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5,542,024 | 3 | 4 | 3. The information processing system according to claim 2, in which said plurality of selected options include a plurality of exit option actions at each interconnected knowledge record. | 3. The information processing system according to claim 2, in which said plurality of selected options include a plurality of exit option actions at each interconnected knowledge record. 4. The information processing system according to claim 3, in which said plurality of exit option actions include operating system commands, internal system commands and list processing commands. | 0.697205 |
8,306,509 | 8 | 12 | 8. A voicemail system comprising: a tangible computer processor; and a non-transitory computer-readable medium having instructions that, when executed by the processor, cause the processor to: receive a call for a called party at the voicemail system, the voicemail system comprising a stored language preference for the called party; prompt a calling party to leave a message; create the message; prompt the calling party to indicate a calling-party-selected language preference for the message; in response to prompting the calling party to indicate the calling-party-selected language preference for the message, receive the calling-party-selected language preference for the message; override the stored language preference for the called party with the calling-party-selected language preference; determine whether the message is in the calling-party-selected language preference; and in response to overriding the stored language preference with the calling-party-selected language preference, and if the message is not in the calling-party-selected preferred language identified by the language preference, translate the message into a preferred language of the calling-party-selected preferred language preference, thereby creating a translated message. | 8. A voicemail system comprising: a tangible computer processor; and a non-transitory computer-readable medium having instructions that, when executed by the processor, cause the processor to: receive a call for a called party at the voicemail system, the voicemail system comprising a stored language preference for the called party; prompt a calling party to leave a message; create the message; prompt the calling party to indicate a calling-party-selected language preference for the message; in response to prompting the calling party to indicate the calling-party-selected language preference for the message, receive the calling-party-selected language preference for the message; override the stored language preference for the called party with the calling-party-selected language preference; determine whether the message is in the calling-party-selected language preference; and in response to overriding the stored language preference with the calling-party-selected language preference, and if the message is not in the calling-party-selected preferred language identified by the language preference, translate the message into a preferred language of the calling-party-selected preferred language preference, thereby creating a translated message. 12. The voicemail system of claim 8 , wherein the message is at least one message type selected from a group of message types consisting of: a video message; a text message; and a voicemail message. | 0.509901 |
7,752,046 | 19 | 23 | 19. A method of building a language model used for automatic speech recognition (ASR), the method comprising: applying a tree growing algorithm to highly fragmented non-speech meta-data related to a caller to a spoken dialog system but does not describe physical characteristics of the caller; identifying a first quantity of leaf nodes in which a history appears as a result of applying the tree growing algorithm; building tree clusters from non-speech meta-data by generating a second quantity of projections based on the highly fragmented non-speech meta-data, wherein the first quantity equals the second quantity; and estimating a meta-data dependent language model using the built tree clusters and speech data, the language model used for ASR. | 19. A method of building a language model used for automatic speech recognition (ASR), the method comprising: applying a tree growing algorithm to highly fragmented non-speech meta-data related to a caller to a spoken dialog system but does not describe physical characteristics of the caller; identifying a first quantity of leaf nodes in which a history appears as a result of applying the tree growing algorithm; building tree clusters from non-speech meta-data by generating a second quantity of projections based on the highly fragmented non-speech meta-data, wherein the first quantity equals the second quantity; and estimating a meta-data dependent language model using the built tree clusters and speech data, the language model used for ASR. 23. The method of claim 19 , wherein the language model is estimated by weighing non-speech meta-data towards a type of data within the non-speech meta-data. | 0.792876 |
8,386,455 | 12 | 17 | 12. A system for generating search results, the system comprising: a non-transitory computer readable medium having executable instructions stored therein, and a processing device, in response to the executable instructions, operative to: receive a search request including at least one search term; access a plurality of data corpus, comprising a search database and an application database; determine relevant content from the search database for inclusion in a search result set on the basis of the at least one term of the search request, the content comprising metadata indicating an application associated with the content; determine a plurality of executable applications from the application database on the basis of the content metadata; and generate a search result output display that presents at least a portion of the search result set and at least one of the plurality of the executable applications, wherein the at least one of the executable applications are presented as embedded objects within the display, created in response to the search request, that when selected cause the executable application associated with the content metadata to be executed. | 12. A system for generating search results, the system comprising: a non-transitory computer readable medium having executable instructions stored therein, and a processing device, in response to the executable instructions, operative to: receive a search request including at least one search term; access a plurality of data corpus, comprising a search database and an application database; determine relevant content from the search database for inclusion in a search result set on the basis of the at least one term of the search request, the content comprising metadata indicating an application associated with the content; determine a plurality of executable applications from the application database on the basis of the content metadata; and generate a search result output display that presents at least a portion of the search result set and at least one of the plurality of the executable applications, wherein the at least one of the executable applications are presented as embedded objects within the display, created in response to the search request, that when selected cause the executable application associated with the content metadata to be executed. 17. The system of claim 12 , the processing device, in response to executable instructions, further operative to: order the display of the applications in the application display portion based on a ranking metric. | 0.766447 |
8,484,014 | 8 | 9 | 8. A computer-readable storage medium that is not a signal containing instructions for controlling a computing device to identify documents relevant to a query, by a method comprising: receiving from a user an input query that includes a word and a part of speech, the part of speech representing a wildcard for any word that is that part of speech; identifying documents with a sentence that includes the word collocated with any word of that part of speech, the document being identified based on mappings from part of speech and word pairs to documents, the mappings generated by: identifying collocated words of sentences of the documents; and for each identified pair of collocated words of a sentence, identifying a part of speech of each word of the pair; generating a first part of speech and word pair that includes the identified part of speech of the first word and the second word and a second part of speech and word pair that includes the first word and the identified part of speech of the second word; and generating a mapping from the first part of speech and word pair and the second part of speech and word pair to the document that contains the sentence; ranking the identified documents; and displaying to the user the identified documents in order of their rankings. | 8. A computer-readable storage medium that is not a signal containing instructions for controlling a computing device to identify documents relevant to a query, by a method comprising: receiving from a user an input query that includes a word and a part of speech, the part of speech representing a wildcard for any word that is that part of speech; identifying documents with a sentence that includes the word collocated with any word of that part of speech, the document being identified based on mappings from part of speech and word pairs to documents, the mappings generated by: identifying collocated words of sentences of the documents; and for each identified pair of collocated words of a sentence, identifying a part of speech of each word of the pair; generating a first part of speech and word pair that includes the identified part of speech of the first word and the second word and a second part of speech and word pair that includes the first word and the identified part of speech of the second word; and generating a mapping from the first part of speech and word pair and the second part of speech and word pair to the document that contains the sentence; ranking the identified documents; and displaying to the user the identified documents in order of their rankings. 9. The computer-readable storage medium of claim 8 wherein the documents are web pages identified by crawling web sites. | 0.5 |
8,775,161 | 3 | 34 | 3. The method of claim 1 further comprising: the processor receiving source data relating to a subject; and the processor computing a plurality of derived features based at least in part on the received source data; wherein the data processed by the processing step comprises the source data and the derived features; and wherein the generating step comprises the processor generating an evaluation indicator indicative of whether a narrative story relating to the processed data that incorporates a story angle of the angle set data structure whose applicability conditions were satisfied by the processed data is to be generated. | 3. The method of claim 1 further comprising: the processor receiving source data relating to a subject; and the processor computing a plurality of derived features based at least in part on the received source data; wherein the data processed by the processing step comprises the source data and the derived features; and wherein the generating step comprises the processor generating an evaluation indicator indicative of whether a narrative story relating to the processed data that incorporates a story angle of the angle set data structure whose applicability conditions were satisfied by the processed data is to be generated. 34. The method of claim 3 wherein the processor comprises a first processor and a second processor, the first processor performing the receiving step, the derived features computing step, the processing step, and the generating step, the method further comprising: the first processor communicating the evaluation indicator to the second processor; the second processor automatically generating a narrative story in response to the communicated evaluation indicator indicating that the narrative story is to be generated. | 0.703303 |
8,527,874 | 14 | 15 | 14. The system of claim 11 , wherein the graphical user interface organizes the one or more additional tiles in a predetermined arrangement providing one or more icons that illustrate the second object type for the one or more other objects, one or more titles that include descriptive content for the one or more other objects, one or more dates when the one or more other objects were created, and one or more available actions for interacting with the one or more other objects. | 14. The system of claim 11 , wherein the graphical user interface organizes the one or more additional tiles in a predetermined arrangement providing one or more icons that illustrate the second object type for the one or more other objects, one or more titles that include descriptive content for the one or more other objects, one or more dates when the one or more other objects were created, and one or more available actions for interacting with the one or more other objects. 15. The system of claim 14 , wherein the one or more available actions for interacting with the one or more other objects include one or more hyperlinks that initiate the one or more available actions for interacting with the one or more other objects. | 0.5 |
8,548,983 | 17 | 19 | 17. A method comprising: transforming a first query, comprising a first lateral view that includes a first predicate that references a database object that is joined with the first lateral view, to a second query that includes: a second view without the first predicate that references the database object, wherein the database object is joined with the second view, and a second predicate outside the second view, wherein the second predicate corresponds to the first predicate, wherein the second predicate references the second view, and wherein the second query is semantically equivalent to the first query; generating an execution plan for executing the second query instead of the first query; wherein the method is performed by one or more computing devices. | 17. A method comprising: transforming a first query, comprising a first lateral view that includes a first predicate that references a database object that is joined with the first lateral view, to a second query that includes: a second view without the first predicate that references the database object, wherein the database object is joined with the second view, and a second predicate outside the second view, wherein the second predicate corresponds to the first predicate, wherein the second predicate references the second view, and wherein the second query is semantically equivalent to the first query; generating an execution plan for executing the second query instead of the first query; wherein the method is performed by one or more computing devices. 19. The method of claim 17 , wherein the second predicate references both the database object and the second view. | 0.886905 |
6,056,549 | 4 | 5 | 4. A communication aid as recited in claim 3 wherein said code means is additionally formed on said plurality of demonstration pieces for identifying each of said number of subject-related demonstration pieces as being representative of one of said plurality of categories. | 4. A communication aid as recited in claim 3 wherein said code means is additionally formed on said plurality of demonstration pieces for identifying each of said number of subject-related demonstration pieces as being representative of one of said plurality of categories. 5. A communication aid as recited in claim 4 wherein said plurality of support structures and said number of subject-related demonstration pieces have equivalent code means formed thereon which are representative of a common one of said plurality of categories. | 0.5 |
9,630,109 | 1 | 2 | 1. A computer-implemented method comprising: causing a context engine comprising an in-memory database engine to collect data from a first source comprising a first gamification platform regarding a first event comprising an action taken in an enterprise by an actor; causing the context engine to collect first context data over an asynchronous message broker from a second source comprising a machine-to-machine stack including a hygroscopic sensor from a wearable of the actor; causing the context engine to collect second context data over the asynchronous message broker from a third source comprising a second gamification platform regarding a second event involving the actor; causing the context engine to perform a first aggregation of the first context data from the second source, and then to perform a second aggregation to process the data and aggregated first context data to create context enriched data by calculating a defined trust metric from the data and the second context data; causing the context engine to store the context enriched data in an in-memory database; causing the context engine to provide the context enriched data in a view within the in-memory database; determining from the context enriched data that the actor has achieved a predetermined goal; based upon achievement of the predetermined goal, triggering the asynchronous message broker to communicate a message to assign an additional role to the actor. | 1. A computer-implemented method comprising: causing a context engine comprising an in-memory database engine to collect data from a first source comprising a first gamification platform regarding a first event comprising an action taken in an enterprise by an actor; causing the context engine to collect first context data over an asynchronous message broker from a second source comprising a machine-to-machine stack including a hygroscopic sensor from a wearable of the actor; causing the context engine to collect second context data over the asynchronous message broker from a third source comprising a second gamification platform regarding a second event involving the actor; causing the context engine to perform a first aggregation of the first context data from the second source, and then to perform a second aggregation to process the data and aggregated first context data to create context enriched data by calculating a defined trust metric from the data and the second context data; causing the context engine to store the context enriched data in an in-memory database; causing the context engine to provide the context enriched data in a view within the in-memory database; determining from the context enriched data that the actor has achieved a predetermined goal; based upon achievement of the predetermined goal, triggering the asynchronous message broker to communicate a message to assign an additional role to the actor. 2. The method of claim 1 further comprising causing the context engine to send the context enriched data to the first gamification platform. | 0.796512 |
8,438,007 | 1 | 2 | 1. A computer implemented method for creating a glossary database, the method comprising: extracting, using a processor, a plurality of user interface strings in at least a first and a second human language from at least one software product having a user interface for at least the first human language and the second human language, where each user interface string is a string displayed in a user interface of the software product; creating a set identifier for each user interface string, wherein the set identifier for a user interface string comprises context information about a use of the user interface string in a user interface of the software product including a name of the software product and an identifier specifying a type of user interface string; grouping user interface strings in the first human language and the second human language having the same set identifier into string sets; generating the glossary database comprising the user interface strings in at least the first and second human languages grouped into string sets by the set identifiers; searching for one or more literal user interface strings in the glossary database that matches a selected user interface string; generating a score for each matching user interface string based on a comparison of (i) context information about a previous use of the matching user interface string with (ii) context information about a previous use of the selected user interface string; and deciding, based on the score and using a processor, whether or not to select a string set. | 1. A computer implemented method for creating a glossary database, the method comprising: extracting, using a processor, a plurality of user interface strings in at least a first and a second human language from at least one software product having a user interface for at least the first human language and the second human language, where each user interface string is a string displayed in a user interface of the software product; creating a set identifier for each user interface string, wherein the set identifier for a user interface string comprises context information about a use of the user interface string in a user interface of the software product including a name of the software product and an identifier specifying a type of user interface string; grouping user interface strings in the first human language and the second human language having the same set identifier into string sets; generating the glossary database comprising the user interface strings in at least the first and second human languages grouped into string sets by the set identifiers; searching for one or more literal user interface strings in the glossary database that matches a selected user interface string; generating a score for each matching user interface string based on a comparison of (i) context information about a previous use of the matching user interface string with (ii) context information about a previous use of the selected user interface string; and deciding, based on the score and using a processor, whether or not to select a string set. 2. The method of claim 1 , further comprising: excluding user interface strings that are not of a specified type or that exceed a specified maximum number of words. | 0.924424 |
7,676,501 | 1 | 11 | 1. A computer-implemented document integrity verification method comprising: receiving an image format document into a computer readable medium, wherein the image format document represents a printed document containing a first original integrity verification code (IVC); generating a first verification data sequence from the image format document from a section of the document that excludes the first original IVC, wherein generating a first verification data sequence comprises performing an optical character recognition (OCR) process on the image format document; generating a first modified verification data sequence from the first verification data sequence in accordance with a set of modification rules, wherein at least one element of the first verification data sequence, between the first and final elements of the first verification data sequence, is modified in the first modified verification data sequence; generating a first verification IVC, wherein generating a first verification IVC comprises performing a one-way operation on the first modified verification data sequence, and wherein the modification rules render tampering undetectable, by a comparison of the first verification IVC with the first original IVC, for at least one element within the first verification data sequence; comparing the first verification IVC with the first original IVC; and reporting an indication of tampering to the printed document, responsive to the comparison of the first verification IVC with the first original IVC. | 1. A computer-implemented document integrity verification method comprising: receiving an image format document into a computer readable medium, wherein the image format document represents a printed document containing a first original integrity verification code (IVC); generating a first verification data sequence from the image format document from a section of the document that excludes the first original IVC, wherein generating a first verification data sequence comprises performing an optical character recognition (OCR) process on the image format document; generating a first modified verification data sequence from the first verification data sequence in accordance with a set of modification rules, wherein at least one element of the first verification data sequence, between the first and final elements of the first verification data sequence, is modified in the first modified verification data sequence; generating a first verification IVC, wherein generating a first verification IVC comprises performing a one-way operation on the first modified verification data sequence, and wherein the modification rules render tampering undetectable, by a comparison of the first verification IVC with the first original IVC, for at least one element within the first verification data sequence; comparing the first verification IVC with the first original IVC; and reporting an indication of tampering to the printed document, responsive to the comparison of the first verification IVC with the first original IVC. 11. The method of claim 1 wherein the modified element comprises a displacement element. | 0.957282 |
7,860,899 | 12 | 13 | 12. The method of claim 11 , further including the step of: based on determining a database representation for the XML datatype, generating Data Description Language (DDL) code to execute to create one or more indexes for the one or more base structures. | 12. The method of claim 11 , further including the step of: based on determining a database representation for the XML datatype, generating Data Description Language (DDL) code to execute to create one or more indexes for the one or more base structures. 13. The method of claim 12 , further comprising: generating comments for the DDL code to execute to create one or more indexes for the base structures, wherein the comments include a reason why the database representation was determined. | 0.5 |
8,435,038 | 51 | 52 | 51. The non-transitory computer-readable medium of claim 30 , further comprising program code for causing a computer to perform a method comprising: allowing the teacher to store one or more of the video feeds. | 51. The non-transitory computer-readable medium of claim 30 , further comprising program code for causing a computer to perform a method comprising: allowing the teacher to store one or more of the video feeds. 52. The non-transitory computer-readable medium of claim 51 , further comprising program code for causing a computer to perform a method comprising: allowing the teacher to selectively transmit one or more of the stored video feeds to one or more of the learners for display on display screens at the respective learners' locations. | 0.5 |
8,909,627 | 1 | 2 | 1. A computer-implemented method comprising: determining, using data associated with search queries submitted by past users of a search engine, that a particular search result selected by a particular, past user of the search engine includes a query term included in an initial search query, and a particular synonym that was generated for the query term included in the initial search query using a particular synonym rule, wherein the data associated with the search queries indicates that the particular search result was selected by the particular, past user of the search engine from among multiple search results that were generated by the search engine using the initial search query and one or more revised search queries that include the particular synonym for the query term; determining, using the data associated with the search queries, that a different search result that also includes the particular synonym for the query term was ranked above the particular search result and was not selected by the particular, past user of the search engine; in response to determining that (i) the particular search result selected by the particular, past user of the search engine includes the query term included in the initial search query, and the particular synonym for the query term, and (ii) the different search result that also includes the particular synonym for the query term was ranked above the particular search result and was not selected by the particular, past user of the search engine, incrementing a particular type of skip count for the particular synonym rule; and determining whether to revise a subsequently received search query that includes the query term included in the initial search query, to include the particular synonym for the query term, based at least on the particular type of skip count for the particular synonym rule. | 1. A computer-implemented method comprising: determining, using data associated with search queries submitted by past users of a search engine, that a particular search result selected by a particular, past user of the search engine includes a query term included in an initial search query, and a particular synonym that was generated for the query term included in the initial search query using a particular synonym rule, wherein the data associated with the search queries indicates that the particular search result was selected by the particular, past user of the search engine from among multiple search results that were generated by the search engine using the initial search query and one or more revised search queries that include the particular synonym for the query term; determining, using the data associated with the search queries, that a different search result that also includes the particular synonym for the query term was ranked above the particular search result and was not selected by the particular, past user of the search engine; in response to determining that (i) the particular search result selected by the particular, past user of the search engine includes the query term included in the initial search query, and the particular synonym for the query term, and (ii) the different search result that also includes the particular synonym for the query term was ranked above the particular search result and was not selected by the particular, past user of the search engine, incrementing a particular type of skip count for the particular synonym rule; and determining whether to revise a subsequently received search query that includes the query term included in the initial search query, to include the particular synonym for the query term, based at least on the particular type of skip count for the particular synonym rule. 2. The method of claim 1 , comprising assigning a score to the particular synonym rule based at least in part on the particular type of skip count for the particular synonym rule. | 0.805857 |
