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7,987,172 | 23 | 24 |
23. A non-transitory computer readable storage medium, for scheduling documents to be crawled by a search engine in an appropriate order to reduce visibility of stale content in web searching, storing one or more programs to be executed by a computer system, wherein the computer system includes a search engine program, the one or more programs comprising: instructions for associating with each of a plurality of documents a respective initial web crawl interval, wherein the initial web crawl interval is determined based at least in part on a document's importance metric; instructions for retrieving each of the plurality of documents from a respective host at one or more times associated with each document's respective initial web crawl interval; instructions for associating a revised web crawl interval with a respective document of the plurality of documents based on the document's respective initial web crawl interval and any changes to content of the document; instructions for partitioning the plurality of documents into multiple tiers according to their respective web crawl intervals, each tier having a distinct associated range of web crawl intervals, including instructions for storing data for each tier identifying documents in the plurality of documents assigned to that tier in accordance with their respective web crawl intervals; instructions for determining, for each tier of the multiple tiers, a web crawl order for the documents assigned to the tier in accordance with their respective revised web crawl intervals; and instructions for moving a respective document between tiers of the multiple tiers when the respective revised web crawl interval of the respective document is associated with a different tier of the multiple tiers than a previous web crawl interval of the respective document.
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23. A non-transitory computer readable storage medium, for scheduling documents to be crawled by a search engine in an appropriate order to reduce visibility of stale content in web searching, storing one or more programs to be executed by a computer system, wherein the computer system includes a search engine program, the one or more programs comprising: instructions for associating with each of a plurality of documents a respective initial web crawl interval, wherein the initial web crawl interval is determined based at least in part on a document's importance metric; instructions for retrieving each of the plurality of documents from a respective host at one or more times associated with each document's respective initial web crawl interval; instructions for associating a revised web crawl interval with a respective document of the plurality of documents based on the document's respective initial web crawl interval and any changes to content of the document; instructions for partitioning the plurality of documents into multiple tiers according to their respective web crawl intervals, each tier having a distinct associated range of web crawl intervals, including instructions for storing data for each tier identifying documents in the plurality of documents assigned to that tier in accordance with their respective web crawl intervals; instructions for determining, for each tier of the multiple tiers, a web crawl order for the documents assigned to the tier in accordance with their respective revised web crawl intervals; and instructions for moving a respective document between tiers of the multiple tiers when the respective revised web crawl interval of the respective document is associated with a different tier of the multiple tiers than a previous web crawl interval of the respective document. 24. The computer readable storage medium of claim 23 , wherein the one or more programs further comprise: instructions for determining for respective documents of the plurality of documents, content update rates of the respective documents, user click rates of the respective documents, and at least one document importance metric of the respective documents; instructions for associating the revised web crawl interval with each document of the plurality of documents based on the document's respective initial web crawl interval, any changes to content of the document, the user click rate of the document, and the at least one document importance metric of the document; and instructions for downloading and recording new copies of at least a subset of the documents in accordance with the determined web crawl order.
| 0.5 |
8,880,495 | 1 | 8 |
1. A method for constructing an expanded search query at a computing device, the method comprising: receiving audio information via a microphone of the computing device; recording the audio information in an overwriteable circular buffer of the computing device, including recording at least some of the audio information during a period when the computing device is powered-on, but is in an inactive state or a sleep state in which a graphical display of the computing device is off or substantially dimmed, said recording initiated responsive to a triggering condition including detection of a sound level via the microphone that exceeds a sound level threshold, the overwriteable circular buffer having a limited data storage capacity in which older audio information is overwritten with newer audio information upon reaching the limited data storage capacity; initiating construction of a search query by receiving a user input via a text-based user interface of the computing device, the user input including one or more keywords forming a user-defined portion of the search query; processing at least a portion of the audio information recorded in the overwriteable circular buffer to obtain one or more additional keywords forming an expanded portion of the search query, the portion of the audio information containing the one or more additional keywords received and recorded in the overwriteable circular buffer prior to receiving the user input including the one or more keywords; supplying the search query including the user-defined portion and the expanded portion to a search engine; and receiving a response to the search query from the search engine, the response generated by the search engine based, at least in part, on the one or more keywords of the user-defined portion and the one or more additional keywords of the expanded portion of the search query.
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1. A method for constructing an expanded search query at a computing device, the method comprising: receiving audio information via a microphone of the computing device; recording the audio information in an overwriteable circular buffer of the computing device, including recording at least some of the audio information during a period when the computing device is powered-on, but is in an inactive state or a sleep state in which a graphical display of the computing device is off or substantially dimmed, said recording initiated responsive to a triggering condition including detection of a sound level via the microphone that exceeds a sound level threshold, the overwriteable circular buffer having a limited data storage capacity in which older audio information is overwritten with newer audio information upon reaching the limited data storage capacity; initiating construction of a search query by receiving a user input via a text-based user interface of the computing device, the user input including one or more keywords forming a user-defined portion of the search query; processing at least a portion of the audio information recorded in the overwriteable circular buffer to obtain one or more additional keywords forming an expanded portion of the search query, the portion of the audio information containing the one or more additional keywords received and recorded in the overwriteable circular buffer prior to receiving the user input including the one or more keywords; supplying the search query including the user-defined portion and the expanded portion to a search engine; and receiving a response to the search query from the search engine, the response generated by the search engine based, at least in part, on the one or more keywords of the user-defined portion and the one or more additional keywords of the expanded portion of the search query. 8. The method of claim 1 , wherein the one or more keywords of the user-defined portion define an initial search domain; and wherein the one or more additional keywords of the expanded portion define one or more sub-domains within the initial search domain.
| 0.798905 |
7,945,632 | 27 | 29 |
27. The hardware-implemented system of claim 24 , wherein said sequential pattern determination module configured to determine one or more sequential patterns associated with the at least one subjective user state and the at least one objective occurrence comprises: a historical data referencing module configured to reference historical data.
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27. The hardware-implemented system of claim 24 , wherein said sequential pattern determination module configured to determine one or more sequential patterns associated with the at least one subjective user state and the at least one objective occurrence comprises: a historical data referencing module configured to reference historical data. 29. The hardware-implemented system of claim 27 , wherein said historical data referencing module configured to reference historical data comprises: a historical data referencing module configured to reference historical data indicating at least one historical sequential pattern.
| 0.570552 |
10,157,070 | 13 | 18 |
13. A computer program product comprising a non-transitory machine-readable medium storing instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising: receiving at least one parameter relating to a document; generating at least one narrative based on the received parameter; generating at least one document mapping based on the at least one generated narrative; wherein the at least one document mapping includes: (i) a plurality of magnet component identifiers, (ii) a plurality of pivot component identifiers, and (iii) a plurality of glow component identifiers; displaying to a user the plurality of magnet component identifiers, the plurality of pivot component identifiers, and the plurality of glow component identifiers; receiving from the user a selected magnet component identifier from the plurality of magnet component identifiers; receiving from the user a selected pivot component identifier from the plurality of pivot component identifiers; receiving from the user a selected glow component identifier from the plurality of glow component identifiers; generating a user-selected map based on the selected magnet component identifier, the selected pivot component identifier, and the selected glow component identifier; and combining the user-selected map and the at least one generated narrative to generate the document.
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13. A computer program product comprising a non-transitory machine-readable medium storing instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising: receiving at least one parameter relating to a document; generating at least one narrative based on the received parameter; generating at least one document mapping based on the at least one generated narrative; wherein the at least one document mapping includes: (i) a plurality of magnet component identifiers, (ii) a plurality of pivot component identifiers, and (iii) a plurality of glow component identifiers; displaying to a user the plurality of magnet component identifiers, the plurality of pivot component identifiers, and the plurality of glow component identifiers; receiving from the user a selected magnet component identifier from the plurality of magnet component identifiers; receiving from the user a selected pivot component identifier from the plurality of pivot component identifiers; receiving from the user a selected glow component identifier from the plurality of glow component identifiers; generating a user-selected map based on the selected magnet component identifier, the selected pivot component identifier, and the selected glow component identifier; and combining the user-selected map and the at least one generated narrative to generate the document. 18. The computer program product according to claim 13 , wherein the operations further comprise selecting at least one portion of the document; modifying the at least one selected portion of the document; and generating, based on the at least one modified selected portion of the document, a modified document.
| 0.5 |
9,853,818 | 24 | 64 |
24. The system as recited in claim 1 , further comprising a plurality of policies under which the signature authority operates.
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24. The system as recited in claim 1 , further comprising a plurality of policies under which the signature authority operates. 64. The system as recited in claim 24 , wherein the plurality of policies of the signature authority further comprises at least one policy selected from the group comprising one or more policies and procedures under which a presentation authority operates to provide the signing party a facsimile of the to be signed document and one or more policies and procedures under which a registration authority operates to authenticate the signing party, whereby the relying party relies on one or more of the plurality of policies of the signature authority for evaluating the risk of relying on the digitally signed electronic document.
| 0.5 |
7,917,847 | 1 | 15 |
1. A method of rendering a page, comprising: starting obtaining operation for obtaining, over a network, a page made by a markup language and definition information, which is information to be applied to the entire page so as to render the page as designated by a markup language document of the page, the obtaining performed in response to a user request for the page; performing a text browsing mode operation on obtained part of data of the page in parallel with the obtaining operation of the page and definition information; displaying text from the obtained part of data of the page in a text browsing mode without using definition information; judging whether or not acquisition of the entirety of the definition information is obtained from over the network; and switching onscreen representation, depending on a result of the judging, by replacing the onscreen representation in the text browsing mode in which the definition information is not applied, with an onscreen representation in which the definition information is applied.
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1. A method of rendering a page, comprising: starting obtaining operation for obtaining, over a network, a page made by a markup language and definition information, which is information to be applied to the entire page so as to render the page as designated by a markup language document of the page, the obtaining performed in response to a user request for the page; performing a text browsing mode operation on obtained part of data of the page in parallel with the obtaining operation of the page and definition information; displaying text from the obtained part of data of the page in a text browsing mode without using definition information; judging whether or not acquisition of the entirety of the definition information is obtained from over the network; and switching onscreen representation, depending on a result of the judging, by replacing the onscreen representation in the text browsing mode in which the definition information is not applied, with an onscreen representation in which the definition information is applied. 15. The method according to claim 1 , wherein the definition information includes at least one of an external style sheet and an external script.
| 0.866236 |
8,463,593 | 1 | 3 |
1. A computer-implemented method for indexing information with word sense disambiguation, the method comprising: determining, by a computing device, a plurality of first word senses S n associated with a given word W; determining, by the computing device, a plurality of hypernyms H n associated with each of the plurality of first word senses S n ; establishing, by the computing device, a word hypernym weight WHW(H n ,W)for each of the plurality of hypernyms H n based on
WHW ( H n, W )=Σ p ( S n |W )f( H n ,S n ), where the word hypernym weight WHW(H n ,W) being equal to a sum, over the plurality of first word senses S n , of the product of the probability p of the sense of the given word S n |W and a function f(H n ,S n ) defined as having a value of one when a given hypernym H is an inherited hypernym of the plurality of word senses Sn, and having a value of zero otherwise; selecting, by the computing device, a hypernym H s from the plurality of hypernyms H n based on the word hypernym weight WHW(H n ,W); and storing, by the computing device, a second word sense S s of the selected hypernym H s into a semantic index.
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1. A computer-implemented method for indexing information with word sense disambiguation, the method comprising: determining, by a computing device, a plurality of first word senses S n associated with a given word W; determining, by the computing device, a plurality of hypernyms H n associated with each of the plurality of first word senses S n ; establishing, by the computing device, a word hypernym weight WHW(H n ,W)for each of the plurality of hypernyms H n based on
WHW ( H n, W )=Σ p ( S n |W )f( H n ,S n ), where the word hypernym weight WHW(H n ,W) being equal to a sum, over the plurality of first word senses S n , of the product of the probability p of the sense of the given word S n |W and a function f(H n ,S n ) defined as having a value of one when a given hypernym H is an inherited hypernym of the plurality of word senses Sn, and having a value of zero otherwise; selecting, by the computing device, a hypernym H s from the plurality of hypernyms H n based on the word hypernym weight WHW(H n ,W); and storing, by the computing device, a second word sense S s of the selected hypernym H s into a semantic index. 3. The method of claim 1 , further comprising storing, by the computing device, the selected hypernym H s into the semantic index.
| 0.539007 |
7,483,894 | 19 | 20 |
19. The method of claim 1 , wherein the additional information comprises a perspective of the user.
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19. The method of claim 1 , wherein the additional information comprises a perspective of the user. 20. The method of claim 19 , wherein the perspective is selected from the list consisting of purchasing, shopping, procurement, bartering, requesting for quotes.
| 0.5 |
9,563,635 | 13 | 16 |
13. A computer system for eliminating redundant information in a log file having unknown grammar, the computer system comprising: one or more computer processors; one or more computer-readable storage media; program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to identify an alphanumeric string in a log file, the alphanumeric string comprising a plurality of alphanumeric substrings separated by non-alphanumeric characters, the plurality of alphanumeric substrings including at least two distinct alphanumeric substrings; program instructions to replace each alphanumeric substring of the plurality of alphanumeric substrings with a first alphanumeric character to generate a first resulting string that includes the non-alphanumeric characters and multiple occurrences of the first alphanumeric character; program instructions to replace each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string with a second alphanumeric character to generate a second resulting string, wherein the program instructions to replace each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string with a second alphanumeric character to generate a second resulting string comprise: program instructions to, responsive to determining that there are multiple distinct pairs of characters of the first resulting string that are identical to another pair of characters of the first resulting string and that the multiple distinct pairs of characters occur an equal number of times in the first resulting string, select a pair of the multiple distinct pairs of characters based on a pre-defined hierarchy of characters included in the multiple distinct pairs of characters, and program instructions to replace the selected pair of characters with a second alphanumeric character to generate a second resulting string; and program instructions to replace consecutive occurrences of the second alphanumeric character, in the second resulting string, with one occurrence of the second alphanumeric character to generate a compressed string.
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13. A computer system for eliminating redundant information in a log file having unknown grammar, the computer system comprising: one or more computer processors; one or more computer-readable storage media; program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to identify an alphanumeric string in a log file, the alphanumeric string comprising a plurality of alphanumeric substrings separated by non-alphanumeric characters, the plurality of alphanumeric substrings including at least two distinct alphanumeric substrings; program instructions to replace each alphanumeric substring of the plurality of alphanumeric substrings with a first alphanumeric character to generate a first resulting string that includes the non-alphanumeric characters and multiple occurrences of the first alphanumeric character; program instructions to replace each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string with a second alphanumeric character to generate a second resulting string, wherein the program instructions to replace each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string with a second alphanumeric character to generate a second resulting string comprise: program instructions to, responsive to determining that there are multiple distinct pairs of characters of the first resulting string that are identical to another pair of characters of the first resulting string and that the multiple distinct pairs of characters occur an equal number of times in the first resulting string, select a pair of the multiple distinct pairs of characters based on a pre-defined hierarchy of characters included in the multiple distinct pairs of characters, and program instructions to replace the selected pair of characters with a second alphanumeric character to generate a second resulting string; and program instructions to replace consecutive occurrences of the second alphanumeric character, in the second resulting string, with one occurrence of the second alphanumeric character to generate a compressed string. 16. The computer system of claim 13 , further comprising: program instructions to associate the second alphanumeric character with each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string to create a substitution rule; and program instructions to generate a list of substitution rules for a plurality of created substitution rules within the log file.
| 0.513699 |
9,832,207 | 10 | 13 |
10. The computing apparatus of claim 7 , wherein the binary translation engine is a Java Virtual Machine, and wherein the IVE is implemented at least partly in Java.
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10. The computing apparatus of claim 7 , wherein the binary translation engine is a Java Virtual Machine, and wherein the IVE is implemented at least partly in Java. 13. The computing apparatus of claim 10 , wherein exporting the input comprises exporting the input to a java native interface wrapper.
| 0.5 |
9,183,294 | 16 | 20 |
16. A computer program product, comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to perform the steps of: defining a meta-ontology, wherein the meta-ontology includes high-level properties and their mappings to specific properties defined in a plurality of different ontologies; receiving a question, wherein the question is associated with a high-level property; and providing an answer to the question, wherein the answer is determined by referring only to the meta-ontology to retrieve required information, and in answering a question about a concept, synonyms of the concept's name used in the question are retrieved, and then, the synonyms are used to retrieve corresponding uniform resource identifiers, wherein a synonym is a high-level property included in a resource description framework description of each of the ontologies, wherein the resource description framework description of a first ontology of the ontologies describes how a first synonym corresponds to a first property from the first ontology and how the first synonym is queried such that the first synonym can be retrieved from the first ontology.
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16. A computer program product, comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to perform the steps of: defining a meta-ontology, wherein the meta-ontology includes high-level properties and their mappings to specific properties defined in a plurality of different ontologies; receiving a question, wherein the question is associated with a high-level property; and providing an answer to the question, wherein the answer is determined by referring only to the meta-ontology to retrieve required information, and in answering a question about a concept, synonyms of the concept's name used in the question are retrieved, and then, the synonyms are used to retrieve corresponding uniform resource identifiers, wherein a synonym is a high-level property included in a resource description framework description of each of the ontologies, wherein the resource description framework description of a first ontology of the ontologies describes how a first synonym corresponds to a first property from the first ontology and how the first synonym is queried such that the first synonym can be retrieved from the first ontology. 20. The computer program product of claim 16 , wherein the meta-ontology includes information about how to generate queries that are used to retrieve information associated with the high-level properties from the ontologies.
| 0.586716 |
8,249,352 | 1 | 16 |
1. A document image processing apparatus comprising: a specifying section that specifies a sentence region including a character row from a document image; an extracting section that extracts at least one of character row images included in the specified sentence region; a recognizing section that recognizes respective characters included in the extracted character row image; an interpreting section that interprets an original sentence character row comprising the recognized characters and generates an interpreted sentence character row; an arranging section that arranges the respective character row images in the sentence region by contracting the respective character row images, the respective character row images each including an image of an original character row, the arranging section that arranges the generated respective interpreted sentence character rows in a vacant region except a region arranging the respective character row images from the sentence region; and a generating section that generates a data of an output document arranged with the respective character row images and the respective interpreted sentence character rows in the sentence region, wherein the arranging section arranges the interpreted sentence character row and the original sentence character row by first aligning the interpreted sentence character row and the original sentence character row, then by correcting a size of the longer of the interpreted sentence character row and the original sentence character row to match the length of the shorter, and then by confining the interpreted sentence character row and the original sentence character row in the sentence region.
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1. A document image processing apparatus comprising: a specifying section that specifies a sentence region including a character row from a document image; an extracting section that extracts at least one of character row images included in the specified sentence region; a recognizing section that recognizes respective characters included in the extracted character row image; an interpreting section that interprets an original sentence character row comprising the recognized characters and generates an interpreted sentence character row; an arranging section that arranges the respective character row images in the sentence region by contracting the respective character row images, the respective character row images each including an image of an original character row, the arranging section that arranges the generated respective interpreted sentence character rows in a vacant region except a region arranging the respective character row images from the sentence region; and a generating section that generates a data of an output document arranged with the respective character row images and the respective interpreted sentence character rows in the sentence region, wherein the arranging section arranges the interpreted sentence character row and the original sentence character row by first aligning the interpreted sentence character row and the original sentence character row, then by correcting a size of the longer of the interpreted sentence character row and the original sentence character row to match the length of the shorter, and then by confining the interpreted sentence character row and the original sentence character row in the sentence region. 16. The document image processing apparatus according to claim 1 , wherein at least one of the respective character row images is divided into a divided portion, the divided portion being arranged at a next line with another respective character row image.
| 0.714286 |
8,078,451 | 7 | 15 |
7. A computer-implemented method for training a proofing tool for providing automated proofing of textual document, comprising: receiving a first text in a language; receiving editorial corrections to be made to the first text; utilizing a computer processor that is a component of a computer to create a data structure that provides information indicative of the first text and the editorial corrections; attaching author information about an author of the first text to the data structure, the author information identifying a native language of the author, the native language of the author being a language other than the language of the first text; and providing the data structure to the proofing tool.
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7. A computer-implemented method for training a proofing tool for providing automated proofing of textual document, comprising: receiving a first text in a language; receiving editorial corrections to be made to the first text; utilizing a computer processor that is a component of a computer to create a data structure that provides information indicative of the first text and the editorial corrections; attaching author information about an author of the first text to the data structure, the author information identifying a native language of the author, the native language of the author being a language other than the language of the first text; and providing the data structure to the proofing tool. 15. A computer-implemented method of claim 7 , wherein the author information attached to the data structure comprises information apart from the first text.
| 0.686 |
4,049,913 | 2 | 3 |
2. A continuous speech recognition system as claimed in claim 1, said word number K being preselected to be equal to said first predetermined number k, wherein said recognition means comprises first matching means responsive to said input and reference pattern feature vectors for finding a partial similarity measure S<p, m> and a partial recognition result n<p, m>, said partial similarity measure being defined as a maximum of similarity measures S[A(p, m), B.sup.n ] between each partial pattern A(p, m) and said reference patterns, said partial pattern being defined by a part of said input pattern feature vector sequence as: EQU A(p, m) = a.sub.p+1, a.sub.p+2, . . . , a.sub.m, said partial recognition result being one of said reference patterns that gives said maximum; second matching means responsive to said word number K and the partial similarity measures for finding a maximum of summations, each being calculated for the partial similarity measures of those partial patterns, K in number, into a concatenation of which said input pattern is divided; and decision means responsive to said word number K and the partial recognition results for deciding said input pattern to be the partial recognition results for those partial patterns of a concatenation for which said maximum summation is found.
