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5,465,304 | 17 | 21 | 17. An apparatus for segmenting portions of a medium representation into text and non-text types, said apparatus comprising: a memory for storing said medium representation, said medium representation including a plurality of scanlines, said plurality of scanlines being organized into a plurality of groups of scanlines; a processor, being coupled to said memory, said processor for compressing said plurality of groups into a plurality of compressed scanlines, said processor for generating a plurality of run lengths by extracting a run length from each compressed scanline in said plurality of compressed scanlines, said processor for generating a plurality of run length classifications by generating a run length classification for each run length in said plurality of run lengths according to a length of each run length, said processor for constructing a set of rectangles from said plurality of run lengths and said plurality of run length classifications, said processor for assigning a classification to each rectangle of said set of rectangles as non-text type or unknown type using said run length classifications associated with each rectangle, and said processor for generating a plurality of text blocks from a set of rectangles of said set of rectangles having an unknown type and for storing said plurality of text blocks in said memory. | 17. An apparatus for segmenting portions of a medium representation into text and non-text types, said apparatus comprising: a memory for storing said medium representation, said medium representation including a plurality of scanlines, said plurality of scanlines being organized into a plurality of groups of scanlines; a processor, being coupled to said memory, said processor for compressing said plurality of groups into a plurality of compressed scanlines, said processor for generating a plurality of run lengths by extracting a run length from each compressed scanline in said plurality of compressed scanlines, said processor for generating a plurality of run length classifications by generating a run length classification for each run length in said plurality of run lengths according to a length of each run length, said processor for constructing a set of rectangles from said plurality of run lengths and said plurality of run length classifications, said processor for assigning a classification to each rectangle of said set of rectangles as non-text type or unknown type using said run length classifications associated with each rectangle, and said processor for generating a plurality of text blocks from a set of rectangles of said set of rectangles having an unknown type and for storing said plurality of text blocks in said memory. 21. The system of claim 17 wherein said processor is further for determining a skew from said set of rectangles and for correcting for said skew. | 0.933729 |
8,719,250 | 6 | 7 | 6. The method set forth in claim 5 wherein: the relational database system includes one or more optimization objects for optimizing queries on the RDF triples table; and in the step of obtaining results, the relational database management system uses the optimization objects to optimize the query on the RDF triples table. | 6. The method set forth in claim 5 wherein: the relational database system includes one or more optimization objects for optimizing queries on the RDF triples table; and in the step of obtaining results, the relational database management system uses the optimization objects to optimize the query on the RDF triples table. 7. The method set forth in claim 6 wherein: the query optimization objects include an index on the RDF triples table. | 0.937232 |
7,996,440 | 31 | 33 | 31. A non-transitory computer-readable medium having stored thereon executable instructions that, when executed, cause the computer to: identify a first set of attributes and a first set of values of a product via a supervised classification algorithm as applied to at least one natural language document; identify a second set of attributes and a second set of values of the product via a semi-supervised classification algorithm as applied to the at least one natural language document based at least in part upon the first set of attributes and the first set of values; provide the first set of attributes and the second set of attributes as at least one attribute; provide the first set of values and the second set of values as at least one value; for at least two attributes of the at least one attribute, calculate correlation values between each of the at least two attributes; for at least two values of the at least one value, calculate correlation values between each of the at least two values; merge attributes of the at least two attributes having correlation values above a correlation threshold; merge values of the at least two values having correlation values above the correlation threshold; and store the at least one attribute and the at least one value. | 31. A non-transitory computer-readable medium having stored thereon executable instructions that, when executed, cause the computer to: identify a first set of attributes and a first set of values of a product via a supervised classification algorithm as applied to at least one natural language document; identify a second set of attributes and a second set of values of the product via a semi-supervised classification algorithm as applied to the at least one natural language document based at least in part upon the first set of attributes and the first set of values; provide the first set of attributes and the second set of attributes as at least one attribute; provide the first set of values and the second set of values as at least one value; for at least two attributes of the at least one attribute, calculate correlation values between each of the at least two attributes; for at least two values of the at least one value, calculate correlation values between each of the at least two values; merge attributes of the at least two attributes having correlation values above a correlation threshold; merge values of the at least two values having correlation values above the correlation threshold; and store the at least one attribute and the at least one value. 33. The computer-readable medium of claim 31 , further comprising executable instructions that, when executed, cause the computer to: obtain the at least one natural language document via a public communication network. | 0.854388 |
9,576,009 | 4 | 5 | 4. A method comprising: a processor defining a communication goal data structure, wherein the defined communication goal data structure is associated with a communication goal of describing a status for a subject, the defined communication goal data structure comprising (1) first data that is indicative of a content block data structure associated with the communication goal data structure, the associated content block data structure comprising a parameterized model for a plurality of data components that need to be analyzed to generate a narrative and a parameterized model for a plurality of computational components for analyzing the data components to generate a narrative, and (2) second data that is indicative of a plurality of communication goal parameters whose values are variable, wherein the plurality of communication goal parameters are used by the parameterized models of the associated content block data structure; and the processor storing the defined communication goal data structure in a memory such that the defined communication goal data structure is accessible for use by a processor when automatically generating a narrative about data based on input about a communication goal to be satisfied by the automatically generated narrative; and wherein the second data comprises: a subject metric parameter; and a time frame parameter. | 4. A method comprising: a processor defining a communication goal data structure, wherein the defined communication goal data structure is associated with a communication goal of describing a status for a subject, the defined communication goal data structure comprising (1) first data that is indicative of a content block data structure associated with the communication goal data structure, the associated content block data structure comprising a parameterized model for a plurality of data components that need to be analyzed to generate a narrative and a parameterized model for a plurality of computational components for analyzing the data components to generate a narrative, and (2) second data that is indicative of a plurality of communication goal parameters whose values are variable, wherein the plurality of communication goal parameters are used by the parameterized models of the associated content block data structure; and the processor storing the defined communication goal data structure in a memory such that the defined communication goal data structure is accessible for use by a processor when automatically generating a narrative about data based on input about a communication goal to be satisfied by the automatically generated narrative; and wherein the second data comprises: a subject metric parameter; and a time frame parameter. 5. The method of claim 4 wherein the second data further comprises: a change threshold parameter. | 0.949001 |
9,262,513 | 10 | 17 | 10. A computing device comprising: one or more processors; and memory to maintain a plurality of components executable by the one or more processors, the plurality of components comprising: a first search module configured to: receive a query including a keyword, and conduct a search to obtain a first set of search results based on literal correlations with the keyword; a second search module configured to determine a second set of search results including one or more search results that are not in the first set of search results, each individual search result of the second set of search results being determined based at least in part on correlations among the keyword and transactional parameters that individually satisfy at least one predetermined condition, each individual transactional parameter of the transactional parameters being determined based on a ratio of a number of users purchasing one or more items associated with the individual search result to a number of users investigating the individual search result; and a sorting search module configured to assign the second set of search results a higher priority than the first set of search results. | 10. A computing device comprising: one or more processors; and memory to maintain a plurality of components executable by the one or more processors, the plurality of components comprising: a first search module configured to: receive a query including a keyword, and conduct a search to obtain a first set of search results based on literal correlations with the keyword; a second search module configured to determine a second set of search results including one or more search results that are not in the first set of search results, each individual search result of the second set of search results being determined based at least in part on correlations among the keyword and transactional parameters that individually satisfy at least one predetermined condition, each individual transactional parameter of the transactional parameters being determined based on a ratio of a number of users purchasing one or more items associated with the individual search result to a number of users investigating the individual search result; and a sorting search module configured to assign the second set of search results a higher priority than the first set of search results. 17. The computing device of claim 10 , wherein: the number of users purchasing one or more items associated with the individual search result represents a purchase index; and the individual transactional parameter is determined further based on a variance of purchase indexes of the second set of search results. | 0.667377 |
9,373,329 | 1 | 9 | 1. A computer-implemented method comprising: receiving, at a computer system, an audio signal; initiating, by the computer system, a plurality of speech recognition tasks for the audio signal, wherein the speech recognition tasks each use a different one of a plurality of language models; detecting that a portion of the plurality of speech recognition tasks have completed, wherein a remaining portion of the plurality of speech recognition tasks have not completed; obtaining recognition results and confidence values for each of the plurality of speech recognition tasks included in the portion, wherein the recognition results identify one or more candidate transcriptions of the audio signal, and the confidence values identify one or more probabilities that the recognition results are correct; determining, by the computer system, whether at least one of the one or more confidence values is greater than or equal to a threshold confidence value; and in response to determining that the at least one of the one or more confidence values is greater than or equal to the threshold confidence value and before all of the remaining portion of the plurality of speech recognition tasks have completed, providing a final recognition result for the audio signal based on the recognition results and the one or more confidence values. | 1. A computer-implemented method comprising: receiving, at a computer system, an audio signal; initiating, by the computer system, a plurality of speech recognition tasks for the audio signal, wherein the speech recognition tasks each use a different one of a plurality of language models; detecting that a portion of the plurality of speech recognition tasks have completed, wherein a remaining portion of the plurality of speech recognition tasks have not completed; obtaining recognition results and confidence values for each of the plurality of speech recognition tasks included in the portion, wherein the recognition results identify one or more candidate transcriptions of the audio signal, and the confidence values identify one or more probabilities that the recognition results are correct; determining, by the computer system, whether at least one of the one or more confidence values is greater than or equal to a threshold confidence value; and in response to determining that the at least one of the one or more confidence values is greater than or equal to the threshold confidence value and before all of the remaining portion of the plurality of speech recognition tasks have completed, providing a final recognition result for the audio signal based on the recognition results and the one or more confidence values. 9. The computer-implemented method of claim 1 , further comprising: in response to determining that the at least one of the one or more confidence values is greater than or equal to the threshold confidence value, aborting the remaining portion of the plurality of speech recognition tasks before the remaining portion of the plurality of speech recognition tasks have completed. | 0.698248 |
9,798,753 | 41 | 42 | 41. The computer-readable computer memory medium of claim 26 , wherein the method further comprises: bundling one or more of the search snapshot objects of the search snapshot history; and facilitating distribution of the bundled one or more search snapshot objects to one or more targets. | 41. The computer-readable computer memory medium of claim 26 , wherein the method further comprises: bundling one or more of the search snapshot objects of the search snapshot history; and facilitating distribution of the bundled one or more search snapshot objects to one or more targets. 42. The computer-readable computer memory medium of claim 41 wherein the one or more targets are at least one of: an individual with expertise in a designated area, an inventor, a reviewer, or an investor. | 0.96297 |
7,696,427 | 1 | 2 | 1. A method for recommending music comprising: identifying a granularity of a plurality of genres based on a request for music similarity, wherein the request identifies a user; training a genre classifier, executing on a computer processor, based on the granularity to obtain a trained genre classifier; calculating, using the computer processor, a first profile by the trained genre classifier, wherein the first profile comprises, for each of the plurality of genres, a likelihood that a music selection associated with the user is in the genre; calculating, using the computer processor, a second profile by the trained genre classifier, wherein the second profile comprises, for each of the plurality of genres, a likelihood that an unknown music selection is in the genre; obtaining a first similarity score between the first profile and the second profile; and recommending the unknown music selection to the user based on the first similarity score. | 1. A method for recommending music comprising: identifying a granularity of a plurality of genres based on a request for music similarity, wherein the request identifies a user; training a genre classifier, executing on a computer processor, based on the granularity to obtain a trained genre classifier; calculating, using the computer processor, a first profile by the trained genre classifier, wherein the first profile comprises, for each of the plurality of genres, a likelihood that a music selection associated with the user is in the genre; calculating, using the computer processor, a second profile by the trained genre classifier, wherein the second profile comprises, for each of the plurality of genres, a likelihood that an unknown music selection is in the genre; obtaining a first similarity score between the first profile and the second profile; and recommending the unknown music selection to the user based on the first similarity score. 2. The method of claim 1 , wherein training the genre classifier comprises: obtaining a sample set for each of the plurality of genres, wherein the sample set is based on the granularity; identifying a plurality of features for each of the sample sets, and wherein training the genre classifier uses linear discriminant analysis on the plurality of features. | 0.753783 |
7,953,674 | 1 | 6 | 1. A computer implemented system comprising the following computer executable components: a processor; and a memory component communicatively coupled to the processor, the memory component having stored therein computer-executable instructions that when executed by the processor cause the processor to implement: a fuzzing system that receives a structured query language (SQL) statement, wherein the SQL statement includes actual grammar associated with the SQL statement and explicit user specified parameters associated with penetration testing of an SQL server; and a parsing component as part of the SQL server that separates the explicit user specified parameters from the actual grammar associated with the SQL statement, wherein the parsing component mitigates parsing errors by replacing the explicit user specified parameters with fuzz values generated within the SQL server that maintain conformance to syntactically correct SQL statements. | 1. A computer implemented system comprising the following computer executable components: a processor; and a memory component communicatively coupled to the processor, the memory component having stored therein computer-executable instructions that when executed by the processor cause the processor to implement: a fuzzing system that receives a structured query language (SQL) statement, wherein the SQL statement includes actual grammar associated with the SQL statement and explicit user specified parameters associated with penetration testing of an SQL server; and a parsing component as part of the SQL server that separates the explicit user specified parameters from the actual grammar associated with the SQL statement, wherein the parsing component mitigates parsing errors by replacing the explicit user specified parameters with fuzz values generated within the SQL server that maintain conformance to syntactically correct SQL statements. 6. The computer implemented system of claim 1 further comprising a transformation component that tracks occurred transformations. | 0.586538 |
7,725,306 | 7 | 11 | 7. A method comprising: setting boundaries of a possible source phrase for a source sentence; using word alignments between words in the possible source phrase and words in a target sentence to set boundaries for a possible target phrase in the target sentence; a processor determining that a target word in the possible target phrase is aligned with an exterior source word of the source sentence that is not in the possible source phrase; and a processor excluding from consideration as possible source phrases for phrase alignment pairs without identifying corresponding possible target phrases, spans of contiguous source words in the source sentence that share a boundary with the possible source phrase, do not include the exterior source word, and include all of the words of the possible source phrase. | 7. A method comprising: setting boundaries of a possible source phrase for a source sentence; using word alignments between words in the possible source phrase and words in a target sentence to set boundaries for a possible target phrase in the target sentence; a processor determining that a target word in the possible target phrase is aligned with an exterior source word of the source sentence that is not in the possible source phrase; and a processor excluding from consideration as possible source phrases for phrase alignment pairs without identifying corresponding possible target phrases, spans of contiguous source words in the source sentence that share a boundary with the possible source phrase, do not include the exterior source word, and include all of the words of the possible source phrase. 11. The method of claim 7 wherein excluding a span of contiguous source words from consideration as a possible source phrase comprises shifting a starting boundary of the possible source phrase toward the ending boundary of the source phrase. | 0.895238 |
9,047,285 | 12 | 14 | 12. The method of claim 1 , wherein the first frame is a benefit frame. | 12. The method of claim 1 , wherein the first frame is a benefit frame. 14. The method of claim 12 , wherein the content of interest is useful as part of a technology scouting process. | 0.968451 |
10,157,344 | 2 | 3 | 2. The method of claim 1 , wherein the calculating the edge strength between the selected entity and the second entity includes: determining an amount of navigation between the selected entity and the second entity. | 2. The method of claim 1 , wherein the calculating the edge strength between the selected entity and the second entity includes: determining an amount of navigation between the selected entity and the second entity. 3. The method of claim 2 , wherein the determining the amount of navigation between the selected entity and the second entity includes: determining user session boundaries for determining related navigation history. | 0.934967 |
8,515,897 | 11 | 13 | 11. The program product of claim 10 , wherein said adjusting said scores of said multiple UIAM items includes adjusting a score of a UIAM item of said second set of one or more UIAM items, said score of said UIAM item indicating a latest interest of said user, wherein said adjusting said score includes: adding M to a score of said UIAM item of said second set of one or more UIAM items if said UIAM item is already included in said cube-based UIAM; adding said UIAM item of said second set of one or more UIAM items as a new record in said cube-based UIAM and assigning a default score of N as said score of said UIAM item if said UIAM item does not already exist in said cube-based UIAM; and subtracting W from score(s) of one or more other UIAM item of said multiple UIAM items in said cube-based UIAM, wherein said one or more other UIAM items are other than said UIAM item, wherein said subtracting W from said score(s) of said one or more other UIAM items includes subtracting W from a score of at least one UIAM item of said first set of one or more UIAM items that is different from said UIAM item of said second set of one or more UIAM items, wherein a result of said adjusting said score of said UIAM item of said second set of said one or more UIAM items is said score of said UIAM item being included in said top k scores, and wherein said automatically generating said one or more reports is based in part on said score of said UIAM item of said second set of one or more UIAM items being included in said top k scores. | 11. The program product of claim 10 , wherein said adjusting said scores of said multiple UIAM items includes adjusting a score of a UIAM item of said second set of one or more UIAM items, said score of said UIAM item indicating a latest interest of said user, wherein said adjusting said score includes: adding M to a score of said UIAM item of said second set of one or more UIAM items if said UIAM item is already included in said cube-based UIAM; adding said UIAM item of said second set of one or more UIAM items as a new record in said cube-based UIAM and assigning a default score of N as said score of said UIAM item if said UIAM item does not already exist in said cube-based UIAM; and subtracting W from score(s) of one or more other UIAM item of said multiple UIAM items in said cube-based UIAM, wherein said one or more other UIAM items are other than said UIAM item, wherein said subtracting W from said score(s) of said one or more other UIAM items includes subtracting W from a score of at least one UIAM item of said first set of one or more UIAM items that is different from said UIAM item of said second set of one or more UIAM items, wherein a result of said adjusting said score of said UIAM item of said second set of said one or more UIAM items is said score of said UIAM item being included in said top k scores, and wherein said automatically generating said one or more reports is based in part on said score of said UIAM item of said second set of one or more UIAM items being included in said top k scores. 13. The program product of claim 11 , wherein said M, N and W are positive integers, wherein N>M, and wherein M>W. | 0.980573 |
7,953,755 | 9 | 10 | 9. The semantic relational database of claim 6 , wherein said phrase registry data store of definitions refers to a stored data item by a multipart key. | 9. The semantic relational database of claim 6 , wherein said phrase registry data store of definitions refers to a stored data item by a multipart key. 10. The semantic relational database of claim 9 , wherein the multipart key is made of five parts, including an Install ID representing a registered database system in which the data item was created, an Item ID representing the data item within its registered database system, a Utility Number ensuring row key uniqueness, anti-lock optimization, and temporary processing identification, a Timestamp that is a date-time value used to track and discriminate upgrades and edits of a value of the data item identified by the Install Number and the Item Number and the Utility Number, and an Update Tracking flag used to track whether the data is inserted, deleted or other mode. | 0.869094 |
7,957,971 | 12 | 13 | 12. The speech processing system using the module of claim 11 , wherein the module configured to convert further converts the word lattice into a word confusion network. | 12. The speech processing system using the module of claim 11 , wherein the module configured to convert further converts the word lattice into a word confusion network. 13. The speech processing system using the module of claim 12 , wherein posterior probabilities of the word confusion network are used as confidence scores. | 0.898039 |
9,229,982 | 8 | 9 | 8. A method for implementation by one or more data processors comprising: specifying, by at least one data processor, a set of database tables defining vertices and database joins defining oriented edges to form a graph, wherein the oriented edges specify directionality characterizing dependent relationships between the database tables; identifying a plurality of query paths in the graph; splitting, by at least one data processor, the graph into one or more directed acyclic graphs, wherein each directed acyclic graph has a single root vertex that does not form a path to itself through oriented edges; and removing, by at least one data processor, selected oriented database joins from each directed acyclic graph to form a tree corresponding to each directed acyclic graph, the removal of the selected oriented database joins minimizing redundancy caused by querying, using the plurality of query paths, of data associated with a vertex of the graph, wherein the removing comprises identifying a simple cycle in each directed acyclic graph that contains only one fan trap and one source, wherein a fan trap is a vertex with two incoming edges, wherein at least a portion of the removed selected oriented edges are within the simple cycle; wherein the simple cycle is identified in the directed acyclic graph by: selecting any edge in the query path and removing such selected edge from the query path; determining that there is a cycle C if there is one other non-oriented path between ends of the selected edge; and determining that there is not a cycle if there is not one other non-oriented path between the ends of the selected edge; wherein when the determined cycle C comprises more than one fan trap and one source: selecting one of the fan traps F having a smallest distance to a root, identifying its two surrounding sources S and T, finding a path P between S and T that does not contain a common descendant, and connecting path P with the path that relates S to F and T in cycle C to yield a new cycle C′, wherein the new cycle C′ is the simple cycle; generate, by at least one data processor, a database query for each tree; apply, by at least one data processor, each database query for each tree to the database tables that correspond to the vertices in the tree to form query results; and display, by at least one data processor, the query results. | 8. A method for implementation by one or more data processors comprising: specifying, by at least one data processor, a set of database tables defining vertices and database joins defining oriented edges to form a graph, wherein the oriented edges specify directionality characterizing dependent relationships between the database tables; identifying a plurality of query paths in the graph; splitting, by at least one data processor, the graph into one or more directed acyclic graphs, wherein each directed acyclic graph has a single root vertex that does not form a path to itself through oriented edges; and removing, by at least one data processor, selected oriented database joins from each directed acyclic graph to form a tree corresponding to each directed acyclic graph, the removal of the selected oriented database joins minimizing redundancy caused by querying, using the plurality of query paths, of data associated with a vertex of the graph, wherein the removing comprises identifying a simple cycle in each directed acyclic graph that contains only one fan trap and one source, wherein a fan trap is a vertex with two incoming edges, wherein at least a portion of the removed selected oriented edges are within the simple cycle; wherein the simple cycle is identified in the directed acyclic graph by: selecting any edge in the query path and removing such selected edge from the query path; determining that there is a cycle C if there is one other non-oriented path between ends of the selected edge; and determining that there is not a cycle if there is not one other non-oriented path between the ends of the selected edge; wherein when the determined cycle C comprises more than one fan trap and one source: selecting one of the fan traps F having a smallest distance to a root, identifying its two surrounding sources S and T, finding a path P between S and T that does not contain a common descendant, and connecting path P with the path that relates S to F and T in cycle C to yield a new cycle C′, wherein the new cycle C′ is the simple cycle; generate, by at least one data processor, a database query for each tree; apply, by at least one data processor, each database query for each tree to the database tables that correspond to the vertices in the tree to form query results; and display, by at least one data processor, the query results. 9. The method of claim 8 , wherein the removal of the selected oriented database joins comprises elimination of at least one of one or more fan traps and one or more sources, each source being a vertex that has two or more outgoing oriented database joins. | 0.501946 |
