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8,190,609 | 19 | 25 | 19. A system for determining whether a first product is an alternative of a second product, the system comprising: a processor, computer-readable memory, and a non-transitory computer-readable storage device; first program instructions for analyzing information regarding a plurality of queries to identify a plurality of product-query pairs, each product-query pair comprising a query and a product that was previously selected from results for the query; second program instructions for determining, for each product-query pair, a number of times that the product was selected from results for the query; third program instructions for determining, for each product-query pair, whether the query of the product-query pair is associated with the product of the product-query pair based on the number of times that the product was selected from results for the query; fourth program instructions for analyzing the information regarding the plurality of queries to identify comparison queries directed to a comparison between two or more of a plurality of products; fifth program instructions for determining a first value by multiplying a ratio between a number of times that a first product (a) was selected from results for a query (x) by a ratio between a number of times that a second product (b) was selected from results for a query (y); sixth program instructions for determining a second value by multiplying the first value by a number of times that a comparison query comprising the query (x) and the query (y) was received; seventh program instructions for determining an association weight by summing the second value over all queries (x) and all queries (y); eighth program instructions for determining whether the association weight meets or exceeds a threshold; and ninth program instructions for, in response to the association weight meeting or exceeding the threshold, determining that the first product is an alternative to the second product; wherein the program instructions are stored on the non-transitory computer-readable storage device for execution by the processor via the computer-readable memory. | 19. A system for determining whether a first product is an alternative of a second product, the system comprising: a processor, computer-readable memory, and a non-transitory computer-readable storage device; first program instructions for analyzing information regarding a plurality of queries to identify a plurality of product-query pairs, each product-query pair comprising a query and a product that was previously selected from results for the query; second program instructions for determining, for each product-query pair, a number of times that the product was selected from results for the query; third program instructions for determining, for each product-query pair, whether the query of the product-query pair is associated with the product of the product-query pair based on the number of times that the product was selected from results for the query; fourth program instructions for analyzing the information regarding the plurality of queries to identify comparison queries directed to a comparison between two or more of a plurality of products; fifth program instructions for determining a first value by multiplying a ratio between a number of times that a first product (a) was selected from results for a query (x) by a ratio between a number of times that a second product (b) was selected from results for a query (y); sixth program instructions for determining a second value by multiplying the first value by a number of times that a comparison query comprising the query (x) and the query (y) was received; seventh program instructions for determining an association weight by summing the second value over all queries (x) and all queries (y); eighth program instructions for determining whether the association weight meets or exceeds a threshold; and ninth program instructions for, in response to the association weight meeting or exceeding the threshold, determining that the first product is an alternative to the second product; wherein the program instructions are stored on the non-transitory computer-readable storage device for execution by the processor via the computer-readable memory. 25. The system of claim 19 , wherein the information regarding the plurality of queries comprises information regarding a plurality of queries received at an Internet search engine and information regarding a plurality of queries received at an Internet shopping website, wherein the information regarding the plurality of queries received at the Internet search engine is used to identify the comparison queries and the information regarding the plurality of queries received at the Internet shopping website is used to identify the plurality of product-query pairs. | 0.5 |
8,612,467 | 13 | 14 | 13. An object-relational mapping (ORM) system comprising: a cache memory to store a filter object associated with a search query object; and a processing system coupled to the cache memory to: receive the search query object for a full-text search in a relational database from an application client, wherein the search query object is in a first format that is incompatible with the relational database being searched; map the search query object to a second format that is compatible with the relational database; invoke a full-text search engine to perform the full-text search in view of the mapped search query object; create the filter object in response to a determination that the filter object has not been cached within the cache memory of the ORM system; filter a search result generated from the full-text search engine using the created filter object and to return the filtered search result to the application client; cache the filter object in the cache memory of the ORM system such that the cached filter object can be used to filter a subsequent search result in response to receipt of a subsequent search query object without having to recreate the filter object; receive the subsequent search query object for a subsequent full-text search in the relational database from the application client, wherein the subsequent search query object is in the first format that is incompatible with the relational database being searched; map the subsequent search query object to the second format that is compatible with the relational database; invoke the full-text search engine to perform the subsequent full-text search in view of the mapped subsequent search query object; in response to a determination that the filter object has been cached within the cache memory of the ORM system, retrieve the cached filter object from the cache memory of the ORM system; and filter the subsequent search result generated from the full-text search engine using the retrieved filter object and return the filtered subsequent search result to the application client. | 13. An object-relational mapping (ORM) system comprising: a cache memory to store a filter object associated with a search query object; and a processing system coupled to the cache memory to: receive the search query object for a full-text search in a relational database from an application client, wherein the search query object is in a first format that is incompatible with the relational database being searched; map the search query object to a second format that is compatible with the relational database; invoke a full-text search engine to perform the full-text search in view of the mapped search query object; create the filter object in response to a determination that the filter object has not been cached within the cache memory of the ORM system; filter a search result generated from the full-text search engine using the created filter object and to return the filtered search result to the application client; cache the filter object in the cache memory of the ORM system such that the cached filter object can be used to filter a subsequent search result in response to receipt of a subsequent search query object without having to recreate the filter object; receive the subsequent search query object for a subsequent full-text search in the relational database from the application client, wherein the subsequent search query object is in the first format that is incompatible with the relational database being searched; map the subsequent search query object to the second format that is compatible with the relational database; invoke the full-text search engine to perform the subsequent full-text search in view of the mapped subsequent search query object; in response to a determination that the filter object has been cached within the cache memory of the ORM system, retrieve the cached filter object from the cache memory of the ORM system; and filter the subsequent search result generated from the full-text search engine using the retrieved filter object and return the filtered subsequent search result to the application client. 14. The system of claim 13 , wherein the processing system is further to define a filter represented by the filter object, wherein the filter comprises an indication that caching is enabled for the filter object, and wherein caching the filter object is in response to a determination that caching is enabled for the filter object. | 0.5 |
9,053,420 | 9 | 12 | 9. A computer program product for a computer implemented system for identifying strong links and discovering hidden relationships among entities, and including one or more computer readable instructions embedded on a non-transitory, tangible computer readable medium and configured to cause one or more computer processors to perform the steps of: identifying with the system strong links and discovering hidden relationships among entities, wherein the entities include places, time slots, people, groups, and organizations; and identifying the strong links and discovering the hidden relationships with the system based on low-level data streams, and incomplete and noisy evidence data streams. | 9. A computer program product for a computer implemented system for identifying strong links and discovering hidden relationships among entities, and including one or more computer readable instructions embedded on a non-transitory, tangible computer readable medium and configured to cause one or more computer processors to perform the steps of: identifying with the system strong links and discovering hidden relationships among entities, wherein the entities include places, time slots, people, groups, and organizations; and identifying the strong links and discovering the hidden relationships with the system based on low-level data streams, and incomplete and noisy evidence data streams. 12. The computer program product of claim 9 , further comprising expanding with the system a hybrid link discovery model from a static database to a multi-stream database. | 0.745536 |
8,862,459 | 8 | 9 | 8. The method of claim 1 , wherein the input couplet comprises first and second scroll sentences. | 8. The method of claim 1 , wherein the input couplet comprises first and second scroll sentences. 9. The method of claim 8 , wherein the first and second sentences have an equal number of words. | 0.5 |
5,457,454 | 1 | 11 | 1. An input device utilizing a virtual keyboard, which enables data to be input by designating at least one input-position corresponding to at least one key indicated in an image of a key arrangement displayed on a display means, by using a designating means, said input device comprising: an input-symbol defining means for defining a form and a meaning of each of input-symbols drawn by said designating means across said image of said key arrangement; and a symbol recognition means for discriminating said input-position and related input-symbol drawn across said image of said key arrangement said input-position on the basis of information defined by said input-symbol defining means and for generating at least one input-code corresponding to at least one input-code in a real keyboard, wherein said input device is operative to generate a specified input-code in accordance with a combination of said input-position and said related input-symbol discriminated by said symbol recognition means, and wherein said input device is operative to display characters or symbols corresponding to said specified input-code on said display means. | 1. An input device utilizing a virtual keyboard, which enables data to be input by designating at least one input-position corresponding to at least one key indicated in an image of a key arrangement displayed on a display means, by using a designating means, said input device comprising: an input-symbol defining means for defining a form and a meaning of each of input-symbols drawn by said designating means across said image of said key arrangement; and a symbol recognition means for discriminating said input-position and related input-symbol drawn across said image of said key arrangement said input-position on the basis of information defined by said input-symbol defining means and for generating at least one input-code corresponding to at least one input-code in a real keyboard, wherein said input device is operative to generate a specified input-code in accordance with a combination of said input-position and said related input-symbol discriminated by said symbol recognition means, and wherein said input device is operative to display characters or symbols corresponding to said specified input-code on said display means. 11. An input device as set forth in claim 1, wherein said specified input-code generated in accordance with a combination of said input-position and said related input-symbol is equivalent to a specified input-code which is different from an input-code indicated simply by said input-position designated by said designating means. | 0.5 |
9,377,948 | 12 | 15 | 12. The information handling device of claim 11 , wherein the instructions are further executable by the one or more processors to determine, using the one or more processors, a position of the special input with respect to one or more other inputs in the handwriting inputs. | 12. The information handling device of claim 11 , wherein the instructions are further executable by the one or more processors to determine, using the one or more processors, a position of the special input with respect to one or more other inputs in the handwriting inputs. 15. The information handling device of claim 12 , wherein the special character is formed in place of one or more strokes in a character of a character-based language. | 0.733227 |