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2. A continuous speech recognition system as claimed in claim 1, said word number K being preselected to be equal to said first predetermined number k, wherein said recognition means comprises first matching means responsive to said input and reference pattern feature vectors for finding a partial similarity measure S<p, m> and a partial recognition result n<p, m>, said partial similarity measure being defined as a maximum of similarity measures S[A(p, m), B.sup.n ] between each partial pattern A(p, m) and said reference patterns, said partial pattern being defined by a part of said input pattern feature vector sequence as: EQU A(p, m) = a.sub.p+1, a.sub.p+2, . . . , a.sub.m, said partial recognition result being one of said reference patterns that gives said maximum; second matching means responsive to said word number K and the partial similarity measures for finding a maximum of summations, each being calculated for the partial similarity measures of those partial patterns, K in number, into a concatenation of which said input pattern is divided; and decision means responsive to said word number K and the partial recognition results for deciding said input pattern to be the partial recognition results for those partial patterns of a concatenation for which said maximum summation is found. 3. A continuous speech recognition system as claimed in claim 2, wherein said second matching means comprises means responsive to said partial similarity measures for finding segmentation points at which said input pattern is divided into those partial patterns of the concatenation for which said maximum summation is found, and said decision means comprises means responsive to said word number K for successively specifying consecutive integers between unity and said word number K and means responsive to said partial recognition results, said consecutive integers, and said segmentation points for successively selecting those partial recognition results with refrence to said segmentation points which are for said partial pattern concatenation.
| 0.5 |
8,671,088 | 1 | 10 |
1. A method comprising: extracting, via a processor, key data from a user query; submitting the key data to a search engine to perform a search and to retrieve a set of top n pages from a database, wherein in response to a restriction to access a restricted page of the set of top n pages, the processor without user interference negotiates a fee to overcome the restriction independent of a user navigation to the restricted page; providing, at a first time, a response to the user query; after providing the response at the first time, continuing, without further user input, to search for information associated with the user query using a machine learning process to expand the search; and presenting an option to a device associated with a user, at a second time which is later than the first time, to view the related information separate from the response.
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1. A method comprising: extracting, via a processor, key data from a user query; submitting the key data to a search engine to perform a search and to retrieve a set of top n pages from a database, wherein in response to a restriction to access a restricted page of the set of top n pages, the processor without user interference negotiates a fee to overcome the restriction independent of a user navigation to the restricted page; providing, at a first time, a response to the user query; after providing the response at the first time, continuing, without further user input, to search for information associated with the user query using a machine learning process to expand the search; and presenting an option to a device associated with a user, at a second time which is later than the first time, to view the related information separate from the response. 10. The method of claim 1 , wherein the user interacts with a virtual agent in a dialog mode.
| 0.705696 |
9,483,741 | 1 | 9 |
1. A computer-implemented method for product classification, the method comprising: receiving, by one or more processors of a server, a product record associated with a product, the product record comprising a description of the product; generating, by the one or more processors, a first ranked list of product types based on the product record using a plurality of rule-based classifiers; generating, by the one or more processors, a second ranked list of product types based on the product record using a plurality of machine learning-based classifiers; aggregating, by the one or more processors, the first ranked list of product types and the second ranked list of product types to generate a combined ranked list of product types; providing the description of the product and a portion of the combined ranked list of product types to a crowdsourcing computer network for evaluation; and returning, from the crowdsourcing computer network, a validation decision, wherein: when the crowdsourcing computer network determines that a type of the product is correct, the validation decision indicates that the type of the product is correct; when the crowdsourcing computer network determines that the type of the product is not correct, the validation decision indicates that the type of the product is not correct; and when the crowdsourcing computer network determines that the description of the product is insufficient to accurately judge whether the type of the product is correct, the validation decision indicates that the type of the product is unclear.
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1. A computer-implemented method for product classification, the method comprising: receiving, by one or more processors of a server, a product record associated with a product, the product record comprising a description of the product; generating, by the one or more processors, a first ranked list of product types based on the product record using a plurality of rule-based classifiers; generating, by the one or more processors, a second ranked list of product types based on the product record using a plurality of machine learning-based classifiers; aggregating, by the one or more processors, the first ranked list of product types and the second ranked list of product types to generate a combined ranked list of product types; providing the description of the product and a portion of the combined ranked list of product types to a crowdsourcing computer network for evaluation; and returning, from the crowdsourcing computer network, a validation decision, wherein: when the crowdsourcing computer network determines that a type of the product is correct, the validation decision indicates that the type of the product is correct; when the crowdsourcing computer network determines that the type of the product is not correct, the validation decision indicates that the type of the product is not correct; and when the crowdsourcing computer network determines that the description of the product is insufficient to accurately judge whether the type of the product is correct, the validation decision indicates that the type of the product is unclear. 9. The method of claim 1 , wherein the plurality of machine learning-based classifiers comprises at least one of a naive Bayes classifier, a k-Nearest Neighbors (KNN) classifier, or a Perceptron classifier.
| 0.896897 |
9,251,206 | 13 | 15 |
13. The system of claim 9 , wherein the operations further comprise: receiving a current query and a plurality of suggested queries, each of the current and suggested queries including one or more terms; for each suggested query: calculating a transition cost between the suggested query and the current query based on a transition cost of a current term and a suggested term; and selecting a suggested query from the plurality of suggested queries based on the edit distance.
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13. The system of claim 9 , wherein the operations further comprise: receiving a current query and a plurality of suggested queries, each of the current and suggested queries including one or more terms; for each suggested query: calculating a transition cost between the suggested query and the current query based on a transition cost of a current term and a suggested term; and selecting a suggested query from the plurality of suggested queries based on the edit distance. 15. The system of claim 13 , wherein the calculating the edit distance comprises: identifying values in a plurality of cost matrices based on a substitution query pair including the current term and the suggested term; and averaging the identified values.
| 0.5 |
7,613,732 | 1 | 2 |
1. A method for email address automation, comprising: a) parsing, by a computing device, an entry in an email addressee field the email addressee field entry residing in computer readable memory; b) determining, by the computing device, whether the entry includes a predefined notation appended to the entry; and c) if the entry has a predefined notation appended to the entry, traversing, by the computing device, a hierarchy structure from a name in the entry to a designated level of the hierarchy structure based on the predefined notation; retrieving, by the computing device, email addresses of names listed at the designated level; and replacing, by the computing device, the entry in the email addressee field with the email addresses retrieved from the designated level of the hierarchy structure; wherein the predefined notation defines a relationship between the names at the designated level and the name included in the entry, the predefined notation including a special character indicating if the designated level is a higher or lower level than a level of the name in the entry, and a level indicator indicating a number of levels between the designated level and the level of the name in the entry.
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1. A method for email address automation, comprising: a) parsing, by a computing device, an entry in an email addressee field the email addressee field entry residing in computer readable memory; b) determining, by the computing device, whether the entry includes a predefined notation appended to the entry; and c) if the entry has a predefined notation appended to the entry, traversing, by the computing device, a hierarchy structure from a name in the entry to a designated level of the hierarchy structure based on the predefined notation; retrieving, by the computing device, email addresses of names listed at the designated level; and replacing, by the computing device, the entry in the email addressee field with the email addresses retrieved from the designated level of the hierarchy structure; wherein the predefined notation defines a relationship between the names at the designated level and the name included in the entry, the predefined notation including a special character indicating if the designated level is a higher or lower level than a level of the name in the entry, and a level indicator indicating a number of levels between the designated level and the level of the name in the entry. 2. The method of claim 1 , further comprising sending, by the computing device, an email to all email addresses listed in the email addressee field.
| 0.775758 |
8,510,274 | 3 | 4 |
3. A method for verifying conversion as set forth in claim 2 , wherein when the first SQL sentence data and the second SQL sentence data are not for acquiring the operation result with respect to the table data, the first SQL sentence data and the second SQL sentence data are converted into SQL sentence data acquiring the data of the operation result or under operation, and the SQL sentence data after conversion is executed in the third step.
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3. A method for verifying conversion as set forth in claim 2 , wherein when the first SQL sentence data and the second SQL sentence data are not for acquiring the operation result with respect to the table data, the first SQL sentence data and the second SQL sentence data are converted into SQL sentence data acquiring the data of the operation result or under operation, and the SQL sentence data after conversion is executed in the third step. 4. A method for verifying conversion as set forth in claim 3 , wherein: first data which is acquired depending on the execution of the first SQL sentence data are stored sequentially in a predetermined point in execution result table data decided beforehand in the third step, and second data which is acquired depending on the execution of the second SQL sentence data are stored sequentially in a predetermined point in the execution result table data in the third step, and the second data are compared with the first data in the execution result table data in the fourth step.
| 0.5 |
8,984,386 | 58 | 64 |
58. One or more non-transitory computer-readable media storing instructions which, when executed by one or more processors, cause the one or more processors to perform a method comprising steps of: creating, by a computer-based service, a plurality of associations, each of which associates (a) occurrence of one or more application events from a plurality of application events, with (b) one or more users from a plurality of users; enabling, by the computer-based service, each user of the plurality of users to interact, over a network, with one or more applications; monitoring, by the computer-based service, for occurrence of said plurality of application events; wherein each application event, from the plurality of application events, corresponds to interaction with at least one of the one or more applications, by at least one user from the plurality of users; in response, at least in part, to occurrence of a first application event from the plurality of application events, the computer-based service sending first information about the first application event to each user of a plurality of second users, from the plurality of users; wherein the first information includes one or more links that provide access to one or more views that are associated with the first application event; wherein the first application event occurred based, at least in part, on interaction of a first user, from the plurality of users, with a given view from the one or more views; wherein sending the first information includes sending the first information to at least one user of the plurality of second users, based, at least in part, on a first association of the plurality of associations; wherein the step of creating includes creating the first association based on the computer-based service receiving, from the at least one user of the plurality of second users, an expression of interest in interactions of the first user; receiving, by the computer-based service, a comment from a particular second user, of the plurality of second users; wherein the first user is a different user than the particular second user; wherein the comment is entered in a text entry interface that is related to the first information; and the computer-based service sending the comment, to each user of the plurality of second users other than the particular second user, to enable display of the comment, in relation to the first information, to the each user of the plurality of second users other than the particular second user.
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58. One or more non-transitory computer-readable media storing instructions which, when executed by one or more processors, cause the one or more processors to perform a method comprising steps of: creating, by a computer-based service, a plurality of associations, each of which associates (a) occurrence of one or more application events from a plurality of application events, with (b) one or more users from a plurality of users; enabling, by the computer-based service, each user of the plurality of users to interact, over a network, with one or more applications; monitoring, by the computer-based service, for occurrence of said plurality of application events; wherein each application event, from the plurality of application events, corresponds to interaction with at least one of the one or more applications, by at least one user from the plurality of users; in response, at least in part, to occurrence of a first application event from the plurality of application events, the computer-based service sending first information about the first application event to each user of a plurality of second users, from the plurality of users; wherein the first information includes one or more links that provide access to one or more views that are associated with the first application event; wherein the first application event occurred based, at least in part, on interaction of a first user, from the plurality of users, with a given view from the one or more views; wherein sending the first information includes sending the first information to at least one user of the plurality of second users, based, at least in part, on a first association of the plurality of associations; wherein the step of creating includes creating the first association based on the computer-based service receiving, from the at least one user of the plurality of second users, an expression of interest in interactions of the first user; receiving, by the computer-based service, a comment from a particular second user, of the plurality of second users; wherein the first user is a different user than the particular second user; wherein the comment is entered in a text entry interface that is related to the first information; and the computer-based service sending the comment, to each user of the plurality of second users other than the particular second user, to enable display of the comment, in relation to the first information, to the each user of the plurality of second users other than the particular second user. 64. The one or more non-transitory computer-readable media of claim 58 wherein: the computer-based service sends the comment to a given second user of the plurality of second users, based, at least in part, on the first information having been sent to the given second user; and the given second user is a different user than the particular second user.
| 0.741581 |
7,584,280 | 1 | 5 |
1. A system for providing a dynamic user configurable output for multi-modal context-sensitive applications in a home network, the system comprising: a processor; a memory couple to the processor; an input processing agent unit classifying inputs from a predetermined input device based on at least one criterion selected from the group consisting of an input block, an input type, a priority, and ranking and then outputting an input with the highest priority and the highest ranking among the classified inputs; an input collaboration agent unit obtaining a pre-defined output action for an input type corresponding to each input based on a user's context by performing real-time analysis on each of the inputs fed by the input processing agent unit and obtaining a possible output action based on the user's context by performing a probabilistic inference on the inputs fed by the input processing agent unit; a user manager agent unit to transmit the current user's profile and a detected user context to the input collaboration agent through an agent server and obtaining a user interface in accordance with an output resource corresponding to the output action determined by the input collaboration agent, wherein the output resource, which is available in the home network and corresponds to the current user's context, is based on the current user's profile and the detected user context; and the agent server obtaining the output resource, which is available in the home network and corresponds to the user's context, based on the output action obtained by comparing the output actions from the input collaboration agent.
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1. A system for providing a dynamic user configurable output for multi-modal context-sensitive applications in a home network, the system comprising: a processor; a memory couple to the processor; an input processing agent unit classifying inputs from a predetermined input device based on at least one criterion selected from the group consisting of an input block, an input type, a priority, and ranking and then outputting an input with the highest priority and the highest ranking among the classified inputs; an input collaboration agent unit obtaining a pre-defined output action for an input type corresponding to each input based on a user's context by performing real-time analysis on each of the inputs fed by the input processing agent unit and obtaining a possible output action based on the user's context by performing a probabilistic inference on the inputs fed by the input processing agent unit; a user manager agent unit to transmit the current user's profile and a detected user context to the input collaboration agent through an agent server and obtaining a user interface in accordance with an output resource corresponding to the output action determined by the input collaboration agent, wherein the output resource, which is available in the home network and corresponds to the current user's context, is based on the current user's profile and the detected user context; and the agent server obtaining the output resource, which is available in the home network and corresponds to the user's context, based on the output action obtained by comparing the output actions from the input collaboration agent. 5. The system of claim 1 , further comprising: a security agent unit authenticating a current user and detecting a profile and a context that correspond to the authenticated current user.
| 0.911458 |
8,805,861 | 5 | 8 |
5. A computer-implemented method for extracting and integrating information from one or more sources, comprising: obtaining a domain model comprising a set of entity types having corresponding properties and relationships between entities in a set of entities, wherein the domain model is characterized by a domain grammar; receiving a first tag layout of a first source document obtained from a first information source associated with the domain model, the first tag layout comprising: (i) a plurality of user-provided navigational tags, wherein a user-provided navigational tag in the plurality of a user-provided navigational tags indicates a navigational position of the first source document relative to a second source document, from the first information source, navigationally connected with the first source document, and (ii) a plurality of corresponding user-identified tokens in the first source document, wherein a user-identified token in the plurality of corresponding user-identified tokens includes a portion of content of the first source document; selecting a page grammar in plurality of page grammars for the first source document in accordance with the plurality of user provided navigational tags; extracting information from a third of source document having a predefined degree of tag layout similarity to the first source document using the page grammar, wherein the second source document is obtained from a second information source; and transforming the information extracted from the second source document in accordance with the domain grammar, thereby extracting and integrating information from a plurality of information sources.
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5. A computer-implemented method for extracting and integrating information from one or more sources, comprising: obtaining a domain model comprising a set of entity types having corresponding properties and relationships between entities in a set of entities, wherein the domain model is characterized by a domain grammar; receiving a first tag layout of a first source document obtained from a first information source associated with the domain model, the first tag layout comprising: (i) a plurality of user-provided navigational tags, wherein a user-provided navigational tag in the plurality of a user-provided navigational tags indicates a navigational position of the first source document relative to a second source document, from the first information source, navigationally connected with the first source document, and (ii) a plurality of corresponding user-identified tokens in the first source document, wherein a user-identified token in the plurality of corresponding user-identified tokens includes a portion of content of the first source document; selecting a page grammar in plurality of page grammars for the first source document in accordance with the plurality of user provided navigational tags; extracting information from a third of source document having a predefined degree of tag layout similarity to the first source document using the page grammar, wherein the second source document is obtained from a second information source; and transforming the information extracted from the second source document in accordance with the domain grammar, thereby extracting and integrating information from a plurality of information sources. 8. A computer-implemented method of claim 5 wherein the page grammar for the first set of documents is selected by running a Viterbi algorithm on the tag layout.
| 0.759701 |
9,245,278 | 14 | 17 |
14. A method comprising: performing by one or more computer processors: obtaining an original text message in a first language authored by a first user: obtaining an initial translation of the original text message in a second language; obtaining a translation correction of the initial translation, wherein the translation correction is authored by a second user; calculating at least one metric associated with the translation correction, the at least one metric being based on a comparison of a word-alignment feature of the original text and the translation correction, wherein calculating the at least one metric comprises determining an alignment of at least one word in the translation correction and a corresponding at least one word in the original message; and determining an accuracy of the translation correction based on the at least one metric.
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14. A method comprising: performing by one or more computer processors: obtaining an original text message in a first language authored by a first user: obtaining an initial translation of the original text message in a second language; obtaining a translation correction of the initial translation, wherein the translation correction is authored by a second user; calculating at least one metric associated with the translation correction, the at least one metric being based on a comparison of a word-alignment feature of the original text and the translation correction, wherein calculating the at least one metric comprises determining an alignment of at least one word in the translation correction and a corresponding at least one word in the original message; and determining an accuracy of the translation correction based on the at least one metric. 17. The method of claim 14 , further comprising: offering an incentive to the second user to provide the translation correction; and rewarding the second user with the respective incentive when the translation correction is determined to be accurate.
| 0.565972 |
7,571,098 | 17 | 18 |
17. A tangible computer-readable medium that stores a program for controlling a computer device to perform a speech processing method, the method comprising: at an automatic speech recognition (ASR) engine: converting a word lattice that describes multiple hypotheses of a received input utterance into a modified word lattice wherein transitions without any input in the word lattice are represented as epsilon transitions in the modified word lattice, and at a spoken language understanding (SLU) engine: receiving the modified word lattice from the ASR engine; and performing an SLU determination via the SLU engine.
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17. A tangible computer-readable medium that stores a program for controlling a computer device to perform a speech processing method, the method comprising: at an automatic speech recognition (ASR) engine: converting a word lattice that describes multiple hypotheses of a received input utterance into a modified word lattice wherein transitions without any input in the word lattice are represented as epsilon transitions in the modified word lattice, and at a spoken language understanding (SLU) engine: receiving the modified word lattice from the ASR engine; and performing an SLU determination via the SLU engine. 18. The tangible computer-readable medium of claim 17 , wherein said performing comprises: calculating an intersection of the modified word lattice and a finite state machine including a plurality of salient grammar fragments; and determining a classification type for the input utterance based on the calculated intersection.
| 0.5 |
9,779,014 | 5 | 6 |
5. A unit test data processing system configured for fault alerting in mock object supported unit testing, the system comprising: a host computing system with at least one computer with at least one processor and memory; a plurality of objects of an application executing in the memory of the host computing system; and, at least one mock object proxying in the memory of the host computing system method calls to a corresponding one of the objects of the application, the mock object comprising program code enabled to proxy by method name an invocation of a method in the object under test, to determine whether or not a method exists in memory for the mock object corresponding to the method name, and to invoke an exception handler for the mock object outputting error text indicating a non-presence of a method associated with the method name responsive to a method by the method name not existing in the memory for the mock object, but otherwise to invoke a method that exists in the memory of the mock object corresponding to the method name; determining whether or not the method exists in memory for the mock object corresponding to the method name and a method signature.
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5. A unit test data processing system configured for fault alerting in mock object supported unit testing, the system comprising: a host computing system with at least one computer with at least one processor and memory; a plurality of objects of an application executing in the memory of the host computing system; and, at least one mock object proxying in the memory of the host computing system method calls to a corresponding one of the objects of the application, the mock object comprising program code enabled to proxy by method name an invocation of a method in the object under test, to determine whether or not a method exists in memory for the mock object corresponding to the method name, and to invoke an exception handler for the mock object outputting error text indicating a non-presence of a method associated with the method name responsive to a method by the method name not existing in the memory for the mock object, but otherwise to invoke a method that exists in the memory of the mock object corresponding to the method name; determining whether or not the method exists in memory for the mock object corresponding to the method name and a method signature. 6. The system of claim 5 , wherein the mock object has a constructor that is private in nature.
| 0.6875 |
7,965,923 | 24 | 25 |
24. The system of claim 19 wherein a VOB file maintained on the storage media item comprises caption content.
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24. The system of claim 19 wherein a VOB file maintained on the storage media item comprises caption content. 25. The system of claim 24 wherein captioning content comprises a description of non-dialogue audio content in a given VOB file.
| 0.5 |
9,165,206 | 12 | 13 |
12. The system of claim 11 , the operations further comprising: searching for a POI listing in a POI data repository containing information that matches the portion of the textual data; generating a new POI listing that includes the at least some of the textual data extracted from the image if no POI listing is found; and storing the new POI listing in the POI data repository.