8,719,018 | 1 | 2 | 1. A biometric speaker-identification apparatus that generates one or more speaker-identity candidates for a speaker based on probe match scores obtained by performing a voice matching operation between a probe and templates in a biometric corpus, comprising: a plurality of prototypes; and a speaker-identification processor coupled to the biometric corpus, the speaker-identification processor configured to select templates of the biometric corpus as the speaker-identity candidates based on the prototypes, wherein the speaker-identification processor is further configured to: perform the voice matching operation between the speaker-identity candidates and the templates in the biometric corpus to obtain one or more speaker-identity-candidate match scores; perform a similarity measurement between the speaker-identity-candidate match scores and the probe match scores to obtain one or more similarity values; and order the speaker-identity candidates based on the similarity values, and wherein the similarity measurement for an i th speaker-identity candidate is a dot product defined as:
DOT i =SUM(tms it *pms t ), where the sum is taken over all the templates in the biometric corpus, tms it is a template match score between the i th speaker-identity candidate and a t th template, and pms t is a probe match score for the t th template. | 1. A biometric speaker-identification apparatus that generates one or more speaker-identity candidates for a speaker based on probe match scores obtained by performing a voice matching operation between a probe and templates in a biometric corpus, comprising: a plurality of prototypes; and a speaker-identification processor coupled to the biometric corpus, the speaker-identification processor configured to select templates of the biometric corpus as the speaker-identity candidates based on the prototypes, wherein the speaker-identification processor is further configured to: perform the voice matching operation between the speaker-identity candidates and the templates in the biometric corpus to obtain one or more speaker-identity-candidate match scores; perform a similarity measurement between the speaker-identity-candidate match scores and the probe match scores to obtain one or more similarity values; and order the speaker-identity candidates based on the similarity values, and wherein the similarity measurement for an i th speaker-identity candidate is a dot product defined as:
DOT i =SUM(tms it *pms t ), where the sum is taken over all the templates in the biometric corpus, tms it is a template match score between the i th speaker-identity candidate and a t th template, and pms t is a probe match score for the t th template. 2. The apparatus of claim 1 wherein the speaker-identification processor is further configured to: perform the voice matching operation between the probe and the prototypes to obtain probe-prototype match scores; perform the voice matching operation between first templates selected from the biometric corpus and the prototypes to obtain template-prototype match scores; and select as the speaker-identity candidates one or more second templates corresponding to template-prototype match scores that are nearest to the probe-prototype match scores based on a nearness measurement. | 0.66895 |
9,665,850 | 14 | 18 | 14. An electronic message reading system comprising: a processor; and a message reading application comprising one or more modules operable to cause the processor to provide a list view of a plurality of messages organized by conversation the plurality of messages organized by conversation provided in the list view being stored in a plurality of different folders, provide a content view of the plurality of messages organized by conversation, present a unified user interface simultaneously displaying the list view and the content view, and to maintain bidirectional synchronization between the list view and the content view, wherein the bidirectional synchronization is maintained by: indicating a message within the list view as selected; in response to indicating the message within the list view as selected, navigating the plurality of messages of the content view and opening for reading a corresponding message as the selected message within the content view; and indicating a message within the list view as selected in response to a corresponding message within the content view being selected; the one or more modules further operable to cause the processor to display a list view pipe within the list view, the list view pipe showing a reply to connection between at least a display of a broken out message and a display of a parent message in the conversation, the list view pipe comprising a plurality of indicators which display a relationship between an entire chain of displayed messages. | 14. An electronic message reading system comprising: a processor; and a message reading application comprising one or more modules operable to cause the processor to provide a list view of a plurality of messages organized by conversation the plurality of messages organized by conversation provided in the list view being stored in a plurality of different folders, provide a content view of the plurality of messages organized by conversation, present a unified user interface simultaneously displaying the list view and the content view, and to maintain bidirectional synchronization between the list view and the content view, wherein the bidirectional synchronization is maintained by: indicating a message within the list view as selected; in response to indicating the message within the list view as selected, navigating the plurality of messages of the content view and opening for reading a corresponding message as the selected message within the content view; and indicating a message within the list view as selected in response to a corresponding message within the content view being selected; the one or more modules further operable to cause the processor to display a list view pipe within the list view, the list view pipe showing a reply to connection between at least a display of a broken out message and a display of a parent message in the conversation, the list view pipe comprising a plurality of indicators which display a relationship between an entire chain of displayed messages. 18. The message reading application of claim 14 , further comprising one or more modules operable to cause the processor to display a content view pipe to associate an expanded frame with a parent message in the conversation, the content view pipe comprising a plurality of indicators for displaying a relationship of a message chain preceding a message within the expanded frame, the message within the expanded frame comprising a reply to the parent message. | 0.53252 |
6,108,620 | 14 | 15 | 14. A computer-readable medium having instructions for causing a computer system to parse an input segment, the input segment comprising words by repeating the following until a complete parse is generated: identifying a syntax rule to be applied to a current partial parse of the input segment; applying the identified syntax rule to the current partial parse of the input segment; determining whether syntax rules with a low probability of leading to a complete parse have recently been applied; and when it is determined that that such syntax rules have recently been applied, establishing a pseudo-end of the input segment so that syntax rules that previously had a low probability now have a higher probability and are thus more likely to be identified. | 14. A computer-readable medium having instructions for causing a computer system to parse an input segment, the input segment comprising words by repeating the following until a complete parse is generated: identifying a syntax rule to be applied to a current partial parse of the input segment; applying the identified syntax rule to the current partial parse of the input segment; determining whether syntax rules with a low probability of leading to a complete parse have recently been applied; and when it is determined that that such syntax rules have recently been applied, establishing a pseudo-end of the input segment so that syntax rules that previously had a low probability now have a higher probability and are thus more likely to be identified. 15. The computer-readable medium of claim 14 wherein the identifying of syntax rules identifies syntax rules is based on their probability of being part of a complete syntax parse tree for the input segment. | 0.818739 |
8,713,029 | 7 | 12 | 7. An apparatus for displaying geographic address element candidates at a user device, comprising: a communication interface configured to retrieve a profile metadata based on the textual input, wherein the profile metadata is generated based on data that is independent from the user, the profile metadata includes a total number of geographic street candidates in a first category and a total number of geographic street element candidates in a second category associated with the textual input, the geographic street element candidates are street attributes other than street candidates, and each of the total number is a positive integer greater than one; and a processor configured to generate a script based on the profile metadata for transmission of the script to the application, wherein the script is generated using the total number of the geographic street candidates in the first category when the total number of the geographic street candidates is less than or equal to a predetermined threshold that is a positive integer, and the script is generated using the geographic street element candidates in the second category when the total number of the geographic street candidates in the first category is more than the predetermined threshold, and the script executes auto-completion of information corresponding to the textual input using at least one of the geographic street element candidates in the second category to display the geographic address element candidates at the user device, wherein the textual input specifies geographic addressing information other than a geographic address element corresponding to the geographic address element candidates, and the script executes the auto-completion by displaying the geographic address element candidates prior to the user inputs any portion of the geographic address element. | 7. An apparatus for displaying geographic address element candidates at a user device, comprising: a communication interface configured to retrieve a profile metadata based on the textual input, wherein the profile metadata is generated based on data that is independent from the user, the profile metadata includes a total number of geographic street candidates in a first category and a total number of geographic street element candidates in a second category associated with the textual input, the geographic street element candidates are street attributes other than street candidates, and each of the total number is a positive integer greater than one; and a processor configured to generate a script based on the profile metadata for transmission of the script to the application, wherein the script is generated using the total number of the geographic street candidates in the first category when the total number of the geographic street candidates is less than or equal to a predetermined threshold that is a positive integer, and the script is generated using the geographic street element candidates in the second category when the total number of the geographic street candidates in the first category is more than the predetermined threshold, and the script executes auto-completion of information corresponding to the textual input using at least one of the geographic street element candidates in the second category to display the geographic address element candidates at the user device, wherein the textual input specifies geographic addressing information other than a geographic address element corresponding to the geographic address element candidates, and the script executes the auto-completion by displaying the geographic address element candidates prior to the user inputs any portion of the geographic address element. 12. The apparatus according to claim 7 , wherein the profile metadata is used to auto-complete the information. | 0.914615 |
8,375,116 | 1 | 5 | 1. A method for routing input business documents received from client computers via a network to one or more operations running on processing servers, the method including: storing on a first server a plurality of operation interface specification data structures that include operation interface specifications, the operation interface specifications including descriptions of operations and definitions of input and output documents; receiving data comprising a document at a second server from a client computer via a network; parsing the document using the second server according to the operation interface specifications to identify an input document and to identify one or more operations that run on one or more processing servers, which accept the identified input document; and routing at least a portion of the input document from the second server to the one or more identified operations running on the processing servers, which accept the identified input document. | 1. A method for routing input business documents received from client computers via a network to one or more operations running on processing servers, the method including: storing on a first server a plurality of operation interface specification data structures that include operation interface specifications, the operation interface specifications including descriptions of operations and definitions of input and output documents; receiving data comprising a document at a second server from a client computer via a network; parsing the document using the second server according to the operation interface specifications to identify an input document and to identify one or more operations that run on one or more processing servers, which accept the identified input document; and routing at least a portion of the input document from the second server to the one or more identified operations running on the processing servers, which accept the identified input document. 5. The method of claim 1 , wherein the operation interface specifications include documents compliant with a definition of a predefined document including logical structures for storing an identifier of a particular operation, and at least one of definitions and references to definitions of input and output documents for the particular operation. | 0.699482 |
7,743,082 | 12 | 15 | 12. One or more computer readable storage media storing computer-executable instructions, which when executed by a processor comprising: searching the selected document library to locate documents having property information that matches the search criteria; receiving a document for storing in association with a selected document library file system folder, the selected document library file system folder is associated with a selected document library from among a plurality of document libraries, each document library among the plurality of document libraries comprising a document library database, a document library file system folder, and documents included within the document library file system folder, wherein each document library of the plurality of document libraries has a corresponding set of properties that apply to the type of documents that are associated with that document library; associating the set of properties corresponding to the selected document library with the document such that the document is associated with a consistent set of properties applied to all documents stored in association with the selected document library, and such that each document in the selected document library has the consistent set of properties that make such documents specific to only the selected document library; writing property value information for at least some of the properties in the set to the document library database of the selected document library that includes an entry for the document to relate the property value information to the document; and storing the document in the selected document library file system folder of the selected document library, such that the document and all other document stored in the selected document library file system folder have consistent properties making such documents specific to the selected document library in which the documents are all stored. | 12. One or more computer readable storage media storing computer-executable instructions, which when executed by a processor comprising: searching the selected document library to locate documents having property information that matches the search criteria; receiving a document for storing in association with a selected document library file system folder, the selected document library file system folder is associated with a selected document library from among a plurality of document libraries, each document library among the plurality of document libraries comprising a document library database, a document library file system folder, and documents included within the document library file system folder, wherein each document library of the plurality of document libraries has a corresponding set of properties that apply to the type of documents that are associated with that document library; associating the set of properties corresponding to the selected document library with the document such that the document is associated with a consistent set of properties applied to all documents stored in association with the selected document library, and such that each document in the selected document library has the consistent set of properties that make such documents specific to only the selected document library; writing property value information for at least some of the properties in the set to the document library database of the selected document library that includes an entry for the document to relate the property value information to the document; and storing the document in the selected document library file system folder of the selected document library, such that the document and all other document stored in the selected document library file system folder have consistent properties making such documents specific to the selected document library in which the documents are all stored. 15. The computer-readable media of claim 12 further comprising: receiving a request to search the selected document library for documents having property information that matches search criteria; searching the selected document library to locate documents having property information that matches the search criteria; and in response to searching the selected document library, returning a result of the search. | 0.536117 |
7,574,742 | 17 | 23 | 17. A tangible computer-readable storage medium containing instructions which, when executed by a processor, cause the processor to perform a string matching method, the method comprising: storing a plurality of signature strings in a database; assigning values to characters in the signature strings; calculating differences between the assigned values of the characters in the signature strings; identifying common features of the signature strings using the calculated differences; grouping the signature strings into signature groups according to the common features; receiving an input string into a memory; detecting predetermined features of the input string; comparing the predetermined features of the input string with the common features of one or more of the signature groups; and comparing the input string with one or more individual signature strings in one of the signature groups if the predetermined features of the input string match the common features of the one of the signature groups. | 17. A tangible computer-readable storage medium containing instructions which, when executed by a processor, cause the processor to perform a string matching method, the method comprising: storing a plurality of signature strings in a database; assigning values to characters in the signature strings; calculating differences between the assigned values of the characters in the signature strings; identifying common features of the signature strings using the calculated differences; grouping the signature strings into signature groups according to the common features; receiving an input string into a memory; detecting predetermined features of the input string; comparing the predetermined features of the input string with the common features of one or more of the signature groups; and comparing the input string with one or more individual signature strings in one of the signature groups if the predetermined features of the input string match the common features of the one of the signature groups. 23. The tangible computer-readable storage medium of claim 17 , the method further comprising: updating the signature strings. | 0.769231 |
7,895,160 | 1 | 5 | 1. A system for application-layer monitoring of communication between one or more database clients and one or more database servers, the system comprising: one or more decoders residing at a decoding layer above a network layer, the decoders residing at a first network location between one or more database clients residing at one or more second network locations and one or more database servers residing at one or more third network locations, the decoders being operable to: receive database messages communicated from the database clients and intended for the database servers and database messages communicated from the database servers and intended for the database clients; decode the database messages; and extract query-language statements from the database messages; and a monitoring application residing at an application layer above the decoding layer, the monitoring application residing at the first network location, the monitoring application being operable to receive query-language statements extracted at the decoders and record observations on the database messages based at least in part on the query-language statements extracted at the decoders. | 1. A system for application-layer monitoring of communication between one or more database clients and one or more database servers, the system comprising: one or more decoders residing at a decoding layer above a network layer, the decoders residing at a first network location between one or more database clients residing at one or more second network locations and one or more database servers residing at one or more third network locations, the decoders being operable to: receive database messages communicated from the database clients and intended for the database servers and database messages communicated from the database servers and intended for the database clients; decode the database messages; and extract query-language statements from the database messages; and a monitoring application residing at an application layer above the decoding layer, the monitoring application residing at the first network location, the monitoring application being operable to receive query-language statements extracted at the decoders and record observations on the database messages based at least in part on the query-language statements extracted at the decoders. 5. The system of claim 1 , wherein observations on the database messages based at least in part on the query-language statements extracted at the decoders comprise full text of the query-language statements. | 0.930676 |
8,091,022 | 9 | 10 | 9. The computer program product as set forth in claim 8 wherein the program instructions to provide the administrator graphical user interface further comprise program instructions to provide one or more user interface functions selected from the group consisting of a report sorter, a report filter, and a report search function. | 9. The computer program product as set forth in claim 8 wherein the program instructions to provide the administrator graphical user interface further comprise program instructions to provide one or more user interface functions selected from the group consisting of a report sorter, a report filter, and a report search function. 10. The computer program product as set forth in claim 9 wherein the program instructions to provide the one or more user interface functions comprise program instructions to provide one or more user interface function criteria specifiers selected from the group consisting of a student's identification, a class of students, a maximum number of references consulted, a list of allowed references for consultation, and a list of disallowed references for consultation. | 0.896092 |
8,538,842 | 1 | 11 | 1. A method comprising the steps of: receiving, over a network, a brand name, wherein the brand name comprises at least one token; generating, using at least one computing device, a plurality of domain names, wherein the plurality of domain names comprises at least one brand domain name comprising the brand name and a top level domain name, and wherein the plurality of domain names further comprises at least one qualified brand domain name comprising the brand name, at least one qualifying term, and the top level domain name; creating, using the at least one computing device, a domain name portfolio, wherein each of the plurality of domain names is checked using the WHOIS protocol to determine if the respective domain name is registered, wherein domain names that are not registered and domain names that are registered to an owner of the brand are inserted into the domain name portfolio; registering, using the at least one computing device, each of the domain names in the domain name portfolio that is not registered to the brand owner, whereby each of the domain names in the domain name portfolio is registered to the brand owner; parking, using the at least one computing device, each of the domain names in the domain name portfolio with a domain name parking service; tracking, using the at least one computing device, network traffic, for each of the domain names in the domain name portfolio over an analysis period; and determining, using the at least one computing device, a first role of brand index, wherein the role of brand index is determined using the ratio of network traffic for the at least one brand domain name to a total of the network traffic for all domain names in the domain name portfolio. | 1. A method comprising the steps of: receiving, over a network, a brand name, wherein the brand name comprises at least one token; generating, using at least one computing device, a plurality of domain names, wherein the plurality of domain names comprises at least one brand domain name comprising the brand name and a top level domain name, and wherein the plurality of domain names further comprises at least one qualified brand domain name comprising the brand name, at least one qualifying term, and the top level domain name; creating, using the at least one computing device, a domain name portfolio, wherein each of the plurality of domain names is checked using the WHOIS protocol to determine if the respective domain name is registered, wherein domain names that are not registered and domain names that are registered to an owner of the brand are inserted into the domain name portfolio; registering, using the at least one computing device, each of the domain names in the domain name portfolio that is not registered to the brand owner, whereby each of the domain names in the domain name portfolio is registered to the brand owner; parking, using the at least one computing device, each of the domain names in the domain name portfolio with a domain name parking service; tracking, using the at least one computing device, network traffic, for each of the domain names in the domain name portfolio over an analysis period; and determining, using the at least one computing device, a first role of brand index, wherein the role of brand index is determined using the ratio of network traffic for the at least one brand domain name to a total of the network traffic for all domain names in the domain name portfolio. 11. The method of claim 1 wherein the top level domain name is selected using a method comprising the steps: submitting, over the network, using the computing device, a query to an Internet search engine, wherein the query comprises at least the brand name; receiving, over the network, a search result comprising a plurality of search result entries; and selecting, using the computing device, the top level domain name, wherein the top level domain is a top level domain name most frequently associated with websites in the search result that reference the brand name. | 0.884802 |
