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9,213,771 | 7 | 8 | 7. The method of claim 1 wherein searching the question-answer paired data from the question-answer paired knowledge database comprises: generating a query statement based on one or more properties associated with the input question, wherein the query statement is executable to perform a full text search of the question-answer paired data to generate search results. | 7. The method of claim 1 wherein searching the question-answer paired data from the question-answer paired knowledge database comprises: generating a query statement based on one or more properties associated with the input question, wherein the query statement is executable to perform a full text search of the question-answer paired data to generate search results. 8. The method of claim 7 wherein the full text search comprises a fuzzy search based on an n-gram algorithm. | 0.597015 |
8,064,696 | 16 | 19 | 16. A random access memory device, a flash memory device, or a read-only memory device having instructions for at least one processor of a processing device recorded thereon, such that when the instructions are executed by the at least one processor, the processing device performs a method comprising: ordering a plurality of strokes of a region according to an ordering relation, the ordering relation including a left-right ordering relation, the plurality of strokes forming a mathematical expression, the instructions for ordering further comprising: defining a first array of strokes {a 1 , a 2 , . . . , a n } such that a i , is less than or equal to a i+1 if and only if a leftmost coordinate of the stroke a i , within a smallest axis aligned rectangle including the stroke a i , is less than or equal to a leftmost coordinate of the stroke a i+1 , within a smallest axis aligned rectangle including the stroke a i+1 , where a set S of n strokes is equal to (s 1 , s 2 , . . . , s n }, {a 1 , a 2 , . . . , a n } is a sorted permutation of the set S and i is a value from 1 to (n−1); using the first array of strokes and applying a plurality of rules to the region, including the plurality of strokes, to partition the region into a plurality of regions, each of the plurality of regions including a subset of the plurality of strokes, the plurality of rules being based, at least in part, on expected positioning of mathematical symbols and expected types of strokes representing a mathematical expression; and recognizing at least one mathematical symbol, each of the at least one mathematical symbol being included in one of the plurality of regions. | 16. A random access memory device, a flash memory device, or a read-only memory device having instructions for at least one processor of a processing device recorded thereon, such that when the instructions are executed by the at least one processor, the processing device performs a method comprising: ordering a plurality of strokes of a region according to an ordering relation, the ordering relation including a left-right ordering relation, the plurality of strokes forming a mathematical expression, the instructions for ordering further comprising: defining a first array of strokes {a 1 , a 2 , . . . , a n } such that a i , is less than or equal to a i+1 if and only if a leftmost coordinate of the stroke a i , within a smallest axis aligned rectangle including the stroke a i , is less than or equal to a leftmost coordinate of the stroke a i+1 , within a smallest axis aligned rectangle including the stroke a i+1 , where a set S of n strokes is equal to (s 1 , s 2 , . . . , s n }, {a 1 , a 2 , . . . , a n } is a sorted permutation of the set S and i is a value from 1 to (n−1); using the first array of strokes and applying a plurality of rules to the region, including the plurality of strokes, to partition the region into a plurality of regions, each of the plurality of regions including a subset of the plurality of strokes, the plurality of rules being based, at least in part, on expected positioning of mathematical symbols and expected types of strokes representing a mathematical expression; and recognizing at least one mathematical symbol, each of the at least one mathematical symbol being included in one of the plurality of regions. 19. The random access memory device, the flash memory device, or the read-only memory device of claim 16 , wherein one of the plurality of rules is for partitioning at least one of the plurality of strokes forming a superscript, the partitioning forming a first region of the plurality of regions including the at least one of the plurality of strokes forming the superscript and a second region of the plurality of regions including at least one other one of the plurality of strokes forming a base of the superscript. | 0.589399 |
9,843,544 | 1 | 4 | 1. In an environment wherein electronic messages having written text may be sent with or without an attachment, a computer-implemented method for determining whether an electronic message should have an attachment, the method comprising: inspecting the written text in the electronic message to detect any words which are in a database of predetermined key terms; inspecting the written text to detect any phrases which are in the database of predetermined key terms; if a word which was detected in the written text is in a database of predetermined negative terms then disregarding the word which was detected; if a phrase which was detected in the written text is in the database of predetermined negative terms then disregarding the phrase which was detected; and if any word which was detected in the written text has not been disregarded, or if any phrase which was detected in the written text has not been disregarded, then providing a suggestion that the electronic message may need an attachment. | 1. In an environment wherein electronic messages having written text may be sent with or without an attachment, a computer-implemented method for determining whether an electronic message should have an attachment, the method comprising: inspecting the written text in the electronic message to detect any words which are in a database of predetermined key terms; inspecting the written text to detect any phrases which are in the database of predetermined key terms; if a word which was detected in the written text is in a database of predetermined negative terms then disregarding the word which was detected; if a phrase which was detected in the written text is in the database of predetermined negative terms then disregarding the phrase which was detected; and if any word which was detected in the written text has not been disregarded, or if any phrase which was detected in the written text has not been disregarded, then providing a suggestion that the electronic message may need an attachment. 4. The method of claim 1 wherein inspecting the written text to detect any words which are in the database of predetermined key terms comprises: accessing the database of predetermined key terms, the database comprising predetermined words; and inspecting the written text in the electronic message for at least one of the predetermined words. | 0.528846 |
8,086,590 | 7 | 9 | 7. A computer-implemented method for providing product suggestion information, the computer-implemented method using a computing device having memory, processor, and database subsystems and comprising: crawling a plurality of sources via a computer system processor; extracting product information comprising product identifiers, name, size, color, and price for each individual product included in the plurality of sources; storing the product identifiers, name, size, color, and price for each individual product in a product database; categorizing each individual product based on a type, a trade name, and the price; generating a product suggestions message in response to a specific product query from a user, the product suggestions message comprising one or more marked product suggestions linked to a respective one or more product details pages; and continuously returning the one or more product details pages for each marked product suggestion stored in the product database that is relevant to partial query strings formulated by the user as the user inputs additional query strings until the user completes the query strings. | 7. A computer-implemented method for providing product suggestion information, the computer-implemented method using a computing device having memory, processor, and database subsystems and comprising: crawling a plurality of sources via a computer system processor; extracting product information comprising product identifiers, name, size, color, and price for each individual product included in the plurality of sources; storing the product identifiers, name, size, color, and price for each individual product in a product database; categorizing each individual product based on a type, a trade name, and the price; generating a product suggestions message in response to a specific product query from a user, the product suggestions message comprising one or more marked product suggestions linked to a respective one or more product details pages; and continuously returning the one or more product details pages for each marked product suggestion stored in the product database that is relevant to partial query strings formulated by the user as the user inputs additional query strings until the user completes the query strings. 9. The computer-implemented method of claim 7 , wherein the plurality of sources include electronic product documents and non-electronic product documents. | 0.729021 |
8,862,582 | 15 | 16 | 15. The computer-readable storage device of claim 14 , wherein the scene description information comprises one of environmental data, chronologically relevant audio input to a network time difference of arrival data, and device orientation data. | 15. The computer-readable storage device of claim 14 , wherein the scene description information comprises one of environmental data, chronologically relevant audio input to a network time difference of arrival data, and device orientation data. 16. The computer-readable storage device of claim 15 , wherein the environmental data comprises one of time, color, object detection, temperature, received audio when the image was received by a device, and audio. | 0.5 |
9,892,725 | 9 | 12 | 9. The system of claim 8 , the an audio transcription tool coupled to the bus that when executing the instructions further causes the system to: compare the text data to the data structure, wherein the data structure comprises a dictionary; and determine a number of inaccurate words in the text data. | 9. The system of claim 8 , the an audio transcription tool coupled to the bus that when executing the instructions further causes the system to: compare the text data to the data structure, wherein the data structure comprises a dictionary; and determine a number of inaccurate words in the text data. 12. The system of claim 9 , wherein the determining the number of inaccurate words comprises identifying a number of words not found in the dictionary. | 0.5 |
9,685,161 | 13 | 14 | 13. The terminal according to claim 12 , wherein the computer processor is further configured to execute the instructions to: segment the original audio stream into a plurality of audio clips according to a preset speaker segmentation algorithm, wherein each audio clip of the plurality of audio clips comprises only audio information of a same speaker of the at least one speaker; and cluster, according to a preset speaker clustering algorithm, the audio clips that comprise only the same speaker of the at least one speaker, to generate an audio stream that comprises only the audio information of the same speaker of the at least one speaker. | 13. The terminal according to claim 12 , wherein the computer processor is further configured to execute the instructions to: segment the original audio stream into a plurality of audio clips according to a preset speaker segmentation algorithm, wherein each audio clip of the plurality of audio clips comprises only audio information of a same speaker of the at least one speaker; and cluster, according to a preset speaker clustering algorithm, the audio clips that comprise only the same speaker of the at least one speaker, to generate an audio stream that comprises only the audio information of the same speaker of the at least one speaker. 14. The terminal according to claim 13 , wherein the computer processor is further configured to execute the instructions to: obtain a matching degree between the audio stream of each speaker of the at least one speaker and the original voiceprint feature model according to the audio stream of each speaker of the at least one speaker and the original voiceprint feature model; and select an audio stream corresponding to a matching degree that is the highest and is greater than a preset matching threshold as the successfully matched audio stream. | 0.5 |
8,498,906 | 1 | 10 | 1. A method comprising: receiving at least two sets of attributes and values for a product through a communications network, each set of attributes representing quantifiable properties of the product and each set of values representing numerical quantities of the respective properties, wherein there is at least one difference between each of the sets of attributes and values; forming a collaborative component taxonomy instantiation, the taxonomy instantiation comprising a union of distinct attributes and values obtained from the at least two sets of attributes and values; associating a unique identifier with the formed collaborative component taxonomy instantiation; comparing the union of product attributes and values in the collaborative component taxonomy instantiation to product catalog information received from different computing systems through a communications network; associating the unique identifier with those matching products included in the received product catalog information based on the comparing; and distributing the unique identifier and the association with a corresponding matching product to each computing system having product catalog information containing the corresponding matching product through the communications network, wherein the unique identifier is associated with each matching product at each computing system through the distributing. | 1. A method comprising: receiving at least two sets of attributes and values for a product through a communications network, each set of attributes representing quantifiable properties of the product and each set of values representing numerical quantities of the respective properties, wherein there is at least one difference between each of the sets of attributes and values; forming a collaborative component taxonomy instantiation, the taxonomy instantiation comprising a union of distinct attributes and values obtained from the at least two sets of attributes and values; associating a unique identifier with the formed collaborative component taxonomy instantiation; comparing the union of product attributes and values in the collaborative component taxonomy instantiation to product catalog information received from different computing systems through a communications network; associating the unique identifier with those matching products included in the received product catalog information based on the comparing; and distributing the unique identifier and the association with a corresponding matching product to each computing system having product catalog information containing the corresponding matching product through the communications network, wherein the unique identifier is associated with each matching product at each computing system through the distributing. 10. The method of claim 1 , wherein the identifier is embedded in an electronic commerce document and sent via an exchange application to distribute the identifier. | 0.673307 |
7,895,275 | 21 | 22 | 21. The central server of claim 16 wherein to effect review of the digital content, the control system is further configured to: a) select a group of reviewers from the others of the plurality of authors for a review at a first quality level that is less than the target quality level based on the reviewer credentials; b) effect transfer of the digital content to user devices associated with the group of reviewers; c) receive feedback from the group of reviewers; d) determine whether the digital content is to be reviewed at a next quality level based on the feedback and the target quality level; and e) if the digital content is to be reviewed at the next quality level, repeat a)-e) for the next quality level. | 21. The central server of claim 16 wherein to effect review of the digital content, the control system is further configured to: a) select a group of reviewers from the others of the plurality of authors for a review at a first quality level that is less than the target quality level based on the reviewer credentials; b) effect transfer of the digital content to user devices associated with the group of reviewers; c) receive feedback from the group of reviewers; d) determine whether the digital content is to be reviewed at a next quality level based on the feedback and the target quality level; and e) if the digital content is to be reviewed at the next quality level, repeat a)-e) for the next quality level. 22. The central server of claim 21 wherein the control system is further configured to provide the feedback to the one of the plurality of authors based on the feedback from each of the groups of reviewers if the digital content is not to be reviewed at the next quality level. | 0.763248 |
9,658,931 | 23 | 24 | 23. A non-transitory computer-readable storage medium storing instructions for enabling a computer to implement a method for testing a computer system, the method comprising: receiving, at the computer, a representation of a graphical user interface of the remote system; and controlling, at the computer, a flow of execution based on a testing script, the flow of execution including: searching the received representation of the remote system graphical user interface for a graphical element based on an image analysis; and responsive to a result of searching the received representation of the remote system graphical user interface for the graphical element, automatically providing a signal through a communications channel to execute an emulated user input action on the remote system graphical user interface, wherein the input action is specified by a specific script command in the testing script. | 23. A non-transitory computer-readable storage medium storing instructions for enabling a computer to implement a method for testing a computer system, the method comprising: receiving, at the computer, a representation of a graphical user interface of the remote system; and controlling, at the computer, a flow of execution based on a testing script, the flow of execution including: searching the received representation of the remote system graphical user interface for a graphical element based on an image analysis; and responsive to a result of searching the received representation of the remote system graphical user interface for the graphical element, automatically providing a signal through a communications channel to execute an emulated user input action on the remote system graphical user interface, wherein the input action is specified by a specific script command in the testing script. 24. The non-transitory computer-readable storage medium of claim 23 , wherein the method further comprises: receiving, at the computer, an additional representation of the graphical user interface of the remote system subsequent to automatically providing the signal to the remote system to execute the input action; and searching, at the computer, the additionally received representation of the remote system graphical user interface for another graphical element based on an image analysis. | 0.5 |
9,922,088 | 13 | 16 | 13. A non-transitory computer-readable storage device having instructions stored thereon that, when executed by at least one computing device, causes the at least one computing device to perform operations that generate a cardinality estimate, the operations comprising: identifying a predicate in a query, wherein the predicate is split into a plurality of equivalence classes, generating a plurality of undirected equivalence graphs from the plurality of equivalence classes, wherein the undirected equivalence graphs include a plurality of weighted edges representing a join predicate between two tables, and wherein the equivalence classes are determined based on sets of common attributes that are included in tables joined in the query; identifying spanning trees in the plurality of undirected equivalence graphs; determining a minimum spanning tree of the identified spanning trees; calculating a cardinality estimate based on the minimum spanning tree based on multiplying each predicate, in a set, of identified predicates in the spanning tress, by a selectivity associated with each edge corresponding to the predicate, wherein a quality of the selectivity indicates a relationship between two tables joined in the query, and wherein the relationship indicates at least one of a key or attribute relationship between the two tables; and selecting a query plan corresponding to the cardinality estimate wherein the cardinality estimate for the selected query plan is associated with a lower consumption of resources amongst a plurality of query plans in an execution of a query by a processor of the at least one computing device. | 13. A non-transitory computer-readable storage device having instructions stored thereon that, when executed by at least one computing device, causes the at least one computing device to perform operations that generate a cardinality estimate, the operations comprising: identifying a predicate in a query, wherein the predicate is split into a plurality of equivalence classes, generating a plurality of undirected equivalence graphs from the plurality of equivalence classes, wherein the undirected equivalence graphs include a plurality of weighted edges representing a join predicate between two tables, and wherein the equivalence classes are determined based on sets of common attributes that are included in tables joined in the query; identifying spanning trees in the plurality of undirected equivalence graphs; determining a minimum spanning tree of the identified spanning trees; calculating a cardinality estimate based on the minimum spanning tree based on multiplying each predicate, in a set, of identified predicates in the spanning tress, by a selectivity associated with each edge corresponding to the predicate, wherein a quality of the selectivity indicates a relationship between two tables joined in the query, and wherein the relationship indicates at least one of a key or attribute relationship between the two tables; and selecting a query plan corresponding to the cardinality estimate wherein the cardinality estimate for the selected query plan is associated with a lower consumption of resources amongst a plurality of query plans in an execution of a query by a processor of the at least one computing device. 16. The non-transitory tangible computer-readable storage device of claim 13 , wherein generating an undirected equivalence graph in the plurality of undirected equivalence graphs, further comprises operations comprising: generating a first node and a second node, wherein the first node corresponds to a first table and a set of attributes and the second node corresponds to a second table and a set of attributes, wherein the first table, the second table and the attributes are included in an equivalence class from the plurality of the equivalence classes; generating an edge between the first node and the second node, and annotating the edge with a second predicate referencing the attributes between the first node and the second node, wherein the second predicate is a component of the query predicate. | 0.5 |
7,720,783 | 4 | 6 | 4. The method of claim 1 , wherein extracting the first set of knowledge comprises extracting a set of words or phrases from each document; and wherein formulating the queries comprises constructing single-word queries, multi-word queries, or both from the extracted words or phrases. | 4. The method of claim 1 , wherein extracting the first set of knowledge comprises extracting a set of words or phrases from each document; and wherein formulating the queries comprises constructing single-word queries, multi-word queries, or both from the extracted words or phrases. 6. The method of claim 4 , wherein extracting a set of words or phrases from each document comprises extracting a pre-determined number of words or phrases from the document. | 0.5 |
9,762,963 | 1 | 2 | 1. A method of controlling an audio presentation, the method comprising: receiving an audio signal by at least one processor; storing the audio signal in a memory, the memory in communication with the at least one processor; receiving a filter list including at least one word; the at least one processor identifying a portion of the audio signal corresponding to the at least one word based on a match between a comparative form of the audio signal and an audio representation of the at least one word, the comparative form of the audio signal being generated based on at least one energy representation of the audio signal, the at least one energy representation includes a-series of vectors of energy involving a total energy of a speech slice and an energy of one or more-frequency bands of the speech slice; and the at least one processor manipulating the portion of the audio signal in the memory to filter the at least one word during the audio presentation by embedding a control code in the audio signal stored in the memory wherein the control code is adapted to attenuate the portion of the audio signal. | 1. A method of controlling an audio presentation, the method comprising: receiving an audio signal by at least one processor; storing the audio signal in a memory, the memory in communication with the at least one processor; receiving a filter list including at least one word; the at least one processor identifying a portion of the audio signal corresponding to the at least one word based on a match between a comparative form of the audio signal and an audio representation of the at least one word, the comparative form of the audio signal being generated based on at least one energy representation of the audio signal, the at least one energy representation includes a-series of vectors of energy involving a total energy of a speech slice and an energy of one or more-frequency bands of the speech slice; and the at least one processor manipulating the portion of the audio signal in the memory to filter the at least one word during the audio presentation by embedding a control code in the audio signal stored in the memory wherein the control code is adapted to attenuate the portion of the audio signal. 2. The method of claim 1 , wherein the audio representation of the at least one word is generated based on at least one energy value for a phonetic representation of the at least one word. | 0.5 |
8,996,559 | 25 | 26 | 25. The non-transitory medium of claim 16 , further comprising instructions to compute the data profile through a result set profiler module through which: a first set of hash tables maps each attribute value of an attribute to a number of times a particular value is observed in the attribute, a second set of hash tables maps patterns exhibited by an attribute value to a count of times a pattern is observed in the attribute, wherein the pattern is constructed based on a regular expression of string-valued attributes. | 25. The non-transitory medium of claim 16 , further comprising instructions to compute the data profile through a result set profiler module through which: a first set of hash tables maps each attribute value of an attribute to a number of times a particular value is observed in the attribute, a second set of hash tables maps patterns exhibited by an attribute value to a count of times a pattern is observed in the attribute, wherein the pattern is constructed based on a regular expression of string-valued attributes. 26. The non-transitory medium of claim 25 , comprising instructions compatible with: the user providing a user defined table value function using a visual interface through an application programming interface, the application programming interface considering at least one of a data source, a table, and a table value aggregate query data as an input to be registered with the result set profiler module, and the user being permitted to mark the subsequent query as completed after an iterative evaluation of the data profile generated from previous queries. | 0.5 |
8,578,481 | 1 | 9 | 1. A method comprising: parsing a character string associated with the suspected domain name of the suspected domain to identify a character in the character string that has a known likelihood of being deceptively substituted for a corresponding legitimate character in a legitimate domain name of the legitimate domain wherein the generating comprising substituting the identified character with the corresponding legitimate character generating an alternate domain name from a suspected domain name; submitting the alternate domain name to a domain name server for resolution; when the alternate domain name is resolved, assigning, a first non-zero likelihood that the suspected domain name is a counterfeit of the legitimate domain; retrieving, by the processor, a first webpage associated with the suspected domain name; retrieving, by the processor, a second webpage associated with the alternate domain name corresponding to the first web page associated with the suspected domain name; computing similarity between a first webpage associated with the suspected domain name and a second webpage associated with the alternate domain name, wherein the second webpage corresponds to the first web page associated with the suspected domain name; in response to the computing, assigning, a processor, a second non-zero likelihood that the suspected domain name is a counterfeit of the legitimate domain, wherein the second non-zero likelihood is greater than the first non-zero likelihood: determining that the first webpage comprises a request for input of personal information; and in response to the determining, assigning, by the processor, a third non-zero likelihood that the suspected domain is a counterfeit of the legitimate domain, wherein the third non-zero likelihood is greater than the second non-zero likelihood. | 1. A method comprising: parsing a character string associated with the suspected domain name of the suspected domain to identify a character in the character string that has a known likelihood of being deceptively substituted for a corresponding legitimate character in a legitimate domain name of the legitimate domain wherein the generating comprising substituting the identified character with the corresponding legitimate character generating an alternate domain name from a suspected domain name; submitting the alternate domain name to a domain name server for resolution; when the alternate domain name is resolved, assigning, a first non-zero likelihood that the suspected domain name is a counterfeit of the legitimate domain; retrieving, by the processor, a first webpage associated with the suspected domain name; retrieving, by the processor, a second webpage associated with the alternate domain name corresponding to the first web page associated with the suspected domain name; computing similarity between a first webpage associated with the suspected domain name and a second webpage associated with the alternate domain name, wherein the second webpage corresponds to the first web page associated with the suspected domain name; in response to the computing, assigning, a processor, a second non-zero likelihood that the suspected domain name is a counterfeit of the legitimate domain, wherein the second non-zero likelihood is greater than the first non-zero likelihood: determining that the first webpage comprises a request for input of personal information; and in response to the determining, assigning, by the processor, a third non-zero likelihood that the suspected domain is a counterfeit of the legitimate domain, wherein the third non-zero likelihood is greater than the second non-zero likelihood. 9. The method of claim 1 further comprising: when the alternate domain name is not resolved, generating, by the processor, one or more another alternate domain names from the suspected domain name and submitting the one or more another alternate domain names to the domain server for resolution. | 0.533228 |