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12. The system of claim 11 , the operations further comprising: searching for a POI listing in a POI data repository containing information that matches the portion of the textual data; generating a new POI listing that includes the at least some of the textual data extracted from the image if no POI listing is found; and storing the new POI listing in the POI data repository. 13. The system of claim 12 , wherein if an existing POI listing containing information that matches the portion of the textual data is found, the operations further comprise updating the existing POI listing to include the at least some of the textual data extracted from the image.
| 0.5 |
10,007,645 | 19 | 21 |
19. A system, comprising: a data processing device; and a non-transitory computer-readable storage medium encoded with instructions that when executed by the data processing device cause the data processing device to perform operations comprising: storing an activity history of a user using a client system, the activity history including at least one of click through rates, conversion rates, and bounce rates associated with presentation styles of content items and publications previously presented to the user on the client system; classifying, by the data processing device, the content items and publications previously presented to the user into categories through analysis of text within the content items and publications that were previously presented; selecting, from among the categories, a category of interest based on the stored activity history that includes the at least one of click through rates, conversion rates, and bounce rates associated with presentation styles of the content items and publications previously presented to the user on the client system; receiving a request for supplemental content to be presented with a publication requested by the user of the client system, wherein the supplemental content comprises a body of text having a plurality of terms, and wherein the publication includes one or more slots that reference the supplemental content; determining that one or more terms of the body of text having the plurality of terms comprise a specified type of term or a phrase; identifying that the one or more terms comprising the specified type of term or the phrase are associated with the category of interest selected from among the categories into which the content items and publications that are previously presented to the user and for which the at least one of click through rates, conversion rates, and bounce rates are stored in the activity history are classified; identifying a particular presentation style by determining a default presentation style for the determined one or more terms of the body of text having the plurality of terms; selecting the particular presentation style for the determined one or more terms that is different from the default presentation style; modifying the supplemental content referenced by the one or more slots to cause the one or more terms identified as being associated with the selected category of interest to appear in the identified particular presentation style such that the identified one or more terms differ in appearance from other terms of the plurality of terms in the supplemental content; and providing the requested publication with the one or more slots, wherein the one or more slots comprise the modified supplemental content.
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19. A system, comprising: a data processing device; and a non-transitory computer-readable storage medium encoded with instructions that when executed by the data processing device cause the data processing device to perform operations comprising: storing an activity history of a user using a client system, the activity history including at least one of click through rates, conversion rates, and bounce rates associated with presentation styles of content items and publications previously presented to the user on the client system; classifying, by the data processing device, the content items and publications previously presented to the user into categories through analysis of text within the content items and publications that were previously presented; selecting, from among the categories, a category of interest based on the stored activity history that includes the at least one of click through rates, conversion rates, and bounce rates associated with presentation styles of the content items and publications previously presented to the user on the client system; receiving a request for supplemental content to be presented with a publication requested by the user of the client system, wherein the supplemental content comprises a body of text having a plurality of terms, and wherein the publication includes one or more slots that reference the supplemental content; determining that one or more terms of the body of text having the plurality of terms comprise a specified type of term or a phrase; identifying that the one or more terms comprising the specified type of term or the phrase are associated with the category of interest selected from among the categories into which the content items and publications that are previously presented to the user and for which the at least one of click through rates, conversion rates, and bounce rates are stored in the activity history are classified; identifying a particular presentation style by determining a default presentation style for the determined one or more terms of the body of text having the plurality of terms; selecting the particular presentation style for the determined one or more terms that is different from the default presentation style; modifying the supplemental content referenced by the one or more slots to cause the one or more terms identified as being associated with the selected category of interest to appear in the identified particular presentation style such that the identified one or more terms differ in appearance from other terms of the plurality of terms in the supplemental content; and providing the requested publication with the one or more slots, wherein the one or more slots comprise the modified supplemental content. 21. The system of claim 19 , wherein the operations further comprise: identifying one or more additional terms of the plurality of terms based on one or more publications that were presented to the user previously and that are associated with the category of interest.
| 0.5 |
9,218,803 | 1 | 2 |
1. A method comprising: receiving, on a device having a processor, text from a user for conversion to speech via a text-to-speech process; identifying, via the processor, a primary speech segment in a primary speech database which does not meet a need of the text-to-speech process; identifying, via the processor, a replacement speech segment which satisfies the need in a secondary speech database; and adding replacement speech segment to the primary database such that the primary database meets the need of the text-to-speech process.
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1. A method comprising: receiving, on a device having a processor, text from a user for conversion to speech via a text-to-speech process; identifying, via the processor, a primary speech segment in a primary speech database which does not meet a need of the text-to-speech process; identifying, via the processor, a replacement speech segment which satisfies the need in a secondary speech database; and adding replacement speech segment to the primary database such that the primary database meets the need of the text-to-speech process. 2. The method of claim 1 , further comprising generating, via the processor, speech using the replacement speech segment from the primary speech database.
| 0.837895 |
9,977,661 | 6 | 8 |
6. A system for generating a user interface, comprising: memory; one or more processors; a script engine having the memory having stored therein a user interface element library comprising a plurality of user interface elements, and the one or more processors in communication with the memory that is configured to: read a user interface description file, analyze the user interface description file, generate user interface data, and transmit the user interface data to a main program; and a main program, wherein the main program is independent of the script engine, stored in the memory to be executed by the one or more processors that is configured to: acquire a user interface element corresponding to the user interface data, draw the user interface according to the user interface element that has been acquired, and the user interface data, detect a user interface adjustment event, transmit a control signal of adjusting the user interface to the script engine such that the script engine is configured to adjust the user interface data according to the control signal and transmit the user interface data that have been adjusted to the main program when the user interface adjustment event is detected, wherein the control signal comprises which user interface elements have been adjusted, acquire the user interface element corresponding to the user interface data that have been adjusted, from the script engine, and draw the user interface according to the user interface element that has been acquired.
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6. A system for generating a user interface, comprising: memory; one or more processors; a script engine having the memory having stored therein a user interface element library comprising a plurality of user interface elements, and the one or more processors in communication with the memory that is configured to: read a user interface description file, analyze the user interface description file, generate user interface data, and transmit the user interface data to a main program; and a main program, wherein the main program is independent of the script engine, stored in the memory to be executed by the one or more processors that is configured to: acquire a user interface element corresponding to the user interface data, draw the user interface according to the user interface element that has been acquired, and the user interface data, detect a user interface adjustment event, transmit a control signal of adjusting the user interface to the script engine such that the script engine is configured to adjust the user interface data according to the control signal and transmit the user interface data that have been adjusted to the main program when the user interface adjustment event is detected, wherein the control signal comprises which user interface elements have been adjusted, acquire the user interface element corresponding to the user interface data that have been adjusted, from the script engine, and draw the user interface according to the user interface element that has been acquired. 8. The system according to claim 6 , wherein the script engine further comprises: an user interface description analyzing module stored in the memory and to be executed by the one or more processors that is configured to: read and analyze the user interface description file to acquire an user interface element identification and combination relation information and style data of the user interface element wherein the combination relation information comprises an arrangement order of the user interface element a position of the user interface element in a hierarchical structure; a layout data generating module stored in the memory and to be executed by the one or more processors that is configured to: calculate position information of the user interface element according to the user interface element identification and the combination relation information to generate layout data wherein the layout data comprise the user interface element identification, the position information and the combination relation information; a user interface data transmitting module stored in the memory and to be executed by the one or more processors that is configured to: transmit the user interface data comprising the layout data and the style data to the main program; wherein the main program further comprises: a function trigger event detecting module stored in the memory and to be executed by the one or more processors that is configured to detect a function trigger event that is directed towards the user interface element; and a function realizing module stored in the memory and to be executed by the one or more processors that is configured to complete a function of the user interface element corresponding to the function trigger event and according to the function trigger event when the function trigger event is detected.
| 0.5 |
8,145,597 | 1 | 9 |
1. A system integrator for mapping dynamic COBOL constructs to object instances for automatic integration to object-oriented computing, the system comprising: a non-transitory computer-readable medium storing computer-executable code, the computer-executable code comprising: a client interface module for generating an interface for receiving a copybook selection, the client interface module adapted for communication to receive the copybook selection; an import module for importing a copybook from a database, the copybook corresponding with a set of COBOL data stored in the database that includes a dynamic COBOL construct, the import module adapted for communication to receive the copybook selection from the client interface module and to import the copybook from the database; an object model module for creating an object model for the copybook, the object model module adapted for communication to receive the copybook from the import module and store the object model in a model library; and a modeler module for receiving the set of COBOL data and forming, based at least in part on the received set of COBOL data, a first object instance that is equivalent to the set of COBOL data, the first object instance including one or more representations for a complete set of one or more properties included in the dynamic COBOL construct without requiring custom coding for the forming of the first object instance, the modeler module adapted for communication to receive the set of COBOL data from the database and to retrieve the object model from the model library; and wherein the modeler module includes an OCCURS DEPENDING ON module for identifying an instance of an OCCURS DEPENDING ON clause and automatically forming the OCCURS DEPENDING ON clause as the first object instance, the OCCURS DEPENDING ON module adapted to read the set of COBOL data; and wherein the OCCURS DEPENDING ON module identifies a controlling numeric value for the OCCURS DEPENDING ON clause and recursively rereads an OCCURS DEPENDING ON subset, and wherein the automatically forming forms each reread portion of the OCCURS DEPENDING ON subset as a portion of the first object instance.
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1. A system integrator for mapping dynamic COBOL constructs to object instances for automatic integration to object-oriented computing, the system comprising: a non-transitory computer-readable medium storing computer-executable code, the computer-executable code comprising: a client interface module for generating an interface for receiving a copybook selection, the client interface module adapted for communication to receive the copybook selection; an import module for importing a copybook from a database, the copybook corresponding with a set of COBOL data stored in the database that includes a dynamic COBOL construct, the import module adapted for communication to receive the copybook selection from the client interface module and to import the copybook from the database; an object model module for creating an object model for the copybook, the object model module adapted for communication to receive the copybook from the import module and store the object model in a model library; and a modeler module for receiving the set of COBOL data and forming, based at least in part on the received set of COBOL data, a first object instance that is equivalent to the set of COBOL data, the first object instance including one or more representations for a complete set of one or more properties included in the dynamic COBOL construct without requiring custom coding for the forming of the first object instance, the modeler module adapted for communication to receive the set of COBOL data from the database and to retrieve the object model from the model library; and wherein the modeler module includes an OCCURS DEPENDING ON module for identifying an instance of an OCCURS DEPENDING ON clause and automatically forming the OCCURS DEPENDING ON clause as the first object instance, the OCCURS DEPENDING ON module adapted to read the set of COBOL data; and wherein the OCCURS DEPENDING ON module identifies a controlling numeric value for the OCCURS DEPENDING ON clause and recursively rereads an OCCURS DEPENDING ON subset, and wherein the automatically forming forms each reread portion of the OCCURS DEPENDING ON subset as a portion of the first object instance. 9. The system integrator of claim 1 , wherein the set of COBOL data is a COBOL data file.
| 0.866766 |
9,306,941 | 7 | 10 |
7. A computer-implemented method for allowing a plurality of user devices to connect to share, view, edit, mark, and save documents over a local network, the method comprising: creating, via a router, the local network between the plurality of user devices, the plurality of user devices comprising a leader device and one or more participant devices approved by the leader device to join the local network; connecting to the router a document storage device containing thereon one or more documents; authenticating, by the router, the leader device; providing, by the router and the document storage device, access to the one or more documents contained on the document storage device when an application installed on the plurality of user devices is run, the application configured to provide a leader graphical user interface (GUI) on the leader device for allowing leader manipulation of at least one of the one or more documents and sharing with the participant devices of at least one of the one or more documents, and a participant GUI on the one or more participant devices for allowing participant manipulation of at least one of the shared documents; wherein the participant GUI is based upon one or more predefined participant types, each participant type provided with a specified functionality in a corresponding participant GUI; wherein a first predefined participant type comprises a court reporter, wherein a corresponding court reporter GUI comprises one or more windows for customizing exhibit stickers, saving exhibit stickers, marking and saving one or more of the at least one of the shared documents, and sharing one or more of the at least one of the shared documents; and wherein a second predefined participant type comprises a guest user, wherein a corresponding guest user GUI comprises one or more windows for selecting, editing, saving, sharing, downloading, and viewing one or more of the at least one of the shared documents.
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7. A computer-implemented method for allowing a plurality of user devices to connect to share, view, edit, mark, and save documents over a local network, the method comprising: creating, via a router, the local network between the plurality of user devices, the plurality of user devices comprising a leader device and one or more participant devices approved by the leader device to join the local network; connecting to the router a document storage device containing thereon one or more documents; authenticating, by the router, the leader device; providing, by the router and the document storage device, access to the one or more documents contained on the document storage device when an application installed on the plurality of user devices is run, the application configured to provide a leader graphical user interface (GUI) on the leader device for allowing leader manipulation of at least one of the one or more documents and sharing with the participant devices of at least one of the one or more documents, and a participant GUI on the one or more participant devices for allowing participant manipulation of at least one of the shared documents; wherein the participant GUI is based upon one or more predefined participant types, each participant type provided with a specified functionality in a corresponding participant GUI; wherein a first predefined participant type comprises a court reporter, wherein a corresponding court reporter GUI comprises one or more windows for customizing exhibit stickers, saving exhibit stickers, marking and saving one or more of the at least one of the shared documents, and sharing one or more of the at least one of the shared documents; and wherein a second predefined participant type comprises a guest user, wherein a corresponding guest user GUI comprises one or more windows for selecting, editing, saving, sharing, downloading, and viewing one or more of the at least one of the shared documents. 10. The method of claim 7 , wherein leader manipulation of at least one of the one or more documents comprises one or more of selecting, editing, annotating, saving, downloading, and viewing the at least one of the one or more documents.
| 0.5 |
9,582,301 | 13 | 15 |
13. The method of claim 8 , wherein the control logic includes at least one access control list (ACL) rule to ensure that a particular data tuple satisfies a set of access control criteria.
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13. The method of claim 8 , wherein the control logic includes at least one access control list (ACL) rule to ensure that a particular data tuple satisfies a set of access control criteria. 15. The method of claim 13 , wherein different types of access controls that are specified by different key-value pairs include two or more of the following: type of access, type of permissions granted, type of user, required type of identifier for the user, and the JS object attribute to which the access control applies.
| 0.5 |
7,805,464 | 1 | 4 |
1. A computer-implemented method for building a web address, comprising: presenting a setup dialog in a single window on a display device, the setup dialog having a website listing area, a parameter edit area, and a web address edit area; displaying in the website listing area a list of websites, each of the websites having a corresponding website Uniform Resource Locator (URL) template for building a web address expression for a web address for the website within the setup dialog; receiving a first input through the setup dialog in the website listing area, the first input specifying a website from the list of websites; automatically determining a list of parameters of the web address for the website based on the corresponding website URL template of the website; presenting the list of parameters in the setup dialog in the parameter edit area; for each parameter presented in the parameter edit area, generating a corresponding parameter edit input for the parameter; receiving a second input through the setup dialog in a parameter edit input for a first parameter, the second input specifying a value for the first parameter; and building the web address expression dynamically in the web address edit area, the web address expression including the first parameter set to the specified value.
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1. A computer-implemented method for building a web address, comprising: presenting a setup dialog in a single window on a display device, the setup dialog having a website listing area, a parameter edit area, and a web address edit area; displaying in the website listing area a list of websites, each of the websites having a corresponding website Uniform Resource Locator (URL) template for building a web address expression for a web address for the website within the setup dialog; receiving a first input through the setup dialog in the website listing area, the first input specifying a website from the list of websites; automatically determining a list of parameters of the web address for the website based on the corresponding website URL template of the website; presenting the list of parameters in the setup dialog in the parameter edit area; for each parameter presented in the parameter edit area, generating a corresponding parameter edit input for the parameter; receiving a second input through the setup dialog in a parameter edit input for a first parameter, the second input specifying a value for the first parameter; and building the web address expression dynamically in the web address edit area, the web address expression including the first parameter set to the specified value. 4. The method of claim 1 , further comprising: presenting information in the setup dialog indicating if the parameter is required or optional for the web address that is generated from the web address expression.
| 0.792157 |
10,140,285 | 9 | 14 |
9. A system comprising: a memory; and a controller configured to: display a graphical user interface to a user, the graphical user interface comprising: an input area for the user to input a base category and one or more phrases, for analysis of the base category, and an input area for the user to input a phrase for analysis; obtain via user input the base category; generate a base trend for the base category based on a frequency of appearance of at least one of the one or more phrases in a set of recorded interactions that are specific to a call center, the base trend comprising a series of numbers of interactions per time unit for each of a series of time units, each recorded interaction comprising a text recording of a conversational exchange, wherein at least some of the text recordings are produced via a speech to text process applied to an audio recording; obtain via user input a candidate phrase; generate an accuracy value for the candidate phrase by determining a correlation between: a first candidate trend determined based on the frequency of appearance of the candidate phrase in the set of recorded interactions determined using a first accuracy value; and a second candidate trend determined based on the frequency of appearance of the candidate phrase in the set of recorded interactions determined using a second accuracy value; generate a candidate trend for the candidate phrase based on a frequency of appearance of the candidate phrase in the set of recorded interactions determined using the generated accuracy value, each of the candidate trend, the first candidate trend, and the second candidate trend comprising a series of numbers of interactions per time unit for each of a series of time units; determine a correlation level by relating the candidate trend to the base trend; if the correlation level is greater than a threshold level then include the candidate phrase in the base category; and displaying to the user the candidate phrase.
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9. A system comprising: a memory; and a controller configured to: display a graphical user interface to a user, the graphical user interface comprising: an input area for the user to input a base category and one or more phrases, for analysis of the base category, and an input area for the user to input a phrase for analysis; obtain via user input the base category; generate a base trend for the base category based on a frequency of appearance of at least one of the one or more phrases in a set of recorded interactions that are specific to a call center, the base trend comprising a series of numbers of interactions per time unit for each of a series of time units, each recorded interaction comprising a text recording of a conversational exchange, wherein at least some of the text recordings are produced via a speech to text process applied to an audio recording; obtain via user input a candidate phrase; generate an accuracy value for the candidate phrase by determining a correlation between: a first candidate trend determined based on the frequency of appearance of the candidate phrase in the set of recorded interactions determined using a first accuracy value; and a second candidate trend determined based on the frequency of appearance of the candidate phrase in the set of recorded interactions determined using a second accuracy value; generate a candidate trend for the candidate phrase based on a frequency of appearance of the candidate phrase in the set of recorded interactions determined using the generated accuracy value, each of the candidate trend, the first candidate trend, and the second candidate trend comprising a series of numbers of interactions per time unit for each of a series of time units; determine a correlation level by relating the candidate trend to the base trend; if the correlation level is greater than a threshold level then include the candidate phrase in the base category; and displaying to the user the candidate phrase. 14. The system of claim 9 , wherein recorded interactions include at least one of: a voice recording, a video recording and a recording of text of a textual interaction.
| 0.905902 |
9,183,321 | 9 | 14 |
9. A computer-implemented method, comprising steps of: within a repository, storing: a first compound document that includes a first parent document that links to a first plurality of subdocuments that includes a first subdocument that corresponds to a first plurality of versions, a second compound document that includes a second parent document that links to a second plurality of subdocuments that includes a second subdocument that corresponds to a second plurality of versions, a first compound declaration in association with the first compound document, and a second compound declaration in association with the second compound document; while performing one or more operations to replace, in the first compound document, (a) links to the first plurality of subdocuments with (b) content of the first plurality of subdocuments, using said first compound declaration to return the most current version of the first plurality of versions of the first subdocument; while performing the one or more operations to replace, in the second compound document, (c) links to the second plurality of subdocuments with (d) content of the second plurality of subdocuments, using said second compound declaration to return a particular version, of the second plurality of versions, that is not the most current version of the second plurality of versions; in response to a request to check out a particular version of the first plurality of versions of the first subdocument for reading or modifying, checking out the particular version of the first subdocument without checking out any other subdocument of the first plurality of subdocuments and without checking out the first parent document.
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9. A computer-implemented method, comprising steps of: within a repository, storing: a first compound document that includes a first parent document that links to a first plurality of subdocuments that includes a first subdocument that corresponds to a first plurality of versions, a second compound document that includes a second parent document that links to a second plurality of subdocuments that includes a second subdocument that corresponds to a second plurality of versions, a first compound declaration in association with the first compound document, and a second compound declaration in association with the second compound document; while performing one or more operations to replace, in the first compound document, (a) links to the first plurality of subdocuments with (b) content of the first plurality of subdocuments, using said first compound declaration to return the most current version of the first plurality of versions of the first subdocument; while performing the one or more operations to replace, in the second compound document, (c) links to the second plurality of subdocuments with (d) content of the second plurality of subdocuments, using said second compound declaration to return a particular version, of the second plurality of versions, that is not the most current version of the second plurality of versions; in response to a request to check out a particular version of the first plurality of versions of the first subdocument for reading or modifying, checking out the particular version of the first subdocument without checking out any other subdocument of the first plurality of subdocuments and without checking out the first parent document. 14. The method of claim 9 , further comprising: creating a new version of the first parent document; and in response to a request to check out the new version of the first parent document for reading or modifying, checking out the new version of the first parent document without checking out any subdocument of the first plurality of subdocuments.
| 0.655446 |
9,336,300 | 1 | 2 |
1. A method comprising, by one or more processors associated with a mobile client system: receiving, at the mobile client system, an unstructured text query from a first user of an online social network; parsing, by the mobile client system, the unstructured text query into one or more n-grams; accessing, from a data store of the mobile client system, a set of nodes of a social graph of the online social network, the social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, the nodes comprising: a first node corresponding to the first user; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; accessing, from the data store of the mobile client system, a set of grammar templates, each grammar template comprising one or more non-terminal tokens and one or more query tokens, wherein the query tokens comprise references to zero or more second nodes and one or more edges, and wherein each grammar template is based on a natural-language string; generating, by the mobile client system, one or more structured queries by matching the unstructured text query to one or more of the accessed nodes and one or more of the grammar templates having non-terminal tokens corresponding to the matched nodes, each structured query comprising references to one or more of the accessed nodes matched to the one or more non-terminal tokens and the zero or more of the second nodes and the one or more edges referenced in the corresponding grammar template; calculating, by the mobile client system, a cost for each grammar template based at least in part on one or more of the n-grams not corresponding to one of the non-terminal tokens or query tokens; and displaying, at the mobile client system, one or more structured queries to the first user; wherein each non-terminal token and query token has an associated insertion cost; and wherein calculating the cost comprises incurring an insertion cost for each of the non-terminal tokens or query tokens not corresponding to one or more n-grams.