8,090,678 | 1 | 4 | 1. A computer-implemented method of extracting information from co-occurring Hyper Text Mark-up Language (HTML) structured documents, the method comprising: presenting a list of web sites to a user; receiving one or more of the web sites selected from the user for data extraction; collecting a plurality of co-occurring different HTML structured documents for each of the selected web sites at a computer comprising a processor; forming a plurality of clusters comprising different subsets of the co-occurring HTML structured documents, wherein: each cluster comprises a different HTML structured document of the plurality of co-occurring HTML structured documents as a centroid document and other HTML structured documents of the plurality of co-occurring HTML structured documents that achieve a threshold of similarity with respect to the centroid document, the clusters are formed by comparing each co-occurring HTML structured document to each centroid document of each cluster based on relative structural similarity of HTML data structure of each co-occurring HTML structured document with respect to HTML data structure of each centroid document of each cluster, an alignment algorithm is used to determine the co-occurring HTML structured documents that achieve the threshold of similarity with respect to each centroid document by comparing structured locations of data fields for storing data elements within each centroid document and structured locations of corresponding data fields for storing data elements within each of the co-occurring HTML structured documents, the co-occurring HTML structured documents are compared to each centroid document based on similarity of structured locations of corresponding data fields within the HTML data structures without regard to content of data elements stored in the corresponding data fields within the HTML data structures, and the relative structural similarity of a particular co-occurring HTML structured document with respect to a particular centroid document is penalized when the co-occurring HTML structured document includes a data field that is within the particular centroid document in a different structured location; displaying a list of clusters; displaying the centroid document of a particular cluster selected from the list of clusters; marking a data element on the centroid document of the particular cluster; identifying a data element on each of the other HTML structured documents of the particular cluster that is stored within a data field having a structured location that corresponds to the structured location of the data field storing the marked data element within the centroid document of the particular cluster; and providing a user interface displaying content of data elements identified from the other HTML structured documents of the particular cluster on a computer display. | 1. A computer-implemented method of extracting information from co-occurring Hyper Text Mark-up Language (HTML) structured documents, the method comprising: presenting a list of web sites to a user; receiving one or more of the web sites selected from the user for data extraction; collecting a plurality of co-occurring different HTML structured documents for each of the selected web sites at a computer comprising a processor; forming a plurality of clusters comprising different subsets of the co-occurring HTML structured documents, wherein: each cluster comprises a different HTML structured document of the plurality of co-occurring HTML structured documents as a centroid document and other HTML structured documents of the plurality of co-occurring HTML structured documents that achieve a threshold of similarity with respect to the centroid document, the clusters are formed by comparing each co-occurring HTML structured document to each centroid document of each cluster based on relative structural similarity of HTML data structure of each co-occurring HTML structured document with respect to HTML data structure of each centroid document of each cluster, an alignment algorithm is used to determine the co-occurring HTML structured documents that achieve the threshold of similarity with respect to each centroid document by comparing structured locations of data fields for storing data elements within each centroid document and structured locations of corresponding data fields for storing data elements within each of the co-occurring HTML structured documents, the co-occurring HTML structured documents are compared to each centroid document based on similarity of structured locations of corresponding data fields within the HTML data structures without regard to content of data elements stored in the corresponding data fields within the HTML data structures, and the relative structural similarity of a particular co-occurring HTML structured document with respect to a particular centroid document is penalized when the co-occurring HTML structured document includes a data field that is within the particular centroid document in a different structured location; displaying a list of clusters; displaying the centroid document of a particular cluster selected from the list of clusters; marking a data element on the centroid document of the particular cluster; identifying a data element on each of the other HTML structured documents of the particular cluster that is stored within a data field having a structured location that corresponds to the structured location of the data field storing the marked data element within the centroid document of the particular cluster; and providing a user interface displaying content of data elements identified from the other HTML structured documents of the particular cluster on a computer display. 4. The method of claim 1 , further comprising automatically marking the data element on the centroid document of the particular cluster. | 0.910878 |
8,838,692 | 16 | 17 | 16. The network of claim 1 , wherein the plurality of XML appliances/routers in the at least one distribution ring loop are configured to check if each received XML message is a duplicate XML message. | 16. The network of claim 1 , wherein the plurality of XML appliances/routers in the at least one distribution ring loop are configured to check if each received XML message is a duplicate XML message. 17. The network of claim 16 , wherein the plurality of XML appliances/routers in the at least one distribution ring are configured to not forward XML messages determined to be duplicate XML messages. | 0.5 |
5,404,514 | 1 | 2 | 1. A method of indexing and retrieving documents, said method using a digital computer system having a central processing unit, a memory, a display screen, a keyboard, and a large capacity file system, said method comprising the steps of: (a) storing in said memory a vocabulary of terms, each term consisting of one or more words, and for each term an associated term-code; (b) storing on said file system a collection of documents each with an associated unique document-number; (c) creating index files which contain for each said term-code in (a) (i) the set of document-numbers in (b) such that the corresponding documents contain the corresponding term; and (ii) for each said document-identifying-number in (i) the frequency-in-document of the corresponding term which is the number of times that said term appears in the corresponding document; (d) creating a weight-in-document file which contains for each document-number in (c)(i) the weight-in-document of the corresponding term which is calculated using the frequency-in-document in (c) (ii), the number of document-numbers in (c) (i), and the total number of terms in (a) which are in the corresponding document (counted multiple times); (e) creating a frequent-companion file which contains for each occurring term-code in (a) a ranked set of pairs of numbers where each pair consists of a first element term-code and a second element companion-percentage, where the companion-percentage is calculated by summing the weight-in-document values of said first element term-code over documents that contain both the term corresponding to said first element term-code and the term corresponding to said occurring term-code and then dividing by the sum over all documents of the weight-in-document of said occurring term-code; (f) creating a relative file which contains for each occurring term-code in (a) a ranked set of pairs of numbers where each pair consists of a first element relative term-code and a second element relative-percentage, where the relative-percentage is calculated by taking a weighted average of the companion-percentage of said first element term-code calculated in step (e) and the companion-percentage of said occurring term-code that was calculated in step (e) when said first element term-code was the occurring term-code and said occurring term-code was the first element term-code; (g) creating a polysemantic file which contains for each occurring term-code in (a), a polysemantic weight which is calculated using the number of sets of pairs in the relative file created in step (f) that said occurring term-code appears in, the number of documents-numbers for which the weight-in-document of said occurring term-code calculated in step (d) is greater than some threshold value, and the averages for several values of N of the first N relative-percentages of said occurring term-code calculated and ranked in step (f); (h) accepting a query consisting of a sequence of words entered by a user using said keyboard and creating a parsed-query table of term-codes which consist of the term-codes in said vocabulary that are associated with the terms that are contained in said query; (i) creating a temporary swap table of pairs of first element term-codes and corresponding second element summed-relative-percentages consisting of those relative term-codes created in step (f) where said corresponding second element summed-relative-percentages are the sum, over all said occurring term-codes that are in said parsed-query table, of the relative percentages of said first element term-codes; (j) creating a modified swap table by modifying said second element summed-relative-percentages created in step (i) by multiplying them by a function of the polysemantic weight of the corresponding first element term-codes; (k) sorting said modified swap table by said modified summed-relative-percentages in descending order; (l) displaying on said display the terms corresponding to the term-codes of said modified swap table; (m) accepting user keypresses or other actions which identify one or more of the terms displayed in step (l) and adding the corresponding term-codes to the parsed-query-table; (n) repeating steps (i) through (m) as many times as the user indicates by his input; (o) accepting an input from the user indicating a command to retrieve documents; (p) creating a temporary rank table of pairs of first element document-numbers and corresponding second element summed-document-weight.times.poly values which pairs comprise those document-numbers for which any of the term-codes that are in said parsed-query table have weight-in-document above a threshold value, and summed-document-weight.times.poly values which are the sums, over all term-codes in said parsed-query table, of a function of me polysemantic weight of the term-code and the weight-in-document of the term-code; (r) creating a sorted rank table by sorting said temporary rank table by the value of the second elements of the pairs in descending order; (s) displaying on the display screen some portion of the document corresponding to the first document number in the sorted rank table and some indication of the corresponding summed-document-weight.times.poly value; (t) displaying other documents corresponding to other document-numbers in the sorted rank table in response to inputs from the user. | 1. A method of indexing and retrieving documents, said method using a digital computer system having a central processing unit, a memory, a display screen, a keyboard, and a large capacity file system, said method comprising the steps of: (a) storing in said memory a vocabulary of terms, each term consisting of one or more words, and for each term an associated term-code; (b) storing on said file system a collection of documents each with an associated unique document-number; (c) creating index files which contain for each said term-code in (a) (i) the set of document-numbers in (b) such that the corresponding documents contain the corresponding term; and (ii) for each said document-identifying-number in (i) the frequency-in-document of the corresponding term which is the number of times that said term appears in the corresponding document; (d) creating a weight-in-document file which contains for each document-number in (c)(i) the weight-in-document of the corresponding term which is calculated using the frequency-in-document in (c) (ii), the number of document-numbers in (c) (i), and the total number of terms in (a) which are in the corresponding document (counted multiple times); (e) creating a frequent-companion file which contains for each occurring term-code in (a) a ranked set of pairs of numbers where each pair consists of a first element term-code and a second element companion-percentage, where the companion-percentage is calculated by summing the weight-in-document values of said first element term-code over documents that contain both the term corresponding to said first element term-code and the term corresponding to said occurring term-code and then dividing by the sum over all documents of the weight-in-document of said occurring term-code; (f) creating a relative file which contains for each occurring term-code in (a) a ranked set of pairs of numbers where each pair consists of a first element relative term-code and a second element relative-percentage, where the relative-percentage is calculated by taking a weighted average of the companion-percentage of said first element term-code calculated in step (e) and the companion-percentage of said occurring term-code that was calculated in step (e) when said first element term-code was the occurring term-code and said occurring term-code was the first element term-code; (g) creating a polysemantic file which contains for each occurring term-code in (a), a polysemantic weight which is calculated using the number of sets of pairs in the relative file created in step (f) that said occurring term-code appears in, the number of documents-numbers for which the weight-in-document of said occurring term-code calculated in step (d) is greater than some threshold value, and the averages for several values of N of the first N relative-percentages of said occurring term-code calculated and ranked in step (f); (h) accepting a query consisting of a sequence of words entered by a user using said keyboard and creating a parsed-query table of term-codes which consist of the term-codes in said vocabulary that are associated with the terms that are contained in said query; (i) creating a temporary swap table of pairs of first element term-codes and corresponding second element summed-relative-percentages consisting of those relative term-codes created in step (f) where said corresponding second element summed-relative-percentages are the sum, over all said occurring term-codes that are in said parsed-query table, of the relative percentages of said first element term-codes; (j) creating a modified swap table by modifying said second element summed-relative-percentages created in step (i) by multiplying them by a function of the polysemantic weight of the corresponding first element term-codes; (k) sorting said modified swap table by said modified summed-relative-percentages in descending order; (l) displaying on said display the terms corresponding to the term-codes of said modified swap table; (m) accepting user keypresses or other actions which identify one or more of the terms displayed in step (l) and adding the corresponding term-codes to the parsed-query-table; (n) repeating steps (i) through (m) as many times as the user indicates by his input; (o) accepting an input from the user indicating a command to retrieve documents; (p) creating a temporary rank table of pairs of first element document-numbers and corresponding second element summed-document-weight.times.poly values which pairs comprise those document-numbers for which any of the term-codes that are in said parsed-query table have weight-in-document above a threshold value, and summed-document-weight.times.poly values which are the sums, over all term-codes in said parsed-query table, of a function of me polysemantic weight of the term-code and the weight-in-document of the term-code; (r) creating a sorted rank table by sorting said temporary rank table by the value of the second elements of the pairs in descending order; (s) displaying on the display screen some portion of the document corresponding to the first document number in the sorted rank table and some indication of the corresponding summed-document-weight.times.poly value; (t) displaying other documents corresponding to other document-numbers in the sorted rank table in response to inputs from the user. 2. A method as in claim 1 wherein additional steps (j)(l) and (p)(l) are carried out after steps (j) and (p) respectively to implement the soft boolean connector algorithm which consists of the following steps: (A) creating a table of relative penalties for each pair of said term-codes in said parsed-query table where said relative penalty is a function of the relative percentage corresponding to the two term-codes of said pair, the number of documents that each of the term-codes of the pair are contained in with a document-weight above a threshold, and the average over all terms of the number of documents that the term is contained in with a document-weight above said threshold; (B) modifying said relative penalties by taking the minimum of the relative penalty and some maximum value which depends on the number of terms in the parsed-query table; (C) summing said modified relative penalties to produce a sum of relative penalties; (D) modifying said sum of relative penalties by taking the minimum of said sum and some maximum sum value which depends on the number of terms in the parsed-query table to produce a modified sum of penalties; (E) summing some function of the polysemantic weights of the term-codes in the parsed-query table that are either relatives of a potential SWAPS term (jl) or are contained in a document (pl) to produce a number of hits value; (F) Calculating some function of the number of hits value and the modified sum of penalties value to produce a power value; (G) Raising a number approximately equal to 2 to the power value to produce an adjust value; (H) Multiplying either the modified summed relative percentages calculated in step j) or the summed document weight.times.poly values calculated in step (p) by the adjust value. | 0.5 |
8,260,729 | 8 | 15 | 8. The system of claim 1 , wherein said subjective user state data solicitation module configured to solicit subjective user state data including data indicating occurrence of at least one subjective user state associated with a user in response to the acquisition of the objective occurrence data comprises: a subjective user state data solicitation module configured to solicit the data indicating occurrence of at least one subjective user state associated with a user from the user. | 8. The system of claim 1 , wherein said subjective user state data solicitation module configured to solicit subjective user state data including data indicating occurrence of at least one subjective user state associated with a user in response to the acquisition of the objective occurrence data comprises: a subjective user state data solicitation module configured to solicit the data indicating occurrence of at least one subjective user state associated with a user from the user. 15. The system of claim 8 , wherein said subjective user state data solicitation module configured to solicit the data indicating occurrence of at least one subjective user state associated with a user from the user comprises: a requesting module configured to request for an indication of occurrence of at least one subjective user state with respect to occurrence of the at least one objective occurrence. | 0.5 |
8,682,640 | 17 | 18 | 17. The computer program product of claim 16 further comprising: instructions for determining a location of the device; instructions for determining whether the particular language is a default language, in response to identifying the particular language of the oral statement; instructions for determining a translation language of the device based on the location of the device and providing the translation of the oral statement in the translation language of the device, in response to determining that the particular language is the default language; and instructions for providing the translation of the oral statement in the default language, in response to determining that the particular language is not the default language. | 17. The computer program product of claim 16 further comprising: instructions for determining a location of the device; instructions for determining whether the particular language is a default language, in response to identifying the particular language of the oral statement; instructions for determining a translation language of the device based on the location of the device and providing the translation of the oral statement in the translation language of the device, in response to determining that the particular language is the default language; and instructions for providing the translation of the oral statement in the default language, in response to determining that the particular language is not the default language. 18. The computer program product of claim 17 further comprising: instructions for determining whether the particular language is one of the default language and the translation language of the device, in response to identifying the particular language of the oral statement; instructions for requesting an input to update the translation language of the device with the particular language, in response to determining that the particular language is not one of the default language and the translation language of the device; and instructions for updating the translation language of the device with the particular language, in response to receiving the input. | 0.601449 |
9,342,608 | 1 | 4 | 1. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive an input question for generation of an answer to the input question; generate a set of candidate answers for the input question based on an analysis of a corpus of information, wherein each candidate answer in the set of candidate answers corresponds to an evidence passage supporting the candidate answer as answering the input question; determine, based on the set of candidate answers, whether clarification of the input question is required; identify, in response to a determination that clarification of the input question is required, a differentiating factor in evidence passages of at least two candidate answers in the set of candidate answers; send, by the data processing system, in response to a determination that clarification of the input question is required, a request for user input to clarify the input question, wherein the request for user input is generated based on the identified differentiating factor; receive user input from the computing device in response to the request; and select at least one candidate answer in the set of candidate answers as an answer for the input question based on the user input, wherein identifying a differentiating factor in evidence passages of at least two candidate answers in the set of candidate answers comprises: identifying a plurality of differentiating factors between evidence passages of the at least two candidate answers; and selecting a subset of differentiating factors from the plurality of differentiating factors based on an evaluation of which differentiating factors in the plurality of differentiating factors clarify the input question. | 1. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive an input question for generation of an answer to the input question; generate a set of candidate answers for the input question based on an analysis of a corpus of information, wherein each candidate answer in the set of candidate answers corresponds to an evidence passage supporting the candidate answer as answering the input question; determine, based on the set of candidate answers, whether clarification of the input question is required; identify, in response to a determination that clarification of the input question is required, a differentiating factor in evidence passages of at least two candidate answers in the set of candidate answers; send, by the data processing system, in response to a determination that clarification of the input question is required, a request for user input to clarify the input question, wherein the request for user input is generated based on the identified differentiating factor; receive user input from the computing device in response to the request; and select at least one candidate answer in the set of candidate answers as an answer for the input question based on the user input, wherein identifying a differentiating factor in evidence passages of at least two candidate answers in the set of candidate answers comprises: identifying a plurality of differentiating factors between evidence passages of the at least two candidate answers; and selecting a subset of differentiating factors from the plurality of differentiating factors based on an evaluation of which differentiating factors in the plurality of differentiating factors clarify the input question. 4. The computer program product of claim 1 , wherein the request for user input comprises a clarification question that is directed to the differentiating factor and a free-form text entry field into which a user may input a textual answer to the clarification question. | 0.703297 |
7,783,474 | 10 | 12 | 10. A computer system comprising: a tokenizer that parses a phrase to be added to a language model into a plurality of tokens including a first token; and a computer code mechanism that: generates a phrase pronunciation for the phrase comprising a token pronunciation for the first token in the phrase, wherein generating the phrase pronunciation for the phrase comprises determining if the first token is represented in a pron component list, and, if so, selecting as the token pronunciation for the first token in the phrase a component pronunciation from the pron component list, wherein the pron component list comprises a list of one or more component pronunciations for at least the first token as pronounced in one or more phrases, wherein the list of one or more component pronunciations is different from any list of one or more language model pronunciations in the language model for the first token; and adds the phrase pronunciation for the phrase to the language model; wherein the computer code mechanism generates the phrase pronunciation for the phrase at least in party by, if the first token is not represented in the pron component list, determining if the first token is represented in the language model, and, if so, selecting a language model pronunciation from the language model as the token pronunciation for the first token in the phrase; and wherein the tokenizer and/or the computer code mechanism is implemented by a computer. | 10. A computer system comprising: a tokenizer that parses a phrase to be added to a language model into a plurality of tokens including a first token; and a computer code mechanism that: generates a phrase pronunciation for the phrase comprising a token pronunciation for the first token in the phrase, wherein generating the phrase pronunciation for the phrase comprises determining if the first token is represented in a pron component list, and, if so, selecting as the token pronunciation for the first token in the phrase a component pronunciation from the pron component list, wherein the pron component list comprises a list of one or more component pronunciations for at least the first token as pronounced in one or more phrases, wherein the list of one or more component pronunciations is different from any list of one or more language model pronunciations in the language model for the first token; and adds the phrase pronunciation for the phrase to the language model; wherein the computer code mechanism generates the phrase pronunciation for the phrase at least in party by, if the first token is not represented in the pron component list, determining if the first token is represented in the language model, and, if so, selecting a language model pronunciation from the language model as the token pronunciation for the first token in the phrase; and wherein the tokenizer and/or the computer code mechanism is implemented by a computer. 12. The computer system of claim 10 , wherein the computer code mechanism selects the pron component list from a plurality of lists in accordance with the position of the first token within the phrase. | 0.754279 |