7,529,668 | 26 | 27 | 26. The method of claim 20 wherein said relevance module determines whether said first pronunciations are observed in said training database. | 26. The method of claim 20 wherein said relevance module determines whether said first pronunciations are observed in said training database. 27. The method of claim 26 wherein said relevance module discards any of said first pronunciations that are not observed in said training database. | 0.957928 |
9,064,489 | 21 | 22 | 21. The non-transitory computer readable medium of claim 20 , wherein the first speech segment corresponds to a word or subword unit. | 21. The non-transitory computer readable medium of claim 20 , wherein the first speech segment corresponds to a word or subword unit. 22. The non-transitory computer readable medium of claim 21 , wherein a subword unit comprises one of a phoneme or diphone. | 0.95184 |
7,681,147 | 12 | 20 | 12. A system to determine probable meanings of words input as search query terms, comprising: a networked server to receive an input of at least one search query word; a processor coupled with the networked server to analyze the inputted word and to determine a probable meaning of the word in accordance with a prior probability of probable meanings of the word and a context frequency probability of probable meanings of the word, wherein the prior probability comprises a probability that the word refers to a predetermined meaning irregardless of a query context in which the word is used, which prior probability is derived from previous analysis of documents containing the word, wherein the processor: estimates an expected final probability for the at least one word given the prior probability of the at least one word; derives an inverse combine function that uses the prior probability and the expected final probability to determine the context frequency probability of the at least one word; and uses a combine mathematical function to combine the prior probability and the context frequency probability to produce a final probability of the probable meaning of the at least one search query word; and a memory coupled with the processor to store the prior probabilities and the context frequency probabilities of probable meanings of previously-inputted words; wherein the processor generates search results listings in accordance with the final probability of the probable meaning of the word for presentation to a user. | 12. A system to determine probable meanings of words input as search query terms, comprising: a networked server to receive an input of at least one search query word; a processor coupled with the networked server to analyze the inputted word and to determine a probable meaning of the word in accordance with a prior probability of probable meanings of the word and a context frequency probability of probable meanings of the word, wherein the prior probability comprises a probability that the word refers to a predetermined meaning irregardless of a query context in which the word is used, which prior probability is derived from previous analysis of documents containing the word, wherein the processor: estimates an expected final probability for the at least one word given the prior probability of the at least one word; derives an inverse combine function that uses the prior probability and the expected final probability to determine the context frequency probability of the at least one word; and uses a combine mathematical function to combine the prior probability and the context frequency probability to produce a final probability of the probable meaning of the at least one search query word; and a memory coupled with the processor to store the prior probabilities and the context frequency probabilities of probable meanings of previously-inputted words; wherein the processor generates search results listings in accordance with the final probability of the probable meaning of the word for presentation to a user. 20. The system of claim 12 , wherein the processor establishes disambiguators in accordance with a text in which the word is used, wherein the disambiguators comprise at least one of: specific disambiguators which includes the meaning of the word as determined in a context of a text that includes the word, other than the text immediately preceding or following the word; and general disambiguators which include a term in a text that uses the word, wherein the term shares an attribute with the word being disambiguated. | 0.500956 |
8,180,153 | 1 | 9 | 1. A method for processing image data, comprising using a processor to perform: providing input image data; segmenting the input image data to generate: a background layer representing the background attributes of an image; a selector layer for identifying one or more foreground attributes of the image not included in the background layer; and a foreground layer representing the foreground attributes of the image; generating a black text layer comprising pixel data representing black text in the input image data; assigning the black text pixel data a predetermined value for the color black; and integrating the background layer, the selector layer, the foreground layer, and the black text layer into a data structure having machine-readable instructions that may be stored in a memory device. | 1. A method for processing image data, comprising using a processor to perform: providing input image data; segmenting the input image data to generate: a background layer representing the background attributes of an image; a selector layer for identifying one or more foreground attributes of the image not included in the background layer; and a foreground layer representing the foreground attributes of the image; generating a black text layer comprising pixel data representing black text in the input image data; assigning the black text pixel data a predetermined value for the color black; and integrating the background layer, the selector layer, the foreground layer, and the black text layer into a data structure having machine-readable instructions that may be stored in a memory device. 9. The method according to claim 1 , further comprising using a processor to perform: altering the resolution of the black text pixel data to be different from the input image data. | 0.872893 |
9,465,797 | 2 | 5 | 2. A computer-implemented method comprising: receiving, at a machine translation system, first original text in a source language and data identifying a target language; obtaining, at the machine translation system, a plurality of bridge language translations for the first original text from the source language into a bridge language, wherein the plurality of bridge language translations comprises one or more dictionary translations obtained from a dictionary associated with the machine translation system that maps each of a plurality of terms in the source language to respective alternative terms in the bridge language and one or more phrase table translations obtained from a phrase table generated by a statistical machine translation system that maps source language terms to bridge language terms; for each bridge language translation, obtaining, at the machine translation system, one or more candidate translations for the bridge language translation into the target language, wherein the candidate translations comprise one or more dictionary translations obtained from a dictionary associated with the machine translation system that maps each of a plurality of terms in the bridge language to respective alternative terms in the target language; determining, at the machine translation system, that a first candidate translation is a dictionary translation obtained for a particular bridge language translation and that the particular bridge language translation is a dictionary translation obtained for the first original text; determining, at the machine translation system, that the first candidate translation is obtained for two or more distinct bridge language translations, wherein the two or more distinct bridge language translations comprise the particular bridge language translation and one or more phrase table translations that are distinct from the particular bridge language translation; and selecting, at the machine translation system, the first candidate translation as a preferred translation of the first original text from the source language to the target language for the machine translation system. | 2. A computer-implemented method comprising: receiving, at a machine translation system, first original text in a source language and data identifying a target language; obtaining, at the machine translation system, a plurality of bridge language translations for the first original text from the source language into a bridge language, wherein the plurality of bridge language translations comprises one or more dictionary translations obtained from a dictionary associated with the machine translation system that maps each of a plurality of terms in the source language to respective alternative terms in the bridge language and one or more phrase table translations obtained from a phrase table generated by a statistical machine translation system that maps source language terms to bridge language terms; for each bridge language translation, obtaining, at the machine translation system, one or more candidate translations for the bridge language translation into the target language, wherein the candidate translations comprise one or more dictionary translations obtained from a dictionary associated with the machine translation system that maps each of a plurality of terms in the bridge language to respective alternative terms in the target language; determining, at the machine translation system, that a first candidate translation is a dictionary translation obtained for a particular bridge language translation and that the particular bridge language translation is a dictionary translation obtained for the first original text; determining, at the machine translation system, that the first candidate translation is obtained for two or more distinct bridge language translations, wherein the two or more distinct bridge language translations comprise the particular bridge language translation and one or more phrase table translations that are distinct from the particular bridge language translation; and selecting, at the machine translation system, the first candidate translation as a preferred translation of the first original text from the source language to the target language for the machine translation system. 5. The method of claim 2 , wherein the phrase table that maps bridge language terms to target language terms and the phrase table that maps source language terms to bridge language terms are generated by a statistical machine translation system. | 0.795492 |
9,922,050 | 1 | 2 | 1. A system comprising: a data store configured to store at least a plurality of color palettes and a plurality of images, wherein each color palette of the plurality of color palettes comprises a name and a plurality of colors, wherein each image of the plurality of images comprises one or more colors, and wherein each image of the plurality of images is associated with an item type; and a hardware processor in communication with the data store, the hardware processor configured to execute computer-executable instructions to at least: receive a search phrase; select a subset of color palettes from the plurality of color palettes, wherein selecting the subset of color palettes comprises: identifying, from the plurality of color palettes, each color palette of the subset of the plurality of color palettes comprising a name matching the search phrase; determining, from the plurality of color palettes, a greater number of color palettes comprising a first color and having a creation time within a threshold period of time than a number of color palettes comprising the first color and having a creation time outside of the threshold period; and determining, from the plurality of color palettes, each color palette of the subset of the plurality of color palettes comprising the first color; select a priority color palette from the subset of color palettes, wherein the priority color palette is selected from the subset of color palettes based at least in part on a creation time of the priority color palette being more recent than a creation time of another color palette from the subset of color palettes; identify a first subset of the plurality of images matching a first color of the priority color palette, wherein the identification of the first subset of the plurality of images is based at least in part on a first item type associated with the first subset of the plurality of images, and wherein a first image of the first subset of the plurality of images is associated with a first item; identify a second subset of the plurality of images matching a second color of the priority color palette, wherein the identification of the second subset of the plurality of images is based at least in part on a second item type associated with the second subset of the plurality of images, and wherein a second image of the second subset of the plurality of images is associated with a second item; and provide the first subset of the plurality of images and the second subset of the plurality of images for presentation. | 1. A system comprising: a data store configured to store at least a plurality of color palettes and a plurality of images, wherein each color palette of the plurality of color palettes comprises a name and a plurality of colors, wherein each image of the plurality of images comprises one or more colors, and wherein each image of the plurality of images is associated with an item type; and a hardware processor in communication with the data store, the hardware processor configured to execute computer-executable instructions to at least: receive a search phrase; select a subset of color palettes from the plurality of color palettes, wherein selecting the subset of color palettes comprises: identifying, from the plurality of color palettes, each color palette of the subset of the plurality of color palettes comprising a name matching the search phrase; determining, from the plurality of color palettes, a greater number of color palettes comprising a first color and having a creation time within a threshold period of time than a number of color palettes comprising the first color and having a creation time outside of the threshold period; and determining, from the plurality of color palettes, each color palette of the subset of the plurality of color palettes comprising the first color; select a priority color palette from the subset of color palettes, wherein the priority color palette is selected from the subset of color palettes based at least in part on a creation time of the priority color palette being more recent than a creation time of another color palette from the subset of color palettes; identify a first subset of the plurality of images matching a first color of the priority color palette, wherein the identification of the first subset of the plurality of images is based at least in part on a first item type associated with the first subset of the plurality of images, and wherein a first image of the first subset of the plurality of images is associated with a first item; identify a second subset of the plurality of images matching a second color of the priority color palette, wherein the identification of the second subset of the plurality of images is based at least in part on a second item type associated with the second subset of the plurality of images, and wherein a second image of the second subset of the plurality of images is associated with a second item; and provide the first subset of the plurality of images and the second subset of the plurality of images for presentation. 2. The system of claim 1 , wherein the priority color palette is further selected from the subset of color palettes based at least in part on the creation time of the priority color palette being a latest creation time of the subset of color palettes. | 0.80205 |
8,713,696 | 1 | 18 | 1. A computer implemented method in a content server for dynamically creating a bundle of content protected by digital rights management, comprising: storing user information for a plurality of users, including a first user; receiving over a network a request for content, the request having an indication of a bundle and an indication of a user identity, the user identity corresponding to the first user; in response to the request and the user identity, automatically determining, using at least one computer system, a set of source portions that correspond to the indicated bundle, the determining including selecting the set of source portions based at least in part on one or more user-specific attributes, obtained using the user identity from the user information stored for the first user, to comprise at least one digital rights management portion, at least one user interface portion, and at least one content portion, the at least one user interface portion to control access to and rendering of the at least one content portion, the at least one digital rights management portion to limit access to the at least one content portion to an authorized user, and wherein the one or more user-specific attributes is at least one of the following: a geographic location of the first user, a subscription level associated with the first user, a demographic property of the first user, a usage history of the first user, and an activity preference of the first user; generating, using the at least one computer system, a set of intermediate portions by translating each portion of the determined set of source portions into a corresponding intermediate portion; merging, using the at least one computer system, each intermediate portion of the generated set of intermediate portions into a secured destination file that corresponds to the requested content; and forwarding the secured destination file over the network. | 1. A computer implemented method in a content server for dynamically creating a bundle of content protected by digital rights management, comprising: storing user information for a plurality of users, including a first user; receiving over a network a request for content, the request having an indication of a bundle and an indication of a user identity, the user identity corresponding to the first user; in response to the request and the user identity, automatically determining, using at least one computer system, a set of source portions that correspond to the indicated bundle, the determining including selecting the set of source portions based at least in part on one or more user-specific attributes, obtained using the user identity from the user information stored for the first user, to comprise at least one digital rights management portion, at least one user interface portion, and at least one content portion, the at least one user interface portion to control access to and rendering of the at least one content portion, the at least one digital rights management portion to limit access to the at least one content portion to an authorized user, and wherein the one or more user-specific attributes is at least one of the following: a geographic location of the first user, a subscription level associated with the first user, a demographic property of the first user, a usage history of the first user, and an activity preference of the first user; generating, using the at least one computer system, a set of intermediate portions by translating each portion of the determined set of source portions into a corresponding intermediate portion; merging, using the at least one computer system, each intermediate portion of the generated set of intermediate portions into a secured destination file that corresponds to the requested content; and forwarding the secured destination file over the network. 18. The method of claim 1 wherein the user interface portion includes controls for at least one of zooming, scrolling, printing, or paginating the at least one content portion. | 0.757576 |
8,756,245 | 11 | 16 | 11. A natural language search system comprising: a processor; a computer readable medium connected to the processor; and a set of instructions on the computer readable medium that are executable by the processor, including: a search engine to receive a search query in the form of a natural language question; a database to store a plurality of database items that are matched to the search query organized into columns and a question annotated to each of the columns, the question being a parameterized question that is answerable by the database items in the column, the parameterized question having a plurality of parameters replaceable by the database items, and a parameterized answer annotated to each of the columns, the parameterized answer having a plurality of parameters corresponding to the plurality of parameters in the parameterized question, the parameters replaceable by the database items and the parameterized answer being matched to the parameterized question by replacing the parameters in the parameterized question with the database items; and a server to search the database for a question that matches the search query and provide an answer corresponding to the database item, parameterized question and parameterized answer to the search engine. | 11. A natural language search system comprising: a processor; a computer readable medium connected to the processor; and a set of instructions on the computer readable medium that are executable by the processor, including: a search engine to receive a search query in the form of a natural language question; a database to store a plurality of database items that are matched to the search query organized into columns and a question annotated to each of the columns, the question being a parameterized question that is answerable by the database items in the column, the parameterized question having a plurality of parameters replaceable by the database items, and a parameterized answer annotated to each of the columns, the parameterized answer having a plurality of parameters corresponding to the plurality of parameters in the parameterized question, the parameters replaceable by the database items and the parameterized answer being matched to the parameterized question by replacing the parameters in the parameterized question with the database items; and a server to search the database for a question that matches the search query and provide an answer corresponding to the database item, parameterized question and parameterized answer to the search engine. 16. The system of claim 11 , further comprising: a question answering interface, in communication with the database, the question answering interface having a question answering algorithm that searches the database for an annotated question corresponding to a question that needs to be answered and answers the question that needs to be answered with the parameterized answer and the database items. | 0.50125 |
9,298,702 | 46 | 47 | 46. The method of claim 1 , further including: transforming a representation of a knowledge structure within the semantic network into a document, the knowledge structure containing information relevant to one of the entities; storing the document within the document repository. | 46. The method of claim 1 , further including: transforming a representation of a knowledge structure within the semantic network into a document, the knowledge structure containing information relevant to one of the entities; storing the document within the document repository. 47. The method of claim 46 wherein the document is formatted in a structured text format. | 0.975374 |
9,582,533 | 5 | 6 | 5. The content reproduction device according to claim 1 , wherein the one or more memory devices stores instructions that further cause the one or more processing devices to: with reference to priority data setting priorities for a plurality of respective databases, display, during the content reproduction, preferentially (i) an object corresponding to a database having a high priority over (ii) an object corresponding to a database having a low priority, wherein the one or more memory devices stores instructions that further cause the one or more processing devices to: in a case where an object displayed has been selected, search a database corresponding to the selected object. | 5. The content reproduction device according to claim 1 , wherein the one or more memory devices stores instructions that further cause the one or more processing devices to: with reference to priority data setting priorities for a plurality of respective databases, display, during the content reproduction, preferentially (i) an object corresponding to a database having a high priority over (ii) an object corresponding to a database having a low priority, wherein the one or more memory devices stores instructions that further cause the one or more processing devices to: in a case where an object displayed has been selected, search a database corresponding to the selected object. 6. The content reproduction device according to claim 5 , wherein the one or more memory devices stores instructions that further cause the one or more processing devices to: with reference to use history data including, in association with each other, (i) information on the plurality of databases and (ii) frequency information indicative of a frequency of searches run with use of each of the plurality of databases, generate the priority data so that the priority data sets a higher priority for a database having a higher frequency of searches. | 0.791572 |
10,056,077 | 1 | 2 | 1. A method of entering text into a music system using a processor, comprising: recording speech presented by a user using a resident capture facility; providing the speech as a recording to a speech recognition facility; selecting at least one statistical language model, including a large vocabulary statistical language model, from a set of language models based at least in part on contextual information relating to the recording, wherein the at least one statistical language model selected includes a general language model for artists, a general language model for song titles, and a general language model for music types; determining that the at least one statistical language model selected provides insufficient recognition output and requires an additional recognition pass of the recording; conducting the additional recognition pass of the recording; selecting at least one other statistical language model based at least in part on the additional recognition pass of the recording and client state information of the recording; generating results utilizing the speech of the recording recognized by the speech recognition facility; and using the results in the music system, wherein the music system provides information relating to a music application to the speech recognition facility, wherein generating the results is based at least in part on the information, wherein the information relating to the music application includes contextual information within the music application, and wherein the contextual information includes at least one of a usage history of the music application and information from at least one of a favorites list and playlists of the user. | 1. A method of entering text into a music system using a processor, comprising: recording speech presented by a user using a resident capture facility; providing the speech as a recording to a speech recognition facility; selecting at least one statistical language model, including a large vocabulary statistical language model, from a set of language models based at least in part on contextual information relating to the recording, wherein the at least one statistical language model selected includes a general language model for artists, a general language model for song titles, and a general language model for music types; determining that the at least one statistical language model selected provides insufficient recognition output and requires an additional recognition pass of the recording; conducting the additional recognition pass of the recording; selecting at least one other statistical language model based at least in part on the additional recognition pass of the recording and client state information of the recording; generating results utilizing the speech of the recording recognized by the speech recognition facility; and using the results in the music system, wherein the music system provides information relating to a music application to the speech recognition facility, wherein generating the results is based at least in part on the information, wherein the information relating to the music application includes contextual information within the music application, and wherein the contextual information includes at least one of a usage history of the music application and information from at least one of a favorites list and playlists of the user. 2. The method of claim 1 , further comprising using user feedback to adapt the at least one statistical language model selected. | 0.804878 |