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1. A method comprising, by one or more processors associated with a mobile client system: receiving, at the mobile client system, an unstructured text query from a first user of an online social network; parsing, by the mobile client system, the unstructured text query into one or more n-grams; accessing, from a data store of the mobile client system, a set of nodes of a social graph of the online social network, the social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, the nodes comprising: a first node corresponding to the first user; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; accessing, from the data store of the mobile client system, a set of grammar templates, each grammar template comprising one or more non-terminal tokens and one or more query tokens, wherein the query tokens comprise references to zero or more second nodes and one or more edges, and wherein each grammar template is based on a natural-language string; generating, by the mobile client system, one or more structured queries by matching the unstructured text query to one or more of the accessed nodes and one or more of the grammar templates having non-terminal tokens corresponding to the matched nodes, each structured query comprising references to one or more of the accessed nodes matched to the one or more non-terminal tokens and the zero or more of the second nodes and the one or more edges referenced in the corresponding grammar template; calculating, by the mobile client system, a cost for each grammar template based at least in part on one or more of the n-grams not corresponding to one of the non-terminal tokens or query tokens; and displaying, at the mobile client system, one or more structured queries to the first user; wherein each non-terminal token and query token has an associated insertion cost; and wherein calculating the cost comprises incurring an insertion cost for each of the non-terminal tokens or query tokens not corresponding to one or more n-grams. 2. The method of claim 1 , wherein the calculating the cost comprises identifying, by the mobile client system, a particular non-terminal token from one or more of the non-terminal tokens that correspond to a particular n-gram based at least in part on the insertion cost of each non-terminal token.
| 0.566667 |
9,354,629 | 1 | 4 |
1. A method comprising: loading an interpretable system-level vendor-independent first script defining a physical topology and control of a process control system including multiple process controllers and process control devices, the first script including tokens that have a type and value to define attributes of the multiple process controllers and process control devices, the topology representing physical communicative couplings between the multiple process controllers and the process control devices; and compiling the first script to form a second script with vendor-specific configuration language by identifying one or more lexemes contained in the first script, identifying the tokens contained in the first script based on the identified one or more lexemes, identifying one or more first expressions based on grammatical relationships between the identified tokens, identifying vendor-specific information associated with the process control system from a device database associated with the process control system, and forming the second script based on the identified one or more first expressions and the identified vendor-specific information, to configure the multiple process controllers and process control devices for control.
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1. A method comprising: loading an interpretable system-level vendor-independent first script defining a physical topology and control of a process control system including multiple process controllers and process control devices, the first script including tokens that have a type and value to define attributes of the multiple process controllers and process control devices, the topology representing physical communicative couplings between the multiple process controllers and the process control devices; and compiling the first script to form a second script with vendor-specific configuration language by identifying one or more lexemes contained in the first script, identifying the tokens contained in the first script based on the identified one or more lexemes, identifying one or more first expressions based on grammatical relationships between the identified tokens, identifying vendor-specific information associated with the process control system from a device database associated with the process control system, and forming the second script based on the identified one or more first expressions and the identified vendor-specific information, to configure the multiple process controllers and process control devices for control. 4. The method as defined in claim 1 , further comprising importing the second script into a process control system configuration database associated with the process control system.
| 0.776543 |
9,911,409 | 1 | 2 |
1. A speech recognition apparatus comprising: a processor configured: to recognize a user's speech using any one or any combination of any two or more of a pronunciation dictionary comprising primitive words, and a language model comprising primitive words, the primitive words being formed of deconstructed compound words; and to correct word spacing in a result of speech recognition based on a word-spacing model, wherein spaces interposed between primitive words of deconstructed compound words are adaptively removed from the result of speech recognition to reconstitute the compound words.
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1. A speech recognition apparatus comprising: a processor configured: to recognize a user's speech using any one or any combination of any two or more of a pronunciation dictionary comprising primitive words, and a language model comprising primitive words, the primitive words being formed of deconstructed compound words; and to correct word spacing in a result of speech recognition based on a word-spacing model, wherein spaces interposed between primitive words of deconstructed compound words are adaptively removed from the result of speech recognition to reconstitute the compound words. 2. The speech recognition apparatus of claim 1 , wherein either one or both of the pronunciation dictionary and the language model are configured to comprise the primitive words according to any one or any combination of any two or more of the following criteria: words whose frequency of use is determined to be greater than a specific threshold; morpheme-level words; and syllable-level words.
| 0.624525 |
8,793,264 | 1 | 3 |
1. A method of determining a subset of documents from which a particular document was derived, the method comprising: receiving similarity measurements indicating similarities between contents of documents; and determining the subset of the documents that the particular document was derived from based on dates the documents were created and the similarity measurements without requiring document tracking information to be associated with the documents to determine the subset.
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1. A method of determining a subset of documents from which a particular document was derived, the method comprising: receiving similarity measurements indicating similarities between contents of documents; and determining the subset of the documents that the particular document was derived from based on dates the documents were created and the similarity measurements without requiring document tracking information to be associated with the documents to determine the subset. 3. The method as recited by claim 1 , wherein the determining of the subset of the documents further comprises: creating a forward-in-time graph based on the similarity measurements and the dates the documents were created.
| 0.5 |
10,072,941 | 1 | 6 |
1. A computer implemented method comprising: receiving, by a processor, at least a portion of a conversational narrative comprising at least one non-verbal physical movement of a portion of a human body of a provider and descriptive of a route to a destination expressed by the provider and directed thereby to a receiver not connected to the processor, the expressed conversational narrative comprising a plurality of conversational elements, wherein the plurality of conversational elements includes a plurality of navigation oriented conversational elements and at least one descriptive element characterizing at least one other of the plurality of conversational elements; identifying, by the processor, the plurality of navigation oriented conversational elements of the plurality of conversational elements as well as any of the at least one descriptive elements characterizing thereof; converting, by the processor, each of the plurality of navigation oriented conversational elements into an associated navigation data element representative thereof based on the identified descriptive elements; compiling, by the processor, the navigation data elements into a navigation route; and presenting, by the processor, at least a portion of the navigation route.
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1. A computer implemented method comprising: receiving, by a processor, at least a portion of a conversational narrative comprising at least one non-verbal physical movement of a portion of a human body of a provider and descriptive of a route to a destination expressed by the provider and directed thereby to a receiver not connected to the processor, the expressed conversational narrative comprising a plurality of conversational elements, wherein the plurality of conversational elements includes a plurality of navigation oriented conversational elements and at least one descriptive element characterizing at least one other of the plurality of conversational elements; identifying, by the processor, the plurality of navigation oriented conversational elements of the plurality of conversational elements as well as any of the at least one descriptive elements characterizing thereof; converting, by the processor, each of the plurality of navigation oriented conversational elements into an associated navigation data element representative thereof based on the identified descriptive elements; compiling, by the processor, the navigation data elements into a navigation route; and presenting, by the processor, at least a portion of the navigation route. 6. The computer implemented method of claim 1 further comprising receiving, by the processor, the at least one non-verbal physical movement of a portion of a human body of the conversational narrative via an optical sensor, a motion sensor, a touch sensor, a proximity sensor, or a combination thereof, coupled therewith and converting, by the processor, the received conversational narrative to data representative thereof.
| 0.5 |
10,108,712 | 1 | 4 |
1. A system comprising: a query rewrite input language (QRIL) processor device comprising: an input/output (I/O) module configured to receive one or more QRIL records, each QRIL record comprising a trigger value, a rewrite value, and one or more metaflag elements comprising a query rewrite type metaflag that identifies each QRIL record as associated with a query rewrite type; a query rewrite resolver module configured to identify a first query rewrite type for a first QRIL record of the one or more QRIL records and process the first QRIL record to identify a set of precedence issues between the first QRIL record and at least one overlapping or conflicting QRIL record; and a search engine query rewrite customization module configured to identify a first search engine and a first query rewrite semantic structure associated with the first search engine and to generate a first standardized query rewrite from the first QRIL record, the set of precedence issues, and the first query rewrite semantic structure, wherein the first standardized query rewrite comprises a standardized trigger value and a standardized rewrite expression for rewriting an input query for the first search engine, and a bag of words dictionary; wherein the QRIL processor device is configured to provide the first standardized query write to facilitate executing a user query using the first standardized query write.
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1. A system comprising: a query rewrite input language (QRIL) processor device comprising: an input/output (I/O) module configured to receive one or more QRIL records, each QRIL record comprising a trigger value, a rewrite value, and one or more metaflag elements comprising a query rewrite type metaflag that identifies each QRIL record as associated with a query rewrite type; a query rewrite resolver module configured to identify a first query rewrite type for a first QRIL record of the one or more QRIL records and process the first QRIL record to identify a set of precedence issues between the first QRIL record and at least one overlapping or conflicting QRIL record; and a search engine query rewrite customization module configured to identify a first search engine and a first query rewrite semantic structure associated with the first search engine and to generate a first standardized query rewrite from the first QRIL record, the set of precedence issues, and the first query rewrite semantic structure, wherein the first standardized query rewrite comprises a standardized trigger value and a standardized rewrite expression for rewriting an input query for the first search engine, and a bag of words dictionary; wherein the QRIL processor device is configured to provide the first standardized query write to facilitate executing a user query using the first standardized query write. 4. The system of claim 1 wherein the QRIL processor device further comprises a bag of words generator module comprising a bag of words model configured to analyze tokens of the first QRIL record to identify dictionary values associated with the first QRIL record; and wherein the first standardized query rewrite is generated using the dictionary values associated with the first QRIL record.
| 0.720399 |
9,454,615 | 1 | 4 |
1. A method for predicting user behaviors based on term taxonomies, comprising: generating phrases respective of user generated content, wherein each phrase is a sentiment phrase or a non-sentiment phrase, each sentiment phrase including at least one word describing a sentiment; identifying at least one connection between at least two of the generated phrases, wherein each connection is a direct connection or a hidden connection; generating at least one term taxonomy based on the identified at least one connection, wherein each term taxonomy is an association between a non-sentiment phrase and at least one of a plurality of sentiment phrases; periodically analyzing the at least one term taxonomy to determine at least one trend of each non-sentiment phrase respective of the associated plurality of sentiment phrases; and generating a prediction of future behavior of the at least one trend with respect to the at least one term taxonomy.
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1. A method for predicting user behaviors based on term taxonomies, comprising: generating phrases respective of user generated content, wherein each phrase is a sentiment phrase or a non-sentiment phrase, each sentiment phrase including at least one word describing a sentiment; identifying at least one connection between at least two of the generated phrases, wherein each connection is a direct connection or a hidden connection; generating at least one term taxonomy based on the identified at least one connection, wherein each term taxonomy is an association between a non-sentiment phrase and at least one of a plurality of sentiment phrases; periodically analyzing the at least one term taxonomy to determine at least one trend of each non-sentiment phrase respective of the associated plurality of sentiment phrases; and generating a prediction of future behavior of the at least one trend with respect to the at least one term taxonomy. 4. The method of claim 1 , further comprising: determining a context of the generated phrases.
| 0.858859 |
10,108,698 | 1 | 4 |
1. An information processing system comprising: a memory area storing computer-executable instructions for generating a common data repository including a plurality of documents that include transcripts from customer service calls; and a processor configured to execute the computer-executable instructions to: identify a plurality of topics including customer service issues by analyzing the plurality of documents; based on the plurality of identified topics, classify the plurality of documents into a plurality of sets, a first set of the plurality of sets associated with a first topic of the plurality of topics; identify via inter-set comparisons, one or more correlations between a first document classified into the first set and another document of the plurality of documents classified into a second set of the plurality of sets, the second set being associated with a second topic of the plurality of topics; based on the one or more identified correlations, generate a taxonomy tree; convert at least the first topic and the second topic of the plurality of topics into a structured knowledge article having a predetermined format of patterns based on the generated taxonomy tree; and generate one or more tools including an interaction script associated with at least the first topic of the plurality of topics based on identification of one or more of the patterns from at least the first document and the other document to improve a transactional efficiency of a user interaction.
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1. An information processing system comprising: a memory area storing computer-executable instructions for generating a common data repository including a plurality of documents that include transcripts from customer service calls; and a processor configured to execute the computer-executable instructions to: identify a plurality of topics including customer service issues by analyzing the plurality of documents; based on the plurality of identified topics, classify the plurality of documents into a plurality of sets, a first set of the plurality of sets associated with a first topic of the plurality of topics; identify via inter-set comparisons, one or more correlations between a first document classified into the first set and another document of the plurality of documents classified into a second set of the plurality of sets, the second set being associated with a second topic of the plurality of topics; based on the one or more identified correlations, generate a taxonomy tree; convert at least the first topic and the second topic of the plurality of topics into a structured knowledge article having a predetermined format of patterns based on the generated taxonomy tree; and generate one or more tools including an interaction script associated with at least the first topic of the plurality of topics based on identification of one or more of the patterns from at least the first document and the other document to improve a transactional efficiency of a user interaction. 4. The information processing system of claim 1 , wherein the processor is configured to execute the computer-executable instructions to extract one or more snippets from one or more documents of the plurality of documents.
| 0.746014 |
8,781,829 | 29 | 30 |
29. The computer readable medium of claim 28 , wherein (C) comprises: (C)(1) prompting a human user to provide the content; (C)(2) receiving input from the human user representing the content; and (C)(3) inserting the content into the structured document.
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29. The computer readable medium of claim 28 , wherein (C) comprises: (C)(1) prompting a human user to provide the content; (C)(2) receiving input from the human user representing the content; and (C)(3) inserting the content into the structured document. 30. The computer readable medium of claim 29 : wherein (C)(1) comprises displaying a structured input element; and wherein (C)(2) comprises receiving input from the human user in the structured input element.
| 0.5 |
8,812,604 | 14 | 17 |
14. A computer-implemented method, comprising evaluating, at a first computer system, an information source according to information retrieved by the first computer system from a search over social network defined by relationships between members of the social network, and filtering messages associated with said information source according to an evaluation of relationships of the members.
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14. A computer-implemented method, comprising evaluating, at a first computer system, an information source according to information retrieved by the first computer system from a search over social network defined by relationships between members of the social network, and filtering messages associated with said information source according to an evaluation of relationships of the members. 17. The method of claim 14 , wherein said filtering includes ranking said messages according to criteria defined by an intended recipient of said messages.
| 0.682377 |
7,865,363 | 2 | 4 |
2. The computer-implemented method of claim 1 wherein outputting comprises displaying text corresponding to the desired character on a user-interface of the computing device.
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2. The computer-implemented method of claim 1 wherein outputting comprises displaying text corresponding to the desired character on a user-interface of the computing device. 4. The computer-implemented method of claim 2 further comprising displaying several desired characters to form a string, wherein a portion of the string comprises at least one word.
| 0.5 |
9,230,220 | 1 | 2 |
1. A system configured to generate a situation-dependent library, comprising: at least one processor and at least one memory, the at least one processor and the at least one memory cooperating to function as: a machine learning trainer configured to receive samples comprising temporal windows of token instances to which a user was exposed and situation identifiers corresponding to situations the user was in while being exposed to the temporal windows; wherein the token instances have overlapping instantiation periods and are spread over a period of time that spans at least a day, and the situation identifiers comprise situation identifiers for first and second situations; the machine learning trainer is further configured to receive target values corresponding to the temporal windows of token instances; the target values represent affective responses of the user to the token instances from the temporal windows of token instances; the machine learning trainer is further configured to train first and second situation-dependent machine learning-based user response models based on respective first and second datasets; wherein the first and second datasets are obtained from partitioning the samples according to the situations the user was in when exposed to the temporal windows of token instances corresponding to the samples; and wherein the first dataset comprises samples comprising situation identifiers for the first situation and corresponding target values, and the second dataset comprises samples comprising situation identifiers for the second situation and corresponding target values; and a model analyzer configured to generate, based on the first and second situation-dependent machine learning-based user response models, the situation-dependent library which describes a first set of expected affective responses of the user to certain tokens while being in the first situation, and a second set of expected affective responses of the user to the certain tokens while being in the second situation; wherein the first set is not identical to the second set, and wherein at least some of the token instances from the temporal windows of token instances are instantiations of the certain tokens.
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1. A system configured to generate a situation-dependent library, comprising: at least one processor and at least one memory, the at least one processor and the at least one memory cooperating to function as: a machine learning trainer configured to receive samples comprising temporal windows of token instances to which a user was exposed and situation identifiers corresponding to situations the user was in while being exposed to the temporal windows; wherein the token instances have overlapping instantiation periods and are spread over a period of time that spans at least a day, and the situation identifiers comprise situation identifiers for first and second situations; the machine learning trainer is further configured to receive target values corresponding to the temporal windows of token instances; the target values represent affective responses of the user to the token instances from the temporal windows of token instances; the machine learning trainer is further configured to train first and second situation-dependent machine learning-based user response models based on respective first and second datasets; wherein the first and second datasets are obtained from partitioning the samples according to the situations the user was in when exposed to the temporal windows of token instances corresponding to the samples; and wherein the first dataset comprises samples comprising situation identifiers for the first situation and corresponding target values, and the second dataset comprises samples comprising situation identifiers for the second situation and corresponding target values; and a model analyzer configured to generate, based on the first and second situation-dependent machine learning-based user response models, the situation-dependent library which describes a first set of expected affective responses of the user to certain tokens while being in the first situation, and a second set of expected affective responses of the user to the certain tokens while being in the second situation; wherein the first set is not identical to the second set, and wherein at least some of the token instances from the temporal windows of token instances are instantiations of the certain tokens. 2. The system of claim 1 , wherein the target values are emotional response annotations, and the situation-dependent library is a situation-dependent library comprising expected emotional responses of the user to the tokens.
| 0.804878 |
9,213,684 | 1 | 6 |
1. A method for rendering a document, the method comprising: converting a plurality of resources in a document file into a plurality of files that are native to a browser; creating a style sheet based on the document file, wherein an aggregate of the plurality of files together with the style sheet are configured to cause the browser to render an appearance of the document file; and generating, based on the document file, an invisible layer to be laid on the appearance, wherein the invisible layer enables actions to be performed on the document file.
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1. A method for rendering a document, the method comprising: converting a plurality of resources in a document file into a plurality of files that are native to a browser; creating a style sheet based on the document file, wherein an aggregate of the plurality of files together with the style sheet are configured to cause the browser to render an appearance of the document file; and generating, based on the document file, an invisible layer to be laid on the appearance, wherein the invisible layer enables actions to be performed on the document file. 6. The method of claim 1 , wherein the plurality of resources comprise text, the method further comprising: mapping the text using to a plurality of equivalent scalable vector graphic operations; and providing the text for the generation of the invisible layer.
| 0.61276 |
8,876,611 | 8 | 11 |
8. A method of operating an online game, comprising: providing a game client and a game server; in the game client: selecting a game to be played; selecting a character for the game; selecting a virtual era for the game; selecting a virtual environment for the game; selecting virtual scenes-a-faire for the era; in the game server: selecting at least one motif for the character; selecting at least one motif for the virtual environment; selecting at least one motif for the virtual scenes-a-faire; initializing an instantiation of the game in the game server in communication with the game client, the character and the corresponding at least one interactive motif thereof, the virtual era, the virtual environment and the corresponding at least one motif thereof, and the scenes-a-faire and the corresponding at least one motif thereof; and playing the selected game thereof in the game client, wherein the selected game interacts with a database to create persistence of the virtual environment and a game server to manage communication from the database, and wherein the selected game is a massively multiplayer role-playing online game.
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8. A method of operating an online game, comprising: providing a game client and a game server; in the game client: selecting a game to be played; selecting a character for the game; selecting a virtual era for the game; selecting a virtual environment for the game; selecting virtual scenes-a-faire for the era; in the game server: selecting at least one motif for the character; selecting at least one motif for the virtual environment; selecting at least one motif for the virtual scenes-a-faire; initializing an instantiation of the game in the game server in communication with the game client, the character and the corresponding at least one interactive motif thereof, the virtual era, the virtual environment and the corresponding at least one motif thereof, and the scenes-a-faire and the corresponding at least one motif thereof; and playing the selected game thereof in the game client, wherein the selected game interacts with a database to create persistence of the virtual environment and a game server to manage communication from the database, and wherein the selected game is a massively multiplayer role-playing online game. 11. The method of claim 8 further comprising: coupling a game server to the game client such that the instantiation joins a virtual world hosted on the game server; and coupling a database having data pertaining to the state of the virtual world to the game server and to the game client.
| 0.5 |
9,959,356 | 8 | 13 |
8. A non-transitory, computer accessible memory medium storing program instructions for modifying a search engine, wherein the program instructions are executable by one or more processors to: create a search engine for a website, wherein said creating the search engine comprises creating search information for a plurality of webpages of the website, wherein the search information specifies a first set of information for each webpage; provide a search-customization user interface for modifying a ranking function of the search engine for the website, wherein the search-customization user interface specifies one or more first ranking factors; after the user inserts one or more first custom tags into source code of at least one webpage of the website, update the search information to include information related to the one or more custom tags, wherein the one or more custom tags are dedicated for customizing the search engine of the web site; provide the search-customization user interface for modifying the ranking function of the search engine for the web site, wherein, in addition to the one or more first ranking factors, the search-customization user interface specifies one or more additional ranking factors corresponding to the one or more first custom tags, wherein each additional ranking factor is added to the search-customization user interface for a respective first custom tag inserted into the source code; receive first user input from the user, wherein the first user input specifies modifying a relative weight of a first additional ranking factor of the one or more additional ranking factors; automatically modify the ranking function of the search engine to use the relative weight of the first additional ranking factor based on the first user input; after automatically modifying the ranking function of the search engine to use the relative weight of the first additional ranking factor, receive a search query for the website; and provide a plurality of search results using the ranking function.