9,372,864 | 1 | 8 | 1. A method comprising: creating, by an online collaboration service executing on a computer system, an online session to share an online binder associated with a presenter between the presenter and one or more participants, the online binder including a plurality of pages representing a plurality of data files associated with the online binder, the data files being of multiple formats and the pages being in a common format; receiving, at the online collaboration service and during the online session, collaboration data from the presenter in real-time, the collaboration data including (a) a page of the online binder displayed on a first device of the presenter and (b) user actions of the presenter that are associated with the page; presenting, during the online session and in real-time, the collaboration data on a second device of the one or more participants, the online binder being agnostic to a platform of the first device or the second device; recording, at the online collaboration service, the online session between the presenter and the one or more participants; and storing, at the online collaboration service, the recording of the online session as a new page of the online binder associated with the presenter. | 1. A method comprising: creating, by an online collaboration service executing on a computer system, an online session to share an online binder associated with a presenter between the presenter and one or more participants, the online binder including a plurality of pages representing a plurality of data files associated with the online binder, the data files being of multiple formats and the pages being in a common format; receiving, at the online collaboration service and during the online session, collaboration data from the presenter in real-time, the collaboration data including (a) a page of the online binder displayed on a first device of the presenter and (b) user actions of the presenter that are associated with the page; presenting, during the online session and in real-time, the collaboration data on a second device of the one or more participants, the online binder being agnostic to a platform of the first device or the second device; recording, at the online collaboration service, the online session between the presenter and the one or more participants; and storing, at the online collaboration service, the recording of the online session as a new page of the online binder associated with the presenter. 8. The method of claim 1 further comprising: presenting a list of online sessions in progress to the one or more participants. | 0.816327 |
10,133,455 | 1 | 3 | 1. A method for collaboratively preparing and presenting a presentation, said method comprising: configuring a computer for use by a control operator to view and manage proposed synchronous contributions by on-line contributors to a presentation script and for saving the presentation script being prepared; structuring the presentation script as a series of segments, each of which segments includes one or more elements; accessing at least one of the elements remotely through the Internet; saving the presentation script on the computer responsive to an interaction with the control operator; and after preparing and saving the presentation script, presenting at least portions of the saved scripted presentation to a presentation audience. | 1. A method for collaboratively preparing and presenting a presentation, said method comprising: configuring a computer for use by a control operator to view and manage proposed synchronous contributions by on-line contributors to a presentation script and for saving the presentation script being prepared; structuring the presentation script as a series of segments, each of which segments includes one or more elements; accessing at least one of the elements remotely through the Internet; saving the presentation script on the computer responsive to an interaction with the control operator; and after preparing and saving the presentation script, presenting at least portions of the saved scripted presentation to a presentation audience. 3. The method of claim 1 wherein saving saves the multimedia script on an Internet hard drive. | 0.830325 |
9,767,096 | 12 | 15 | 12. A tangible, non-transitory, computer readable medium storing executable instructions configured to: non-destructively test an item; present a first text in a first language on an operations object via a display during a sensing operation of a portable non-destructive testing (NDT) device; create a second text in a second language via a user interface of the mobile device; present the second text via the operations object on the display as an alternative to the first text during the sensing operation of the portable non-destructive testing (NDT) device; present a first multimedia in the first language during the operation of the portable NDT device; create a second multimedia in the second language as an alternative to the first multimedia during an operation of the NDT device; and transmit the second multimedia from the portable NDT device to a second portable NDT device via a communications system. | 12. A tangible, non-transitory, computer readable medium storing executable instructions configured to: non-destructively test an item; present a first text in a first language on an operations object via a display during a sensing operation of a portable non-destructive testing (NDT) device; create a second text in a second language via a user interface of the mobile device; present the second text via the operations object on the display as an alternative to the first text during the sensing operation of the portable non-destructive testing (NDT) device; present a first multimedia in the first language during the operation of the portable NDT device; create a second multimedia in the second language as an alternative to the first multimedia during an operation of the NDT device; and transmit the second multimedia from the portable NDT device to a second portable NDT device via a communications system. 15. The computer readable medium of claim 12 , wherein the instructions comprise instructions configured to translate the first text into the second text via an internal language translation system, via an external language translation service, or a combination thereof. | 0.613181 |
8,516,606 | 22 | 23 | 22. A computer-implemented method comprising: accessing characters of a challenge phrase; determining first processing to apply to a first group of characters from the challenge phrase and second processing to apply to a second group of characters from the challenge phrase, the first group of characters and the second group of characters comprising a common character, wherein the first processing comprises obscuring a first part of the common character and the second processing comprises obscuring a second part of the common character, the second part of the common character being different than the first part of the common character; generating, using a computer processor, a first image comprising the first group of characters using the first processing; generating, using the computer processor, a second image comprising the second group of characters using the second processing; and providing the first image and the second image for use in a challenge-response test to control access to protected content. | 22. A computer-implemented method comprising: accessing characters of a challenge phrase; determining first processing to apply to a first group of characters from the challenge phrase and second processing to apply to a second group of characters from the challenge phrase, the first group of characters and the second group of characters comprising a common character, wherein the first processing comprises obscuring a first part of the common character and the second processing comprises obscuring a second part of the common character, the second part of the common character being different than the first part of the common character; generating, using a computer processor, a first image comprising the first group of characters using the first processing; generating, using the computer processor, a second image comprising the second group of characters using the second processing; and providing the first image and the second image for use in a challenge-response test to control access to protected content. 23. The computer-implemented method according to claim 22 , wherein the second processing further comprises leaving the first part of the character unobscured. | 0.5 |
9,495,977 | 8 | 12 | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: generating text based on speech received from a user; identifying a key phrase in the text based on an emotion of the user; receiving data from a user profile, the data comprising information describing usage habits of the user; and selecting an advertisement related to the key phrase and the data. | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: generating text based on speech received from a user; identifying a key phrase in the text based on an emotion of the user; receiving data from a user profile, the data comprising information describing usage habits of the user; and selecting an advertisement related to the key phrase and the data. 12. The system of claim 8 , wherein the speech is received at a first device and the advertisement is displayed on a second device different than the first device. | 0.747678 |
7,567,711 | 1 | 5 | 1. A method in a computing device having a processor for cleaning up handwriting, the method comprising: under control of the processor: receiving handwriting of a user that has been digitized; analyzing the handwriting to identify strokes that satisfy a cleanup criterion, each stroke representing a sequence of points starting when the user places a pen tip on a writing tablet and ending when the user lift the pen tip off the writing tablet; and when strokes have been identified as satisfying the cleanup criterion, performing cleanup on the handwriting wherein a cleanup criterion includes an intra-stroke overtracing criterion indicating that when the user has traced over a portion of a stroke with another portion of the same stroke in an attempt to clarify the handwriting, the cleanup includes replacing the overtraced and overtracing portions with an averaged portion, wherein a cleanup criterion includes an inter-stroke overtracing criterion indicating that when the user has traced over one stroke with a different stroke in an attempt to clarify the handwriting, the cleanup includes replacing the overtraced and the overtracing strokes with a merged stroke that includes common overtraced parts of the strokes, wherein a cleanup criterion includes a correction criterion indicating a correction occurring when the user has overwritten one character with another character, the cleanup including replacing the overwritten character with the overwriting character, wherein a cleanup criterion includes a touch up stroke criterion indicating a stroke touch up correction occurring when the user wrote a touch up stroke to complete an existing stroke, the cleanup including merging the touch up stroke and the existing stroke, and wherein a clean up criterion includes an insertion criterion indicating an insertion correction occurring when the user wrote a character between two existing characters, the cleanup including inserting the character between the two existing characters. | 1. A method in a computing device having a processor for cleaning up handwriting, the method comprising: under control of the processor: receiving handwriting of a user that has been digitized; analyzing the handwriting to identify strokes that satisfy a cleanup criterion, each stroke representing a sequence of points starting when the user places a pen tip on a writing tablet and ending when the user lift the pen tip off the writing tablet; and when strokes have been identified as satisfying the cleanup criterion, performing cleanup on the handwriting wherein a cleanup criterion includes an intra-stroke overtracing criterion indicating that when the user has traced over a portion of a stroke with another portion of the same stroke in an attempt to clarify the handwriting, the cleanup includes replacing the overtraced and overtracing portions with an averaged portion, wherein a cleanup criterion includes an inter-stroke overtracing criterion indicating that when the user has traced over one stroke with a different stroke in an attempt to clarify the handwriting, the cleanup includes replacing the overtraced and the overtracing strokes with a merged stroke that includes common overtraced parts of the strokes, wherein a cleanup criterion includes a correction criterion indicating a correction occurring when the user has overwritten one character with another character, the cleanup including replacing the overwritten character with the overwriting character, wherein a cleanup criterion includes a touch up stroke criterion indicating a stroke touch up correction occurring when the user wrote a touch up stroke to complete an existing stroke, the cleanup including merging the touch up stroke and the existing stroke, and wherein a clean up criterion includes an insertion criterion indicating an insertion correction occurring when the user wrote a character between two existing characters, the cleanup including inserting the character between the two existing characters. 5. The method of claim 1 wherein groups of strokes are classified as a character without performing character recognition. | 0.890877 |
9,589,399 | 17 | 19 | 17. A tangible machine readable medium storing instructions that, when executed by a computing device, cause the computing device to perform a method, the method comprising: producing biometric data from a user by sensing a biometric with a biometric identification unit, and producing an image of the biometric from the biometric data, and matching the image to a stored template associated with the user; providing an authentication risk management natural identification authentication score using a biometric identification unit natural identification evaluation engine, wherein the natural identification authentication score is based on a hardware marking, a quality of the image of the biometric and a matching granularity between the image of the biometric and the stored template; generating a computed authentication score based on at least one of a PIN, a password and a token; and receiving the natural identification authentication score and the computed authentication score and providing a credentials quality assessment engine (CQAE) authentication score based on a combination of the natural identification authentication score and the computed authentication score. | 17. A tangible machine readable medium storing instructions that, when executed by a computing device, cause the computing device to perform a method, the method comprising: producing biometric data from a user by sensing a biometric with a biometric identification unit, and producing an image of the biometric from the biometric data, and matching the image to a stored template associated with the user; providing an authentication risk management natural identification authentication score using a biometric identification unit natural identification evaluation engine, wherein the natural identification authentication score is based on a hardware marking, a quality of the image of the biometric and a matching granularity between the image of the biometric and the stored template; generating a computed authentication score based on at least one of a PIN, a password and a token; and receiving the natural identification authentication score and the computed authentication score and providing a credentials quality assessment engine (CQAE) authentication score based on a combination of the natural identification authentication score and the computed authentication score. 19. The machine readable medium of claim 17 wherein the CQAE comprises at least a part of a user authentication profile engine. | 0.584967 |
9,129,279 | 18 | 21 | 18. A method for delivering financial services comprising: receiving, by a computer, a start session request from a customer through a remote device identifying a type of the remote device; instantiating, by a computer, a session bubble by instantiating one or more mini-app dialogue components, a transaction executor component, and a presentation manager component, and instantiating computer resources necessary to execute functions of the one or more mini-app dialogue components, the transaction executor component, and the presentation manager component; receiving, by a computer, a request for a financial service function through one of the one or more mini-app dialogue component from the remote device; collecting, by a computer, information through the remote device using one of the one or more mini-app dialogue components; performing, by a computer, the financial service function that was requested using the transaction executor component and generating information regarding the financial service function that was performed; selecting, by a computer, a template configured for the type of the requesting remote device; formatting, by a computer, the generated information regarding the financial service function by the presentation manager component into a screen display presentation format by mapping objects associated with the generated information using the template configured for the type of the requesting remote device; and encoding, by a computer, the screen display presentation format for display on the remote device. | 18. A method for delivering financial services comprising: receiving, by a computer, a start session request from a customer through a remote device identifying a type of the remote device; instantiating, by a computer, a session bubble by instantiating one or more mini-app dialogue components, a transaction executor component, and a presentation manager component, and instantiating computer resources necessary to execute functions of the one or more mini-app dialogue components, the transaction executor component, and the presentation manager component; receiving, by a computer, a request for a financial service function through one of the one or more mini-app dialogue component from the remote device; collecting, by a computer, information through the remote device using one of the one or more mini-app dialogue components; performing, by a computer, the financial service function that was requested using the transaction executor component and generating information regarding the financial service function that was performed; selecting, by a computer, a template configured for the type of the requesting remote device; formatting, by a computer, the generated information regarding the financial service function by the presentation manager component into a screen display presentation format by mapping objects associated with the generated information using the template configured for the type of the requesting remote device; and encoding, by a computer, the screen display presentation format for display on the remote device. 21. The method of claim 18 , further comprising: authenticating, by a computer, the customer by validating received customer authentication credential using information stored in a customer ID component. | 0.671521 |
8,996,641 | 7 | 8 | 7. A method for transmitting a marketing communication, comprising: storing, by a processor, profile data for a plurality of recipients; storing, by the processor, a template for the marketing communication, the template comprising a marketing message, the template including universal information that is transmitted to all recipients of the marketing communication, the marketing communication comprising a telephonic communication; storing, by the processor, a plurality of sets of variable information to be included in the marketing communication based on the profile data of an individual recipient of the plurality of recipients, the profile data comprising an annual income and a credit rating for each of the plurality of recipients, where each of the plurality of sets of variable information comprises information on a specific marketing offer, the specific marketing offer comprising an offer of a specific product; presenting, by the processor, an option to a human user to insert a personal message in the marketing communication for a first recipient of the plurality of recipients, wherein the personal message is personalized to the first recipient, wherein the personal message satisfies a conformance rule, wherein the personal message is certified as conforming to the conformance rule before the personal message is entered in the marketing communication, wherein the certifying conformance to the conformance rule comprises confirming from the human user that the personal message does not exceed a predetermined length before the personal message is inserted in the communication; and transmitting, by the processor, the marketing communication to the first recipient of the plurality of recipients, the marketing communication including a first set of the plurality of sets of variable information based on the profile data corresponding to the first recipient and including the personal message. | 7. A method for transmitting a marketing communication, comprising: storing, by a processor, profile data for a plurality of recipients; storing, by the processor, a template for the marketing communication, the template comprising a marketing message, the template including universal information that is transmitted to all recipients of the marketing communication, the marketing communication comprising a telephonic communication; storing, by the processor, a plurality of sets of variable information to be included in the marketing communication based on the profile data of an individual recipient of the plurality of recipients, the profile data comprising an annual income and a credit rating for each of the plurality of recipients, where each of the plurality of sets of variable information comprises information on a specific marketing offer, the specific marketing offer comprising an offer of a specific product; presenting, by the processor, an option to a human user to insert a personal message in the marketing communication for a first recipient of the plurality of recipients, wherein the personal message is personalized to the first recipient, wherein the personal message satisfies a conformance rule, wherein the personal message is certified as conforming to the conformance rule before the personal message is entered in the marketing communication, wherein the certifying conformance to the conformance rule comprises confirming from the human user that the personal message does not exceed a predetermined length before the personal message is inserted in the communication; and transmitting, by the processor, the marketing communication to the first recipient of the plurality of recipients, the marketing communication including a first set of the plurality of sets of variable information based on the profile data corresponding to the first recipient and including the personal message. 8. The method of claim 7 , further comprising: transmitting, by the processor, the marketing communication to a second recipient of the plurality of recipients, the marketing communication including a second set of the plurality of sets of variable information based on the profile data corresponding to the second recipient. | 0.5 |
8,661,065 | 25 | 33 | 25. A computer-program product, tangibly embodied in a machine-readable non-transitory storage medium, including instructions executable to cause a data processing apparatus to perform operations including: storing data in a computerized data storage system that facilitates collaborative data management, wherein collaborative data management includes performance of multiple data management tasks, each data management task associated with a different one of multiple classes of data management tasks, wherein each one of the classes of data management tasks is associated with a unique group of users having permission to perform the data management tasks of the one class; activating a definition interface for defining terms used to manage the data, wherein a term is applicable to the data, and wherein a term includes a definition or a requirement; activating an instruction interface for effectuating terms, wherein the instruction interface facilitates an input of instructions into a data management system such that the inputted instructions effectuate a defined term within the data storage system, and wherein the inputted instructions cause the data storage system to associate the data with the defined term effectuated by the inputted instructions; processing the data according to the defined term effectuated by the inputted instructions; and displaying the inputted instructions, the defined term effectuated by the inputted instructions, and the processed data, wherein displaying includes using a monitoring interface that facilitates monitoring the data stored in the data storage system. | 25. A computer-program product, tangibly embodied in a machine-readable non-transitory storage medium, including instructions executable to cause a data processing apparatus to perform operations including: storing data in a computerized data storage system that facilitates collaborative data management, wherein collaborative data management includes performance of multiple data management tasks, each data management task associated with a different one of multiple classes of data management tasks, wherein each one of the classes of data management tasks is associated with a unique group of users having permission to perform the data management tasks of the one class; activating a definition interface for defining terms used to manage the data, wherein a term is applicable to the data, and wherein a term includes a definition or a requirement; activating an instruction interface for effectuating terms, wherein the instruction interface facilitates an input of instructions into a data management system such that the inputted instructions effectuate a defined term within the data storage system, and wherein the inputted instructions cause the data storage system to associate the data with the defined term effectuated by the inputted instructions; processing the data according to the defined term effectuated by the inputted instructions; and displaying the inputted instructions, the defined term effectuated by the inputted instructions, and the processed data, wherein displaying includes using a monitoring interface that facilitates monitoring the data stored in the data storage system. 33. The computer-program product of claim 25 , wherein a term further includes an attribute, and wherein an attribute includes a name attribute, description attribute, or a requirement attribute. | 0.649281 |
9,747,897 | 7 | 10 | 7. The computer-implemented method of claim 1 , further comprising: generating an identifier based on the like-pronunciation group; and associating the identifier with the substitute pronunciation. | 7. The computer-implemented method of claim 1 , further comprising: generating an identifier based on the like-pronunciation group; and associating the identifier with the substitute pronunciation. 10. The computer-implemented method of claim 7 , further comprising: identifying a mapping between the substitute pronunciation and an actual pronunciation for the one or more corresponding phones of the actual phonetic transcription; associating the mapping with the identifier; and storing the association and the mapping in the confusion matrix. | 0.5 |
9,529,852 | 8 | 14 | 8. A system, comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: receiving a content item request that includes context data specifying a user group that will be presented a content item and a resource on which the content item will be presented; in response to receiving the content item request: identifying a given content item that is eligible to be presented in response to the content item request; identifying a template feed from which a template for the given content item is to be selected, the template feed including a set of templates; determining, for each particular template from the set of templates, a contextual performance measure based on (i) a performance of one or more first content items when the particular template has been used to create the one or more first content items for presentation in response to content item requests that included a particular attribute of the context data and (ii) a performance of one or more second content items when the particular template has been used to create the one or more second content items for presentation with the resource; selecting, from the template feed and based on the contextual performance measure of each template in the set of templates, a template for the given content item; populating the selected template with content for the given content item to create a formatted content item; and providing the formatted content item in response to the content item request. | 8. A system, comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: receiving a content item request that includes context data specifying a user group that will be presented a content item and a resource on which the content item will be presented; in response to receiving the content item request: identifying a given content item that is eligible to be presented in response to the content item request; identifying a template feed from which a template for the given content item is to be selected, the template feed including a set of templates; determining, for each particular template from the set of templates, a contextual performance measure based on (i) a performance of one or more first content items when the particular template has been used to create the one or more first content items for presentation in response to content item requests that included a particular attribute of the context data and (ii) a performance of one or more second content items when the particular template has been used to create the one or more second content items for presentation with the resource; selecting, from the template feed and based on the contextual performance measure of each template in the set of templates, a template for the given content item; populating the selected template with content for the given content item to create a formatted content item; and providing the formatted content item in response to the content item request. 14. The system of claim 8 , wherein the operations further comprise: receiving filtering data specifying a proper subset of templates in the set of templates that are eligible to be used for content item requests including a particular set of context data; and filtering the set of templates based on the filtering data and the context data of the received content item request. | 0.5 |
8,321,371 | 3 | 5 | 3. The method of claim 2 wherein linking the plurality of attributes to the plurality of response templates comprises: forming by the computer system a megacategory, with the megacategory linking a combination of attributes to one of the plurality of response templates using one of the plurality of Boolean expressions. | 3. The method of claim 2 wherein linking the plurality of attributes to the plurality of response templates comprises: forming by the computer system a megacategory, with the megacategory linking a combination of attributes to one of the plurality of response templates using one of the plurality of Boolean expressions. 5. The method of claim 3 wherein the combination of attributes using one of the plurality of Boolean expressions comprises: a name for each attribute in the combination; and an operator Boolean expression. | 0.674603 |