7,917,544 | 6 | 10 | 6. A tangible computer-readable medium having instructions stored thereon, the instructions executable by a computing device in order to cause the computing device to perform operations comprising: accessing a data structure having a plurality of postal address elements selectively associated with a plurality of postal addresses such that each postal address is associated with a subset of the postal address elements that collectively indicate the respective postal address; receiving location information regarding an individual, the location information indicating at least a portion of one or more of a city, a state, or a postal code; receiving at least a portion of a building number associated with the individual; identifying a postal address in the data structure that is associated with a location element substantially matching the received location information and is associated with a building number element substantially matching the received building number; and providing postal address elements associated with the identified postal address to a separate software application so that the identified postal address is usable in the separate software application. | 6. A tangible computer-readable medium having instructions stored thereon, the instructions executable by a computing device in order to cause the computing device to perform operations comprising: accessing a data structure having a plurality of postal address elements selectively associated with a plurality of postal addresses such that each postal address is associated with a subset of the postal address elements that collectively indicate the respective postal address; receiving location information regarding an individual, the location information indicating at least a portion of one or more of a city, a state, or a postal code; receiving at least a portion of a building number associated with the individual; identifying a postal address in the data structure that is associated with a location element substantially matching the received location information and is associated with a building number element substantially matching the received building number; and providing postal address elements associated with the identified postal address to a separate software application so that the identified postal address is usable in the separate software application. 10. The computer-readable medium of claim 6 , wherein said identifying comprises searching the data structure for an exact match between a location element and the received location information and then, if an exact match is not located, searching the data structure for a close match between the location element and the received location information. | 0.71885 |
9,245,263 | 1 | 15 | 1. A method for adding functionality to a web-page served to a client-computer by a first web-server, the method comprising: at a second web-server including a microprocessor, receiving a first request from the client-computer for client-side script source code to add purchase functionality to the web-page being served by the first web-server; sending the client-side script source code for purchase functionality to the client-computer using the microprocessor, wherein said client-side script source code for purchase functionality includes instructions that cause the client-computer to insert a script element into the web-page; receiving a second request for client-side script source code from the client-computer, the second request including a URL with information about objects identified in the web-page as relating to the purchase functionality and a request for information about the objects; generating client-side script source code, based on the second request, including information about the objects encoded using a scripting language; sending the client-side script source code including the information about the objects to the client-computer using the microprocessor; receiving a third request for client-side script source code from the client computer, the third request including a URL with instruction to complete the purchase from the client-computer and payment information; and sending client-side script source code including a confirmation of the completion of the purchase encoded using the scripting language to the client-computer and instructions to cause the client-computer to display the confirmation using the microprocessor. | 1. A method for adding functionality to a web-page served to a client-computer by a first web-server, the method comprising: at a second web-server including a microprocessor, receiving a first request from the client-computer for client-side script source code to add purchase functionality to the web-page being served by the first web-server; sending the client-side script source code for purchase functionality to the client-computer using the microprocessor, wherein said client-side script source code for purchase functionality includes instructions that cause the client-computer to insert a script element into the web-page; receiving a second request for client-side script source code from the client-computer, the second request including a URL with information about objects identified in the web-page as relating to the purchase functionality and a request for information about the objects; generating client-side script source code, based on the second request, including information about the objects encoded using a scripting language; sending the client-side script source code including the information about the objects to the client-computer using the microprocessor; receiving a third request for client-side script source code from the client computer, the third request including a URL with instruction to complete the purchase from the client-computer and payment information; and sending client-side script source code including a confirmation of the completion of the purchase encoded using the scripting language to the client-computer and instructions to cause the client-computer to display the confirmation using the microprocessor. 15. The method of claim 1 , wherein at least one of items purchased by a consumer is a downloadable item that is not currently available, the method further comprising: providing an authorization code to allow downloading of the at least one of items purchased when it becomes available. | 0.617333 |
9,355,385 | 16 | 18 | 16. A computer-readable storage medium having instructions stored thereon that, when executed, cause a processor to perform a method comprising: in response to receiving, from a personal information management application, a request message comprising a find places request and content from a location field within a meeting item of the personal information management application, parsing the request message for a place name, street address, or source-related identifier, wherein the meeting item includes: a meeting request form, appointment, email, calendar entry, or a contact entry; querying a web service, a mailbox associated with a user of the personal information management application, and/or a managed database using the place name, the street address, or the source-related identifier; receiving results of the query; and filtering and formatting the results to generate a response message, the response message comprising location information associated with the place name or the source-related identifier indicated by the request message. | 16. A computer-readable storage medium having instructions stored thereon that, when executed, cause a processor to perform a method comprising: in response to receiving, from a personal information management application, a request message comprising a find places request and content from a location field within a meeting item of the personal information management application, parsing the request message for a place name, street address, or source-related identifier, wherein the meeting item includes: a meeting request form, appointment, email, calendar entry, or a contact entry; querying a web service, a mailbox associated with a user of the personal information management application, and/or a managed database using the place name, the street address, or the source-related identifier; receiving results of the query; and filtering and formatting the results to generate a response message, the response message comprising location information associated with the place name or the source-related identifier indicated by the request message. 18. The medium of claim 16 , wherein the response message comprises at least one parameter selected from the group consisting of a display name, street, city, state, country, postal code, post office box, geo-coordinates, uniform resource identifier (URI), a source of location information, phone number, and web site. | 0.690661 |
8,966,360 | 11 | 13 | 11. A computer program product, comprising: a non-transitory computer-readable medium with computer program instructions encoded thereon, wherein the computer program instructions, when processed by a computer, instruct the computer to perform a method for enabling a user to edit a time-based media program that includes recorded speech, the method comprising: causing the computer to receive an augmented transcript of the recorded speech in a mark-up language format, wherein the augmented transcript includes text of a transcript of the recorded speech and timing information that, for each of a plurality of words of the text within the transcript, associates that text word with a temporal location of recorded speech within the time-based media program that corresponds to that text word; in a user interface displaying a transcript text view of the augmented transcript, enabling the user to edit the transcript text of the augmented transcript, wherein the editing comprises selecting one or more spans of text words, copying a span of the text words, and pasting a span of the text words into the transcript text, wherein the association of the timing information with each of the plurality of words within the transcript is preserved during the editing, and wherein editing the augmented transcript does not involve playback of the time-based media; and causing the computer to output the edited augmented transcript, wherein the edited augmented transcript, when received and processed by a time-based media editing system, is capable of causing the time-based media editing system to generate an edited version of the time-based media program that includes time-based media in a temporal sequence that corresponds to the transcript text of the edited augmented transcript. | 11. A computer program product, comprising: a non-transitory computer-readable medium with computer program instructions encoded thereon, wherein the computer program instructions, when processed by a computer, instruct the computer to perform a method for enabling a user to edit a time-based media program that includes recorded speech, the method comprising: causing the computer to receive an augmented transcript of the recorded speech in a mark-up language format, wherein the augmented transcript includes text of a transcript of the recorded speech and timing information that, for each of a plurality of words of the text within the transcript, associates that text word with a temporal location of recorded speech within the time-based media program that corresponds to that text word; in a user interface displaying a transcript text view of the augmented transcript, enabling the user to edit the transcript text of the augmented transcript, wherein the editing comprises selecting one or more spans of text words, copying a span of the text words, and pasting a span of the text words into the transcript text, wherein the association of the timing information with each of the plurality of words within the transcript is preserved during the editing, and wherein editing the augmented transcript does not involve playback of the time-based media; and causing the computer to output the edited augmented transcript, wherein the edited augmented transcript, when received and processed by a time-based media editing system, is capable of causing the time-based media editing system to generate an edited version of the time-based media program that includes time-based media in a temporal sequence that corresponds to the transcript text of the edited augmented transcript. 13. The computer program product of claim 11 , wherein the editing step is performed using a text editor. | 0.841867 |
8,275,614 | 2 | 3 | 2. The support device according to claim 1 , further comprising: a top setting unit for changing, when a part of text is confirmed as a confirmed character string, a top position of an unconfirmed part having unconfirmed text in the speech data, from a top position of an unconfirmed part having unconfirmed text in the speech data before confirmation, to a position advanced from the top position by an utterance time consumed to utter the confirmed character string at the confirmed utterance rate. | 2. The support device according to claim 1 , further comprising: a top setting unit for changing, when a part of text is confirmed as a confirmed character string, a top position of an unconfirmed part having unconfirmed text in the speech data, from a top position of an unconfirmed part having unconfirmed text in the speech data before confirmation, to a position advanced from the top position by an utterance time consumed to utter the confirmed character string at the confirmed utterance rate. 3. The support device according to claim 2 , wherein: the top position setting unit, when a part of text is confirmed as a confirmed character string, changes a first phoneme of an unconfirmed part having unconfirmed text in the speech data, from a first phoneme of an unconfirmed part having unconfirmed text in the speech data before confirmation, to a phoneme right behind the last phoneme uttered within an utterance time consumed to utter the confirmed character string at the confirmed utterance rate. | 0.912223 |
9,275,042 | 2 | 3 | 2. The method as claimed in claim 1 , wherein the corpus is a first corpus, and wherein the method further comprises: computationally processing through a linguistics analysis of a second corpus of user utterances to identify semantic graphs that match respective user utterances in the second corpus, wherein the additional attached semantic graphs of user utterances are from the second corpus. | 2. The method as claimed in claim 1 , wherein the corpus is a first corpus, and wherein the method further comprises: computationally processing through a linguistics analysis of a second corpus of user utterances to identify semantic graphs that match respective user utterances in the second corpus, wherein the additional attached semantic graphs of user utterances are from the second corpus. 3. The method as claimed in claim 2 , wherein the one or more semantic clusters correspond to topics that occur in the first corpus but not in the second corpus. | 0.911246 |
7,600,017 | 46 | 47 | 46. The method of claim 45 , wherein processing the messages further comprises computing a numerical migration score based on the set of messages and movement of influential posting activity within the one or more electronic discussion forums, and the report output is further based upon, at least in part, the numerical migration score. | 46. The method of claim 45 , wherein processing the messages further comprises computing a numerical migration score based on the set of messages and movement of influential posting activity within the one or more electronic discussion forums, and the report output is further based upon, at least in part, the numerical migration score. 47. The method of claim 46 , wherein the migration score provides a measurement, on a numerical scale, of the degree of movement of posting activity levels between topics or groups of topics from the topic. | 0.950433 |
8,837,018 | 2 | 5 | 2. The image scanning apparatus according to claim 1 , wherein the foreign object detecting unit detects a stripe pattern that extends in a scanning direction in the image data on the page of the document scanned by the image scanning unit to detect whether a foreign object exists on the scanning unit. | 2. The image scanning apparatus according to claim 1 , wherein the foreign object detecting unit detects a stripe pattern that extends in a scanning direction in the image data on the page of the document scanned by the image scanning unit to detect whether a foreign object exists on the scanning unit. 5. The image scanning apparatus according to claim 2 , wherein, if the stripe pattern is detected in the image data on the last page of the document, the control unit compares the position of the stripe pattern in the image data on a page of the document, which is scanned before the last page of the document, with the position of the stripe pattern in the image data on the last page of the document to cause the display unit to display the detection of the stripe pattern if a difference in position between the stripe patterns is over a predetermined threshold value. | 0.842178 |
8,768,917 | 16 | 18 | 16. A system comprising: one or more computers and one or more computer-readable storage devices storing instructions that, when executed by the one or more computers cause the one or more computers to perform operations comprising: identifying a candidate n-gram that includes two or more consecutive terms of a search query; determining a first quantity of search results that (i) were identified as responsive to the search query, and (ii) have been selected by other users; determining a second quantity of the search results that (i) were identified as responsive to the search query, (ii) have been selected by the other users, and (iii) are associated with text in which the candidate n-gram occurs; determining a value using the first quantity and the second quantity; and classifying the candidate n-gram as a particular type of n-gram, from among multiple types of n-grams, based on the determined value. | 16. A system comprising: one or more computers and one or more computer-readable storage devices storing instructions that, when executed by the one or more computers cause the one or more computers to perform operations comprising: identifying a candidate n-gram that includes two or more consecutive terms of a search query; determining a first quantity of search results that (i) were identified as responsive to the search query, and (ii) have been selected by other users; determining a second quantity of the search results that (i) were identified as responsive to the search query, (ii) have been selected by the other users, and (iii) are associated with text in which the candidate n-gram occurs; determining a value using the first quantity and the second quantity; and classifying the candidate n-gram as a particular type of n-gram, from among multiple types of n-grams, based on the determined value. 18. The system of claim 16 , wherein classifying the candidate n-gram further comprises: determining that the value is higher than a first predetermined threshold but lower than a second predetermined threshold, then classifying the candidate compound n-gram as a weak n-gram. | 0.501805 |
8,406,384 | 1 | 10 | 1. A computer-implemented method employing at least one hardware based computer processor to develop query tags for classification of user queries to a call routing application, the method comprising: accessing a plurality of user query corpuses containing user queries from a plurality of call routing applications in a plurality of different vertical domains; selecting a set of frequent user queries that appear in a plurality of different query corpuses in a plurality of different vertical domains; developing frequent query tags for semantic classification of the frequent user queries; and storing the frequent query tags in a query tag database; wherein the user queries and the query tags are in a first language, and the method further comprises: automatically translating the user queries into a second language; and storing the translated user queries with the frequent query tags in a call routing database for a call routing application in the second language. | 1. A computer-implemented method employing at least one hardware based computer processor to develop query tags for classification of user queries to a call routing application, the method comprising: accessing a plurality of user query corpuses containing user queries from a plurality of call routing applications in a plurality of different vertical domains; selecting a set of frequent user queries that appear in a plurality of different query corpuses in a plurality of different vertical domains; developing frequent query tags for semantic classification of the frequent user queries; and storing the frequent query tags in a query tag database; wherein the user queries and the query tags are in a first language, and the method further comprises: automatically translating the user queries into a second language; and storing the translated user queries with the frequent query tags in a call routing database for a call routing application in the second language. 10. A method according to claim 1 , further comprising: using the stored query tags as an input for injection of soft knowledge in a call steering application. | 0.790237 |
9,934,777 | 5 | 9 | 5. A computer-implemented method, comprising: identifying a first language model configured for speech processing corresponding to multiple devices; identifying a first table representing words corresponding to the first language model; identifying a plurality of word strings associated with a first user profile; creating a second language model configured for speech processing corresponding to the plurality of word strings, the second language model including a plurality of references to a second table; generating a second table representing words of the plurality of word strings, the second table including at least: a first entry including a first word in the plurality of word strings and a first index value corresponding to a third entry in the first table, the third entry corresponding to the first word, and a second entry including a second word in the plurality of word strings and a second index value corresponding to a fourth entry in the first table, the fourth entry corresponding to the second word; generating a second language model configured for speech processing corresponding to the first user profile, the second language model including a third index value corresponding to the first entry and a fourth index value corresponding to the second entry; and storing the second table and the second language model as associated with the first user profile. | 5. A computer-implemented method, comprising: identifying a first language model configured for speech processing corresponding to multiple devices; identifying a first table representing words corresponding to the first language model; identifying a plurality of word strings associated with a first user profile; creating a second language model configured for speech processing corresponding to the plurality of word strings, the second language model including a plurality of references to a second table; generating a second table representing words of the plurality of word strings, the second table including at least: a first entry including a first word in the plurality of word strings and a first index value corresponding to a third entry in the first table, the third entry corresponding to the first word, and a second entry including a second word in the plurality of word strings and a second index value corresponding to a fourth entry in the first table, the fourth entry corresponding to the second word; generating a second language model configured for speech processing corresponding to the first user profile, the second language model including a third index value corresponding to the first entry and a fourth index value corresponding to the second entry; and storing the second table and the second language model as associated with the first user profile. 9. The computer-implemented method of claim 5 , further comprising: determining that a third word in the plurality of word strings is not represented in the first table; and performing grapheme-to-phoneme processing to determine pronunciation data representing an estimated pronunciation of the third word, wherein creating the second table further comprises creating a third entry including a reference to the pronunciation data. | 0.824346 |
7,957,975 | 12 | 13 | 12. The system of claim 11 , wherein the voice command is stored in a storage media on the wireless communication, and wherein the voice command is stored on the server computer; wherein the software based application presents a list of potential commands to be recorded; and wherein the software based application presents a list of potential commands to be executed. | 12. The system of claim 11 , wherein the voice command is stored in a storage media on the wireless communication, and wherein the voice command is stored on the server computer; wherein the software based application presents a list of potential commands to be recorded; and wherein the software based application presents a list of potential commands to be executed. 13. The system of claim 12 , wherein in response to the voice command, the system directs the voice command to specific content providers. | 0.971238 |
8,108,371 | 10 | 14 | 10. A method for displaying a set of search results received in response to a search-engine query, the method comprising: submitting the search-engine query that is input into a field of a web browser running on a computing device, the web browser including a control that enables thumbnails to be presented together with the set of search results; receiving a plurality of web-page addresses of web pages deemed to satisfy the search-engine query; without user intervention, creating a set of instances of the control, wherein each instance is associated with a respective web-page address selected from among the plurality of web-page addresses; simultaneously executing a plurality of web browsers on background threads of the web browser, wherein each web browser of the plurality of web browsers is associated with a respective instance from among the set of instances and wherein each web browser executes the respective web-page address of the respective instance associated therewith; receiving the web pages deemed to satisfy the search-engine query, wherein the web pages are stored in a cache of the computing device and wherein, because the plurality of web browsers are executed after submission of the search-engine query, the web pages stored in the cache are current relative to the search-engine query; and from a web page stored in the cache, creating a thumbnail depicting the web page, wherein the thumbnail is displayed adjacent to a web-page address of the web page. | 10. A method for displaying a set of search results received in response to a search-engine query, the method comprising: submitting the search-engine query that is input into a field of a web browser running on a computing device, the web browser including a control that enables thumbnails to be presented together with the set of search results; receiving a plurality of web-page addresses of web pages deemed to satisfy the search-engine query; without user intervention, creating a set of instances of the control, wherein each instance is associated with a respective web-page address selected from among the plurality of web-page addresses; simultaneously executing a plurality of web browsers on background threads of the web browser, wherein each web browser of the plurality of web browsers is associated with a respective instance from among the set of instances and wherein each web browser executes the respective web-page address of the respective instance associated therewith; receiving the web pages deemed to satisfy the search-engine query, wherein the web pages are stored in a cache of the computing device and wherein, because the plurality of web browsers are executed after submission of the search-engine query, the web pages stored in the cache are current relative to the search-engine query; and from a web page stored in the cache, creating a thumbnail depicting the web page, wherein the thumbnail is displayed adjacent to a web-page address of the web page. 14. The method of claim 10 , wherein the web pages are retrieved in a manner that restricts execution of web-page active components. | 0.684211 |
8,386,335 | 1 | 10 | 1. A method comprising: providing a document that includes a navigational tool configured to permit navigation among hierarchical categories of products, the navigational tool presenting a first set of sub-categories each corresponding to a different cluster of products; identifying unstructured text of one or more consumer-submitted comments in a document associated with a first product; identifying, in the unstructured text of the one or more consumer-submitted comments, a reference to a second product different from the first product; determining one or more relationships between the first product and the second product based on content of the unstructured text of the one or more consumer-submitted comments; in response to determining the one or more relationships between the first product and the second product, including the first product and the second product in a cluster of related products; in response to determining the one or more relationships between the first product and the second product, changing the first set of sub-categories to generate a second set of sub-categories different from the first set of sub-categories, the second set of sub-categories comprising a sub-category that corresponds to the cluster that includes the first product and the second product; and after changing the first set of sub-categories, providing the document that includes the navigational tool such that the navigational tool presents the second set of sub-categories, wherein each of the above are performed by one or more processing devices. | 1. A method comprising: providing a document that includes a navigational tool configured to permit navigation among hierarchical categories of products, the navigational tool presenting a first set of sub-categories each corresponding to a different cluster of products; identifying unstructured text of one or more consumer-submitted comments in a document associated with a first product; identifying, in the unstructured text of the one or more consumer-submitted comments, a reference to a second product different from the first product; determining one or more relationships between the first product and the second product based on content of the unstructured text of the one or more consumer-submitted comments; in response to determining the one or more relationships between the first product and the second product, including the first product and the second product in a cluster of related products; in response to determining the one or more relationships between the first product and the second product, changing the first set of sub-categories to generate a second set of sub-categories different from the first set of sub-categories, the second set of sub-categories comprising a sub-category that corresponds to the cluster that includes the first product and the second product; and after changing the first set of sub-categories, providing the document that includes the navigational tool such that the navigational tool presents the second set of sub-categories, wherein each of the above are performed by one or more processing devices. 10. The method of claim 1 , wherein changing the first set of sub-categories to generate the second set of sub-categories comprises one or more of generating the second set of sub-categories to include a number of sub-categories different from the number of sub-categories included in the first set of sub-categories, changing a type of one of the sub-categories included in the first set of sub-categories, and changing a name of one of the sub-categories included in the first set of sub-categories. | 0.500996 |
