 0.759293 |
9,099,090 | 1 | 2 | 1. A computer-implemented method, the computer-implemented method comprising: under control of a computing device configured with specific computer-executable instructions, receiving a first portion of audio data; generating, with an automatic speech recognition engine, first transcribed text corresponding to the first portion of the audio data; determining a confidence level for transcription accuracy of the first transcribed text; transmitting the first transcribed text to a first device for presentation on the first device; transmitting the confidence level to the first device, the confidence level associated with a cue for presentation on the first device, wherein the cue indicates the confidence level for transcription accuracy of the first transcribed text, and wherein the cue is distinct from the first transcribed text; substantially while the first transcribed text is being presented on the first device, receiving a second portion of the audio data; and generating, with the automatic speech recognition engine, second transcribed text corresponding to the first portion of the audio data and the second portion of the audio data; and transmitting the second transcribed text to the first device for presentation on the first device. | 1. A computer-implemented method, the computer-implemented method comprising: under control of a computing device configured with specific computer-executable instructions, receiving a first portion of audio data; generating, with an automatic speech recognition engine, first transcribed text corresponding to the first portion of the audio data; determining a confidence level for transcription accuracy of the first transcribed text; transmitting the first transcribed text to a first device for presentation on the first device; transmitting the confidence level to the first device, the confidence level associated with a cue for presentation on the first device, wherein the cue indicates the confidence level for transcription accuracy of the first transcribed text, and wherein the cue is distinct from the first transcribed text; substantially while the first transcribed text is being presented on the first device, receiving a second portion of the audio data; and generating, with the automatic speech recognition engine, second transcribed text corresponding to the first portion of the audio data and the second portion of the audio data; and transmitting the second transcribed text to the first device for presentation on the first device. 2. The computer-implemented method of claim 1 , wherein the confidence level is based at least in part on at least one of: a background noise level of the first portion of the audio data; or a volume of the first portion of the audio data. | 0.784296 |
9,355,650 | 18 | 19 | 18. The non-transitory computer-readable medium according to claim 17 , wherein the processor further determines that the current emotional state of the audio signal changes to the other emotional state of the plurality of emotional states when the emotional state of one of the plurality of segments is the other emotional state with the confidence score of the emotional state of the one of the plurality of segments being greater than the predetermined threshold. | 18. The non-transitory computer-readable medium according to claim 17 , wherein the processor further determines that the current emotional state of the audio signal changes to the other emotional state of the plurality of emotional states when the emotional state of one of the plurality of segments is the other emotional state with the confidence score of the emotional state of the one of the plurality of segments being greater than the predetermined threshold. 19. The non-transitory computer-readable medium according to claim 18 , wherein the predetermined number of the plurality of segments is consecutive in the audio signal. | 0.942281 |
9,672,010 | 12 | 18 | 12. A universal modeling language (UML) analysis method that utilizes at least one processor to execute program instructions stored on a memory, the method comprising: importing at least one tool-specific UML model from at least one UML tool; capturing a snapshot of the at least one tool-specific UML model, wherein the snapshot comprises text data and at least one diagram; translating by at least one transforming mechanism the at least one tool-specific UML model into at least one transformed UML model having a universal UML format, wherein the translating operation comprises extracting base data and one or more associated extended elements from the at least one tool-specific UML model; display a model navigation interface on a monitor coupled to the at least one processor; and displaying particular model elements based on commands input through the model navigation interface. | 12. A universal modeling language (UML) analysis method that utilizes at least one processor to execute program instructions stored on a memory, the method comprising: importing at least one tool-specific UML model from at least one UML tool; capturing a snapshot of the at least one tool-specific UML model, wherein the snapshot comprises text data and at least one diagram; translating by at least one transforming mechanism the at least one tool-specific UML model into at least one transformed UML model having a universal UML format, wherein the translating operation comprises extracting base data and one or more associated extended elements from the at least one tool-specific UML model; display a model navigation interface on a monitor coupled to the at least one processor; and displaying particular model elements based on commands input through the model navigation interface. 18. The UML analysis method of claim 12 , wherein the at least one tool-specific UML model comprises a plurality of tool-specific UML models, wherein each of the plurality of tool-specific UML models has a having unique tool-specific UML format, and wherein the universal UML format differs from any of the unique tool-specific UML formats. | 0.788557 |