9,830,318 | 1 | 2 | 1. A computer-implemented method comprising: determining, by an automatic speech recognition unit, spoken sound from a first speaker in a first language; creating a plurality of partial hypotheses of the spoken sound of the first speaker; merging, by a resegmentation unit that is in communication with the automatic speech recognition unit, at least two of the partial hypotheses received from the automatic speech recognition unit; receiving an end-of-sentence cue from one or more listeners, the end-of-sentence cue being commonly associated with an end of a sentence; determining a segment boundary for a translatable segment based on the received end-of-sentence cue; resegmenting, by the resegmentation unit, the merged partial hypotheses into the translatable segment in the first language based on the determined segment boundary; and receiving, by a machine translation unit that is in communication with the resegmentation unit, the translatable segment in the first language from the resegmentation unit outputting, by the machine translation unit, a translation of the spoken sound from the first speaker into a second language based on the received translatable segment. | 1. A computer-implemented method comprising: determining, by an automatic speech recognition unit, spoken sound from a first speaker in a first language; creating a plurality of partial hypotheses of the spoken sound of the first speaker; merging, by a resegmentation unit that is in communication with the automatic speech recognition unit, at least two of the partial hypotheses received from the automatic speech recognition unit; receiving an end-of-sentence cue from one or more listeners, the end-of-sentence cue being commonly associated with an end of a sentence; determining a segment boundary for a translatable segment based on the received end-of-sentence cue; resegmenting, by the resegmentation unit, the merged partial hypotheses into the translatable segment in the first language based on the determined segment boundary; and receiving, by a machine translation unit that is in communication with the resegmentation unit, the translatable segment in the first language from the resegmentation unit outputting, by the machine translation unit, a translation of the spoken sound from the first speaker into a second language based on the received translatable segment. 2. The computer-implemented method of claim 1 , further comprising: receiving, by a speech captioning unit that is in communication with the resegmentation unit, the translatable segment in the first language from the resegmentation unit; and outputting, by the speech captioning unit, a caption of the spoken sound from the first speaker in the first language based on the received translatable segment. | 0.5 |
9,760,380 | 16 | 17 | 16. The system of claim 15 , wherein the deserialization engine is further operable to obtain a version of the grammar from the metadata, the version used to create the serialized data, the deserialization engine further operable to compare the version to a version of the another grammar. | 16. The system of claim 15 , wherein the deserialization engine is further operable to obtain a version of the grammar from the metadata, the version used to create the serialized data, the deserialization engine further operable to compare the version to a version of the another grammar. 17. The system of claim 16 , wherein the deserialization engine is further operable to refrain from de-serializing the serialized data if the version of the grammar used to create the serialized data is more than a minor version different than the version of the another grammar. | 0.5 |
9,519,716 | 1 | 10 | 1. A method comprising: receiving, by a computing device, a search query including one or more search terms from a user; generating, based upon the one or more search terms and from tracked user search behavior, by the computing device, a user profile for the user in a data store comprising a plurality of user profiles; establishing, by the computing device, a contextual relationship between the one or more search terms and user profile characteristics associated with each user profile of the plurality of user profiles; parsing, by the computing device, the search query into categorical verticals; determining, by the computing device, search refinement data relative to the categorical verticals, the search refinement data including at least one of: profile information, environmental data relative to the search query and historical behavior data relating to other search queries; accessing, by the computing device, a database of aggregated search data based on the search refinement data, the search data comprising a plurality of query terms and the plurality of user profiles; determining, by the computing device, alternative query terms in the plurality of query terms, the alternative query terms relevant to a set of user profiles in the plurality other than a user's primary profile selected by the user; determining, by the computing device, a most relevant search query from the plurality of search queries and the alternative query terms and a most relevant user profile from the plurality of user profiles, the most relevant user profile based on a plurality of sponsor-purchased public user profiles and both the most relevant search query and the most relevant user profile based on the aggregated search data; refining, by the computing device, the search query based on the most relevant search query and most relevant user profile; and generating, by the computing device, an output display including a search result set based on the refined search query. | 1. A method comprising: receiving, by a computing device, a search query including one or more search terms from a user; generating, based upon the one or more search terms and from tracked user search behavior, by the computing device, a user profile for the user in a data store comprising a plurality of user profiles; establishing, by the computing device, a contextual relationship between the one or more search terms and user profile characteristics associated with each user profile of the plurality of user profiles; parsing, by the computing device, the search query into categorical verticals; determining, by the computing device, search refinement data relative to the categorical verticals, the search refinement data including at least one of: profile information, environmental data relative to the search query and historical behavior data relating to other search queries; accessing, by the computing device, a database of aggregated search data based on the search refinement data, the search data comprising a plurality of query terms and the plurality of user profiles; determining, by the computing device, alternative query terms in the plurality of query terms, the alternative query terms relevant to a set of user profiles in the plurality other than a user's primary profile selected by the user; determining, by the computing device, a most relevant search query from the plurality of search queries and the alternative query terms and a most relevant user profile from the plurality of user profiles, the most relevant user profile based on a plurality of sponsor-purchased public user profiles and both the most relevant search query and the most relevant user profile based on the aggregated search data; refining, by the computing device, the search query based on the most relevant search query and most relevant user profile; and generating, by the computing device, an output display including a search result set based on the refined search query. 10. The method of claim 1 wherein the determination of the search refinement data is based on the profile information, the method further comprising: associating a sponsored interest with the profile; and refining the search query based on the profile including limiting the search results solely to results associated with the sponsored interest. | 0.5 |
8,510,289 | 8 | 9 | 8. A system comprising: one or more processors to: receive a query from a client device, the query including one or more terms; identify terms related to the one or more terms of the query, the terms related to the one or more terms of the query including synonyms of the one or more terms of the query; determine whether the query is a commercial query, where, when determining whether the query is a commercial query, the one or more processors are to: compare the one or more terms of the query, in any order, to words in a commercial query pattern in a list of commercial query patterns, compare the one or more terms of the query, in any order, to words related to the words in the commercial query pattern, compare the terms related to the one or more terms of the query to words in the commercial query pattern in the list of commercial query patterns, compare the terms related to the one or more terms of the query to words related to the words in the commercial query pattern, and identify the query as a commercial query when at least one of: the one or more terms of the query, in any order, match the words in the commercial query pattern, the one or more terms of the query, in any order, match the words related to the words in the commercial query pattern, the terms related to the one or more terms of the query match the words in the commercial query pattern in the list of commercial query patterns, or the terms related to the one or more terms of the query match the words related to the words in the commercial query pattern; process the query in a first manner based on determining that the query is not a commercial query; and process the query in a second manner based on determining that the query is a commercial query, where the second manner is different than the first manner. | 8. A system comprising: one or more processors to: receive a query from a client device, the query including one or more terms; identify terms related to the one or more terms of the query, the terms related to the one or more terms of the query including synonyms of the one or more terms of the query; determine whether the query is a commercial query, where, when determining whether the query is a commercial query, the one or more processors are to: compare the one or more terms of the query, in any order, to words in a commercial query pattern in a list of commercial query patterns, compare the one or more terms of the query, in any order, to words related to the words in the commercial query pattern, compare the terms related to the one or more terms of the query to words in the commercial query pattern in the list of commercial query patterns, compare the terms related to the one or more terms of the query to words related to the words in the commercial query pattern, and identify the query as a commercial query when at least one of: the one or more terms of the query, in any order, match the words in the commercial query pattern, the one or more terms of the query, in any order, match the words related to the words in the commercial query pattern, the terms related to the one or more terms of the query match the words in the commercial query pattern in the list of commercial query patterns, or the terms related to the one or more terms of the query match the words related to the words in the commercial query pattern; process the query in a first manner based on determining that the query is not a commercial query; and process the query in a second manner based on determining that the query is a commercial query, where the second manner is different than the first manner. 9. The system of claim 8 , where, when comparing the terms related to the one or more terms of the query to the words in the commercial query pattern, the one or more processors are further to: compare stems of the one or more terms of the query to words in the commercial query pattern in the list of commercial query patterns. | 0.6 |
7,496,496 | 1 | 10 | 1. A method of training a machine translation computing device to generate confidence scores indicative of a quality of a translation result, comprising: translating a source string with a machine translation computing device to generate a target string; extracting features from the machine translator, indicative of performance of translation steps in the machine translator; obtaining a trusted entity-assigned translation score indicative of a trusted entity-assigned translation quality of the target string; identifying a relationship between a subset of the extracted features and the trusted entity-assigned translation score; parsing the source string into a source intermediate linguistic structure indicative of a meaning of the source string; wherein translating includes translating the source intermediate linguistic structure to a target intermediate linguistic structure; wherein translating the source intermediate linguistic structure comprises identifying mappings, in a mapping database, that map portions of the source intermediate linguistic structure to portions of the target intermediate linguistic structure; and wherein extracting one or more features indicative of a quality of transiating the source intermediate linguistic structure comprises extracting a feature indicative of a number of identified mappings. | 1. A method of training a machine translation computing device to generate confidence scores indicative of a quality of a translation result, comprising: translating a source string with a machine translation computing device to generate a target string; extracting features from the machine translator, indicative of performance of translation steps in the machine translator; obtaining a trusted entity-assigned translation score indicative of a trusted entity-assigned translation quality of the target string; identifying a relationship between a subset of the extracted features and the trusted entity-assigned translation score; parsing the source string into a source intermediate linguistic structure indicative of a meaning of the source string; wherein translating includes translating the source intermediate linguistic structure to a target intermediate linguistic structure; wherein translating the source intermediate linguistic structure comprises identifying mappings, in a mapping database, that map portions of the source intermediate linguistic structure to portions of the target intermediate linguistic structure; and wherein extracting one or more features indicative of a quality of transiating the source intermediate linguistic structure comprises extracting a feature indicative of a number of identified mappings. 10. The method of claim 1 wherein extracting features comprises: calculating a perplexity of the target string with a statistical language model. | 0.771293 |
8,301,544 | 24 | 25 | 24. The method of claim 23 wherein the price optimization is effected in light of received market data, historical data and seller targets. | 24. The method of claim 23 wherein the price optimization is effected in light of received market data, historical data and seller targets. 25. The method of claim 24 wherein all the optimized prices are integrated to produce a seller price quote. | 0.5 |
9,600,272 | 14 | 18 | 14. A computer system comprising: a logical processor; a memory in operable communication with the logical processor; a computer program source code residing in at least one source code file in the memory, the computer program source code written in one or more programming languages; a compiler; and a directives document residing in the memory outside a compilation portion of the computer program source code and having runtime behavior characteristic directives which are written in a human-readable software-parsable format and are not written in the programming languages; and wherein upon execution by the logical processor(s) the compiler compiles at least the compilation portion of the computer program source code from the source code file(s) into at least one native code file as directed by the directives document, including performing at least one of the following: (a) making a type T of the computer program source code be a required type, an optional type, or a prohibited type in the environment, (b) making a type member M of the computer program source code be a required type member, an optional type member, or a prohibited type member in the environment, or (c) enabling or disabling a degree D for a type T or a type member M in the environment. | 14. A computer system comprising: a logical processor; a memory in operable communication with the logical processor; a computer program source code residing in at least one source code file in the memory, the computer program source code written in one or more programming languages; a compiler; and a directives document residing in the memory outside a compilation portion of the computer program source code and having runtime behavior characteristic directives which are written in a human-readable software-parsable format and are not written in the programming languages; and wherein upon execution by the logical processor(s) the compiler compiles at least the compilation portion of the computer program source code from the source code file(s) into at least one native code file as directed by the directives document, including performing at least one of the following: (a) making a type T of the computer program source code be a required type, an optional type, or a prohibited type in the environment, (b) making a type member M of the computer program source code be a required type member, an optional type member, or a prohibited type member in the environment, or (c) enabling or disabling a degree D for a type T or a type member M in the environment. 18. The system of claim 14 , wherein the compiler executes instructions which perform at least one of the following: apply at least one composition rule to at least two runtime behavior characteristic directives to produce a composite runtime behavior characteristic directive, or output native code instantiating a generic parameter in response to at least one runtime behavior characteristic directive. | 0.5 |
9,158,860 | 19 | 27 | 19. A non-transitory computer readable storage medium storing computer instructions executable by a processor to perform a method comprising: identifying a partial query entered into a search field; providing for display a query completion template, the query completion template provided for display in response to identifying the partial query and being for a category of information associated with one or more terms within the partial query, the query completion template including an interactive field that is user editable and including one or more additional fields, the query completion template defining the number of terms, type of terms, and ordering of terms within a search query formed using the query template; identifying user interaction with the interactive field; updating the display of the query completion template to include the results of the user interaction within the interactive field of the query completion template; identifying user selection of the updated query completion template; and transmitting the updated display of the query completion template as a search query in response to the user selection, the search query including one or more query terms that are based on the results of the user interaction with the interactive field and one or more additional query terms based on the one or more additional fields, the one or more query terms and the one or more additional query terms being ordered based on the ordering of terms defined by the query completion template. | 19. A non-transitory computer readable storage medium storing computer instructions executable by a processor to perform a method comprising: identifying a partial query entered into a search field; providing for display a query completion template, the query completion template provided for display in response to identifying the partial query and being for a category of information associated with one or more terms within the partial query, the query completion template including an interactive field that is user editable and including one or more additional fields, the query completion template defining the number of terms, type of terms, and ordering of terms within a search query formed using the query template; identifying user interaction with the interactive field; updating the display of the query completion template to include the results of the user interaction within the interactive field of the query completion template; identifying user selection of the updated query completion template; and transmitting the updated display of the query completion template as a search query in response to the user selection, the search query including one or more query terms that are based on the results of the user interaction with the interactive field and one or more additional query terms based on the one or more additional fields, the one or more query terms and the one or more additional query terms being ordered based on the ordering of terms defined by the query completion template. 27. The non-transitory computer readable storage medium of claim 19 , wherein providing for display the query completion template includes initially providing for display text within the interactive field. | 0.833333 |
9,135,255 | 9 | 10 | 9. A system for identifying interests comprising one or more processors and one or more memory devices operably coupled to the one or more processors, the one or more memory devices storing executable and operational data effective to cause the one or more processors to: evaluate social media data of a user; identify from the social media data a plurality of communities each community of the plurality of communities including a plurality of friends of the user, each community of the plurality of communities identified according to social media interconnections and interactions among friends of the user in each community; for each community of the plurality of communities, identify common interests from personal interests of the plurality of friends of the user of the each community; identify, for each community of the plurality of communities, at least one characterizing interest of the common interests identified for the each community, the at least one characterizing interest being absent from any self-identified interests of the user in the social media data; and select one or more inferred interests for the user from among the at least one characterizing interests of the plurality of communities; wherein the executable and operational data further effective to cause the one or more processors to identify, for each community of the plurality of communities, at least one characterizing interest of the common interests identified for each community of the plurality of communities by, for each community: performing a first ranking of the common interests identified for the each community according to popularity of the common interests identified within the each community; and selecting the at least one characterizing interest for the each community according to the first ranking; and wherein the executable and operational data are further effective to cause the one or more processors to select the one or more inferred interests for the user from among the at least one characterizing interests of the plurality of communities by: evaluating frequency of interaction of the user with the plurality of friends of the user corresponding to each community of the plurality of communities; ranking the at least one characterizing interests of the plurality of communities according to the frequency of interaction of the user with the plurality of friends of the user corresponding to each community of the plurality of communities; and selecting the one or more inferred interests according to the ranking. | 9. A system for identifying interests comprising one or more processors and one or more memory devices operably coupled to the one or more processors, the one or more memory devices storing executable and operational data effective to cause the one or more processors to: evaluate social media data of a user; identify from the social media data a plurality of communities each community of the plurality of communities including a plurality of friends of the user, each community of the plurality of communities identified according to social media interconnections and interactions among friends of the user in each community; for each community of the plurality of communities, identify common interests from personal interests of the plurality of friends of the user of the each community; identify, for each community of the plurality of communities, at least one characterizing interest of the common interests identified for the each community, the at least one characterizing interest being absent from any self-identified interests of the user in the social media data; and select one or more inferred interests for the user from among the at least one characterizing interests of the plurality of communities; wherein the executable and operational data further effective to cause the one or more processors to identify, for each community of the plurality of communities, at least one characterizing interest of the common interests identified for each community of the plurality of communities by, for each community: performing a first ranking of the common interests identified for the each community according to popularity of the common interests identified within the each community; and selecting the at least one characterizing interest for the each community according to the first ranking; and wherein the executable and operational data are further effective to cause the one or more processors to select the one or more inferred interests for the user from among the at least one characterizing interests of the plurality of communities by: evaluating frequency of interaction of the user with the plurality of friends of the user corresponding to each community of the plurality of communities; ranking the at least one characterizing interests of the plurality of communities according to the frequency of interaction of the user with the plurality of friends of the user corresponding to each community of the plurality of communities; and selecting the one or more inferred interests according to the ranking. 10. The system of claim 9 , wherein the executable and operational data are further effective to cause the one or more processors to identify, for each community of the plurality of communities, at least one characterizing interest of the common interests identified for each community of the plurality of communities by, for each community: performing a second ranking of the common interests identified for the each community according to an inverse of global popularity for the common interests identified; and selecting the at least one characterizing interest for the each community according to the first ranking and the second ranking. | 0.5 |
8,271,503 | 1 | 4 | 1. A computer program product tangibly embodied in a non-transitory machine-readable storage device that stores instructions for causing data processing apparatus to perform operations for facilitating automated identification of matches between elements of disparate schemas, the operations comprising: calculating a first degree of similarity between elements of a first schema and elements of a second schema using a first matching process; calculating a second degree of similarity between the elements of the first schema and the elements of a second schema using a second matching process; combining the first degree of similarity and the second degree of similarity using a first weighting vector to provide a combined degree of similarity, the first weighting vector comprising a first weighting coefficient corresponding to the first matching process and a second weighting coefficient corresponding to the second matching process; determining a level of ambiguity based on the first combined degree of similarity, the level of ambiguity accounting for at least one of a number of unambiguous matches between elements of the first and second schemas, a number of ambiguous matches between elements of the first and second schemas and a number of impossible matches between elements of the first and second schemas; and adjusting the first weighting coefficient and the second weighting coefficient based on the level of ambiguity to provide a second weighting vector by receiving user feedback relating to a subset of possible matches between the elements of the first schema and the elements of the second schema, the first coefficient and the second coefficient being adjusted based on the user feedback. | 1. A computer program product tangibly embodied in a non-transitory machine-readable storage device that stores instructions for causing data processing apparatus to perform operations for facilitating automated identification of matches between elements of disparate schemas, the operations comprising: calculating a first degree of similarity between elements of a first schema and elements of a second schema using a first matching process; calculating a second degree of similarity between the elements of the first schema and the elements of a second schema using a second matching process; combining the first degree of similarity and the second degree of similarity using a first weighting vector to provide a combined degree of similarity, the first weighting vector comprising a first weighting coefficient corresponding to the first matching process and a second weighting coefficient corresponding to the second matching process; determining a level of ambiguity based on the first combined degree of similarity, the level of ambiguity accounting for at least one of a number of unambiguous matches between elements of the first and second schemas, a number of ambiguous matches between elements of the first and second schemas and a number of impossible matches between elements of the first and second schemas; and adjusting the first weighting coefficient and the second weighting coefficient based on the level of ambiguity to provide a second weighting vector by receiving user feedback relating to a subset of possible matches between the elements of the first schema and the elements of the second schema, the first coefficient and the second coefficient being adjusted based on the user feedback. 4. The computer program product of claim 1 , wherein the level of ambiguity is normalized based on a total number of elements of the first and second schemas. | 0.852336 |