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8. A non-transitory, computer accessible memory medium storing program instructions for modifying a search engine, wherein the program instructions are executable by one or more processors to: create a search engine for a website, wherein said creating the search engine comprises creating search information for a plurality of webpages of the website, wherein the search information specifies a first set of information for each webpage; provide a search-customization user interface for modifying a ranking function of the search engine for the website, wherein the search-customization user interface specifies one or more first ranking factors; after the user inserts one or more first custom tags into source code of at least one webpage of the website, update the search information to include information related to the one or more custom tags, wherein the one or more custom tags are dedicated for customizing the search engine of the web site; provide the search-customization user interface for modifying the ranking function of the search engine for the web site, wherein, in addition to the one or more first ranking factors, the search-customization user interface specifies one or more additional ranking factors corresponding to the one or more first custom tags, wherein each additional ranking factor is added to the search-customization user interface for a respective first custom tag inserted into the source code; receive first user input from the user, wherein the first user input specifies modifying a relative weight of a first additional ranking factor of the one or more additional ranking factors; automatically modify the ranking function of the search engine to use the relative weight of the first additional ranking factor based on the first user input; after automatically modifying the ranking function of the search engine to use the relative weight of the first additional ranking factor, receive a search query for the website; and provide a plurality of search results using the ranking function. 13. The non-transitory, computer accessible memory medium of claim 8 , wherein the first one or more custom tags comprise a tag associated with economic attributes of the at least one webpage.
| 0.66782 |
8,225,273 | 1 | 2 |
1. A system for displaying unified model (UM) data in a UM visualization, comprising: a weighting system for assigning weights to UM elements; a clustering system for clustering the weighted UM elements into clusters, the weighting system further assigning weights to the clusters; and a visualization system for displaying the weighted clusters and the weighted UM elements in the weighted clusters within a conceptual framework; wherein a size of each weighted UM element displayed within the conceptual framework is proportional to the weight assigned to the weighted UM element, and wherein a size of each weighted cluster displayed within the conceptual framework is proportional to the weight assigned to the weighted cluster.
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1. A system for displaying unified model (UM) data in a UM visualization, comprising: a weighting system for assigning weights to UM elements; a clustering system for clustering the weighted UM elements into clusters, the weighting system further assigning weights to the clusters; and a visualization system for displaying the weighted clusters and the weighted UM elements in the weighted clusters within a conceptual framework; wherein a size of each weighted UM element displayed within the conceptual framework is proportional to the weight assigned to the weighted UM element, and wherein a size of each weighted cluster displayed within the conceptual framework is proportional to the weight assigned to the weighted cluster. 2. The system of claim 1 , wherein the weighting system determines weights manually based on user input.
| 0.603053 |
9,245,038 | 1 | 8 |
1. A method comprising, by one or more computing devices: receiving, from a client device associated with a first user of an online social network, an unstructured text query comprising one or more n-grams, the online social network being associated with a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes; identifying one or more of the nodes based at least on a determined probability for each node that the node corresponds to at least one of the n-grams, each of the identified nodes matching at least a portion of one or more of the n-grams; identifying one or more of the edges, each of the identified edges being connected to at least one of the identified nodes, each of the identified edges matching at least a portion of one or more of the n-grams; generating one or more structured queries that each comprise the n-grams of the text query and references to one or more of the identified nodes and one or more of the identified edges; and sending, to the client device associated with the first user in response to receiving the text query, one or more of the structured queries for presentation to the first user.
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1. A method comprising, by one or more computing devices: receiving, from a client device associated with a first user of an online social network, an unstructured text query comprising one or more n-grams, the online social network being associated with a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes; identifying one or more of the nodes based at least on a determined probability for each node that the node corresponds to at least one of the n-grams, each of the identified nodes matching at least a portion of one or more of the n-grams; identifying one or more of the edges, each of the identified edges being connected to at least one of the identified nodes, each of the identified edges matching at least a portion of one or more of the n-grams; generating one or more structured queries that each comprise the n-grams of the text query and references to one or more of the identified nodes and one or more of the identified edges; and sending, to the client device associated with the first user in response to receiving the text query, one or more of the structured queries for presentation to the first user. 8. The method of claim 1 , further comprising ranking each of the structured queries based on a textual relevance of the structured query.
| 0.859756 |
7,562,069 | 21 | 25 |
21. A computer system comprising: at least one processor; and at least one machine-readable storage device encoded with machine readable instructions that, when executed by the at least one processor, operate to cause the at least one processor to perform operations comprising: maintaining, in electronic storage, a query ontology that includes one or more query categories and one or more queries associated with each of the one or more categories; receiving a query from a user, the received query including a first portion and a second portion that is different than the first portion; in response to receiving the query, accessing, from the electronic storage, one or more queries included within the query ontology; comparing the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a first group of multiple categories that are associated with a query that matches the first portion of the received query; comparing the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a second group of multiple categories that are associated with a query that matches the second portion of the received query, the second group of multiple categories being different than the first group of multiple categories; comparing the second group of multiple categories with the first group of multiple categories; based on the comparison of the second group of multiple categories with the first group of multiple categories, identifying a category that is included in the second group of multiple categories identified for the second portion of the received query and the first group of multiple categories identified for the first portion of the received query; performing a search process that uses the identified category in identifying search results responsive to the received query, the search process comprising: accessing, from the electronic storage, a subset of one or more query terms included within the query ontology and associated with the identified category; configuring the received query to include the accessed subset of one or more query terms associated with the identified category, the configured query being different than the received query; submitting the configured query to a search engine; receiving, from the search engine, search results corresponding to the configured query; and storing, in electronic storage, the received search results corresponding to the configured query.
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21. A computer system comprising: at least one processor; and at least one machine-readable storage device encoded with machine readable instructions that, when executed by the at least one processor, operate to cause the at least one processor to perform operations comprising: maintaining, in electronic storage, a query ontology that includes one or more query categories and one or more queries associated with each of the one or more categories; receiving a query from a user, the received query including a first portion and a second portion that is different than the first portion; in response to receiving the query, accessing, from the electronic storage, one or more queries included within the query ontology; comparing the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a first group of multiple categories that are associated with a query that matches the first portion of the received query; comparing the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a second group of multiple categories that are associated with a query that matches the second portion of the received query, the second group of multiple categories being different than the first group of multiple categories; comparing the second group of multiple categories with the first group of multiple categories; based on the comparison of the second group of multiple categories with the first group of multiple categories, identifying a category that is included in the second group of multiple categories identified for the second portion of the received query and the first group of multiple categories identified for the first portion of the received query; performing a search process that uses the identified category in identifying search results responsive to the received query, the search process comprising: accessing, from the electronic storage, a subset of one or more query terms included within the query ontology and associated with the identified category; configuring the received query to include the accessed subset of one or more query terms associated with the identified category, the configured query being different than the received query; submitting the configured query to a search engine; receiving, from the search engine, search results corresponding to the configured query; and storing, in electronic storage, the received search results corresponding to the configured query. 25. The computer system of claim 21 wherein identifying the category comprises identifying, without user input, a category based on characteristics of the first group of multiple categories and characteristics of the second group of multiple categories.
| 0.734244 |
8,713,042 | 14 | 20 |
14. A system including memory and one or more processors operable to execute instructions stored in the memory, comprising instructions to: identify a plurality of autocomplete suggestions and corresponding autocomplete scores for a query; identify multiple term autocomplete suggestions of the autocomplete suggestions, each of the multiple term autocomplete suggestions having a first term and one or more subsequent terms; generate additional suggestions for the multiple term autocomplete suggestions, the additional suggestions for one or more of the multiple term autocomplete suggestions including the first term of the multiple term autocomplete suggestion and also including the first term combined with at least one contiguous of the subsequent terms of the multiple term autocomplete suggestion; determining additional suggestion scores for one or more of the additional suggestions, wherein the additional suggestion score for an additional suggestion is determined from the autocomplete score of the multiple term autocomplete suggestion used to generate the additional suggestion; identify one or more of the autocomplete suggestions and one or more of the additional suggestions as potential autocomplete suggestions; identify groupings of like entries among the additional suggestions and the autocomplete suggestions; combine the groupings of like entries into a consolidated entry for each of said groupings; and determine a combined consolidated score for each said consolidated entry based on one or more of the additional suggestion scores and based on any of the autocomplete scores of the like entries combined into the consolidated entry.
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14. A system including memory and one or more processors operable to execute instructions stored in the memory, comprising instructions to: identify a plurality of autocomplete suggestions and corresponding autocomplete scores for a query; identify multiple term autocomplete suggestions of the autocomplete suggestions, each of the multiple term autocomplete suggestions having a first term and one or more subsequent terms; generate additional suggestions for the multiple term autocomplete suggestions, the additional suggestions for one or more of the multiple term autocomplete suggestions including the first term of the multiple term autocomplete suggestion and also including the first term combined with at least one contiguous of the subsequent terms of the multiple term autocomplete suggestion; determining additional suggestion scores for one or more of the additional suggestions, wherein the additional suggestion score for an additional suggestion is determined from the autocomplete score of the multiple term autocomplete suggestion used to generate the additional suggestion; identify one or more of the autocomplete suggestions and one or more of the additional suggestions as potential autocomplete suggestions; identify groupings of like entries among the additional suggestions and the autocomplete suggestions; combine the groupings of like entries into a consolidated entry for each of said groupings; and determine a combined consolidated score for each said consolidated entry based on one or more of the additional suggestion scores and based on any of the autocomplete scores of the like entries combined into the consolidated entry. 20. The system of claim 14 , further comprising determining a subset of the potential autocomplete suggestions in response to the query based on the autocomplete scores and the consolidated scores of the potential autocomplete suggestions.
| 0.5 |
7,899,657 | 23 | 30 |
23. The method of claim 1 , further comprising: determining a second objective function, wherein the second objective function represents a specified objective of reservoir operations; and using the optimizer and the parameterized model to determine operation of the reservoir that satisfies the second objective function.
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23. The method of claim 1 , further comprising: determining a second objective function, wherein the second objective function represents a specified objective of reservoir operations; and using the optimizer and the parameterized model to determine operation of the reservoir that satisfies the second objective function. 30. The method of claim 23 , wherein said using the optimizer and the parameterized model to determine operation of the reservoir that satisfies the second objective function subject to one or more operational constraints comprises: determining one or more rates of stimulant injection to maximize production.
| 0.673362 |
4,610,025 | 39 | 40 |
39. The method of claim 35, further comprising the step of analyzing said document including the arrangement of glyphs and groups of glyphs on said document, to determine and classify said document as being that of a particular type.
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39. The method of claim 35, further comprising the step of analyzing said document including the arrangement of glyphs and groups of glyphs on said document, to determine and classify said document as being that of a particular type. 40. The method of claim 39, wherein the step of decrypting said identifiers includes the step of selecting an appropriate set of decryption routines based on said document type classification.
| 0.5 |
7,805,455 | 13 | 22 |
13. A system for problem analysis comprising: a computer program stored within a computer-readable storage medium for execution on a computer system, the computer system comprising: one or more computer processing elements; one or more display devices; one or more user input devices; and communication elements for communicating with the one or more databases; one or more cause/effect databases having cause and effect elements stored in the cause/effect database; an event store comprising an element extractor and models having one or more event statements, wherein, based on a machine representation of a problem, the element extractor identifies an event statement from the models and determines which half of a cause-effect relationship is represented by the event statement and extracts elements from the event statement to determine a cause element or an effect element as half of the cause-effect relationship; a query formulator configured to generate a query based on the determined cause element or the determined effect element; and a knowledge search engine configured to determine one or more complete cause-effect relationships, wherein the knowledge search engine is adapted to: receive the query; search the one or more cause/effect databases to: locate one or more effect elements that form complete cause-effect relationships with the determined cause element of the query, or locate one or more cause elements that form complete cause-effect relationships with the determined effect element of the query; and output the one or more causes-effect relationships by presenting the determined cause element or effect element of the query with the located one or more effect elements or cause elements from the one or more knowledge bases.
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13. A system for problem analysis comprising: a computer program stored within a computer-readable storage medium for execution on a computer system, the computer system comprising: one or more computer processing elements; one or more display devices; one or more user input devices; and communication elements for communicating with the one or more databases; one or more cause/effect databases having cause and effect elements stored in the cause/effect database; an event store comprising an element extractor and models having one or more event statements, wherein, based on a machine representation of a problem, the element extractor identifies an event statement from the models and determines which half of a cause-effect relationship is represented by the event statement and extracts elements from the event statement to determine a cause element or an effect element as half of the cause-effect relationship; a query formulator configured to generate a query based on the determined cause element or the determined effect element; and a knowledge search engine configured to determine one or more complete cause-effect relationships, wherein the knowledge search engine is adapted to: receive the query; search the one or more cause/effect databases to: locate one or more effect elements that form complete cause-effect relationships with the determined cause element of the query, or locate one or more cause elements that form complete cause-effect relationships with the determined effect element of the query; and output the one or more causes-effect relationships by presenting the determined cause element or effect element of the query with the located one or more effect elements or cause elements from the one or more knowledge bases. 22. The system according to claim 13 , wherein the one or more databases comprise one or more databases selected from a group consisting of: one or more locally accessible databases; one or more databases containing corporate knowledge; and one or more publicly accessible databases.
| 0.5 |
7,996,384 | 17 | 18 |
17. The system of claim 15 , wherein the conditional statement of the first abstract rule and the conditional statement of the second abstract rule are composed from a plurality of logical fields defined in a data abstraction model modeling an underlying physical database.
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17. The system of claim 15 , wherein the conditional statement of the first abstract rule and the conditional statement of the second abstract rule are composed from a plurality of logical fields defined in a data abstraction model modeling an underlying physical database. 18. The system of claim 17 , wherein the rule set container further includes an abstract query composed from the plurality of logical fields defined in the data abstraction model, and wherein the steps further comprise: transforming the abstract query into an executable query; and executing the executable query to retrieve a plurality of data records processed by the first abstract rule and the second abstract rule.
| 0.5 |
7,917,457 | 14 | 16 |
14. The system of claim 10 , wherein the contextual pattern decoder engine is further configured to subdivide one of the plurality of knowledge elements using a second pattern matching at least a part of the abstract representation, to identify the subdivided knowledge element with context information in the abstract representation, and wherein the pattern classification engine is further configured to classify the subdivided knowledge element in the abstract representation as a business rule using the context information and a third pattern.
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14. The system of claim 10 , wherein the contextual pattern decoder engine is further configured to subdivide one of the plurality of knowledge elements using a second pattern matching at least a part of the abstract representation, to identify the subdivided knowledge element with context information in the abstract representation, and wherein the pattern classification engine is further configured to classify the subdivided knowledge element in the abstract representation as a business rule using the context information and a third pattern. 16. The system of claim 14 , wherein the third pattern comprises a predefined pattern or a dynamic pattern.
| 0.753456 |
7,496,856 | 7 | 10 |
7. The computer-implemented method as recited in claim 1 , further comprising: receiving an annotation of the object; determining a position of the annotated object in the document; and storing the position and the annotation of the annotated object separately from a non-modifiable portion of the document.
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7. The computer-implemented method as recited in claim 1 , further comprising: receiving an annotation of the object; determining a position of the annotated object in the document; and storing the position and the annotation of the annotated object separately from a non-modifiable portion of the document. 10. The computer-implemented method as recited in claim 7 , wherein said determining comprises: counting bytes from a beginning of the non-modifiable portion of the document to the annotated object.
| 0.795031 |
8,484,015 | 20 | 21 |
20. A natural language (NL) system comprising: a first database to store data relevant to entities; a second database to store web page data, the web page data including web pages configured to display answers to NL queries; a caching manager, communicatively connected to each of the first database and second database, the caching manager configured to: receive data representing a received NL query, determine whether the second database contains a first web page configured to display an answer to the received NL query, and fetch the first web page from the second database when the first web page is stored in the second database, wherein the first web page is made available to the network; and a NL query answering engine, communicatively connected to the caching manager, the NL query answering engine configured to determine an answer to the received NL query when it is determined that the first web page is not stored on the second database, wherein the answer to the received NL query is determined using data from the first database; wherein the caching manager is further configured to, after the NL query answering engine determines the answer to the received NL query: determine, using one or more computing devices, whether to store a new web page to the second database, the new web page including the answer to the received NL query determined by the NL query answering engine, and store in the second database the new web page when it is determined that the new web page should be stored.
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20. A natural language (NL) system comprising: a first database to store data relevant to entities; a second database to store web page data, the web page data including web pages configured to display answers to NL queries; a caching manager, communicatively connected to each of the first database and second database, the caching manager configured to: receive data representing a received NL query, determine whether the second database contains a first web page configured to display an answer to the received NL query, and fetch the first web page from the second database when the first web page is stored in the second database, wherein the first web page is made available to the network; and a NL query answering engine, communicatively connected to the caching manager, the NL query answering engine configured to determine an answer to the received NL query when it is determined that the first web page is not stored on the second database, wherein the answer to the received NL query is determined using data from the first database; wherein the caching manager is further configured to, after the NL query answering engine determines the answer to the received NL query: determine, using one or more computing devices, whether to store a new web page to the second database, the new web page including the answer to the received NL query determined by the NL query answering engine, and store in the second database the new web page when it is determined that the new web page should be stored. 21. The NL system of claim 20 , wherein the first database comprises: a plurality of entities categorized by class and sub-class, a plurality of attributes associated with the entities.
| 0.675439 |
9,542,945 | 10 | 13 |
10. A non-transitory computer-readable storage device having instructions stored thereon that, when executed by a computing device of an automated speech recognition system, cause the computing device to perform speech recognition operations comprising: receiving, by the computing device of the automated speech recognition system, audio data and context data associated with the audio data, wherein the received context data indicates a current context of a device when the device captured the audio data; identifying, by the computing device of the automated speech recognition system, a topic based on a comparison of the received context data with second context data indicating a previous context of a device, wherein identifying the topic includes: selecting, by the computing device of the automated speech recognition system, a term based on the comparison between the received context data and the second context data; and in response to selecting the term, selecting, by the computing device of the automated speech recognition system and as the identified topic, a topic that is associated with the selected term; based on identifying the topic, adjusting, by the computing device of the automated speech recognition system, a language model based on the identified topic to adjust a likelihood that the language model indicates for one or more terms associated with the topic; determining, by the computing device of the automated speech recognition system, a transcription of the audio data using the adjusted language model; and outputting, by the computing device of the automated speech recognition system, the transcription determined using the adjusted language model, the transcription being output as a speech recognition output of the automated speech recognition system.
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10. A non-transitory computer-readable storage device having instructions stored thereon that, when executed by a computing device of an automated speech recognition system, cause the computing device to perform speech recognition operations comprising: receiving, by the computing device of the automated speech recognition system, audio data and context data associated with the audio data, wherein the received context data indicates a current context of a device when the device captured the audio data; identifying, by the computing device of the automated speech recognition system, a topic based on a comparison of the received context data with second context data indicating a previous context of a device, wherein identifying the topic includes: selecting, by the computing device of the automated speech recognition system, a term based on the comparison between the received context data and the second context data; and in response to selecting the term, selecting, by the computing device of the automated speech recognition system and as the identified topic, a topic that is associated with the selected term; based on identifying the topic, adjusting, by the computing device of the automated speech recognition system, a language model based on the identified topic to adjust a likelihood that the language model indicates for one or more terms associated with the topic; determining, by the computing device of the automated speech recognition system, a transcription of the audio data using the adjusted language model; and outputting, by the computing device of the automated speech recognition system, the transcription determined using the adjusted language model, the transcription being output as a speech recognition output of the automated speech recognition system. 13. The non-transitory computer-readable storage device of claim 10 , wherein the operations comprise: selecting, from among multiple sets of terms that are each associated with a respective topic, a particular set of terms that are associated with the identified topic; and wherein adjusting the language model based on the identified topic to adjust the likelihood that the language model indicates for one or more terms associated with the topic, includes: adjusting the language model based on the identified topic to adjust a likelihood that the language model indicates for each of the terms in the particular set of terms associated with the topic.
| 0.5 |
7,599,829 | 9 | 10 |
9. A computer-implemented system for phonetically searching character data, the system comprising: a processor and a computer-readable storage medium; an operating environment stored on the computer-readable storage medium and executing on the processor and that is configured to interact with: an application interface that is configured to receive an input string that comprises a partial character of a spoken language; and a filter that is configured to receive the partial character, that is configured to receive a character from a datastore, wherein the characters are encoded using phonetic codes of a spoken language, that is configured to decode the received character into a comparison string that comprises a sequence of phonetic codes that is associated with the received character; and that is configured to compare the comparison string with the partial character and returning a result based on the comparison when a match is found.
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9. A computer-implemented system for phonetically searching character data, the system comprising: a processor and a computer-readable storage medium; an operating environment stored on the computer-readable storage medium and executing on the processor and that is configured to interact with: an application interface that is configured to receive an input string that comprises a partial character of a spoken language; and a filter that is configured to receive the partial character, that is configured to receive a character from a datastore, wherein the characters are encoded using phonetic codes of a spoken language, that is configured to decode the received character into a comparison string that comprises a sequence of phonetic codes that is associated with the received character; and that is configured to compare the comparison string with the partial character and returning a result based on the comparison when a match is found. 10. The system of claim 9 wherein the text to be searched is entered by a user.
| 0.842629 |
9,342,675 | 10 | 14 |
10. A system, comprising: a processor configured to: determine, by an online education course operator, whether submitting coursework by a user in an online education course is an event requiring authentication; if submitting coursework by the user is determined to be an event not requiring authentication, accept, by the online education course operator, the coursework as being submitted by the user; if submitting coursework by the user is determined to be an event requiring authentication, initiate, by the online education course operator, an authentication process including: prompting the user to provide an authentication typing sample by entering an authentication phrase on a keyboard in order to authenticate the user submitting the coursework in the online education course, wherein the online education course that corresponds with a database that stores user identification profiles specific to the online education course, the user identification profiles including collected enrollment/registration and authentication information including one or more of keystroke biometrics, webcam headshots, webcam capture of photo ID documentation, and personal user identification information, and wherein the authentication phrase the user is prompted to enter on the keyboard is selected by the online education course operator, and the user, or is a hybrid phrase where part of the phrase is selected by the online education course operator and another part is selected by the user; comparing the authentication typing sample to an enrollment typing sample captured earlier in order to determine whether the authentication typing sample matches the enrollment typing sample, wherein the enrollment typing sample includes a profile of the user's unique typing pattern measured on a time scale of an order of a millisecond; in the case that the authentication typing sample is determined to match the enrollment typing sample, indicating that the user's identity has been authenticated and accept the coursework as being submitted and signed by the user; and in the case that the authentication typing sample is not determined to match the enrollment typing sample, prompting the user to provide a second type of authentication information for matching by the processor with an enrollment sample of the second type of authentication information in the database that stores the user identification profiles specific to the online education course, and based on the matching of the second type of authentication information authenticating the user's identity and accepting the coursework as being submitted and signed by the user; and a memory coupled to the processor and configured to provide the processor with instructions on how to compare the authentication typing sample to the enrollment typing sample and how to compare the second type of authentication information with the enrollment sample of the second type.