8,346,794 | 9 | 10 | 9. The method of claim 8 wherein the querying a reference database comprises querying the reference database for reference database records that possibly match the input data query, the method further comprising: in response to failing to find a matching reference database record but finding one or more possibly matching reference database records, determining whether a possibly matching record can be considered a near-matching record to the input data query; and in response to identifying a near-matching record, applying at least one transformation rule to convert the near-matching reference database record to a plurality of forms, wherein individual ones of the plurality of forms correspond to individual target databases of a plurality of target databases, and querying using at least one of the individual ones of the plurality of forms at least one of the plurality of target databases for one or more target database records that correspond to the individual ones of the plurality of forms. | 9. The method of claim 8 wherein the querying a reference database comprises querying the reference database for reference database records that possibly match the input data query, the method further comprising: in response to failing to find a matching reference database record but finding one or more possibly matching reference database records, determining whether a possibly matching record can be considered a near-matching record to the input data query; and in response to identifying a near-matching record, applying at least one transformation rule to convert the near-matching reference database record to a plurality of forms, wherein individual ones of the plurality of forms correspond to individual target databases of a plurality of target databases, and querying using at least one of the individual ones of the plurality of forms at least one of the plurality of target databases for one or more target database records that correspond to the individual ones of the plurality of forms. 10. The method of claim 9 further comprising: in response to failing to find a matching reference database record and finding one or more possibly matching reference database records but failing to identify a near-matching record, generating at the computing device a selection request to choose from among the one or more possibly matching records a record that corresponds to the input data query; and in response to a possibly matching record that corresponds to the input data query and is chosen, applying at least one transformation rule to convert the chosen record to a plurality of forms, wherein individual ones of the plurality of forms correspond to individual target databases of a plurality of target databases, and querying at the computing device using at least one of the individual ones of the plurality of forms at least one of the plurality of target databases for the one or more target database records that correspond to the individual ones of the plurality of forms. | 0.717466 |
7,584,451 | 14 | 17 | 14. A computer-readable storage medium having computer-readable instructions stored thereon, which, when executed by a computer, control said computer to provide a user interface mechanism which allows a user to enter user input data which defines a transaction which is a formula which expresses the composition of services which make up said transaction where a service is part of a class which is part of an object model which is part of a conceptual model of a target computer program to be automatically written and whose functionality is defined by said conceptual model, and wherein said transaction is a molecular execution unit expressed in terms of a formula that specifies services in the form of events or transactions which together comprise said molecular execution unit, and said instructions controlling said computer to convert said user input data into one or more data structures in the form of one or more formal language statements written in a formal language which has rules of syntax and semantics which define a grammar, said formal language statements defining said transaction, and said instructions controlling said computer to use said rules of syntax and semantics to validate said formal language statements. | 14. A computer-readable storage medium having computer-readable instructions stored thereon, which, when executed by a computer, control said computer to provide a user interface mechanism which allows a user to enter user input data which defines a transaction which is a formula which expresses the composition of services which make up said transaction where a service is part of a class which is part of an object model which is part of a conceptual model of a target computer program to be automatically written and whose functionality is defined by said conceptual model, and wherein said transaction is a molecular execution unit expressed in terms of a formula that specifies services in the form of events or transactions which together comprise said molecular execution unit, and said instructions controlling said computer to convert said user input data into one or more data structures in the form of one or more formal language statements written in a formal language which has rules of syntax and semantics which define a grammar, said formal language statements defining said transaction, and said instructions controlling said computer to use said rules of syntax and semantics to validate said formal language statements. 17. The computer-readable storage medium of claim 14 wherein said computer-readable instructions control said computer to provide a user interface mechanism which allows a user to enter user input data which defines said transaction as a local transaction wherein said one or more services which comprise said local transaction are events or transactions owned by the class or the ancestor of the class which owns said transaction which owns said transaction formula, or said one or more services which comprise said transaction are owned by classes related with the class owning the transaction which owns said transaction formula, and wherein said computer-readable instructions control said computer to convert said user input data into one or more data structures in the form of one or more formal language statements written in a formal language which has rules of syntax and rules of semantics which define a grammar, said one or more formal language statements defining said local transaction, said instructions also controlling said computer to use said rules of syntax and semantics to validate said one or more formal language statements to ensure each is complete and correct. | 0.813247 |