6,104,989 | 17 | 20 | 17. The apparatus of claim 13, wherein said detecting means further comprises: means for successively looking backward from a current word to a prior word, beginning where said prior word is said current word, wherein for each step in said succession a determination is made whether a comparative topic metric is greater than said first threshold ratio, said metric including some likelihood measure that a word string from said current word to said prior word will be found in a context of a topic in said battery, not including a neutral topic; wherein if said determination is YES, said prior word is declared an onset point of a new topic different from a current topic; wherein if said determination is NO, said prior word is moved back one word and said succession is repeated until said prior word is a regeneration point; wherein if all said successive determinations are less than one, said current word is declared a new regeneration point, and otherwise said current word is advanced by one word and said successive determinations are repeated. | 17. The apparatus of claim 13, wherein said detecting means further comprises: means for successively looking backward from a current word to a prior word, beginning where said prior word is said current word, wherein for each step in said succession a determination is made whether a comparative topic metric is greater than said first threshold ratio, said metric including some likelihood measure that a word string from said current word to said prior word will be found in a context of a topic in said battery, not including a neutral topic; wherein if said determination is YES, said prior word is declared an onset point of a new topic different from a current topic; wherein if said determination is NO, said prior word is moved back one word and said succession is repeated until said prior word is a regeneration point; wherein if all said successive determinations are less than one, said current word is declared a new regeneration point, and otherwise said current word is advanced by one word and said successive determinations are repeated. 20. The apparatus of claim 17, wherein said identifying means further comprises: means for verifying whether said new topic associated with said word string beginning with said onset point is in said battery; means for either switching to said neutral topic if said new topic is not in said battery, or determining whether a second comparative topic metric is greater than said second threshold ratio for a topic in said battery other than said current topic; wherein if said determination is YES, said topic is declared to be the new topic, and wherein if said determination is NO, a word is added to said word string and said identification step is repeated. | 0.5 |
8,156,129 | 13 | 16 | 13. A system, comprising: a processor; a data repository that includes a computer-implemented bipartite graph, wherein the bipartite graph includes a first set of nodes that represent queries, a second set of nodes that represent URLs, and weighted edges that represent relationships between queries and URLs, wherein the edges are weighted based at least in part upon a number of user selections of URLs given particular queries, wherein the first set of nodes includes a first node that represents a first query and a second node that represents a second query; a memory that comprises a plurality of components that are executed by the processor, the plurality of components comprising: an analyzer component that analyzes queries submitted by users and corresponding URLs selected by the users, wherein the queries include the first query and the second query, and wherein the analyzer component initiates a random walk at the first node in the bi-partite graph and counts a number of steps taken during the random walk until the random walk reaches the second node in the bipartite graph, the analyzer component determining that the first query and the second query are substantially similar based at least in part upon the number of steps taken during the random walk; and a correlator component that, responsive to the analyzer component determining that the first query and the second query are substantially similar, generates correlation data that indicates that the first and second queries are substantially similar. | 13. A system, comprising: a processor; a data repository that includes a computer-implemented bipartite graph, wherein the bipartite graph includes a first set of nodes that represent queries, a second set of nodes that represent URLs, and weighted edges that represent relationships between queries and URLs, wherein the edges are weighted based at least in part upon a number of user selections of URLs given particular queries, wherein the first set of nodes includes a first node that represents a first query and a second node that represents a second query; a memory that comprises a plurality of components that are executed by the processor, the plurality of components comprising: an analyzer component that analyzes queries submitted by users and corresponding URLs selected by the users, wherein the queries include the first query and the second query, and wherein the analyzer component initiates a random walk at the first node in the bi-partite graph and counts a number of steps taken during the random walk until the random walk reaches the second node in the bipartite graph, the analyzer component determining that the first query and the second query are substantially similar based at least in part upon the number of steps taken during the random walk; and a correlator component that, responsive to the analyzer component determining that the first query and the second query are substantially similar, generates correlation data that indicates that the first and second queries are substantially similar. 16. The system of claim 13 , wherein the correlator component causes the first query and the second query to be correlated in a database of substantially similar queries. | 0.669261 |
9,507,824 | 1 | 9 | 1. A method implemented on a computer system, the method comprising, the computer system: for each table of a plurality of database tables and for each column of a plurality of columns within the each table, creating a profile for the each column by accessing and analyzing a subset of values stored in the column; establishing a join graph of nodes, wherein each node represents one of the plurality of database tables; for each pair of a plurality of pairs of a first table and a second table from the plurality of database tables, wherein the first table is different than the second table and wherein no defined relationship exists between the first table and the second table: for each pair of a plurality of pairs of a first column from the first table and a second column from the second table, calculating a joinability score representative of a predicted level of success in performing a join from the first table on the first column to the second table on the second column, wherein the score is determined based upon the profile for the first column and the profile for the second column, and for one pair of the plurality of pairs of the first column from the first table and the second column from the second table, adding, based on the joinability score, a directed edge to the join graph from a node representing the first table to a node representing the second table; receiving a selection of a subset of the plurality of database tables; creating a join tree comprising a subset of edges in the join graph that spans a subset of nodes in the join graph corresponding to the selected subset of the plurality of database tables; extracting a set of joins represented by the subset of edges; and providing the extracted set of joins as a result, wherein creating a profile for the each column comprises: processing the each column to create a set of m observables, with m being a positive integer constant greater than one, wherein each observable is a function of a set of elements in the each column, independent of replications, and including the set of m observables in the profile for the each column, and wherein calculating the joinability score comprises: combining the set of m observables included in the profile for the first column and the set of m observables included in the profile for the second column to create a combined set of m observables, wherein each observable in the combined set of m observables is a function of a set of elements in a union between the first column and the second column, independent of replications, computing an estimated cardinality of a union between the first column and the second column based on the combined set of m observables without creating a union between the first column and the second column, computing an estimated cardinality of an intersection between the first column and the second column by subtracting the estimated cardinality of the union from the sum of an estimated cardinality of the first column and an estimated cardinality of the second column, and dividing the estimated cardinality of the intersection by the estimated cardinality of the first column. | 1. A method implemented on a computer system, the method comprising, the computer system: for each table of a plurality of database tables and for each column of a plurality of columns within the each table, creating a profile for the each column by accessing and analyzing a subset of values stored in the column; establishing a join graph of nodes, wherein each node represents one of the plurality of database tables; for each pair of a plurality of pairs of a first table and a second table from the plurality of database tables, wherein the first table is different than the second table and wherein no defined relationship exists between the first table and the second table: for each pair of a plurality of pairs of a first column from the first table and a second column from the second table, calculating a joinability score representative of a predicted level of success in performing a join from the first table on the first column to the second table on the second column, wherein the score is determined based upon the profile for the first column and the profile for the second column, and for one pair of the plurality of pairs of the first column from the first table and the second column from the second table, adding, based on the joinability score, a directed edge to the join graph from a node representing the first table to a node representing the second table; receiving a selection of a subset of the plurality of database tables; creating a join tree comprising a subset of edges in the join graph that spans a subset of nodes in the join graph corresponding to the selected subset of the plurality of database tables; extracting a set of joins represented by the subset of edges; and providing the extracted set of joins as a result, wherein creating a profile for the each column comprises: processing the each column to create a set of m observables, with m being a positive integer constant greater than one, wherein each observable is a function of a set of elements in the each column, independent of replications, and including the set of m observables in the profile for the each column, and wherein calculating the joinability score comprises: combining the set of m observables included in the profile for the first column and the set of m observables included in the profile for the second column to create a combined set of m observables, wherein each observable in the combined set of m observables is a function of a set of elements in a union between the first column and the second column, independent of replications, computing an estimated cardinality of a union between the first column and the second column based on the combined set of m observables without creating a union between the first column and the second column, computing an estimated cardinality of an intersection between the first column and the second column by subtracting the estimated cardinality of the union from the sum of an estimated cardinality of the first column and an estimated cardinality of the second column, and dividing the estimated cardinality of the intersection by the estimated cardinality of the first column. 9. The method of claim 1 , wherein the profile for the each column further comprises a density. | 0.910714 |
8,131,540 | 1 | 10 | 1. A method in a computer system for performing a relationship search of a corpus of documents, each document having at least one sentence, comprising: receiving a relationship search query that designates a desired grammatical relationship between a first entity and at least one of a second entity or an action; transforming the search query into a Boolean expression; under control of the computer system, automatically determining a set of data objects that match the Boolean expression using a keyword-style search of a data structure that indexes terms of the documents in a memory of the computer system by including, for at least some of a plurality of terms, grammatical relationship information that specifies that the corresponding term is a subject, object, or modifier of another term, and including for at least one of the plurality of terms having the included grammatical relationship information, semantic information that specifies an entity type that identifies the term as a type of person, location, or thing; when the received relationship search query designates a desired grammatical relationship between the first entity and any action, returning an indication of a plurality of matching objects in the corpus that encompass the first entity along with an indication of the corresponding action encompassed by the matching objects; and otherwise, returning an indication of a plurality of matching objects in the corpus that encompass the desired grammatical relationship. | 1. A method in a computer system for performing a relationship search of a corpus of documents, each document having at least one sentence, comprising: receiving a relationship search query that designates a desired grammatical relationship between a first entity and at least one of a second entity or an action; transforming the search query into a Boolean expression; under control of the computer system, automatically determining a set of data objects that match the Boolean expression using a keyword-style search of a data structure that indexes terms of the documents in a memory of the computer system by including, for at least some of a plurality of terms, grammatical relationship information that specifies that the corresponding term is a subject, object, or modifier of another term, and including for at least one of the plurality of terms having the included grammatical relationship information, semantic information that specifies an entity type that identifies the term as a type of person, location, or thing; when the received relationship search query designates a desired grammatical relationship between the first entity and any action, returning an indication of a plurality of matching objects in the corpus that encompass the first entity along with an indication of the corresponding action encompassed by the matching objects; and otherwise, returning an indication of a plurality of matching objects in the corpus that encompass the desired grammatical relationship. 10. The method of claim 1 wherein the receiving the relationship search query that designates the desired grammatical relationship between the first entity and at least one of the second entity or the action specifies at least one of a prepositional constraint, a document keyword constraint, or a document metadata constraint. | 0.5 |
7,831,596 | 18 | 19 | 18. The system of claim 17 wherein the rating tool is further operable to analyze webpages in the set of webpages by determining a metric of change of the webpages in the set of webpages; and determining a webpage score based at least in part on the determined metric of change. | 18. The system of claim 17 wherein the rating tool is further operable to analyze webpages in the set of webpages by determining a metric of change of the webpages in the set of webpages; and determining a webpage score based at least in part on the determined metric of change. 19. The system of claim 18 wherein a metric of change is based at least in part on change in the at least one webpage relative to a prior version of the at least one webpage and the change comprises a change in at least one of text, images, or ratings. | 0.5 |