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10. A system, comprising: a processor configured to: determine, by an online education course operator, whether submitting coursework by a user in an online education course is an event requiring authentication; if submitting coursework by the user is determined to be an event not requiring authentication, accept, by the online education course operator, the coursework as being submitted by the user; if submitting coursework by the user is determined to be an event requiring authentication, initiate, by the online education course operator, an authentication process including: prompting the user to provide an authentication typing sample by entering an authentication phrase on a keyboard in order to authenticate the user submitting the coursework in the online education course, wherein the online education course that corresponds with a database that stores user identification profiles specific to the online education course, the user identification profiles including collected enrollment/registration and authentication information including one or more of keystroke biometrics, webcam headshots, webcam capture of photo ID documentation, and personal user identification information, and wherein the authentication phrase the user is prompted to enter on the keyboard is selected by the online education course operator, and the user, or is a hybrid phrase where part of the phrase is selected by the online education course operator and another part is selected by the user; comparing the authentication typing sample to an enrollment typing sample captured earlier in order to determine whether the authentication typing sample matches the enrollment typing sample, wherein the enrollment typing sample includes a profile of the user's unique typing pattern measured on a time scale of an order of a millisecond; in the case that the authentication typing sample is determined to match the enrollment typing sample, indicating that the user's identity has been authenticated and accept the coursework as being submitted and signed by the user; and in the case that the authentication typing sample is not determined to match the enrollment typing sample, prompting the user to provide a second type of authentication information for matching by the processor with an enrollment sample of the second type of authentication information in the database that stores the user identification profiles specific to the online education course, and based on the matching of the second type of authentication information authenticating the user's identity and accepting the coursework as being submitted and signed by the user; and a memory coupled to the processor and configured to provide the processor with instructions on how to compare the authentication typing sample to the enrollment typing sample and how to compare the second type of authentication information with the enrollment sample of the second type. 14. The system of claim 10 , wherein the processor determines whether the authentication typing sample matches the enrollment typing sample by matching keystroke biometrics of the authentication typing sample against keystroke biometrics of the enrollment typing sample.
| 0.5 |
7,624,399 | 1 | 3 |
1. A computer system for identifying a target component in an apparatus that has components related in a hierarchy, the computer system comprising: a first computer operable to execute a first application, wherein the first application relates objects representing corresponding components in both a type hierarchy identifying types of components and a separate object hierarchy identifying information associated with objects, wherein the type hierarchy and the object hierarchy identify the components in a first natural language; a second computer coupled to the first computer via a network; wherein the first computer includes a message generator operable to receive information relating to both the type hierarchy and the object hierarchy from the first application and the message generator further operable to provide to the second computer a message comprising a type chain identifying a path in the type hierarchy in a parent-child direction and an object chain identifying a path in the object hierarchy in the parent-child direction, wherein the type chain identifies a type node associated with a target object and the object chain identifies an object node associated with the target object, wherein a combination of the type node and the object node identifies the target object that corresponds to the target component, and wherein a combination of ascendants of the type node and ascendants of the object node correspond to parent components; and wherein the second computer has a message interpreter operable to parse both chains to provide identification of the target component with the combination of the type node and the object node as well as to provide identification of the parent components with the combination of ascendants of the type node and ascendants of the object node, wherein the identification provided by the message interpreter further includes translating information from the first natural language to a different natural language using both the chains.
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1. A computer system for identifying a target component in an apparatus that has components related in a hierarchy, the computer system comprising: a first computer operable to execute a first application, wherein the first application relates objects representing corresponding components in both a type hierarchy identifying types of components and a separate object hierarchy identifying information associated with objects, wherein the type hierarchy and the object hierarchy identify the components in a first natural language; a second computer coupled to the first computer via a network; wherein the first computer includes a message generator operable to receive information relating to both the type hierarchy and the object hierarchy from the first application and the message generator further operable to provide to the second computer a message comprising a type chain identifying a path in the type hierarchy in a parent-child direction and an object chain identifying a path in the object hierarchy in the parent-child direction, wherein the type chain identifies a type node associated with a target object and the object chain identifies an object node associated with the target object, wherein a combination of the type node and the object node identifies the target object that corresponds to the target component, and wherein a combination of ascendants of the type node and ascendants of the object node correspond to parent components; and wherein the second computer has a message interpreter operable to parse both chains to provide identification of the target component with the combination of the type node and the object node as well as to provide identification of the parent components with the combination of ascendants of the type node and ascendants of the object node, wherein the identification provided by the message interpreter further includes translating information from the first natural language to a different natural language using both the chains. 3. The computer system of claim 1 , wherein the message generator at the first computer is operable to append an identifier type to the type chain, and to append an identifier object to the object chain.
| 0.612595 |
7,676,742 | 11 | 12 |
11. A method for processing of markup language information comprising: receiving markup language information at a first data processor for identifying a part of the markup language information for compression; assigning a label representative of the part to form compressed information representative of the mark up language information comprising the label; sending the compressed information to a second data processor in communication with the first data processor; decompressing the compressed information in the second data processor; identifying the label; and associating the label with the part of markup language information.
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11. A method for processing of markup language information comprising: receiving markup language information at a first data processor for identifying a part of the markup language information for compression; assigning a label representative of the part to form compressed information representative of the mark up language information comprising the label; sending the compressed information to a second data processor in communication with the first data processor; decompressing the compressed information in the second data processor; identifying the label; and associating the label with the part of markup language information. 12. A method of claim 11 further comprising storing in a data value database the label representative of a predetermined part of markup language information.
| 0.589005 |
8,612,468 | 20 | 21 |
20. The method of claim 19 , wherein generating a relational query comprises: performing a traversal of the current expression tree; and generating the relational query based on the current expression tree.
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20. The method of claim 19 , wherein generating a relational query comprises: performing a traversal of the current expression tree; and generating the relational query based on the current expression tree. 21. The method of claim 20 , further comprising caching the current expression tree created for relational queries generated.
| 0.5 |
9,870,539 | 1 | 12 |
1. A method, comprising: using one or more computers to send and receive messages in an electronic message board over a network, said messages comprising user content and an icon selection received from at least one user, wherein the user content comprises non-textual and textual content, wherein the non-textual content comprises audio content; recognizing speech in the received audio content; comparing content of the recognized speech to a predetermined set of usage metaphors, each of the set of usage metaphors associated with an icon, to identify a first usage metaphor corresponding to the recognized speech; storing, in a non-transitory data storage associated with the electronic message board based on the comparing, the received user content and an association between the received user content and the first usage metaphor and a first icon corresponding to the icon selection, wherein other content received from other users is stored in the data storage and associated with other metaphors that are different than the first usage metaphor; searching, after the associating, for stored content related to the first usage metaphor; identifying, based on the searching, at least one result associated with the first usage metaphor, each result comprising a respective audio element and a respective icon stored for the respective audio element; and display on a user interface associated with the electronic message board, for each result of the at least one result, a representation of the result including the respective icon of the result, and a corresponding control for activating the respective audio element of the result.
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1. A method, comprising: using one or more computers to send and receive messages in an electronic message board over a network, said messages comprising user content and an icon selection received from at least one user, wherein the user content comprises non-textual and textual content, wherein the non-textual content comprises audio content; recognizing speech in the received audio content; comparing content of the recognized speech to a predetermined set of usage metaphors, each of the set of usage metaphors associated with an icon, to identify a first usage metaphor corresponding to the recognized speech; storing, in a non-transitory data storage associated with the electronic message board based on the comparing, the received user content and an association between the received user content and the first usage metaphor and a first icon corresponding to the icon selection, wherein other content received from other users is stored in the data storage and associated with other metaphors that are different than the first usage metaphor; searching, after the associating, for stored content related to the first usage metaphor; identifying, based on the searching, at least one result associated with the first usage metaphor, each result comprising a respective audio element and a respective icon stored for the respective audio element; and display on a user interface associated with the electronic message board, for each result of the at least one result, a representation of the result including the respective icon of the result, and a corresponding control for activating the respective audio element of the result. 12. The method of claim 1 , further comprising: receiving an indication that a stored audio element of an identified result was activated via the control corresponding to the identified result; and play the stored audio element in response to receiving the indication.
| 0.575949 |
8,319,985 | 1 | 2 |
1. An image formation apparatus that reconstructs and prints a document including text data and image data, based on document data written in a markup language, the document data including (i) one or more pieces of text data, (ii) text layout information for the one or more pieces of text data, and (iii) one or more pieces of image data attribute information that show identifiers of one or more pieces of image data respectively, locations of the one or more pieces of image data respectively, and image layout information for the one or more pieces of image data, the image formation apparatus comprising: a reconstructor operable, by using browser software, to arrange the one or more pieces of text data included in the document data within a page of the document according to the text layout information, and attempt to acquire the one or more pieces of image data from relevant servers according to the identifiers and the locations of the one or more pieces of image data and arrange acquired pieces among the one or more pieces of image data within the page of the document according to the image layout information; a judgment part operable, in a case where the reconstructor has failed to acquire some of the one or more pieces of image data, to judge whether each of the some of the one or more pieces of image data is important or not according to a corresponding piece of the image data attribute information; a controller operable to execute printing of the document reconstructed based on the one or more pieces of text data and/or the acquired pieces of image data if the judgment part judges negatively as to all of the some of the one or more pieces of image data that the reconstructor has failed to acquire, and to cancel the printing if the judgment part judges affirmatively as to any of the some of the one or more pieces of image data that the reconstructor has failed to acquire; and a storage that prestores therein locations of one or more pieces of low-importance image data, wherein if a location of a piece of image data that the reconstructor has failed to acquire is identical to any one of the locations of the one or more pieces of low-importance image data, the judgment part judges that the piece of image data that the reconstructor has failed to acquire is not important.
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1. An image formation apparatus that reconstructs and prints a document including text data and image data, based on document data written in a markup language, the document data including (i) one or more pieces of text data, (ii) text layout information for the one or more pieces of text data, and (iii) one or more pieces of image data attribute information that show identifiers of one or more pieces of image data respectively, locations of the one or more pieces of image data respectively, and image layout information for the one or more pieces of image data, the image formation apparatus comprising: a reconstructor operable, by using browser software, to arrange the one or more pieces of text data included in the document data within a page of the document according to the text layout information, and attempt to acquire the one or more pieces of image data from relevant servers according to the identifiers and the locations of the one or more pieces of image data and arrange acquired pieces among the one or more pieces of image data within the page of the document according to the image layout information; a judgment part operable, in a case where the reconstructor has failed to acquire some of the one or more pieces of image data, to judge whether each of the some of the one or more pieces of image data is important or not according to a corresponding piece of the image data attribute information; a controller operable to execute printing of the document reconstructed based on the one or more pieces of text data and/or the acquired pieces of image data if the judgment part judges negatively as to all of the some of the one or more pieces of image data that the reconstructor has failed to acquire, and to cancel the printing if the judgment part judges affirmatively as to any of the some of the one or more pieces of image data that the reconstructor has failed to acquire; and a storage that prestores therein locations of one or more pieces of low-importance image data, wherein if a location of a piece of image data that the reconstructor has failed to acquire is identical to any one of the locations of the one or more pieces of low-importance image data, the judgment part judges that the piece of image data that the reconstructor has failed to acquire is not important. 2. The image formation apparatus of claim 1 , wherein if the image layout information shows that a piece of image data that the reconstructor has failed to acquire is to be arranged in a peripheral area of the page of the document, the judgment part judges that the piece of image data that the reconstructor has failed to acquire is not important.
| 0.5 |
9,613,161 | 10 | 13 |
10. A method comprising: submitting, to a server, a search query generated by a user; receiving a plurality of search results from the server, the plurality of search results corresponding to a first quantity of pages; receiving a pagination control size from the server, the pagination control size indicating a second quantity of pages based on prior interactions of other users with search results after other search queries similar to the search query; and displaying, on a display device, a page of the first quantity of pages of the plurality of search results along with a pagination control having the pagination control size, the pagination control operable to select a page from the second quantity of pages.
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10. A method comprising: submitting, to a server, a search query generated by a user; receiving a plurality of search results from the server, the plurality of search results corresponding to a first quantity of pages; receiving a pagination control size from the server, the pagination control size indicating a second quantity of pages based on prior interactions of other users with search results after other search queries similar to the search query; and displaying, on a display device, a page of the first quantity of pages of the plurality of search results along with a pagination control having the pagination control size, the pagination control operable to select a page from the second quantity of pages. 13. The method of claim 10 , wherein the plurality of search results are displayed in a scrollable interface; and the method further comprises, responsive to an amount of scrolling of the scrollable interface transgressing a threshold, displaying refinement data in a non-scrollable element, the refinement data including one or more refinement options, the displaying of the non-scrollable element being performed in conjunction with the displaying of the plurality of search results.
| 0.5 |
6,138,087 | 1 | 6 |
1. A method of processing natural language, which comprises steps providing electronically encoded data which is representative of said natural language, providing a dictionary data base wherein said dictionary data base contains a plurality of entries which are comprised of one or more of syntax usage data, associated word sense numbers having associated state representation data, lexically processing said electronically encoded data to access said dictionary data base, utilizing said syntax usage data and said word sense numbers which are from entries of said dictionary data base and which are associated with words of said natural language to access said state representation data.
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1. A method of processing natural language, which comprises steps providing electronically encoded data which is representative of said natural language, providing a dictionary data base wherein said dictionary data base contains a plurality of entries which are comprised of one or more of syntax usage data, associated word sense numbers having associated state representation data, lexically processing said electronically encoded data to access said dictionary data base, utilizing said syntax usage data and said word sense numbers which are from entries of said dictionary data base and which are associated with words of said natural language to access said state representation data. 6. A method of processing as defined in claim 1, which comprises processing steps that access said state representation data of said word sense number such that said word sense number's said state representation data has one or more states and values such that said states and values are requirements for another said word sense number's said state representation data to meet so as to be an instance of said word sense number's state representation data.
| 0.507576 |
9,537,706 | 24 | 36 |
24. A matching service system of a matching service, comprising: a number of communications ports which provide communications with a plurality of end user devices, the end user devices logically associable with a plurality of end user client accounts of the matching service, each end user client account of the plurality of end user client accounts logically associable with a respective end user client of the matching service; at least one nontransitory processor-readable medium that stores at least one of processor executable instructions or data; and at least one processor communicatively coupled to the communications ports and the at least one nontransitory processor-readable medium, and that: monitors communications with the plurality of end user devices; receives indications that respective pairs of the end user clients are no longer participating in the matching service, each end user client identified as one end user client in a pair of end user clients based at least in part on the monitoring of the communications with the plurality of end user devices; designates each of the end user clients in a pair of end user clients for which an indication is received as a successfully paired end user client; for each successfully paired end user client of the matching service, populates a successfully paired end user clients database with information for each successfully paired end user client; monitors communications with the end user devices for a reappearance of any of the successfully paired end user clients; and for each of the successfully paired end user clients in the successfully paired end user clients database that reappear, culls the information for at least the successfully paired end user client that reappears from the successfully paired end user clients database.
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24. A matching service system of a matching service, comprising: a number of communications ports which provide communications with a plurality of end user devices, the end user devices logically associable with a plurality of end user client accounts of the matching service, each end user client account of the plurality of end user client accounts logically associable with a respective end user client of the matching service; at least one nontransitory processor-readable medium that stores at least one of processor executable instructions or data; and at least one processor communicatively coupled to the communications ports and the at least one nontransitory processor-readable medium, and that: monitors communications with the plurality of end user devices; receives indications that respective pairs of the end user clients are no longer participating in the matching service, each end user client identified as one end user client in a pair of end user clients based at least in part on the monitoring of the communications with the plurality of end user devices; designates each of the end user clients in a pair of end user clients for which an indication is received as a successfully paired end user client; for each successfully paired end user client of the matching service, populates a successfully paired end user clients database with information for each successfully paired end user client; monitors communications with the end user devices for a reappearance of any of the successfully paired end user clients; and for each of the successfully paired end user clients in the successfully paired end user clients database that reappear, culls the information for at least the successfully paired end user client that reappears from the successfully paired end user clients database. 36. The matching service system of claim 24 wherein the at least one processor populates the successfully paired end user clients database with information collected during use of the matching service by the at least one end user client and which is indicative of non-profile related end user client interactions via the matching service.
| 0.676245 |
8,615,452 | 12 | 13 |
12. The computer of claim 8 , wherein the processor is to provide the transaction-tax-related information in a data file, and wherein the data file is a file of tokenized data.
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12. The computer of claim 8 , wherein the processor is to provide the transaction-tax-related information in a data file, and wherein the data file is a file of tokenized data. 13. The computer of claim 12 , wherein the data is tokenized by XML, SGML, or another markup language.
| 0.5 |
7,523,036 | 13 | 21 |
13. A text-to-speech synthesis apparatus comprising: selecting means for selecting at least two speaker voices; transmitting means for transmitting speaker voice identification data for identifying said speaker voices selected by said selecting means to another apparatus; receiving means for receiving phoneme data of said speaker voices corresponding to said speaker voice identification data transmitted from said transmitting means; and text-to-speech synthesis processing means for linking said phoneme data of said speaker voices received by said receiving means to convert input data into a synthetic speech, wherein said text-to-speech synthesis processing means can convert said input data into a synthetic speech including at least said two speaker voices including said speaker voice corresponding to said speaker voice identification data.
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13. A text-to-speech synthesis apparatus comprising: selecting means for selecting at least two speaker voices; transmitting means for transmitting speaker voice identification data for identifying said speaker voices selected by said selecting means to another apparatus; receiving means for receiving phoneme data of said speaker voices corresponding to said speaker voice identification data transmitted from said transmitting means; and text-to-speech synthesis processing means for linking said phoneme data of said speaker voices received by said receiving means to convert input data into a synthetic speech, wherein said text-to-speech synthesis processing means can convert said input data into a synthetic speech including at least said two speaker voices including said speaker voice corresponding to said speaker voice identification data. 21. The text-to-speech synthesis apparatus according to claim 13 , wherein said selecting means selects script data as specified by said user; said transmitting means transmits, to another apparatus, script identification data for identifying said script data selected by said selecting means; said receiving means receives phoneme data of a speaker voice corresponding to said speaker voice identification data transmitted by said transmitting means and said script data corresponding to said script identification data; said text-to-speech synthesis processing means links said phoneme data of said speaker voice received by said receiving means to convert said script data into a synthetic speech.
| 0.5 |
8,280,733 | 7 | 10 |
7. A computer-implemented method for adapting a speech recognition system, comprising: detecting a user-initiated change to dictated text; automatically assigning a categorization to the user-initiated change to the dictated text, the categorization being automatically assigned based at least in part upon a measurement of time indicative of how long it took the user to initiate the change, wherein automatically assigning the categorization comprises automatically identifying, based at least in part upon the measurement of time, the user-initiated change as being either a correction or an edit operation; calculating a distance between a pronunciation of the dictated text and a pronunciation of the change to the dictated text; comparing the calculated distance to a threshold value; and selectively adapting the speech recognition engine depending upon the categorization and the calculated distance, and wherein selectively adapting further comprises determining a number of times that the pronunciation of the change to the dictated text has occurred and then selectively adapting the speech recognition engine when the number of times exceeds a selected number of times.
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7. A computer-implemented method for adapting a speech recognition system, comprising: detecting a user-initiated change to dictated text; automatically assigning a categorization to the user-initiated change to the dictated text, the categorization being automatically assigned based at least in part upon a measurement of time indicative of how long it took the user to initiate the change, wherein automatically assigning the categorization comprises automatically identifying, based at least in part upon the measurement of time, the user-initiated change as being either a correction or an edit operation; calculating a distance between a pronunciation of the dictated text and a pronunciation of the change to the dictated text; comparing the calculated distance to a threshold value; and selectively adapting the speech recognition engine depending upon the categorization and the calculated distance, and wherein selectively adapting further comprises determining a number of times that the pronunciation of the change to the dictated text has occurred and then selectively adapting the speech recognition engine when the number of times exceeds a selected number of times. 10. The method of claim 7 , wherein selectively adapting comprises not adapting if the categorization indicates that the user-initiated correction is not due to a recognition error made by the speech recognition engine.
| 0.732927 |
9,152,672 | 1 | 15 |
1. A method for performing queries on a distributed time series data storage system having a time series database that stores data blocks containing time stamped data across a plurality of computing devices, and an index database that stores an index associated with the time stamped data in each data block, the method comprising: sending a query to a query layer running on a first computing device, the query specifying criteria that define a set of data retrieved from the time series data storage system and an analysis performed on the set of data; requesting from the index database the indices associated with the data blocks stored in the time series database needed to evaluate the query; returning the indices back to the query layer; preparing a sub-query that produces appropriate data matching the criteria, the sub-query including the criteria and a logical operation performed on the data matching the criteria; forwarding the sub-query to an evaluator running on each of the plurality of computing devices that are identified in the returned indices as holding data corresponding to the data blocks needed to evaluate the query; evaluating the criteria specified in the sub-query in each evaluator with respect to the data blocks stored on the same computing device on which the evaluator is running in order to select a subset of data; performing the logical operation specified in the sub-query in each evaluator on the subset of data generated in that evaluator in the evaluating step above to generate a sub-result; receiving each sub-result from each evaluator at an output handler; and combining the sub-result from each evaluator into a query result.