9,152,632 | 1 | 4 | 1. A method of operating an information management system, comprising: for each source file in a first collection of source files: parsing, by a processor of a computing device, the respective source file to extract one or more chemical structures, comparing, by the processor, the one or more chemical structures to chemical structures stored in at least one dictionary, wherein each dictionary of the at least one dictionary comprises a hierarchical listing of chemical structures, and comparing comprises identifying one or more matching chemical structures, and associating, by the processor, with the respective source file, the one or more matching chemical structures; generating, by the processor, a first virtual relational network comprising the source files in the first collection, wherein the first virtual relational network comprises: one or more nodes, wherein each node represents a particular matching chemical structure of the one or more matching chemical structures associated with a particular source file of the source files in the first collection, and one or more links, wherein each link represents a connection between a pair of nodes, wherein each node of the pair of nodes is associated with a common chemical structure; and comparing, by the processor, the first virtual relational network to a second virtual relational network, wherein comparing comprises identifying at least one of a) one or more nodes and b) one or more links common to both the first virtual relational network and the second virtual relational network, wherein the second virtual relational network is created from a second collection of source files different than the first collection of source files; and the first virtual relational network and the second virtual relational network share at least one common dictionary, wherein the at least one dictionary comprises the at least one common dictionary. | 1. A method of operating an information management system, comprising: for each source file in a first collection of source files: parsing, by a processor of a computing device, the respective source file to extract one or more chemical structures, comparing, by the processor, the one or more chemical structures to chemical structures stored in at least one dictionary, wherein each dictionary of the at least one dictionary comprises a hierarchical listing of chemical structures, and comparing comprises identifying one or more matching chemical structures, and associating, by the processor, with the respective source file, the one or more matching chemical structures; generating, by the processor, a first virtual relational network comprising the source files in the first collection, wherein the first virtual relational network comprises: one or more nodes, wherein each node represents a particular matching chemical structure of the one or more matching chemical structures associated with a particular source file of the source files in the first collection, and one or more links, wherein each link represents a connection between a pair of nodes, wherein each node of the pair of nodes is associated with a common chemical structure; and comparing, by the processor, the first virtual relational network to a second virtual relational network, wherein comparing comprises identifying at least one of a) one or more nodes and b) one or more links common to both the first virtual relational network and the second virtual relational network, wherein the second virtual relational network is created from a second collection of source files different than the first collection of source files; and the first virtual relational network and the second virtual relational network share at least one common dictionary, wherein the at least one dictionary comprises the at least one common dictionary. 4. The method of claim 1 , wherein associating the one or more matching chemical structures comprises, for each dictionary of the at least one dictionary, associating the one or more matching chemical structures from the respective dictionary with the respective source file as a separate set of chemical structures. | 0.705224 |
9,998,552 | 12 | 13 | 12. The apparatus according to claim 9 , wherein the application is further configured to cause the processor to: determine a topic of the medium; determine acquaintances of the user; determine one or more of the acquaintances that have an interest in the topic; and notify the one or more acquaintances that are interested in the topic about the medium. | 12. The apparatus according to claim 9 , wherein the application is further configured to cause the processor to: determine a topic of the medium; determine acquaintances of the user; determine one or more of the acquaintances that have an interest in the topic; and notify the one or more acquaintances that are interested in the topic about the medium. 13. The apparatus according to claim 12 , wherein the application is further configured to cause the processor to: automatically generate at least one content update to the medium; update the medium with the at least one automatically generated content update; and notify at least one of the one or more acquaintances that are interested in the topic about the at least one automatically generated content update. | 0.883924 |
9,779,632 | 8 | 10 | 8. The method of claim 1 wherein adaptively deriving, from the learning graph, the customized learning path for the particular person node comprises: traversing the learning graph from a particular one of the one or more person nodes to a learning goal node, the learning goal node specifying information to be learned; traversing the learning graph to find a plurality of relevant content to the learning goal based on one or more predefined content identification strategy algorithms; and compiling the relevant content into said customized learning path. | 8. The method of claim 1 wherein adaptively deriving, from the learning graph, the customized learning path for the particular person node comprises: traversing the learning graph from a particular one of the one or more person nodes to a learning goal node, the learning goal node specifying information to be learned; traversing the learning graph to find a plurality of relevant content to the learning goal based on one or more predefined content identification strategy algorithms; and compiling the relevant content into said customized learning path. 10. The method of claim 8 wherein at least one of the predefined content identification strategy algorithms analyzes nodes and edges in the learning graph. | 0.935092 |