9,171,082 | 7 | 8 | 7. A system to provide contractual precedents, the system comprising: a server device including a processor module configured to: receive a user selection of one or more predefined queries for contractual information; execute a search of one or more databases including agreements based on the received user selection, the received user selection defining search results; and receive a user-defined filter associated with the contractual information, the user-defined filter being based on at least a first trait, the user-defined filter being associated with an identifier corresponding to the user, the identifier defining access rights of at least one additional user; and execute the user-defined filter thereby filtering the search results; and an access device configured to: display a subset of the search results based on the user-defined filter associated with the identifier corresponding to the user; and transmit at least one contractual provision selected from the subset of the search results into an editable document to facilitate review in an active user interface using an editing application. | 7. A system to provide contractual precedents, the system comprising: a server device including a processor module configured to: receive a user selection of one or more predefined queries for contractual information; execute a search of one or more databases including agreements based on the received user selection, the received user selection defining search results; and receive a user-defined filter associated with the contractual information, the user-defined filter being based on at least a first trait, the user-defined filter being associated with an identifier corresponding to the user, the identifier defining access rights of at least one additional user; and execute the user-defined filter thereby filtering the search results; and an access device configured to: display a subset of the search results based on the user-defined filter associated with the identifier corresponding to the user; and transmit at least one contractual provision selected from the subset of the search results into an editable document to facilitate review in an active user interface using an editing application. 8. The system of claim 7 , wherein the first trait is one of a company name, geographic region, an industry, a deal size, a contractual type and an additional trait. | 0.628378 |
7,676,798 | 19 | 21 | 19. A system that handles input parameters, the system comprising: one or more processors; and memory to store a plurality of computer-executable instructions for execution by the one or more processors, the computer-executable instructions, when execute, operable to: receive a string into a command line interactive environment, the string including a plurality of pipelined cmdlets, the plurality of pipelined cmdlets to share use of one or more common directive functions provided by an administrative tool framework, the one or more common directive functions are applicable to each of the cmdlets via attributions; identify an attribution for each of the plurality of pipelined cmdlets within the string, each attribution to specify a constraint for an associated construct; identify the associated construct of each attribution in the string; save information that correlates each constraint with its associated construct as metadata that is associated with each construct; and execute the string in the interactive environment, wherein the execution includes: executing a first cmdlet of the plurality of pipelined cmdlets by using metadata associated with a first construct to apply a first constraint to the first construct to produce output objects; providing the output objects to a second cmdlet of the plurality of pipelined cmdlets as input for a second construct; and executing the second cmdlet by using metadata associated with the second construct to apply a second constraint to the second construct, wherein the one or more common directive functions used by each cmdlet is specified by a corresponding data structure that is instantiated into an object for the administrative tool framework. | 19. A system that handles input parameters, the system comprising: one or more processors; and memory to store a plurality of computer-executable instructions for execution by the one or more processors, the computer-executable instructions, when execute, operable to: receive a string into a command line interactive environment, the string including a plurality of pipelined cmdlets, the plurality of pipelined cmdlets to share use of one or more common directive functions provided by an administrative tool framework, the one or more common directive functions are applicable to each of the cmdlets via attributions; identify an attribution for each of the plurality of pipelined cmdlets within the string, each attribution to specify a constraint for an associated construct; identify the associated construct of each attribution in the string; save information that correlates each constraint with its associated construct as metadata that is associated with each construct; and execute the string in the interactive environment, wherein the execution includes: executing a first cmdlet of the plurality of pipelined cmdlets by using metadata associated with a first construct to apply a first constraint to the first construct to produce output objects; providing the output objects to a second cmdlet of the plurality of pipelined cmdlets as input for a second construct; and executing the second cmdlet by using metadata associated with the second construct to apply a second constraint to the second construct, wherein the one or more common directive functions used by each cmdlet is specified by a corresponding data structure that is instantiated into an object for the administrative tool framework. 21. The system of claim 19 , wherein at least one of the attributions specifies applying intellisense to the construct to auto-complete the construct. | 0.76489 |
8,949,237 | 1 | 5 | 1. At least one computer-readable memory, which is not a signal, comprising computer-executable instructions that, when executed by at least one processor, perform a method, the method comprising acts of: receiving inputs relating to a plurality of entities in a set, each input indicating approval of an entity in the set for another entity in the set; maintaining a database storing indications of approval associated with each of the plurality of entities in the set; processing the database to determine one or more clusters in the set, the clusters each comprising entities for which a metric of approval of members within the cluster exceeds a metric of approval from entities in the set that are not in the cluster, the processing the database to determine one or more clusters in the set includes: selecting an entity as a seed for the cluster; adding entities to the cluster, the adding comprising iteratively: for a candidate entity determining a fraction of indications of approval for the candidate entity received from entities within the cluster; and selectively adding the candidate entity based, at least in part, on the fraction being above a threshold; and after selectively adding the candidate item, selectively removing items from the cluster that do not meet at least one relatedness criteria; and presenting a suggestion, the suggestion relating to an action involving one or more entities and the suggestion being developed based on the one or more clusters such that the one or more entities are within at least one of the one or more clusters. | 1. At least one computer-readable memory, which is not a signal, comprising computer-executable instructions that, when executed by at least one processor, perform a method, the method comprising acts of: receiving inputs relating to a plurality of entities in a set, each input indicating approval of an entity in the set for another entity in the set; maintaining a database storing indications of approval associated with each of the plurality of entities in the set; processing the database to determine one or more clusters in the set, the clusters each comprising entities for which a metric of approval of members within the cluster exceeds a metric of approval from entities in the set that are not in the cluster, the processing the database to determine one or more clusters in the set includes: selecting an entity as a seed for the cluster; adding entities to the cluster, the adding comprising iteratively: for a candidate entity determining a fraction of indications of approval for the candidate entity received from entities within the cluster; and selectively adding the candidate entity based, at least in part, on the fraction being above a threshold; and after selectively adding the candidate item, selectively removing items from the cluster that do not meet at least one relatedness criteria; and presenting a suggestion, the suggestion relating to an action involving one or more entities and the suggestion being developed based on the one or more clusters such that the one or more entities are within at least one of the one or more clusters. 5. The computer-readable memory of claim 1 , wherein the entity selected as the seed is an item in a dataset about which information has been requested by a user, and wherein the candidate entity has a node in a graph that is close to a node representing the seed. | 0.501887 |
8,938,438 | 7 | 12 | 7. A system, comprising a server computer communicatively coupled to a network and comprising: a website; a web page within the website; and a content within the web page; and at least one software module running on the server computer and configured to: receive: a selection of the web page for a page-level content analysis and optimization; and at least one keyword topically relevant to the content; identify at least one instance of the at least one keyword within the content; request, from a search engine: a first metric comprising a quantity of times, during a time period, that the at least one keyword has appeared in a search query along with at least one question keyword; and a second metric comprising a probability of receiving a high search engine rank associated with the at least one keyword and the at least one question keyword; receive, from the search engine, the first metric and the second metric; calculate, from the first metric and the second metric, a keyword effectiveness index wherein the keyword effectiveness index: identifies at least one most often searched keyword or question searched in the search engine; is utilized by the server computer to: generate, organize and sequence a recommended keyword list; and calculate an assigned effectiveness ranking for each of at least one request result as reflected in the recommended keyword list; and comprises: a logarithm of the first metric multiplied by the difference of the second metric subtracted from 1; and a recommendation score for each of the at least one request result; generate: at least one recommendation to include a high ranked suggested content, according to the keyword effectiveness index, on the web page; a keyword count comprising a list of instances, within the content, of the at least one keyword; a keyword percentage comparing the at least one keyword to a total of words within the content; a keyword grouping count comprising a list of instances of at least one grouping of content words within the content; and a keyword grouping percentage comparing the at least one grouping to the total of words; assign a favorability to a request result, wherein: a favorable result comprises the request result higher than a first number; a non-favorable result comprises the request result lower than a second number; and an ideal or neutral result comprises the request result between the first number and the second number; associate with the favorability a visual indicator, comprising a color, an interface element or a graphic, wherein: a first visual indicator is associated with the favorable result; a second visual indicator is associated with the non-favorable result; and a third visual indicator is associated with the ideal or neutral result; transmit, to a client computer communicatively coupled to the network: the at least one recommendation; the favorability; and the visual indicator. | 7. A system, comprising a server computer communicatively coupled to a network and comprising: a website; a web page within the website; and a content within the web page; and at least one software module running on the server computer and configured to: receive: a selection of the web page for a page-level content analysis and optimization; and at least one keyword topically relevant to the content; identify at least one instance of the at least one keyword within the content; request, from a search engine: a first metric comprising a quantity of times, during a time period, that the at least one keyword has appeared in a search query along with at least one question keyword; and a second metric comprising a probability of receiving a high search engine rank associated with the at least one keyword and the at least one question keyword; receive, from the search engine, the first metric and the second metric; calculate, from the first metric and the second metric, a keyword effectiveness index wherein the keyword effectiveness index: identifies at least one most often searched keyword or question searched in the search engine; is utilized by the server computer to: generate, organize and sequence a recommended keyword list; and calculate an assigned effectiveness ranking for each of at least one request result as reflected in the recommended keyword list; and comprises: a logarithm of the first metric multiplied by the difference of the second metric subtracted from 1; and a recommendation score for each of the at least one request result; generate: at least one recommendation to include a high ranked suggested content, according to the keyword effectiveness index, on the web page; a keyword count comprising a list of instances, within the content, of the at least one keyword; a keyword percentage comparing the at least one keyword to a total of words within the content; a keyword grouping count comprising a list of instances of at least one grouping of content words within the content; and a keyword grouping percentage comparing the at least one grouping to the total of words; assign a favorability to a request result, wherein: a favorable result comprises the request result higher than a first number; a non-favorable result comprises the request result lower than a second number; and an ideal or neutral result comprises the request result between the first number and the second number; associate with the favorability a visual indicator, comprising a color, an interface element or a graphic, wherein: a first visual indicator is associated with the favorable result; a second visual indicator is associated with the non-favorable result; and a third visual indicator is associated with the ideal or neutral result; transmit, to a client computer communicatively coupled to the network: the at least one recommendation; the favorability; and the visual indicator. 12. The system of claim 7 , wherein the server computer is further configured to: receive a selection of: the web page to be optimized for search engine optimization; at least one optimization option; and a filter for at least one request result, the filter comprising: the at least one question keyword; at least one geographical area; or at least one language; responsive to the selection of the filter, filter the at least one request result; and receive the at least one request result comprising the first metric and the second metric according to the filter. | 0.639386 |
8,463,595 | 1 | 3 | 1. A system for performing detailed sentiment analysis, comprising: a processor configured to: analyze a first portion of text included in a content source to generate a first sentiment score for a first entity on a first dimension analyze a second portion of text included in the content source to generate a second sentiment score for the first entity on a second dimension, wherein the first and second portions of text are at least partially overlapping; and a memory coupled to the processor and configured to provide the processor with instructions. | 1. A system for performing detailed sentiment analysis, comprising: a processor configured to: analyze a first portion of text included in a content source to generate a first sentiment score for a first entity on a first dimension analyze a second portion of text included in the content source to generate a second sentiment score for the first entity on a second dimension, wherein the first and second portions of text are at least partially overlapping; and a memory coupled to the processor and configured to provide the processor with instructions. 3. The system of claim 1 wherein the content source comprises at least one result of performing a search for the first entity in a search engine. | 0.624352 |
7,890,324 | 7 | 9 | 7. A method of temporarily providing one of a plurality of widgets to a user in the course of a multi-modal dialog with a computer device in a map-based application, the method comprising: after first user input received in a combination of a first mode and a second mode, determining whether further user input would be advantageous before the computer device presents information to the user; if further user input would be advantageous, selecting a widget from a plurality of widgets to yield a selected widget, the selected widget being associated with the further user input; maintaining a current display screen context by only presenting additional data on a display in response to the first user input until further user input is received via user interaction with the additional data that clarifies the further user input; maintaining a current dialog context; presenting speech to the user requesting the further user input to clarify the first user input; and presenting the selected widget in a corner of the display for receiving the further user input as directed by the presented speech, wherein the further user input is received in a non-speech mode and provides distance range data that is shown on the display screen as the selected widget is adjusted by the further user input. | 7. A method of temporarily providing one of a plurality of widgets to a user in the course of a multi-modal dialog with a computer device in a map-based application, the method comprising: after first user input received in a combination of a first mode and a second mode, determining whether further user input would be advantageous before the computer device presents information to the user; if further user input would be advantageous, selecting a widget from a plurality of widgets to yield a selected widget, the selected widget being associated with the further user input; maintaining a current display screen context by only presenting additional data on a display in response to the first user input until further user input is received via user interaction with the additional data that clarifies the further user input; maintaining a current dialog context; presenting speech to the user requesting the further user input to clarify the first user input; and presenting the selected widget in a corner of the display for receiving the further user input as directed by the presented speech, wherein the further user input is received in a non-speech mode and provides distance range data that is shown on the display screen as the selected widget is adjusted by the further user input. 9. The method of claim 7 , wherein the computer device dynamically generates the content of the selected widget according to the required further user input. | 0.503165 |
9,202,127 | 15 | 16 | 15. The apparatus of claim 13 , wherein the plurality of text region detectors is configured to: identify at least one non-candidate text region in the plurality of grayscale images; and in response to two or more non-candidate text regions of the at least one non-candidate text region being identified in two or more of the plurality of grayscale images, identify a common portion of the two or more non-candidate text regions. | 15. The apparatus of claim 13 , wherein the plurality of text region detectors is configured to: identify at least one non-candidate text region in the plurality of grayscale images; and in response to two or more non-candidate text regions of the at least one non-candidate text region being identified in two or more of the plurality of grayscale images, identify a common portion of the two or more non-candidate text regions. 16. The apparatus of claim 15 , wherein the plurality of text region detectors is further configured to add the common portion to at least one candidate text region to create an adjusted candidate text region. | 0.904216 |
9,761,241 | 3 | 4 | 3. The mobile device of claim 1 , wherein when it is determined that the conversational service is to be processed locally using the mobile device, the at least one processor is configured to: process the conversational service using conversational resources at the mobile device. | 3. The mobile device of claim 1 , wherein when it is determined that the conversational service is to be processed locally using the mobile device, the at least one processor is configured to: process the conversational service using conversational resources at the mobile device. 4. The mobile device of claim 3 , wherein the at least one processor is configured to: determine, based on results of processing the conversational service using conversational resources at the mobile device, whether to process the conversational service using the at least one server. | 0.895909 |
4,853,873 | 4 | 5 | 4. In an information processing system which has processing means, memory means, and input/output means, a knowledge information processing system comprising: knowledge defining means for defining knowledge information to specify data structure of a result of an inference on the basis of inputted information by interaction with said input/output means; rule defining means for defining rules to renew a result of an inference; and updating means for forming said result of an inference from knowledge defined from the knowledge defining means to specify a data structure, and rules defined by said rule defining means to update said result of an inference. | 4. In an information processing system which has processing means, memory means, and input/output means, a knowledge information processing system comprising: knowledge defining means for defining knowledge information to specify data structure of a result of an inference on the basis of inputted information by interaction with said input/output means; rule defining means for defining rules to renew a result of an inference; and updating means for forming said result of an inference from knowledge defined from the knowledge defining means to specify a data structure, and rules defined by said rule defining means to update said result of an inference. 5. A knowledge information processing system according to claim 4, wherein the updating means includes means for generating updates in an event-driven manner. | 0.731293 |
8,131,547 | 8 | 14 | 8. A computer-readable storage medium storing a set of program instructions executable on a processor device and usable to reduce speech unit boundaries, the instructions causing the processing device to perform the steps: aligning a trained set of HMMs to produce phone labels that are segmented, wherein each phone label has a spectral boundary; performing a spectral boundary correction on the phone labels, wherein spectral boundary correction re-aligns each spectral boundary using bending points of spectral transitions; and synthesizing speech using the phone labels having spectral boundary correction. | 8. A computer-readable storage medium storing a set of program instructions executable on a processor device and usable to reduce speech unit boundaries, the instructions causing the processing device to perform the steps: aligning a trained set of HMMs to produce phone labels that are segmented, wherein each phone label has a spectral boundary; performing a spectral boundary correction on the phone labels, wherein spectral boundary correction re-aligns each spectral boundary using bending points of spectral transitions; and synthesizing speech using the phone labels having spectral boundary correction. 14. The computer-readable storage medium of claim 8 , wherein the instructions further comprise performing spectral boundary correction on the phone labels within a context-dependent time window. | 0.811047 |
8,856,056 | 1 | 6 | 1. A sentiment calculator using social media messages for the real-time evaluation of publicly traded assets wherein a sentiment is a computed integer per asset comprising: means for determining polarity in the social media messages based upon pairs of lexical items in local syntactic context; and means for determining a strength value in the social media messages based upon the pairs of lexical items in local syntactic context. | 1. A sentiment calculator using social media messages for the real-time evaluation of publicly traded assets wherein a sentiment is a computed integer per asset comprising: means for determining polarity in the social media messages based upon pairs of lexical items in local syntactic context; and means for determining a strength value in the social media messages based upon the pairs of lexical items in local syntactic context. 6. The sentiment calculator according to claim 1 , wherein the strength value is an integer, minimally ranging from 1 to 3. | 0.763462 |
8,712,759 | 1 | 3 | 1. A method of semantically parsing a natural language expression, comprising: constructing, by a processor, a first ambiguous meaning representation for a first natural language expression; fully or partially disambiguating, by a processor, the first meaning representation by specializing it by replacing a first semantic descriptor in it by a second, more specific semantic descriptor; associating with at least one semantic descriptor in the meaning representation a weight indicating an evaluation of how good an alternative it is; and adjusting at least one such weight in response to a later parsing or disambiguation action. | 1. A method of semantically parsing a natural language expression, comprising: constructing, by a processor, a first ambiguous meaning representation for a first natural language expression; fully or partially disambiguating, by a processor, the first meaning representation by specializing it by replacing a first semantic descriptor in it by a second, more specific semantic descriptor; associating with at least one semantic descriptor in the meaning representation a weight indicating an evaluation of how good an alternative it is; and adjusting at least one such weight in response to a later parsing or disambiguation action. 3. The method of claim 1 , further comprising further disambiguating a meaning representation that has already been partially disambiguated by further specializing it by replacing the second semantic descriptor in it by a third, even more specific semantic descriptor. | 0.719078 |
9,626,447 | 1 | 3 | 1. A non-transitory computer-readable recording medium having recorded thereon a browser program running on a computer including a storage unit that stores a table showing correspondences between text languages of web pages and character strings used in URLs to indicate the respective text languages, the browser program causing the computer to perform: a receiving step of receiving a designation of a URL; an acquiring step of acquiring information indicating a text language designated by a user; a first searching step of searching for a top-level domain “com” or the top-level domain “com” with a slash “/” added to the end of the designated URL; a determining step of determining whether or not the designated URL includes, at the end thereof, the top-level domain “com” or the top-level domain “com” with a slash “/” added to the end thereof; a second searching step of, when the determining step determines that a top-level domain “com” or the top-level domain “com” with a slash “/” has been added to the end of the designated URL, acquiring source code of a web page indicated by the designated URL, and searching the acquired source code for a URL including a character string corresponding to the designated text language with reference to the table stored in the storage unit; and a display control step of, when the URL including the character string corresponding to the designated text language is found in the second searching step, acquiring a web page indicated by the found URL from a web server over a network and displaying the acquired web page indicated by the found URL, and, when the URL including the character string corresponding to the designated text language is not found in the second searching step, displaying the web page indicated by the designated URL according to the acquired source code. | 1. A non-transitory computer-readable recording medium having recorded thereon a browser program running on a computer including a storage unit that stores a table showing correspondences between text languages of web pages and character strings used in URLs to indicate the respective text languages, the browser program causing the computer to perform: a receiving step of receiving a designation of a URL; an acquiring step of acquiring information indicating a text language designated by a user; a first searching step of searching for a top-level domain “com” or the top-level domain “com” with a slash “/” added to the end of the designated URL; a determining step of determining whether or not the designated URL includes, at the end thereof, the top-level domain “com” or the top-level domain “com” with a slash “/” added to the end thereof; a second searching step of, when the determining step determines that a top-level domain “com” or the top-level domain “com” with a slash “/” has been added to the end of the designated URL, acquiring source code of a web page indicated by the designated URL, and searching the acquired source code for a URL including a character string corresponding to the designated text language with reference to the table stored in the storage unit; and a display control step of, when the URL including the character string corresponding to the designated text language is found in the second searching step, acquiring a web page indicated by the found URL from a web server over a network and displaying the acquired web page indicated by the found URL, and, when the URL including the character string corresponding to the designated text language is not found in the second searching step, displaying the web page indicated by the designated URL according to the acquired source code. 3. The non-transitory computer-readable recording medium according to claim 1 , wherein the acquiring step acquires the information indicating the designated text language from a plurality of predetermined sources, when the designated text language comprises a plurality of designated text languages, the second searching step searches the acquired source code for URLs including character strings corresponding to the respective designated text languages, the browser program causes the computer to further perform: a selection receiving step of, when the URLs including the character strings corresponding to the respective designated text languages are found in the second searching step, receiving a selection of one of the found URLs, and the display control step acquires a web page indicated by the selected URL from the web server and displays the acquired web page indicated by the selected URL. | 0.711551 |