8,188,978 | 17 | 19 | 17. The handheld electronic device of claim 11 , wherein the operations further comprise: when unable to identify a word frame corresponding with the ambiguous input, identifying, from the stored word frames, a word frame partially corresponding with the ambiguous input. | 17. The handheld electronic device of claim 11 , wherein the operations further comprise: when unable to identify a word frame corresponding with the ambiguous input, identifying, from the stored word frames, a word frame partially corresponding with the ambiguous input. 19. The handheld electronic device of claim 17 , wherein: all of the sequentially selected input keys of the ambiguous input correspond with a root portion of the partially corresponding word frame, and the root portion of the partially corresponding word frame includes a linguistic element not corresponding with the sequentially selected input keys of the ambiguous input. | 0.5 |
8,306,635 | 1 | 6 | 1. A computer based exercise method comprising the steps of: providing an exercise machine on which a person exercises, wherein said exercise machine resists the effort of said person when exercising; providing a computer and a computer-controlled video display for viewing by said person; electro-optically determining data concerning a plurality of points on at least one of said person and said machine; processing said data to determine a variable related to one or more of said points; and using said determined variable, controlling a video game program in said computer. | 1. A computer based exercise method comprising the steps of: providing an exercise machine on which a person exercises, wherein said exercise machine resists the effort of said person when exercising; providing a computer and a computer-controlled video display for viewing by said person; electro-optically determining data concerning a plurality of points on at least one of said person and said machine; processing said data to determine a variable related to one or more of said points; and using said determined variable, controlling a video game program in said computer. 6. A method according to claim 1 wherein said processing determines the velocity of at least one point. | 0.629496 |
8,572,107 | 1 | 4 | 1. A horizontal anomaly detection method comprising: receiving a plurality of descriptions describing a plurality of objects, each object of the plurality of objects being described by a plurality of different information sources, wherein each individual information source of the plurality of information sources captures a plurality of similarity relationships between the plurality of objects; generating a similarity matrix from the plurality of different information sources, wherein entries of the similarity matrix represent quantitative scores of similarity between pairs of the plurality of objects; and identifying at least one horizontal anomaly within the plurality of objects from the similarity matrix, wherein the horizontal anomalies each comprise a clustering of at least two objects of the plurality of objects into a common cluster based on a first information source of the plurality of different information sources and simultaneously clustering the at least two objects of the plurality of objects into different clusters based on a second information source of the plurality of different information sources, wherein the steps of receiving the descriptions, generating the similarity matrix, and identifying the at least one horizontal anomalies are performed using a computer system, and wherein combining the information sources comprises; placing each individual similarity matrix along a block diagonal of the similarity matrix; and filling off-diagonal entries of the similarity matrix using weighted identity matrices, wherein a weight of the weighted identity matrices is a constraint on relationships across the plurality of information sources. | 1. A horizontal anomaly detection method comprising: receiving a plurality of descriptions describing a plurality of objects, each object of the plurality of objects being described by a plurality of different information sources, wherein each individual information source of the plurality of information sources captures a plurality of similarity relationships between the plurality of objects; generating a similarity matrix from the plurality of different information sources, wherein entries of the similarity matrix represent quantitative scores of similarity between pairs of the plurality of objects; and identifying at least one horizontal anomaly within the plurality of objects from the similarity matrix, wherein the horizontal anomalies each comprise a clustering of at least two objects of the plurality of objects into a common cluster based on a first information source of the plurality of different information sources and simultaneously clustering the at least two objects of the plurality of objects into different clusters based on a second information source of the plurality of different information sources, wherein the steps of receiving the descriptions, generating the similarity matrix, and identifying the at least one horizontal anomalies are performed using a computer system, and wherein combining the information sources comprises; placing each individual similarity matrix along a block diagonal of the similarity matrix; and filling off-diagonal entries of the similarity matrix using weighted identity matrices, wherein a weight of the weighted identity matrices is a constraint on relationships across the plurality of information sources. 4. The horizontal anomaly detection method of claim 1 , wherein higher quantitative scores correspond to anomalies. | 0.814516 |
8,655,899 | 7 | 8 | 7. A database system for the comparison of pangenetic and non-pangenetic attributes of users to establish, following such comparison, a pangenetic social network group within an existing social network, comprising: a) a receiver for receiving a request to identify a subset of one or more users of the social network having a common attribute set to a first user, wherein the common attribute set comprises at least one pangenetic and at least one non-pangenetic attribute, and wherein the pangenetic attribute(s) consist of genetic or epigenetic attribute(s); b) a database containing attributes of a set of users of the social network, wherein the database of attributes includes pangenetic and non-pangenetic attributes of the set of users of the social network; and c) a processor for: i. determining, based on a correlation of the common attribute set and the attributes of the set of users of the social network, the subset of one or more users of the social network having the common attribute set to the first user, wherein the correlation is based on determining if the number of pangenetic and non-pangenetic attributes of the attributes of each of the users of the set of users of the social network that overlap with the common attribute set exceeds a predetermined threshold; and ii. recommending an association between the first user and at least some of the set of one or more users of the social network having the common attribute set, wherein the association allows the creation of a social network group based on common interests and pangenetic similarity. | 7. A database system for the comparison of pangenetic and non-pangenetic attributes of users to establish, following such comparison, a pangenetic social network group within an existing social network, comprising: a) a receiver for receiving a request to identify a subset of one or more users of the social network having a common attribute set to a first user, wherein the common attribute set comprises at least one pangenetic and at least one non-pangenetic attribute, and wherein the pangenetic attribute(s) consist of genetic or epigenetic attribute(s); b) a database containing attributes of a set of users of the social network, wherein the database of attributes includes pangenetic and non-pangenetic attributes of the set of users of the social network; and c) a processor for: i. determining, based on a correlation of the common attribute set and the attributes of the set of users of the social network, the subset of one or more users of the social network having the common attribute set to the first user, wherein the correlation is based on determining if the number of pangenetic and non-pangenetic attributes of the attributes of each of the users of the set of users of the social network that overlap with the common attribute set exceeds a predetermined threshold; and ii. recommending an association between the first user and at least some of the set of one or more users of the social network having the common attribute set, wherein the association allows the creation of a social network group based on common interests and pangenetic similarity. 8. The system of claim 7 , wherein the recommending comprises transmitting an electronic notification of the social network group to at least some of the set of one or more of the users of the social network having the common attribute set. | 0.5 |
9,767,520 | 1 | 4 | 1. A method comprising: receiving a posting of an item through a social networking site, wherein the social networking site receives and transmits posted items from posting entities to receiving entities; when the posting is not associated with a product for purchase in a product database: transmitting the posting through the social networking site without an option to buy; and when the posting references the product in the product database, and thus indicating a sale-related intent: inserting, by the social networking site, a payment process initiation object into the posting to yield a product posting, the payment process initiation object, when interacted with by a user, indicating an intent by the user to initiate a process to purchase a product in the product posting; transmitting the product posting through the social networking site with the payment process initiation object associated with the product, wherein the payment process initiation object comprises one of a button, a drop-down menu, or a hyperlink; receiving an interaction associated with the payment process initiation object; and based on the interaction: transitioning the user from the social networking site to a merchant site associated with the product posting; based on a buy interaction by the user with a pay object on the merchant site, receiving a payment request, from the merchant site, via a browser application programming interface between a browser and the merchant site, wherein the browser presents the merchant site to the user; and in response to the payment request, communicating authorized payment data for the user from the browser and through the browser application programming interface to the merchant site to enable the merchant site to use the authorized payment data to complete a purchase of the product. | 1. A method comprising: receiving a posting of an item through a social networking site, wherein the social networking site receives and transmits posted items from posting entities to receiving entities; when the posting is not associated with a product for purchase in a product database: transmitting the posting through the social networking site without an option to buy; and when the posting references the product in the product database, and thus indicating a sale-related intent: inserting, by the social networking site, a payment process initiation object into the posting to yield a product posting, the payment process initiation object, when interacted with by a user, indicating an intent by the user to initiate a process to purchase a product in the product posting; transmitting the product posting through the social networking site with the payment process initiation object associated with the product, wherein the payment process initiation object comprises one of a button, a drop-down menu, or a hyperlink; receiving an interaction associated with the payment process initiation object; and based on the interaction: transitioning the user from the social networking site to a merchant site associated with the product posting; based on a buy interaction by the user with a pay object on the merchant site, receiving a payment request, from the merchant site, via a browser application programming interface between a browser and the merchant site, wherein the browser presents the merchant site to the user; and in response to the payment request, communicating authorized payment data for the user from the browser and through the browser application programming interface to the merchant site to enable the merchant site to use the authorized payment data to complete a purchase of the product. 4. The method of claim 1 , wherein the payment process initiation object comprises a buy button. | 0.885442 |
7,979,840 | 22 | 23 | 22. The computer program product of claim 19 , further comprising: program code for deriving an SOA-method model to provide a generic framework for service modeling in an SOA solution. | 22. The computer program product of claim 19 , further comprising: program code for deriving an SOA-method model to provide a generic framework for service modeling in an SOA solution. 23. The computer program product of claim 22 , further comprising: program code for deploying said SOA-method model for at least one entity consulting services platform to increase productivity of at least one practitioner. | 0.5 |
8,341,607 | 2 | 6 | 2. The method of claim 1 , wherein identifying input elements from intermediate language code, comprises identifying input literals, symbols and sub-expressions from intermediate language code. | 2. The method of claim 1 , wherein identifying input elements from intermediate language code, comprises identifying input literals, symbols and sub-expressions from intermediate language code. 6. The method of claim 2 , wherein creating a unifiable form for each of the input elements of common and unique use, comprises creating a unifiable form of a symbol for each symbol element of common and unique use in the intermediate language code. | 0.530189 |
5,469,568 | 5 | 6 | 5. The method for determining and selecting joint selectivities as defined in claim 1 further comprising the machine-executed step of taking the effect of a local predicate into account. | 5. The method for determining and selecting joint selectivities as defined in claim 1 further comprising the machine-executed step of taking the effect of a local predicate into account. 6. The method as defined in claim 5 further comprising the machine-executed step of accounting for the effect of the local predicate on the cardinality of the relation. | 0.538462 |
7,779,002 | 1 | 12 | 1. A method comprising: receiving search results in response to a query, the query including one or more keywords, the search results including a first search result and a second search result; generating a set of final search results from the received search results with one or more processors, including: adding the first search result to the set of final search results; determining that a first document corresponding to the first search result and a second document corresponding to the second search result are query-specific duplicate documents from a comparison of one or more first query-relevant parts of the first document and one or more second query-relevant parts of the second document, where each query-relevant part includes at least one of the one or more keywords; and in response to the determination, not adding the second search result to the set of final search results; and presenting the set of final search results. | 1. A method comprising: receiving search results in response to a query, the query including one or more keywords, the search results including a first search result and a second search result; generating a set of final search results from the received search results with one or more processors, including: adding the first search result to the set of final search results; determining that a first document corresponding to the first search result and a second document corresponding to the second search result are query-specific duplicate documents from a comparison of one or more first query-relevant parts of the first document and one or more second query-relevant parts of the second document, where each query-relevant part includes at least one of the one or more keywords; and in response to the determination, not adding the second search result to the set of final search results; and presenting the set of final search results. 12. The method of claim 1 wherein the query-relevant parts include a predetermined number of words. | 0.912698 |
9,613,029 | 11 | 12 | 11. A computing device, comprising: a keyboard that receives user input from a user indicating input text in a first character set via an input method editor; a transliteration determination module configured to (i) receive the input text and determine a set of possible transliterations of the input text based on a plurality of mapping standards and the input text, each possible transliteration of the set of possible transliterations corresponding to a transliteration of the input text into a second character set corresponding to a target language, each mapping standard of the plurality of mapping standards defining a mapping of each and every character in the second character set to one or more characters in the first character set and each mapping standard having an associated transliteration probability stored for use with the input method editor, each transliteration probability being indicative of a likelihood that its corresponding mapping standard is appropriate for transliterating text from the user in the first character set to the second character set, and (ii) determine a transliteration score for each of the possible transliterations based on the transliteration probabilities, the transliteration score being indicative of a likelihood that its corresponding possible transliteration is an accurate transliteration of the input text; a candidate word determination module configured to determine a set of candidate words in the target language based on the set of possible transliterations and a text corpus of the target language, the text corpus corresponding to a set of known words in the target language; a word selection module configured to: a) determine a likelihood score for each candidate in the set of candidate words based on a language model in the target language and one or more previous words received, each likelihood score being indicative of a probability that its corresponding candidate word corresponds to the input text, b) provide one or more candidate words of the set of candidate words based on the likelihood scores, the transliteration probabilities of the one or more candidate words, and the transliteration scores, and c) receive a user selection indicating one of the candidate words; and a feedback module configured to: monitor tendencies of the user by determining a particular mapping standard of the plurality of mapping standards on which the selected candidate word was based; and adjust the transliteration probabilities stored for use with the input method editor based on the tendencies of the user as determined from the particular mapping standard. | 11. A computing device, comprising: a keyboard that receives user input from a user indicating input text in a first character set via an input method editor; a transliteration determination module configured to (i) receive the input text and determine a set of possible transliterations of the input text based on a plurality of mapping standards and the input text, each possible transliteration of the set of possible transliterations corresponding to a transliteration of the input text into a second character set corresponding to a target language, each mapping standard of the plurality of mapping standards defining a mapping of each and every character in the second character set to one or more characters in the first character set and each mapping standard having an associated transliteration probability stored for use with the input method editor, each transliteration probability being indicative of a likelihood that its corresponding mapping standard is appropriate for transliterating text from the user in the first character set to the second character set, and (ii) determine a transliteration score for each of the possible transliterations based on the transliteration probabilities, the transliteration score being indicative of a likelihood that its corresponding possible transliteration is an accurate transliteration of the input text; a candidate word determination module configured to determine a set of candidate words in the target language based on the set of possible transliterations and a text corpus of the target language, the text corpus corresponding to a set of known words in the target language; a word selection module configured to: a) determine a likelihood score for each candidate in the set of candidate words based on a language model in the target language and one or more previous words received, each likelihood score being indicative of a probability that its corresponding candidate word corresponds to the input text, b) provide one or more candidate words of the set of candidate words based on the likelihood scores, the transliteration probabilities of the one or more candidate words, and the transliteration scores, and c) receive a user selection indicating one of the candidate words; and a feedback module configured to: monitor tendencies of the user by determining a particular mapping standard of the plurality of mapping standards on which the selected candidate word was based; and adjust the transliteration probabilities stored for use with the input method editor based on the tendencies of the user as determined from the particular mapping standard. 12. The computing device of claim 11 , wherein the text corpus includes at least one dictionary listing a plurality of words in the target language. | 0.789773 |
9,619,910 | 13 | 14 | 13. A computing device comprising at least one memory and at least one processing unit operable to execute instructions for performing a method of creating a first graphical diagram, the method comprising: receiving a first line of text and a second line of text in a content entry area; receiving one or more formats in addition to the first line of text and the second line of text; in response to receiving the one or more formats, determining a hierarchical relationship between the first line of text and the second line of text based on the one or more formats; receiving a selection of a first graphical layout from a layout gallery displaying a plurality of graphical layouts for creating the first graphical diagram; and creating the first graphical diagram in a drawing canvas that is separate from the content entry area and the layout gallery, wherein the creating comprising: combining the first line of text with the first graphical layout to generate a first shape, the first shape at least substantially encapsulating the first line of text; combining the second line of text with the first graphical layout to generate a second shape, the second shape at least substantially encapsulating the second line of text; displaying a transition between the first shape and the second shape, the transition representing the hierarchical relationship between the first line of text and the second line of text; displaying the first line of text and the second line of text in the content entry area; and displaying the first graphical diagram having the first shape and the second shape in the drawing canvas area. | 13. A computing device comprising at least one memory and at least one processing unit operable to execute instructions for performing a method of creating a first graphical diagram, the method comprising: receiving a first line of text and a second line of text in a content entry area; receiving one or more formats in addition to the first line of text and the second line of text; in response to receiving the one or more formats, determining a hierarchical relationship between the first line of text and the second line of text based on the one or more formats; receiving a selection of a first graphical layout from a layout gallery displaying a plurality of graphical layouts for creating the first graphical diagram; and creating the first graphical diagram in a drawing canvas that is separate from the content entry area and the layout gallery, wherein the creating comprising: combining the first line of text with the first graphical layout to generate a first shape, the first shape at least substantially encapsulating the first line of text; combining the second line of text with the first graphical layout to generate a second shape, the second shape at least substantially encapsulating the second line of text; displaying a transition between the first shape and the second shape, the transition representing the hierarchical relationship between the first line of text and the second line of text; displaying the first line of text and the second line of text in the content entry area; and displaying the first graphical diagram having the first shape and the second shape in the drawing canvas area. 14. The computing device according to claim 13 , further comprising: receiving a first customization to a presentation property of the first shape; and updating the presentation property of the first shape with the first customization. | 0.546332 |
9,760,953 | 24 | 25 | 24. The method of claim 1 , transforming the first data structure into the second data structure comprising transforming he pre-determined question-and-answer flow into a directed graph. | 24. The method of claim 1 , transforming the first data structure into the second data structure comprising transforming he pre-determined question-and-answer flow into a directed graph. 25. The method of claim 24 , further comprising transforming the second data structure comprising the directed graph into a third data structure different from the first data structure and the second data structure. | 0.5 |
9,633,650 | 13 | 14 | 13. The method of claim 12 , further comprising averaging a plurality of per utterance conformities for each audio file to calculate the transcription quality score for each of the audio files. | 13. The method of claim 12 , further comprising averaging a plurality of per utterance conformities for each audio file to calculate the transcription quality score for each of the audio files. 14. The method of claim 13 , further comprising normalizing the transcription quality scores between the plurality of audio files. | 0.5 |
10,089,582 | 25 | 27 | 25. A non-transitory computer readable storage medium having stored thereon processor-executable software instructions configured to cause a processor of a of a computing device to perform operations comprising: receiving from a server computing device a full classifier model and sigmoid parameters; determining a normalized confidence value based on the received sigmoid parameters; and 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 the normalized confidence value. | 25. A non-transitory computer readable storage medium having stored thereon processor-executable software instructions configured to cause a processor of a of a computing device to perform operations comprising: receiving from a server computing device a full classifier model and sigmoid parameters; determining a normalized confidence value based on the received sigmoid parameters; and 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 the normalized confidence value. 27. The non-transitory computer readable storage medium of claim 25 , wherein the stored processor-executable instructions are configured to cause the processor to perform operations further comprising generating the lean classifier model based on the full classifier model. | 0.855026 |
8,830,200 | 3 | 8 | 3. The method according to claim 1 , comprising, absent detection of a further touch, reducing the size of the area associated with each character of the set of next characters with time at a rate dependent on a factor related to touch-sensitive display operation. | 3. The method according to claim 1 , comprising, absent detection of a further touch, reducing the size of the area associated with each character of the set of next characters with time at a rate dependent on a factor related to touch-sensitive display operation. 8. The method according to claim 3 , wherein reducing the size of the area associated with each character of the set of next characters at a rate dependent on a factor comprises reducing the size at a rate dependent on a previously entered string. | 0.562057 |
9,384,289 | 1 | 6 | 1. A method for determining a geographic location of a user, the method comprising: receiving a query at a search engine from the user searching an inverted index to identify one or more geographical locations associated with one or more terms of the received query, wherein the inverted index comprises plurality of listed query terms, each of which is associated with at least one geographic location and respective relevance score associated therewith, wherein each respective relevance score indicates a level of relevancy of a respective geographical location with the listed query term and is computed based on previously submitted search query terms by at least one user and whether the previously submitted search query terms corresponds to a location specific search query selecting one of the identified one or more geographic locations as the geographic location of the user based on relevance scores associated with the search query and whether the search query is a location specific search query. | 1. A method for determining a geographic location of a user, the method comprising: receiving a query at a search engine from the user searching an inverted index to identify one or more geographical locations associated with one or more terms of the received query, wherein the inverted index comprises plurality of listed query terms, each of which is associated with at least one geographic location and respective relevance score associated therewith, wherein each respective relevance score indicates a level of relevancy of a respective geographical location with the listed query term and is computed based on previously submitted search query terms by at least one user and whether the previously submitted search query terms corresponds to a location specific search query selecting one of the identified one or more geographic locations as the geographic location of the user based on relevance scores associated with the search query and whether the search query is a location specific search query. 6. The method of claim 1 , wherein said selecting comprises: displaying a heat map that shows the identified one or more geographical locations and indicates a relevance of each of the identified one or more geographical locations based on the relevance scores thereof. | 0.856915 |