8,671,109 | 20 | 21 | 20. The method defined in claim 17 , wherein each of the reference data elements includes a respective first set of (value, position) pairs each identifying a value and a position of a respective feature extracted from the reference video stream, wherein each of the query data elements includes a respective second set of (value, position) pairs each identifying a value and a position of a respective feature extracted from the query video stream, and wherein determining a distance between the selected reference data element and each of the query data elements comprises determining a total distance between the first set of (value, position) pairs corresponding to the selected reference data element and each of the second sets of (value, position) pairs, and selecting as the fingerprint associated with the selected reference. | 20. The method defined in claim 17 , wherein each of the reference data elements includes a respective first set of (value, position) pairs each identifying a value and a position of a respective feature extracted from the reference video stream, wherein each of the query data elements includes a respective second set of (value, position) pairs each identifying a value and a position of a respective feature extracted from the query video stream, and wherein determining a distance between the selected reference data element and each of the query data elements comprises determining a total distance between the first set of (value, position) pairs corresponding to the selected reference data element and each of the second sets of (value, position) pairs, and selecting as the fingerprint associated with the selected reference. 21. The method defined in claim 20 , wherein determining a total distance between the first set of (value, position) pairs corresponding to the selected reference data element and a particular one of the second sets of (value, position) pairs comprises determining a distance between the value of a first (value, position) pair in the first set of (value, position) pairs and the value of a second (value, position) pair in the particular one of the second sets of (value, position) pairs for which the position is the same, and combining the distances over all positions. | 0.604426 |
8,510,298 | 22 | 24 | 22. The method of claim 21 , wherein the brand-store affinity matrix comprises the one or more values, for one or more instances of the brand, calculated based on normalized scores of one or more instances of the store. | 22. The method of claim 21 , wherein the brand-store affinity matrix comprises the one or more values, for one or more instances of the brand, calculated based on normalized scores of one or more instances of the store. 24. The method of claim 22 , wherein the normalized scores of the one or more instances of the brand are calculated based on the one or more values corresponding to an attribute instance of the brand. | 0.970947 |
8,892,438 | 1 | 7 | 1. A method comprising: selecting a plurality of language models; for each period of a plurality of time periods: identifying a first utterance and a second utterance received during each time period, wherein the first utterance was recognized using a first language model of the plurality of language models and the second utterance was recognized using a second language model of the plurality of language models; identifying distinctions between the first utterance and the second utterance for each of the plurality of time periods; determining when a significant word usage change has occurred within the first language model and the second language model by comparing the distinctions to previously recorded distinctions; and when the significant word usage change is detected: identifying a word corresponding to the significant word usage change; generating, from the utterances, a first cluster of utterances comprising the word; generating, from the utterances, a second cluster of utterances not comprising the word; and updating the plurality of language models using the first cluster of utterances and the second cluster of utterances. | 1. A method comprising: selecting a plurality of language models; for each period of a plurality of time periods: identifying a first utterance and a second utterance received during each time period, wherein the first utterance was recognized using a first language model of the plurality of language models and the second utterance was recognized using a second language model of the plurality of language models; identifying distinctions between the first utterance and the second utterance for each of the plurality of time periods; determining when a significant word usage change has occurred within the first language model and the second language model by comparing the distinctions to previously recorded distinctions; and when the significant word usage change is detected: identifying a word corresponding to the significant word usage change; generating, from the utterances, a first cluster of utterances comprising the word; generating, from the utterances, a second cluster of utterances not comprising the word; and updating the plurality of language models using the first cluster of utterances and the second cluster of utterances. 7. The method of claim 1 , wherein the plurality of time periods comprises two non-overlapping months. | 0.959874 |
9,337,960 | 1 | 5 | 1. An encoding method of an Ethernet physical layer, the method comprising: determining a to-be-encoded first information group, wherein the first information group comprises m characters, m≧2, and m is an integer, wherein a character attribute of any character is a data character, a boundary character, or a third-type character, one character occupies one byte, and the third-type character is a character except the data character and the boundary character; detecting a character attribute of each character in the first information group; if the first information group comprises n boundary characters, wherein n≧1, and n is an integer, deleting the n boundary characters, and generating a second information group by using a character, except the n boundary characters, in the first information group, and type information and position information that are of the n boundary characters, wherein the second information group comprises m bytes; and adding header information to the second information group according to a type of the first information group and a correspondence between a prestored type of a information group and a type of header information of the information group, wherein the type of the first information group is determined by the prestored type of the information group and character attributes of the characters in the first information