9,866,506 | 1 | 7 | 1. A method of controlling a group chat, the method comprising: controlling, by a controller, a display unit to display a group chatting window for the group chat, if a request of a user of a portable device for the group chat is detected through an input unit; detecting, by the controller, a request for an extraction of a dialog for at least one certain conversation partner of conversation partners in the group chat; if the request for the extraction of the dialog is detected, extracting, by the controller, the dialog of the at least one certain conversation partner from one or more dialogs in the group chat; and controlling, by the controller, the display unit to display the extracted dialog on a sub-chatting window, wherein the controller extracts automatically the dialog of the at least one certain conversation partner during the group chatting, and controls the display unit to display the dialog on the sub-chatting window. | 1. A method of controlling a group chat, the method comprising: controlling, by a controller, a display unit to display a group chatting window for the group chat, if a request of a user of a portable device for the group chat is detected through an input unit; detecting, by the controller, a request for an extraction of a dialog for at least one certain conversation partner of conversation partners in the group chat; if the request for the extraction of the dialog is detected, extracting, by the controller, the dialog of the at least one certain conversation partner from one or more dialogs in the group chat; and controlling, by the controller, the display unit to display the extracted dialog on a sub-chatting window, wherein the controller extracts automatically the dialog of the at least one certain conversation partner during the group chatting, and controls the display unit to display the dialog on the sub-chatting window. 7. The method of claim 1 , further comprising: detecting a dialog transmission or reception event for the group chat; determining whether the event is generated by the certain conversation partner; and in response to the event being generated by the certain conversation partner, displaying a dialog which is transmitted or received by the event on the sub-chatting window. | 0.616255 |
7,801,887 | 16 | 24 | 16. A computer-implemented method for processing documents in a document database, the documents having an initial ranking based upon a user search query provided by a user using a computer-implemented system comprising a processor and a display operatively coupled to the processor, the method comprising: operating the processor to perform the following selecting N top ranked documents from the retrieved documents, with N being an integer greater than 1; displaying for the user the initial ranking of the N top ranked retrieved documents; permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents, with at least one of the vocabulary words not being in the user search query; generating respective relevancies of the user-selected vocabulary words in the N top ranked retrieved documents based on counting how many times a respective vocabulary word is used in the N top ranked documents; and counting how many of the N top ranked documents uses the respective vocabulary word; generating a re-ranking of the N top ranked documents based on the relevancies of the vocabulary words; and operating the display to display for the user the re-ranking of the documents, and for each document being displayed, also to display its initial ranking. | 16. A computer-implemented method for processing documents in a document database, the documents having an initial ranking based upon a user search query provided by a user using a computer-implemented system comprising a processor and a display operatively coupled to the processor, the method comprising: operating the processor to perform the following selecting N top ranked documents from the retrieved documents, with N being an integer greater than 1; displaying for the user the initial ranking of the N top ranked retrieved documents; permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved documents, with at least one of the vocabulary words not being in the user search query; generating respective relevancies of the user-selected vocabulary words in the N top ranked retrieved documents based on counting how many times a respective vocabulary word is used in the N top ranked documents; and counting how many of the N top ranked documents uses the respective vocabulary word; generating a re-ranking of the N top ranked documents based on the relevancies of the vocabulary words; and operating the display to display for the user the re-ranking of the documents, and for each document being displayed, also to display its initial ranking. 24. A computer-implemented method according to claim 16 further comprising determining which documents from at least some of the retrieved documents are irrelevant to the user search query; and wherein generating the re-ranking of the retrieved documents is also based on the irrelevant documents. | 0.55 |
8,797,605 | 1 | 5 | 1. A method of creating a structural document, the method comprising: receiving, by a host computing device in a cloud system, content information pertaining to one or more contents that are to be encased by a structural document; determining, by the host computing device, a shape of a structural document based at least in part on the received content information; determining, by the host computing device, a plurality of dimensions of the structural document based at least in part on the received content information; receiving, via a communications network by the host computing device from a user computing device that is remote from the host computing device, content item information associated with one or more content items, wherein the content item information comprises at least one brand identifier associated with a provider of the one or more contents; causing a graphical representation of the structural document to be displayed at the user computing device, wherein a shape of the graphical representation corresponds to the determined shape, wherein a plurality of dimensions of the graphical representation correspond to the determined plurality of dimensions, wherein the graphical representation comprises at least a portion of the received content items; receiving, from the user computing device by the host computing device, an indication that a user is finished creating the structural document; generating a print document comprising an encoded data mark; and providing the print document to one or more print-related devices. | 1. A method of creating a structural document, the method comprising: receiving, by a host computing device in a cloud system, content information pertaining to one or more contents that are to be encased by a structural document; determining, by the host computing device, a shape of a structural document based at least in part on the received content information; determining, by the host computing device, a plurality of dimensions of the structural document based at least in part on the received content information; receiving, via a communications network by the host computing device from a user computing device that is remote from the host computing device, content item information associated with one or more content items, wherein the content item information comprises at least one brand identifier associated with a provider of the one or more contents; causing a graphical representation of the structural document to be displayed at the user computing device, wherein a shape of the graphical representation corresponds to the determined shape, wherein a plurality of dimensions of the graphical representation correspond to the determined plurality of dimensions, wherein the graphical representation comprises at least a portion of the received content items; receiving, from the user computing device by the host computing device, an indication that a user is finished creating the structural document; generating a print document comprising an encoded data mark; and providing the print document to one or more print-related devices. 5. The method of claim 1 , wherein receiving, from a user computing device, the one or more content items comprises: causing a set of candidate content items to be displayed at the user computing device; and receiving a selection of one or more of the candidate content items. | 0.77 |
8,296,151 | 12 | 13 | 12. A system as in claim 11 , wherein: the subset of sound commands is organized in one or more hierarchical levels, wherein each hierarchical level is only loaded into the computer as necessary to process a gesture. | 12. A system as in claim 11 , wherein: the subset of sound commands is organized in one or more hierarchical levels, wherein each hierarchical level is only loaded into the computer as necessary to process a gesture. 13. A system as in claim 12 , wherein: a subsequent hierarchical level of sound commands is loaded and displayed only after a sound command from a previous hierarchical level has been recognized and the desired action associated with the sound command taken. | 0.5 |
9,594,831 | 1 | 3 | 1. A method implemented by one or more computer processing devices, the method comprising: receiving and storing a list of multiple different named entities, the multiple different named entities homogenously pertaining to a particular subject matter domain; determining and storing a set of candidate mentions of the multiple different named entities, each candidate mention being an occurrence of a corresponding named entity in the list of multiple different named entities, the set of candidate mentions including true mentions and false mentions occurring in a collection of documents; identifying particular candidate mentions as the true mentions within the set of candidate mentions by leveraging homogeneity in the list of multiple different named entities, each true mention corresponding to a valid occurrence of an individual named entity in the collection of documents, the identifying including assigning scores to individual candidate mentions of the set of candidate mentions and identifying the particular candidate mentions as the true mentions using the scores; and outputting the true mentions. | 1. A method implemented by one or more computer processing devices, the method comprising: receiving and storing a list of multiple different named entities, the multiple different named entities homogenously pertaining to a particular subject matter domain; determining and storing a set of candidate mentions of the multiple different named entities, each candidate mention being an occurrence of a corresponding named entity in the list of multiple different named entities, the set of candidate mentions including true mentions and false mentions occurring in a collection of documents; identifying particular candidate mentions as the true mentions within the set of candidate mentions by leveraging homogeneity in the list of multiple different named entities, each true mention corresponding to a valid occurrence of an individual named entity in the collection of documents, the identifying including assigning scores to individual candidate mentions of the set of candidate mentions and identifying the particular candidate mentions as the true mentions using the scores; and outputting the true mentions. 3. The method of claim 1 , wherein the set of candidate mentions contains: at least one occurrence of an individual named entity from the list that is an individual true mention; and at least one false mention that is a homograph of the individual named entity. | 0.868976 |
9,791,999 | 1 | 12 | 1. A method comprising: displaying, by a processor, a touch phrase button in a first state; receiving, by the processor, a first input associated with the touch phrase button in the first state; in response to the first input associated with the touch phrase button, displaying, by the processor, a plurality of option buttons associated with the touch phrase button, wherein a first text is displayed within each of the option buttons; receiving, by the processor, a second input associated with at least one of the plurality of option buttons; and in response to the second input associated with at least one of the plurality of option buttons, displaying, by the processor, the touch phrase button in a second state, wherein displaying the touch phrase button in the second state comprises automatically associating a second text with the touch phrase button without user input of the second text, wherein the second text is displayed within the touch phrase button, and wherein the second text is related to the second input, and wherein the first text is different than the second text. | 1. A method comprising: displaying, by a processor, a touch phrase button in a first state; receiving, by the processor, a first input associated with the touch phrase button in the first state; in response to the first input associated with the touch phrase button, displaying, by the processor, a plurality of option buttons associated with the touch phrase button, wherein a first text is displayed within each of the option buttons; receiving, by the processor, a second input associated with at least one of the plurality of option buttons; and in response to the second input associated with at least one of the plurality of option buttons, displaying, by the processor, the touch phrase button in a second state, wherein displaying the touch phrase button in the second state comprises automatically associating a second text with the touch phrase button without user input of the second text, wherein the second text is displayed within the touch phrase button, and wherein the second text is related to the second input, and wherein the first text is different than the second text. 12. The method of claim 1 , wherein the first text displayed within each of the option buttons is unique to the respective option buttons. | 0.875451 |
6,108,632 | 9 | 11 | 9. A method of operating a transaction support apparatus for use by one or more transaction operators, the support apparatus comprising an electronic speech recognition device, said method comprising: coupling the electronic speech recognition device to receive a speech signal including a confirmatory dialogue from a transaction operator to another party; recognizing values of parameters of the transaction within the speech of the transaction operator utilizing said electronic speech recognizer; and supplying data recording the results of said recognition in electronic form from said electronic speech recognizing unit to an electronic transaction recording computer. | 9. A method of operating a transaction support apparatus for use by one or more transaction operators, the support apparatus comprising an electronic speech recognition device, said method comprising: coupling the electronic speech recognition device to receive a speech signal including a confirmatory dialogue from a transaction operator to another party; recognizing values of parameters of the transaction within the speech of the transaction operator utilizing said electronic speech recognizer; and supplying data recording the results of said recognition in electronic form from said electronic speech recognizing unit to an electronic transaction recording computer. 11. The method of claim 9 further comprising the step of: outputting a confirmatory output indication, recognizable by a said human transaction operator, of values of said parameters thus recognized. | 0.5 |