9,135,571 | 9 | 11 | 9. Apparatus comprising: at least one processor; and at least one processor-readable storage medium storing processor-executable instructions that, when executed by the at least one processor, perform a method comprising: matching a token from at least a portion of a text string with a matching concept in an ontology, wherein the at least a portion of the text string has been labeled as corresponding to a particular entity type; identifying a first concept as being hierarchically related to the matching concept within the ontology; identifying a second concept as being hierarchically related to the first concept within the ontology; and training a statistical model to associate the first concept with a first probability of corresponding to the particular entity type and the second concept with a second probability of corresponding to the particular entity type, based at least in part on the labeling of the at least a portion of the text string as corresponding to the particular entity type. | 9. Apparatus comprising: at least one processor; and at least one processor-readable storage medium storing processor-executable instructions that, when executed by the at least one processor, perform a method comprising: matching a token from at least a portion of a text string with a matching concept in an ontology, wherein the at least a portion of the text string has been labeled as corresponding to a particular entity type; identifying a first concept as being hierarchically related to the matching concept within the ontology; identifying a second concept as being hierarchically related to the first concept within the ontology; and training a statistical model to associate the first concept with a first probability of corresponding to the particular entity type and the second concept with a second probability of corresponding to the particular entity type, based at least in part on the labeling of the at least a portion of the text string as corresponding to the particular entity type. 11. The apparatus of claim 9 , wherein the first concept is a parent concept of the matching concept within the ontology, and wherein the second concept is a parent concept of the first concept within the ontology. | 0.651466 |
7,823,058 | 1 | 6 | 1. An interactive, electronic method of authoring annotated traversals through visual data, the method comprising: displaying the visual data, wherein the visual data comprises motion video; interactively defining a traversal of the displayed visual data by positioning a resizable overlay window relative to the displayed visual data, wherein said resizable overlay window is resizable while the visual data is being displayed, said traversal comprising a subset of motion video that specifies a time-based sequence of frames of said motion video, each of said frames comprising the visual data delineated by the overlay window, wherein the displaying said visual data comprises displaying the visual data in a cylindrical layout, and wherein said positioning of the overlay window is defined by a field of view of a virtual camera located centrally to said cylindrical layout; annotating the traversal; storing a persistent record of the annotated traversal; and using an integrated graphical user interface to perform said method, and wherein said graphical user interface comprises a plurality of computer display regions including: an overview region displaying the visual data; a detail region displaying current data within the overlay window; and a worksheet region displaying a list of a plurality of stored annotated traversal records. | 1. An interactive, electronic method of authoring annotated traversals through visual data, the method comprising: displaying the visual data, wherein the visual data comprises motion video; interactively defining a traversal of the displayed visual data by positioning a resizable overlay window relative to the displayed visual data, wherein said resizable overlay window is resizable while the visual data is being displayed, said traversal comprising a subset of motion video that specifies a time-based sequence of frames of said motion video, each of said frames comprising the visual data delineated by the overlay window, wherein the displaying said visual data comprises displaying the visual data in a cylindrical layout, and wherein said positioning of the overlay window is defined by a field of view of a virtual camera located centrally to said cylindrical layout; annotating the traversal; storing a persistent record of the annotated traversal; and using an integrated graphical user interface to perform said method, and wherein said graphical user interface comprises a plurality of computer display regions including: an overview region displaying the visual data; a detail region displaying current data within the overlay window; and a worksheet region displaying a list of a plurality of stored annotated traversal records. 6. The method of claim 1 , wherein the displaying said visual data comprises displaying visual data in a rectangular layout. | 0.796721 |
8,892,422 | 1 | 9 | 1. A computer implemented method of identifying a phrase weighting of a sequence of words as a function of the position of words present in the sequence of words, comprising: identifying a sequence of words; determining, utilizing one or more processors, a centrality value for each of a plurality of identified words in the sequence of words, the centrality value for each of the identified words based on a co-occurrence consistency with other of the identified words in their respective relative positions in the sequence of words; and determining, utilizing one or more processors, a phrase weighting of the sequence of words based on the determined centrality value for each of the identified words, wherein the phrase weighting provides an indication of the likelihood that the sequence of words is a phrase. | 1. A computer implemented method of identifying a phrase weighting of a sequence of words as a function of the position of words present in the sequence of words, comprising: identifying a sequence of words; determining, utilizing one or more processors, a centrality value for each of a plurality of identified words in the sequence of words, the centrality value for each of the identified words based on a co-occurrence consistency with other of the identified words in their respective relative positions in the sequence of words; and determining, utilizing one or more processors, a phrase weighting of the sequence of words based on the determined centrality value for each of the identified words, wherein the phrase weighting provides an indication of the likelihood that the sequence of words is a phrase. 9. The method of claim 1 , wherein the co-occurrence consistency for each of the identified words with other of the identified words in their respective relative positions in the sequence of words factors in how much more likely than incidental it is for each of the identified words to co-occur with other identified words in their respective relative positions. | 0.81994 |
9,959,362 | 6 | 10 | 6. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions for: receiving an event trigger configured to report an event, the event trigger containing at least one attribute that provides context to the event; retrieving a weighting table corresponding to a logon user that describes a plurality of content tiles that are associated with the event, wherein a content tile from the plurality of content tiles includes a weighting value of a first weighting table column configured to represent the significance of the content tile, a second weighting table column identifies a library of the content tile, a third weighting table column provides a role of the logon user, and a fourth weighting table column provides an identifier to locate the content tile within the library; selecting a ranked list of content tiles from the weighting table to include in a landing page, wherein the ranked list includes the content tile and the position of the content tile in the ranked list is based on the weighting value, and wherein selecting the ranked list of content tiles comprises, identifying a condition of the content tile, the condition specifying a parameter used to query for content related to the content tile, determining that the condition is satisfied by the at least one attribute of the triggering event, and including the content tile as part of the ranked list of content tiles based on the determination; populating the content tile with content; generating the landing page that contains the content tile retrieved from the library; receiving an input from the logon user representative of deleting the content tile from the landing page; adjusting the weighting value of the content tile in the weighting table in response to the input, without propagating the weighting table to another weighting table corresponding to a different role of the logon user; and displaying on a changed landing page, another content tile replacing a size and a position of the content tile. | 6. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions for: receiving an event trigger configured to report an event, the event trigger containing at least one attribute that provides context to the event; retrieving a weighting table corresponding to a logon user that describes a plurality of content tiles that are associated with the event, wherein a content tile from the plurality of content tiles includes a weighting value of a first weighting table column configured to represent the significance of the content tile, a second weighting table column identifies a library of the content tile, a third weighting table column provides a role of the logon user, and a fourth weighting table column provides an identifier to locate the content tile within the library; selecting a ranked list of content tiles from the weighting table to include in a landing page, wherein the ranked list includes the content tile and the position of the content tile in the ranked list is based on the weighting value, and wherein selecting the ranked list of content tiles comprises, identifying a condition of the content tile, the condition specifying a parameter used to query for content related to the content tile, determining that the condition is satisfied by the at least one attribute of the triggering event, and including the content tile as part of the ranked list of content tiles based on the determination; populating the content tile with content; generating the landing page that contains the content tile retrieved from the library; receiving an input from the logon user representative of deleting the content tile from the landing page; adjusting the weighting value of the content tile in the weighting table in response to the input, without propagating the weighting table to another weighting table corresponding to a different role of the logon user; and displaying on a changed landing page, another content tile replacing a size and a position of the content tile. 10. The non-transitory computer readable storage medium of claim 6 , further comprising: receiving the input representative of deleting the content tile from the landing page; and adjusting the weighting value of the content tile in response to the input. | 0.623894 |
8,920,472 | 1 | 11 | 1. A system for correcting a spinal deformity, the system comprising: a first rod adapted to extend along a first side of a spine of a patient; a first anchor adapted to be fixed to a vertebra of the spine and to receive the first rod such that the first rod is secured against substantial lateral translation relative to the first anchor and the first rod is allowed to slide axially relative to the first anchor through a first pivot point and to change in at least two of pitch, yaw, and roll about the first pivot point during correction; a second anchor adapted to be fixed to a vertebra of the spine and to receive the first rod such that the first rod is secured against substantial lateral translation relative to the second anchor and is allowed to change in at least pitch and yaw about a second pivot point during correction; a second rod adapted to extend along a second side of the spine of the patient; a third anchor adapted to be fixed to a vertebra of the spine and to receive the second rod such that the second rod is secured against substantial lateral translation relative to the third anchor during correction and such that the second rod is secured against changes in pitch, yaw, roll, and axial sliding; a fourth anchor adapted to be fixed to a vertebra of the spine and to receive the second rod such that the second rod is secured against substantial lateral translation relative to the fourth anchor; and a lateral coupling adapted to extend between and laterally secure the first rod and the second rod such that the lateral coupling facilitates derotation and translation of the spine. | 1. A system for correcting a spinal deformity, the system comprising: a first rod adapted to extend along a first side of a spine of a patient; a first anchor adapted to be fixed to a vertebra of the spine and to receive the first rod such that the first rod is secured against substantial lateral translation relative to the first anchor and the first rod is allowed to slide axially relative to the first anchor through a first pivot point and to change in at least two of pitch, yaw, and roll about the first pivot point during correction; a second anchor adapted to be fixed to a vertebra of the spine and to receive the first rod such that the first rod is secured against substantial lateral translation relative to the second anchor and is allowed to change in at least pitch and yaw about a second pivot point during correction; a second rod adapted to extend along a second side of the spine of the patient; a third anchor adapted to be fixed to a vertebra of the spine and to receive the second rod such that the second rod is secured against substantial lateral translation relative to the third anchor during correction and such that the second rod is secured against changes in pitch, yaw, roll, and axial sliding; a fourth anchor adapted to be fixed to a vertebra of the spine and to receive the second rod such that the second rod is secured against substantial lateral translation relative to the fourth anchor; and a lateral coupling adapted to extend between and laterally secure the first rod and the second rod such that the lateral coupling facilitates derotation and translation of the spine. 11. The system of claim 1 , wherein the third anchor is adapted to secure the second rod at a desired position and to selectively secure the second rod against changes in pitch, yaw, roll, and axial sliding. | 0.741895 |
6,151,683 | 27 | 28 | 27. The apparatus as recited in claim 26 wherein the second data storage stores the component information as a plurality of tokens, each token including a value representing one aspect of the component information and an indication of an association with one of the elements in the static tree. | 27. The apparatus as recited in claim 26 wherein the second data storage stores the component information as a plurality of tokens, each token including a value representing one aspect of the component information and an indication of an association with one of the elements in the static tree. 28. The method as recited in claim 27 wherein the plurality of tokens are stored in the form of a hashtable. | 0.896947 |
10,042,539 | 11 | 13 | 11. The system of claim 10 , wherein the process further comprises: changing, in response to receiving a second user input requesting adjustment of the adjustable slide control, a characteristic of the default text contained in the text window without changing the width and the height of the text window. | 11. The system of claim 10 , wherein the process further comprises: changing, in response to receiving a second user input requesting adjustment of the adjustable slide control, a characteristic of the default text contained in the text window without changing the width and the height of the text window. 13. The system of claim 11 , wherein the text characteristic is a font size, and wherein the changing of the characteristic includes changing the font size from a first size to a second size that is different than the first size. | 0.5 |
8,280,882 | 8 | 15 | 8. A system for an author-centric search, the system including a processor and memory, the system comprising: means for initializing a first data structure and a second data structure for each of a plurality of documented communications wherein each of the plurality documented communications has at least one author to which the respective documented communication is attributed; means for utilizing the first data structure and the second data structure to compute a relevancy score for each of the plurality of documented communications; means for determining a score for each author of at least one of the plurality of documented communications based in part on the relevancy score for each of the plurality of documented communications authored by each respective author; means for prompting a user to enter a search string; means for parsing the search string into one or more words; means for filling at least one memory space of the first data structure for each documented communication with data based on the occurrence of the one or more words in the documented communication; means for filling at least one memory space of the second data structure for each documented communication with a weighted value for an author of a given documented communication that signifies a statistical preference for the data in the corresponding memory space of the first data structure; and means for executing a mathematical function based on an aggregate of the data and the weighted value of the first and second data structures for each documented communication in order to compute the relevancy score for the documented communication; and means for displaying search results based at least in part upon a ranked listing of the score determined for each of the authors, wherein the weighted value for an author comprises a predefined value utilized to create the statistical preference for data in the corresponding memory space of the first data structure, the weighted value for the author being determined based on at least two of: a time of publication for the documented communication, a number of documented communications having the given author, a prestige of the documented communications, and a number of authors for the documented communication. | 8. A system for an author-centric search, the system including a processor and memory, the system comprising: means for initializing a first data structure and a second data structure for each of a plurality of documented communications wherein each of the plurality documented communications has at least one author to which the respective documented communication is attributed; means for utilizing the first data structure and the second data structure to compute a relevancy score for each of the plurality of documented communications; means for determining a score for each author of at least one of the plurality of documented communications based in part on the relevancy score for each of the plurality of documented communications authored by each respective author; means for prompting a user to enter a search string; means for parsing the search string into one or more words; means for filling at least one memory space of the first data structure for each documented communication with data based on the occurrence of the one or more words in the documented communication; means for filling at least one memory space of the second data structure for each documented communication with a weighted value for an author of a given documented communication that signifies a statistical preference for the data in the corresponding memory space of the first data structure; and means for executing a mathematical function based on an aggregate of the data and the weighted value of the first and second data structures for each documented communication in order to compute the relevancy score for the documented communication; and means for displaying search results based at least in part upon a ranked listing of the score determined for each of the authors, wherein the weighted value for an author comprises a predefined value utilized to create the statistical preference for data in the corresponding memory space of the first data structure, the weighted value for the author being determined based on at least two of: a time of publication for the documented communication, a number of documented communications having the given author, a prestige of the documented communications, and a number of authors for the documented communication. 15. The system of claim 8 , wherein the means for displaying further comprising means for presenting an ordered list of the each of the authors ranked by the score associated with each of the authors. | 0.726027 |
10,121,493 | 12 | 13 | 12. The system of claim 9 , wherein the computer-readable instructions causing the system to be configured to provide the feedback includes at least one of: computer-readable instructions causing the system to be configured to request clarification on the identified portion of the first input, computer-readable instructions causing the system to be configured to suggest a completion of the received first input, and computer-readable instructions causing the system to be configured to repeat the portion of the first input to the user, so as to notify the user that the portion of the first input is potentially incorrectly recognized. | 12. The system of claim 9 , wherein the computer-readable instructions causing the system to be configured to provide the feedback includes at least one of: computer-readable instructions causing the system to be configured to request clarification on the identified portion of the first input, computer-readable instructions causing the system to be configured to suggest a completion of the received first input, and computer-readable instructions causing the system to be configured to repeat the portion of the first input to the user, so as to notify the user that the portion of the first input is potentially incorrectly recognized. 13. The system of claim 12 , wherein the request for clarification on the identified portion of the first input is based at least in part on a determination that a disfluency occurs after the user has provided the portion of the first input. | 0.510163 |
8,972,233 | 1 | 18 | 1. A method for relating measurable or observable characteristics of hydrocarbon source rocks to estimated conditions at the time of formation of the hydrocarbon source rocks, comprising: (a) selecting a first set of variables representing measurable or observable characteristics describing presence, quantity or quality of hydrocarbon source rocks; (b) selecting a second set of variables representing historical quantities that influence source rock formation, comprising at least one variable representing each of the following three types of influencing factors: (i) geologic age factors; (ii) paleogeographic factors; and (iii) paleoenvironmental conditions, said second set of variables being classifiable according to whether they affect rate of production, destruction or dilution of organic matter that forms hydrocarbon source rocks; (c) forming a network with nodes comprising both sets of variables, said network having directional links connecting causally-related nodes; (d) selecting one or more variables from either set to be unknowns and assigning at least one data value to each of the other variables along with associated probabilities of having the respective data values, said values and probabilities being estimated from measurement, observation or inferred indirectly; and (e) solving the network including the data and probability distributions for at least one of the one or more unknown variables using a Bayesian Network algorithm programmed on a computer and conservation of organic matter expressible as:
organic matter enrichment=production−(destruction+dilution) and downloading or saving results of solving the network to computer memory or storage. | 1. A method for relating measurable or observable characteristics of hydrocarbon source rocks to estimated conditions at the time of formation of the hydrocarbon source rocks, comprising: (a) selecting a first set of variables representing measurable or observable characteristics describing presence, quantity or quality of hydrocarbon source rocks; (b) selecting a second set of variables representing historical quantities that influence source rock formation, comprising at least one variable representing each of the following three types of influencing factors: (i) geologic age factors; (ii) paleogeographic factors; and (iii) paleoenvironmental conditions, said second set of variables being classifiable according to whether they affect rate of production, destruction or dilution of organic matter that forms hydrocarbon source rocks; (c) forming a network with nodes comprising both sets of variables, said network having directional links connecting causally-related nodes; (d) selecting one or more variables from either set to be unknowns and assigning at least one data value to each of the other variables along with associated probabilities of having the respective data values, said values and probabilities being estimated from measurement, observation or inferred indirectly; and (e) solving the network including the data and probability distributions for at least one of the one or more unknown variables using a Bayesian Network algorithm programmed on a computer and conservation of organic matter expressible as:
organic matter enrichment=production−(destruction+dilution) and downloading or saving results of solving the network to computer memory or storage. 18. The method of claim 1 , wherein the paleoenvironmental conditions comprise at least one of upwelling annual average, upwelling seasonality, upwelling range; and upwelling annual. | 0.789352 |
9,128,968 | 12 | 13 | 12. The system of claim 11 , wherein a string dictionary is associated with each column. | 12. The system of claim 11 , wherein a string dictionary is associated with each column. 13. The system of claim 12 , wherein a string dictionary index is assigned to a unique string in a column. | 0.5 |
8,897,634 | 5 | 11 | 5. A camera system comprising: (a) a camera that is operable to take and store pictures, and that includes: (i) a lens, (ii) an image sensor, (iii) at least one microphone, (iv) a voice recognizer, (v) a camera controller, (vi) a wireless network interface, and (vii) a touch sensitive display; (b) the camera controller including a control program having instructions to control and respond to the voice recognizer; (c) the voice recognizer coupled to the microphone and the camera controller, and configured to receive and process sounds into recognized words; (d) the camera further configured to maintain and store a plurality of recognizable words having different plain meanings and commonly associated with taking a picture, the recognition of any of which will cause the camera to take a picture; (e) wherein the voice recognizer is operable to receive a first and a second human sound spoken by the same person, and to recognize: (i) the first human sound as a first human spoken word from among the plurality, the recognized first human spoken word being assigned by the control program to be a command for the camera to take a picture, and (ii) the second human sound as a second human spoken word from among the plurality, the recognized second human spoken word being different from the first human spoken word and also assigned by the control program to be the same camera command to take a picture; (f) the camera controller configured to: (i) cause the camera to take a picture in response to the voice recognizer recognizing either the first or second human spoken word and to store the picture in a local memory in the camera; and (ii) automatically upload the picture stored in the local memory of the camera via the wireless network interface and an internet connection to a location at an internet picture hosting website as instructed by a user of the camera, but only if predetermined conditions are met, the predetermined conditions including at least the camera controller receiving: (1) an indication from the wireless network interface that the system can make an internet connection via the wireless network interface; and (2) an indication from the local memory that a user has elected an option to designate at least one picture stored in local memory to be uploaded to the internet picture hosting website. | 5. A camera system comprising: (a) a camera that is operable to take and store pictures, and that includes: (i) a lens, (ii) an image sensor, (iii) at least one microphone, (iv) a voice recognizer, (v) a camera controller, (vi) a wireless network interface, and (vii) a touch sensitive display; (b) the camera controller including a control program having instructions to control and respond to the voice recognizer; (c) the voice recognizer coupled to the microphone and the camera controller, and configured to receive and process sounds into recognized words; (d) the camera further configured to maintain and store a plurality of recognizable words having different plain meanings and commonly associated with taking a picture, the recognition of any of which will cause the camera to take a picture; (e) wherein the voice recognizer is operable to receive a first and a second human sound spoken by the same person, and to recognize: (i) the first human sound as a first human spoken word from among the plurality, the recognized first human spoken word being assigned by the control program to be a command for the camera to take a picture, and (ii) the second human sound as a second human spoken word from among the plurality, the recognized second human spoken word being different from the first human spoken word and also assigned by the control program to be the same camera command to take a picture; (f) the camera controller configured to: (i) cause the camera to take a picture in response to the voice recognizer recognizing either the first or second human spoken word and to store the picture in a local memory in the camera; and (ii) automatically upload the picture stored in the local memory of the camera via the wireless network interface and an internet connection to a location at an internet picture hosting website as instructed by a user of the camera, but only if predetermined conditions are met, the predetermined conditions including at least the camera controller receiving: (1) an indication from the wireless network interface that the system can make an internet connection via the wireless network interface; and (2) an indication from the local memory that a user has elected an option to designate at least one picture stored in local memory to be uploaded to the internet picture hosting website. 11. The camera system of claim 5 wherein the camera controller is configured with picture editing programming that enables a user to edit pictures stored in the local memory. | 0.628205 |