group. | 1. An encoding method of an Ethernet physical layer, the method comprising: determining a to-be-encoded first information group, wherein the first information group comprises m characters, m≧2, and m is an integer, wherein a character attribute of any character is a data character, a boundary character, or a third-type character, one character occupies one byte, and the third-type character is a character except the data character and the boundary character; detecting a character attribute of each character in the first information group; if the first information group comprises n boundary characters, wherein n≧1, and n is an integer, deleting the n boundary characters, and generating a second information group by using a character, except the n boundary characters, in the first information group, and type information and position information that are of the n boundary characters, wherein the second information group comprises m bytes; and adding header information to the second information group according to a type of the first information group and a correspondence between a prestored type of a information group and a type of header information of the information group, wherein the type of the first information group is determined by the prestored type of the information group and character attributes of the characters in the first information group. 5. The encoding method according to claim 1 , wherein: m≦64; and if the prestored type of the information group is an all-data-character type and a non-all-data-character type, the header information of the information group comprises at least two types; or if the prestored type of the information group is an all-data-character type, an all-third-type-character type, and a boundary-character-included type, the header information of the information group comprises at least three types. | 0.836564 |
9,699,249 | 1 | 7 | 1. A method, performed by a client, to dynamically generate an application programming interface that enables the client to access a service provided by a server, the method comprising: receiving a request to connect to the server that provides the service, and in response thereto, connecting to the server; downloading an interface definition language file, wherein the interface definition languages file defines the service; generating interface metadata based on the interface definition language file, wherein the interface metadata includes methods, data types, and messages supported by the server; storing the generated interface metadata in a local memory or storage of the client; and in response to a request to execute a method of the service: generating instructions which implement interface bindings for the method based on the stored interface metadata, and executing the method, wherein the executing of the method includes exchanging messages with the server and receiving a result of the method execution from the server. | 1. A method, performed by a client, to dynamically generate an application programming interface that enables the client to access a service provided by a server, the method comprising: receiving a request to connect to the server that provides the service, and in response thereto, connecting to the server; downloading an interface definition language file, wherein the interface definition languages file defines the service; generating interface metadata based on the interface definition language file, wherein the interface metadata includes methods, data types, and messages supported by the server; storing the generated interface metadata in a local memory or storage of the client; and in response to a request to execute a method of the service: generating instructions which implement interface bindings for the method based on the stored interface metadata, and executing the method, wherein the executing of the method includes exchanging messages with the server and receiving a result of the method execution from the server. 7. The method of claim 1 , wherein executing the method comprises implementing a call-back function. | 0.902153 |
9,916,194 | 1 | 7 | 1. A computer-implemented method for client system component failure diagnosis, the computer-implemented method comprising: determining, by a server computer, whether a number of component failure cases corresponding to a client data processing system stored in a historical diagnosis database is less than a pre-defined threshold number of component failure cases needed to run a machine learning diagnosis component of the server computer to predict a system component failure root cause within the client data processing system; responsive to the server computer determining that the number of component failure cases corresponding to the client data processing system stored in the historical diagnosis database is less than the pre-defined threshold number of component failure cases needed to run the machine learning diagnosis component of the server computer to predict the system component failure root cause within the client data processing system, running, by the server computer, a rule-based reasoning diagnosis component of the server computer to predict the system component failure root cause within the client data processing system; calculating, by the server computer, a diagnosis accuracy of the system component failure root cause predicted by the rule-based reasoning diagnosis component of the server computer based on historical data corresponding to the client data processing system stored in the historical diagnosis database; verifying, by the server computer, the system component failure root cause within the client data processing system based on the diagnosis accuracy; and fixing, by the server computer, the verified system component failure root cause within the client data processing system increasing performance of the client data processing system. | 1. A computer-implemented method for client system component failure diagnosis, the computer-implemented method comprising: determining, by a server computer, whether a number of component failure cases corresponding to a client data processing system stored in a historical diagnosis database is less than a pre-defined threshold number of component failure cases needed to run a machine learning diagnosis component of the server computer to predict a system component failure root cause within the client data processing system; responsive to the server computer determining that the number of component failure cases corresponding to the