10,032,072 | 10 | 11 | 10. The computer-implemented method of claim 1 , wherein the second trained neural network is operable to iteratively adjust a size of each region of the first set of the plurality of regions of interest to accommodate one or more words in their entirety, iteratively adjust a size of a region of the first set of the plurality of regions of interest to accommodate one or more word in their entirety, iteratively reposition a region of the first set of the plurality of regions of interest to accommodate one or more words in their entirety, or iteratively change a shape of a region of the first set of the plurality of regions of interest to accommodate one or more words in their entirety. | 10. The computer-implemented method of claim 1 , wherein the second trained neural network is operable to iteratively adjust a size of each region of the first set of the plurality of regions of interest to accommodate one or more words in their entirety, iteratively adjust a size of a region of the first set of the plurality of regions of interest to accommodate one or more word in their entirety, iteratively reposition a region of the first set of the plurality of regions of interest to accommodate one or more words in their entirety, or iteratively change a shape of a region of the first set of the plurality of regions of interest to accommodate one or more words in their entirety. 11. The computer-implemented method of claim 10 , further comprising: generating a background layer using portions of images from a database of images; generating foreground text; merging the background layer and the foreground text to generate a blended image; and adding one or random noise or artifacts to the blended image to generate synthetic text data. | 0.5 |
8,098,177 | 1 | 6 | 1. A method of mapping a keypad, the method comprising: mapping at least one key on a numeric keypad to alphabetic letters of a language, wherein a plurality of the alphabetic letters are assigned to each of the at least one key on the numeric keypad; receiving a first interaction with one key of the at least one key; selecting a first alphabetic letter from among the plurality of alphabetic letters assigned to the one key of the at least one key, in response to the first interaction with the one key, such that the first alphabetic letter is a first most frequently used letter from among said plurality of alphabetic letters assigned to the one key; receiving a second interaction with the one key of the at least one key; and selecting a second alphabetic letter from among the plurality of alphabetic letters assigned to the one key of the at least one key, in response to the second interaction with the one key, such that the second alphabetic letter is a second most frequently used letter from among said plurality of letters assigned to the one key, wherein the plurality of alphabetic letters assigned to the one key of the at least one key are displayed on a surface of the one key in a stylized manner reflecting frequency of use of each of said plurality of alphabetic letters such that more frequently used letters are styled in a more ubiquitous manner in comparison to less frequently used letters, and wherein a color coding scheme or a font visualization scheme is used to distinguish the more frequently used letters from the less frequently used letters. | 1. A method of mapping a keypad, the method comprising: mapping at least one key on a numeric keypad to alphabetic letters of a language, wherein a plurality of the alphabetic letters are assigned to each of the at least one key on the numeric keypad; receiving a first interaction with one key of the at least one key; selecting a first alphabetic letter from among the plurality of alphabetic letters assigned to the one key of the at least one key, in response to the first interaction with the one key, such that the first alphabetic letter is a first most frequently used letter from among said plurality of alphabetic letters assigned to the one key; receiving a second interaction with the one key of the at least one key; and selecting a second alphabetic letter from among the plurality of alphabetic letters assigned to the one key of the at least one key, in response to the second interaction with the one key, such that the second alphabetic letter is a second most frequently used letter from among said plurality of letters assigned to the one key, wherein the plurality of alphabetic letters assigned to the one key of the at least one key are displayed on a surface of the one key in a stylized manner reflecting frequency of use of each of said plurality of alphabetic letters such that more frequently used letters are styled in a more ubiquitous manner in comparison to less frequently used letters, and wherein a color coding scheme or a font visualization scheme is used to distinguish the more frequently used letters from the less frequently used letters. 6. The method of claim 1 , wherein a most frequently used letter assigned to the one key of the at least one key is displayed in a first size, and a less frequently used letter assigned to the one key of the at least one key is displayed in a second size different from the first size. | 0.505208 |
7,823,139 | 1 | 4 | 1. A system that includes a processor that executes instructions that provides programming language translation, comprising: a first compiler comprises a first lexical analysis, a first syntactic analysis, a first semantic analysis, a first optimization, and a first code generation; a second compiler comprises a second lexical analysis, a second syntactic analysis, a second semantic analysis, a second optimization, and a second code generation; and a transformation component; where the first compiler compiles a source file in a first programming language into a parsed representation of the first programming language, the first compiler transforming the source file into first language tokens, and parsing the first language tokens into the parsed representation; where the transformation component receives the parsed representation from the first semantic analysis and generates a token stream from the parsed representation wherein the token stream comprises second language tokens of a second programming language and wherein a plurality of compilation phases of the first compiler are skipped; where the second syntactic analysis phase of the second compiler receives the token stream from the transformation component and compiles the token stream into an object code, wherein a plurality of compilation phase of the second compiler are skipped; wherein the transformation component provides the token stream to the second compiler in memory; wherein the plurality of compilation phases of the first compiler that are skipped comprise the first optimization, the first code generation, and writing the object code as an output file; and wherein the plurality of compilation phases of the second compiler that are skipped comprise the second lexical analysis and accepting the object code as an input file. | 1. A system that includes a processor that executes instructions that provides programming language translation, comprising: a first compiler comprises a first lexical analysis, a first syntactic analysis, a first semantic analysis, a first optimization, and a first code generation; a second compiler comprises a second lexical analysis, a second syntactic analysis, a second semantic analysis, a second optimization, and a second code generation; and a transformation component; where the first compiler compiles a source file in a first programming language into a parsed representation of the first programming language, the first compiler transforming the source file into first language tokens, and parsing the first language tokens into the parsed representation; where the transformation component receives the parsed representation from the first semantic analysis and generates a token stream from the parsed representation wherein the token stream comprises second language tokens of a second programming language and wherein a plurality of compilation phases of the first compiler are skipped; where the second syntactic analysis phase of the second compiler receives the token stream from the transformation component and compiles the token stream into an object code, wherein a plurality of compilation phase of the second compiler are skipped; wherein the transformation component provides the token stream to the second compiler in memory; wherein the plurality of compilation phases of the first compiler that are skipped comprise the first optimization, the first code generation, and writing the object code as an output file; and wherein the plurality of compilation phases of the second compiler that are skipped comprise the second lexical analysis and accepting the object code as an input file. 4. The system according to claim 1 , wherein: the second compiler performs at least one of the following compilation phases: optimization; generating an object code in the second programming language; and writing the object code in the second programming language to the disk as an output file. | 0.5 |
8,695,018 | 17 | 23 | 17. A method comprising: accessing, via a computing device, an extensible framework that accepts one or more mark-up language parsers or generators implemented as plug-ins, with different plug-ins enabling different kinds of markup languages to be handled; enabling, via the extensible framework, the one or more mark-up language parsers or generators to access components to validate, pre-filter or alter data, in which the components are plug-in components to the extensible framework and operate using a chain of responsibility design pattern; wherein the one or more mark-up language parsers or generators uses a namespace collection to retrieve information about a specific namespace during the parsing or generating phrase; enabling said one or more mark-up language parsers plug-ins or generators plug-ins to access data from a generic data supplier application programming interface (API); enabling said generic data supplier API to access data from at least one data source; wherein the extensible framework and the generic data supplier API are loaded on a computing device, and, via said generic data supplier API, the extensible framework insulates said one or more mark-up language parsers or generators from direct communication with said at least one data source; and causing, via the one or more mark-up language parser, a validator plug-in to be notified of elements the parser is parsing, the elements in turn going to an auto correction plug-in to be fixed if required and finally to a client that receives these elements. | 17. A method comprising: accessing, via a computing device, an extensible framework that accepts one or more mark-up language parsers or generators implemented as plug-ins, with different plug-ins enabling different kinds of markup languages to be handled; enabling, via the extensible framework, the one or more mark-up language parsers or generators to access components to validate, pre-filter or alter data, in which the components are plug-in components to the extensible framework and operate using a chain of responsibility design pattern; wherein the one or more mark-up language parsers or generators uses a namespace collection to retrieve information about a specific namespace during the parsing or generating phrase; enabling said one or more mark-up language parsers plug-ins or generators plug-ins to access data from a generic data supplier application programming interface (API); enabling said generic data supplier API to access data from at least one data source; wherein the extensible framework and the generic data supplier API are loaded on a computing device, and, via said generic data supplier API, the extensible framework insulates said one or more mark-up language parsers or generators from direct communication with said at least one data source; and causing, via the one or more mark-up language parser, a validator plug-in to be notified of elements the parser is parsing, the elements in turn going to an auto correction plug-in to be fixed if required and finally to a client that receives these elements. 23. The method of claim 17 , further comprising enabling, via the extensible framework, a parser or generator to access data from any source that conforms to the generic data supplier API. | 0.745946 |
9,684,448 | 12 | 16 | 12. The method of claim 9 , further comprising: determining that the received user touch-input calls a Braille keyboard; and presenting the plurality of input regions being defined by and separated by input region boundaries. | 12. The method of claim 9 , further comprising: determining that the received user touch-input calls a Braille keyboard; and presenting the plurality of input regions being defined by and separated by input region boundaries. 16. The method of claim 12 , further comprising: receiving touch input selecting one or more of the input regions; determining that the touch input selecting one or more of the input regions corresponds to a six-dot Braille character; and presenting via the speaker an audio message indicating the six-dot Braille character. | 0.5 |
7,685,252 | 56 | 65 | 56. The apparatus of claim 43 , wherein one of the interaction-based programming components represent conversational gestures. | 56. The apparatus of claim 43 , wherein one of the interaction-based programming components represent conversational gestures. 65. The apparatus of claim 56 , wherein the conversational gestures comprise a gesture for encapsulating rules for validating results of a given conversational gesture. | 0.530726 |
7,761,301 | 5 | 7 | 5. A computer implemented prosodic control rule generation method executed on a suitably programmed computer, the method including: dividing an input text into language units; estimating a punctuation mark incidence at a boundary between language units in the input text, the punctuation mark incidence indicating a degree that a punctuation mark occurs at the boundary, based on attribute information items of a plurality of language units adjacent to the boundary; generating a plurality of learning data items each concerning prosodic boundary between the language units and including the punctuation mark incidence between the language units; and generating, by the computer, a prosodic boundary estimation rule for determining a type of a prosodic boundary and including a condition for the punctuation mark incidence between the language units based on the learning data items concerning prosodic boundary. | 5. A computer implemented prosodic control rule generation method executed on a suitably programmed computer, the method including: dividing an input text into language units; estimating a punctuation mark incidence at a boundary between language units in the input text, the punctuation mark incidence indicating a degree that a punctuation mark occurs at the boundary, based on attribute information items of a plurality of language units adjacent to the boundary; generating a plurality of learning data items each concerning prosodic boundary between the language units and including the punctuation mark incidence between the language units; and generating, by the computer, a prosodic boundary estimation rule for determining a type of a prosodic boundary and including a condition for the punctuation mark incidence between the language units based on the learning data items concerning prosodic boundary. 7. The computer implemented prosodic control rule generation method according to claim 5 , further including: generating a plurality of learning data items each concerning prosody and including the type of the prosodic boundary between language units; and generating a prosodic control rule for speech synthesis including a condition for the type of the prosodic boundary based on the learning data items concerning prosody. | 0.546039 |