8,171,451 | 14 | 16 | 14. The method as claimed in claim 13 further comprising the steps of: receiving from the client application a request for rendering a selected report as defined by the WSDL definition; requesting rendering of the selected report; receiving rendered results; generates a generalized model of the rendered results; selecting relevant objects from the generalized model based on information in the WSDL definition; formatting representation of the relevant objects; and transporting the formatted objects to the client application as the requested report content of the selected report. | 14. The method as claimed in claim 13 further comprising the steps of: receiving from the client application a request for rendering a selected report as defined by the WSDL definition; requesting rendering of the selected report; receiving rendered results; generates a generalized model of the rendered results; selecting relevant objects from the generalized model based on information in the WSDL definition; formatting representation of the relevant objects; and transporting the formatted objects to the client application as the requested report content of the selected report. 16. The method as recited in claim 14 , wherein the formatting step comprises one of the steps of: formatting the relevant objects in Extensible Markup Language (XML); formatting the relevant objects in Hypertext Markup Language (HTML); formatting the relevant objects in HTML fragments; formatting the relevant objects in images; and formatting the relevant objects in a print-friendly format. | 0.536471 |
8,769,484 | 3 | 4 | 3. A computer program product comprising a non-transitory computer useable recordable storage medium having computer useable program code for enabling a method for Service-Oriented Architecture (SOA) process decomposition and service modeling, said computer program product including: computer useable program code for packaging said method for SOA process decomposition and service modeling; computer useable program code for facilitating lifecycle management of modeling assets by taking into account an enablement lifecycle of a meta-data model to determine changes to the meta-data model, wherein the meta-data model models data elements that are used to represent and operate objects and a relationship among the objects, and the enablement lifecycle of the meta data model comprises a model deployment component, a model maintenance component and a model instantiation component, and model maintenance takes place both during model deployment and during model instantiation, and wherein said model maintenance comprises modifying existing modeling assets of the meta-data model while maintaining an underlying structure of the meta-data model, and adding new modeling assets to the meta-data model and making corresponding changes to the underlying structure of the meta-data model when adding the new modeling assets; and computer useable program code for facilitating maintenance of said existing and new modeling assets, wherein the computer useable program code for packaging said method for SOA process decomposition and service modeling comprises: computer useable program code for customizing a modeling template from the meta-data model for at least one industry-specific application; and computer useable program code for instantiating the modeling template for validating an SOA solution. | 3. A computer program product comprising a non-transitory computer useable recordable storage medium having computer useable program code for enabling a method for Service-Oriented Architecture (SOA) process decomposition and service modeling, said computer program product including: computer useable program code for packaging said method for SOA process decomposition and service modeling; computer useable program code for facilitating lifecycle management of modeling assets by taking into account an enablement lifecycle of a meta-data model to determine changes to the meta-data model, wherein the meta-data model models data elements that are used to represent and operate objects and a relationship among the objects, and the enablement lifecycle of the meta data model comprises a model deployment component, a model maintenance component and a model instantiation component, and model maintenance takes place both during model deployment and during model instantiation, and wherein said model maintenance comprises modifying existing modeling assets of the meta-data model while maintaining an underlying structure of the meta-data model, and adding new modeling assets to the meta-data model and making corresponding changes to the underlying structure of the meta-data model when adding the new modeling assets; and computer useable program code for facilitating maintenance of said existing and new modeling assets, wherein the computer useable program code for packaging said method for SOA process decomposition and service modeling comprises: computer useable program code for customizing a modeling template from the meta-data model for at least one industry-specific application; and computer useable program code for instantiating the modeling template for validating an SOA solution. 4. The computer program product of claim 3 , wherein the computer useable program code for packaging said method for SOA process decomposition and service modeling further comprises: computer useable program code for providing a general framework for consulting services to build value-added services. | 0.5 |
8,321,471 | 1 | 8 | 1. A method of forming a target error model to facilitate spell checking input text related to a target data collection comprising steps of: a) providing a source query log containing user queries to at least one source data collection; b) generating target relational data based on the source query log including corrective substring suggestions that relate to the target data collection and corresponding misspelled substrings for the corrective substring suggestions extracted from the source query log, by applying a source error model to the source query log to thereby generate source relational data including corrective substring suggestions for misspelled substrings of the source query log, and selecting a subset of the source relational data that relate to the target data collection as the target relational data; c) building a target error model using the target relational data including target statistical occurrence data for the substrings of the target relational data derived from the source query log; and d) storing the target error model on a computer readable medium. | 1. A method of forming a target error model to facilitate spell checking input text related to a target data collection comprising steps of: a) providing a source query log containing user queries to at least one source data collection; b) generating target relational data based on the source query log including corrective substring suggestions that relate to the target data collection and corresponding misspelled substrings for the corrective substring suggestions extracted from the source query log, by applying a source error model to the source query log to thereby generate source relational data including corrective substring suggestions for misspelled substrings of the source query log, and selecting a subset of the source relational data that relate to the target data collection as the target relational data; c) building a target error model using the target relational data including target statistical occurrence data for the substrings of the target relational data derived from the source query log; and d) storing the target error model on a computer readable medium. 8. The method of claim 1 , wherein the building step c) includes providing a searchable lexicon data structure. | 0.721106 |
10,061,831 | 10 | 13 | 10. A system for reference partitioning database objects by values in a reference field, the system comprising: at least one hardware processor; at least one database environment, the database environment supporting triggers and partitioning; at least one application program; and memory storing: a reference field metadata framework that: identifies classes in a hierarchy of database objects, identifies at least one class as a root of the hierarchy, identifies, for each non-root class, a reference field inheritance function for the class, and identifies, for each parent class-child class pair in the hierarchy, a relation-join query, the relation-join query being a join between tables in the database environment onto which the parent class and child class are persisted, and triggers that use the framework to maintain values for the reference field for non-root database objects, including at least a first trigger invoked after a reference field of a database object in a root class is changed, a second trigger invoked responsive to a non-root database object being inserted, and a third trigger invoked responsive to a non-root database object having a change in parent. | 10. A system for reference partitioning database objects by values in a reference field, the system comprising: at least one hardware processor; at least one database environment, the database environment supporting triggers and partitioning; at least one application program; and memory storing: a reference field metadata framework that: identifies classes in a hierarchy of database objects, identifies at least one class as a root of the hierarchy, identifies, for each non-root class, a reference field inheritance function for the class, and identifies, for each parent class-child class pair in the hierarchy, a relation-join query, the relation-join query being a join between tables in the database environment onto which the parent class and child class are persisted, and triggers that use the framework to maintain values for the reference field for non-root database objects, including at least a first trigger invoked after a reference field of a database object in a root class is changed, a second trigger invoked responsive to a non-root database object being inserted, and a third trigger invoked responsive to a non-root database object having a change in parent. 13. The system of claim 10 , wherein the third trigger uses the reference field metadata framework to: determine a value for the reference field of each parent database object of the non-root database object; apply the reference field inheritance function for the class of the non-root database object to determine a value for the reference field of the non-root database object, wherein the database object is assigned to a partition according to the value; assign the non-root database object to a partition according to the determined value; traverse the hierarchy from the non-root database object downwards, avoiding cycles; and set a lifecycle state of each object reached in the traversal according to the reference field inheritance function for a class of the object reached in the traversal. | 0.5 |
6,108,656 | 25 | 28 | 25. The computer system of claim 22 wherein said target server computer comprises means for accessing a lookup table, said lookup table for storing a decryption key associated with said source identifier data string, to obtain said decryption key associated with said source identifier data string, and means for decrypting, utilizing said decryption key, said encrypted user information received from said client computer. | 25. The computer system of claim 22 wherein said target server computer comprises means for accessing a lookup table, said lookup table for storing a decryption key associated with said source identifier data string, to obtain said decryption key associated with said source identifier data string, and means for decrypting, utilizing said decryption key, said encrypted user information received from said client computer. 28. The computer system of claim 25 wherein said user information comprises a credit card number associated with said user of said client computer, and wherein said client computer further comprises means for executing on online electronic commercial transaction by utilizing said credit card number. | 0.5 |
9,489,446 | 1 | 5 | 1. A computer-implemented method for generating a training set for use during document review, comprising: assigning classification codes to a set of documents; receiving further classification codes assigned to the same set of documents; comparing the classification code for at least one document with the further classification code for that document; determining whether a disagreement exists between the assigned classification code and the further classification code for at least one document; identifying those documents with disagreeing classification codes as training set candidates; applying a stop threshold to the training set candidates, wherein the stop threshold comprises one of a percentage of disagreement, a number of documents with disagreeing classifications, and a zero-defect test; and designating the training set candidates as a training set when the stop threshold is satisfied. | 1. A computer-implemented method for generating a training set for use during document review, comprising: assigning classification codes to a set of documents; receiving further classification codes assigned to the same set of documents; comparing the classification code for at least one document with the further classification code for that document; determining whether a disagreement exists between the assigned classification code and the further classification code for at least one document; identifying those documents with disagreeing classification codes as training set candidates; applying a stop threshold to the training set candidates, wherein the stop threshold comprises one of a percentage of disagreement, a number of documents with disagreeing classifications, and a zero-defect test; and designating the training set candidates as a training set when the stop threshold is satisfied. 5. A method according to claim 1 , further comprising: automatically classifying documents when a disagreement between the assigned classification code and the further classification code for the at least one document does not exist. | 0.5 |
6,101,492 | 6 | 7 | 6. The index generator of claim 5, wherein the statistical knowledge base is generated by operation on a restricted training corpus to generate statistical knowledge about the words of the corpus for storage in the statistical knowledge base. | 6. The index generator of claim 5, wherein the statistical knowledge base is generated by operation on a restricted training corpus to generate statistical knowledge about the words of the corpus for storage in the statistical knowledge base. 7. The index generator of claim 6, wherein the derivational generator includes a set of transducers for producing derivatives of each word of the disambiguated corpus. | 0.5 |
9,129,448 | 6 | 7 | 6. The method according to claim 1 , wherein the semantic analysis is performed automatically. | 6. The method according to claim 1 , wherein the semantic analysis is performed automatically. 7. The method according to claim 6 , further comprising editing the results of the automatic semantic analysis manually by a user. | 0.5 |
4,525,860 | 4 | 5 | 4. The invention set forth in claim 1 wherein said traversing rules comprise the steps of determining a node having a fork thereat determining at said node a next adjacent branch of said character, and traversing said character along said branch of said character starting from said node and moving along said branch. | 4. The invention set forth in claim 1 wherein said traversing rules comprise the steps of determining a node having a fork thereat determining at said node a next adjacent branch of said character, and traversing said character along said branch of said character starting from said node and moving along said branch. 5. The invention set forth in claim 4 wherein said next branch determining step includes the steps of establishing a direction pointing toward a last traversed node, and starting from said direction finding a next untraversed node in a clockwise direction. | 0.5 |
8,510,101 | 1 | 4 | 1. A computerized auditing method comprising: receiving, via a processor, a data file comprising one or more auditable items, each auditable item being a line item from an insurance demand file and comprising a word string having one or more words; translating, using the processor, each word string for each auditable item into a translated part item identifier via a part translator having a first parts translator and a second parts translator, wherein the first parts translator and the second parts translator are both configured to receive each said word string for each auditable item and wherein the second parts translator is different from the first parts translator; comparing, using the processor, each translated part item identifier to a plurality of terms to generate matching information; associating, using the processor, each translated part item identifier with an item identifier based on the matching information; and accepting, using the processor, or rejecting each auditable item based on the item identifier, wherein the first parts translator is adapted to translate the word string by performing text matching, and wherein the second parts translator is adapted to translate the word string by searching a build table to generate a relationship between the one or more words of the word string based on the relative position of parts in a vehicle, and wherein the build table comprises one or more index words, each index word being associated with index information, wherein the index information comprises noun information, adjective information, build number, and orientation information, from which the relationship is based upon. | 1. A computerized auditing method comprising: receiving, via a processor, a data file comprising one or more auditable items, each auditable item being a line item from an insurance demand file and comprising a word string having one or more words; translating, using the processor, each word string for each auditable item into a translated part item identifier via a part translator having a first parts translator and a second parts translator, wherein the first parts translator and the second parts translator are both configured to receive each said word string for each auditable item and wherein the second parts translator is different from the first parts translator; comparing, using the processor, each translated part item identifier to a plurality of terms to generate matching information; associating, using the processor, each translated part item identifier with an item identifier based on the matching information; and accepting, using the processor, or rejecting each auditable item based on the item identifier, wherein the first parts translator is adapted to translate the word string by performing text matching, and wherein the second parts translator is adapted to translate the word string by searching a build table to generate a relationship between the one or more words of the word string based on the relative position of parts in a vehicle, and wherein the build table comprises one or more index words, each index word being associated with index information, wherein the index information comprises noun information, adjective information, build number, and orientation information, from which the relationship is based upon. 4. The method of claim 1 , further comprising: unsuccessfully associating a translated part item identifier with a single item identifier; and associating the translated part item identifier with a plurality of item identifiers. | 0.677054 |
9,699,145 | 16 | 18 | 16. A computer program product comprising a non-transitory computer-readable storage medium having program code embodied therewith, the program code executable by at least one hardware processor to: receive input from a user with respect to masking of a data element in one or more documents of a java script object notation (JSON) type, said one or more documents each comprise a hierarchy of at least two levels identified by name-value pairs, wherein the input comprises: (i) an identifier of the data element, and (ii) one or more constraints for masking the data element based on the hierarchy of the one or more documents of the JSON-type, said one or more constraints defines the masking with respect to a level of the at least two levels; and generate a masking rule for the one or more documents of the JSON-type based on the input, wherein the masking rule is generated automatically upon completion of the masking rule being defined by the input; wherein the generating of the masking rule comprises generating a script; and the enforcing of the masking rule on the document comprises executing the script on the document. | 16. A computer program product comprising a non-transitory computer-readable storage medium having program code embodied therewith, the program code executable by at least one hardware processor to: receive input from a user with respect to masking of a data element in one or more documents of a java script object notation (JSON) type, said one or more documents each comprise a hierarchy of at least two levels identified by name-value pairs, wherein the input comprises: (i) an identifier of the data element, and (ii) one or more constraints for masking the data element based on the hierarchy of the one or more documents of the JSON-type, said one or more constraints defines the masking with respect to a level of the at least two levels; and generate a masking rule for the one or more documents of the JSON-type based on the input, wherein the masking rule is generated automatically upon completion of the masking rule being defined by the input; wherein the generating of the masking rule comprises generating a script; and the enforcing of the masking rule on the document comprises executing the script on the document. 18. The computer program product of claim 16 , wherein the generating of the masking rule comprises generating a script. | 0.72973 |
7,836,428 | 16 | 19 | 16. The computer readable storage device of claim 13 , wherein said call function structure comprises a call to a non-declarative function. | 16. The computer readable storage device of claim 13 , wherein said call function structure comprises a call to a non-declarative function. 19. The computer readable storage device of claim 16 , wherein said call to said non-declarative function comprises a call to an external procedure. | 0.5 |
7,983,917 | 1 | 2 | 1. A method for reducing a search space for a recognition grammar used when interpreting natural language speech utterances, the method comprising: creating a phonemic representation of acoustic elements associated with an acoustic speech model, the acoustic elements including at least an unstressed central vowel and plurality of phonemic elements; representing syllables associated with the acoustic speech model using the phonemic representation, each of the represented syllables including a series of acoustic elements; constructing, via an electronic device, an acoustic grammar that contains transitions between the acoustic elements of the represented syllables, the transitions constrained according to phonotactic rules of the acoustic speech model; and using the unstressed central vowel as a linking element between sequential phonemic elements contained in the constructed acoustic grammar. | 1. A method for reducing a search space for a recognition grammar used when interpreting natural language speech utterances, the method comprising: creating a phonemic representation of acoustic elements associated with an acoustic speech model, the acoustic elements including at least an unstressed central vowel and plurality of phonemic elements; representing syllables associated with the acoustic speech model using the phonemic representation, each of the represented syllables including a series of acoustic elements; constructing, via an electronic device, an acoustic grammar that contains transitions between the acoustic elements of the represented syllables, the transitions constrained according to phonotactic rules of the acoustic speech model; and using the unstressed central vowel as a linking element between sequential phonemic elements contained in the constructed acoustic grammar. 2. The method of claim 1 , the series of acoustic elements defining an onset, a nucleus, and a coda for a given one of the represented syllables. | 0.5 |
6,130,665 | 4 | 5 | 4. A data input and display device comprising: a screen which allows for the input and output of information; the screen comprising two levels: a first level displaying a virtual alphanumeric keypad for allowing a user to input information; and a second level for displaying the information associated with the user input; wherein the user-input information and the virtual keypad are displayed using different attributes; and a touch key for allowing a user swap display levels. | 4. A data input and display device comprising: a screen which allows for the input and output of information; the screen comprising two levels: a first level displaying a virtual alphanumeric keypad for allowing a user to input information; and a second level for displaying the information associated with the user input; wherein the user-input information and the virtual keypad are displayed using different attributes; and a touch key for allowing a user swap display levels. 5. The data input and display device according to claim 4 wherein the different attributes are different colors. | 0.616438 |
9,721,010 | 1 | 14 | 1. A method of annotating content based upon user reaction data, comprising: detecting first user reaction data associated with a first portion of the content, the detecting including firstly detecting a presence of metadata of the content that specifies a probability of a user reaction to the first portion of the content, secondly, after the detecting, determining whether the probability of a user reaction to the first portion of that content exceeds a threshold, and thirdly, after the detecting and a result of the determining is affirmative, utilizing a first sensor to detect the first user reaction data, so that the first sensor is used to detect the first user reaction data only after a result of the determining is affirmative; and annotating the first portion of the content with a first reaction annotation based upon the first user reaction data. | 1. A method of annotating content based upon user reaction data, comprising: detecting first user reaction data associated with a first portion of the content, the detecting including firstly detecting a presence of metadata of the content that specifies a probability of a user reaction to the first portion of the content, secondly, after the detecting, determining whether the probability of a user reaction to the first portion of that content exceeds a threshold, and thirdly, after the detecting and a result of the determining is affirmative, utilizing a first sensor to detect the first user reaction data, so that the first sensor is used to detect the first user reaction data only after a result of the determining is affirmative; and annotating the first portion of the content with a first reaction annotation based upon the first user reaction data. 14. The method of claim 1 , further comprising: aggregating annotation data associated with the content from a plurality of users to generate aggregated annotation data; and responsive to receiving a reaction search through a search interface, providing at least a portion of the content corresponding to the reaction search based upon the aggregated annotation data. | 0.5 |
8,090,669 | 1 | 3 | 1. A computer-implemented data correction system, comprising: one or more memories operatively coupled to one or more processors providing: an adaptive learning component for learning an updated error correction model based on input actions related to correction of data, the adaptive learning component includes one or more adaptive learning algorithms reducing a score adjustment to a model as more data is retrieved and capping the score adjustment using upper and lower limits; and a quality component for computing effectiveness of the adaptive learning component for learning the updated error correction model. | 1. A computer-implemented data correction system, comprising: one or more memories operatively coupled to one or more processors providing: an adaptive learning component for learning an updated error correction model based on input actions related to correction of data, the adaptive learning component includes one or more adaptive learning algorithms reducing a score adjustment to a model as more data is retrieved and capping the score adjustment using upper and lower limits; and a quality component for computing effectiveness of the adaptive learning component for learning the updated error correction model. 3. The system of claim 1 , wherein the quality component employs a corpus of original text and annotated text for processing through a correction tool to check quality of the updated error correction model, the quality defines the effectiveness of the adaptive learning component. | 0.5 |