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1. A method for performing queries on a distributed time series data storage system having a time series database that stores data blocks containing time stamped data across a plurality of computing devices, and an index database that stores an index associated with the time stamped data in each data block, the method comprising: sending a query to a query layer running on a first computing device, the query specifying criteria that define a set of data retrieved from the time series data storage system and an analysis performed on the set of data; requesting from the index database the indices associated with the data blocks stored in the time series database needed to evaluate the query; returning the indices back to the query layer; preparing a sub-query that produces appropriate data matching the criteria, the sub-query including the criteria and a logical operation performed on the data matching the criteria; forwarding the sub-query to an evaluator running on each of the plurality of computing devices that are identified in the returned indices as holding data corresponding to the data blocks needed to evaluate the query; evaluating the criteria specified in the sub-query in each evaluator with respect to the data blocks stored on the same computing device on which the evaluator is running in order to select a subset of data; performing the logical operation specified in the sub-query in each evaluator on the subset of data generated in that evaluator in the evaluating step above to generate a sub-result; receiving each sub-result from each evaluator at an output handler; and combining the sub-result from each evaluator into a query result. 15. The method of claim 1 , wherein the time stamped data is associated with the behavior of a plurality of assets.
| 0.874454 |
9,275,046 | 1 | 8 |
1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: providing an interface for selecting a vertical language text translation box corresponding to one or more words in the first language, wherein the first language is an Asian language comprising a plurality of characters having a vertical alignment; cropping a frame of the real-time video feed of the one or more words of the first language to fit inside the vertical language text translation box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments; performing character recognition on the merged character segments to produce a plurality of recognized characters; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language in augmented reality in the real-time video feed.
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1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: providing an interface for selecting a vertical language text translation box corresponding to one or more words in the first language, wherein the first language is an Asian language comprising a plurality of characters having a vertical alignment; cropping a frame of the real-time video feed of the one or more words of the first language to fit inside the vertical language text translation box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments; performing character recognition on the merged character segments to produce a plurality of recognized characters; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language in augmented reality in the real-time video feed. 8. The method of claim 1 , wherein the step of performing the one or more translations further comprises: processing the recognized characters through a translation engine to produce the translation of the recognized characters in the first language into the one or more translated words of the second language, while calculating a translation engine score representing how many and/or how well characters have been translated for each translated line.
| 0.599291 |
8,572,024 | 13 | 16 |
13. An apparatus for implementing a data extraction process, the apparatus comprising a workstation storage device, a workstation processor connected to the workstation storage device, the workstation storage device storing a workstation program for controlling the workstation processor, and the workstation processor operative with the workstation program to: receive one or more web sites selected by a user for data extraction; collect a plurality of co-occurring different HTML structured documents for each of the selected web sites; form a plurality of clusters comprising different subsets of a group of co-occurring Hyper Text Mark-up Language (HTML) structured documents for each of the selected web sites, wherein: each cluster comprises a different HTML structured document of the group of co-occurring HTML structured documents as a centroid document and other HTML structured documents of the group of co-occurring HTML structured documents that achieve a threshold of similarity with respect to the centroid document, the clusters are formed by comparing each co-occurring HTML structured document to each centroid document of each cluster based on relative structural similarity of HTML data structure of each co-occurring HTML structured document with respect to HTML data structure of each centroid document of each cluster, and an alignment algorithm is used to determine the co-occurring HTML structured documents that achieve the threshold of similarity with respect to each centroid document by comparing structured locations of data fields for storing data elements within each centroid document and structured locations of corresponding data fields for storing data elements within each of the co-occurring HTML structured documents, the co-occurring HTML structured documents are compared to each centroid document based on similarity of structured locations of corresponding data fields within the HTML data structures, display the centroid document of a particular cluster selected from a list of clusters; mark a data element on the centroid document of the particular cluster; and provide a user interface displaying content of data elements identified from the other HTML structured documents of the particular cluster on a computer display.
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13. An apparatus for implementing a data extraction process, the apparatus comprising a workstation storage device, a workstation processor connected to the workstation storage device, the workstation storage device storing a workstation program for controlling the workstation processor, and the workstation processor operative with the workstation program to: receive one or more web sites selected by a user for data extraction; collect a plurality of co-occurring different HTML structured documents for each of the selected web sites; form a plurality of clusters comprising different subsets of a group of co-occurring Hyper Text Mark-up Language (HTML) structured documents for each of the selected web sites, wherein: each cluster comprises a different HTML structured document of the group of co-occurring HTML structured documents as a centroid document and other HTML structured documents of the group of co-occurring HTML structured documents that achieve a threshold of similarity with respect to the centroid document, the clusters are formed by comparing each co-occurring HTML structured document to each centroid document of each cluster based on relative structural similarity of HTML data structure of each co-occurring HTML structured document with respect to HTML data structure of each centroid document of each cluster, and an alignment algorithm is used to determine the co-occurring HTML structured documents that achieve the threshold of similarity with respect to each centroid document by comparing structured locations of data fields for storing data elements within each centroid document and structured locations of corresponding data fields for storing data elements within each of the co-occurring HTML structured documents, the co-occurring HTML structured documents are compared to each centroid document based on similarity of structured locations of corresponding data fields within the HTML data structures, display the centroid document of a particular cluster selected from a list of clusters; mark a data element on the centroid document of the particular cluster; and provide a user interface displaying content of data elements identified from the other HTML structured documents of the particular cluster on a computer display. 16. The apparatus of claim 13 , further configured to automatically mark the data element on the centroid document of the particular cluster.
| 0.806319 |
7,697,668 | 1 | 2 |
1. A computer-readable medium storing instructions for controlling a computing device to customize a voice in a multi-media message created by a sender for a recipient, the multi-media message comprising a text message from the sender to be delivered by an animated entity, the instructions comprising: receiving from the sender inserted voice emoticons, which may be repeated, into the text message associated with parameters of a voice used by an animated entity to deliver the text message; and transmitting the text message such that a recipient device can deliver the multi-media message at a variable level associated with a number of times a respective voice emoticon is repeated.
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1. A computer-readable medium storing instructions for controlling a computing device to customize a voice in a multi-media message created by a sender for a recipient, the multi-media message comprising a text message from the sender to be delivered by an animated entity, the instructions comprising: receiving from the sender inserted voice emoticons, which may be repeated, into the text message associated with parameters of a voice used by an animated entity to deliver the text message; and transmitting the text message such that a recipient device can deliver the multi-media message at a variable level associated with a number of times a respective voice emoticon is repeated. 2. The computer-readable medium of claim 1 , wherein the voice emoticons comprise emoticons associated with at least one of voice stress, volume, pause, and emotion.
| 0.704301 |
7,717,712 | 10 | 13 |
10. A computer program product comprising a computer readable medium having computer readable instructions embodied therein for causing a computer to provide language learning for a language learner, the instructions comprising: instructions for causing the computer to retrieve stored text; instructions for causing the computer to replace each of at least two portions of the text with a corresponding key word or phrase; instructions for causing the computer to display the text having the at least two key words or phrases with a plurality of active regions, each active region corresponding to a different one of the at least two key words or phrases, each active region being associated with a corresponding menu of linguistic choices, each keyword or phrase representing a type of answer selection in the associated menu, the linguistic choices of each menu comprising at least two correct choices and at least one incorrect choice; instructions for causing the computer to enable a language learner to select a first active region of the active regions by selecting the corresponding key word or phrase of the first active region; instructions for causing the computer to display a first menu of linguistic choices corresponding to the key word or phrase of the first active region in response to the language learner selecting the key word or phrase of the first active region; instructions for causing the computer to enable the language learner to select one of the linguistic choices in the first menu; instructions for causing the computer to provide an error message when a linguistically incorrect choice is selected, the error message comprising explanation as to why the selection was incorrect; instructions for causing the computer to replace the key word or phrase of the first active region with the selected linguistic choice when a correct linguistic choice is made; instructions for causing linguistic choices in a second menu associated with another of the active regions in the text to change corresponding to the selected correct choice from the first active region; instructions for causing the computer to enable a language learner to select the another of the active regions by selecting the corresponding key word or phrase of the another active region; instructions for causing the computer to display the second menu of linguistic choices corresponding to the key word or phrase of the another active region in response to the language learner selecting the keyword or phrase of the second active region; instructions for causing the computer to enable the language learner to select one of the linguistic choice in the second menu; and instructions for determining when a linguistic choice selected from a second menu is linguistically incompatible with the linguistic choice selected from the first menu, wherein each active region corresponds to a choice of content of the text that needs to be made by the language learner, and wherein another error message is provided when the linguistic choice selected from each of the remaining active regions is linguistically incompatible with the linguistic choice selected from the menu of previously selected menu choices.
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10. A computer program product comprising a computer readable medium having computer readable instructions embodied therein for causing a computer to provide language learning for a language learner, the instructions comprising: instructions for causing the computer to retrieve stored text; instructions for causing the computer to replace each of at least two portions of the text with a corresponding key word or phrase; instructions for causing the computer to display the text having the at least two key words or phrases with a plurality of active regions, each active region corresponding to a different one of the at least two key words or phrases, each active region being associated with a corresponding menu of linguistic choices, each keyword or phrase representing a type of answer selection in the associated menu, the linguistic choices of each menu comprising at least two correct choices and at least one incorrect choice; instructions for causing the computer to enable a language learner to select a first active region of the active regions by selecting the corresponding key word or phrase of the first active region; instructions for causing the computer to display a first menu of linguistic choices corresponding to the key word or phrase of the first active region in response to the language learner selecting the key word or phrase of the first active region; instructions for causing the computer to enable the language learner to select one of the linguistic choices in the first menu; instructions for causing the computer to provide an error message when a linguistically incorrect choice is selected, the error message comprising explanation as to why the selection was incorrect; instructions for causing the computer to replace the key word or phrase of the first active region with the selected linguistic choice when a correct linguistic choice is made; instructions for causing linguistic choices in a second menu associated with another of the active regions in the text to change corresponding to the selected correct choice from the first active region; instructions for causing the computer to enable a language learner to select the another of the active regions by selecting the corresponding key word or phrase of the another active region; instructions for causing the computer to display the second menu of linguistic choices corresponding to the key word or phrase of the another active region in response to the language learner selecting the keyword or phrase of the second active region; instructions for causing the computer to enable the language learner to select one of the linguistic choice in the second menu; and instructions for determining when a linguistic choice selected from a second menu is linguistically incompatible with the linguistic choice selected from the first menu, wherein each active region corresponds to a choice of content of the text that needs to be made by the language learner, and wherein another error message is provided when the linguistic choice selected from each of the remaining active regions is linguistically incompatible with the linguistic choice selected from the menu of previously selected menu choices. 13. The computer program product of claim 10 , wherein the text is a single literary unit, and the text is one of a phrase, a sentence, a paragraph, a poem, a sonnet, a song, a story, a lyric, a novel, a composition, and an expression.
| 0.5 |
8,566,044 | 1 | 5 |
1. A method, comprising: at an electronic device with a touch-sensitive display, the electronic device configured to execute at least a first software application and a second software application, the first software application including a first set of one or more gesture recognizers, the second software application including one or more views and a second set of one or more gesture recognizers, and respective gesture recognizers having corresponding gesture handlers: displaying at least a subset of the one or more views of the second software application; and while displaying at least the subset of the one or more views of the second software application: detecting a sequence of touch inputs on the touch-sensitive display, the sequence of touch inputs including a first portion of one or more touch inputs and a second portion of one or more touch inputs subsequent to the first portion; and during a first phase of detecting the sequence of touch inputs: delivering the first portion of one or more touch inputs to the first software application and the second software application; identifying from gesture recognizers in the first set, one or more matching gesture recognizers that recognize the first portion of one or more touch inputs; and processing the first portion of one or more touch inputs with one or more gesture handlers corresponding to the one or more matching gesture recognizers.
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1. A method, comprising: at an electronic device with a touch-sensitive display, the electronic device configured to execute at least a first software application and a second software application, the first software application including a first set of one or more gesture recognizers, the second software application including one or more views and a second set of one or more gesture recognizers, and respective gesture recognizers having corresponding gesture handlers: displaying at least a subset of the one or more views of the second software application; and while displaying at least the subset of the one or more views of the second software application: detecting a sequence of touch inputs on the touch-sensitive display, the sequence of touch inputs including a first portion of one or more touch inputs and a second portion of one or more touch inputs subsequent to the first portion; and during a first phase of detecting the sequence of touch inputs: delivering the first portion of one or more touch inputs to the first software application and the second software application; identifying from gesture recognizers in the first set, one or more matching gesture recognizers that recognize the first portion of one or more touch inputs; and processing the first portion of one or more touch inputs with one or more gesture handlers corresponding to the one or more matching gesture recognizers. 5. The method of claim 1 , including: during a second phase of detecting the sequence of touch inputs, subsequent to the first phase: delivering the second portion of one or more touch inputs to the first software application without delivering the second portion of one or more touch inputs to the second software application; identifying from the one or more matching gesture recognizers a second matching gesture recognizer that recognizes the sequence of touch inputs; and processing the sequence of touch inputs with a gesture handler corresponding to the respective matching gesture recognizer.
| 0.5 |
8,037,086 | 11 | 12 |
11. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a pair of terms that includes a term and a candidate synonym of the term; determining that the terms of the pair have been identified as being potentially non-synonymous; evaluating the pair of terms using one or more penalty criteria that are only applied to terms that are identified as being potentially non-synonymous, comprising determining a quantity of switches that have occurred between queries that include the term and queries that include the candidate synonym of the term; selecting a first threshold if the pair of terms satisfies the penalty criteria, or a second threshold if the pair of terms does not satisfy the penalty criteria, wherein the first threshold is a same threshold that is applied to pairs of terms that are not identified as being potentially non-synonymous, and wherein the second threshold is higher than the first threshold; and determining that the terms of the pair are synonyms when the selected threshold is exceeded.
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11. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a pair of terms that includes a term and a candidate synonym of the term; determining that the terms of the pair have been identified as being potentially non-synonymous; evaluating the pair of terms using one or more penalty criteria that are only applied to terms that are identified as being potentially non-synonymous, comprising determining a quantity of switches that have occurred between queries that include the term and queries that include the candidate synonym of the term; selecting a first threshold if the pair of terms satisfies the penalty criteria, or a second threshold if the pair of terms does not satisfy the penalty criteria, wherein the first threshold is a same threshold that is applied to pairs of terms that are not identified as being potentially non-synonymous, and wherein the second threshold is higher than the first threshold; and determining that the terms of the pair are synonyms when the selected threshold is exceeded. 12. The system of claim 11 , wherein the determining that the terms of the pair have been identified as being potentially non-synonymous comprises determining that the terms occur in a list of terms that are potentially non-synonymous.
| 0.716184 |
8,150,835 | 1 | 6 |
1. A method comprising: receiving queries over information sources; for each of the queries, generating a polynomial by defining each query against the information sources as input parameters in polynomial form; providing irreducible polynomials over a finite field of a degree of orthogonality by factoring polynomials generated from the queries; adjusting the degree of orthogonality of the irreducible polynomials to provide adjusted irreducible polynomials, each of which is a signature and corresponds to a signature fragment, such that the signature fragments have overlapping portions; and causing at least in part storage of the signatures or the signature fragments in a signature domain over an information space.
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1. A method comprising: receiving queries over information sources; for each of the queries, generating a polynomial by defining each query against the information sources as input parameters in polynomial form; providing irreducible polynomials over a finite field of a degree of orthogonality by factoring polynomials generated from the queries; adjusting the degree of orthogonality of the irreducible polynomials to provide adjusted irreducible polynomials, each of which is a signature and corresponds to a signature fragment, such that the signature fragments have overlapping portions; and causing at least in part storage of the signatures or the signature fragments in a signature domain over an information space. 6. The method of claim 1 , wherein the signature fragment constitutes a finest lossless component in an information representation format or structure that has one or more overlapping portions with one or more other signature fragments.
| 0.5 |
7,587,387 | 7 | 8 |
7. A system for displaying sources of a fact, comprising: one or more processors; memory; and one or more programs stored in the memory, the one or more programs comprising instructions for implementing: a query receiver to receive a user-formulated factual query, the factual query including one or more query terms and information identifying source documents that include one or more query terms of the factual query and one or more of the factual answer terms of the answer; said answer identifier additionally searching a document database distinct from the fact repository to identify documents matching the user formulated factual query; an answer identifier to identify, from a fact repository, an answer to the factual query, the answer including one or more factual answer terms; a source document identifier, for execution after the answer identifier identifies the answer, to access at least one of the source documents in the document database distinct from the fact repository; a snippet generator to generate a snippet for at least one of the source document, the snippet including one or more query terms of the factual query and one or more of the factual answer terms of the answer; and a response generator to generate a response including the snippet, wherein the snippet itself provides factual information that answers the factual query and information identifying at least a subset of the documents of the documents identified from the document database.
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7. A system for displaying sources of a fact, comprising: one or more processors; memory; and one or more programs stored in the memory, the one or more programs comprising instructions for implementing: a query receiver to receive a user-formulated factual query, the factual query including one or more query terms and information identifying source documents that include one or more query terms of the factual query and one or more of the factual answer terms of the answer; said answer identifier additionally searching a document database distinct from the fact repository to identify documents matching the user formulated factual query; an answer identifier to identify, from a fact repository, an answer to the factual query, the answer including one or more factual answer terms; a source document identifier, for execution after the answer identifier identifies the answer, to access at least one of the source documents in the document database distinct from the fact repository; a snippet generator to generate a snippet for at least one of the source document, the snippet including one or more query terms of the factual query and one or more of the factual answer terms of the answer; and a response generator to generate a response including the snippet, wherein the snippet itself provides factual information that answers the factual query and information identifying at least a subset of the documents of the documents identified from the document database. 8. The system of claim 7 , wherein the response generator further includes instructions to highlight within the generated snippet the one or more terms of the factual query and the one or more factual answer terms of the answer.
| 0.747228 |
7,478,038 | 9 | 10 |
9. The method of claim 8 wherein generating background n-gram class count data based on the background data and the semantic entities and classes thereof comprises counting unique class level n-grams of the tagged background data.
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9. The method of claim 8 wherein generating background n-gram class count data based on the background data and the semantic entities and classes thereof comprises counting unique class level n-grams of the tagged background data. 10. The method of claim 9 wherein generating background n-gram class count data based on the background data and the semantic entities and classes thereof comprises discarding some class n-grams from the tagged background data.
| 0.5 |
9,710,461 | 10 | 12 |
10. A non-transitory computer-readable storage medium having computer-readable instructions, which when executed by a receiving computing device, cause the receiving computing device to provide a graphical user interface configured to: receive, via a Local Area Network (LAN) connection, a stream of text from a transmitting device remote to the receiving computing device, the stream of text transmitted to the receiving computing device in response to text data being received by the transmitting device, wherein the stream of text corresponds to a media content item being actively displayed by the transmitting device, wherein the media content item includes video data, and wherein the stream of text is provided to the receiving computing device via the LAN connection independent of the video data, and wherein the receiving computing device does not receive the video data; perform, using scripting instructions provided to the graphical user interface, natural language processing of the stream of text to extract content terms, in response to receiving the stream of text from the transmitting device; perform a query using the content terms to locate and obtain a set of related content, wherein the set of related content is automatically accessed and delivered from the media content source based on pre-established user preferences; and output, concurrently in time with the active display of the video data by the transmitting device, the related content in the graphical user interface of the receiving computing device, wherein the output of the set of related content is automatically displayed by the receiving computing device.
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10. A non-transitory computer-readable storage medium having computer-readable instructions, which when executed by a receiving computing device, cause the receiving computing device to provide a graphical user interface configured to: receive, via a Local Area Network (LAN) connection, a stream of text from a transmitting device remote to the receiving computing device, the stream of text transmitted to the receiving computing device in response to text data being received by the transmitting device, wherein the stream of text corresponds to a media content item being actively displayed by the transmitting device, wherein the media content item includes video data, and wherein the stream of text is provided to the receiving computing device via the LAN connection independent of the video data, and wherein the receiving computing device does not receive the video data; perform, using scripting instructions provided to the graphical user interface, natural language processing of the stream of text to extract content terms, in response to receiving the stream of text from the transmitting device; perform a query using the content terms to locate and obtain a set of related content, wherein the set of related content is automatically accessed and delivered from the media content source based on pre-established user preferences; and output, concurrently in time with the active display of the video data by the transmitting device, the related content in the graphical user interface of the receiving computing device, wherein the output of the set of related content is automatically displayed by the receiving computing device. 12. The computer-readable storage medium of claim 10 , wherein the stream of text associated with the video data is provided by a real-time datastream associated with the video data.
| 0.74221 |
8,518,085 | 1 | 8 |
1. An adaptive spinal rod adapted to stabilize a spinal segment, wherein the spinal rod comprises: an elongated rod having a first end, a second end and a longitudinal rod axis; an aperture at the first end of the rod; a partially-spherical mount contained in the aperture, the partially-spherical mount can rotate and pivot within the aperture, wherein the partially-spherical mount has a central axis perpendicular to a base side of the partially-spherical mount; the partially-spherical mount having an elongated slot adapted to receive a post of a bone anchor, wherein the elongated slot has a first dimension perpendicular to the central axis of the partially-spherical mount and a second dimension parallel to the central axis of the partial-spherical mount, wherein the post is loosely coupled to the elongated slot such that the post can slide in the first dimension and the second dimension of the elongated slot, and rotate in the elongated slot; and wherein the bone anchor can be secured relative to the partially-spherical mount while permitting the bone anchor to change in angle relative to the longitudinal rod axis.