7,996,462 | 8 | 13 | 8. A system for connecting information resources, the system comprising: at least one of a processor and a memory providing: a collaborative work environment accessible by a plurality of users who contribute collaboration data to the collaborative work environment via one or more user interfaces; a repository framework including a plurality of collaboration data sources that includes the collaborative work environment; and a collaborative bot service connected with the repository framework, the collaborative bot service including one or more bots that perform functions comprising: maintaining a topic list of topics previously identified in the plurality of collaboration data sources automatically and autonomously monitoring the collaboration work environment, the monitoring comprising traversing the collaboration information provided within the collaborative work environment via a user interface by the plurality of users; extracting, using a text-mining tool upon detection via the monitoring of new collaboration information contributed by one of the plurality of users in the collaborative work environment for use by at least one other of the plurality of users in the collaborative work environment, an extracted topic of the new collaboration information, the extracted topic comprising at least one of a theme, a question, a problem, and a subject matter of the new collaboration information; identifying an information resource within the plurality of collaboration data sources that is related to the extracted topic, the identifying comprising comparing the extracted topic to the topic list and determining that previously contributed collaboration information available from the information resource has a topic related to the extracted topic; creating a link insertable into a collaborative process, through which the plurality of users can send communications, of the collaborative work environment, the link being to the information resource identified as related to the extracted topic of the new collaboration information contributed by the one of the plurality of users for use by the at least one other of the plurality of users in the collaborative work environment; and inserting the link into the collaborative process through which the plurality of users can send communications and into the user interface in a close proximal relation to the new collaboration information. | 8. A system for connecting information resources, the system comprising: at least one of a processor and a memory providing: a collaborative work environment accessible by a plurality of users who contribute collaboration data to the collaborative work environment via one or more user interfaces; a repository framework including a plurality of collaboration data sources that includes the collaborative work environment; and a collaborative bot service connected with the repository framework, the collaborative bot service including one or more bots that perform functions comprising: maintaining a topic list of topics previously identified in the plurality of collaboration data sources automatically and autonomously monitoring the collaboration work environment, the monitoring comprising traversing the collaboration information provided within the collaborative work environment via a user interface by the plurality of users; extracting, using a text-mining tool upon detection via the monitoring of new collaboration information contributed by one of the plurality of users in the collaborative work environment for use by at least one other of the plurality of users in the collaborative work environment, an extracted topic of the new collaboration information, the extracted topic comprising at least one of a theme, a question, a problem, and a subject matter of the new collaboration information; identifying an information resource within the plurality of collaboration data sources that is related to the extracted topic, the identifying comprising comparing the extracted topic to the topic list and determining that previously contributed collaboration information available from the information resource has a topic related to the extracted topic; creating a link insertable into a collaborative process, through which the plurality of users can send communications, of the collaborative work environment, the link being to the information resource identified as related to the extracted topic of the new collaboration information contributed by the one of the plurality of users for use by the at least one other of the plurality of users in the collaborative work environment; and inserting the link into the collaborative process through which the plurality of users can send communications and into the user interface in a close proximal relation to the new collaboration information. 13. A system in accordance with claim 8 , further comprising an administration interface for receiving user commands and for configuring each of the one or more bots. | 0.726974 |
8,868,509 | 16 | 19 | 16. A system for backing up data computed using an application in a cloud computing environment, comprising: a processor; a module to modify the application to register a servlet, and publish the application to the cloud computing environment, and during execution of the application, the module being further to use the servlet for detecting annotated entities created in the code of the application by parsing user codes, finding out properties and property types of the annotated entities, generating a plurality of structured query language (SQL) statements to query out data to be backed up in accordance with the annotated entities, and publishing the backed up data. | 16. A system for backing up data computed using an application in a cloud computing environment, comprising: a processor; a module to modify the application to register a servlet, and publish the application to the cloud computing environment, and during execution of the application, the module being further to use the servlet for detecting annotated entities created in the code of the application by parsing user codes, finding out properties and property types of the annotated entities, generating a plurality of structured query language (SQL) statements to query out data to be backed up in accordance with the annotated entities, and publishing the backed up data. 19. The system according to claim 16 , further comprising a display device to display one of the plurality of the SQL statements performed during the execution of the application. | 0.5 |
9,213,624 | 1 | 6 | 1. A process for testing for trigger conditions and providing warnings or suggestions during the development of a portable device application, the process comprising the steps of: receiving a portable device application; displaying, by a development environment, a list of application categories, the list of application categories including at least three of the following application categories: Books, Business, Catalogs, Education, Email, Entertainment, Finance, Games, Health & Fitness, Lifestyle, Medical, Music, Navigation/Search, News, Password Manager, Photo & Video, Productivity, Reference, Social Networking, Sports, Travel, Utilities, Weather; receiving a user selected application category for the portable device application in the development environment, the application category selected from said list of application categories; determining a testing procedure for the portable device application based on the selected application category; testing the portable device application based on the determined testing procedure and providing warnings or suggestions based on the testing, wherein the process further comprises issuing a warning or suggestion consistent with at least one of the following conditions: if the application category is Social Networking, testing for compliance with start-up time requirements, and if noncompliant, issuing a warning from the development environment indicating that the application has a start-up time exceeding a trigger threshold for Social Networking applications; if the application category is Password Manager or Finance, testing for compliance with one or more security policies, and if noncompliant, issuing a warning from the development environment indicating that the application should adhere to security policies associated with Password Manager or Finance application categories; if the application category is News or Photo & Video, testing for compliance with policies regarding delays between photo requests, and if noncompliant, issuing a warning from the development environment indicating that the application should request several photos simultaneously instead of requesting them one at a time with delays in between the requests; if the application category is Email, Photo & Video, News, or Social Networking, testing for compliance with image resolution requirements, and if noncompliant, issuing at least one of the following warnings from the development environment: the application should try to detect what kind of network is available, the application should try to detect what video resolutions are available, the application should consider the network bandwidth, or the application should consider the user's data plan costs; if the application category is Photo & Video, testing whether the application determines whether a camera is available and if it does not, issuing a warning from the development environment indicating that the application should detect whether a camera is available on the device running the application; if the application category is Navigation/Search, testing whether the application determines whether the application uses power efficient APIs to resolve location and if it does not, issuing a warning from the development environment that the application should use power efficient APIs to resolve location; if the application category is Weather, testing for compliance with width and/or height controls, and if noncompliant, issuing a warning from the development environment indicating that the application should adhere to width and/or height of controls to accommodate content in various locales; if the application category is News, testing for compliance with minimum dimension requirements stated in user interface guidelines, and if noncompliant, issuing a warning from the development environment that the application should ensure that all controls meet minimum dimension requirements stated in user interface guidelines; if the application category is News, testing for compliance with color combination requirements, and if noncompliant, issuing a suggestion or warning from the development environment indicating that the application content use a different color combination; if the application category is Games, testing for compliance with back-key handling requirements, and if noncompliant, issuing a warning from the development environment indicating that the application should adhere to platform application model guidelines for back-key handling. | 1. A process for testing for trigger conditions and providing warnings or suggestions during the development of a portable device application, the process comprising the steps of: receiving a portable device application; displaying, by a development environment, a list of application categories, the list of application categories including at least three of the following application categories: Books, Business, Catalogs, Education, Email, Entertainment, Finance, Games, Health & Fitness, Lifestyle, Medical, Music, Navigation/Search, News, Password Manager, Photo & Video, Productivity, Reference, Social Networking, Sports, Travel, Utilities, Weather; receiving a user selected application category for the portable device application in the development environment, the application category selected from said list of application categories; determining a testing procedure for the portable device application based on the selected application category; testing the portable device application based on the determined testing procedure and providing warnings or suggestions based on the testing, wherein the process further comprises issuing a warning or suggestion consistent with at least one of the following conditions: if the application category is Social Networking, testing for compliance with start-up time requirements, and if noncompliant, issuing a warning from the development environment indicating that the application has a start-up time exceeding a trigger threshold for Social Networking applications; if the application category is Password Manager or Finance, testing for compliance with one or more security policies, and if noncompliant, issuing a warning from the development environment indicating that the application should adhere to security policies associated with Password Manager or Finance application categories; if the application category is News or Photo & Video, testing for compliance with policies regarding delays between photo requests, and if noncompliant, issuing a warning from the development environment indicating that the application should request several photos simultaneously instead of requesting them one at a time with delays in between the requests; if the application category is Email, Photo & Video, News, or Social Networking, testing for compliance with image resolution requirements, and if noncompliant, issuing at least one of the following warnings from the development environment: the application should try to detect what kind of network is available, the application should try to detect what video resolutions are available, the application should consider the network bandwidth, or the application should consider the user's data plan costs; if the application category is Photo & Video, testing whether the application determines whether a camera is available and if it does not, issuing a warning from the development environment indicating that the application should detect whether a camera is available on the device running the application; if the application category is Navigation/Search, testing whether the application determines whether the application uses power efficient APIs to resolve location and if it does not, issuing a warning from the development environment that the application should use power efficient APIs to resolve location; if the application category is Weather, testing for compliance with width and/or height controls, and if noncompliant, issuing a warning from the development environment indicating that the application should adhere to width and/or height of controls to accommodate content in various locales; if the application category is News, testing for compliance with minimum dimension requirements stated in user interface guidelines, and if noncompliant, issuing a warning from the development environment that the application should ensure that all controls meet minimum dimension requirements stated in user interface guidelines; if the application category is News, testing for compliance with color combination requirements, and if noncompliant, issuing a suggestion or warning from the development environment indicating that the application content use a different color combination; if the application category is Games, testing for compliance with back-key handling requirements, and if noncompliant, issuing a warning from the development environment indicating that the application should adhere to platform application model guidelines for back-key handling. 6. The process of claim 1 , wherein the process further comprises issuing at least one of the following: a suggestion that the application use a different color combination in daylight; a suggestion that the application use a different color combination in a light theme; a warning that the application uses a control layout that does not comply with a touch area requirement. | 0.710324 |
9,318,128 | 17 | 20 | 17. A system, comprising: at least one processor; and data storage comprising program instructions executable by the at least one processor to perform functions comprising: receiving information indicating a plurality of actions that a given application is configured to perform, wherein the information indicating each respective action of the plurality of actions includes one or more parameters that are used to enable the given application to perform the respective action; receiving, for each respective action, one or more example instructions that, when recognized by the given application, causes the given application to perform the respective action, wherein the one or more example instructions comprise natural language; based on the one or more example instructions for each respective action, the plurality of actions, and the one or more parameters included for each respective action, determining a plurality of candidate instructions for each respective action that, when recognized by a voice interface of the given application, causes the given application to perform the respective action, wherein each candidate instruction of the plurality of candidate instructions comprises one or more grammars recognizable by the voice interface of the given application; receiving a plurality of acceptance information comprising, for each candidate instruction, respective acceptance information indicative of whether the candidate instruction is applicable to the respective action, wherein the plurality of acceptance information indicates, for each respective action of at least one of the plurality of actions, that at least one of the plurality of candidate instructions determined for the respective action is rejected; based on the plurality of acceptance information, storing, at the computing device, for each candidate instruction, a respective identifier associated with the candidate instruction and indicative of whether the candidate instruction is rejected; comparing at least a portion of the respective acceptance information with a stored acceptance information log so as to determine a correlation between the respective acceptance information and the stored acceptance information log, wherein the stored acceptance information log comprises a plurality of predetermined acceptance information associated with a plurality of predetermined example instructions; and based on the correlation, referring to the stored identifiers to determine a set of instructions that are recognizable by the voice interface and that, when recognized by the voice interface, causes the given application to perform one or more of the plurality of actions, wherein determining the set of instructions comprises, for each respective action, (i) selecting, based on the stored identifiers, one or more of the plurality of candidate instructions for the respective action to be included in the set of instructions and (ii) selecting, based on the stored identifiers, the at least one rejected candidate instruction for the respective action to not be included in the set of instructions and to not be recognizable by the voice interface to cause the given application to perform the respective action. | 17. A system, comprising: at least one processor; and data storage comprising program instructions executable by the at least one processor to perform functions comprising: receiving information indicating a plurality of actions that a given application is configured to perform, wherein the information indicating each respective action of the plurality of actions includes one or more parameters that are used to enable the given application to perform the respective action; receiving, for each respective action, one or more example instructions that, when recognized by the given application, causes the given application to perform the respective action, wherein the one or more example instructions comprise natural language; based on the one or more example instructions for each respective action, the plurality of actions, and the one or more parameters included for each respective action, determining a plurality of candidate instructions for each respective action that, when recognized by a voice interface of the given application, causes the given application to perform the respective action, wherein each candidate instruction of the plurality of candidate instructions comprises one or more grammars recognizable by the voice interface of the given application; receiving a plurality of acceptance information comprising, for each candidate instruction, respective acceptance information indicative of whether the candidate instruction is applicable to the respective action, wherein the plurality of acceptance information indicates, for each respective action of at least one of the plurality of actions, that at least one of the plurality of candidate instructions determined for the respective action is rejected; based on the plurality of acceptance information, storing, at the computing device, for each candidate instruction, a respective identifier associated with the candidate instruction and indicative of whether the candidate instruction is rejected; comparing at least a portion of the respective acceptance information with a stored acceptance information log so as to determine a correlation between the respective acceptance information and the stored acceptance information log, wherein the stored acceptance information log comprises a plurality of predetermined acceptance information associated with a plurality of predetermined example instructions; and based on the correlation, referring to the stored identifiers to determine a set of instructions that are recognizable by the voice interface and that, when recognized by the voice interface, causes the given application to perform one or more of the plurality of actions, wherein determining the set of instructions comprises, for each respective action, (i) selecting, based on the stored identifiers, one or more of the plurality of candidate instructions for the respective action to be included in the set of instructions and (ii) selecting, based on the stored identifiers, the at least one rejected candidate instruction for the respective action to not be included in the set of instructions and to not be recognizable by the voice interface to cause the given application to perform the respective action. 20. The system of claim 17 , wherein the given application includes a graphical interface provided by a mobile device. | 0.736607 |
9,411,899 | 11 | 12 | 11. The method of claim 10 , further comprising: causing the first different page to be displayed on the device; and receiving a user action on the first different page, wherein causing the current page to be displayed on the device is performed in response to the user action. | 11. The method of claim 10 , further comprising: causing the first different page to be displayed on the device; and receiving a user action on the first different page, wherein causing the current page to be displayed on the device is performed in response to the user action. 12. The method of claim 11 , wherein: the user action comprises a user action on one of the functional options of the first different page. | 0.5 |
9,213,978 | 1 | 6 | 1. A method comprising: receiving, as part of a speech trend analysis request, a set of candidate feature constraints, an objective mathematical function with respect to a speech trend to be analyzed, and a set of speech record constraints to be applied to a group of speech records; selecting a speech record from the group of speech records based on the set of speech record constraints; identifying features in the speech record based on the set of candidate feature constraints, to yield identified features; assigning, via a processor, using a statistical regression, a weight to each of the identified features, wherein a scalar value associated with each identified feature is evaluated using the objective mathematical function to yield the weight; ranking the identified features by respective weights, to yield ranked identified features; comparing the ranked identified features to a hand-picked set of alarm features, to yield a comparison; and when the comparison indicates an alarm condition has been met, outputting one of the ranked identified features associated with a speech-based trend in response to the speech as an alarm. | 1. A method comprising: receiving, as part of a speech trend analysis request, a set of candidate feature constraints, an objective mathematical function with respect to a speech trend to be analyzed, and a set of speech record constraints to be applied to a group of speech records; selecting a speech record from the group of speech records based on the set of speech record constraints; identifying features in the speech record based on the set of candidate feature constraints, to yield identified features; assigning, via a processor, using a statistical regression, a weight to each of the identified features, wherein a scalar value associated with each identified feature is evaluated using the objective mathematical function to yield the weight; ranking the identified features by respective weights, to yield ranked identified features; comparing the ranked identified features to a hand-picked set of alarm features, to yield a comparison; and when the comparison indicates an alarm condition has been met, outputting one of the ranked identified features associated with a speech-based trend in response to the speech as an alarm. 6. The method of claim 1 , wherein the objective mathematical function utilizes a combination of features and time. | 0.760417 |
9,679,072 | 1 | 9 | 1. A system of a mobile device, Alpha, and a mobile device, Beta; where Alpha is controlled by a first user; where Beta is controlled by a second user; where the first user and the second user are different persons; where Alpha shows a first image; where Alpha makes a data containing an Universal Resource Locator (URL) of the first image; where the data furthermore contains an electronic address of the first user; where Alpha displays the data in a barcode as a second image; where Beta has a camera; where Beta scans the barcode with the camera to obtain an image Phi; where Beta decodes Phi to extract the data; where Beta sends an electronic message to the electronic address of the first user; where the electronic message contains an electronic address of the second user. | 1. A system of a mobile device, Alpha, and a mobile device, Beta; where Alpha is controlled by a first user; where Beta is controlled by a second user; where the first user and the second user are different persons; where Alpha shows a first image; where Alpha makes a data containing an Universal Resource Locator (URL) of the first image; where the data furthermore contains an electronic address of the first user; where Alpha displays the data in a barcode as a second image; where Beta has a camera; where Beta scans the barcode with the camera to obtain an image Phi; where Beta decodes Phi to extract the data; where Beta sends an electronic message to the electronic address of the first user; where the electronic message contains an electronic address of the second user. 9. The system of claim 1 , where a reply includes a link to a webpage of an owner of Beta. | 0.878049 |
8,380,502 | 1 | 9 | 1. A method comprising: receiving, by one or more processors, a voice search query from a user; deriving, by the one or more processors, a plurality of recognition hypotheses from the voice search query; determining, by the one or more processors, a plurality of scores associated with the plurality of recognition hypotheses, the plurality of scores being based on a comparison of the plurality of recognition hypotheses to previously received search queries; discarding, by the one or more processors, at least one of the plurality of recognition hypotheses that is associated with at least one first score, of the plurality of scores, that is less than a threshold value; constructing, by the one or more processors, a first query using at least one first non-discarded recognition hypothesis of the plurality of recognition hypotheses, where the at least one first non-discarded recognition hypothesis is associated with at least one second score, of the plurality of scores, that at least meets the threshold value, constructing the first query including: forming an initial query based on the at least one first non-discarded recognition hypothesis, identifying a plurality of stop words in the initial query, and pruning, from the initial query, one or more of the plurality of stop words to form the first query, the first query satisfying a length threshold; forwarding, by the one or more processors, the first query to a search system; receiving, by the one or more processors and from the search system, first results associated with the first query; and providing, by the one or more processors and to the user, the first results. | 1. A method comprising: receiving, by one or more processors, a voice search query from a user; deriving, by the one or more processors, a plurality of recognition hypotheses from the voice search query; determining, by the one or more processors, a plurality of scores associated with the plurality of recognition hypotheses, the plurality of scores being based on a comparison of the plurality of recognition hypotheses to previously received search queries; discarding, by the one or more processors, at least one of the plurality of recognition hypotheses that is associated with at least one first score, of the plurality of scores, that is less than a threshold value; constructing, by the one or more processors, a first query using at least one first non-discarded recognition hypothesis of the plurality of recognition hypotheses, where the at least one first non-discarded recognition hypothesis is associated with at least one second score, of the plurality of scores, that at least meets the threshold value, constructing the first query including: forming an initial query based on the at least one first non-discarded recognition hypothesis, identifying a plurality of stop words in the initial query, and pruning, from the initial query, one or more of the plurality of stop words to form the first query, the first query satisfying a length threshold; forwarding, by the one or more processors, the first query to a search system; receiving, by the one or more processors and from the search system, first results associated with the first query; and providing, by the one or more processors and to the user, the first results. 9. The method of claim 1 , where providing the first results further comprises: determining a quantity of the first results; and when the quantity of the first results is less than a particular number: constructing a second query based on the voice search query, forwarding the second query to the search system, receiving, from the search system, second results associated with the second query, and providing, to the user, the second results. | 0.5 |