8,984,397 | 1 | 4 | 1. A processing system, comprising: an extensible markup language processor; and a workflow selection processor; said workflow selection processor receiving workflow specifications and document fragments to be processed, a workflow specification describing a process to be carried out on a corresponding document fragment; said workflow selection processor outputting workflow specifications and document fragments to said extensible markup language processor; said extensible markup language processor producing a new workflow specification and a corresponding modified document fragment; said extensible markup language processor outputting said new workflow specification and corresponding modified document fragment to said workflow selection processor; said extensible markup language processor analyzing a document fragment to determine a new workflow specification. | 1. A processing system, comprising: an extensible markup language processor; and a workflow selection processor; said workflow selection processor receiving workflow specifications and document fragments to be processed, a workflow specification describing a process to be carried out on a corresponding document fragment; said workflow selection processor outputting workflow specifications and document fragments to said extensible markup language processor; said extensible markup language processor producing a new workflow specification and a corresponding modified document fragment; said extensible markup language processor outputting said new workflow specification and corresponding modified document fragment to said workflow selection processor; said extensible markup language processor analyzing a document fragment to determine a new workflow specification. 4. The processing system as claimed in claim 1 , wherein said extensible markup language processor acquires required resources. | 0.653005 |
9,710,382 | 1 | 5 | 1. A method of facilitating address translation in a computing environment, said method comprising: obtaining an address to be translated from the address to another address using a hierarchy of address translation structures, the hierarchy of address translation structures comprising a plurality of levels; determining, based on an indicator in an address translations structure of the hierarchy of address translation structures, that at a last level of the plurality of levels that translation through the hierarchy of address translation structures is split into a plurality of translation paths, wherein the plurality of levels comprises 1 to n levels and n is the last level in the hierarchy of the address translation structures, wherein n is an integer greater than or equal to 2, and wherein the indicator is in the address translation structure at the last level of the plurality of levels; traversing the hierarchy of address translation structures to obtain information to be used to translate the address to the another address, wherein the traversing comprises selecting, based on the determining and based on an attribute of the address to be translated, one translation path of the plurality of translation paths from which to obtain the information to be used to translate the address to the another address, wherein the another address is different for each path, wherein the selecting further comprises: selecting, based on the attribute being an instruction fetch, one translation path of the plurality of translation paths comprising a first address translation structure, the one translation path to use a first address in an entry of an address translation structure at the last level to translate the address to the another address; and selecting, based on the attribute being a data access, another translation path of the plurality of translation paths comprising a second address translation structure, the another translation path to use the first address in the entry to obtain a second address to be used to translate the address to another address, the traversing selecting the one path or the another path based on the attribute; and using the information to translate the address to the another address. | 1. A method of facilitating address translation in a computing environment, said method comprising: obtaining an address to be translated from the address to another address using a hierarchy of address translation structures, the hierarchy of address translation structures comprising a plurality of levels; determining, based on an indicator in an address translations structure of the hierarchy of address translation structures, that at a last level of the plurality of levels that translation through the hierarchy of address translation structures is split into a plurality of translation paths, wherein the plurality of levels comprises 1 to n levels and n is the last level in the hierarchy of the address translation structures, wherein n is an integer greater than or equal to 2, and wherein the indicator is in the address translation structure at the last level of the plurality of levels; traversing the hierarchy of address translation structures to obtain information to be used to translate the address to the another address, wherein the traversing comprises selecting, based on the determining and based on an attribute of the address to be translated, one translation path of the plurality of translation paths from which to obtain the information to be used to translate the address to the another address, wherein the another address is different for each path, wherein the selecting further comprises: selecting, based on the attribute being an instruction fetch, one translation path of the plurality of translation paths comprising a first address translation structure, the one translation path to use a first address in an entry of an address translation structure at the last level to translate the address to the another address; and selecting, based on the attribute being a data access, another translation path of the plurality of translation paths comprising a second address translation structure, the another translation path to use the first address in the entry to obtain a second address to be used to translate the address to another address, the traversing selecting the one path or the another path based on the attribute; and using the information to translate the address to the another address. 5. The method of claim 1 , wherein one translation path comprises a third translation structure having one entry to point to the first address translation structure, and the another translation path comprises the third translation structure having another entry to point to the second address translation structure. | 0.625891 |
8,560,945 | 7 | 8 | 7. The image forming apparatus of claim 6 , wherein the processor is adapted to further perform: a first function comprising: correlating the print job with Fixed Document or Fixed Page of the XPS file; creating first elements being necessary for editing the XPS file; and, when conducting a creation, designating a single first relationship or plural first relationships between the first elements created for an insertion or an overwriting of a document, a second function comprising: shifting a number of the Fixed Document or the Fixed Page; adding all of the first elements created under the Fixed Document or the Fixed Page thereto; and registering the Fixed Document or the Fixed Page added with the first elements into a predetermined area, when conducting the insertion of the document concerned, and a third function comprising: deleting all of second elements currently set under the Fixed Document or the Fixed Page and second relationships between the second elements; adding all of the first elements created under the Fixed Document or the Fixed Page thereto; and registering the Fixed Document or the Fixed Page added with the first elements into the predetermined area, when conducting the overwriting of the document concerned. | 7. The image forming apparatus of claim 6 , wherein the processor is adapted to further perform: a first function comprising: correlating the print job with Fixed Document or Fixed Page of the XPS file; creating first elements being necessary for editing the XPS file; and, when conducting a creation, designating a single first relationship or plural first relationships between the first elements created for an insertion or an overwriting of a document, a second function comprising: shifting a number of the Fixed Document or the Fixed Page; adding all of the first elements created under the Fixed Document or the Fixed Page thereto; and registering the Fixed Document or the Fixed Page added with the first elements into a predetermined area, when conducting the insertion of the document concerned, and a third function comprising: deleting all of second elements currently set under the Fixed Document or the Fixed Page and second relationships between the second elements; adding all of the first elements created under the Fixed Document or the Fixed Page thereto; and registering the Fixed Document or the Fixed Page added with the first elements into the predetermined area, when conducting the overwriting of the document concerned. 8. The image forming apparatus of claim 7 , wherein when conducting the creation of the document, the first function further comprises: correlating the print job with the Fixed Document of the XPS file; creating all of third elements to be set under Fixed Document Sequence; and designating third relationships between the third elements, when conducting the insertion or the overwriting of the document and when the Fixed Page is not designated, the first function further comprises: correlating the print job with the Fixed Document of the XPS file; creating all of fourth elements to be set under Fixed Document; and designating fourth relationships between the fourth elements created, and when conducting the insertion or the overwriting of the document and when the Fixed Page is designated, the first function further comprise: correlating the print job with the Fixed Page of the XPS file; creating all of fifth elements to be set under Fixed Page; and designating fifth relationships between the fifth elements created. | 0.7299 |
10,096,315 | 13 | 15 | 13. The computer system of claim 12 , wherein conducting speech recognition on the channel recording comprises using a conversation-specific language model. | 13. The computer system of claim 12 , wherein conducting speech recognition on the channel recording comprises using a conversation-specific language model. 15. The computer system of claim 13 , wherein the conversation-specific language model comprises an n-gram model where n is greater than or equal to 6. | 0.92119 |
7,694,284 | 7 | 8 | 7. A method for rendering an object model in terms of XML, the XML comprising a plurality of XML tags, the method comprising: for each XML tag in the XML defining translators, each translator including common, parser-independent mappings for the XML tag of said XML to an associated object model feature, whereby the parser-independent mappings are each useable with multiple types of parser mechanisms including at least parser mechanisms that use a document object model and parser mechanisms that are event driven; parsing the XML using a parser-specific implementation, including creating a parser specific adapter for each XML tag of the XML; and translating the results of said parsing with the parser specific adapter to render the object model, wherein each parser specific adapter uses the common, parser-independent mappings of the associated translator for each XML tag to produce the object model. | 7. A method for rendering an object model in terms of XML, the XML comprising a plurality of XML tags, the method comprising: for each XML tag in the XML defining translators, each translator including common, parser-independent mappings for the XML tag of said XML to an associated object model feature, whereby the parser-independent mappings are each useable with multiple types of parser mechanisms including at least parser mechanisms that use a document object model and parser mechanisms that are event driven; parsing the XML using a parser-specific implementation, including creating a parser specific adapter for each XML tag of the XML; and translating the results of said parsing with the parser specific adapter to render the object model, wherein each parser specific adapter uses the common, parser-independent mappings of the associated translator for each XML tag to produce the object model. 8. The method of claim 7 , wherein the defining step includes: mapping each XML tag to a feature of a meta model describing each associated object model feature. | 0.756061 |
9,563,699 | 7 | 8 | 7. A non-transitory computer-readable storage medium storing instructions for identifying an audio content sample, the instructions which when executed by a processor cause the processor to: monitor a plurality of broadcast stations, fingerprint and save the fingerprints of broadcast audio content in a database of unidentified broadcast content as it is received; access playlists, comprising portions of identified broadcast audio content from the plurality of monitored broadcast stations, and fingerprints corresponding to the identified broadcast audio content; receive data representing sampled audio content from a portable device and search for a match between fingerprints of the sampled audio content and the fingerprints corresponding to at least parts of multiple playlists, further including: upon finding a fingerprint match against the fingerprints corresponding to a particular playlist for a particular monitored broadcast station, report the particular monitored broadcast station as a source of the sampled audio content, and identification of the sampled audio content back to the portable device; and upon not finding a fingerprint match against the fingerprints corresponding to any of the multiple playlists, further search for a match the fingerprints of sampled audio content, against at least one of: parts of the database of unidentified broadcast content from the monitored broadcast stations, to identify a source of the sampled audio content; and a reference database of identified audio content not associated with a particular broadcast station, to identify the sampled audio content; and report back to the portable device at least one of the source of the sampled audio content and the identity of the sampled audio content. | 7. A non-transitory computer-readable storage medium storing instructions for identifying an audio content sample, the instructions which when executed by a processor cause the processor to: monitor a plurality of broadcast stations, fingerprint and save the fingerprints of broadcast audio content in a database of unidentified broadcast content as it is received; access playlists, comprising portions of identified broadcast audio content from the plurality of monitored broadcast stations, and fingerprints corresponding to the identified broadcast audio content; receive data representing sampled audio content from a portable device and search for a match between fingerprints of the sampled audio content and the fingerprints corresponding to at least parts of multiple playlists, further including: upon finding a fingerprint match against the fingerprints corresponding to a particular playlist for a particular monitored broadcast station, report the particular monitored broadcast station as a source of the sampled audio content, and identification of the sampled audio content back to the portable device; and upon not finding a fingerprint match against the fingerprints corresponding to any of the multiple playlists, further search for a match the fingerprints of sampled audio content, against at least one of: parts of the database of unidentified broadcast content from the monitored broadcast stations, to identify a source of the sampled audio content; and a reference database of identified audio content not associated with a particular broadcast station, to identify the sampled audio content; and report back to the portable device at least one of the source of the sampled audio content and the identity of the sampled audio content. 8. The non-transitory computer-readable storage medium of claim 7 , further including instructions, which when executed by the processor, cause the processor to: receive a location from the portable device; and use the location to validate an identity of the source of the broadcast audio content. | 0.667785 |
9,792,527 | 1 | 2 | 1. A computer-implemented method for automated slide content comparison, the method comprising executing on a computer processor the steps of: in response to an identification of an input slide, generating text content confidence scores that represent amounts of similarity of slide text content of the input slide to compared text content of a plurality of slides that are included within slide presentation files of a repository; generating graphic element content confidence scores that represent amounts of similarity of graphic content of the input slide to compared graphic element content of the respective ones of the plurality of slides; generating similarity confidence scores for each of the respective ones of the plurality of slides as functions of weighted averages of the text content confidence scores and the graphic element content confidence scores generated for the respective ones of the plurality of slides, wherein the graphic element content confidence scores are weighted differently from the text content confidence scores; and ranking the plurality of slides for similarity to the input slide as a function of the generated similarity confidence scores. | 1. A computer-implemented method for automated slide content comparison, the method comprising executing on a computer processor the steps of: in response to an identification of an input slide, generating text content confidence scores that represent amounts of similarity of slide text content of the input slide to compared text content of a plurality of slides that are included within slide presentation files of a repository; generating graphic element content confidence scores that represent amounts of similarity of graphic content of the input slide to compared graphic element content of the respective ones of the plurality of slides; generating similarity confidence scores for each of the respective ones of the plurality of slides as functions of weighted averages of the text content confidence scores and the graphic element content confidence scores generated for the respective ones of the plurality of slides, wherein the graphic element content confidence scores are weighted differently from the text content confidence scores; and ranking the plurality of slides for similarity to the input slide as a function of the generated similarity confidence scores. 2. The method of claim 1 , wherein the step of generating the similarity confidence scores for each of the respective ones of the plurality of slides as the functions of the weighted averages of the text content confidence scores and the graphic element content confidence scores generated for the respective ones of the plurality of slides comprises: generating first weighted averages of the graphic element content confidence scores and the text content confidence scores for each of the plurality of slides of the each slides as functions of a first differential weighting of the graphic element content confidence scores relative to the text content confidence scores; comparing the graphic element content confidence scores of the plurality of slides to an image content confidence threshold value that indicates a strength of match of an attribute of the graphic content of the input slide to a corresponding attribute of the graphic content of the plurality of slides; for each of the plurality of slides having a compared graphic element content confidence score that meets the image content confidence threshold value, generating second weighted averages of the graphic element content confidence scores and the text content confidence scores as functions of a second differential weighting of the graphic element content confidence scores relative to the text content confidence scores, wherein the second differential weighting increases a weighting of the graphic element content confidence score relative to the text content confidence score more than the first differential weighting; and selecting higher value ones of the first weighted averages and the second weighted averages as the similarity confidence scores for each of the respective ones of the plurality of slides. | 0.583682 |
9,058,580 | 1 | 3 | 1. A method, comprising: receiving or capturing an image comprising an identity document (ID) using a mobile device; classifying the ID; wherein the classifying comprises: generating a reduced-resolution representation of the ID, determining the ID corresponds to a particular state; and identifying the particular state to which the ID corresponds; and extracting data from the ID based at least in part on the ID classification; and driving at least a portion of a workflow based on the extracted data, wherein the classifying is based on the image characteristics corresponding to the reduced-resolution representation of the identity document. | 1. A method, comprising: receiving or capturing an image comprising an identity document (ID) using a mobile device; classifying the ID; wherein the classifying comprises: generating a reduced-resolution representation of the ID, determining the ID corresponds to a particular state; and identifying the particular state to which the ID corresponds; and extracting data from the ID based at least in part on the ID classification; and driving at least a portion of a workflow based on the extracted data, wherein the classifying is based on the image characteristics corresponding to the reduced-resolution representation of the identity document. 3. The method as recited in claim 1 , further comprising determining the extracted data are relevant to the workflow, wherein the determining is based at least in part on one or more of: the ID classification; determining the portion of the extracted data comprises one or more predetermined strings; and determining the portion of the extracted data comprises one or more predetermined images. | 0.701967 |
9,880,815 | 1 | 10 | 1. A structured query language (SQL) Visualizer, comprising: a processor of a computer system, wherein the processor is arranged to cause the computer system to transform a textual SQL statement into a graphical diagram which represents said textual SQL statement; said SQL Visualizer being arranged: a) to cause the computer system to transform a textual SQL procedure into a graphical diagram which represents said textual SQL procedure such that the structure of the SQL procedure is visually represented in said graphical diagram; and b) to transform a textual data manipulation language (DML) statement into a graphical diagram which represents the logic of said textual DML statement; wherein said textual DML statement includes an insert, update or delete, statement; wherein said graphical diagram which represents the logic of said textual DML statement includes at least an insert, update or delete icon; and wherein the SQL Visualizer further comprises a user interface, wherein said user interface comprises a dictionary selection control which allows a user to select a database used in said textual SQL statement, and to thereby provide a definition for said database for use in transforming said textual SQL statement into said graphical diagram which represents said textual SQL statement. | 1. A structured query language (SQL) Visualizer, comprising: a processor of a computer system, wherein the processor is arranged to cause the computer system to transform a textual SQL statement into a graphical diagram which represents said textual SQL statement; said SQL Visualizer being arranged: a) to cause the computer system to transform a textual SQL procedure into a graphical diagram which represents said textual SQL procedure such that the structure of the SQL procedure is visually represented in said graphical diagram; and b) to transform a textual data manipulation language (DML) statement into a graphical diagram which represents the logic of said textual DML statement; wherein said textual DML statement includes an insert, update or delete, statement; wherein said graphical diagram which represents the logic of said textual DML statement includes at least an insert, update or delete icon; and wherein the SQL Visualizer further comprises a user interface, wherein said user interface comprises a dictionary selection control which allows a user to select a database used in said textual SQL statement, and to thereby provide a definition for said database for use in transforming said textual SQL statement into said graphical diagram which represents said textual SQL statement. 10. A SQL Visualizer as claimed in claim 1 , which further comprises a user interface comprising an editor into which a user may place textual elements prior to their conversion into graphical form. | 0.747449 |
9,524,279 | 13 | 17 | 13. A system, comprising: one or more processors; and a memory that includes one or more software components that are executable by the one or more processors to: parse a text instruction in a text-based document of an application to identify a noun that corresponds to a user interface (UI) element of the application and a related verb that corresponds to an operation action performed on the UI element; in response to being unable to parse the text instruction for the related verb, prompt a user, via a user interface (UI), to manually enter the related verb or to select the operation action that corresponds to the related verb; receive, via the user interface (UI), one of the manual entry of the related verb or a selection of the operation action; generate, based at least in part on the noun and the related verb, an operation record from the text-based help document of the application, the operation record including data for animating the operation action that is able to be performed on the user interface (UI) element of the application as described in the text-based help document; modify the text-based help document to generate an enhanced help document including a control that loads the operation record; play an animation of the operation action that is able to be performed on the UI element upon activation of the control in the enhanced help document, the animation including a visualization of one or more steps for completing the operation action; and present an option menu to enable a user to, upon completion of playing the animation of the operation action, retain the operation action performed and undo the operation action performed. | 13. A system, comprising: one or more processors; and a memory that includes one or more software components that are executable by the one or more processors to: parse a text instruction in a text-based document of an application to identify a noun that corresponds to a user interface (UI) element of the application and a related verb that corresponds to an operation action performed on the UI element; in response to being unable to parse the text instruction for the related verb, prompt a user, via a user interface (UI), to manually enter the related verb or to select the operation action that corresponds to the related verb; receive, via the user interface (UI), one of the manual entry of the related verb or a selection of the operation action; generate, based at least in part on the noun and the related verb, an operation record from the text-based help document of the application, the operation record including data for animating the operation action that is able to be performed on the user interface (UI) element of the application as described in the text-based help document; modify the text-based help document to generate an enhanced help document including a control that loads the operation record; play an animation of the operation action that is able to be performed on the UI element upon activation of the control in the enhanced help document, the animation including a visualization of one or more steps for completing the operation action; and present an option menu to enable a user to, upon completion of playing the animation of the operation action, retain the operation action performed and undo the operation action performed. 17. The system of claim 13 , wherein the one or more components are further executable to generate one of the operation record at least by: traversing a user interface (UI) element tree of the application to obtain a hierarchic path from a main window to a UI element of the application; and representing the user interface (UI) element of the application in the operation record via a corresponding hierarchic structure that includes hierarchical strings that lead from the main window of the application to the user interface (UI) element. | 0.59139 |