10,078,688 | 14 | 15 | 14. A computer-readable non-transitory storage medium comprising executable instructions that, when executed by a computer system, cause the computer system to: identify a plurality of hyper-parameters of a text classifier model, wherein the plurality of hyper-parameters include a number of nearest neighbors to be analyzed by the text classifier model; partition a corpus of natural language texts into a training data set comprising a first plurality of natural language texts and a validation data set comprising a second plurality of natural language texts; determine, in view of the training data set, a set of values of the hyper-parameters of the text classifier model, which maximizes a number of natural language texts of the validation data set that are classified correctly by the text classifier model using the set of values of the hyper-parameters; perform a semantico-syntactic analysis of an input natural language text to produce a semantic structure representing a set of semantic classes; and produce a plurality of values by applying, to the semantic structure representing the input natural language text, the text classifier model using the set of values of the hyper-parameters, wherein each value of the plurality of values reflects a degree of association of the input natural language text with a particular category of natural language texts; associate the input natural language text with a category corresponding to an optimal value among the plurality of values; and utilize the category to perform a natural language processing task. | 14. A computer-readable non-transitory storage medium comprising executable instructions that, when executed by a computer system, cause the computer system to: identify a plurality of hyper-parameters of a text classifier model, wherein the plurality of hyper-parameters include a number of nearest neighbors to be analyzed by the text classifier model; partition a corpus of natural language texts into a training data set comprising a first plurality of natural language texts and a validation data set comprising a second plurality of natural language texts; determine, in view of the training data set, a set of values of the hyper-parameters of the text classifier model, which maximizes a number of natural language texts of the validation data set that are classified correctly by the text classifier model using the set of values of the hyper-parameters; perform a semantico-syntactic analysis of an input natural language text to produce a semantic structure representing a set of semantic classes; and produce a plurality of values by applying, to the semantic structure representing the input natural language text, the text classifier model using the set of values of the hyper-parameters, wherein each value of the plurality of values reflects a degree of association of the input natural language text with a particular category of natural language texts; associate the input natural language text with a category corresponding to an optimal value among the plurality of values; and utilize the category to perform a natural language processing task. 15. The computer-readable non-transitory storage medium of claim 14 , wherein partitioning the corpus of natural language texts comprises cross-validating the first plurality of natural language texts and the second plurality of natural language texts. | 0.5 |
8,290,946 | 12 | 13 | 12. A method according to claim 11 , further comprising determining the probability of the out-of-document phrase in a way that is consistent with the probabilities of the in-document phrases. | 12. A method according to claim 11 , further comprising determining the probability of the out-of-document phrase in a way that is consistent with the probabilities of the in-document phrases. 13. A method according to claim 12 , wherein weights of kernel functions for linearly combining the functions are trained using a dataset. | 0.5 |
9,086,736 | 1 | 4 | 1. A computer-implemented method for text-entry interpretation, comprising: receiving, via a keypad associated with a digital device, user entry of a sequence of keypresses representing a series of symbols indicative of a textual object intended by a user; for each keypress received, generating an interpretation of the sequence of keypresses by using multiple keypress interpretation strategies, the interpretation including at least one vocabulary entry predictive of a potential textual object intended by the user; providing, via a display associated with the digital device, a human-readable presentation of the interpretation, the providing including changing a symbol associated with the at least one vocabulary entry based on a subsequent keypress received from the user subsequent to an initial presentation, wherein changing the symbol results in an updated human-readable presentation of the interpretation provided via the display, wherein providing the human-readable presentation further includes maintaining the human-readable presentation to include a greater number of vocabulary entries arising from a first keypress interpretation strategy than a number of vocabulary entries arising from a second keypress interpretation strategy until vocabulary entries arising from the first keypress interpretation strategy fall below a prescribed quantity. | 1. A computer-implemented method for text-entry interpretation, comprising: receiving, via a keypad associated with a digital device, user entry of a sequence of keypresses representing a series of symbols indicative of a textual object intended by a user; for each keypress received, generating an interpretation of the sequence of keypresses by using multiple keypress interpretation strategies, the interpretation including at least one vocabulary entry predictive of a potential textual object intended by the user; providing, via a display associated with the digital device, a human-readable presentation of the interpretation, the providing including changing a symbol associated with the at least one vocabulary entry based on a subsequent keypress received from the user subsequent to an initial presentation, wherein changing the symbol results in an updated human-readable presentation of the interpretation provided via the display, wherein providing the human-readable presentation further includes maintaining the human-readable presentation to include a greater number of vocabulary entries arising from a first keypress interpretation strategy than a number of vocabulary entries arising from a second keypress interpretation strategy until vocabulary entries arising from the first keypress interpretation strategy fall below a prescribed quantity. 4. The computer-implemented method of claim 1 , wherein the multiple keypress interpretation strategies include a one-keypress-per-letter interpretation strategy and a multi-tap interpretation strategy. | 0.831386 |
8,843,474 | 9 | 12 | 9. A computer accessible memory medium storing program instructions for executing a extended markup language (XML) database query, wherein the program instructions are executable by a processor implement: a compiler adapted to generate at least two database query execution plans, wherein upon execution the at least two alternate execution plans provide a same response to the XML database query; and at least one switch adapted to select one of the at least two database query execution plans during runtime; and an execution engine adapted to execute the selected execution plan; wherein said selecting comprises the at least one switch dynamically selecting one of the at least two alternative database query execution plans, wherein the switch performs the selection based on intermediate results, which are at least partly reused for evaluating the result of the execution of the XML database query according to at least one of the at least two alternative database query execution plans. | 9. A computer accessible memory medium storing program instructions for executing a extended markup language (XML) database query, wherein the program instructions are executable by a processor implement: a compiler adapted to generate at least two database query execution plans, wherein upon execution the at least two alternate execution plans provide a same response to the XML database query; and at least one switch adapted to select one of the at least two database query execution plans during runtime; and an execution engine adapted to execute the selected execution plan; wherein said selecting comprises the at least one switch dynamically selecting one of the at least two alternative database query execution plans, wherein the switch performs the selection based on intermediate results, which are at least partly reused for evaluating the result of the execution of the XML database query according to at least one of the at least two alternative database query execution plans. 12. The computer accessible memory medium of claim 9 , wherein the at least two execution plans differ by the use of at least one database index. | 0.721154 |
9,477,652 | 13 | 16 | 13. A non-transitory computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for creating a dialect-specific training data set, the operations comprising: selecting an initial training data set as a current training data set, wherein the initial training data set is selected by: receiving one or more initial content items; establishing dialect parameters for two or more of the initial content items, wherein the dialect parameters identify a first of the two or more of the initial content items as being composed in a first dialect and identify a second of the two or more of the initial content items as being composed in a second dialect; and sorting each of the initial content items into one or more dialect groups based on the established dialect parameters; generating, based on the initial training data set and corresponding one or more dialect groups, a dialect classifier configured to detect language dialects of content items to be classified as being in one of two or more dialects, the two or more dialects including at least the first dialect and the second dialect; augmenting the current training data set with additional training data by applying the dialect classifier to candidate content items, wherein at least one of the candidate content items that is in the augmented current training data set was not included in the initial training data set; and updating the dialect classifier based on the augmented current training data set; and returning the updated dialect classifier, wherein the updated dialect classifier is configured to identify additional content items that are not in the initial training data and are not in the augmented current training data set as being in one of the two or more dialects. | 13. A non-transitory computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for creating a dialect-specific training data set, the operations comprising: selecting an initial training data set as a current training data set, wherein the initial training data set is selected by: receiving one or more initial content items; establishing dialect parameters for two or more of the initial content items, wherein the dialect parameters identify a first of the two or more of the initial content items as being composed in a first dialect and identify a second of the two or more of the initial content items as being composed in a second dialect; and sorting each of the initial content items into one or more dialect groups based on the established dialect parameters; generating, based on the initial training data set and corresponding one or more dialect groups, a dialect classifier configured to detect language dialects of content items to be classified as being in one of two or more dialects, the two or more dialects including at least the first dialect and the second dialect; augmenting the current training data set with additional training data by applying the dialect classifier to candidate content items, wherein at least one of the candidate content items that is in the augmented current training data set was not included in the initial training data set; and updating the dialect classifier based on the augmented current training data set; and returning the updated dialect classifier, wherein the updated dialect classifier is configured to identify additional content items that are not in the initial training data and are not in the augmented current training data set as being in one of the two or more dialects. 16. The computer-readable storage medium of claim 13 , wherein establishing the dialect parameters comprises: identifying content items that use one or more n-grams, n-gram types, or word endings correlated to the dialect. | 0.5 |
8,694,491 | 17 | 23 | 17. The system of claim 1 , wherein the system is further configured to: evaluate search results from the rerun query and to select search results that meet predefined search result selection criteria; and wherein the search results sent to the computer associated with the particular individual computer user correspond to at least some of the selected search results. | 17. The system of claim 1 , wherein the system is further configured to: evaluate search results from the rerun query and to select search results that meet predefined search result selection criteria; and wherein the search results sent to the computer associated with the particular individual computer user correspond to at least some of the selected search results. 23. The system of claim 17 , wherein at least one of the predefined search result selection criteria used to evaluate a search result from the rerun query is based on the search result being the only new search result in the top N search results returned for the rerun query, where N is an integer. | 0.641827 |
8,682,574 | 1 | 2 | 1. A machine-readable, non-transitory storage medium encoded with instructions that, when executed by one or more processors, cause the one or more processors to carry out a process for generating directions for use in navigation during a current driving session, the process comprising: receiving a target destination; generating at least one candidate route; probabilistically determining that one of a plurality of conditional variant models associated with a target attribute corresponds to a condition of the target attribute, the plurality of conditional variant models learned from previous user driving sessions; scoring the at least one candidate route using the determined conditional variant model; providing a scored route to a user; detecting a change in the condition of the target attribute, wherein the detecting a change in the condition of the target attribute comprises: recomputing probabilities for the conditional variant models associated with the target attribute periodically during the current driving session using subsequently observed data of the current driving session; and probabilistically determining that a second conditional variant model currently corresponds to the condition of the target attribute; and providing an altered route to the user based on the detected change. | 1. A machine-readable, non-transitory storage medium encoded with instructions that, when executed by one or more processors, cause the one or more processors to carry out a process for generating directions for use in navigation during a current driving session, the process comprising: receiving a target destination; generating at least one candidate route; probabilistically determining that one of a plurality of conditional variant models associated with a target attribute corresponds to a condition of the target attribute, the plurality of conditional variant models learned from previous user driving sessions; scoring the at least one candidate route using the determined conditional variant model; providing a scored route to a user; detecting a change in the condition of the target attribute, wherein the detecting a change in the condition of the target attribute comprises: recomputing probabilities for the conditional variant models associated with the target attribute periodically during the current driving session using subsequently observed data of the current driving session; and probabilistically determining that a second conditional variant model currently corresponds to the condition of the target attribute; and providing an altered route to the user based on the detected change. 2. The machine-readable, non-transitory storage medium of claim 1 , the process further comprising: determining a driver ID for the current driving session; and restricting the plurality of conditional variant models associated with the target attribute to include only conditional variant models associated with the driver ID. | 0.5 |