9,002,908 | 9 | 10 | 9. A system for routing and managing stored documents based on document content, comprising: at least one processor; a data repository; at least one memory coupled to the at least one processor and comprising computer readable program code embodied in the at least one memory that when executed by the at least one processor causes the at least one processor to perform operations comprising: determining a classification for a document based on the document content; determining a storage location for the document based on the document classification and storage rules of a storage provider policy; determining whether the document is stored in the determined storage location; when the document is stored in the determined storage location, updating the document in the determined storage location; when the document is not stored in the determined storage location, determining whether the document is stored in another storage location; when the document is stored in another storage location, adding the document to the determined storage location and deleting the document from the other storage location; when the document is not stored in the determined storage location or the other storage location, adding the document to the determined storage location; reclassifying the document with a new document classification responsive to an update of the document; determining a new storage provider for the document responsive to a comparison of the new document classification and the storage provider policy; adding the document to a new storage location of the new storage provider; deleting the document from the determined storage location; and updating an entry of the document in a storage map responsive to the adding the document to the new storage location. | 9. A system for routing and managing stored documents based on document content, comprising: at least one processor; a data repository; at least one memory coupled to the at least one processor and comprising computer readable program code embodied in the at least one memory that when executed by the at least one processor causes the at least one processor to perform operations comprising: determining a classification for a document based on the document content; determining a storage location for the document based on the document classification and storage rules of a storage provider policy; determining whether the document is stored in the determined storage location; when the document is stored in the determined storage location, updating the document in the determined storage location; when the document is not stored in the determined storage location, determining whether the document is stored in another storage location; when the document is stored in another storage location, adding the document to the determined storage location and deleting the document from the other storage location; when the document is not stored in the determined storage location or the other storage location, adding the document to the determined storage location; reclassifying the document with a new document classification responsive to an update of the document; determining a new storage provider for the document responsive to a comparison of the new document classification and the storage provider policy; adding the document to a new storage location of the new storage provider; deleting the document from the determined storage location; and updating an entry of the document in a storage map responsive to the adding the document to the new storage location. 10. The system according to claim 9 , wherein the operations further comprise: determining whether an entry for the document exists in the storage map; when the entry exists and when the document is stored in the other storage location, updating the entry for the document to the storage map; and when the entry does not exist, adding the entry for the document to the storage map. | 0.643258 |
9,823,900 | 16 | 17 | 16. A method for generating a software application using a computer system, comprising the steps of: (a) modeling business processes in a graphical design tool implemented in said computer system, said graphical design tool capable of generating models to serve as blueprints in development of the software application; (b) creating, in said computer system via Unified Modeling Language (UML), at least one UML model to formalize the business processes modeled in step (a) by using one or more state diagrams to represent the modeled business processes, and one or more class diagrams to represent data models and to represent predetermined business rules that are applied to the modeled business processes, wherein a tagged value is used in the data models to define an exclusive dependency between a current field and another field in the same entity type of the data models or in another entity type of the data models with a relation; (c) validating, in said computer system, the at least one UML model by detecting syntax errors using a predetermined syntax, to validate either said one or more state diagrams or said one or more class diagrams, or a combination of said one or more state diagrams and said one or more class diagrams, producing at least one validated UML model, wherein one or more use-cases and allowed actions for each use-case is generated via said one or more state diagrams, facilitating defining actions and drawing use-cases by a user; (d) transforming, in said computer system, said at least one validated UML model validated in step (c) into metadata that are used to generate functional and non-functional aspects of the software application, the software application being a layer that sits on too of a UML visual modeling tool as a plug-in; and (e) generating, via the at least one UML model a new Enterprise Application Archive (Ear) file and/or selecting an existing Ear file, the new Ear file and/or the selected existing Ear file comprising a plurality of Java Archive (JAR) files required for deployment of the software, wherein at least one JAR file is added and/or removed; (f) generating a project that contains said at least one validated UML model, wherein generating said project comprises removing all conflicting stereotypes; (g) deploying the software application as a layer that sits on top of a UML visual modeling tool as a plug in; and (h) generating code automatically by: converting the UML model into an XML file; using the XML file to generate Java source code; and compiling the generated Java source code using a compiler and creating the at least one JAR. | 16. A method for generating a software application using a computer system, comprising the steps of: (a) modeling business processes in a graphical design tool implemented in said computer system, said graphical design tool capable of generating models to serve as blueprints in development of the software application; (b) creating, in said computer system via Unified Modeling Language (UML), at least one UML model to formalize the business processes modeled in step (a) by using one or more state diagrams to represent the modeled business processes, and one or more class diagrams to represent data models and to represent predetermined business rules that are applied to the modeled business processes, wherein a tagged value is used in the data models to define an exclusive dependency between a current field and another field in the same entity type of the data models or in another entity type of the data models with a relation; (c) validating, in said computer system, the at least one UML model by detecting syntax errors using a predetermined syntax, to validate either said one or more state diagrams or said one or more class diagrams, or a combination of said one or more state diagrams and said one or more class diagrams, producing at least one validated UML model, wherein one or more use-cases and allowed actions for each use-case is generated via said one or more state diagrams, facilitating defining actions and drawing use-cases by a user; (d) transforming, in said computer system, said at least one validated UML model validated in step (c) into metadata that are used to generate functional and non-functional aspects of the software application, the software application being a layer that sits on too of a UML visual modeling tool as a plug-in; and (e) generating, via the at least one UML model a new Enterprise Application Archive (Ear) file and/or selecting an existing Ear file, the new Ear file and/or the selected existing Ear file comprising a plurality of Java Archive (JAR) files required for deployment of the software, wherein at least one JAR file is added and/or removed; (f) generating a project that contains said at least one validated UML model, wherein generating said project comprises removing all conflicting stereotypes; (g) deploying the software application as a layer that sits on top of a UML visual modeling tool as a plug in; and (h) generating code automatically by: converting the UML model into an XML file; using the XML file to generate Java source code; and compiling the generated Java source code using a compiler and creating the at least one JAR. 17. The method of claim 16 , wherein predefined types of classes and decorations are applied within the one or more class diagrams and the decorations are organized, in part, by tagged values in step (b). | 0.650685 |
9,396,188 | 15 | 17 | 15. An apparatus for assigning a tag to a content item, said apparatus comprising: one or more processors; and one or more memories operatively coupled to at least one of the one or more processors and having instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to: receive a content item that has been accessed by a user; determine at least one term associated with at least one of one or more search queries that resulted in the content item being located by a search engine and accessed by the user, the at least one term being useful in describing the content item; assign a tag to the content item, wherein the tag is associated with the at least one term; and place the tag in a categorization structure that includes at least one tag set. | 15. An apparatus for assigning a tag to a content item, said apparatus comprising: one or more processors; and one or more memories operatively coupled to at least one of the one or more processors and having instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to: receive a content item that has been accessed by a user; determine at least one term associated with at least one of one or more search queries that resulted in the content item being located by a search engine and accessed by the user, the at least one term being useful in describing the content item; assign a tag to the content item, wherein the tag is associated with the at least one term; and place the tag in a categorization structure that includes at least one tag set. 17. The apparatus of claim 15 , wherein at least one of the one or more memories has further instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to allow editing of the term or tag. | 0.581288 |
7,536,641 | 1 | 8 | 1. A method for composing a user defined web page, comprising: at a client, using a web browser executed at the client: displaying in a first browser window an authoring web page, including displaying a graphical user interface of an authoring tool that is embedded in the authoring web page; the displayed graphical user interface for composing the user defined web page; using the displayed graphical user interface of the authoring tool to receive user instructions, and responding to the user instructions by placing instances of predefined structured fields in the user defined web page and associating user specified content with the instances of the predefined structured fields, wherein a respective instance of the predefined structured fields in the user-defined web page corresponds to a geometric region of the user-defined web page having a visible and adjustable boundary; displaying a preview of the user defined web page in a second web browser window; and sending the user defined web page to a server for public access. | 1. A method for composing a user defined web page, comprising: at a client, using a web browser executed at the client: displaying in a first browser window an authoring web page, including displaying a graphical user interface of an authoring tool that is embedded in the authoring web page; the displayed graphical user interface for composing the user defined web page; using the displayed graphical user interface of the authoring tool to receive user instructions, and responding to the user instructions by placing instances of predefined structured fields in the user defined web page and associating user specified content with the instances of the predefined structured fields, wherein a respective instance of the predefined structured fields in the user-defined web page corresponds to a geometric region of the user-defined web page having a visible and adjustable boundary; displaying a preview of the user defined web page in a second web browser window; and sending the user defined web page to a server for public access. 8. The method of claim 1 , wherein at least one instance of a predefined structured field includes a heuristic instruction suggesting a type of content suitable for adding to the at least one instance of a predefined structured field. | 0.8 |
7,831,420 | 1 | 7 | 1. A method for modifying a speech signal, the method comprising: receiving, by a formants modifier of a speech converter of a speech processing system, Mth order linear predictive coding (LPC) coefficients representative of an input speech signal; converting the Mth order LPC coefficients to Mth order line spectral pairs (LSPs), by the formants modifier; multiplying, by the formants modifier, the Mth order LSPs by a scale factor to produce scaled Mth order LSPs; removing, by the formants modifier, any pair of scaled LSP with at least one coefficient in the pair above a frequency threshold to produce a Pth order set of LSPs, where P<M; converting the Pth order set of scaled LSPs to a Pth order set of LPCs, by the formants modifier; padding the Pth order set of LPCs with M-P zeros, by the formants modifier; converting the Pth order set of LPCs padded with zeros to a second Mth order set of LSPs, by the formants modifier; processing, by the formants modifier, the second Mth order set of LSPs and at least a third set of Mth order LSPs of another frame; converting the processed LSPs to processed LPCs, by the formants modifier; and re-synthesizing speech, by an LPC synthesizer of a decoder of the speech processing system, using the processed LPCs. | 1. A method for modifying a speech signal, the method comprising: receiving, by a formants modifier of a speech converter of a speech processing system, Mth order linear predictive coding (LPC) coefficients representative of an input speech signal; converting the Mth order LPC coefficients to Mth order line spectral pairs (LSPs), by the formants modifier; multiplying, by the formants modifier, the Mth order LSPs by a scale factor to produce scaled Mth order LSPs; removing, by the formants modifier, any pair of scaled LSP with at least one coefficient in the pair above a frequency threshold to produce a Pth order set of LSPs, where P<M; converting the Pth order set of scaled LSPs to a Pth order set of LPCs, by the formants modifier; padding the Pth order set of LPCs with M-P zeros, by the formants modifier; converting the Pth order set of LPCs padded with zeros to a second Mth order set of LSPs, by the formants modifier; processing, by the formants modifier, the second Mth order set of LSPs and at least a third set of Mth order LSPs of another frame; converting the processed LSPs to processed LPCs, by the formants modifier; and re-synthesizing speech, by an LPC synthesizer of a decoder of the speech processing system, using the processed LPCs. 7. The method of claim 1 , wherein the scale factor is part of a set of parameters corresponding to a control signal. | 0.692105 |
8,752,074 | 1 | 4 | 1. A method performed by one or more processing devices comprising: polling a server for script relating to a device; receiving the script from the server, the script being in a self-describing computer language, the script comprising simple object access protocol (SOAP) commands and executable code that is in the self-describing computer language and that defines functions to be performed on variables to be passed from the executable code to corresponding SOAP commands; interpreting a part of the script to perform a function contained in the script on a variable and to pass the variable to a SOAP command; parsing the SOAP command from the script; passing the SOAP command to a SOAP interpreter to execute the SOAP command with the variable; and repeating the interpreting, parsing and passing for a different part of the script comprising a different function, a different variable, and a different SOAP command; wherein interpreting, parsing, passing and repeating are performed without requiring further communication to the server; and wherein the function comprises an If-Then statement or an If-Then-Else statement. | 1. A method performed by one or more processing devices comprising: polling a server for script relating to a device; receiving the script from the server, the script being in a self-describing computer language, the script comprising simple object access protocol (SOAP) commands and executable code that is in the self-describing computer language and that defines functions to be performed on variables to be passed from the executable code to corresponding SOAP commands; interpreting a part of the script to perform a function contained in the script on a variable and to pass the variable to a SOAP command; parsing the SOAP command from the script; passing the SOAP command to a SOAP interpreter to execute the SOAP command with the variable; and repeating the interpreting, parsing and passing for a different part of the script comprising a different function, a different variable, and a different SOAP command; wherein interpreting, parsing, passing and repeating are performed without requiring further communication to the server; and wherein the function comprises an If-Then statement or an If-Then-Else statement. 4. The method of claim 1 , wherein: the script declares the variable; and a value of the variable is passed to the SOAP command prior to executing the SOAP command. | 0.57732 |
8,661,065 | 6 | 7 | 6. The method of claim 5 , wherein the glossary is accessible through both the definition interface and the instruction interface. | 6. The method of claim 5 , wherein the glossary is accessible through both the definition interface and the instruction interface. 7. The method of claim 6 , wherein the glossary is further configured to facilitate sharing of information between different users, each of the different users belonging to a different one of the groups of users. | 0.5 |
7,685,194 | 1 | 8 | 1. A computer-implemented system that facilitates fine-grained access control of a database, comprising: a processor configured to execute computer-readable instructions; a performance component for detecting and removing redundant authorizations associated with a query expression, the removing including: implementing a set of transformation rules, the transformation rules including: testing for semi-join subsumption and relation mapping; and given disjunction of query expression, transforming the expression into a disjunction of semi-joins, and testing for subsumption of each of the semi-joins; and initiating redundancy removal before applying decorrelation transformations; security component for controlling information leakage associated with the query expression, the security component configured to identify at least one unsafe function in the query expression and to determine an optimal safe location for the at least one unsafe function in an optimal query plan; and a safety component for maintaining safety of the query plan, the query plan including a relocation of the at least one unsafe function to a safe location determined in part by a safety analysis and in part by a cost-based analysis, the unsafe functions including user defined functions, system-defined functions, and operators that may reveal information whether directly or by means of exception or error messages, the maintaining including: parsing the query expression and determining base relations of the query expression; specifying authorizations based on predicated grants in the query expression; creating a regular view by combining a plurality of authorizations made to a user; and giving permission to the user on the regular view instead of underlying relations. | 1. A computer-implemented system that facilitates fine-grained access control of a database, comprising: a processor configured to execute computer-readable instructions; a performance component for detecting and removing redundant authorizations associated with a query expression, the removing including: implementing a set of transformation rules, the transformation rules including: testing for semi-join subsumption and relation mapping; and given disjunction of query expression, transforming the expression into a disjunction of semi-joins, and testing for subsumption of each of the semi-joins; and initiating redundancy removal before applying decorrelation transformations; security component for controlling information leakage associated with the query expression, the security component configured to identify at least one unsafe function in the query expression and to determine an optimal safe location for the at least one unsafe function in an optimal query plan; and a safety component for maintaining safety of the query plan, the query plan including a relocation of the at least one unsafe function to a safe location determined in part by a safety analysis and in part by a cost-based analysis, the unsafe functions including user defined functions, system-defined functions, and operators that may reveal information whether directly or by means of exception or error messages, the maintaining including: parsing the query expression and determining base relations of the query expression; specifying authorizations based on predicated grants in the query expression; creating a regular view by combining a plurality of authorizations made to a user; and giving permission to the user on the regular view instead of underlying relations. 8. The system of claim 1 , wherein the performance component checks for redundancy between predicates in a query and predicates in authorizations. | 0.643902 |
7,720,782 | 9 | 11 | 9. A system for predicting a future event associated with a business based on historical data associated with a model of past events of the business, comprising: a processor; and a memory in communication with the processor, the memory storing a plurality of processing instructions for directing the processor to: obtain a plurality of modeling variables associated with the model, a dependent variable associated with the model and dependent on the plurality of modeling variables, and the historical data associated with the model; perform a transformation of the plurality of modeling variables to obtain a linear relationship of each of the plurality of modeling variables in relation to the dependent variable; select a subset of the plurality of transformed modeling variables, wherein the selecting comprises applying a selecting rule based on at least one of: (i) a correlation between a transformed variable and the dependent variable, and (ii) a proportion of a range of the dependent variable explained by the transformed variable; or a selection rule based on a log-likelihood difference; determine a set of prediction variables, wherein the determining is based on a regression of the subset of the plurality of transformed variables; and generate a predictive model using the prediction variables obtained from the regression, wherein the predictive model is used by the system to predict the future event. | 9. A system for predicting a future event associated with a business based on historical data associated with a model of past events of the business, comprising: a processor; and a memory in communication with the processor, the memory storing a plurality of processing instructions for directing the processor to: obtain a plurality of modeling variables associated with the model, a dependent variable associated with the model and dependent on the plurality of modeling variables, and the historical data associated with the model; perform a transformation of the plurality of modeling variables to obtain a linear relationship of each of the plurality of modeling variables in relation to the dependent variable; select a subset of the plurality of transformed modeling variables, wherein the selecting comprises applying a selecting rule based on at least one of: (i) a correlation between a transformed variable and the dependent variable, and (ii) a proportion of a range of the dependent variable explained by the transformed variable; or a selection rule based on a log-likelihood difference; determine a set of prediction variables, wherein the determining is based on a regression of the subset of the plurality of transformed variables; and generate a predictive model using the prediction variables obtained from the regression, wherein the predictive model is used by the system to predict the future event. 11. The system of claim 9 , further comprising instructions for directing the processor to: substitute at least one of a replacement value or a minimum value for at least one of missing values, invalid values, or zero values, the substitution being performed in the historical data. | 0.571429 |
9,753,546 | 1 | 9 | 1. A computer-implemented method comprising: processing a plurality of data frames, each data frame of the plurality of data frames comprising one or more body point locations of each of a plurality of collaborating users that are interfacing with an application at each of a plurality of time intervals; defining a spatial volume for each of the plurality of collaborating users based on the plurality of processed data frames; detecting a gesture performed by a first collaborating user of the plurality of collaborating users based on the plurality of processed data frames; determining the gesture to be an input gesture based on the gesture being performed by the first collaborating user in a first spatial volume; interpreting, by a machine having a memory and at least one processor, the input gesture based on a context of the first spatial volume, the context of the first spatial volume comprising an intersection volume between the first spatial volume and a second spatial volume for a second collaborating user; and providing an input command to the application based on the interpreted input gesture, the input command being different for the gesture being within the intersection volume than for the gesture being outside of the intersection volume. | 1. A computer-implemented method comprising: processing a plurality of data frames, each data frame of the plurality of data frames comprising one or more body point locations of each of a plurality of collaborating users that are interfacing with an application at each of a plurality of time intervals; defining a spatial volume for each of the plurality of collaborating users based on the plurality of processed data frames; detecting a gesture performed by a first collaborating user of the plurality of collaborating users based on the plurality of processed data frames; determining the gesture to be an input gesture based on the gesture being performed by the first collaborating user in a first spatial volume; interpreting, by a machine having a memory and at least one processor, the input gesture based on a context of the first spatial volume, the context of the first spatial volume comprising an intersection volume between the first spatial volume and a second spatial volume for a second collaborating user; and providing an input command to the application based on the interpreted input gesture, the input command being different for the gesture being within the intersection volume than for the gesture being outside of the intersection volume. 9. The computer-implemented method of claim 1 , wherein defining the spatial volume is further based on a measurement of a body part of the corresponding collaborating user. | 0.72884 |
9,576,269 | 1 | 4 | 1. A method for managing documents in a computer implemented document management system, comprising: creating a document profile that is associated with a document within the document management system and includes fields of attributes of the document; and associating one or more documents external to the document management system with the document profile by creating a URL in the document profile containing an address to a file that does not have an associated profile in the document management system and is of a file type that is not created within the document management system. | 1. A method for managing documents in a computer implemented document management system, comprising: creating a document profile that is associated with a document within the document management system and includes fields of attributes of the document; and associating one or more documents external to the document management system with the document profile by creating a URL in the document profile containing an address to a file that does not have an associated profile in the document management system and is of a file type that is not created within the document management system. 4. The method of claim 1 further comprising: creating a document profile that includes fields of attributes of a document for each of the documents; generating a unique identifier for each of the documents, the unique identifier including at least a first portion including information descriptive of an attribute of the document and at least a second portion including an automatically generated number, the unique identifier being visible to users of the document management system and providing information about the corresponding document to the users so that each of the documents can be identified from the corresponding unique identifier among a group including unique identifiers corresponding to other documents; and storing the document profile for each of the documents. | 0.5 |
8,903,724 | 1 | 4 | 1. A speech recognition device comprising: a processor; and a memory which stores a plurality of instructions, which when executed by the processor, cause the processor to execute, conducting a search, by speech recognition, on audio data stored in a first memory to extract wordspoken portions where plural words transferred are each spoken and, of the word-spoken portions extracted, rejects the word-spoken portion for the word designated as a rejecting object; obtaining a derived word of a designated search target word, the derived word being generated in accordance with a derived word generation rule stored in a second memory or read out from the second memory where the derived word is stored in association with the search target word, and sets the derived word to an outputting object or the rejecting object according to setting designation information or a user's instruction, the setting designation information being stored in the second memory and indicating whether the derived word is the outputting object or the rejecting object; transferring the derived word and the search target word to the conducting, the derived word being obtained and set to the outputting object or the rejecting object by the obtaining; and outputting the word-spoken portion extracted and not rejected in the search of the conducting, wherein the derived word generation rule is generated based on a difference between the search target word and a derived word that is stored in the second memory. | 1. A speech recognition device comprising: a processor; and a memory which stores a plurality of instructions, which when executed by the processor, cause the processor to execute, conducting a search, by speech recognition, on audio data stored in a first memory to extract wordspoken portions where plural words transferred are each spoken and, of the word-spoken portions extracted, rejects the word-spoken portion for the word designated as a rejecting object; obtaining a derived word of a designated search target word, the derived word being generated in accordance with a derived word generation rule stored in a second memory or read out from the second memory where the derived word is stored in association with the search target word, and sets the derived word to an outputting object or the rejecting object according to setting designation information or a user's instruction, the setting designation information being stored in the second memory and indicating whether the derived word is the outputting object or the rejecting object; transferring the derived word and the search target word to the conducting, the derived word being obtained and set to the outputting object or the rejecting object by the obtaining; and outputting the word-spoken portion extracted and not rejected in the search of the conducting, wherein the derived word generation rule is generated based on a difference between the search target word and a derived word that is stored in the second memory. 4. The device according to claim 1 , wherein the processor presents the derived word, and sets the derived word presented to the outputting object or the rejecting object based on an instruction. | 0.864771 |