8,762,191 | 18 | 28 | 18. A risk identifying apparatus, comprising: a memory; a processor disposed in communication with said memory, and configured to issue a plurality of processing instructions stored in the memory, wherein the processor issues instructions to: receive information associated with at least one risk for identifying at least one predetermined indicator of risk-relevant information; analyze the received information to determine relevancy of the information with regard to the at least one risk and tagging the information with at least one risk-relevancy tag based on a determination of the relevancy of the information with regard to the at least one risk; process the tagged information to remove redundant information and information not deemed to be relevant to the at least one risk, thereby creating the risk-relevant information; parse the risk-relevant information into a plurality of portions categorized by the at least one risk-relevancy tag; determine a risk-relevancy metric of each of the plurality of portions, wherein the at least one risk-relevancy tag identifies the risk-relevancy metric associated with a relevant portion of the information with respect to the at least one risk, the risk-relevancy metric indicating a likelihood that the relevant portion of the information is relevant to the at least one risk; store the risk-relevant information In a data storage structure, wherein the data storage structure includes a plurality of areas that are interrelated to facilitate the identification of the at least one risk; and output the risk-relevant information stored in the data storage structure to a risk identification graphical user interface. | 18. A risk identifying apparatus, comprising: a memory; a processor disposed in communication with said memory, and configured to issue a plurality of processing instructions stored in the memory, wherein the processor issues instructions to: receive information associated with at least one risk for identifying at least one predetermined indicator of risk-relevant information; analyze the received information to determine relevancy of the information with regard to the at least one risk and tagging the information with at least one risk-relevancy tag based on a determination of the relevancy of the information with regard to the at least one risk; process the tagged information to remove redundant information and information not deemed to be relevant to the at least one risk, thereby creating the risk-relevant information; parse the risk-relevant information into a plurality of portions categorized by the at least one risk-relevancy tag; determine a risk-relevancy metric of each of the plurality of portions, wherein the at least one risk-relevancy tag identifies the risk-relevancy metric associated with a relevant portion of the information with respect to the at least one risk, the risk-relevancy metric indicating a likelihood that the relevant portion of the information is relevant to the at least one risk; store the risk-relevant information In a data storage structure, wherein the data storage structure includes a plurality of areas that are interrelated to facilitate the identification of the at least one risk; and output the risk-relevant information stored in the data storage structure to a risk identification graphical user interface. 28. The apparatus of claim 18 , wherein the processor further issues instructions to compute an overall risk relevancy for the information. | 0.88754 |
10,101,752 | 13 | 14 | 13. The hydrocarbon extractor evaluator system of claim 8 , the hierarchical equipment rule set and the hierarchical well feature rule set each containing rules formulated from subject matter expert knowledge. | 13. The hydrocarbon extractor evaluator system of claim 8 , the hierarchical equipment rule set and the hierarchical well feature rule set each containing rules formulated from subject matter expert knowledge. 14. The hydrocarbon extractor system of claim 13 , the rules engine operable to generate rules from inferences of additional knowledge from the subject matter expert knowledge. | 0.961233 |
8,892,438 | 14 | 15 | 14. The method of claim 1 , further comprising performing, before performing the acts of claim 1 : for each of the plurality of time periods, computing a matrix of associational usage scores among all words of a list of frequently occurring words; computing differences in the associational scores of two of the matrices to produce a difference matrix; producing a set of clusters of utterances based on similarity in associational usage scores of the difference matrix, to yield a produced set of clusters; and creating a plurality of word classes based on a result of producing a set of clusters of utterances, wherein: determining determines a significant word usage class change, and generating the first cluster comprises generating, from the examined utterances, a cluster of utterances having a word class corresponding to the significant word class change. | 14. The method of claim 1 , further comprising performing, before performing the acts of claim 1 : for each of the plurality of time periods, computing a matrix of associational usage scores among all words of a list of frequently occurring words; computing differences in the associational scores of two of the matrices to produce a difference matrix; producing a set of clusters of utterances based on similarity in associational usage scores of the difference matrix, to yield a produced set of clusters; and creating a plurality of word classes based on a result of producing a set of clusters of utterances, wherein: determining determines a significant word usage class change, and generating the first cluster comprises generating, from the examined utterances, a cluster of utterances having a word class corresponding to the significant word class change. 15. The method of claim 14 , further comprising: prioritizing the first cluster of utterances and the second cluster of utterances. | 0.957905 |
9,134,726 | 1 | 5 | 1. A method for configuration of SOA-based automation devices having an embedded High-Level Petri Net Orchestration Engine for controlling mechatronic components of an automation system, comprising the process steps: generation of HLPN component models for each type of mechatronic component of the automation system, creation of a Component Instance Model from an HLPN component model for each physically present mechatronic component, creation of a Layout Configuration File, which describes relationships among the Component Instance Models, composition of the Component Instance Models to form at least one System Model based on the Layout Configuration File, such that logic ports of the Component Instance Models are interconnected/linked to one another, generation of Configuration Files based on the at least one System Model as well as Device Descriptor Files and WSDL files of the Component Instance Models, such that the configuration files include at least one Device Configuration File and one Service Configuration File, loading the configuration files into the automation device containing the HLPN orchestration engine, wherein the configuration file comprises data on hosted service information with the required discovery hints or a service endpoint address for the HLPN orchestration engine to resolve referenced component services, and the device configuration file has a service class descriptor with referenced types of ports and a model representation, execution of the configuration files by the distributed HLPN orchestration engines of the automation devices. | 1. A method for configuration of SOA-based automation devices having an embedded High-Level Petri Net Orchestration Engine for controlling mechatronic components of an automation system, comprising the process steps: generation of HLPN component models for each type of mechatronic component of the automation system, creation of a Component Instance Model from an HLPN component model for each physically present mechatronic component, creation of a Layout Configuration File, which describes relationships among the Component Instance Models, composition of the Component Instance Models to form at least one System Model based on the Layout Configuration File, such that logic ports of the Component Instance Models are interconnected/linked to one another, generation of Configuration Files based on the at least one System Model as well as Device Descriptor Files and WSDL files of the Component Instance Models, such that the configuration files include at least one Device Configuration File and one Service Configuration File, loading the configuration files into the automation device containing the HLPN orchestration engine, wherein the configuration file comprises data on hosted service information with the required discovery hints or a service endpoint address for the HLPN orchestration engine to resolve referenced component services, and the device configuration file has a service class descriptor with referenced types of ports and a model representation, execution of the configuration files by the distributed HLPN orchestration engines of the automation devices. 5. The method according to claim 1 , wherein the Device Descriptor Files establish a 1 : 1 link between the binding reference names of the models and the actual DPWS devices/services. | 0.664835 |
8,670,974 | 10 | 13 | 10. A non-transitory computer-readable medium storing one or more instructions which, when executed by one or more processors, cause the one or more processors to perform: identifying, within a bilingual webpage, a set of one or more bilingual term pairs, wherein a bilingual term pair comprises a first term in a first language and a second term in a second language; based at least in part on a layout of the one or more bilingual term pairs in the bilingual webpage, identifying a plurality of candidate patterns; identifying, for each candidate pattern of the plurality of candidate patterns, one or more features; based at least in part on the one or more features of each candidate pattern, selecting a first candidate pattern from the plurality of candidate patterns; after selecting the first candidate pattern, identifying a set of candidate translation pairs that match the first candidate pattern within the bilingual webpage and that were not previously identified within the bilingual webpage before selecting the first candidate pattern. | 10. A non-transitory computer-readable medium storing one or more instructions which, when executed by one or more processors, cause the one or more processors to perform: identifying, within a bilingual webpage, a set of one or more bilingual term pairs, wherein a bilingual term pair comprises a first term in a first language and a second term in a second language; based at least in part on a layout of the one or more bilingual term pairs in the bilingual webpage, identifying a plurality of candidate patterns; identifying, for each candidate pattern of the plurality of candidate patterns, one or more features; based at least in part on the one or more features of each candidate pattern, selecting a first candidate pattern from the plurality of candidate patterns; after selecting the first candidate pattern, identifying a set of candidate translation pairs that match the first candidate pattern within the bilingual webpage and that were not previously identified within the bilingual webpage before selecting the first candidate pattern. 13. The non-transitory computer-readable medium of claim 10 , wherein identifying the one or more candidate patterns comprises: identifying a first bilingual term pair; assigning a first generic token to a first term of the bilingual term pair; assigning a second generic token to a second term of the bilingual pair; assigning a non-generic token to a term or tab between the first term and the second term; and identifying, based on a layout pattern of the first generic token, the second generic token, and the non-generic token, a first candidate pattern. | 0.500893 |
7,904,522 | 18 | 19 | 18. The non-transitory storage medium of claim 1 , further comprising instructions for causing said computer to implement: deploying, accessing, and executing process software for providing search and reference functions for use with a messaging system, said deploying, accessing, and executing process software implemented through a virtual private network; wherein said deploying, accessing, and executing process software further comprises: determining if a virtual private network is required; checking for remote access to said virtual private network when it is required; if said remote access does not exist, identifying a third party provider to provide secure, encrypted connections between a private network and remote users; identifying said remote users; and setting up a network access server operable for downloading and installing client software on desktop computers for remote access of said virtual private network; accessing said process software; transporting said process software to at least one remote user's desktop computer; and executing said process software on said at least one remote user's desktop computer. | 18. The non-transitory storage medium of claim 1 , further comprising instructions for causing said computer to implement: deploying, accessing, and executing process software for providing search and reference functions for use with a messaging system, said deploying, accessing, and executing process software implemented through a virtual private network; wherein said deploying, accessing, and executing process software further comprises: determining if a virtual private network is required; checking for remote access to said virtual private network when it is required; if said remote access does not exist, identifying a third party provider to provide secure, encrypted connections between a private network and remote users; identifying said remote users; and setting up a network access server operable for downloading and installing client software on desktop computers for remote access of said virtual private network; accessing said process software; transporting said process software to at least one remote user's desktop computer; and executing said process software on said at least one remote user's desktop computer. 19. The non-transitory storage medium of claim 18 , further comprising instructions for causing said computer to implement: determining if said virtual private network has a site-to-site configuration for providing site-to-site access, and if said virtual private network is not so available, installing equipment required to establish a site-to-site configuration for said virtual private network; installing large scale encryption into said site-to-site virtual private network; and accessing said process software through said site-to-site configuration with large scale encryption. | 0.877049 |
9,141,605 | 2 | 4 | 2. The method of claim 1 , wherein the method further comprises: after said matching is performed for one matched element of the matched elements, said processor determining that at least one condition is indicated for the one matched element; responsive to determining that at least one condition is indicated for the one matched element, said processor fulfilling each condition of the at least one condition for the one matched element, wherein the at least one condition is selected from the group consisting of specificity, proximity, both specificity and proximity, both specificity and completeness, and both proximity and completeness, wherein fulfilling specificity for the one matched element comprises identifying an activity associated with the at least one matched element, wherein fulfilling completeness for the one matched element comprises obtaining additional information associated with the at least one matched element, and wherein fulfilling proximity for the one matched element comprises identifying proximity relationships for the one matched element. | 2. The method of claim 1 , wherein the method further comprises: after said matching is performed for one matched element of the matched elements, said processor determining that at least one condition is indicated for the one matched element; responsive to determining that at least one condition is indicated for the one matched element, said processor fulfilling each condition of the at least one condition for the one matched element, wherein the at least one condition is selected from the group consisting of specificity, proximity, both specificity and proximity, both specificity and completeness, and both proximity and completeness, wherein fulfilling specificity for the one matched element comprises identifying an activity associated with the at least one matched element, wherein fulfilling completeness for the one matched element comprises obtaining additional information associated with the at least one matched element, and wherein fulfilling proximity for the one matched element comprises identifying proximity relationships for the one matched element. 4. The method of claim 2 , wherein the at least one condition consists of proximity. | 0.971506 |
9,454,525 | 8 | 9 | 8. A method of extracting information from a text input having a first feature and a second feature using a natural language understanding system, comprising: determining a first value for the first feature using a selected text processing technique; selecting a statistical model from a plurality of statistical models associated with a second feature based upon the first value; determining a second value for the second feature using the selected statistical model; forming, using a processor, a complex information target by combining the first and second values; and outputting the complex information target. | 8. A method of extracting information from a text input having a first feature and a second feature using a natural language understanding system, comprising: determining a first value for the first feature using a selected text processing technique; selecting a statistical model from a plurality of statistical models associated with a second feature based upon the first value; determining a second value for the second feature using the selected statistical model; forming, using a processor, a complex information target by combining the first and second values; and outputting the complex information target. 9. The method of claim 8 , wherein the selected text processing technique is a statistical model associated with the first feature. | 0.915155 |
10,055,495 | 14 | 15 | 14. The method for searching information using a computer device according to claim 1 , wherein displaying the search parameters as selectable posts in the search window further comprises: displaying the gaze search parameters as first set of selectable posts in the search window; and displaying the non gaze search parameters as a second set of selectable posts in the search window. | 14. The method for searching information using a computer device according to claim 1 , wherein displaying the search parameters as selectable posts in the search window further comprises: displaying the gaze search parameters as first set of selectable posts in the search window; and displaying the non gaze search parameters as a second set of selectable posts in the search window. 15. The method for searching information using a computer device according to claim 14 , wherein the selected combination is selected by: receiving a first user selection of a first label of the set of labels, the first label being of a first selectable post of the set of selectable posts, and the first selectable post corresponding to the at least one gaze search parameter; and receiving a second user selection of a second selectable post from the second set of selectable posts, the second selectable post corresponding to the at least one non gaze search parameter. | 0.835159 |
8,117,225 | 28 | 35 | 28. The computer program product of claim 15 , wherein the computer program product is capable of cooperating with at least one mobile application adapted for accessing at least one of the different online applications utilizing a mobile device, said computer program product further being capable of allowing the at least one mobile application to provide at least a portion of a functionality of the at least one of the different online applications. | 28. The computer program product of claim 15 , wherein the computer program product is capable of cooperating with at least one mobile application adapted for accessing at least one of the different online applications utilizing a mobile device, said computer program product further being capable of allowing the at least one mobile application to provide at least a portion of a functionality of the at least one of the different online applications. 35. The computer program product of claim 28 , wherein the computer program product is operable such that the portion of the functionality includes user interface-related functionality. | 0.982334 |
7,702,691 | 1 | 7 | 1. A computer implemented system to support querying of a software object, comprising: at least one processor; a software object finder, which runs on the at least one processor, to perform the steps of: querying a plurality of databases using a plurality of queries in different query languages, wherein at least one database in the plurality of databases is associated with a different query language from another database in the plurality of databases; mapping a matched data entity from the plurality of databases to one or more instances of the software object; performing relationship caching of one or more additional software objects from the plurality of databases into a cache using queries in different query languages, wherein the one or more additional software objects are related to the software object by one or more predefined relationships, wherein the relationship caching allows the one or more additional software objects to be loaded into the cache in a join query prior to the mapping step, and wherein both the software object and the one or more additional software objects are created and managed by a container and run as part of an application server to support software applications, wherein the software object and the related software objects use one or more deployment descriptors at deploy time, wherein the one or more deployment descriptors allow an editing of structural information about the software object and the one or more additional software objects; and storing the one or more instances of the software object in a result set; and wherein the one or more deployment descriptors of the software object define: the different query languages used by the software object finder; and selection information of the different query languages. | 1. A computer implemented system to support querying of a software object, comprising: at least one processor; a software object finder, which runs on the at least one processor, to perform the steps of: querying a plurality of databases using a plurality of queries in different query languages, wherein at least one database in the plurality of databases is associated with a different query language from another database in the plurality of databases; mapping a matched data entity from the plurality of databases to one or more instances of the software object; performing relationship caching of one or more additional software objects from the plurality of databases into a cache using queries in different query languages, wherein the one or more additional software objects are related to the software object by one or more predefined relationships, wherein the relationship caching allows the one or more additional software objects to be loaded into the cache in a join query prior to the mapping step, and wherein both the software object and the one or more additional software objects are created and managed by a container and run as part of an application server to support software applications, wherein the software object and the related software objects use one or more deployment descriptors at deploy time, wherein the one or more deployment descriptors allow an editing of structural information about the software object and the one or more additional software objects; and storing the one or more instances of the software object in a result set; and wherein the one or more deployment descriptors of the software object define: the different query languages used by the software object finder; and selection information of the different query languages. 7. The system according to claim 1 , wherein: the software object finder further performs at least one of: leaving one or more columns in the data entity unmapped to the one or more instances of the software object; marking the one or more columns as “as-is”; and passing the one or more columns to an object-oriented programming language code. | 0.586538 |
8,065,388 | 1 | 4 | 1. A method of delivering directions to a mobile device, the method comprising: communicating with the mobile device over a communications network; in response to a request from the mobile device for directions, determining a list of turn-by-turn directions to a location based on content relating to the location to be transmitted to the mobile device; determining an optimization constraint associated with at least one of the mobile device and the request; determining optional selectable content to include with the directions to be transmitted to the mobile device based on at least the optimization constraint; and transmitting the list of turn-by-turn directions to the mobile device. | 1. A method of delivering directions to a mobile device, the method comprising: communicating with the mobile device over a communications network; in response to a request from the mobile device for directions, determining a list of turn-by-turn directions to a location based on content relating to the location to be transmitted to the mobile device; determining an optimization constraint associated with at least one of the mobile device and the request; determining optional selectable content to include with the directions to be transmitted to the mobile device based on at least the optimization constraint; and transmitting the list of turn-by-turn directions to the mobile device. 4. A method as in claim 1 wherein the directions include an image of a map illustrating the directions. | 0.850725 |
9,871,802 | 1 | 11 | 1. A method comprising: receiving a request from a user of a social networking system to create a limited user profile for an additional user of a particular age; determining that the additional user does not satisfy one or more criteria for maintaining a user profile via the social networking system, the determining based in part on a comparison of a threshold age limit with the particular age of the additional user; determining that the additional user is a child based on the determination not satisfying the one or more criteria; responsive to determining that the additional user is a child, identifying one or more permissions associated with the limited user profile for the additional user by the user, the identified one or more permissions specifying fewer permissions than associated with a user profile maintained by the social networking system, determining one or more privacy settings associated with the limited user profile for the additional user by the user, a privacy setting associated with a type of interaction with the limited user profile and identifying a user who is able to authorize the type of interaction with the limited user profile, generating the limited user profile for the additional user based at least in part on information included in the request, the identified one or more permissions, and the determined one or more privacy settings, and storing the limited user profile for the additional user and a connection between the limited user profile for the additional user and the user; and associating the additional user with content maintained by the social networking system in response to approval from a user who is able to authorize the association as specified in the one or more privacy settings. | 1. A method comprising: receiving a request from a user of a social networking system to create a limited user profile for an additional user of a particular age; determining that the additional user does not satisfy one or more criteria for maintaining a user profile via the social networking system, the determining based in part on a comparison of a threshold age limit with the particular age of the additional user; determining that the additional user is a child based on the determination not satisfying the one or more criteria; responsive to determining that the additional user is a child, identifying one or more permissions associated with the limited user profile for the additional user by the user, the identified one or more permissions specifying fewer permissions than associated with a user profile maintained by the social networking system, determining one or more privacy settings associated with the limited user profile for the additional user by the user, a privacy setting associated with a type of interaction with the limited user profile and identifying a user who is able to authorize the type of interaction with the limited user profile, generating the limited user profile for the additional user based at least in part on information included in the request, the identified one or more permissions, and the determined one or more privacy settings, and storing the limited user profile for the additional user and a connection between the limited user profile for the additional user and the user; and associating the additional user with content maintained by the social networking system in response to approval from a user who is able to authorize the association as specified in the one or more privacy settings. 11. The method of claim 1 , further comprising: responsive to determining the additional user subsequently satisfies criteria for maintaining a user profile via the social networking system, generating a user profile associated with the additional user based at least in part on the limited user profile associated with the additional user, one or more associations between the limited user profile and content maintained by the additional user, and one or more connections between the limited user profile and users of the social networking system. | 0.744888 |