9,348,894 | 2 | 3 | 2. The method of claim 1 , wherein generating the one or more semantic clusters comprises clustering based on words contained in code elements of source code. | 2. The method of claim 1 , wherein generating the one or more semantic clusters comprises clustering based on words contained in code elements of source code. 3. The method of claim 2 , wherein the query is received from a user searching for source code; wherein the source-code query results are sent to the client device for display in the user interface; and wherein the source-code query results correspond to the code elements of the source code. | 0.5 |
8,510,321 | 14 | 28 | 14. A method of accessing and managing a relational database comprising: executing a program of instructions with a machine, the program of instructions being configured to: query a relational database; and access semantically relevant query results from the relational database, wherein to access query results from the relational database further comprises; accessing at least one ontology; extracting domain knowledge from at least one ontology and; employing the domain knowledge in obtaining the semantically relevant query results from the relational database; wherein said semantically relevant query results comprise direct results obtained directly from relational database tables, inferred results inferred utilizing information explicitly listed in the relational database and the at least one ontology, and related results obtained utilizing data in the relational database tables and one or more definitions of similarity of concepts and individuals based on the at least one ontology; and wherein to access semantically relevant query results comprises: applying a query generalization strategy, the query generalization strategy comprising applying strategies to an original query to obtain a generalized level of queries comprising one or more general queries and repeatedly applying the strategies to the generalized level of queries until a prespecified number of results is obtained; and ranking results obtained through the query generalization strategy based on a number generalizations performed. | 14. A method of accessing and managing a relational database comprising: executing a program of instructions with a machine, the program of instructions being configured to: query a relational database; and access semantically relevant query results from the relational database, wherein to access query results from the relational database further comprises; accessing at least one ontology; extracting domain knowledge from at least one ontology and; employing the domain knowledge in obtaining the semantically relevant query results from the relational database; wherein said semantically relevant query results comprise direct results obtained directly from relational database tables, inferred results inferred utilizing information explicitly listed in the relational database and the at least one ontology, and related results obtained utilizing data in the relational database tables and one or more definitions of similarity of concepts and individuals based on the at least one ontology; and wherein to access semantically relevant query results comprises: applying a query generalization strategy, the query generalization strategy comprising applying strategies to an original query to obtain a generalized level of queries comprising one or more general queries and repeatedly applying the strategies to the generalized level of queries until a prespecified number of results is obtained; and ranking results obtained through the query generalization strategy based on a number generalizations performed. 28. The method according to claim 14 , further comprising translating data from the relational database into a predetermined format. | 0.835 |
9,177,104 | 5 | 6 | 5. The non-transitory computer-readable storage medium of claim 4 , where a binomial factor 2 i transforms the LBP to a number, where the bits of the number are measured in Hamming distance, where the LBP is invariant to local gray-scale shift, and where a circular bitwise right shift is performed p times on p bits within the circle, where the minimum resulting number of the circular bitwise right shift is retained as the final LBP. | 5. The non-transitory computer-readable storage medium of claim 4 , where a binomial factor 2 i transforms the LBP to a number, where the bits of the number are measured in Hamming distance, where the LBP is invariant to local gray-scale shift, and where a circular bitwise right shift is performed p times on p bits within the circle, where the minimum resulting number of the circular bitwise right shift is retained as the final LBP. 6. The non-transitory computer-readable storage medium of claim 5 , the method comprising finding a similarity between a pair of LBPs at the plurality of scales, where the similarity is computed as a dissimilarity metric, where the dissimilarity metric is measured by a kernel defined as H(x, x′)=Σ n=1 N d H (x n , x n ′), where N is a number of operations of varying (p, r), where d H (x n , x n ′) is the Hamming distance, where d H =Σ i=0 p n -1 (x i ≠x i ′), where x i is the i-th bit of x, and x i ′ is the i-th bit of x′. | 0.5 |
9,275,036 | 1 | 3 | 1. A method, comprising: tracking frequencies of historical replacement character strings for a specific user and a community of users; and providing a list of “n” number of the historical replacement character strings in response to a character string which was previously changed or is not recognized, wherein the character string is automatically replaced when the character string exceeds a threshold of a sum of all the frequencies of the historical replacement character strings, wherein the list of “n” number of the historical replacement character strings are ranked according to a combined weighted frequency, wherein the combined weighted frequency is a sum of a user weight for the specific user and a community weight for the community of users such that the combined weighted frequency is weighted towards historical replacement character strings of the specific user, wherein the user weight is calculated based on a user frequency of a corresponding character string in comparison to a sum of all user frequencies of the historical replacement character strings, wherein the community weight is calculated based on a community frequency of a corresponding character string in comparison to a sum of all community frequencies of the historical replacement character strings, wherein the community of users comprise the specific user, and wherein the combined weight is different for each user of the community of users. | 1. A method, comprising: tracking frequencies of historical replacement character strings for a specific user and a community of users; and providing a list of “n” number of the historical replacement character strings in response to a character string which was previously changed or is not recognized, wherein the character string is automatically replaced when the character string exceeds a threshold of a sum of all the frequencies of the historical replacement character strings, wherein the list of “n” number of the historical replacement character strings are ranked according to a combined weighted frequency, wherein the combined weighted frequency is a sum of a user weight for the specific user and a community weight for the community of users such that the combined weighted frequency is weighted towards historical replacement character strings of the specific user, wherein the user weight is calculated based on a user frequency of a corresponding character string in comparison to a sum of all user frequencies of the historical replacement character strings, wherein the community weight is calculated based on a community frequency of a corresponding character string in comparison to a sum of all community frequencies of the historical replacement character strings, wherein the community of users comprise the specific user, and wherein the combined weight is different for each user of the community of users. 3. The method of claim 1 , wherein the tracking and providing are performed by a service provider. | 0.937179 |
8,296,130 | 8 | 9 | 8. The method of claim 1 , wherein: the offensiveness threshold value is set by a user of a service; the string of words is an intended output from the service to the user; and the string of words containing a candidate word identified as an offender word by having an offensiveness score that exceeds the offensiveness threshold set by the user is modified prior to being displayed to the user. | 8. The method of claim 1 , wherein: the offensiveness threshold value is set by a user of a service; the string of words is an intended output from the service to the user; and the string of words containing a candidate word identified as an offender word by having an offensiveness score that exceeds the offensiveness threshold set by the user is modified prior to being displayed to the user. 9. The method of claim 8 , wherein the string of words is modified according to one of the following: deleting the string of words such that the string of words is not displayed to the user; deleting the offensive word from the string of words so that the offensive word is not displayed to the user; censoring the string of words such that the string of words is not displayed to the user; or censoring the offensive word from the string of words so that the offensive word is not displayed to the user. | 0.5 |
9,116,871 | 1 | 8 | 1. A method executed on a computing device for converting a handwritten ink input to text representations, the method comprising: detecting an action to provide ink input on content viewed on the computing device; analyzing a context of the ink input; converting the ink input to a text annotation; suggesting a placement of the text annotation based on the context of the ink input in response to a determination that an intent of the action is ambiguous; detecting one of an acceptance action and an edit action on the text annotation in response to the suggested placement of the text annotation; and displaying the text annotation in an annotation view on a user interface of the computing device. | 1. A method executed on a computing device for converting a handwritten ink input to text representations, the method comprising: detecting an action to provide ink input on content viewed on the computing device; analyzing a context of the ink input; converting the ink input to a text annotation; suggesting a placement of the text annotation based on the context of the ink input in response to a determination that an intent of the action is ambiguous; detecting one of an acceptance action and an edit action on the text annotation in response to the suggested placement of the text annotation; and displaying the text annotation in an annotation view on a user interface of the computing device. 8. The method of claim 1 , further comprising: processing the ink input to differentiate one or more of: text, shapes, and symbols from one or more of: a comment, text intended for insertion into the content, and an instruction for another action intended to be performed on the content. | 0.5 |
8,209,311 | 10 | 16 | 10. A computing system, comprising: a processor configured to execute instructions; and a memory system comprising one or more computer readable media, wherein the memory system stores computer instructions that, when executed by the process, cause the processor to perform a method comprising: receiving a plurality of masks, each mask comprising a string of one or more characters; accessing a list of URLs; for each URL in the list of URLs: identifying any portions of the URL that match the one or more characters in the plurality of masks, and removing from the URL the identified portions to create a resultant URL; and collapsing all identical resultant URLs into one URL. | 10. A computing system, comprising: a processor configured to execute instructions; and a memory system comprising one or more computer readable media, wherein the memory system stores computer instructions that, when executed by the process, cause the processor to perform a method comprising: receiving a plurality of masks, each mask comprising a string of one or more characters; accessing a list of URLs; for each URL in the list of URLs: identifying any portions of the URL that match the one or more characters in the plurality of masks, and removing from the URL the identified portions to create a resultant URL; and collapsing all identical resultant URLs into one URL. 16. The system of claim 10 , wherein one or more of the URLs are associated with media and include content indicating at least one of an artist of the media, a title of the media, a host of the media, a bit rate of the media, a sampling rate of the media, and a duration of the media. | 0.640506 |
8,755,612 | 19 | 20 | 19. The system of claim 17 , comprising a stored table of screen controls and their associated designated character strings. | 19. The system of claim 17 , comprising a stored table of screen controls and their associated designated character strings. 20. The system of claim 19 , wherein a designated character string is identifiable in the table by a coordinate of its corresponding screen control. | 0.5 |