9,685,158 | 8 | 13 | 8. A non-transitory computer-readable storage medium storing computer-readable instructions, which when executed, cause a computing device to: store, by at least one processor, first data associated with prior communications sent to a user, the first data comprising a first profile for a caller that creates a voice message for the user, and the prior communications including at least one prior communication received from the caller; send, by the at least one processor, to a speech recognition system, the voice message for transcribing using at least a portion of the first data to provide a transcribed message; receive, from the speech recognition system, the transcribed message; and cause a presentation on a display, the presentation comprising the transcribed message, and the presentation further comprising options for selection of a corrected word by the user to correct a misspelled word in the transcribed message. | 8. A non-transitory computer-readable storage medium storing computer-readable instructions, which when executed, cause a computing device to: store, by at least one processor, first data associated with prior communications sent to a user, the first data comprising a first profile for a caller that creates a voice message for the user, and the prior communications including at least one prior communication received from the caller; send, by the at least one processor, to a speech recognition system, the voice message for transcribing using at least a portion of the first data to provide a transcribed message; receive, from the speech recognition system, the transcribed message; and cause a presentation on a display, the presentation comprising the transcribed message, and the presentation further comprising options for selection of a corrected word by the user to correct a misspelled word in the transcribed message. 13. The storage medium of claim 8 , wherein the instructions further cause the computing device to present, on the display, a list of messages, each message in the list being referenced in the transcribed message. | 0.5 |
8,023,962 | 1 | 17 | 1. A system for providing geographic information comprising: a database containing geographic information, the database accessible via a network connection; and a mobile device connectable to the database from a remote location, the mobile device having a controller, a position sensor for determining a location of the mobile device and a pointing device adapted to orient the mobile device pointing in a direction to intersect a particular one of an object, geographical feature or location of interest to a user, the controller being adapted to receive a thematic query from a user, the controller being further adapted retrieve a portion of the geographic information from the database selected by a combination of the location of the mobile device, a pointing direction of the device and the thematic query, and the geographical information is about the particular object, geographical feature or location. | 1. A system for providing geographic information comprising: a database containing geographic information, the database accessible via a network connection; and a mobile device connectable to the database from a remote location, the mobile device having a controller, a position sensor for determining a location of the mobile device and a pointing device adapted to orient the mobile device pointing in a direction to intersect a particular one of an object, geographical feature or location of interest to a user, the controller being adapted to receive a thematic query from a user, the controller being further adapted retrieve a portion of the geographic information from the database selected by a combination of the location of the mobile device, a pointing direction of the device and the thematic query, and the geographical information is about the particular object, geographical feature or location. 17. The mobile device of claim 1 wherein the mobile device includes a mobile unit and a separate pointing device coupled to the mobile unit. | 0.77918 |
4,829,572 | 21 | 22 | 21. The method of claim 20 wherein the sweep spectra deriving step includes passing the output of the difference amplifiers through respective upward and downward edge detectors which generate step functions of fixed amplitude and duration, and summing the step functions of adjacent sets of upward and downward edge detectors to generate upward and downward sweep spectra. | 21. The method of claim 20 wherein the sweep spectra deriving step includes passing the output of the difference amplifiers through respective upward and downward edge detectors which generate step functions of fixed amplitude and duration, and summing the step functions of adjacent sets of upward and downward edge detectors to generate upward and downward sweep spectra. 22. The method of claim 21 wherein the summing step includes summing the step functions of adjacent, overlapping sets of edge detectors. | 0.5 |
9,870,393 | 1 | 2 | 1. A computer-implemented system comprising: a graph mapper configured to store data representing a graph into a first table in a relational database, each node in the graph having a single-valued property and a multi-valued property, the multi-valued property being a non-local property and containing a reference to at least one adjacent node, the mapper configured to store each node in a corresponding record in the first table by: storing the single-valued property in a single-valued field, and storing the multi-valued property in a multi-valued field; a query translator configured to: receive a graph query on the graph, the query including a traversal from a first node to a second node that is adjacent to the first node, convert the graph query into a structured query language (SQL) query over the first table and a second table, and retrieve the multi-valued property of the first node from the first table and obtain data of the second node from the second table with the SQL query; and the graph mapper further configured to: store, for each node in the graph, an adjacency list in the multi-valued field, the adjacency list containing the reference to the at least one adjacent node, transform the adjacency list to a temporary table; and use the temporary table to locate the corresponding record. | 1. A computer-implemented system comprising: a graph mapper configured to store data representing a graph into a first table in a relational database, each node in the graph having a single-valued property and a multi-valued property, the multi-valued property being a non-local property and containing a reference to at least one adjacent node, the mapper configured to store each node in a corresponding record in the first table by: storing the single-valued property in a single-valued field, and storing the multi-valued property in a multi-valued field; a query translator configured to: receive a graph query on the graph, the query including a traversal from a first node to a second node that is adjacent to the first node, convert the graph query into a structured query language (SQL) query over the first table and a second table, and retrieve the multi-valued property of the first node from the first table and obtain data of the second node from the second table with the SQL query; and the graph mapper further configured to: store, for each node in the graph, an adjacency list in the multi-valued field, the adjacency list containing the reference to the at least one adjacent node, transform the adjacency list to a temporary table; and use the temporary table to locate the corresponding record. 2. The system of claim 1 , wherein the query translator is configured to generate the SQL query that invokes a predefined function on the multi-valued property of the first node to create the temporary table, the temporary table being a temporary junction table associating the first node and the at least one adjacent node. | 0.73955 |
8,977,645 | 21 | 23 | 21. A non-transitory computer storage medium encoded with instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a search query; providing a structured presentation for display on a display device responsive to the search query, the structured presentation visually presenting information in a systematic and structured arrangement that conforms with a structured design, the structured presentation denoting associations between an instance and values that characterize attributes of an entity corresponding to the instance using an arrangement of the values in respective cells of the structured presentation, wherein one or more values of in the respective cells are populated from one or more electronic documents identified from a search of an unstructured collection of electronic documents; receiving a user interaction with a first cell of the structured presentation, the first cell having a first value for a particular attribute of an instance associated with the first cell; and in response to the received user interaction with the first cell: determining that the first value of the first cell provided in the structured presentations resulted from a prior search of the unstructured collection of electronic documents by a system comprising one or more computers that identified one or more particular electronic documents as including content characterizing the particular attribute of the instance, wherein the first value was determined from the content of the one or more particular electronic documents; and in response to determining that the prior search was conducted, providing information regarding the prior search including providing a search interface associated with the first value of the first cell for presentation on the display device, the search interface configured to present search result information characterizing the prior search including providing information identifying a first electronic document of the particular electronic documents from which the first value for the attribute of the instance was determined including providing for display a link to the first electronic document. | 21. A non-transitory computer storage medium encoded with instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a search query; providing a structured presentation for display on a display device responsive to the search query, the structured presentation visually presenting information in a systematic and structured arrangement that conforms with a structured design, the structured presentation denoting associations between an instance and values that characterize attributes of an entity corresponding to the instance using an arrangement of the values in respective cells of the structured presentation, wherein one or more values of in the respective cells are populated from one or more electronic documents identified from a search of an unstructured collection of electronic documents; receiving a user interaction with a first cell of the structured presentation, the first cell having a first value for a particular attribute of an instance associated with the first cell; and in response to the received user interaction with the first cell: determining that the first value of the first cell provided in the structured presentations resulted from a prior search of the unstructured collection of electronic documents by a system comprising one or more computers that identified one or more particular electronic documents as including content characterizing the particular attribute of the instance, wherein the first value was determined from the content of the one or more particular electronic documents; and in response to determining that the prior search was conducted, providing information regarding the prior search including providing a search interface associated with the first value of the first cell for presentation on the display device, the search interface configured to present search result information characterizing the prior search including providing information identifying a first electronic document of the particular electronic documents from which the first value for the attribute of the instance was determined including providing for display a link to the first electronic document. 23. The computer storage medium of claim 21 , wherein the wherein the operations further comprise providing information identifying a collection of electronic documents from which the first value could have been determined. | 0.730676 |
7,751,511 | 18 | 28 | 18. The wireless communication apparatus of claim 17 , wherein the circuitry is configured to select a subset of the modeled impairment correlation terms by selecting the modeled impairment correlation terms having corresponding model fitting parameters that satisfy a threshold. | 18. The wireless communication apparatus of claim 17 , wherein the circuitry is configured to select a subset of the modeled impairment correlation terms by selecting the modeled impairment correlation terms having corresponding model fitting parameters that satisfy a threshold. 28. The wireless communication apparatus of claim 18 , wherein the circuitry is further configured to filter the model fitting parameters to reduce estimation variance. | 0.820513 |
10,042,896 | 1 | 5 | 1. A method for providing a search recommendation, the method comprising: obtaining a first search term, the first search term input by a user; matching the first search term with at least one keyword in a list to select the at least one keyword from the list, a respective keyword in the list corresponding to at least one search recommendation; obtaining one or more search recommendations corresponding to the at least one keyword; and obtaining the at least one search recommendation corresponding to the respective keyword, including: obtaining a historical user behavior relating to the respective keyword from a log record; obtaining a document generated by the historical user behavior; applying a text segmentation of the document to obtain one or more candidate recommendations; filtering the one or more candidate recommendations according to importance degree characteristics of the one or more candidate recommendations; and improving a probability that the at least one search recommendation fits user requirements and reducing a number of user searches, search time, and search traffic by using a candidate recommendation passing the filtering as a search recommendation corresponding to the respective keyword. | 1. A method for providing a search recommendation, the method comprising: obtaining a first search term, the first search term input by a user; matching the first search term with at least one keyword in a list to select the at least one keyword from the list, a respective keyword in the list corresponding to at least one search recommendation; obtaining one or more search recommendations corresponding to the at least one keyword; and obtaining the at least one search recommendation corresponding to the respective keyword, including: obtaining a historical user behavior relating to the respective keyword from a log record; obtaining a document generated by the historical user behavior; applying a text segmentation of the document to obtain one or more candidate recommendations; filtering the one or more candidate recommendations according to importance degree characteristics of the one or more candidate recommendations; and improving a probability that the at least one search recommendation fits user requirements and reducing a number of user searches, search time, and search traffic by using a candidate recommendation passing the filtering as a search recommendation corresponding to the respective keyword. 5. The method of claim 1 , wherein the applying the text segmentation of the document comprises applying the text segmentation of a title or an attribute content of the document. | 0.857372 |
9,460,217 | 1 | 5 | 1. A system, comprising: a client computer configured to: receive on behalf of a user, from a user interface element displayed on an electronic form, at least one keyword describing a web page selected to be optimized for a high search engine rank; and display a notification recommending that the user create an optimized content for the web page comprising a searched question and an answer to the searched question; a first server computer operated by a search engine, the first server computer running an application programming interface (API); a processor executing instructions causing a second server computer to: receive, from the user interface element displayed on the electronic form, the at least one keyword; transmit a remote procedure call (RPC) to the API, the RPC comprising the at least one keyword and at least one question keyword comprising what, who, when, why or how; receive, from the API in response to the RPC, a plurality of searched questions comprising the at least one keyword and the at least one question keyword, and for each one of the plurality of searched questions: a usage metric defining a number of times the at least one searched question appeared in a search performed by the search engine during a day, a week, a month, or a year; and a competition metric based on a total number of websites optimized for the search engine and including each of the plurality of searched questions; calculate a recommendation score for each of the plurality of searched questions; generate the notification recommending the one of the plurality of searched questions associated with a highest recommendation score; identify, within the content of the selected web page, a plurality of words; generate a running count of each of the plurality of words; determine a percentage of each of the plurality of words as compared to the total number of words within the content; assign an optimal keyword density within the content; display a font color or graphic indicating if the percentage of each of the plurality of words is greater or less than the optimal keyword density; and transmit the notification to the client computer for display on a user interface. | 1. A system, comprising: a client computer configured to: receive on behalf of a user, from a user interface element displayed on an electronic form, at least one keyword describing a web page selected to be optimized for a high search engine rank; and display a notification recommending that the user create an optimized content for the web page comprising a searched question and an answer to the searched question; a first server computer operated by a search engine, the first server computer running an application programming interface (API); a processor executing instructions causing a second server computer to: receive, from the user interface element displayed on the electronic form, the at least one keyword; transmit a remote procedure call (RPC) to the API, the RPC comprising the at least one keyword and at least one question keyword comprising what, who, when, why or how; receive, from the API in response to the RPC, a plurality of searched questions comprising the at least one keyword and the at least one question keyword, and for each one of the plurality of searched questions: a usage metric defining a number of times the at least one searched question appeared in a search performed by the search engine during a day, a week, a month, or a year; and a competition metric based on a total number of websites optimized for the search engine and including each of the plurality of searched questions; calculate a recommendation score for each of the plurality of searched questions; generate the notification recommending the one of the plurality of searched questions associated with a highest recommendation score; identify, within the content of the selected web page, a plurality of words; generate a running count of each of the plurality of words; determine a percentage of each of the plurality of words as compared to the total number of words within the content; assign an optimal keyword density within the content; display a font color or graphic indicating if the percentage of each of the plurality of words is greater or less than the optimal keyword density; and transmit the notification to the client computer for display on a user interface. 5. The system of claim 1 , wherein the instructions cause the second server computer to: receive, from the electronic form, a uniform resource locator (URL) for at least one web page; identify, within the content of the at least one web page, a plurality of words; determine a total number of each of the plurality of words; display, on a user interface on the client computer, a list of each of the plurality of words, ranked according to a highest total number. | 0.5 |
8,935,260 | 1 | 11 | 1. A computer-implemented method of extracting key phrases from a document comprising: accessing a repository comprising hyperlinked subjects, the repository comprising first and second data structures representing the relationship between said hyperlinked subjects using different representation criteria; pruning the first data structure by removing hyperlinks between subjects based on a further relationship between said subjects in the second data structure; matching phrases in said document to said subjects in the pruned first data structure; further pruning the pruned first data structure by removing unmatched subjects that are not hyperlinked to matched subjects; determining a ranking for each matched subject; and selecting key phrases using the determined subject rankings, wherein the first data structure is a directional graph comprising the subjects as nodes and the hyperlinks between subjects as edges between nodes; the second data structure is a directional graph comprising organized subject categories; and the further relationship comprises the shortest distance between respective categories to which respective subjects belong in the second data structure, the hyperlink between said subjects being removed if the shortest distance exceeds a threshold value. | 1. A computer-implemented method of extracting key phrases from a document comprising: accessing a repository comprising hyperlinked subjects, the repository comprising first and second data structures representing the relationship between said hyperlinked subjects using different representation criteria; pruning the first data structure by removing hyperlinks between subjects based on a further relationship between said subjects in the second data structure; matching phrases in said document to said subjects in the pruned first data structure; further pruning the pruned first data structure by removing unmatched subjects that are not hyperlinked to matched subjects; determining a ranking for each matched subject; and selecting key phrases using the determined subject rankings, wherein the first data structure is a directional graph comprising the subjects as nodes and the hyperlinks between subjects as edges between nodes; the second data structure is a directional graph comprising organized subject categories; and the further relationship comprises the shortest distance between respective categories to which respective subjects belong in the second data structure, the hyperlink between said subjects being removed if the shortest distance exceeds a threshold value. 11. The method of claim 1 , further comprising extracting key phrases from a further document by repeating the phrase matching, further pruning, subject ranking, and key phrase selection steps for the further document. | 0.626712 |
9,201,861 | 18 | 19 | 18. A character input prediction method comprising: obtaining information of a first character input operation that is performed by a user using a character key layout display in which a plurality of character keys are arranged; detecting an indication position and an indication direction in the character key layout display from the information of the first character input operation, the indication position showing a position of the first character input operation, and the indication direction showing a movement direction of the first character input operation; determining a vector having the indication position as a base point using the indication position and the indication direction, a character key layout showing an arrangement of a plurality of character keys in the character key layout display, and determining a character range using the character key layout, the character range including a plurality of character keys located in an extending direction of the vector; and searching a plurality of candidate character strings included in a dictionary, for a predictive character string that includes a character corresponding to any one of the plurality of character keys included in the character range. | 18. A character input prediction method comprising: obtaining information of a first character input operation that is performed by a user using a character key layout display in which a plurality of character keys are arranged; detecting an indication position and an indication direction in the character key layout display from the information of the first character input operation, the indication position showing a position of the first character input operation, and the indication direction showing a movement direction of the first character input operation; determining a vector having the indication position as a base point using the indication position and the indication direction, a character key layout showing an arrangement of a plurality of character keys in the character key layout display, and determining a character range using the character key layout, the character range including a plurality of character keys located in an extending direction of the vector; and searching a plurality of candidate character strings included in a dictionary, for a predictive character string that includes a character corresponding to any one of the plurality of character keys included in the character range. 19. A non-transitory computer-readable recording medium for use in a computer, the recording medium having a program of the character input prediction method according to claim 18 recorded thereon. | 0.5 |
9,311,292 | 2 | 3 | 2. The device of claim 1 , wherein the instructions are executable by the processor to: responsive to input invoking message composition and based at least in part on a determination that the first multi-term phrase appears in plural messages among the past messages at least the threshold number of times, present on the device at least plural terms from the first multi-term phrase. | 2. The device of claim 1 , wherein the instructions are executable by the processor to: responsive to input invoking message composition and based at least in part on a determination that the first multi-term phrase appears in plural messages among the past messages at least the threshold number of times, present on the device at least plural terms from the first multi-term phrase. 3. The device of claim 2 , wherein the input invoking message composition includes an identification of at least one recipient, and wherein the instructions are executable by the processor to: responsive to the input invoking message composition and based at least in part on the identification of at least one recipient, present on the device at least plural terms from the first multi-term phrase. | 0.5 |
8,336,025 | 1 | 5 | 1. A computer-implemented method comprising: determining, by a computer, a user selected construct within a design tool; receiving, by the computer, a selection of a computing environment within the design tool, the computing environment being selected from at least one textual computing environment and at least one graphical computing environment; identifying, by the computer, the selected computing environment into which the user selected construct is placed; determining, by the computer, a position of the user selected construct placed in the selected computing environment; selecting, by the computer, a template based on the selected computing environment and the user selected construct; and inserting, by the computer, the selected template into the selected computing environment at the determined position in the selected computing environment. | 1. A computer-implemented method comprising: determining, by a computer, a user selected construct within a design tool; receiving, by the computer, a selection of a computing environment within the design tool, the computing environment being selected from at least one textual computing environment and at least one graphical computing environment; identifying, by the computer, the selected computing environment into which the user selected construct is placed; determining, by the computer, a position of the user selected construct placed in the selected computing environment; selecting, by the computer, a template based on the selected computing environment and the user selected construct; and inserting, by the computer, the selected template into the selected computing environment at the determined position in the selected computing environment. 5. The method according to claim 1 , wherein the design tool comprises a floating tool bar window. | 0.946565 |
9,569,729 | 11 | 12 | 11. The computer readable medium of claim 1 where a credibility score for an actor is comprised of assessing an at least one of the group of perspective score, sincerity score, objectivity score, and substance score. | 11. The computer readable medium of claim 1 where a credibility score for an actor is comprised of assessing an at least one of the group of perspective score, sincerity score, objectivity score, and substance score. 12. The computer readable medium of claim 11 where assessing the sincerity score is comprised of assessing sincerity and assessing a probability that the actor is an outsider posing as a member. | 0.5 |
7,526,464 | 2 | 4 | 2. The system of claim 1 , further comprising: a fourth function to generate a usage metric associated with a subset of the fuzzy network. | 2. The system of claim 1 , further comprising: a fourth function to generate a usage metric associated with a subset of the fuzzy network. 4. The system of claim 2 , wherein a fourth function to generate a usage metric associated with a subset of the fuzzy network comprises: a fifth function to generate an influence metric associated with a subset of the fuzzy network. | 0.508475 |
9,454,523 | 7 | 8 | 7. A non-transitory computer-readable storage medium for storing an expanded-display program for causing a computer to function as: an acronym-extracting device that extracts an acronym from a designated reference; a category-determining device that extracts a category given in a corpus for each of N words occurring most frequently in the designated reference, and determines that a category extracted most often is a category of the designated reference; and an expanded-display device that displays an expanded form corresponding to the acronym by using an acronym list in which the expanded form corresponding to the acronym and the frequency with which the acronym is used to refer to the expanded form are correlated; and the expanded-display device using the acronym list, in which the acronym, the expanded form, the frequency, and the category are correlated, to display the expanded form correlated with the acronym extracted from the designated reference and the determined category of the designated reference in the acronym list, along with a degree of accuracy based on the frequency; the degree of accuracy being a value correlated with the acronym, the category and the expanded form in the acronym list. | 7. A non-transitory computer-readable storage medium for storing an expanded-display program for causing a computer to function as: an acronym-extracting device that extracts an acronym from a designated reference; a category-determining device that extracts a category given in a corpus for each of N words occurring most frequently in the designated reference, and determines that a category extracted most often is a category of the designated reference; and an expanded-display device that displays an expanded form corresponding to the acronym by using an acronym list in which the expanded form corresponding to the acronym and the frequency with which the acronym is used to refer to the expanded form are correlated; and the expanded-display device using the acronym list, in which the acronym, the expanded form, the frequency, and the category are correlated, to display the expanded form correlated with the acronym extracted from the designated reference and the determined category of the designated reference in the acronym list, along with a degree of accuracy based on the frequency; the degree of accuracy being a value correlated with the acronym, the category and the expanded form in the acronym list. 8. The non-transitory computer-readable storage medium of claim 7 , the program causing the computer to function as an expanded-form-inputting device that inputs the expanded form selected from among the displayed expanded forms at the position, in the designated reference, of the acronym serving as the basis of the display of the expanded form. | 0.5 |