client data processing system stored in the historical diagnosis database is less than the pre-defined threshold number of component failure cases needed to run the machine learning diagnosis component of the server computer to predict the system component failure root cause within the client data processing system, running, by the server computer, a rule-based reasoning diagnosis component of the server computer to predict the system component failure root cause within the client data processing system; calculating, by the server computer, a diagnosis accuracy of the system component failure root cause predicted by the rule-based reasoning diagnosis component of the server computer based on historical data corresponding to the client data processing system stored in the historical diagnosis database; verifying, by the server computer, the system component failure root cause within the client data processing system based on the diagnosis accuracy; and fixing, by the server computer, the verified system component failure root cause within the client data processing system increasing performance of the client data processing system. 7. The computer-implemented method of claim 1 , wherein the server computer combines a similarity confidence level value, a frequency confidence level value, a timing confidence level value, and a component-function causal relationship confidence level value in the machine learning diagnosis component of the server computer to calculate an overall confidence level value corresponding to a system component that is most likely the system component failure root cause within the client data processing system. | 0.795673 |
9,401,147 | 9 | 15 | 9. A non-transitory computer-readable medium encoded with instructions that, when executed, operate to cause one or more processors to perform operations comprising: receiving, by a computing system, voice input that was captured by a microphone of a mobile computing device; interpreting, by the computing system, the voice input using a speech recognition system that is configured to convert the voice input to text; identifying, by the computing system, a portion of the voice input as being ambiguous due to the portion of the voice input being able to be represented by either of two or more homophones or homonyms; identifying, by the computing system, one or more geographic locations of the mobile computing device, the mobile computing device having received one or more wireless signals from one or more external transmitting devices and from which the mobile computing device was able to determine the one or more geographic locations; applying, by the computing system, the portion of the voice input that is able to be represented by either of the two or more homophones or homonyms to one or more rules that use the one or more geographic locations of the mobile computing device to select one of the two or more homophones or homonyms as a selected homophone or homonym that represents the portion of the voice input; and outputting, by the computing system and in response to the computing system having selected the one of the two or more homophones or homonyms as the selected homophone or homonym, the selected homophone or homonym to a computer application or computer service that is associated with the voice input. | 9. A non-transitory computer-readable medium encoded with instructions that, when executed, operate to cause one or more processors to perform operations comprising: receiving, by a computing system, voice input that was captured by a microphone of a mobile computing device; interpreting, by the computing system, the voice input using a speech recognition system that is configured to convert the voice input to text; identifying, by the computing system, a portion of the voice input as being ambiguous due to the portion of the voice input being able to be represented by either of two or more homophones or homonyms; identifying, by the computing system, one or more geographic locations of the mobile computing device, the mobile computing device having received one or more wireless signals from one or more external transmitting devices and from which the mobile computing device was able to determine the one or more geographic locations; applying, by the computing system, the portion of the voice input that is able to be represented by either of the two or more homophones or homonyms to one or more rules that use the one or more geographic locations of the mobile computing device to select one of the two or more homophones or homonyms as a selected homophone or homonym that represents the portion of the voice input; and outputting, by the computing system and in response to the computing system having selected the one of the two or more homophones or homonyms as the selected homophone or homonym, the selected homophone or homonym to a computer application or computer service that is associated with the voice input. 15. The non-transitory computer-readable medium of claim 9 , wherein: the one or more geographic locations is multiple geographic locations; and applying the portion of the voice input to the one or more rules that use the one or more geographic locations of the mobile computing device to select one of the two or more homophones or homonyms includes determining that the multiple geographic locations indicate that the mobile computing device is traveling with a rate of speed that exceeds a predefined rate of speed in order to select one of the two or more homophones or homonyms that is associated with travel in a vehicle. | 0.500795 |