8,396,864 | 1 | 5 | 1. A method comprising: selecting a topic from a hierarchy of topics; receiving, from a user, a seed set including one or more seed pages for the topic; receiving a document that is not associated with the topic; using the seed to determine, with a processor, a topic destination score and a topic source score for the document relative to the document, the topic destination score indicating an amount of content in the document relating to the topic and the topic source score indicating reachability of content relating to the topic through the document; receiving a query; and returning the document as a result for the query based at least in part on the topic source score and the topic destination score for the document; wherein returning the document as a result for the query based at least in part on the topic source score and the topic destination score for the document further comprises calculating a topic score according to a weighted average of the topic source score and topic destination score; and returning the document as a result for the query based at least in part on the topic score. | 1. A method comprising: selecting a topic from a hierarchy of topics; receiving, from a user, a seed set including one or more seed pages for the topic; receiving a document that is not associated with the topic; using the seed to determine, with a processor, a topic destination score and a topic source score for the document relative to the document, the topic destination score indicating an amount of content in the document relating to the topic and the topic source score indicating reachability of content relating to the topic through the document; receiving a query; and returning the document as a result for the query based at least in part on the topic source score and the topic destination score for the document; wherein returning the document as a result for the query based at least in part on the topic source score and the topic destination score for the document further comprises calculating a topic score according to a weighted average of the topic source score and topic destination score; and returning the document as a result for the query based at least in part on the topic score. 5. The method of claim 1 wherein the seed represents a flavor. | 0.867521 |
7,493,259 | 25 | 30 | 25. A method for accessing an enterprise data system via a telephone, comprising: enabling a telephone connection to a voice access system; authenticating the telephone connection using a user identifier, wherein the authenticating comprises: querying a database with the user identifier, and in response to the querying, verifying the user identifier and receiving from the database an enterprise data system log-in data comprising a password for the enterprise data system; automatically logging into the enterprise data system using the enterprise data system log-in data; providing a voice user interface that enables: access to a plurality of domains, and navigation and querying of data from an accessed domain using spoken navigation and spoken query commands, wherein each of a plurality of domains comprises data corresponding to a respective type of object in the enterprise data system; determining a navigation context; receiving a navigation command; updating the navigation context in response to the navigation command; providing a system prompt based on the navigation context; determining a currently accessed domain among the plurality of domains; and providing feedback data in a verbal format via the telephone connection in response to spoken navigation and spoken query commands, wherein the feedback data is based, at least in part, on the currently accessed domain, and the providing the feedback data comprises: generating audio data by performing a text-to-speech conversion on retrieved data; and generating a verbalized system response by interspersing the audio data with waveform data of prompts. | 25. A method for accessing an enterprise data system via a telephone, comprising: enabling a telephone connection to a voice access system; authenticating the telephone connection using a user identifier, wherein the authenticating comprises: querying a database with the user identifier, and in response to the querying, verifying the user identifier and receiving from the database an enterprise data system log-in data comprising a password for the enterprise data system; automatically logging into the enterprise data system using the enterprise data system log-in data; providing a voice user interface that enables: access to a plurality of domains, and navigation and querying of data from an accessed domain using spoken navigation and spoken query commands, wherein each of a plurality of domains comprises data corresponding to a respective type of object in the enterprise data system; determining a navigation context; receiving a navigation command; updating the navigation context in response to the navigation command; providing a system prompt based on the navigation context; determining a currently accessed domain among the plurality of domains; and providing feedback data in a verbal format via the telephone connection in response to spoken navigation and spoken query commands, wherein the feedback data is based, at least in part, on the currently accessed domain, and the providing the feedback data comprises: generating audio data by performing a text-to-speech conversion on retrieved data; and generating a verbalized system response by interspersing the audio data with waveform data of prompts. 30. The method of claim 25 , wherein the spoken navigation and spoken query commands includes a query accessing, which comprises a request to retrieve data corresponding to a domain a user is currently that is provided to the enterprise data system and returns a plurality of data sets comprising header data identifying items pertaining to the current domain, the method further comprising: enabling the user to browse the header data on an item-by-item basis using verbal navigation commands; and reading the header data corresponding to each item in response to a user navigation to that item. | 0.5 |
9,959,271 | 7 | 12 | 7. A computer-implemented method for classifying a quality of translated segments generated by a machine translation system, the method comprising: generating an estimated difficulty feature score of a supervised machine learning model in translating input text segments based, at least in part, on a number of out-of-vocabulary words in the input text segments; training a machine translation quality classifier stored in a memory to classify the quality of the translated segments utilizing the supervised machine learning model configured with a misclassification cost configured to offset an imbalance between a plurality of classes of training data, the training data comprising one or more feature scores associated with machine translated segments of a target language and correct class labels for the machine translated segments in the target language, the one or more feature scores including the estimated difficulty feature score; and a loss function configured to penalize a misclassification of a lower-quality translated segment as a higher-quality translated segment more greatly than a misclassification of a higher-quality translated segment as a lower-quality translated segment; and utilizing the machine translation quality classifier at a computer in a service provider network to classify the quality of the translated segments generated by the machine translation system into the plurality of classes. | 7. A computer-implemented method for classifying a quality of translated segments generated by a machine translation system, the method comprising: generating an estimated difficulty feature score of a supervised machine learning model in translating input text segments based, at least in part, on a number of out-of-vocabulary words in the input text segments; training a machine translation quality classifier stored in a memory to classify the quality of the translated segments utilizing the supervised machine learning model configured with a misclassification cost configured to offset an imbalance between a plurality of classes of training data, the training data comprising one or more feature scores associated with machine translated segments of a target language and correct class labels for the machine translated segments in the target language, the one or more feature scores including the estimated difficulty feature score; and a loss function configured to penalize a misclassification of a lower-quality translated segment as a higher-quality translated segment more greatly than a misclassification of a higher-quality translated segment as a lower-quality translated segment; and utilizing the machine translation quality classifier at a computer in a service provider network to classify the quality of the translated segments generated by the machine translation system into the plurality of classes. 12. The computer-implemented method of claim 7 , wherein the plurality of classes comprises a perfect or near perfect class, an understandable class, and a residual class. | 0.852586 |
8,452,793 | 27 | 28 | 27. The computer readable storage medium of claim 20 , wherein the modified search results webpage comprises a second plurality of search results, wherein a copy of the modified search results webpage is locally cached, and wherein the one or more sequences of instructions, when executed by the one or more processors further cause: receiving a second user selection of a search result of the second plurality of search results, wherein selection of the search result of the second plurality of search results causes a document corresponding to the second user selection to be displayed; modifying the locally cached copy of the modified search results webpage to include metadata associated with the second user selection of the search result of the second plurality of search results; in response to receiving a request to re-display the modified search results webpage: generating a third plurality of search results based on the first user selection and the second user selection; and presenting a third webpage including the third plurality of search results. | 27. The computer readable storage medium of claim 20 , wherein the modified search results webpage comprises a second plurality of search results, wherein a copy of the modified search results webpage is locally cached, and wherein the one or more sequences of instructions, when executed by the one or more processors further cause: receiving a second user selection of a search result of the second plurality of search results, wherein selection of the search result of the second plurality of search results causes a document corresponding to the second user selection to be displayed; modifying the locally cached copy of the modified search results webpage to include metadata associated with the second user selection of the search result of the second plurality of search results; in response to receiving a request to re-display the modified search results webpage: generating a third plurality of search results based on the first user selection and the second user selection; and presenting a third webpage including the third plurality of search results. 28. The computer readable storage medium of claim 27 , wherein generating the third plurality of search results comprises: identifying repetitive subject matter in the document corresponding to the first user selection and the document corresponding to the second user selection; generating the third plurality of search results based on the repetitive subject matter. | 0.653484 |
8,024,333 | 15 | 20 | 15. A non-transitory computer readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method for providing data based on object relevance, the method comprising: receiving one or more query terms from a user via a communications interface associated with at least one computing device; determining a preliminary relevance of one or more objects associated with an enterprise system based on the query terms; assigning at least one rating to the one or more objects based on the preliminary relevance; propogating the preliminary relevance among the one or more objects; establishing an overall relevance of the one or more objects based on the at least one rating, utilizing the preliminary relevance and the propogation; ranking the one or more objects according to the overall relevance; providing data as search results comprised of the one or more objects according to the ranking to the user; filtering the search results based on at least one selected, dynamically generated filter associated with the one or more objects; and transmit to display the search results to the user via the at least one computing device. | 15. A non-transitory computer readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method for providing data based on object relevance, the method comprising: receiving one or more query terms from a user via a communications interface associated with at least one computing device; determining a preliminary relevance of one or more objects associated with an enterprise system based on the query terms; assigning at least one rating to the one or more objects based on the preliminary relevance; propogating the preliminary relevance among the one or more objects; establishing an overall relevance of the one or more objects based on the at least one rating, utilizing the preliminary relevance and the propogation; ranking the one or more objects according to the overall relevance; providing data as search results comprised of the one or more objects according to the ranking to the user; filtering the search results based on at least one selected, dynamically generated filter associated with the one or more objects; and transmit to display the search results to the user via the at least one computing device. 20. The computer readable storage medium recited in claim 15 , further comprising receiving at least one further query term from the user for narrowing the search results. | 0.5 |
9,633,649 | 11 | 12 | 11. The system of claim 8 , wherein the demographic of the user comprises a geographic location. | 11. The system of claim 8 , wherein the demographic of the user comprises a geographic location. 12. The system of claim 11 , wherein the geographic location is a school. | 0.5 |