6,069,939 | 48 | 63 | 48. An apparatus for providing a called party with audio prompts in a language selected by a calling party, comprising: means for determining dialed digits that identify said called party; means for selecting a language previously determined by said calling party from a plurality of languages for delivery of audio prompts in response to determined dialed digits; and means for providing said called party with audio prompts in the selected language. | 48. An apparatus for providing a called party with audio prompts in a language selected by a calling party, comprising: means for determining dialed digits that identify said called party; means for selecting a language previously determined by said calling party from a plurality of languages for delivery of audio prompts in response to determined dialed digits; and means for providing said called party with audio prompts in the selected language. 63. The apparatus of claim 48, wherein said means for determining further comprise means for determining a dialed city/region that corresponds to said dialed country code and a dialed city code. | 0.550926 |
7,836,002 | 1 | 2 | 1. Computer storage media having a system embodied thereon including computer-executable instructions that, when executed, perform a method for facilitating focusing of a domain, the system comprising: a receiving component that accesses information related to an activity a user is attempting to accomplish, wherein the accessed information comprises information related to at least one of a lithe user, the user's environment, or the activity; and a domain scoping component that automatically scopes the domain into a plurality of sub-domains to facilitate accomplishment of the activity by reducing the domain resources available and narrowing a search space or recognition scope, wherein the domain comprises resources including one or more applications and at least one of one or more files, web links, functionalities, services, or views, wherein each sub-domain includes a subset of the resources in the domain, and wherein the domain scoping component comprises: an activity selection component that infers the activity the user is attempting to accomplish from the accessed information, an application selection component that identifies domain resources, including one or more applications, to limit access to or functionality of for each sub-domain based on the inferred activity, and a scaling component that limits access to or functionality of applications and other resources identified by the application selection component for each sub-domain to provide a focused workspace, including narrowing a grammar and lexicon available for recognition in natural language and speech processing to provide more efficient processing by limiting the number of words and grammatical constructs against which a language or speech input is compared during processing. | 1. Computer storage media having a system embodied thereon including computer-executable instructions that, when executed, perform a method for facilitating focusing of a domain, the system comprising: a receiving component that accesses information related to an activity a user is attempting to accomplish, wherein the accessed information comprises information related to at least one of a lithe user, the user's environment, or the activity; and a domain scoping component that automatically scopes the domain into a plurality of sub-domains to facilitate accomplishment of the activity by reducing the domain resources available and narrowing a search space or recognition scope, wherein the domain comprises resources including one or more applications and at least one of one or more files, web links, functionalities, services, or views, wherein each sub-domain includes a subset of the resources in the domain, and wherein the domain scoping component comprises: an activity selection component that infers the activity the user is attempting to accomplish from the accessed information, an application selection component that identifies domain resources, including one or more applications, to limit access to or functionality of for each sub-domain based on the inferred activity, and a scaling component that limits access to or functionality of applications and other resources identified by the application selection component for each sub-domain to provide a focused workspace, including narrowing a grammar and lexicon available for recognition in natural language and speech processing to provide more efficient processing by limiting the number of words and grammatical constructs against which a language or speech input is compared during processing. 2. The media of claim 1 , wherein the domain scoping component enhances recognition-based searching associated with the activity the user is attempting to accomplish. | 0.772603 |
8,352,266 | 7 | 13 | 7. A method for generating a dynamic grammar file for use by a speech recognition engine to resolve unrecognized sound groups in a speech using concept to keywords mappings and sentence types, each sentence type having a plurality of associated grammar rules, the grammar rules being expressed in concepts, said method comprising the steps of: parsing the partially recognized speech using a natural language processor into a pre-determined sentence type and an associated ordered list of recognized words and place holders corresponding to the unrecognized sound groups; selecting a list of grammar rules associated with the sentence type from a plurality of grammar rules stored by a storage unit on a storage medium, each grammar rule of said list having a plurality of constituent concepts, each of said constituent concepts corresponding to one of the recognized words and the unrecognized sound groups; for each place holder corresponding to said unrecognized sound group, merging said corresponding constituent concepts in all said selected grammar rules into a list of concepts; generating the dynamic grammar rule from said ordered list by replacing each concept of said list of merged concepts with a list of keywords a list of candidate words using the concept to keywords mappings stored by the storage unit wherein each of the keywords mapped from the merged concept are expandable to a plurality of words conceptually related to each of the merged concepts and wherein the plurality of words are the list of candidate words; and providing the dynamic grammar rule to the speech recognition engine to enable the speech recognition engine to use the dynamic grammar rule to resolve the unrecognized sound groups in the partially recognized speech corresponding to the place holders. | 7. A method for generating a dynamic grammar file for use by a speech recognition engine to resolve unrecognized sound groups in a speech using concept to keywords mappings and sentence types, each sentence type having a plurality of associated grammar rules, the grammar rules being expressed in concepts, said method comprising the steps of: parsing the partially recognized speech using a natural language processor into a pre-determined sentence type and an associated ordered list of recognized words and place holders corresponding to the unrecognized sound groups; selecting a list of grammar rules associated with the sentence type from a plurality of grammar rules stored by a storage unit on a storage medium, each grammar rule of said list having a plurality of constituent concepts, each of said constituent concepts corresponding to one of the recognized words and the unrecognized sound groups; for each place holder corresponding to said unrecognized sound group, merging said corresponding constituent concepts in all said selected grammar rules into a list of concepts; generating the dynamic grammar rule from said ordered list by replacing each concept of said list of merged concepts with a list of keywords a list of candidate words using the concept to keywords mappings stored by the storage unit wherein each of the keywords mapped from the merged concept are expandable to a plurality of words conceptually related to each of the merged concepts and wherein the plurality of words are the list of candidate words; and providing the dynamic grammar rule to the speech recognition engine to enable the speech recognition engine to use the dynamic grammar rule to resolve the unrecognized sound groups in the partially recognized speech corresponding to the place holders. 13. The method according to claim 7 , wherein the step of comparing includes comparing the partially recognized speech with discarding includes discarding grammar rules that do not match any recognized words in the partially recognized speech. | 0.732379 |
7,930,320 | 7 | 9 | 7. The apparatus of claim 6 , wherein each of the plurality of nodes has (1) a label indicative of an operand or all elements and a flag indicative of whether or not the node is highlighted or (2) a pointer to another nested object, a user-defined label, and a flag indicative of whether or not the node is highlighted. | 7. The apparatus of claim 6 , wherein each of the plurality of nodes has (1) a label indicative of an operand or all elements and a flag indicative of whether or not the node is highlighted or (2) a pointer to another nested object, a user-defined label, and a flag indicative of whether or not the node is highlighted. 9. The apparatus of claim 7 , wherein when the operation is an AND operation, it is determined which one of types each of a first and second nested objects to be operated on belongs to, the types including a first type in which a nested object has only one highlighted node and no lower node, a second type in which a nested object has only one node which is highlighted and whose higher node is not highlighted, and a third type in which a nested object does not belong to either the first or second type, and addition of node and inversion of flag are selectively performed in accordance with the types of the first and the second nested objects. | 0.5 |
8,953,844 | 1 | 9 | 1. In a system including a computing environment coupled to a capture device for capturing image data from a field of view of the capture device, the image data representing a position of a user, a method of estimating user body position comprising: (a) receiving image data from the field of view; (b) applying one or more computer models for generating body part proposals from the image data, at least one computer model accounting for missing joint information by using a position of the missing joint identified in a past frame as a basis for the position of the missing joint in the current frame; and (c) analyzing the one or more computer models produced in said step (b) by one or more methodologies to choose at least one computer model of the one or more computer models estimated to provide the best body part proposal. | 1. In a system including a computing environment coupled to a capture device for capturing image data from a field of view of the capture device, the image data representing a position of a user, a method of estimating user body position comprising: (a) receiving image data from the field of view; (b) applying one or more computer models for generating body part proposals from the image data, at least one computer model accounting for missing joint information by using a position of the missing joint identified in a past frame as a basis for the position of the missing joint in the current frame; and (c) analyzing the one or more computer models produced in said step (b) by one or more methodologies to choose at least one computer model of the one or more computer models estimated to provide the best body part proposal. 9. The method of claim 1 , said step (b) of applying one or more computer models comprising the step of applying one or more skeletal hypotheses including an estimated position of joints of a user captured for the frame by the capture device. | 0.71327 |
8,195,458 | 13 | 14 | 13. A method of semantically classifying a data set of open class nouns comprising: loading, by a processing device, a data set comprising one or more open class nouns from a computer readable medium operably connected to the processing device; processing, by the processing device, the data set to determine one or more application programming interfaces (APIs) to query; extracting, by the processing device, the one or more open class nouns from the data set; for each open class noun, querying, by the processing device, the determined one or more APIs to produce one or more results, wherein the one or more results define one or more classifications for each open class noun in the data set; and wherein the deriving the confidence score comprises: analyzing the one or more classifications for each open class noun in the data set based upon the one or more results; and determining the confidence score based upon a combination of the one or more classifications for each open class noun; deriving, by the processing device, a confidence score for the data set based upon the one or more results; and determining, by the processing device, a classification for the data set based upon the derived confidence score. | 13. A method of semantically classifying a data set of open class nouns comprising: loading, by a processing device, a data set comprising one or more open class nouns from a computer readable medium operably connected to the processing device; processing, by the processing device, the data set to determine one or more application programming interfaces (APIs) to query; extracting, by the processing device, the one or more open class nouns from the data set; for each open class noun, querying, by the processing device, the determined one or more APIs to produce one or more results, wherein the one or more results define one or more classifications for each open class noun in the data set; and wherein the deriving the confidence score comprises: analyzing the one or more classifications for each open class noun in the data set based upon the one or more results; and determining the confidence score based upon a combination of the one or more classifications for each open class noun; deriving, by the processing device, a confidence score for the data set based upon the one or more results; and determining, by the processing device, a classification for the data set based upon the derived confidence score. 14. The method of claim 13 , further comprising displaying, on a display device operably connected to the processing device, the one or more results. | 0.5 |
10,078,626 | 4 | 5 | 4. The method of claim 1 , wherein the first layout rule is based at least in part on one or more user device characteristics. | 4. The method of claim 1 , wherein the first layout rule is based at least in part on one or more user device characteristics. 5. The method of claim 4 , wherein the one or more user device characteristics comprises at least one of: display resolution, display color capability, or display redraw characteristics. | 0.5 |
7,512,620 | 2 | 4 | 2. The computer program product of claim 1 , wherein the method further comprises: associating a plurality of names with the object; and indexing the object responsive to a plurality of prefixes of each of the plurality of names. | 2. The computer program product of claim 1 , wherein the method further comprises: associating a plurality of names with the object; and indexing the object responsive to a plurality of prefixes of each of the plurality of names. 4. The computer program product of claim 2 , wherein the object comprises a multimedia object and a name of the plurality of names comprises at least one of: an artist name, a director name, an actor name, a composer name, a song name, and an album name. | 0.5 |
9,460,712 | 13 | 17 | 13. A system, comprising: one or more processors; and memory storing instructions that when executed by at least some of the one or more processors effectuates operations comprising: receiving, over the Internet, from a user terminal, a query spoken by a user, wherein the query spoken by the user includes a speech utterance representing a category of businesses and a speech utterance representing a geographic location; recognizing the geographic location with a speech recognition engine based on the speech utterance representing the geographic location; recognizing the category of businesses with the speech recognition engine based on the speech utterance representing the category of businesses; searching a business listing for businesses within both the recognized category of businesses and the recognized geographic location to select businesses responsive to the query spoken by the user; and sending to the user terminal information related to at least some of the responsive businesses. | 13. A system, comprising: one or more processors; and memory storing instructions that when executed by at least some of the one or more processors effectuates operations comprising: receiving, over the Internet, from a user terminal, a query spoken by a user, wherein the query spoken by the user includes a speech utterance representing a category of businesses and a speech utterance representing a geographic location; recognizing the geographic location with a speech recognition engine based on the speech utterance representing the geographic location; recognizing the category of businesses with the speech recognition engine based on the speech utterance representing the category of businesses; searching a business listing for businesses within both the recognized category of businesses and the recognized geographic location to select businesses responsive to the query spoken by the user; and sending to the user terminal information related to at least some of the responsive businesses. 17. The system of claim 13 , wherein the operations comprise selecting, based on the recognized location, location-specific categories of businesses including the recognized category of businesses. | 0.83719 |
9,535,883 | 15 | 16 | 15. A non-transitory computer-readable medium, comprising instructions executable on a processor, the instructions causing the processor to perform steps of: receiving a request from a client device for a preview of a native document, the preview representing the native document in a file format other than the file format of the native document; inserting, by a document mapping module in the native document prior to rendering a preview, a set of unique links comprising a uniform resource locator (URL) and each unique link associated with a different word in the native document, the native object comprising a renderable portion of the native document; rendering, by a document rendering module, the native document into a preview of the native document and thereby generating a bounding area for each of the unique links in the set of unique links, the bounding area mapping a page and pixel location on the preview to the native object associated with the unique link; and providing the preview to the client device for display. | 15. A non-transitory computer-readable medium, comprising instructions executable on a processor, the instructions causing the processor to perform steps of: receiving a request from a client device for a preview of a native document, the preview representing the native document in a file format other than the file format of the native document; inserting, by a document mapping module in the native document prior to rendering a preview, a set of unique links comprising a uniform resource locator (URL) and each unique link associated with a different word in the native document, the native object comprising a renderable portion of the native document; rendering, by a document rendering module, the native document into a preview of the native document and thereby generating a bounding area for each of the unique links in the set of unique links, the bounding area mapping a page and pixel location on the preview to the native object associated with the unique link; and providing the preview to the client device for display. 16. The non-transitory computer-readable medium of claim 15 , further comprising identifying a comment in the native document; determining at least one native object associated with the comment in the native document; determining a bounding area for the comment by combining the bounding areas for the unique links of the at least one native object associated with the comment; and providing the comment and the bounding area for the comment to the client device for display with the preview. | 0.569177 |
8,633,838 | 1 | 20 | 1. A computer-implemented method of compressing data, comprising carrying out steps of the computer-implemented method by a computer system with at least a processor and a memory, the computer-implemented steps of the method including: a) receiving a current instance of data in memory comprising an input buffer; b) selecting a candidate chunk of a representation of the current instance from the input buffer; c) computing by the processor a signature hash from a signature length range of data starting in the candidate chunk; d) identifying a matching dictionary entry stored in memory having a matching signature hash from a multi-tiered dictionary, wherein the matching dictionary entry prospectively identifies a location of a prior occurrence of a selected range of consecutive symbols including the signature length range of data within at least one of the representation of the current instance of data and a representation of a prior instance of data in the input buffer; e) computing a dedupe processed representation of the instance of data in the input buffer, wherein a dedupe item is substituted for the selected range of consecutive symbols if the selected range is verified as recurring, wherein the dedupe item identifies the location of the prior occurrence of the selected range; and f) making the dedupe processed representation of the instance of data available for communication to a target computer. | 1. A computer-implemented method of compressing data, comprising carrying out steps of the computer-implemented method by a computer system with at least a processor and a memory, the computer-implemented steps of the method including: a) receiving a current instance of data in memory comprising an input buffer; b) selecting a candidate chunk of a representation of the current instance from the input buffer; c) computing by the processor a signature hash from a signature length range of data starting in the candidate chunk; d) identifying a matching dictionary entry stored in memory having a matching signature hash from a multi-tiered dictionary, wherein the matching dictionary entry prospectively identifies a location of a prior occurrence of a selected range of consecutive symbols including the signature length range of data within at least one of the representation of the current instance of data and a representation of a prior instance of data in the input buffer; e) computing a dedupe processed representation of the instance of data in the input buffer, wherein a dedupe item is substituted for the selected range of consecutive symbols if the selected range is verified as recurring, wherein the dedupe item identifies the location of the prior occurrence of the selected range; and f) making the dedupe processed representation of the instance of data available for communication to a target computer. 20. The computer-implemented method of claim 1 wherein the dictionary provides a signature count number of signature hash and offset pairs for dictionary entries, wherein each signature hash for a given dictionary entry is associated with a unique remainder as determined from mod (signature hash, signature count). | 0.576613 |
9,430,547 | 1 | 11 | 1. A computing system hosting an in-memory database, the system comprising: a partitioner node comprising a processor configured to, in response to receiving a collection of one or more records of the in-memory database, determine whether to compress the collection based on a machine-readable schema file associated with the collection, logically partition the collection into one or more partitions according to the schema file, and distribute the one or more partitions to one or more storage nodes according to the schema file; a storage node comprising a non-transitory machine-readable main memory storing a partition of the in-memory database received from one or more partitioner nodes associated with the storage node according to the schema file; a search manager node comprising a processor configured to receive a search query from a client device of the system, and transmit the search queries as search conductor queries to one or more search conductors upon receiving the search query from the client device, wherein the search query is a machine-readable computer file containing parameters associated with one or more records satisfying the search query, and wherein the search manager node transmits the search queries to the one or more search conductors in accordance with the schema file; a search conductor node associated with one or more partitioners according to the schema file and comprising a processor configured to, in response to receiving a search conductor query from the search manager node: query a set of one or more partitions of the in-memory database as indicated by the search conductor query, identify one or more candidate records of the in-memory database stored in the set of partitions queried by the search conductor, calculate a first score for each respective candidate record using a scoring algorithm, and transmit to the search manager node a set of one or more query results containing one or more candidate records satisfying a threshold value; and an analytics agent node comprising a processor configured to automatically generate a machine-readable computer file containing a set of one or more results derived from the set of query results, responsive to identifying in the set of query results received from the search manager node, wherein each of the storage node, the search conductor node, and the analytics agent node is a distinct node. | 1. A computing system hosting an in-memory database, the system comprising: a partitioner node comprising a processor configured to, in response to receiving a collection of one or more records of the in-memory database, determine whether to compress the collection based on a machine-readable schema file associated with the collection, logically partition the collection into one or more partitions according to the schema file, and distribute the one or more partitions to one or more storage nodes according to the schema file; a storage node comprising a non-transitory machine-readable main memory storing a partition of the in-memory database received from one or more partitioner nodes associated with the storage node according to the schema file; a search manager node comprising a processor configured to receive a search query from a client device of the system, and transmit the search queries as search conductor queries to one or more search conductors upon receiving the search query from the client device, wherein the search query is a machine-readable computer file containing parameters associated with one or more records satisfying the search query, and wherein the search manager node transmits the search queries to the one or more search conductors in accordance with the schema file; a search conductor node associated with one or more partitioners according to the schema file and comprising a processor configured to, in response to receiving a search conductor query from the search manager node: query a set of one or more partitions of the in-memory database as indicated by the search conductor query, identify one or more candidate records of the in-memory database stored in the set of partitions queried by the search conductor, calculate a first score for each respective candidate record using a scoring algorithm, and transmit to the search manager node a set of one or more query results containing one or more candidate records satisfying a threshold value; and an analytics agent node comprising a processor configured to automatically generate a machine-readable computer file containing a set of one or more results derived from the set of query results, responsive to identifying in the set of query results received from the search manager node, wherein each of the storage node, the search conductor node, and the analytics agent node is a distinct node. 11. The system according to claim 1 , wherein the partitioner assigns a unique record identifier to each of the respective records stored in the collection according to the schema file, and generates a machine-readable index file associated with each of the partitions of the collection using the unique record identifier assigned to each respective record in the collection. | 0.678388 |
9,589,234 | 2 | 3 | 2. The method of claim 1 , further comprising adding a detected missing case according to said labeling in said constraint model. | 2. The method of claim 1 , further comprising adding a detected missing case according to said labeling in said constraint model. 3. The method of claim 2 , further comprising generating a family of missing cases by grouping a plurality of missing cases utilizing one or more truth values of nodes of the constraint model. | 0.5 |
9,507,519 | 21 | 24 | 21. A mobile computing device comprising: a processor; a display responsive to the processor; at least one local storage device responsive to the processor; and instructions in the local storage device that, when executed by the mobile computing device, enable the mobile computing device to perform operations comprising: in a first portion of the display, displaying at least part of an electronic form containing input objects to accept user input; displaying a virtual keyboard in a second portion of the display, wherein the second portion of the display is distinct from the first portion of the display, and wherein the virtual keyboard comprises at least a first alphabetic button to enable a user to enter a first alphabetic character and a second alphabetic button to enable the user to enter a second alphabetic character; automatically parsing the electronic form to discover attributes of at least one of the input objects in the electronic form; automatically determining whether the electronic form includes a non-textual input object, based on results of the parsing; and in response to discovering that the electronic form includes a non-textual input object, automatically adding a corresponding non-textual virtual keyboard component to the virtual keyboard; wherein displaying the virtual keyboard comprises displaying the virtual keyboard with the first and second alphabetic buttons and with the added non-textual virtual keyboard component in the second portion of the display; and wherein the added non-textual virtual keyboard component is configured to allow a user to invoke, from the virtual keyboard, a function associated with the corresponding non-textual input object in the electronic form. | 21. A mobile computing device comprising: a processor; a display responsive to the processor; at least one local storage device responsive to the processor; and instructions in the local storage device that, when executed by the mobile computing device, enable the mobile computing device to perform operations comprising: in a first portion of the display, displaying at least part of an electronic form containing input objects to accept user input; displaying a virtual keyboard in a second portion of the display, wherein the second portion of the display is distinct from the first portion of the display, and wherein the virtual keyboard comprises at least a first alphabetic button to enable a user to enter a first alphabetic character and a second alphabetic button to enable the user to enter a second alphabetic character; automatically parsing the electronic form to discover attributes of at least one of the input objects in the electronic form; automatically determining whether the electronic form includes a non-textual input object, based on results of the parsing; and in response to discovering that the electronic form includes a non-textual input object, automatically adding a corresponding non-textual virtual keyboard component to the virtual keyboard; wherein displaying the virtual keyboard comprises displaying the virtual keyboard with the first and second alphabetic buttons and with the added non-textual virtual keyboard component in the second portion of the display; and wherein the added non-textual virtual keyboard component is configured to allow a user to invoke, from the virtual keyboard, a function associated with the corresponding non-textual input object in the electronic form. 24. A mobile computing device according to claim 21 , wherein: the operation of displaying at least part of the electronic form in the first portion of the display comprises displaying a first part of the electronic form that does not include the non-textual input object in the first portion of the display; and the operation of displaying the virtual keyboard in the second portion of the display comprises displaying the virtual keyboard with the added non-textual virtual keyboard component in the second portion of the display, while the first part of the electronic form that does not include the non-textual input object is displayed in the first portion of the display. | 0.5 |