9,015,101 | 1 | 7 | 1. A system for user customization of clinical data objects using a clinical modeling language, the system comprising: a processor and a memory to implement: a constraint definition language processor to define a detailed clinical model to express a clinical concept as a standardized and reusable set of clinical knowledge, the constraint definition language processor using a compiled, context-free constraint definition language to define the detailed clinical model as a compiled object, wherein compiling the detailed clinical model into a compiled object validates the detailed clinical model for correctness and consistency, the constraint definition language processor providing the compiled object as content for at least one of a clinical content database and a clinical information system, wherein content represents one or more parameters to instruct a clinical application, wherein the detailed clinical model defines an information model representing one or more instances of clinical information and a logical model representing an implementation of this information model, wherein the logical model represents clinical data using a two-layer data modeling approach in which a structure of a clinical data object is separated from a definition of information contained within the clinical data object, the logical model (i) defining information in the detailed clinical model as a set of constraints progressively limiting allowable data values in the detailed clinical model until a specific clinical data item is defined and (ii) defining relationships among information in the detailed clinical model, wherein the constraint definition language processor authorizes the detailed clinical model including the information model and the logical model and wherein the constraint definition language processor validates the detailed clinical model for correctness and consistency and compiles the detailed clinical model into the compiled object to instruct the clinical application regarding execution and consumption of data, the detailed clinical model extensible to allow a new detailed clinical model to be defined by a content author and an attribute to be added to an existing detailed clinical model to change behavior of the clinical application without requiring corresponding changes to the clinical application or underlying database structures. | 1. A system for user customization of clinical data objects using a clinical modeling language, the system comprising: a processor and a memory to implement: a constraint definition language processor to define a detailed clinical model to express a clinical concept as a standardized and reusable set of clinical knowledge, the constraint definition language processor using a compiled, context-free constraint definition language to define the detailed clinical model as a compiled object, wherein compiling the detailed clinical model into a compiled object validates the detailed clinical model for correctness and consistency, the constraint definition language processor providing the compiled object as content for at least one of a clinical content database and a clinical information system, wherein content represents one or more parameters to instruct a clinical application, wherein the detailed clinical model defines an information model representing one or more instances of clinical information and a logical model representing an implementation of this information model, wherein the logical model represents clinical data using a two-layer data modeling approach in which a structure of a clinical data object is separated from a definition of information contained within the clinical data object, the logical model (i) defining information in the detailed clinical model as a set of constraints progressively limiting allowable data values in the detailed clinical model until a specific clinical data item is defined and (ii) defining relationships among information in the detailed clinical model, wherein the constraint definition language processor authorizes the detailed clinical model including the information model and the logical model and wherein the constraint definition language processor validates the detailed clinical model for correctness and consistency and compiles the detailed clinical model into the compiled object to instruct the clinical application regarding execution and consumption of data, the detailed clinical model extensible to allow a new detailed clinical model to be defined by a content author and an attribute to be added to an existing detailed clinical model to change behavior of the clinical application without requiring corresponding changes to the clinical application or underlying database structures. 7. The system of claim 1 , wherein the detailed clinical model defines a panel referencing one or more statements including one or more values taken as a single observation having associations between the one or more statements. | 0.571429 |
9,704,130 | 16 | 17 | 16. The computer program product of claim 14 , wherein the computer readable program code for calculating the probability score is for one or more of: (a) determining that a user explicitly indicated a connection between the first one of the second nodes and the first one of the first nodes and responsively setting the probability score to one hundred percent; (b) determining from historical information an existence of a plurality of recorded situations in which a map for the first domain includes the first one of the first nodes and in which a map for the second domain includes the first one of the second nodes; computing a first quantity of times representing a sub-quantity of the recorded situations where the first one of the first nodes was connected to the first one of the second nodes; computing a second quantity of times representing a sub-quantity of the recorded situations where the first one of the first nodes was not connected to the second one of the second nodes; and calculating the probability score from the computed first quantity and the computed second quantity; and (c) determining the probability score based on a level of similarity that a first set of nodes having an edge to the first one of the first nodes have to a second set of nodes having an edge to the first one of the second nodes. | 16. The computer program product of claim 14 , wherein the computer readable program code for calculating the probability score is for one or more of: (a) determining that a user explicitly indicated a connection between the first one of the second nodes and the first one of the first nodes and responsively setting the probability score to one hundred percent; (b) determining from historical information an existence of a plurality of recorded situations in which a map for the first domain includes the first one of the first nodes and in which a map for the second domain includes the first one of the second nodes; computing a first quantity of times representing a sub-quantity of the recorded situations where the first one of the first nodes was connected to the first one of the second nodes; computing a second quantity of times representing a sub-quantity of the recorded situations where the first one of the first nodes was not connected to the second one of the second nodes; and calculating the probability score from the computed first quantity and the computed second quantity; and (c) determining the probability score based on a level of similarity that a first set of nodes having an edge to the first one of the first nodes have to a second set of nodes having an edge to the first one of the second nodes. 17. The computer program product of claim 16 , wherein the first graphical map is a topic map representation showing a set of first nodes and their interrelationships in accordance with topic map recorded information stored for the first domain, wherein the second graphical map is topic map representation showing a set of second nodes and their interrelationships in accordance with topic map recorded information stored for the second domain. | 0.879273 |