7,702,623 | 1 | 8 | 1. A method comprising: generating a cursor for a previous query; wherein generating the cursor for the previous query includes generating an execution plan for the previous query that is based, at least in part, on a first characteristic that is present at a time when the cursor is generated for the previous query; wherein the first characteristic reflects at least one factor, independent of the previous query itself, that has an effect on the execution plan produced for the previous query; storing, in association with the cursor, first data that indicates the first characteristic; receiving a current query; in response to receiving the current query, determining whether the current query is semantically equivalent to the previous query; determining second data that indicates a second characteristic, present at a time when the current query is processed, that would have an effect on an execution plan of the current query if such an execution plan were to be generated for the current query; wherein the second characteristic reflects at least one factor independent of the current query itself; performing a comparison between the first data and the second data; when the current query is semantically equivalent to the previous query, determining, based on the comparison of the first data and the second data, whether compiling the current query would produce an execution plan that satisfies certain criteria; and in response to determining that compiling the current query would produce an execution plan that satisfies the certain criteria, executing the current query using the cursor that was previously generated for the previous query. | 1. A method comprising: generating a cursor for a previous query; wherein generating the cursor for the previous query includes generating an execution plan for the previous query that is based, at least in part, on a first characteristic that is present at a time when the cursor is generated for the previous query; wherein the first characteristic reflects at least one factor, independent of the previous query itself, that has an effect on the execution plan produced for the previous query; storing, in association with the cursor, first data that indicates the first characteristic; receiving a current query; in response to receiving the current query, determining whether the current query is semantically equivalent to the previous query; determining second data that indicates a second characteristic, present at a time when the current query is processed, that would have an effect on an execution plan of the current query if such an execution plan were to be generated for the current query; wherein the second characteristic reflects at least one factor independent of the current query itself; performing a comparison between the first data and the second data; when the current query is semantically equivalent to the previous query, determining, based on the comparison of the first data and the second data, whether compiling the current query would produce an execution plan that satisfies certain criteria; and in response to determining that compiling the current query would produce an execution plan that satisfies the certain criteria, executing the current query using the cursor that was previously generated for the previous query. 8. The method of claim 1 , wherein: the first characteristic is a first selectivity of a predicate in the previous query; the first selectivity indicates at least an estimate of a percentage of data items in a database object that satisfy the predicate in the previous query; and the second characteristic is a second selectivity of a predicate in the current query; and the second selectivity indicates at least an estimate of a percentage of data items in the database object that satisfy the predicate in the current query. | 0.5 |
9,665,826 | 15 | 16 | 15. One or more computer-readable storage devices or memory devices comprising device-readable instructions which, upon execution perform operations comprising: processing a plurality of bug reports; identifying a plurality of phrases that are repeated in a bug report from the plurality of bug reports; selecting a first phrase from the plurality of phrases to keep and a second phrase from the plurality of phrases to drop based on a meaning of the first phrase being greater in significance in the bug report than a meaning of the second phrase; mapping the first phrase to one or more of a plurality of classes of an ontology model associated with the bug report, the ontology model defining valid interactions between the plurality of classes; determining whether the first phrase corresponds to a valid interaction defined by the ontology model; and based on determining the first phrase corresponds to a valid interaction defined by the ontology model, generating an output corresponding to the first phrase. | 15. One or more computer-readable storage devices or memory devices comprising device-readable instructions which, upon execution perform operations comprising: processing a plurality of bug reports; identifying a plurality of phrases that are repeated in a bug report from the plurality of bug reports; selecting a first phrase from the plurality of phrases to keep and a second phrase from the plurality of phrases to drop based on a meaning of the first phrase being greater in significance in the bug report than a meaning of the second phrase; mapping the first phrase to one or more of a plurality of classes of an ontology model associated with the bug report, the ontology model defining valid interactions between the plurality of classes; determining whether the first phrase corresponds to a valid interaction defined by the ontology model; and based on determining the first phrase corresponds to a valid interaction defined by the ontology model, generating an output corresponding to the first phrase. 16. The one or more computer-readable storage devices or memory devices of claim 15 , wherein selecting the first phrase further comprises performing pattern extraction on the plurality of bug reports to obtain at least a portion of the first phrase. | 0.774368 |
9,558,170 | 4 | 6 | 4. The method of claim 1 , wherein providing the first view of the collection further comprises determining at least one of a view priority, a column order, a date filter, a column filter, a current zoom factor, a label priority, a sort order and a column width. | 4. The method of claim 1 , wherein providing the first view of the collection further comprises determining at least one of a view priority, a column order, a date filter, a column filter, a current zoom factor, a label priority, a sort order and a column width. 6. The method of claim 4 , wherein determining the column filter further comprises classifying the image data in a column to clusters and filtering the column using the clusters. | 0.572115 |
8,635,201 | 5 | 8 | 5. At least one non-transitory computer readable medium having encoded thereon instructions which, when executed by at least one computer, perform a method comprising acts of: (A) receiving a query from a device and location data indicating a location of the device, the location data having a level of specificity; (B) in response to the query being received, identifying at least one first search engine to which to submit a representation of the query and information indicating the location of the device; (C) determining whether the level of specificity of the location data received in (A) is sufficient for the at least one first search engine; (D) when the level of specificity of the location data is sufficient, instructing the device to issue the representation of the query to the at least one first search engine; and (E) when the level of specificity of the location data is not sufficient, instructing the device to send, to the at least one computer, location data at a greater level of specificity, wherein the act (C) comprises determining that the level of specificity of the location data received in (A) is not sufficient for the at least one first search engine, and wherein the method further comprises acts of: (F) receiving location data at the greater level of specificity; and (G) instructing the device to submit a representation of the query and information specifying the location of the device at the greater level of specificity to the at least one first search engine. | 5. At least one non-transitory computer readable medium having encoded thereon instructions which, when executed by at least one computer, perform a method comprising acts of: (A) receiving a query from a device and location data indicating a location of the device, the location data having a level of specificity; (B) in response to the query being received, identifying at least one first search engine to which to submit a representation of the query and information indicating the location of the device; (C) determining whether the level of specificity of the location data received in (A) is sufficient for the at least one first search engine; (D) when the level of specificity of the location data is sufficient, instructing the device to issue the representation of the query to the at least one first search engine; and (E) when the level of specificity of the location data is not sufficient, instructing the device to send, to the at least one computer, location data at a greater level of specificity, wherein the act (C) comprises determining that the level of specificity of the location data received in (A) is not sufficient for the at least one first search engine, and wherein the method further comprises acts of: (F) receiving location data at the greater level of specificity; and (G) instructing the device to submit a representation of the query and information specifying the location of the device at the greater level of specificity to the at least one first search engine. 8. The at least one non-transitory computer readable medium of claim 5 , wherein the act (C) is performed based at least in part on predefined specificity requirements of the at least one first search engine. | 0.5 |
7,580,831 | 1 | 8 | 1. A healthcare dictionary system providing a term repository accessible for use in supporting the operation of a healthcare enterprise, comprising: an input processor for acquiring healthcare transaction message data including data for communication from a first healthcare facility to at least a second different healthcare facility in at least one of a plurality of different communication protocol data formats and being communicated between different facilities of a healthcare enterprise; a data processor for, parsing said acquired transaction message data to identify a communication protocol data format of said transaction message and extracting a term from said acquired transaction message data, comparing said extracted term to terms in a first term repository, said first term repository including at least one of, (a) definitions indicating meaning of a plurality of healthcare terms used by a particular healthcare facility and (b) synonyms of a plurality of healthcare terms used by a particular healthcare facility and updating said first term repository to include said extracted term in response to a determination, said extracted term is absent from said first term repository; and a communication processor for intermittently processing content of said first term repository to be suitable for communication to a second term repository including definitions of a plurality of healthcare terms used by a different healthcare facility. | 1. A healthcare dictionary system providing a term repository accessible for use in supporting the operation of a healthcare enterprise, comprising: an input processor for acquiring healthcare transaction message data including data for communication from a first healthcare facility to at least a second different healthcare facility in at least one of a plurality of different communication protocol data formats and being communicated between different facilities of a healthcare enterprise; a data processor for, parsing said acquired transaction message data to identify a communication protocol data format of said transaction message and extracting a term from said acquired transaction message data, comparing said extracted term to terms in a first term repository, said first term repository including at least one of, (a) definitions indicating meaning of a plurality of healthcare terms used by a particular healthcare facility and (b) synonyms of a plurality of healthcare terms used by a particular healthcare facility and updating said first term repository to include said extracted term in response to a determination, said extracted term is absent from said first term repository; and a communication processor for intermittently processing content of said first term repository to be suitable for communication to a second term repository including definitions of a plurality of healthcare terms used by a different healthcare facility. 8. A system according to claim 1 , wherein said transaction message data comprises at least one of, (a) a communication involving a healthcare enterprise laboratory, (b) a communication involving a healthcare enterprise pharmacy, (c) a communication involving a healthcare enterprise radiology department, (d) a communication involving a healthcare enterprise modality department, (e) a communication involving a healthcare enterprise administration operation and (f) a communication involving a healthcare enterprise orders or results management operation. | 0.5 |
8,356,030 | 1 | 2 | 1. A method of constructing a domain-specific sentiment classifier for classifying sentiment expressed by documents in a specified domain, comprising: scoring sentiments expressed by one or more domain-specific documents, the scoring comprising: determining that one or more of the domain-specific documents include an n-gram, calculating a score for the n-gram included in the one or more domain-specific documents, and calculating a sentiment score for the one or more domain-specific documents based on the score for the n-gram included in the documents; creating a domain-specific sentiment lexicon based at least in part on said scoring sentiments expressed by one or more domain-specific documents; generating the domain-specific sentiment classifier based on the domain-specific sentiment lexicon; and storing the domain-specific sentiment classifier. | 1. A method of constructing a domain-specific sentiment classifier for classifying sentiment expressed by documents in a specified domain, comprising: scoring sentiments expressed by one or more domain-specific documents, the scoring comprising: determining that one or more of the domain-specific documents include an n-gram, calculating a score for the n-gram included in the one or more domain-specific documents, and calculating a sentiment score for the one or more domain-specific documents based on the score for the n-gram included in the documents; creating a domain-specific sentiment lexicon based at least in part on said scoring sentiments expressed by one or more domain-specific documents; generating the domain-specific sentiment classifier based on the domain-specific sentiment lexicon; and storing the domain-specific sentiment classifier. 2. The method of claim 1 , wherein scoring sentiments expressed by one or more domain-specific documents is based on a domain-independent sentiment lexicon, the method further comprising: establishing the domain-independent sentiment lexicon by specifying a magnitude and polarity of sentiment expressed by each of a plurality of n-grams drawn from a domain-independent source. | 0.659747 |
9,383,970 | 15 | 19 | 15. A method executed by a processor of a computing device, the method comprising: receiving structured data and unstructured data pertaining to development, maintenance, or support of a computer-readable code from a plurality of computing devices that are remotely located from one another, the structured data comprising: a bug report for a detected bug in the software application; and a memory dump; the unstructured data comprising an email authored by a developer of the software application; assigning version information to the structured data and the unstructured data upon receipt of the structured data and the unstructured data; formatting the structured data and the unstructured data in accordance with at least one schema, thereby causing the structured data and the unstructured data to be stored as canonical data that is distributed across data repositories in a common access format; and executing an analytic process over the canonical data stored in the common access format to generate a relationship graph that is indicative of relationships between items in the structured data and the unstructured data, wherein executing the analytic process comprises accessing a plurality of predefined libraries. | 15. A method executed by a processor of a computing device, the method comprising: receiving structured data and unstructured data pertaining to development, maintenance, or support of a computer-readable code from a plurality of computing devices that are remotely located from one another, the structured data comprising: a bug report for a detected bug in the software application; and a memory dump; the unstructured data comprising an email authored by a developer of the software application; assigning version information to the structured data and the unstructured data upon receipt of the structured data and the unstructured data; formatting the structured data and the unstructured data in accordance with at least one schema, thereby causing the structured data and the unstructured data to be stored as canonical data that is distributed across data repositories in a common access format; and executing an analytic process over the canonical data stored in the common access format to generate a relationship graph that is indicative of relationships between items in the structured data and the unstructured data, wherein executing the analytic process comprises accessing a plurality of predefined libraries. 19. The method of claim 15 , further comprising: executing a query over the relationship graph; and outputting a ranked list of bug data for the computer-executable application responsive to executing the query over the relationship graph. | 0.635671 |
9,195,632 | 11 | 24 | 11. A computer-implemented method comprising: storing, in a social networking system, a brand page associated with an entity; storing one or more user profiles of users of the social networking system and a set of connections among the users, each user profile including information corresponding to at least one user interest, and wherein one or more of the user profiles includes a connection to the brand page, the information of each user profile including at least one affinity corresponding to the at least one user interest; receiving, from the entity, a plurality of content items for posting to the brand page, at least one of the plurality of content items including an additional content message for accessing one or more additional content items, and another at least one of the plurality of content items including at least one of: information about the entity associated with the brand page, information about a brand of the brand page, and information about a product associated with a brand of the brand page; receiving, from the entity, an association between each content item of the plurality with one or more keywords describing at least one of the brand of the brand page and the information about the product associated with the brand of the brand page, each of the one or more keywords defined by the entity; receiving, at the social networking system, a request to view the brand page from a user having a user profile connected to the brand page stored in the social networking system; accessing the user profile of the social networking system, the user profile associated with the user requesting to view the brand page; selecting, by the social networking system, content items from the plurality of content items, the selecting based on: an affinity of the at least one affinity, the affinity between the at least one user interest and the content items; the one or more keywords associated with each of the plurality of content items, and the information corresponding to the at least one user interest in the user profile associated with the user requesting to view the brand page, wherein at least one of the selected content items includes the additional content message for accessing additional content items; generating, using the selected content items, a personalized representation of the brand page for display in the social networking system to the user requesting to view the brand page, the personalized representation of the brand page containing one or more of the selected content items; and sending the generated personalized representation of the brand page for display to the user requesting to view the brand page. | 11. A computer-implemented method comprising: storing, in a social networking system, a brand page associated with an entity; storing one or more user profiles of users of the social networking system and a set of connections among the users, each user profile including information corresponding to at least one user interest, and wherein one or more of the user profiles includes a connection to the brand page, the information of each user profile including at least one affinity corresponding to the at least one user interest; receiving, from the entity, a plurality of content items for posting to the brand page, at least one of the plurality of content items including an additional content message for accessing one or more additional content items, and another at least one of the plurality of content items including at least one of: information about the entity associated with the brand page, information about a brand of the brand page, and information about a product associated with a brand of the brand page; receiving, from the entity, an association between each content item of the plurality with one or more keywords describing at least one of the brand of the brand page and the information about the product associated with the brand of the brand page, each of the one or more keywords defined by the entity; receiving, at the social networking system, a request to view the brand page from a user having a user profile connected to the brand page stored in the social networking system; accessing the user profile of the social networking system, the user profile associated with the user requesting to view the brand page; selecting, by the social networking system, content items from the plurality of content items, the selecting based on: an affinity of the at least one affinity, the affinity between the at least one user interest and the content items; the one or more keywords associated with each of the plurality of content items, and the information corresponding to the at least one user interest in the user profile associated with the user requesting to view the brand page, wherein at least one of the selected content items includes the additional content message for accessing additional content items; generating, using the selected content items, a personalized representation of the brand page for display in the social networking system to the user requesting to view the brand page, the personalized representation of the brand page containing one or more of the selected content items; and sending the generated personalized representation of the brand page for display to the user requesting to view the brand page. 24. The computer-implemented method of claim 11 , wherein generating, using the selected content items, the personalized representation of the brand page for display in the social networking system further comprises omitting from the personalized representation of the brand page content items of the plurality of content items that do not include the information corresponding to the user interest in the user profile associated with the user requesting to view the brand page. | 0.619427 |
9,477,771 | 16 | 18 | 16. A non-transitory machine-readable medium having stored thereon machine-readable instructions executable to cause a machine to perform operations comprising: defining a plurality of token indicators, wherein each token indicator is associated with a token indicator type and comprises a special text character and/or a graphics image; for at least one of the plurality of token indicators, defining a plurality of templates, wherein each template is associated with the token indicator type and a token type; identifying an input token indicator; identifying an input token in conjunction with the input token indicator; selecting a template corresponding to the input token indicator, wherein selecting the template corresponding to the input token indicator comprises: determining a token indicator type associated with the input token indicator and a token type associated with the input token and selecting, from one of the plurality of templates, a template whose associated token type matches that of the token type of the input token; and executing a process enabled according to the input token and the selected template. | 16. A non-transitory machine-readable medium having stored thereon machine-readable instructions executable to cause a machine to perform operations comprising: defining a plurality of token indicators, wherein each token indicator is associated with a token indicator type and comprises a special text character and/or a graphics image; for at least one of the plurality of token indicators, defining a plurality of templates, wherein each template is associated with the token indicator type and a token type; identifying an input token indicator; identifying an input token in conjunction with the input token indicator; selecting a template corresponding to the input token indicator, wherein selecting the template corresponding to the input token indicator comprises: determining a token indicator type associated with the input token indicator and a token type associated with the input token and selecting, from one of the plurality of templates, a template whose associated token type matches that of the token type of the input token; and executing a process enabled according to the input token and the selected template. 18. The non-transitory machine-readable medium of claim 16 wherein executing a process enabled according to the input token and the selected template further comprises: generating a uniform resource locator (URL) according to a distinctive visual characteristic of the input token indicator. | 0.627877 |
9,256,784 | 18 | 19 | 18. A system comprising: one or more processors; an eye sensor device; and one or more computer-readable storage media storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to: receive, from the eye sensor device, information related to a gaze direction of eyes of a user as the user reads displayed text of a document in a first formatted version; determine, based on an analysis of the information related to the gaze direction, a current reading speed of the displayed text; detect that an irregularity occurs based on a determination that the current reading speed is less than a regular reading speed of the user; determine that the irregularity is associated with a display screen location that contains a portion of the displayed text; and associate the display screen location that contains the portion of the displayed text with an identifiable section within a second formatted version of the document that is different than the first formatted version of the document, wherein the identifiable section comprises a page. | 18. A system comprising: one or more processors; an eye sensor device; and one or more computer-readable storage media storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to: receive, from the eye sensor device, information related to a gaze direction of eyes of a user as the user reads displayed text of a document in a first formatted version; determine, based on an analysis of the information related to the gaze direction, a current reading speed of the displayed text; detect that an irregularity occurs based on a determination that the current reading speed is less than a regular reading speed of the user; determine that the irregularity is associated with a display screen location that contains a portion of the displayed text; and associate the display screen location that contains the portion of the displayed text with an identifiable section within a second formatted version of the document that is different than the first formatted version of the document, wherein the identifiable section comprises a page. 19. The system as recited in claim 18 , wherein the computer-executable instructions further cause the one or more processors to determine the regular reading speed based on tracking the gaze direction of the eyes of the user as the user reads other documents. | 0.501916 |
9,020,957 | 10 | 11 | 10. The system of claim 9 , wherein enhancement module is programmed to enhance the social networking content by: injecting the additional content item into the social networking content; displaying the social networking content enhanced with the injected additional content item. | 10. The system of claim 9 , wherein enhancement module is programmed to enhance the social networking content by: injecting the additional content item into the social networking content; displaying the social networking content enhanced with the injected additional content item. 11. The system of claim 10 , wherein the enhancement module is programmed to inject the additional content item into the social networking content by contextualizing the content item in the social networking content with the additional content item. | 0.5 |
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