7,962,331 | 1 | 3 | 1. A method of tuning a speech recognizer, the method comprising: playing a selected portion of a digital audio data file with a digital audio player; creating and/or modifying a digital transcript of the selected audio portion; displaying information associated with a decode of the selected audio portion on an electronic display, wherein the displayed information includes a menu of selectable noise tags for identifying noise events in the transcript; receiving an input selected from the displayed menu, the input identifying at least one noise event in the transcript; modifying, by a computing device, the transcript based on the input; and utilizing the modified transcript to improve the performance of the speech recognizer. | 1. A method of tuning a speech recognizer, the method comprising: playing a selected portion of a digital audio data file with a digital audio player; creating and/or modifying a digital transcript of the selected audio portion; displaying information associated with a decode of the selected audio portion on an electronic display, wherein the displayed information includes a menu of selectable noise tags for identifying noise events in the transcript; receiving an input selected from the displayed menu, the input identifying at least one noise event in the transcript; modifying, by a computing device, the transcript based on the input; and utilizing the modified transcript to improve the performance of the speech recognizer. 3. The method of claim 1 , wherein the information comprises a confidence score. | 0.832636 |
8,527,965 | 12 | 16 | 12. A non-transitory computer readable medium comprising instructions for analyzing a plurality of potential bug statements, the instructions comprising functionality for: obtaining a plurality of static program analyses; recursively reducing the plurality of potential bug statements in the source code by: selecting a static program analysis for each recursion from the plurality of static program analyses in order from least time consuming to most time consuming; evaluating the plurality of potential bug statements using the static program analysis of the plurality of static program analyses to determine a subgroup of bug free statements of the plurality of potential bug statements in each recursion, wherein evaluating the plurality of potential bug statements comprises: evaluating a first potential bug statement using a first static program analysis of the plurality of static program analyses to determine whether the first potential bug statement is a bug free statement, wherein if it cannot be determined whether the first potential bug statement is a bug free statement and subsequent to evaluating the first potential bug statement using the first static program analysis, concurrently: evaluating the first potential bug statement using a second static program analysis of the plurality of static program analyses to determine whether the first potential bug statement is a bug free statement; and evaluating a second potential bug statement using the first static program analysis to determine whether the second potential bug statement is a bug free statement, wherein the first static program analysis is less time consuming than the second static program analysis; and removing the subgroup of the bug free statements from the plurality of potential bug statements to reduce the plurality of potential bug statements in each recursion; thereby filtering at least one subgroup of bug free statements out of the plurality of potential bug statements in the source code. | 12. A non-transitory computer readable medium comprising instructions for analyzing a plurality of potential bug statements, the instructions comprising functionality for: obtaining a plurality of static program analyses; recursively reducing the plurality of potential bug statements in the source code by: selecting a static program analysis for each recursion from the plurality of static program analyses in order from least time consuming to most time consuming; evaluating the plurality of potential bug statements using the static program analysis of the plurality of static program analyses to determine a subgroup of bug free statements of the plurality of potential bug statements in each recursion, wherein evaluating the plurality of potential bug statements comprises: evaluating a first potential bug statement using a first static program analysis of the plurality of static program analyses to determine whether the first potential bug statement is a bug free statement, wherein if it cannot be determined whether the first potential bug statement is a bug free statement and subsequent to evaluating the first potential bug statement using the first static program analysis, concurrently: evaluating the first potential bug statement using a second static program analysis of the plurality of static program analyses to determine whether the first potential bug statement is a bug free statement; and evaluating a second potential bug statement using the first static program analysis to determine whether the second potential bug statement is a bug free statement, wherein the first static program analysis is less time consuming than the second static program analysis; and removing the subgroup of the bug free statements from the plurality of potential bug statements to reduce the plurality of potential bug statements in each recursion; thereby filtering at least one subgroup of bug free statements out of the plurality of potential bug statements in the source code. 16. The non-transitory computer readable medium of claim 12 , wherein a time consumption of the static program analysis is determined based on a runtime complexity estimate. | 0.915938 |
9,928,241 | 1 | 9 | 1. A system for managing online documents, the system comprising: a sheet data store configured to store a plurality of sheets, wherein each sheet includes a set of rows, and wherein each row includes a set of columns; an interaction monitoring engine configured to monitor interactions by users with the plurality of sheets; an interaction data store configured to store records of the interactions monitored by the interaction monitoring engine; a sheet metadata data store configured to store sheet metadata representing relationships between sheets of the plurality of sheets; a collaboration graph generation engine configured to generate a collaboration graph that represents relationships between the sheets and the users based on the interaction records and the sheet metadata; a collaboration graph analysis engine configured to analyze vertices the collaboration graph for similarities; a visualization generation engine configured to generate one or more visualizations of collaboration graphs generated by the collaboration graph generation engine; and a collaboration graph data store configured to store a plurality of collaboration graph versions generated over time; wherein the visualizations include an animation that shows changes in the collaboration graph versions over time. | 1. A system for managing online documents, the system comprising: a sheet data store configured to store a plurality of sheets, wherein each sheet includes a set of rows, and wherein each row includes a set of columns; an interaction monitoring engine configured to monitor interactions by users with the plurality of sheets; an interaction data store configured to store records of the interactions monitored by the interaction monitoring engine; a sheet metadata data store configured to store sheet metadata representing relationships between sheets of the plurality of sheets; a collaboration graph generation engine configured to generate a collaboration graph that represents relationships between the sheets and the users based on the interaction records and the sheet metadata; a collaboration graph analysis engine configured to analyze vertices the collaboration graph for similarities; a visualization generation engine configured to generate one or more visualizations of collaboration graphs generated by the collaboration graph generation engine; and a collaboration graph data store configured to store a plurality of collaboration graph versions generated over time; wherein the visualizations include an animation that shows changes in the collaboration graph versions over time. 9. The system of claim 1 , further comprising: a front-end interface engine configured to provide a set of user interfaces to the sheets; wherein the set of user interfaces includes one or more of: a sheet management interface; and an email sharing interface. | 0.5 |
9,454,759 | 7 | 8 | 7. A method for maintaining consumer privacy in behavioral prediction scoring, comprising: receiving, by a receiver of a first computing system, a plurality of account identifiers, and, for each account identifier, a corresponding first encrypted account identifier and corresponding disguised set of consumer characteristics from a second computing system, wherein the first encrypted account identifier is a produced via encryption of the corresponding account identifier using a first one-way encryption, and wherein the receiver of the first computing system is configured to encrypt each account identifier into a second encrypted account identifier using a second one-way encryption upon receipt; receiving, by the receiver of the first computing system, a plurality of transaction data entries, wherein each transaction data entry includes data related to a payment transaction including at least a second encrypted account identifier and transaction data; and calculating, by a processor of the first computing system, a behavior prediction score corresponding to the behavior prediction request for each second encrypted account identifier based on at least the transaction data included in each transaction data entry including the respective second encrypted account identifier; and transmitting, by a transmitter of the first computing system, the calculated behavior prediction score for each second encrypted account identifier, wherein the first computing system does not receive any unencrypted account identifiers, any undisguised consumer characteristics, or any personally identifiable information. | 7. A method for maintaining consumer privacy in behavioral prediction scoring, comprising: receiving, by a receiver of a first computing system, a plurality of account identifiers, and, for each account identifier, a corresponding first encrypted account identifier and corresponding disguised set of consumer characteristics from a second computing system, wherein the first encrypted account identifier is a produced via encryption of the corresponding account identifier using a first one-way encryption, and wherein the receiver of the first computing system is configured to encrypt each account identifier into a second encrypted account identifier using a second one-way encryption upon receipt; receiving, by the receiver of the first computing system, a plurality of transaction data entries, wherein each transaction data entry includes data related to a payment transaction including at least a second encrypted account identifier and transaction data; and calculating, by a processor of the first computing system, a behavior prediction score corresponding to the behavior prediction request for each second encrypted account identifier based on at least the transaction data included in each transaction data entry including the respective second encrypted account identifier; and transmitting, by a transmitter of the first computing system, the calculated behavior prediction score for each second encrypted account identifier, wherein the first computing system does not receive any unencrypted account identifiers, any undisguised consumer characteristics, or any personally identifiable information. 8. The method of claim 7 , wherein the generated algorithm is transmitted in response to the received transmitted data. | 0.711165 |
9,224,041 | 1 | 2 | 1. A method comprising: selecting organizational table entry/target text fragment pairs of an organizational table from text fragments of a same document based on textual similarity, each pair of text fragments comprising a text fragment of an organizational table entry and a candidate target text fragment of the same document; training a classifier to identify organizational table entry/target text fragment pairs of the organizational table using a training set having positive examples including at least some of the selected organizational table entry/target text fragment pairs and negative examples including at least some text fragment pairs of the document not selected as organizational table entry/target text fragment pairs, the classifier considering features including at least one text formatting feature; and reselecting organizational table entry/target text fragment pairs of the organizational table of the document using the trained classifier. | 1. A method comprising: selecting organizational table entry/target text fragment pairs of an organizational table from text fragments of a same document based on textual similarity, each pair of text fragments comprising a text fragment of an organizational table entry and a candidate target text fragment of the same document; training a classifier to identify organizational table entry/target text fragment pairs of the organizational table using a training set having positive examples including at least some of the selected organizational table entry/target text fragment pairs and negative examples including at least some text fragment pairs of the document not selected as organizational table entry/target text fragment pairs, the classifier considering features including at least one text formatting feature; and reselecting organizational table entry/target text fragment pairs of the organizational table of the document using the trained classifier. 2. The method as set forth in claim 1 , wherein the selecting comprises: identifying a set of candidate target text fragments from the document based on textual similarity with organizational table entries; and choosing target text fragments from the set of candidate target text fragments based on a plurality of criteria. | 0.5 |
8,682,989 | 17 | 20 | 17. A system for making document changes using electronic messages, comprising: a network connection that is configured to connect to a network; a processor, memory, and a computer-readable storage medium; an operating environment stored on the computer-readable storage medium and executing on the processor; a document; and a change manager operating in conjunction with the operating environment that is configured to perform actions comprising: creating an electronic message that includes: a change made to a shared document and a comment area that is used to enter a comment that is to be included within the document for the change made to the document within a body of the electronic message, wherein the document is collaborated on by reviewers; sending the electronic message to at least a portion of the reviewers that includes the change made to the document within the body of the electronic message; receiving a reply to the electronic message that includes a received change that is to be incorporated into the document that is made without editing the document; and incorporating the received change into the document. | 17. A system for making document changes using electronic messages, comprising: a network connection that is configured to connect to a network; a processor, memory, and a computer-readable storage medium; an operating environment stored on the computer-readable storage medium and executing on the processor; a document; and a change manager operating in conjunction with the operating environment that is configured to perform actions comprising: creating an electronic message that includes: a change made to a shared document and a comment area that is used to enter a comment that is to be included within the document for the change made to the document within a body of the electronic message, wherein the document is collaborated on by reviewers; sending the electronic message to at least a portion of the reviewers that includes the change made to the document within the body of the electronic message; receiving a reply to the electronic message that includes a received change that is to be incorporated into the document that is made without editing the document; and incorporating the received change into the document. 20. The system of claim 17 , wherein receiving the reply to the electronic message that includes the received change that is to be incorporated into the document comprises determining when the received change is at least one of: a comment to the change and a revised change to the change included within the electronic message. | 0.5 |
7,536,673 | 27 | 28 | 27. A method for application business object processing, the method comprising: preparing a script comprising a plurality of business object operations for an application, wherein at least one of the inputs for the script comprises a multi- dimensional data type; determining whether a synchronization point defined by the application has occurred; if a synchronization point has occurred, preparing to send at least a portion of the script to a processing enaine for processing. the preparing further comprising: serializing the script into a transportable format, wherein an obiect reference is serialized using a name reference; and marshaling parameters of the script by mapping between a current environment and a destination environment, wherein the processing engine is operable to: receive the script; initiate execution of the operations; determine whether a result of an executed operation is input for another operation; if a result of an executed operation is input for another operation. use the result as input for the other operation; determine whether a result is relevant for an application using an identifier in the script; if a result is not relevant for the application, refuse to return the result; and return the results of the executed operations; determining whether processing of the script portion is complete; and if processing of the script portion is complete, updating return values. | 27. A method for application business object processing, the method comprising: preparing a script comprising a plurality of business object operations for an application, wherein at least one of the inputs for the script comprises a multi- dimensional data type; determining whether a synchronization point defined by the application has occurred; if a synchronization point has occurred, preparing to send at least a portion of the script to a processing enaine for processing. the preparing further comprising: serializing the script into a transportable format, wherein an obiect reference is serialized using a name reference; and marshaling parameters of the script by mapping between a current environment and a destination environment, wherein the processing engine is operable to: receive the script; initiate execution of the operations; determine whether a result of an executed operation is input for another operation; if a result of an executed operation is input for another operation. use the result as input for the other operation; determine whether a result is relevant for an application using an identifier in the script; if a result is not relevant for the application, refuse to return the result; and return the results of the executed operations; determining whether processing of the script portion is complete; and if processing of the script portion is complete, updating return values. 28. The method of claim 27 , wherein a synchronization point comprises an application requesting a value that has not been returned. | 0.622857 |
7,991,733 | 16 | 23 | 16. A computer program product comprising a computer usable medium having control logic stored therein for causing a computer to facilitate knowledge navigation and discovery, said control logic comprising: first computer readable program code means for causing the computer to load at least one data store comprising a plurality of records related to a field of endeavor; second computer readable program code means for causing the computer to load at least one thesauri, wherein said at least one thesauri contains an N number of concepts relevant to said field of endeavor, wherein said N is an integer; third computer readable program code means for causing the computer to assign a unique identifier to each of said N concepts in said thesaurus; fourth computer readable program code means for causing the computer to create an index of the locations where each of said N concepts is found within said plurality of records in said at least one data store; fifth computer readable program code means for causing the computer to search said plurality of records within said at least one data store, using said index, to determine semantic relationships between each pair of N concepts; sixth computer readable program code means for causing the computer to calculate, using the results of said fifth computer readable program code means, a Z number of semantic relationship values between each pair of N concepts, wherein said Z is an integer; seventh computer readable program code means for causing the computer to store: (i) at least one of said unique identifiers corresponding to one of said N concepts; and (ii) said Z semantic relationship values corresponding to said one of said N concepts and the remaining N−1 concepts; eighth computer readable program code means for establishing that said Z semantic relationship values are indicative of how said one of said N concepts relates to the remaining N−1 concepts in said at least one thesauri. | 16. A computer program product comprising a computer usable medium having control logic stored therein for causing a computer to facilitate knowledge navigation and discovery, said control logic comprising: first computer readable program code means for causing the computer to load at least one data store comprising a plurality of records related to a field of endeavor; second computer readable program code means for causing the computer to load at least one thesauri, wherein said at least one thesauri contains an N number of concepts relevant to said field of endeavor, wherein said N is an integer; third computer readable program code means for causing the computer to assign a unique identifier to each of said N concepts in said thesaurus; fourth computer readable program code means for causing the computer to create an index of the locations where each of said N concepts is found within said plurality of records in said at least one data store; fifth computer readable program code means for causing the computer to search said plurality of records within said at least one data store, using said index, to determine semantic relationships between each pair of N concepts; sixth computer readable program code means for causing the computer to calculate, using the results of said fifth computer readable program code means, a Z number of semantic relationship values between each pair of N concepts, wherein said Z is an integer; seventh computer readable program code means for causing the computer to store: (i) at least one of said unique identifiers corresponding to one of said N concepts; and (ii) said Z semantic relationship values corresponding to said one of said N concepts and the remaining N−1 concepts; eighth computer readable program code means for establishing that said Z semantic relationship values are indicative of how said one of said N concepts relates to the remaining N−1 concepts in said at least one thesauri. 23. The computer program product of claim 16 , wherein said field of endeavor is biomedicine, and said at least one data store is selected from the group consisting of: PubMed; UMLS; UniProtKB/Swiss-Prot; IntAct; and GO. | 0.722222 |
4,609,357 | 1 | 3 | 1. A phonetic language translation method for translating a word of any one of various languages into a graphically expressed phonetically correct sounded translation of said word, said method comprising the steps of: eliminating all silent alphabetic characters, or groups of alphabetic characters, from said word; representing all said alphabetic characters, or combinations of said characters, of said word which phonetically express the traditional speech sound of a single said alphabetic character with said single alphabetic character; representing all said alphabetic characters, or combinations of said characters, of said word which phonetically express the alphabetic characters name of a single said alphabetic character with said single alphabetic character and a first coding symbol placed proximate said single alphabetic character; and representing all said alphabetic characters and combinations of said characters of said word which phonetically express a sound other than said traditional speech sound of said single alphabetic character, or said alphabetic character name of said single alphabetic character, with a preselected coded translation character representative of each said other sound. | 1. A phonetic language translation method for translating a word of any one of various languages into a graphically expressed phonetically correct sounded translation of said word, said method comprising the steps of: eliminating all silent alphabetic characters, or groups of alphabetic characters, from said word; representing all said alphabetic characters, or combinations of said characters, of said word which phonetically express the traditional speech sound of a single said alphabetic character with said single alphabetic character; representing all said alphabetic characters, or combinations of said characters, of said word which phonetically express the alphabetic characters name of a single said alphabetic character with said single alphabetic character and a first coding symbol placed proximate said single alphabetic character; and representing all said alphabetic characters and combinations of said characters of said word which phonetically express a sound other than said traditional speech sound of said single alphabetic character, or said alphabetic character name of said single alphabetic character, with a preselected coded translation character representative of each said other sound. 3. The phonetic language translation method of claim 1 comprising the further step of dividing said word into said word's sounded syllables. | 0.809783 |
9,008,490 | 16 | 17 | 16. The computer-readable medium of claim 15 , wherein comparing the monophonic melody line extracted from the audio channel of the data encoding the sounds produced by the human voice with the one or more monophonic melody lines of the candidate videos of the subset comprises: selecting, from among a collection of videos, the set of candidate videos that are each (i) identified as being associated with the particular song, and (ii) are classified as a cappella video recordings; extracting, from each of the candidate videos of the set that (i) are identified as being associated with the particular song, and (ii) are classified as a cappella video recordings, a monophonic melody line from an audio channel of the candidate video; selecting, from among the set of candidate videos that are each (i) identified as being associated with the particular song, and (ii) are classified as a cappella video recordings, the subset of candidate videos based on a similarity of the monophonic melody lines of the candidate videos of the subset with each other; and providing, to the recognizer that recognizes songs from sounds produced by a human voice, one or more of the monophonic melody lines of the candidate videos of the subset. | 16. The computer-readable medium of claim 15 , wherein comparing the monophonic melody line extracted from the audio channel of the data encoding the sounds produced by the human voice with the one or more monophonic melody lines of the candidate videos of the subset comprises: selecting, from among a collection of videos, the set of candidate videos that are each (i) identified as being associated with the particular song, and (ii) are classified as a cappella video recordings; extracting, from each of the candidate videos of the set that (i) are identified as being associated with the particular song, and (ii) are classified as a cappella video recordings, a monophonic melody line from an audio channel of the candidate video; selecting, from among the set of candidate videos that are each (i) identified as being associated with the particular song, and (ii) are classified as a cappella video recordings, the subset of candidate videos based on a similarity of the monophonic melody lines of the candidate videos of the subset with each other; and providing, to the recognizer that recognizes songs from sounds produced by a human voice, one or more of the monophonic melody lines of the candidate videos of the subset. 17. The computer-readable medium of claim 16 , wherein providing the one or more of the monophonic melody lines of the candidate videos of the subset to the recognizer that recognizes songs from sounds produced by a human voice comprises providing the identifier of the particular song to the recognizer that recognizes songs from sounds produced by a human voice. | 0.5 |