8,019,710 | 29 | 50 | 29. A system for guiding the progressive development and documentation of user thinking and knowledge about an inquiry based project according to exemplary approaches used by experts, comprising: processor executable instructions embodied on a computer readable media, memory, or processor readable device, or a combination thereof, said instructions comprising: instructions to receive user specification of an initial stage of understanding regarding an arbitrary problem or inquiry based project according to at least one of a plurality of entry or starting points; instructions for accomplishing at least one of an interactive workspace or a user suggestion or both, to facilitate the further development of the understanding regarding an arbitrary problem or inquiry project towards a completion stage; instructions to display or output, or both, an integrated archetype based model of user understanding regarding the arbitrary problem or inquiry based project. | 29. A system for guiding the progressive development and documentation of user thinking and knowledge about an inquiry based project according to exemplary approaches used by experts, comprising: processor executable instructions embodied on a computer readable media, memory, or processor readable device, or a combination thereof, said instructions comprising: instructions to receive user specification of an initial stage of understanding regarding an arbitrary problem or inquiry based project according to at least one of a plurality of entry or starting points; instructions for accomplishing at least one of an interactive workspace or a user suggestion or both, to facilitate the further development of the understanding regarding an arbitrary problem or inquiry project towards a completion stage; instructions to display or output, or both, an integrated archetype based model of user understanding regarding the arbitrary problem or inquiry based project. 50. The system of claim 29 further comprising the automatic entry to an additional information source or search field or both. | 0.932836 |
9,058,374 | 1 | 6 | 1. A method, in a data processing system comprising a processor and a memory, for generating section metadata for an electronic document, the method comprising: receiving, by the data processing system, an electronic document for processing; analyzing, by the data processing system, the electronic document to identify concepts present within textual content of the electronic document; correlating, by the data processing system, concepts within the textual content with one another to identify concept groups within the textual content based on the application of one or more rules defining related concepts or concept patterns; determining, by the data processing system, at least one section of text within the textual content based on the correlation of concepts within the textual content; generating, by the data processing system, based on results of the determining, section metadata for the electronic document to thereby identify the at least one section in the electronic document; and storing, by the data processing system, the section metadata in association with the electronic document for use by a document processing system. | 1. A method, in a data processing system comprising a processor and a memory, for generating section metadata for an electronic document, the method comprising: receiving, by the data processing system, an electronic document for processing; analyzing, by the data processing system, the electronic document to identify concepts present within textual content of the electronic document; correlating, by the data processing system, concepts within the textual content with one another to identify concept groups within the textual content based on the application of one or more rules defining related concepts or concept patterns; determining, by the data processing system, at least one section of text within the textual content based on the correlation of concepts within the textual content; generating, by the data processing system, based on results of the determining, section metadata for the electronic document to thereby identify the at least one section in the electronic document; and storing, by the data processing system, the section metadata in association with the electronic document for use by a document processing system. 6. The method of claim 1 , wherein determining at least one section of text within the textual content based on the correlation of concepts within the textual content comprises performing a statistical analysis of the concepts within the textual content, wherein the statistical analysis comprises at least one of concept density analysis, inverse document frequency analysis, or concept commonality analysis amongst a plurality of proposed sections of text within the textual content. | 0.636432 |
8,214,347 | 1 | 6 | 1. A method of operating a computer system environment for the processing of search results which match a search query to provide for sub-topic identification of the search results, the method comprising: receiving a search result; extracting snippets from said search result that contain said query; truncating snippets on an instance of a boundary token; identifying phrases within said snippets that include the query; comparing all said phrases to determine optimal phrases; and presenting said optimal phrases; wherein said comparing all said phrases comprises comparisons between a first phrase and a second phrase, wherein said comparisons between combinations of two phrases comprises: skipping comparisons where said first phrase starts with the query term and said second phrase ends with the query term; eliminating a first phrase that is a superstring of said second phrase if said first phrase has a lower frequency of occurrence than said second phrase; and eliminating said first phrase that is a substring of said second phrase if said first phrase has the same frequency of occurrence as said second phrase. | 1. A method of operating a computer system environment for the processing of search results which match a search query to provide for sub-topic identification of the search results, the method comprising: receiving a search result; extracting snippets from said search result that contain said query; truncating snippets on an instance of a boundary token; identifying phrases within said snippets that include the query; comparing all said phrases to determine optimal phrases; and presenting said optimal phrases; wherein said comparing all said phrases comprises comparisons between a first phrase and a second phrase, wherein said comparisons between combinations of two phrases comprises: skipping comparisons where said first phrase starts with the query term and said second phrase ends with the query term; eliminating a first phrase that is a superstring of said second phrase if said first phrase has a lower frequency of occurrence than said second phrase; and eliminating said first phrase that is a substring of said second phrase if said first phrase has the same frequency of occurrence as said second phrase. 6. A method according to claim 1 , wherein said comparing of phrases comprises comparing frequency of occurrence for eliminating phrases with lower frequencies. | 0.769452 |
8,452,778 | 13 | 15 | 13. A computer system comprising: a computer processor; and a computer program executable by the computer processor, the program comprising: instructions for storing a taxonomy of hierarchically-arranged categories; instructions for storing a set of labeled videos, each of the labeled videos having associated textual metadata and being initially labeled as representing one or more of the categories; instructions for storing labels initially associated with a set of text documents distinct from the labeled videos, each stored label corresponding to one of the categories and indicating that the associated text document represents the category; instructions for identifying, for each of the categories, a positive training subset of the text documents that represent the category based on their stored labels, and a negative training subset of the text documents that do not represent the category based on their stored labels; instructions for training a set of text-based classifiers based on the positive training subsets and the negative training subsets, each text-based classifier associated with one of the categories and producing, when applied to text, a score providing a measure of how strongly the text represents the associated category; instructions for identifying, for each of the categories, a positive training subset of the labeled videos that represent the category based on their labels, and a negative training subset of the labeled videos that do not represent the category based on their labels; instructions for, for each video of the positive training subsets of the labeled videos and of the negative training subsets of the labeled videos: applying the text-based classifiers to the associated textual metadata of the video, thereby producing a vector of scores for the video, the scores providing measures of how strongly the textual metadata of the video represents the categories associated with the text-based classifiers; extracting a content feature vector from video content of frames of the video; forming a hybrid feature vector comprising the vector of scores and the content feature vector for the video; and instructions for training a set of adapted classifiers based on the hybrid feature vectors of the videos in the positive training subsets of the labeled videos and on the hybrid feature vectors of the videos in the negative training subsets of the labeled videos, each adapted classifier associated with one of the categories and producing, when applied to an unlabeled video, a score providing a measure of how strongly the unlabeled video represents the associated category. | 13. A computer system comprising: a computer processor; and a computer program executable by the computer processor, the program comprising: instructions for storing a taxonomy of hierarchically-arranged categories; instructions for storing a set of labeled videos, each of the labeled videos having associated textual metadata and being initially labeled as representing one or more of the categories; instructions for storing labels initially associated with a set of text documents distinct from the labeled videos, each stored label corresponding to one of the categories and indicating that the associated text document represents the category; instructions for identifying, for each of the categories, a positive training subset of the text documents that represent the category based on their stored labels, and a negative training subset of the text documents that do not represent the category based on their stored labels; instructions for training a set of text-based classifiers based on the positive training subsets and the negative training subsets, each text-based classifier associated with one of the categories and producing, when applied to text, a score providing a measure of how strongly the text represents the associated category; instructions for identifying, for each of the categories, a positive training subset of the labeled videos that represent the category based on their labels, and a negative training subset of the labeled videos that do not represent the category based on their labels; instructions for, for each video of the positive training subsets of the labeled videos and of the negative training subsets of the labeled videos: applying the text-based classifiers to the associated textual metadata of the video, thereby producing a vector of scores for the video, the scores providing measures of how strongly the textual metadata of the video represents the categories associated with the text-based classifiers; extracting a content feature vector from video content of frames of the video; forming a hybrid feature vector comprising the vector of scores and the content feature vector for the video; and instructions for training a set of adapted classifiers based on the hybrid feature vectors of the videos in the positive training subsets of the labeled videos and on the hybrid feature vectors of the videos in the negative training subsets of the labeled videos, each adapted classifier associated with one of the categories and producing, when applied to an unlabeled video, a score providing a measure of how strongly the unlabeled video represents the associated category. 15. The computer system of claim 13 , wherein the text documents are web pages. | 0.913943 |
8,881,005 | 1 | 2 | 1. A method implemented in a computer infrastructure, comprising: reviewing an input text to detect spelling errors in one or more words by detecting space-deletion errors and space-insertion errors; calculating a variable cost distance of letters associated with the one or more words; determining a best candidate solution for correcting the spelling errors based on the variable cost distance; and correcting the spelling errors using the best candidate solution, wherein: the detecting space-deletion errors comprises choosing a sequence of letters with a maximum marginal probability via an A* lattice search and m-grams probability estimation; and the detecting space-insertion errors comprises generating all possible combinations between words in an input phrase. | 1. A method implemented in a computer infrastructure, comprising: reviewing an input text to detect spelling errors in one or more words by detecting space-deletion errors and space-insertion errors; calculating a variable cost distance of letters associated with the one or more words; determining a best candidate solution for correcting the spelling errors based on the variable cost distance; and correcting the spelling errors using the best candidate solution, wherein: the detecting space-deletion errors comprises choosing a sequence of letters with a maximum marginal probability via an A* lattice search and m-grams probability estimation; and the detecting space-insertion errors comprises generating all possible combinations between words in an input phrase. 2. The method of claim 1 , wherein the spelling errors include one or more insertions, deletions, substitutions, or transpositions. | 0.934369 |
9,711,117 | 1 | 3 | 1. A method for recognising music symbols based on handwritten music notations on computing devices, each computing device comprising a processor and at least one non-transitory computer readable medium for recognizing handwriting input under control of the processor, the method comprising: segmenting the handwritten music notations into a plurality of ink segments; determining at least one music symbol candidate for graphical objects representing groupings of the ink segments based on spatial relationships therebetween, the at least one music symbol candidate having an associated symbol cost; forming one or more graphs including the at least one music symbol candidate and one or more grammar rules applied to the at least one music symbol candidate, each grammar rule applied to at least two music symbol candidates having an associated spatial cost based on the spatial relationships between the graphical objects of the at least two music symbol candidates; and selecting at least one graph of the one or more graphs as representing the handwritten music notations based on the symbol costs and the spatial costs associated with the one or more graphs. | 1. A method for recognising music symbols based on handwritten music notations on computing devices, each computing device comprising a processor and at least one non-transitory computer readable medium for recognizing handwriting input under control of the processor, the method comprising: segmenting the handwritten music notations into a plurality of ink segments; determining at least one music symbol candidate for graphical objects representing groupings of the ink segments based on spatial relationships therebetween, the at least one music symbol candidate having an associated symbol cost; forming one or more graphs including the at least one music symbol candidate and one or more grammar rules applied to the at least one music symbol candidate, each grammar rule applied to at least two music symbol candidates having an associated spatial cost based on the spatial relationships between the graphical objects of the at least two music symbol candidates; and selecting at least one graph of the one or more graphs as representing the handwritten music notations based on the symbol costs and the spatial costs associated with the one or more graphs. 3. The method according to claim 1 , wherein the at least one music symbol candidate is determined based on graphical features extracted from the graphical objects. | 0.848708 |
8,166,456 | 1 | 4 | 1. A programming language type system comprising: a processor for executing: fixed-point rules that preserve integer-ness for one or more integer operations; integer rules in which integer types are distinct from fixed-point types and integer types can be automatically converted to fixed-point types; and a storage device for storing a result of at least one of executing the fixed-point rules and the integer rules. | 1. A programming language type system comprising: a processor for executing: fixed-point rules that preserve integer-ness for one or more integer operations; integer rules in which integer types are distinct from fixed-point types and integer types can be automatically converted to fixed-point types; and a storage device for storing a result of at least one of executing the fixed-point rules and the integer rules. 4. The system of claim 1 in which the fixed-point rules for multiplication and division integer operations use a graduated radix point rule. | 0.580838 |
8,374,316 | 1 | 2 | 1. In a data processor comprising a software application, a method comprising: detecting speech indicative of a number spoken during one of a telephone call and a voicemail message; transcribing the spoken number into text, wherein said transcribing further comprises: in response to the transcribed number sequence being a telephone number, determining whether the transcription is taking place on a listener's end or on a speaker's end; optionally prompting the speaker of the transcribed number for an approval prior to the transmission of the telephone number to the listener; and enabling the processing of the telephone number in the presence of an unclear communication channel as a result of a localized transcription; and when the transcription takes place on the speaker's end, forwarding a message, which includes the phone number information, to the listener for the number to be placed in the pre-specified events log of the listener's communication device; determining whether a sequence of the transcribed spoken numbers is a telephone number; and recording the telephone number in a pre-specified events log of a memory of the communication device of the listener. | 1. In a data processor comprising a software application, a method comprising: detecting speech indicative of a number spoken during one of a telephone call and a voicemail message; transcribing the spoken number into text, wherein said transcribing further comprises: in response to the transcribed number sequence being a telephone number, determining whether the transcription is taking place on a listener's end or on a speaker's end; optionally prompting the speaker of the transcribed number for an approval prior to the transmission of the telephone number to the listener; and enabling the processing of the telephone number in the presence of an unclear communication channel as a result of a localized transcription; and when the transcription takes place on the speaker's end, forwarding a message, which includes the phone number information, to the listener for the number to be placed in the pre-specified events log of the listener's communication device; determining whether a sequence of the transcribed spoken numbers is a telephone number; and recording the telephone number in a pre-specified events log of a memory of the communication device of the listener. 2. The method of claim 1 further comprising: in response to a number not including the area code, prefixing the transcribed number with the current area code of the speaker of number; providing access to the transcribed number in the events list in order to execute one or more functions including: (1) dialing the transcribed number; (2) saving the transcribed number in a file of contacts; and (3) transmitting a text message to the transcribed number. | 0.677557 |
9,710,538 | 5 | 14 | 5. The processing device according to claim 1 , wherein given a first search query containing keywords, the search device searches for an object that is matched with all of the keywords, the acquisition code is configured to acquire, for each category contained in the hierarchical structure, first frequencies of the name of the category and the keywords co-occurring in the first search query given to the search device, when at least a part of the distribution of the acquired first frequencies in the hierarchical structure is in conformity with a second distribution pattern that is one of the at least one distribution pattern, the identification code is configured to identify the position in the hierarchical structure of a category of which the name is given by the keyword based on the conformed part in the hierarchical structure and the position pre-associated with the second distribution pattern, and the second distribution pattern is a distribution pattern in which frequencies are all higher than a frequency presenting the absence of co-occurrence with reference to a given comparison criterion, and is pre-associated with the position immediately below the frequency at the end in the sequence of the frequencies. | 5. The processing device according to claim 1 , wherein given a first search query containing keywords, the search device searches for an object that is matched with all of the keywords, the acquisition code is configured to acquire, for each category contained in the hierarchical structure, first frequencies of the name of the category and the keywords co-occurring in the first search query given to the search device, when at least a part of the distribution of the acquired first frequencies in the hierarchical structure is in conformity with a second distribution pattern that is one of the at least one distribution pattern, the identification code is configured to identify the position in the hierarchical structure of a category of which the name is given by the keyword based on the conformed part in the hierarchical structure and the position pre-associated with the second distribution pattern, and the second distribution pattern is a distribution pattern in which frequencies are all higher than a frequency presenting the absence of co-occurrence with reference to a given comparison criterion, and is pre-associated with the position immediately below the frequency at the end in the sequence of the frequencies. 14. The processing device according to claim 5 , wherein the keyword is the name of a category contained in the hierarchical structure, and further comprising: a determination code configured to determine whether the position in the hierarchical structure of a category of which the name is given by the keyword coincides with the identified position. | 0.927088 |
9,514,129 | 18 | 25 | 18. At least one non-transitory computer readable medium having computer readable instructions stored thereon, wherein said instructions when executed by a processor cause the performance of the following operations comprising: in response to receipt of a first signal containing audio information from an audio sensor: transmitting said audio information to at least one loudspeaker; converting said audio information to textual information; preparing a message containing at least a portion of said textual information; and transmitting a second signal containing a first copy of said message to all addresses of a Wi-Fi network, the Wi-Fi network configured to connect to a plurality of mobile computing devices; and in response to receipt of a request from at least one of said plurality of mobile computing devices: transmitting a third signal containing second copy of said message to the at least one mobile computing device that issued the request. | 18. At least one non-transitory computer readable medium having computer readable instructions stored thereon, wherein said instructions when executed by a processor cause the performance of the following operations comprising: in response to receipt of a first signal containing audio information from an audio sensor: transmitting said audio information to at least one loudspeaker; converting said audio information to textual information; preparing a message containing at least a portion of said textual information; and transmitting a second signal containing a first copy of said message to all addresses of a Wi-Fi network, the Wi-Fi network configured to connect to a plurality of mobile computing devices; and in response to receipt of a request from at least one of said plurality of mobile computing devices: transmitting a third signal containing second copy of said message to the at least one mobile computing device that issued the request. 25. The at least one non-transitory computer readable medium of claim 18 , wherein said audio sensor comprises an array microphone. | 0.895032 |
8,280,902 | 9 | 13 | 9. A precision search engine comprising: a processor that controls the precision search engine; an input interface that receives a full-text search request; a profiler that transforms the full-text search request into a graphical profile that is a graphical representation of key terms in the full-text search request; a searcher that searches one or more databases based on the graphical profile to return search results; an entity extractor that extracts entities from the search results that are not included in the graphical profile as a first set of suggested modifications to the graphical profile; and an information extractor that extracts concepts from the search results that are not included in the graphical profile but are included in an operational taxonomy as a second set of suggested modifications to the graphical profile. | 9. A precision search engine comprising: a processor that controls the precision search engine; an input interface that receives a full-text search request; a profiler that transforms the full-text search request into a graphical profile that is a graphical representation of key terms in the full-text search request; a searcher that searches one or more databases based on the graphical profile to return search results; an entity extractor that extracts entities from the search results that are not included in the graphical profile as a first set of suggested modifications to the graphical profile; and an information extractor that extracts concepts from the search results that are not included in the graphical profile but are included in an operational taxonomy as a second set of suggested modifications to the graphical profile. 13. The precision search engine according to claim 9 , further comprising: an XML content tagger that assigns XML content tags to the key terms in the graphical profile based on the operational taxonomy and updates the operational taxonomy to include any key terms in the graphical profile that are not located in the operational taxonomy. | 0.769388 |
7,761,461 | 38 | 39 | 38. The computer-readable medium of claim 36 , wherein the data source is a document in text-based markup language. | 38. The computer-readable medium of claim 36 , wherein the data source is a document in text-based markup language. 39. The computer-readable medium of claim 38 , wherein the text-based markup language is one of the eXtended Markup Language (XML) and the MicroArray Gene Expression Markup Language (MAGE-ML). | 0.937214 |
9,552,613 | 1 | 15 | 1. A computer-implemented method, comprising: receiving one or more user-specified attribute labels of a user node and a set of probability distributions associated with possible attribute labels of nodes directly connected from the user node from a social graph in a social networking system; establishing multiple functions with variable likelihood scores of possible attribute labels of the user node and the set of the probability distributions as parameters; generating multiple equations representing explainability scores respectively corresponding to the nodes based on the multiple functions and the probability distributions associated with the nodes, each explainability score measuring a likelihood that a direct social connection between a directly connected node (“v”) and the user node is explained by at least a shared attribute label between the user node and the directly connected node; and ranking a first set of the possible attribute labels for the user node by maximizing the explainability scores utilizing the multiple equations respectively associated with the nodes, the explainability scores being implicit predictions of formation reasons of social connections between each of the nodes and the user node. | 1. A computer-implemented method, comprising: receiving one or more user-specified attribute labels of a user node and a set of probability distributions associated with possible attribute labels of nodes directly connected from the user node from a social graph in a social networking system; establishing multiple functions with variable likelihood scores of possible attribute labels of the user node and the set of the probability distributions as parameters; generating multiple equations representing explainability scores respectively corresponding to the nodes based on the multiple functions and the probability distributions associated with the nodes, each explainability score measuring a likelihood that a direct social connection between a directly connected node (“v”) and the user node is explained by at least a shared attribute label between the user node and the directly connected node; and ranking a first set of the possible attribute labels for the user node by maximizing the explainability scores utilizing the multiple equations respectively associated with the nodes, the explainability scores being implicit predictions of formation reasons of social connections between each of the nodes and the user node. 15. The computer-implemented method of claim 1 , further comprising associating a top ranked label in the first set of the possible attribute labels with the user node in the social networking system. | 0.864865 |
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