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1. An adaptive spinal rod adapted to stabilize a spinal segment, wherein the spinal rod comprises: an elongated rod having a first end, a second end and a longitudinal rod axis; an aperture at the first end of the rod; a partially-spherical mount contained in the aperture, the partially-spherical mount can rotate and pivot within the aperture, wherein the partially-spherical mount has a central axis perpendicular to a base side of the partially-spherical mount; the partially-spherical mount having an elongated slot adapted to receive a post of a bone anchor, wherein the elongated slot has a first dimension perpendicular to the central axis of the partially-spherical mount and a second dimension parallel to the central axis of the partial-spherical mount, wherein the post is loosely coupled to the elongated slot such that the post can slide in the first dimension and the second dimension of the elongated slot, and rotate in the elongated slot; and wherein the bone anchor can be secured relative to the partially-spherical mount while permitting the bone anchor to change in angle relative to the longitudinal rod axis. 8. The adaptive spinal rod of claim 1 , wherein the elongated slot is adapted to allow the bone anchor to slide, pivot and rotate relative to the elongated slot in the adaptive spinal rod.
| 0.807377 |
8,160,977 | 1 | 7 |
1. A computer implemented method for estimating a probability that a future event will occur based on user input, the method comprises: decomposing by one or more computer systems a data input stream to build a first database of precursor data to build at least one predictive model; building by the one or more computer systems at least one model generated by a model building process using the precursor data in the precursor database, with the at least one model being a model that produces predictions of the likelihood of an event occurring in the future; and storing by the one or more computer systems the at least one model in a second database that stores models, with the second database being searchable to permit the at least one model in the second database to be accessed by users; and calculating by the one or more computer systems accuracy of the at least one model against historical data.
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1. A computer implemented method for estimating a probability that a future event will occur based on user input, the method comprises: decomposing by one or more computer systems a data input stream to build a first database of precursor data to build at least one predictive model; building by the one or more computer systems at least one model generated by a model building process using the precursor data in the precursor database, with the at least one model being a model that produces predictions of the likelihood of an event occurring in the future; and storing by the one or more computer systems the at least one model in a second database that stores models, with the second database being searchable to permit the at least one model in the second database to be accessed by users; and calculating by the one or more computer systems accuracy of the at least one model against historical data. 7. The method of claim 1 further comprising: calculating the accuracy of the model using a k-fold cross-validation.
| 0.678771 |
9,374,284 | 1 | 18 |
1. A computer-implemented method for reporting a performance score for a Web page, comprising computer-implemented operations of: sending, by a Web browser tool on a first computing system a request to a second computing system to load data from the Web page, such that the first computing system causes the second computing system to respond by sending the data to load the Web page in the Web browser tool of the first computing system; heuristically calculating a performance sub-score for each of a plurality of Web page performance metrics; combining said performance sub-scores to produce at least one interpretable Web page performance score; and compiling and outputting a report of the at least one interpretable Web page performance score.
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1. A computer-implemented method for reporting a performance score for a Web page, comprising computer-implemented operations of: sending, by a Web browser tool on a first computing system a request to a second computing system to load data from the Web page, such that the first computing system causes the second computing system to respond by sending the data to load the Web page in the Web browser tool of the first computing system; heuristically calculating a performance sub-score for each of a plurality of Web page performance metrics; combining said performance sub-scores to produce at least one interpretable Web page performance score; and compiling and outputting a report of the at least one interpretable Web page performance score. 18. The method according to claim 1 , further comprising entering a revisit time, which is a measurement of how frequently a visitor returns to the Web page.
| 0.582447 |
9,235,659 | 1 | 4 |
1. A method for Computer Aided Design (CAD) editing performed by a data processing system, comprising: receiving a CAD model including a plurality of entities; receiving a user input including a selection of at least one entity and a movement of the selected entity; applying any basic condition behaviors that correspond to the user input; applying any optional condition behaviors that correspond to the user input; building a variational system to be solved based on the user input, any applied basic condition behaviors, and any optional condition behaviors; performing a variational solve on the variational system to produce an edited CAD model; and storing the edited CAD model.
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1. A method for Computer Aided Design (CAD) editing performed by a data processing system, comprising: receiving a CAD model including a plurality of entities; receiving a user input including a selection of at least one entity and a movement of the selected entity; applying any basic condition behaviors that correspond to the user input; applying any optional condition behaviors that correspond to the user input; building a variational system to be solved based on the user input, any applied basic condition behaviors, and any optional condition behaviors; performing a variational solve on the variational system to produce an edited CAD model; and storing the edited CAD model. 4. The method of claim 1 , wherein building the variational system includes ordering and applying preferences.
| 0.817276 |
9,477,767 | 12 | 19 |
12. A system including memory and one or more processors operable to execute instructions, stored in the memory, including instructions to: receive a sequence of one or more characters entered into a search field on a computing device, wherein the sequence of characters represents a first partial query; provide a first list of query completions for the first partial query for display on the computing device; receive one or more additional characters entered into the search field upon display of the first list, wherein the sequence of characters and the additional characters cumulatively represent a second partial query; obtain a second list of query completions for the second partial query; identify, for each of one or more query completions in the second list, an initial ranking score for the query completion for the second partial query; identify one or more query completions in the second list that appear in the first list; calculate demotion scores for the identified query completions, wherein a demotion score for a particular identified query completion is a function of both: the initial ranking score for the particular identified query completion, and a value that is based on a period of time between when the first list was displayed and when the additional characters were entered; use the demotion scores to demote one or more of the identified query completions to a lesser position within the second list, thereby forming a refined second list; and provide the refined second list of query completions for the second list of query completions for display on the computing device.
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12. A system including memory and one or more processors operable to execute instructions, stored in the memory, including instructions to: receive a sequence of one or more characters entered into a search field on a computing device, wherein the sequence of characters represents a first partial query; provide a first list of query completions for the first partial query for display on the computing device; receive one or more additional characters entered into the search field upon display of the first list, wherein the sequence of characters and the additional characters cumulatively represent a second partial query; obtain a second list of query completions for the second partial query; identify, for each of one or more query completions in the second list, an initial ranking score for the query completion for the second partial query; identify one or more query completions in the second list that appear in the first list; calculate demotion scores for the identified query completions, wherein a demotion score for a particular identified query completion is a function of both: the initial ranking score for the particular identified query completion, and a value that is based on a period of time between when the first list was displayed and when the additional characters were entered; use the demotion scores to demote one or more of the identified query completions to a lesser position within the second list, thereby forming a refined second list; and provide the refined second list of query completions for the second list of query completions for display on the computing device. 19. The system of claim 12 , wherein the one or more additional characters is a single character.
| 0.953853 |
8,886,661 | 14 | 17 |
14. The information extraction method according to claim 13 , wherein the pattern determining step determines a forward character string and a backward character string of the phrase included in the input word list as patterns, the phrase candidate extracting step extracts a character string interposed between the forward character string and the backward character string from the document and determines the extracted character string as a candidate of a phrase, and the phrase selecting step selects a phrase of an output subject from the candidates of the phrases, which are extracted by the phrase candidate extracting step.
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14. The information extraction method according to claim 13 , wherein the pattern determining step determines a forward character string and a backward character string of the phrase included in the input word list as patterns, the phrase candidate extracting step extracts a character string interposed between the forward character string and the backward character string from the document and determines the extracted character string as a candidate of a phrase, and the phrase selecting step selects a phrase of an output subject from the candidates of the phrases, which are extracted by the phrase candidate extracting step. 17. The information extraction method according to claim 14 , wherein the phrase selecting step calculates a phrase score indicating a value of a degree of importance of a candidate of the pattern used in specifying the candidate of the phrase or the amount of documents where the candidate of the phrase appears for each of the candidates of the phrases, sorts the candidates of the phrases in the order of high phrase scores, and selects the candidate of the phrase at high ranks of a predetermined ratio as the phrase of the output subject.
| 0.5 |
10,075,742 | 21 | 22 |
21. The method for extracting and tracking media tags within video content, comprising the steps of: receiving video content with a server from one or more content sources; saving the video content in a storage; extracting on the server at least one frame of the video content; detecting on the server one or more unknown text within the frame and creating one or more images, each of the one or more images associated with one of the one or more unknown text; retrieving metadata associated with the one or more unknown text appearing in the frame; scanning the one or more images using optical character recognition and converting the one or more images into one or more known text, each of the one or more known text associated with one of the one or more unknown text; and determining whether the one or more known text is a media tag.
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21. The method for extracting and tracking media tags within video content, comprising the steps of: receiving video content with a server from one or more content sources; saving the video content in a storage; extracting on the server at least one frame of the video content; detecting on the server one or more unknown text within the frame and creating one or more images, each of the one or more images associated with one of the one or more unknown text; retrieving metadata associated with the one or more unknown text appearing in the frame; scanning the one or more images using optical character recognition and converting the one or more images into one or more known text, each of the one or more known text associated with one of the one or more unknown text; and determining whether the one or more known text is a media tag. 22. The method of claim 21 , wherein the step of detecting comprises the steps of: identifying one or more regions of the frame where the one or more unknown text is displayed; and extracting the one or more regions from the frame for creating the one or more images.
| 0.708515 |
8,571,932 | 1 | 2 |
1. A computer-implemented method for determining at least one supplemental advertisement to be presented on an advertiser landing Web page, the advertiser landing page being referenced from a user selected advertisement, comprising: a) accepting, by a computer system including one or more computers on a network, advertiser policies provided by an advertiser associated with the advertiser landing Web page, the advertiser policies including 1) a condition that supplemental advertisements on the advertiser landing page must not include any links to another document, and 2) a condition that supplemental advertisements on the advertiser landing page advertise a different product or service than the product or service advertised in the user selected advertisement; b) accepting, by the computer system, search query information sourced from a user device; c) generating, by the computer system and for presentation on the user device, a document with search results determined using the search query information and at least one advertisement determined, by the computer system and using the search query information, wherein each of the at least one advertisement includes a reference to an advertiser landing Web page and wherein each of the at least one advertisement advertises a product or service; d) transmitting, by the computer system and to induce presentation on the user device, the generated document including the search results and the at least one advertisement; e) accepting, by the computer system, a selection, sourced from the user device, of one of the at least one advertisement; f) determining at least one supplemental advertisement, by the computer system, using 1) the search query information, and 2) the accepted advertiser policies including the condition that the at least one supplemental advertisement must not include any links to another document, and the condition that the at least one supplemental advertisement advertises a different product or service than the product or service advertised in the selected at least one advertisement; and g) generating, by the computer system and for presentation on the user device, the advertiser landing Web page referenced from the selected at least one advertisement, the advertiser landing Web page including the at least one supplemental advertisement determined by the computer system.
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1. A computer-implemented method for determining at least one supplemental advertisement to be presented on an advertiser landing Web page, the advertiser landing page being referenced from a user selected advertisement, comprising: a) accepting, by a computer system including one or more computers on a network, advertiser policies provided by an advertiser associated with the advertiser landing Web page, the advertiser policies including 1) a condition that supplemental advertisements on the advertiser landing page must not include any links to another document, and 2) a condition that supplemental advertisements on the advertiser landing page advertise a different product or service than the product or service advertised in the user selected advertisement; b) accepting, by the computer system, search query information sourced from a user device; c) generating, by the computer system and for presentation on the user device, a document with search results determined using the search query information and at least one advertisement determined, by the computer system and using the search query information, wherein each of the at least one advertisement includes a reference to an advertiser landing Web page and wherein each of the at least one advertisement advertises a product or service; d) transmitting, by the computer system and to induce presentation on the user device, the generated document including the search results and the at least one advertisement; e) accepting, by the computer system, a selection, sourced from the user device, of one of the at least one advertisement; f) determining at least one supplemental advertisement, by the computer system, using 1) the search query information, and 2) the accepted advertiser policies including the condition that the at least one supplemental advertisement must not include any links to another document, and the condition that the at least one supplemental advertisement advertises a different product or service than the product or service advertised in the selected at least one advertisement; and g) generating, by the computer system and for presentation on the user device, the advertiser landing Web page referenced from the selected at least one advertisement, the advertiser landing Web page including the at least one supplemental advertisement determined by the computer system. 2. The computer-implemented method of claim 1 wherein the advertiser landing Web page referenced from the selected at least one advertisement includes content, and wherein the at least one supplemental advertisement is determined using at least the content of the advertiser landing Web page in addition to (1) the search query information and (2) the accepted advertiser policies.
| 0.749342 |
8,001,125 | 17 | 18 |
17. The apparatus of claim 15 , wherein defining the relationship further involves expressing the strength of the relationship between the initial tag and the second tag using a percentage scale.
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17. The apparatus of claim 15 , wherein defining the relationship further involves expressing the strength of the relationship between the initial tag and the second tag using a percentage scale. 18. The apparatus of claim 17 , wherein defining the relationship involves specifying one or more of the following: that the initial tag and the second tag are unrelated; that the initial tag and the second tag specify loosely-related concepts; that the initial tag and the second tag specify closely-related concepts; and/or that the initial tag and the second tag are synonymous.
| 0.5 |
9,875,234 | 1 | 17 |
1. A method programmed in a non-transitory memory of a device comprising: a. capturing social networking information, including the social networking information of a user, from a social networking system; b. analyzing the social networking information of the user, including: i. determining interests of the user; and ii. storing the interests of the user in a data structure; c. processing the social networking information, including parsing the social networking information into parsed information; d. fact checking, with the device, the social networking information by comparing the parsed information with source information to generate fact checking results, including indicating when the parsed information is factually accurate and indicating when the parsed information is factually inaccurate; e. summarizing the social networking information to generate a summary of the social networking information, including determining total strengths of sentences within the social networking information, wherein a total strength of a sentence is based on a strength of a lexical chain, the interests of the user, and factual accuracy of the sentence based on the fact checking results generated by fact checking the social networking information, wherein summarizing the social networking information utilizes the interests of the user stored in the data structure by increasing the strength of the lexical chain when a word in the lexical chain matches at least one of the interests in the data structure, wherein lexical chaining includes selecting a set of candidate words or phrases, finding an appropriate chain using relatedness criteria among members of chains for each candidate word, and inserting a word in the lexical chain when the word is found, wherein the total strength of the sentence is increased when the sentence is factually accurate, wherein the summary of the social networking information includes the fact checking results; and f. providing the summary of the social networking information in real-time.
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1. A method programmed in a non-transitory memory of a device comprising: a. capturing social networking information, including the social networking information of a user, from a social networking system; b. analyzing the social networking information of the user, including: i. determining interests of the user; and ii. storing the interests of the user in a data structure; c. processing the social networking information, including parsing the social networking information into parsed information; d. fact checking, with the device, the social networking information by comparing the parsed information with source information to generate fact checking results, including indicating when the parsed information is factually accurate and indicating when the parsed information is factually inaccurate; e. summarizing the social networking information to generate a summary of the social networking information, including determining total strengths of sentences within the social networking information, wherein a total strength of a sentence is based on a strength of a lexical chain, the interests of the user, and factual accuracy of the sentence based on the fact checking results generated by fact checking the social networking information, wherein summarizing the social networking information utilizes the interests of the user stored in the data structure by increasing the strength of the lexical chain when a word in the lexical chain matches at least one of the interests in the data structure, wherein lexical chaining includes selecting a set of candidate words or phrases, finding an appropriate chain using relatedness criteria among members of chains for each candidate word, and inserting a word in the lexical chain when the word is found, wherein the total strength of the sentence is increased when the sentence is factually accurate, wherein the summary of the social networking information includes the fact checking results; and f. providing the summary of the social networking information in real-time. 17. The method of claim 1 wherein the social networking information includes a plurality of social networking content, and each social networking content of the plurality of social networking content receives a factual accuracy rating based on fact checking, further wherein a social networking content of the plurality of social networking content with a lowest factual accuracy rating is summarized with a base number of sentences, and the social networking content with higher factual accuracy ratings are summarized with the base number of sentences plus additional sentences such that the social networking content with the highest factual accuracy rating is summarized with the base number of sentences plus a maximum number of additional sentences.
| 0.57774 |
8,781,989 | 1 | 3 |
1. A computer based system for predicting a data value, said system comprising: a processor capable of executing machine instructions; the machine instructions including a means for predicting a predicted data value of a first data set at a predicted dimension value utilizing a focus topic profile and a means for analyzing a second data set using a latent variable method; the latent variable method using at least one focus feature from a third data set to create at least one focus topic from the second data set; and the focus topic profile comprises at least one focus topic value of the at least one focus topic from the second data set.
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1. A computer based system for predicting a data value, said system comprising: a processor capable of executing machine instructions; the machine instructions including a means for predicting a predicted data value of a first data set at a predicted dimension value utilizing a focus topic profile and a means for analyzing a second data set using a latent variable method; the latent variable method using at least one focus feature from a third data set to create at least one focus topic from the second data set; and the focus topic profile comprises at least one focus topic value of the at least one focus topic from the second data set. 3. The computer based system of claim 1 wherein the means for predicting the predicted data value comprises using a predictive model of a temporal relationship of the focus topic profile and the first data set.
| 0.522727 |
9,996,592 | 15 | 17 |
15. A computer program product, the computer program product being tangibly embodied on a non-transitory computer-readable storage medium and comprising instructions that, when executed, are configured to: select a plurality of queries, each query structured for repeated application against a database to yield a query result that is updated over time with each repeated application; identify query parts of individual queries; determine for each query, a relation, if any, of an included query part to any query part of remaining queries of the plurality of queries; create, for each query, a query relationship data structure in which the query is related to at least one other query of the plurality of queries, based on the determined relation of a query part of the query and a query part of the at least one other query of the plurality of queries; store the query relationship data structures in a query relationship data structure (RELSTRUCT) repository; calculate, for a first query and a second query of the plurality of queries, a dependency between a first query result and a second query result thereof, based on the determined relation between the query parts of the first query and the second query as determined from a corresponding RELSTRUCT; and visually display the first query result, the second query result, and the dependency therebetween, including maintaining the dependency with each repeated application of the first query and the second query, using the stored, corresponding RELSTRUCT, wherein the first query result includes a first Key Performance Indicator (KPI) representing a state or value for an entity in a business context, and the second query result includes a second KPI.
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15. A computer program product, the computer program product being tangibly embodied on a non-transitory computer-readable storage medium and comprising instructions that, when executed, are configured to: select a plurality of queries, each query structured for repeated application against a database to yield a query result that is updated over time with each repeated application; identify query parts of individual queries; determine for each query, a relation, if any, of an included query part to any query part of remaining queries of the plurality of queries; create, for each query, a query relationship data structure in which the query is related to at least one other query of the plurality of queries, based on the determined relation of a query part of the query and a query part of the at least one other query of the plurality of queries; store the query relationship data structures in a query relationship data structure (RELSTRUCT) repository; calculate, for a first query and a second query of the plurality of queries, a dependency between a first query result and a second query result thereof, based on the determined relation between the query parts of the first query and the second query as determined from a corresponding RELSTRUCT; and visually display the first query result, the second query result, and the dependency therebetween, including maintaining the dependency with each repeated application of the first query and the second query, using the stored, corresponding RELSTRUCT, wherein the first query result includes a first Key Performance Indicator (KPI) representing a state or value for an entity in a business context, and the second query result includes a second KPI. 17. The computer program product of claim 15 , wherein the instructions, when executed, are further configured to cause the at least one processor to store the query relationship data structures in the query relationship data structure (RELSTRUCT) repository in a hierarchical manner, in which at least some of the query relationship data structures are connected, in one or both of a parent or child relationship, to at least one other query relationship data structure.
| 0.5 |
8,244,767 | 8 | 9 |
8. A computer-readable storage medium containing program instructions that, when executed by a computer system, cause the computer system to execute a method of analyzing a plurality of documents in a corpus of documents, the method comprising: selecting a current document from the corpus; computing a composite hash value for the current document; determining whether a previous document having the same composite hash value as the current document has been analyzed; in the event that a previous document having the same composite hash value as the current document has not been analyzed, analyzing the current document, wherein analyzing the current document includes determining one or more items of analytic metadata to be associated with the current document; in the event that a previous document having the same composite hash value as the current document has been analyzed, associating the current document with one or more items of analytic metadata determined from analyzing the previous document; storing a representation of the association between the one or more items of analytic metadata and the current document; and repeating the acts of selecting, computing, determining, either analyzing or associating, and storing until all of the plurality of documents have been analyzed.
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8. A computer-readable storage medium containing program instructions that, when executed by a computer system, cause the computer system to execute a method of analyzing a plurality of documents in a corpus of documents, the method comprising: selecting a current document from the corpus; computing a composite hash value for the current document; determining whether a previous document having the same composite hash value as the current document has been analyzed; in the event that a previous document having the same composite hash value as the current document has not been analyzed, analyzing the current document, wherein analyzing the current document includes determining one or more items of analytic metadata to be associated with the current document; in the event that a previous document having the same composite hash value as the current document has been analyzed, associating the current document with one or more items of analytic metadata determined from analyzing the previous document; storing a representation of the association between the one or more items of analytic metadata and the current document; and repeating the acts of selecting, computing, determining, either analyzing or associating, and storing until all of the plurality of documents have been analyzed. 9. The computer-readable storage medium of claim 8 wherein the method further comprises: transforming the current document to a content vector having a plurality of components; for each of a number N of subsets of the components of the content vector, computing a hash vector component by applying a hash function to that subset of the components of the content vector; and applying a hash function to the N hash vector components.
| 0.5 |
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