8,812,645 | 5 | 6 | 5. An article of manufacture for executing on a parallel computer system with a plurality of compute nodes comprising: a query optimizer that creates an optimized query from a query to reduce network traffic over at least one of a plurality of independent networks connecting the plurality of compute nodes to a single database on the parallel computer system, wherein the query optimizer creates the optimized query by splitting the query to use multiple independent networks of a plurality of independent networks to access the single database, wherein the query optimizer uses plan cache statistics from previously executed queries to determine whether to use the multiple independent networks to optimize the query; and non-transitory computer recordable media on which computer instructions are stored, which instructions, when read by a computer, cause the computer to perform the steps of the query optimizer; wherein the plan cache statistics comprises: query identification (ID), execution time, nodes involved, and estimated number of bytes for the query; and wherein the query optimizer uses a network file containing network file information for the multiple independent networks comprising: network ID, a timestamp; current utilization, availability, latency, and retransmits. | 5. An article of manufacture for executing on a parallel computer system with a plurality of compute nodes comprising: a query optimizer that creates an optimized query from a query to reduce network traffic over at least one of a plurality of independent networks connecting the plurality of compute nodes to a single database on the parallel computer system, wherein the query optimizer creates the optimized query by splitting the query to use multiple independent networks of a plurality of independent networks to access the single database, wherein the query optimizer uses plan cache statistics from previously executed queries to determine whether to use the multiple independent networks to optimize the query; and non-transitory computer recordable media on which computer instructions are stored, which instructions, when read by a computer, cause the computer to perform the steps of the query optimizer; wherein the plan cache statistics comprises: query identification (ID), execution time, nodes involved, and estimated number of bytes for the query; and wherein the query optimizer uses a network file containing network file information for the multiple independent networks comprising: network ID, a timestamp; current utilization, availability, latency, and retransmits. 6. The article of manufacture of claim 5 wherein the optimized query utilizes additional networks to increase communication speed to allow the query to execute faster. | 0.525568 |
8,522,133 | 12 | 15 | 12. A system comprising: token generation logic configured to generate a sequence of tokens using at least one processor, each token being an integer representation of a respective sequence of characters that is included in a style sheet, each token corresponding to a respective character position that indicates a position of that token in the style sheet; token identification logic configured to identify a designated token in the sequence of tokens that includes a user-initiated change, the designated token following a first subset of the tokens in the sequence of tokens and preceding a second subset of the tokens in the sequence of tokens; and determination logic configured to determine whether the user-initiated change is identified as a type of change that changes no attributes, other than the character positions, of the tokens in the second subset of the tokens, the determination logic further configured to determine that the second subset of the tokens is not to be re-tokenized in response to the user-initiated change being identified as a type of change that changes no attributes, other than the character positions, of the tokens in the second subset of the tokens, the determination logic further configured to determine that the second subset of the tokens is to be re-tokenized in response to the user-initiated change not being identified as a type of change that changes no attributes, other than the character positions, of the tokens in the second subset of the tokens. | 12. A system comprising: token generation logic configured to generate a sequence of tokens using at least one processor, each token being an integer representation of a respective sequence of characters that is included in a style sheet, each token corresponding to a respective character position that indicates a position of that token in the style sheet; token identification logic configured to identify a designated token in the sequence of tokens that includes a user-initiated change, the designated token following a first subset of the tokens in the sequence of tokens and preceding a second subset of the tokens in the sequence of tokens; and determination logic configured to determine whether the user-initiated change is identified as a type of change that changes no attributes, other than the character positions, of the tokens in the second subset of the tokens, the determination logic further configured to determine that the second subset of the tokens is not to be re-tokenized in response to the user-initiated change being identified as a type of change that changes no attributes, other than the character positions, of the tokens in the second subset of the tokens, the determination logic further configured to determine that the second subset of the tokens is to be re-tokenized in response to the user-initiated change not being identified as a type of change that changes no attributes, other than the character positions, of the tokens in the second subset of the tokens. 15. The system of claim 12 , wherein the token generation logic is further configured to re-tokenize an initial subset of the tokens in the sequence of tokens to provide one or more revised tokens in response to a determination that the second subset of the tokens is to be re-tokenized, the initial subset of the tokens including the designated token and the second subset of the tokens; and wherein the system further comprises: comparison logic configured to compare the initial subset of the tokens to the one or more revised tokens to determine whether a structure of the one or more revised tokens differs from a structure of the initial subset of the tokens; and parsing logic configured to parse the one or more revised tokens in response to the structure of the one or more revised tokens differing from the structure of the initial subset, the parsing logic further configured to not parse the one or more revised tokens in response to the structure of the one or more revised tokens being same as the structure of the initial subset. | 0.5 |
9,009,220 | 1 | 21 | 1. An apparatus comprising: a data storage system associated with a provider entity and storing data on behalf of a client entity, the data being accessible from the data storage system by the client entity; a data interface enabling access by the provider entity to the data of the data storage system; and an analysis engine comprising a processor and memory maintained by the provider entity to, at discrete intervals determined by the analysis engine: access the data using the data interface, identify, among the data, electronic communications at least some of which each include data identifying a sender or a receiver, the sender or receiver being an individual associated with the client entity, analyze the data, including: identifying one or more words or phrases that occur in one or more of the electronic communications and meet a threshold frequency of occurrence, and comparing the identified words or phrases to one or more words or phrases occurring in electronic communications analyzed by the analysis engine at multiple previous discrete intervals, and at times determined based on the results of the analysis and the user's preferences for receiving information, generate results of the analysis to the client entity, the results indicating a characteristic of at least one of the individuals associated with the client entity, the characteristic being related to at least one of the identified words or phrases. | 1. An apparatus comprising: a data storage system associated with a provider entity and storing data on behalf of a client entity, the data being accessible from the data storage system by the client entity; a data interface enabling access by the provider entity to the data of the data storage system; and an analysis engine comprising a processor and memory maintained by the provider entity to, at discrete intervals determined by the analysis engine: access the data using the data interface, identify, among the data, electronic communications at least some of which each include data identifying a sender or a receiver, the sender or receiver being an individual associated with the client entity, analyze the data, including: identifying one or more words or phrases that occur in one or more of the electronic communications and meet a threshold frequency of occurrence, and comparing the identified words or phrases to one or more words or phrases occurring in electronic communications analyzed by the analysis engine at multiple previous discrete intervals, and at times determined based on the results of the analysis and the user's preferences for receiving information, generate results of the analysis to the client entity, the results indicating a characteristic of at least one of the individuals associated with the client entity, the characteristic being related to at least one of the identified words or phrases. 21. The apparatus of claim 1 in which the discrete intervals each correspond to one or more measures of time. | 0.851093 |
4,639,877 | 4 | 5 | 4. A computer system in accordance with claim 2 wherein: said time delay mechanism includes a counting mechanism that is initialized to a count value equal to the numeric value of at least a portion of one of said command data entries in said command memory and that counts the passage of a number of fixed length time intervals equal to the count value. | 4. A computer system in accordance with claim 2 wherein: said time delay mechanism includes a counting mechanism that is initialized to a count value equal to the numeric value of at least a portion of one of said command data entries in said command memory and that counts the passage of a number of fixed length time intervals equal to the count value. 5. A computer system in accordance with claim 4 wherein: the fixed length of time interval is a multiple of 12.5 milliseconds. | 0.5 |
7,523,104 | 1 | 4 | 1. A structured-document search apparatus for searching a plurality of structured documents stored in a database for a document structure in a structured document corresponding to first structure-designating information, in response to a search request containing the first structure-designating information and issued from a client terminal, the first structure-designating information designating an arbitrary document structure including tags, the arbitrary document structure being a logical tree structure represented using the tags, comprising: structure-template-storing means for storing a plurality of structure templates as templates of tag structures in relation to identifiers assigned to the structure templates, the structure templates corresponding to document structures included in the structured documents stored in the database, the tag structures being logical tree structures represented using tags; a synonym dictionary which stores synonym group identifiers indicating synonym groups, and sets of tags belonging to the synonym groups, said each synonym group being a set of tags having a common concept; synonym search means for search processing for searching the synonym dictionary for synonym group identifiers indicating synonym groups to which the tags included in the first structure-designating information belong; inquiry means for inquiring of a user of the client terminal, when the synonym search means detects the synonym group identifiers indicating synonym groups to which the tags included in the first structure-designating information belong, which one of synonym groups indicated by the synonym group identifiers for said tags should be selected, said tags included in the first structure- designating information corresponding to the detected synonym group identifiers; structure-designating-information generation means for generating, based on a search result of the synonym search means for search processing, second structure-designating information in which the tags included in the first structure-designating information are replaced with the respective synonym group identifiers based on the user's selection; synonym-structure-template-storing means for storing synonym structure templates in which all tags included in the structure templates stored in the structure-template-storing means are replaced with the synonym group identifiers indicating the synonym groups to which said all tags belong; synonym-structure-template-searching means for searching the synonym-structure-template-storing means for a synonym structure template corresponding to the second structure-designating information; and acquisition means for acquiring, from the database, a document structure in a structured document indicated by the structure template searched for by the synonym-structure-template-searching means. | 1. A structured-document search apparatus for searching a plurality of structured documents stored in a database for a document structure in a structured document corresponding to first structure-designating information, in response to a search request containing the first structure-designating information and issued from a client terminal, the first structure-designating information designating an arbitrary document structure including tags, the arbitrary document structure being a logical tree structure represented using the tags, comprising: structure-template-storing means for storing a plurality of structure templates as templates of tag structures in relation to identifiers assigned to the structure templates, the structure templates corresponding to document structures included in the structured documents stored in the database, the tag structures being logical tree structures represented using tags; a synonym dictionary which stores synonym group identifiers indicating synonym groups, and sets of tags belonging to the synonym groups, said each synonym group being a set of tags having a common concept; synonym search means for search processing for searching the synonym dictionary for synonym group identifiers indicating synonym groups to which the tags included in the first structure-designating information belong; inquiry means for inquiring of a user of the client terminal, when the synonym search means detects the synonym group identifiers indicating synonym groups to which the tags included in the first structure-designating information belong, which one of synonym groups indicated by the synonym group identifiers for said tags should be selected, said tags included in the first structure- designating information corresponding to the detected synonym group identifiers; structure-designating-information generation means for generating, based on a search result of the synonym search means for search processing, second structure-designating information in which the tags included in the first structure-designating information are replaced with the respective synonym group identifiers based on the user's selection; synonym-structure-template-storing means for storing synonym structure templates in which all tags included in the structure templates stored in the structure-template-storing means are replaced with the synonym group identifiers indicating the synonym groups to which said all tags belong; synonym-structure-template-searching means for searching the synonym-structure-template-storing means for a synonym structure template corresponding to the second structure-designating information; and acquisition means for acquiring, from the database, a document structure in a structured document indicated by the structure template searched for by the synonym-structure-template-searching means. 4. The structured-document search apparatus according to claim 1 , wherein the first structure-designating information designates the arbitrary document structure by using a path. | 0.928742 |
9,966,089 | 12 | 13 | 12. A speech communication system comprising: non-transitory memory; a transcription unit, the transcription unit configured to transcribe a recorded portion of a speech communication between the at least first and second user stored in the memory to form a transcribed portion, a selecting unit, the selecting unit configured to select and mark at least one of the words of the transcribed portion which is considered to be a keyword of the speech communication, a search unit, the search unit configured to perform at least one search for each keyword and produce at least one definition for each keyword that identifies a meaning of that keyword, a trustworthiness unit, the trustworthiness unit configured to calculate a trustworthiness factor for each keyword, each trustworthiness factor indicating a calculated validity of a respective definition for a respective keyword; and a display unit, the display unit configured to display the transcribed portion such that, in response to a pointer being positioned over at least one keyword of the displayed transcribed portion or selection of at least one displayed keyword, displaying of the at least one definition of the keyword together with the calculated trustworthiness factor for each displayed definition is actuated. | 12. A speech communication system comprising: non-transitory memory; a transcription unit, the transcription unit configured to transcribe a recorded portion of a speech communication between the at least first and second user stored in the memory to form a transcribed portion, a selecting unit, the selecting unit configured to select and mark at least one of the words of the transcribed portion which is considered to be a keyword of the speech communication, a search unit, the search unit configured to perform at least one search for each keyword and produce at least one definition for each keyword that identifies a meaning of that keyword, a trustworthiness unit, the trustworthiness unit configured to calculate a trustworthiness factor for each keyword, each trustworthiness factor indicating a calculated validity of a respective definition for a respective keyword; and a display unit, the display unit configured to display the transcribed portion such that, in response to a pointer being positioned over at least one keyword of the displayed transcribed portion or selection of at least one displayed keyword, displaying of the at least one definition of the keyword together with the calculated trustworthiness factor for each displayed definition is actuated. 13. The speech communication system of claim 12 , further comprising: a recording unit, the recording unit configured to record real-time speech communication. | 0.756135 |
8,364,776 | 1 | 2 | 1. A computing system implemented process for employing user input to classify unknown websites comprising: using a processor associated with a computing system to monitor websites accessed by and/or through a given user computing system; using a processor associated with a computing system to compare a given website accessed by and/or through the given user computing system with known website classification data in an attempt to classify the given website accessed by and/or through the given user computing system as a malicious website or a legitimate website; as a result of the comparison of the given website accessed by and/or through the given user computing system with the known website classification data, determining that the given website accessed by and/or through the given user computing system cannot currently be classified as either a malicious website or a legitimate website, thereby transforming the status of the given website accessed by and/or through the given user computing system to a given unknown/unclassified website; requesting user input regarding the legitimacy of the given unknown/unclassified website from a given user associated with the given user computing system; obtaining user input regarding the legitimacy of the given unknown/unclassified website from the given user associated with the given user computing system; storing data representing the user input regarding the legitimacy of the given unknown/unclassified website in a memory system associated with a computing system; obtaining data representing a classification of the given unknown/unclassified website from at least one source other than the given user associated with the given user computing system, thereby transforming the status of the given unknown/unclassified website accessed by and/or through the given user computing system to a known/classified website; using a processor associated with a computing system to compare the data representing the user input regarding the legitimacy of the given unknown/unclassified website with the data representing the classification of the given unknown/unclassified website from at least one source other than the given user associated with the given user computing system to determine the accuracy of the user input regarding the legitimacy of the given unknown/unclassified website; using a processor associated with a computing system to calculate a reliability score to be associated with the given user, the reliability score being calculated based, at least in part, on the comparison of the data representing the user input regarding the legitimacy of the given unknown/unclassified website with the data representing a classification of the given unknown/unclassified website from at least one source other than the given user; and using a processor associated with a computing system to the determine a value to be assigned to future user input regarding the legitimacy of unknown/unclassified websites from the given user based, at least in part, on the given user's reliability score, thereby transforming subsequent data representing user input regarding the legitimacy of unknown/unclassified websites from the given user into weighted data representing user input regarding the legitimacy of unknown/unclassified websites. | 1. A computing system implemented process for employing user input to classify unknown websites comprising: using a processor associated with a computing system to monitor websites accessed by and/or through a given user computing system; using a processor associated with a computing system to compare a given website accessed by and/or through the given user computing system with known website classification data in an attempt to classify the given website accessed by and/or through the given user computing system as a malicious website or a legitimate website; as a result of the comparison of the given website accessed by and/or through the given user computing system with the known website classification data, determining that the given website accessed by and/or through the given user computing system cannot currently be classified as either a malicious website or a legitimate website, thereby transforming the status of the given website accessed by and/or through the given user computing system to a given unknown/unclassified website; requesting user input regarding the legitimacy of the given unknown/unclassified website from a given user associated with the given user computing system; obtaining user input regarding the legitimacy of the given unknown/unclassified website from the given user associated with the given user computing system; storing data representing the user input regarding the legitimacy of the given unknown/unclassified website in a memory system associated with a computing system; obtaining data representing a classification of the given unknown/unclassified website from at least one source other than the given user associated with the given user computing system, thereby transforming the status of the given unknown/unclassified website accessed by and/or through the given user computing system to a known/classified website; using a processor associated with a computing system to compare the data representing the user input regarding the legitimacy of the given unknown/unclassified website with the data representing the classification of the given unknown/unclassified website from at least one source other than the given user associated with the given user computing system to determine the accuracy of the user input regarding the legitimacy of the given unknown/unclassified website; using a processor associated with a computing system to calculate a reliability score to be associated with the given user, the reliability score being calculated based, at least in part, on the comparison of the data representing the user input regarding the legitimacy of the given unknown/unclassified website with the data representing a classification of the given unknown/unclassified website from at least one source other than the given user; and using a processor associated with a computing system to the determine a value to be assigned to future user input regarding the legitimacy of unknown/unclassified websites from the given user based, at least in part, on the given user's reliability score, thereby transforming subsequent data representing user input regarding the legitimacy of unknown/unclassified websites from the given user into weighted data representing user input regarding the legitimacy of unknown/unclassified websites. 2. The computing system implemented process for employing user input to classify unknown websites of claim 1 , wherein: the data representing a classification of the given unknown/unclassified website from at least one source other than the given user associated with the given user computing system is obtained from one or more sources other than the given user associated with the given user computing system selected from the group of sources other than the given user associated with the given user computing system consisting of: analysis of the given unknown/unclassified website performed by a security system associated with the computing system implemented process for employing user input to classify unknown websites; analysis of the given unknown/unclassified website performed by a third party; and user input from one or more users other than the given user associated with the given user computing system. | 0.708307 |
9,686,337 | 1 | 5 | 1. A method comprising: by one or more computer systems, accessing a social graph of a social-networking system, the social graph comprising: user nodes that are each associated with a respective user of the social-networking system; concept nodes that each correspond to a respective device; and a plurality of ownership edges connecting the user nodes and the concept nodes, each particular ownership edge indicating that a particular user corresponding to a particular user node owns a particular device corresponding to a particular concept node; by the one or more computer systems, determining from the social graph a device of a user of the social-networking system; by the one or more computer systems, determining, from the social graph, media content that a friend or a connection of the user in the social graph is currently viewing; and by the one or more computer systems, providing the media content that the friend or the connection of the user is currently viewing for display on the device of the user. | 1. A method comprising: by one or more computer systems, accessing a social graph of a social-networking system, the social graph comprising: user nodes that are each associated with a respective user of the social-networking system; concept nodes that each correspond to a respective device; and a plurality of ownership edges connecting the user nodes and the concept nodes, each particular ownership edge indicating that a particular user corresponding to a particular user node owns a particular device corresponding to a particular concept node; by the one or more computer systems, determining from the social graph a device of a user of the social-networking system; by the one or more computer systems, determining, from the social graph, media content that a friend or a connection of the user in the social graph is currently viewing; and by the one or more computer systems, providing the media content that the friend or the connection of the user is currently viewing for display on the device of the user. 5. The method of claim 1 , wherein the media content comprises: a show; a movie; a picture; a desktop; or music. | 0.895131 |
8,548,983 | 1 | 3 | 1. A method comprising: transforming a first query, comprising a first lateral view that includes a first predicate that references a database object that is joined with the first lateral view, to a second query that includes: a second view without the first predicate that references the database object, wherein the database object is joined with the second view, and a second predicate outside the second view, wherein the second predicate corresponds to the first predicate, wherein the second predicate references the second view, and wherein the second query is semantically equivalent to the first query; causing execution of the second query instead of the first query; wherein the method is performed by one or more computing devices. | 1. A method comprising: transforming a first query, comprising a first lateral view that includes a first predicate that references a database object that is joined with the first lateral view, to a second query that includes: a second view without the first predicate that references the database object, wherein the database object is joined with the second view, and a second predicate outside the second view, wherein the second predicate corresponds to the first predicate, wherein the second predicate references the second view, and wherein the second query is semantically equivalent to the first query; causing execution of the second query instead of the first query; wherein the method is performed by one or more computing devices. 3. The method of claim 1 , wherein the second predicate references both the database object and the second view. | 0.888446 |
10,068,025 | 8 | 9 | 8. A computer program product for associating geographic information with textual information, the computer program product stored on a non-transitory computer-readable medium and including instructions configured to cause a processor to carry out the steps of: receiving, from a first computer, a request for a digital map of a specified geographic region; identifying a spatial key associated with the geographic region; encrypting the identified spatial key; embedding the encrypted spatial key into the requested digital map; returning, to the first computer, the requested digital map including the encrypted spatial key; receiving, from a second computer, a request to decrypt the encrypted spatial key, the encrypted spatial key extracted by the second computer from the digital map; decrypting the spatial key; and returning, to the second computer, the decrypted spatial key. | 8. A computer program product for associating geographic information with textual information, the computer program product stored on a non-transitory computer-readable medium and including instructions configured to cause a processor to carry out the steps of: receiving, from a first computer, a request for a digital map of a specified geographic region; identifying a spatial key associated with the geographic region; encrypting the identified spatial key; embedding the encrypted spatial key into the requested digital map; returning, to the first computer, the requested digital map including the encrypted spatial key; receiving, from a second computer, a request to decrypt the encrypted spatial key, the encrypted spatial key extracted by the second computer from the digital map; decrypting the spatial key; and returning, to the second computer, the decrypted spatial key. 9. The computer program product of claim 8 further comprising instructions for embedding a bounding box in the digital map. | 0.781915 |