9,152,730 | 25 | 26 | 25. A non-transitory computer-readable medium, according to claim 24 , wherein a first set of formulas is used to determine the top score candidate and a second, different, set of formulas is used to determine if a different top score candidate should be selected. | 25. A non-transitory computer-readable medium, according to claim 24 , wherein a first set of formulas is used to determine the top score candidate and a second, different, set of formulas is used to determine if a different top score candidate should be selected. 26. A non-transitory computer-readable medium, according to claim 25 , wherein a different top score candidate is not used if using the second set of formulas results in the same top score candidate as using the first set of formulas. | 0.932448 |
10,114,965 | 10 | 11 | 10. A method of managing information comprising: providing an organization having an information management system comprising one or more rules and policy abstractions stored at a policy server to manage information of the organization, wherein a rule comprises an expression having a policy abstraction; within the organization, providing a user logged onto a client device and a confidential document managed by the information management system, wherein the client device comprises an interceptor code component and a policy engine code component executing on the client device, the interceptor code component resides within an operating system layer of the client device and is designed to intercept file system library requests received by an operating system installed on the client device, and the policy engine code component installed outside of the operating system layer receives information on the intercepted file system library requests; receiving at the information management system a profile of the client device, wherein the profile is based on the user and the client device; at the information management system, determining a subset of the one or more rules of the policy server relevant to the profile, wherein a rule is relevant to the profile when the client device is capable of supporting a syntax format of the rule; determining a first rule of the subset of the one or more rules in a first syntax format is not supported by the client device; converting the first rule into a second syntax format, wherein the client device supports the second syntax format but not the first syntax format; storing the subset of the one or more rules of the policy server on the client device including the first translated rule, wherein when an application program on a client device attempts to access the confidential document, the document access operation is initiated by the application program and detected by the interceptor code component, and the interceptor code component transfers handling of the document access operation to the policy engine code component; and in response to the operation, evaluating, based on received information associated with the operation from the engine code component installed outside of the operating system layer and the one or more rules, to determine whether to store information regarding the operation in a storage location. | 10. A method of managing information comprising: providing an organization having an information management system comprising one or more rules and policy abstractions stored at a policy server to manage information of the organization, wherein a rule comprises an expression having a policy abstraction; within the organization, providing a user logged onto a client device and a confidential document managed by the information management system, wherein the client device comprises an interceptor code component and a policy engine code component executing on the client device, the interceptor code component resides within an operating system layer of the client device and is designed to intercept file system library requests received by an operating system installed on the client device, and the policy engine code component installed outside of the operating system layer receives information on the intercepted file system library requests; receiving at the information management system a profile of the client device, wherein the profile is based on the user and the client device; at the information management system, determining a subset of the one or more rules of the policy server relevant to the profile, wherein a rule is relevant to the profile when the client device is capable of supporting a syntax format of the rule; determining a first rule of the subset of the one or more rules in a first syntax format is not supported by the client device; converting the first rule into a second syntax format, wherein the client device supports the second syntax format but not the first syntax format; storing the subset of the one or more rules of the policy server on the client device including the first translated rule, wherein when an application program on a client device attempts to access the confidential document, the document access operation is initiated by the application program and detected by the interceptor code component, and the interceptor code component transfers handling of the document access operation to the policy engine code component; and in response to the operation, evaluating, based on received information associated with the operation from the engine code component installed outside of the operating system layer and the one or more rules, to determine whether to store information regarding the operation in a storage location. 11. The method of claim 10 wherein determining whether the first syntax format is not supported by the client device comprises determining whether an available computing power or memory of the client device is sufficient to execute rules in the first syntax format. | 0.591049 |
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