7,490,073 | 8 | 16 | 8. A method of encoding knowledge that can be used to automatically detect problems in software application deployments, comprising: accessing a source of knowledge describing a problem known to occur in deployments of a particular software application, and which identifies a plurality of conditions associated with the problem; generating an encoded representation of the knowledge source according to a predefined knowledge encoding methodology, said encoded representation adapted to be applied automatically by a computer to analyze data representing a current state of a monitored deployment of said software application to detect whether said conditions and said problem exist therein; and storing the encoded representation in computer storage, in a format in which the encoded representation can be used by the computer to automatically detect the problem in said monitored deployment of said software application; wherein the encoded representation of the knowledge source includes logic for automatically generating, in connection with a detection of an occurrence of the problem, a confidence value representing a confidence that the detection is accurate; wherein the encoded representation of the knowledge source specifies at least one query for affirmatively causing a collection of new telemetry data from said monitored deployment of the software application to obtain a new value of a time-varying state metric of the deployment when the encoded representation has not been previously used to evaluate said state metric during the detection of a particular one of the conditions, wherein the query is represented in the encoded representation, the encoded representation being configured to be used in combination with at least the value obtained via said query to evaluate whether the problem exists in the deployment. | 8. A method of encoding knowledge that can be used to automatically detect problems in software application deployments, comprising: accessing a source of knowledge describing a problem known to occur in deployments of a particular software application, and which identifies a plurality of conditions associated with the problem; generating an encoded representation of the knowledge source according to a predefined knowledge encoding methodology, said encoded representation adapted to be applied automatically by a computer to analyze data representing a current state of a monitored deployment of said software application to detect whether said conditions and said problem exist therein; and storing the encoded representation in computer storage, in a format in which the encoded representation can be used by the computer to automatically detect the problem in said monitored deployment of said software application; wherein the encoded representation of the knowledge source includes logic for automatically generating, in connection with a detection of an occurrence of the problem, a confidence value representing a confidence that the detection is accurate; wherein the encoded representation of the knowledge source specifies at least one query for affirmatively causing a collection of new telemetry data from said monitored deployment of the software application to obtain a new value of a time-varying state metric of the deployment when the encoded representation has not been previously used to evaluate said state metric during the detection of a particular one of the conditions, wherein the query is represented in the encoded representation, the encoded representation being configured to be used in combination with at least the value obtained via said query to evaluate whether the problem exists in the deployment. 16. The method of claim 8 , wherein the encoded representation of the knowledge source comprises a plurality of logic gates, wherein at least one of the gates is configured to produce a bead if a condition exists within the deployment, and at least another of the gates is configured to receive at least one bead as an input and produce an output bead, the beads configured to be represented in computer storage, containing variable substitutions, and capable of propagating time information representative of times that particular conditions are detected, such that the time information can be used to detect the problem. | 0.5 |
9,548,066 | 22 | 23 | 22. The method of claim 6 , wherein the audio signal is a first audio signal, wherein the user speech is user speech, and wherein the intent is a first intent, the method further comprising: receiving a second audio signal that represents second user speech from the speech interface device, wherein the second user speech indicates a second intent; performing natural language understanding on the second audio signal to determine the second intent; and providing a second indication of the second intent to the speech interface device. | 22. The method of claim 6 , wherein the audio signal is a first audio signal, wherein the user speech is user speech, and wherein the intent is a first intent, the method further comprising: receiving a second audio signal that represents second user speech from the speech interface device, wherein the second user speech indicates a second intent; performing natural language understanding on the second audio signal to determine the second intent; and providing a second indication of the second intent to the speech interface device. 23. The method of claim 22 , further comprising determining that no application for responding to the second intent has been selected by the user for execution on the one or more server computers. | 0.5 |
8,706,487 | 10 | 14 | 10. A speech recognition method carried out by a speech recognition apparatus, comprising steps of: classifying speaking sections included in speech data according to lengths of the speaking sections; classifying detailed data parts corresponding to predetermined parts in each of the classified speaking sections according to start time of the predetermined parts; learning acoustic models about a set of phonemes and language models about a chain probability of a word group consisting of the set of phonemes by using the classified detailed data parts specified both of the lengths of the speaking sections and the start time of the predetermined parts; and implementing a speech recognition process by using the learned acoustic models and language models. | 10. A speech recognition method carried out by a speech recognition apparatus, comprising steps of: classifying speaking sections included in speech data according to lengths of the speaking sections; classifying detailed data parts corresponding to predetermined parts in each of the classified speaking sections according to start time of the predetermined parts; learning acoustic models about a set of phonemes and language models about a chain probability of a word group consisting of the set of phonemes by using the classified detailed data parts specified both of the lengths of the speaking sections and the start time of the predetermined parts; and implementing a speech recognition process by using the learned acoustic models and language models. 14. The speech recognition method according to claim 10 , wherein when learning acoustic models, the speech recognition apparatus recognizes a length of a speaking section in speech data having power more than a threshold, as the speaking length. | 0.764818 |
9,600,842 | 15 | 17 | 15. The apparatus of claim 1 , wherein the system is configured such that the processing includes creating software elements having a format with a hierarchal relationship between the software elements based on the at least one original document. | 15. The apparatus of claim 1 , wherein the system is configured such that the processing includes creating software elements having a format with a hierarchal relationship between the software elements based on the at least one original document. 17. The apparatus of claim 15 , wherein the system is configured such that the at least one computer-readable XML-compliant data document is generated by retrieving the at least one original value from at least one of the plurality of original documents. | 0.5 |
7,602,309 | 1 | 3 | 1. A method of managing data stored in a electronic device, the method comprising: electronically identifying a user input written on a display of the electronic device as a written user direction to transfer data displayed on the electronic device, the written user input defining at least one alphanumeric character; determining a desired memory storage location for the data displayed on the electronic device responsive to the written user direction, wherein the desired memory storage location corresponds to the alphanumeric character defined by the written user input; and transferring the data displayed on the electronic device to the desired memory storage location responsive to the determination. | 1. A method of managing data stored in a electronic device, the method comprising: electronically identifying a user input written on a display of the electronic device as a written user direction to transfer data displayed on the electronic device, the written user input defining at least one alphanumeric character; determining a desired memory storage location for the data displayed on the electronic device responsive to the written user direction, wherein the desired memory storage location corresponds to the alphanumeric character defined by the written user input; and transferring the data displayed on the electronic device to the desired memory storage location responsive to the determination. 3. The method of claim 1 , wherein receiving the written user input defining at least one alphanumeric character and/or symbol comprises: receiving the written user input comprising moving a cursor displayed on the electronic device using a mouse, trackball, and/or joystick to define the at least one alphanumeric character and/or symbol. | 0.518466 |
8,352,273 | 8 | 9 | 8. The method according to claim 6 , wherein the outputting step includes the steps of: referring to a speech knowledge including a plurality of sentence patterns relevant to the corresponding domain, and calculating a degree of adaptation between the speech and each of the plurality of sentence patterns; and selecting the sentence pattern having a highest degree of adaptation, and outputting the selected sentence pattern and the degree of adaptation of the sentence pattern as a speech understanding result. | 8. The method according to claim 6 , wherein the outputting step includes the steps of: referring to a speech knowledge including a plurality of sentence patterns relevant to the corresponding domain, and calculating a degree of adaptation between the speech and each of the plurality of sentence patterns; and selecting the sentence pattern having a highest degree of adaptation, and outputting the selected sentence pattern and the degree of adaptation of the sentence pattern as a speech understanding result. 9. The method according to claim 8 , wherein the selecting step includes the step of calculating a degree of reliability by multiplying the degree of adaptation by a weight set for each of the plurality of domains, and selecting the domain having a highest degree of reliability as the relevant domain. | 0.5 |
7,672,985 | 1 | 6 | 1. A computer implemented method for processing database content, the method comprising the steps of: syndicating one or more data objects associated with a term database to one or more remote computers, wherein the one or more data objects contain data associated with one or more terms; parsing one or more documents to identify at least one term based on at least one rule; identifying content for the at least one term; and associating the at least one term with the identified content; wherein the one or more data objects associated with the term database provide a representation of at least a portion of the term database at the one or more remote computers and are used to link the identified content with the at least one term. | 1. A computer implemented method for processing database content, the method comprising the steps of: syndicating one or more data objects associated with a term database to one or more remote computers, wherein the one or more data objects contain data associated with one or more terms; parsing one or more documents to identify at least one term based on at least one rule; identifying content for the at least one term; and associating the at least one term with the identified content; wherein the one or more data objects associated with the term database provide a representation of at least a portion of the term database at the one or more remote computers and are used to link the identified content with the at least one term. 6. The method of claim 1 , wherein the one or more remote computers access data associated with the term database for linking to the supplemental content, without a connection to the term database. | 0.548165 |
8,103,613 | 1 | 34 | 1. A system in the form of a machine, article of manufacture, or composition of matter, comprising: an objective occurrence data solicitation module configured to solicit at least a portion of objective occurrence data including soliciting data indicating incidence of at least one objective occurrence, the solicitation being prompted based at least in part on a hypothesis linking one or more objective occurrences with one or more subjective user states and in response, at least in part, to an occurrence of at least one subjective user state associated with a user; and an objective occurrence data acquisition module configured to acquire the objective occurrence data, the objective occurrence data to be acquired including the data indicating incidence of at least one objective occurrence. | 1. A system in the form of a machine, article of manufacture, or composition of matter, comprising: an objective occurrence data solicitation module configured to solicit at least a portion of objective occurrence data including soliciting data indicating incidence of at least one objective occurrence, the solicitation being prompted based at least in part on a hypothesis linking one or more objective occurrences with one or more subjective user states and in response, at least in part, to an occurrence of at least one subjective user state associated with a user; and an objective occurrence data acquisition module configured to acquire the objective occurrence data, the objective occurrence data to be acquired including the data indicating incidence of at least one objective occurrence. 34. The system of claim 1 , wherein said objective occurrence data acquisition module configured to acquire the objective occurrence data, the objective occurrence data to be acquired including the data indicating incidence of at least one objective occurrence comprises: an objective occurrence data reception module configured to receive at least the data indicating incidence of at least one objective occurrence. | 0.75898 |
10,031,967 | 6 | 7 | 6. The method of claim 1 , wherein translating of either the first phrase, the second phrase, or the third phrase comprises: extracting a word from either the first phrase, the second phrase, or the third phrase; comparing the word to entries of a database that indicates word types of known words; determining whether a word type is known based on the comparing; and in response to determining that the word type is known, replacing the word with the word type indicated in an entry corresponding with the word. | 6. The method of claim 1 , wherein translating of either the first phrase, the second phrase, or the third phrase comprises: extracting a word from either the first phrase, the second phrase, or the third phrase; comparing the word to entries of a database that indicates word types of known words; determining whether a word type is known based on the comparing; and in response to determining that the word type is known, replacing the word with the word type indicated in an entry corresponding with the word. 7. The method of claim 6 , further comprising, in response to determining that the word type is unknown: comparing the word to entries of a dictionary database to determine a grammatical category of the word; comparing the word to entries of a graph to determine a high-level category corresponding to the word; and extrapolating a word type based on the grammatical category and the high-level category. | 0.5 |
8,788,262 | 2 | 3 | 2. The method of claim 1 : wherein combining the text phrase of the abstract phrase and the text value comprises: creating a delimited phrase, comprising: inserting the text value into the abstract phrase at the particular position indicated by the variable; and inserting a delimiter before and/or after the inserted text value; wherein applying the integration rule comprises: determining whether the delimited phrase satisfies a condition of the rule, the determining based at least in part on the location of a delimiter within the delimited phrase; responsive to the determination, performing an action of the rule, the action comprising modifying the delimited phrase; and wherein the method further comprises: creating an integrated phrase, comprising removing delimiters from the delimited phrase. | 2. The method of claim 1 : wherein combining the text phrase of the abstract phrase and the text value comprises: creating a delimited phrase, comprising: inserting the text value into the abstract phrase at the particular position indicated by the variable; and inserting a delimiter before and/or after the inserted text value; wherein applying the integration rule comprises: determining whether the delimited phrase satisfies a condition of the rule, the determining based at least in part on the location of a delimiter within the delimited phrase; responsive to the determination, performing an action of the rule, the action comprising modifying the delimited phrase; and wherein the method further comprises: creating an integrated phrase, comprising removing delimiters from the delimited phrase. 3. The method of claim 2 , wherein determining whether the text of the delimited phrase satisfies a condition of the rule comprises determining whether a particular pattern of characters is present in the delimited phrase, the particular pattern including a delimiter character, and wherein modifying the delimited phrase comprises modifying the particular pattern of characters. | 0.5 |
8,239,758 | 5 | 6 | 5. A computer program product for truncating character strings in a computing environment, comprising a non-transitory computer usable medium including a computer readable program including program instructions, wherein the computer readable program when executed on a computer causes the computer to: receive a list including plural character strings; truncate one or more of the character strings to generate a display list of unique character strings based on determining a truncation location within each string, including: scoring each character in the string for similarity to the other characters in the display list and then finding the lowest scoring N characters where N is the length of the truncated string; if the determined truncation location does not reach either end of the string, then truncating at that location; wherein the strings are truncated at the beginning, end, or in between; and display the character strings of the display list in context with each other on a user interface; wherein each displayed character string is unique in relation to the other displayed character strings, enabling a user to more easily differentiate between the displayed character string. | 5. A computer program product for truncating character strings in a computing environment, comprising a non-transitory computer usable medium including a computer readable program including program instructions, wherein the computer readable program when executed on a computer causes the computer to: receive a list including plural character strings; truncate one or more of the character strings to generate a display list of unique character strings based on determining a truncation location within each string, including: scoring each character in the string for similarity to the other characters in the display list and then finding the lowest scoring N characters where N is the length of the truncated string; if the determined truncation location does not reach either end of the string, then truncating at that location; wherein the strings are truncated at the beginning, end, or in between; and display the character strings of the display list in context with each other on a user interface; wherein each displayed character string is unique in relation to the other displayed character strings, enabling a user to more easily differentiate between the displayed character string. 6. The computer program product of claim 5 wherein determining the truncation location further includes determining the truncation location at the start of the string or at the end of the string or in between, to generate a display list of character strings where each string is unique in relation to other strings. | 0.5 |
9,015,081 | 14 | 18 | 14. A system for predicting escalations, comprising: a feature extraction component configured to extract an escalation feature from a webpage; a classification component configured to run the escalation feature through a classifier; and generate an escalation likelihood result from running the escalation feature through the classifier, the escalation likelihood result comprising at least one of: an estimation that a subsequent search query will comprise an escalation when compared to a previous search query; or an estimation that a subsequent webpage selection will comprise an escalation when compared to a previous webpage selection; a component configured to generate a resource utilization intent (RUI) likelihood result from running the escalation feature through the classifier, the RUI likelihood result comprising an estimation that a second subsequent search query will comprise a resource identification query, where a resource identified by the resource identification query comprises at least one of a service or a good related to a prior search query; and a processing unit configured to implement at least some of at least one of the feature extraction component, the classification component or the component. | 14. A system for predicting escalations, comprising: a feature extraction component configured to extract an escalation feature from a webpage; a classification component configured to run the escalation feature through a classifier; and generate an escalation likelihood result from running the escalation feature through the classifier, the escalation likelihood result comprising at least one of: an estimation that a subsequent search query will comprise an escalation when compared to a previous search query; or an estimation that a subsequent webpage selection will comprise an escalation when compared to a previous webpage selection; a component configured to generate a resource utilization intent (RUI) likelihood result from running the escalation feature through the classifier, the RUI likelihood result comprising an estimation that a second subsequent search query will comprise a resource identification query, where a resource identified by the resource identification query comprises at least one of a service or a good related to a prior search query; and a processing unit configured to implement at least some of at least one of the feature extraction component, the classification component or the component. 18. The system of claim 14 , the feature extraction component configured to extract the escalation feature from one or more of: a user session; or a user session history. | 0.647303 |
8,713,034 | 16 | 17 | 16. The system of claim 12 , wherein the descriptiveness score retriever is configured to retrieve a first descriptiveness score for each pair of consecutive words, and the descriptiveness score modifier is configured to modify the first descriptiveness score for each pair of consecutive words. | 16. The system of claim 12 , wherein the descriptiveness score retriever is configured to retrieve a first descriptiveness score for each pair of consecutive words, and the descriptiveness score modifier is configured to modify the first descriptiveness score for each pair of consecutive words. 17. The system of claim 16 , further comprising: a second descriptive database configured to store descriptiveness scores for a second corpus, the second corpus being of first and last names of persons, wherein: the descriptiveness score retriever is configured to retrieve a second descriptiveness score for each pair of consecutive words in a current document from the second descriptive database, and a factor upon which the modification of the first descriptiveness score for each pair of consecutive words is based is the second descriptiveness score for the pair of consecutive words. | 0.5 |
9,836,503 | 19 | 20 | 19. A computer system comprising: a query processor to receive a SQL database query language statement on a SQL database, wherein the SQL database query language statement comprises one or more SQL query clauses and a table function that transforms at least one SPARQL endpoint into a row source for the SQL database to integrate local relational data with non-local RDF data retrieved from the one or more SPARQL endpoints, and a SPARQL query string and at least one SPARQL endpoint of one or more SPARQL endpoints are embedded in the table function of SQL database query language statement; an SQL database engine that executes the SQL database query language statement including the table function on the SQL database to transform the at least one SPARQL endpoint into a row source for the SQL database, wherein during execution of the SQL database query language statement on the SQL database, the SQL database engine is further configured to execute the one or more SQL query language strings on the SQL database, to send at least the SPARQL query string embedded in the SQL database query language statement to the at least one SPARQL endpoint that is embedded in the SQL database query language statement, wherein the at least one SPARQL endpoint is identified by parsing at least the table function in the SQL database query language statement that has been executed, to receive query results from the at least one SPARQL endpoint, at least a portion of the query results corresponding to the non-local RDF data, to convert the non-local RDF data into a relational data format to generate converted RDF data, and to combine the converted RDF data with relational data from a local relational database. | 19. A computer system comprising: a query processor to receive a SQL database query language statement on a SQL database, wherein the SQL database query language statement comprises one or more SQL query clauses and a table function that transforms at least one SPARQL endpoint into a row source for the SQL database to integrate local relational data with non-local RDF data retrieved from the one or more SPARQL endpoints, and a SPARQL query string and at least one SPARQL endpoint of one or more SPARQL endpoints are embedded in the table function of SQL database query language statement; an SQL database engine that executes the SQL database query language statement including the table function on the SQL database to transform the at least one SPARQL endpoint into a row source for the SQL database, wherein during execution of the SQL database query language statement on the SQL database, the SQL database engine is further configured to execute the one or more SQL query language strings on the SQL database, to send at least the SPARQL query string embedded in the SQL database query language statement to the at least one SPARQL endpoint that is embedded in the SQL database query language statement, wherein the at least one SPARQL endpoint is identified by parsing at least the table function in the SQL database query language statement that has been executed, to receive query results from the at least one SPARQL endpoint, at least a portion of the query results corresponding to the non-local RDF data, to convert the non-local RDF data into a relational data format to generate converted RDF data, and to combine the converted RDF data with relational data from a local relational database. 20. The computer system of claim 19 , wherein the database engine receives at least some RDF data from the one or more SPARQL endpoints. | 0.5 |
7,852,499 | 1 | 10 | 1. Method for detecting captions in a document that includes text fragments and objects of interest, the method comprising: assigning a signature to each text fragment, the signature being the value for that text fragment of a text fragment representation comprising at least one text fragment attribute; computing a near property for each text fragment, the near property having a near value if the proximity of the text fragment to at least one object of interest in the document satisfies a near criterion and a value other than the near value otherwise; identifying a caption signature as a signature assigned to a substantial number of text fragments that are near at least one object of interest in the document, the near property being used in the identifying to recognize text fragments that are near at least one object of interest in the document, wherein the identifying includes computing a signature-nearness association score for each signature indicative of a strength of association of the signature with text fragments having the near value; and detecting one or more captions as one or more text fragments each assigned a caption signature. | 1. Method for detecting captions in a document that includes text fragments and objects of interest, the method comprising: assigning a signature to each text fragment, the signature being the value for that text fragment of a text fragment representation comprising at least one text fragment attribute; computing a near property for each text fragment, the near property having a near value if the proximity of the text fragment to at least one object of interest in the document satisfies a near criterion and a value other than the near value otherwise; identifying a caption signature as a signature assigned to a substantial number of text fragments that are near at least one object of interest in the document, the near property being used in the identifying to recognize text fragments that are near at least one object of interest in the document, wherein the identifying includes computing a signature-nearness association score for each signature indicative of a strength of association of the signature with text fragments having the near value; and detecting one or more captions as one or more text fragments each assigned a caption signature. 10. The method as set forth in claim 1 , further comprising: grouping a selected number of contiguous detected captions as an annotation. | 0.798529 |
8,156,129 | 18 | 20 | 18. A computer-readable data storage device comprising instructions that, when executed by a processor, cause the processor to perform acts comprising: receiving a first query; accessing a computer-implemented bipartite graph, wherein the bipartite graph includes a first set of nodes that represent queries and a second set of nodes that represent URLs, wherein the first set of nodes includes a first node that is representative of the first query and wherein the bipartite graph further includes a first weighted edge that couples the first node to at least one node in the second set of nodes and includes weighted edges that couple nodes in the first set of nodes with nodes in the second set of nodes; initiating a random walk from the first node, wherein edges in the random walk are selected pseudo-randomly while considering weights of the edges; and outputting a second query that is determined to be substantially similar to the first query based at least in part upon a number of steps taken during the random walk between the first node and a second node that represents the second query. | 18. A computer-readable data storage device comprising instructions that, when executed by a processor, cause the processor to perform acts comprising: receiving a first query; accessing a computer-implemented bipartite graph, wherein the bipartite graph includes a first set of nodes that represent queries and a second set of nodes that represent URLs, wherein the first set of nodes includes a first node that is representative of the first query and wherein the bipartite graph further includes a first weighted edge that couples the first node to at least one node in the second set of nodes and includes weighted edges that couple nodes in the first set of nodes with nodes in the second set of nodes; initiating a random walk from the first node, wherein edges in the random walk are selected pseudo-randomly while considering weights of the edges; and outputting a second query that is determined to be substantially similar to the first query based at least in part upon a number of steps taken during the random walk between the first node and a second node that represents the second query. 20. The computer-readable data storage device of claim 18 , wherein the acts further comprise: subsequent to outputting the second query, replacing a first term in the first query with a second term in the second query to generate a modified query; and automatically executing a web search utilizing the modified query. | 0.682271 |
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