7,640,006 | 1 | 6 | 1. A method of providing information assistance to a wireless terminal, comprising the steps of: receiving, from a wireless terminal operated by a requestor, a contact information request with an information assistance application located on an information assistance server, wherein the contact information request is a request for contact information of a user of a subscriber terminal that is other than the wireless terminal; querying a participating communication provider database of a communication provider providing communication services to the wireless terminal to identify a virtual key of the requestor from unique information of the wireless terminal included with the contact information request, the virtual key being a universal anonymous identifier of the requestor that is shared among a plurality of different participating businesses; accessing a consumer internal profile database containing verification data of the requestor and proprietary information of the requestor with the virtual key of the requestor, the verification data providing verification of consent by the requestor of release and use of the proprietary information of the requestor; accessing permissions of the user of the subscriber terminal with the information assistance application to determine if the contact information request should be automatically denied categorically or specifically, based on the proprietary information of the requestor obtained from the consumer internal profile database with the virtual key of the requestor; determining a contact preference for how to contact the subscriber terminal about the received contact information request with the information assistance application only when the information request is determined as not being automatically denied; generating an authorization request to request permission from the subscriber terminal to provide the contact information of the user of the subscriber terminal to the wireless terminal, wherein the authorization request includes an indication of an identity of the requestor based on the proprietary information of the requestor; transmitting the authorization request to the subscriber terminal in accordance with the determined contact preference; receiving a reply from the subscriber terminal indicative of whether or not the requested information record is permitted to be provided to the wireless terminal; accessing the consumer internal profile database to determine pre-determined contact parameters of the requestor based on the virtual key of the requestor; and generating a response for transmittal to the wireless terminal when the reply is indicative of permission to proceed with provision of the requested contact information of the user to the wireless terminal, the response including only contact information identified by the user of the subscriber terminal as permissible to send to the wireless terminal, the response generated in accordance with the format preferences of the requestor. | 1. A method of providing information assistance to a wireless terminal, comprising the steps of: receiving, from a wireless terminal operated by a requestor, a contact information request with an information assistance application located on an information assistance server, wherein the contact information request is a request for contact information of a user of a subscriber terminal that is other than the wireless terminal; querying a participating communication provider database of a communication provider providing communication services to the wireless terminal to identify a virtual key of the requestor from unique information of the wireless terminal included with the contact information request, the virtual key being a universal anonymous identifier of the requestor that is shared among a plurality of different participating businesses; accessing a consumer internal profile database containing verification data of the requestor and proprietary information of the requestor with the virtual key of the requestor, the verification data providing verification of consent by the requestor of release and use of the proprietary information of the requestor; accessing permissions of the user of the subscriber terminal with the information assistance application to determine if the contact information request should be automatically denied categorically or specifically, based on the proprietary information of the requestor obtained from the consumer internal profile database with the virtual key of the requestor; determining a contact preference for how to contact the subscriber terminal about the received contact information request with the information assistance application only when the information request is determined as not being automatically denied; generating an authorization request to request permission from the subscriber terminal to provide the contact information of the user of the subscriber terminal to the wireless terminal, wherein the authorization request includes an indication of an identity of the requestor based on the proprietary information of the requestor; transmitting the authorization request to the subscriber terminal in accordance with the determined contact preference; receiving a reply from the subscriber terminal indicative of whether or not the requested information record is permitted to be provided to the wireless terminal; accessing the consumer internal profile database to determine pre-determined contact parameters of the requestor based on the virtual key of the requestor; and generating a response for transmittal to the wireless terminal when the reply is indicative of permission to proceed with provision of the requested contact information of the user to the wireless terminal, the response including only contact information identified by the user of the subscriber terminal as permissible to send to the wireless terminal, the response generated in accordance with the format preferences of the requestor. 6. The method of claim 1 , wherein receiving, from a wireless terminal, a contact information request comprises interpreting the contact information request with a voice recognition module when the contact information request is a spoken request. | 0.680519 |
8,655,864 | 1 | 3 | 1. A computer implemented method, comprising: accessing a mapping document that represents an organization of related network-accessible documents within a website, at least some of the network-accessible documents whose organization is represented by the mapping document being mobile content; receiving an indication that at least some of the network-accessible documents whose organization is represented by the mapping document are mobile content; selecting, based on the indication that at least some of the network-accessible documents whose organization is represented by the mapping document are mobile content, a mobile content crawling mode to crawl the network-accessible documents of the website that are mobile content; crawling the website based on the mapping document to obtain information from the network-accessible documents, wherein the network-accessible documents that are mobile content are crawled in the mobile content crawling mode; adding the information from at least some of the network-accessible documents to a search engine index; receiving a search request from a mobile device; and transmitting search results to the mobile device, the search results responsive to the search request and identified at least in part using information in the search engine index. | 1. A computer implemented method, comprising: accessing a mapping document that represents an organization of related network-accessible documents within a website, at least some of the network-accessible documents whose organization is represented by the mapping document being mobile content; receiving an indication that at least some of the network-accessible documents whose organization is represented by the mapping document are mobile content; selecting, based on the indication that at least some of the network-accessible documents whose organization is represented by the mapping document are mobile content, a mobile content crawling mode to crawl the network-accessible documents of the website that are mobile content; crawling the website based on the mapping document to obtain information from the network-accessible documents, wherein the network-accessible documents that are mobile content are crawled in the mobile content crawling mode; adding the information from at least some of the network-accessible documents to a search engine index; receiving a search request from a mobile device; and transmitting search results to the mobile device, the search results responsive to the search request and identified at least in part using information in the search engine index. 3. The method of claim 1 , further comprising receiving a notification that the mapping document is available, wherein crawling the website is in response to the notification. | 0.587264 |
8,482,500 | 2 | 3 | 2. The mobile display apparatus as set forth in claim 1 , wherein: the display section includes a display element driven by a thin film element; and the video signal input section, the display control section, the text recognizing section, and the voice output control section are either directly provided on a thin film substrate on which a pixel driving circuit element of the display element is provided, or include active elements provided on another substrate which is bonded to the thin film substrate. | 2. The mobile display apparatus as set forth in claim 1 , wherein: the display section includes a display element driven by a thin film element; and the video signal input section, the display control section, the text recognizing section, and the voice output control section are either directly provided on a thin film substrate on which a pixel driving circuit element of the display element is provided, or include active elements provided on another substrate which is bonded to the thin film substrate. 3. The mobile display apparatus as set forth in claim 2 , wherein: the voice output section includes a sound source element which is layered on the display element of the display section within a flat region of the display element; and a sound source element generates voice sounds by vibrating the display element. | 0.5 |
9,767,263 | 8 | 9 | 8. The system of claim 6 , wherein the one or more services further: receive a second request for one or more resources, the second request including a successful solution to the challenge-response problem; identify the second request as originating from an automated-agent; and limit or block access to the one or more resources in response to the second request, based at least in part on identifying the second request as originating from the automated-agent. | 8. The system of claim 6 , wherein the one or more services further: receive a second request for one or more resources, the second request including a successful solution to the challenge-response problem; identify the second request as originating from an automated-agent; and limit or block access to the one or more resources in response to the second request, based at least in part on identifying the second request as originating from the automated-agent. 9. The system of claim 8 , wherein the one or more actions in response to the successful solution to the challenge-response problem include providing a different one or more resources than the one or more resources requested by the second request. | 0.5 |
9,858,313 | 7 | 9 | 7. An apparatus, comprising: a computing platform to: determine a first group of result tuples to be based at least in part on one or more first dominance relationships between pairs of result tuples to be associated with a plurality of query-independent attribute values; in response to initiation of processing of a search query, identify two or more result tuples from the first group to be comparable to one or more tuples for the search query the two or more result tuples are to be identified as comparable at least partially in response to a determination that comparability values between pairs of the two or more result tuples to have at least a threshold value of comparability; determine one or more second dominance relationships between the pairs of the two or more result tuples to be based at least in part on at least one query-dependent value of the two or more result tuples; and determine a suggestion set to comprise a set of the two or more result tuples, the set of the two or more result tuples to comprise one or more result tuples to be determined to not be dominated by another of the result tuples to be based at least in part on the one or more second dominance relationships and to be further based at least in part on one or more inference rules to be indicative of an existence of one or more static domination relationships between attributes of the plurality of entities, wherein a first tuple of the two or more result tuples is to be determined not to dominate a second tuple of the two or more result tuples at least partially in response to a determination that query-dependent individual first attribute values of at least two of the attributes of the first tuple to not indicate the greater scope of interest than query-dependent individual second attribute values of the at least two of the attributes of the second tuple. | 7. An apparatus, comprising: a computing platform to: determine a first group of result tuples to be based at least in part on one or more first dominance relationships between pairs of result tuples to be associated with a plurality of query-independent attribute values; in response to initiation of processing of a search query, identify two or more result tuples from the first group to be comparable to one or more tuples for the search query the two or more result tuples are to be identified as comparable at least partially in response to a determination that comparability values between pairs of the two or more result tuples to have at least a threshold value of comparability; determine one or more second dominance relationships between the pairs of the two or more result tuples to be based at least in part on at least one query-dependent value of the two or more result tuples; and determine a suggestion set to comprise a set of the two or more result tuples, the set of the two or more result tuples to comprise one or more result tuples to be determined to not be dominated by another of the result tuples to be based at least in part on the one or more second dominance relationships and to be further based at least in part on one or more inference rules to be indicative of an existence of one or more static domination relationships between attributes of the plurality of entities, wherein a first tuple of the two or more result tuples is to be determined not to dominate a second tuple of the two or more result tuples at least partially in response to a determination that query-dependent individual first attribute values of at least two of the attributes of the first tuple to not indicate the greater scope of interest than query-dependent individual second attribute values of the at least two of the attributes of the second tuple. 9. The apparatus of claim 7 , wherein the suggestions set to comprise a specified number of query suggestions. | 0.764957 |
10,001,977 | 1 | 11 | 1. A method comprising: for a plurality of operations, each operation defined to operate on one or more input arguments including one or more constraints, receiving input data; identifying, by a first processor, a first operation in which the input data satisfies the one or more constraints of the one or more input arguments of the first operation; identifying, by the first or a second processor, a second operation in which the input data does not satisfy the one or more constraints of the one or more input arguments of the second operation; presenting, on a display coupled to the first or the second processor, the first operation in a form selectable for execution by a user based on the input data satisfying the one or more constraints of the one or more input arguments of the first operation; presenting on the display the second operation in a form that is non-selectable for execution by the user based on the input data not satisfying the one or more constraints of the one or more input arguments of the second operation; executing, by the first, the second or a third processor, the first operation utilizing the input data; and presenting a result of the executing of the first operation on the display. | 1. A method comprising: for a plurality of operations, each operation defined to operate on one or more input arguments including one or more constraints, receiving input data; identifying, by a first processor, a first operation in which the input data satisfies the one or more constraints of the one or more input arguments of the first operation; identifying, by the first or a second processor, a second operation in which the input data does not satisfy the one or more constraints of the one or more input arguments of the second operation; presenting, on a display coupled to the first or the second processor, the first operation in a form selectable for execution by a user based on the input data satisfying the one or more constraints of the one or more input arguments of the first operation; presenting on the display the second operation in a form that is non-selectable for execution by the user based on the input data not satisfying the one or more constraints of the one or more input arguments of the second operation; executing, by the first, the second or a third processor, the first operation utilizing the input data; and presenting a result of the executing of the first operation on the display. 11. The method of claim 1 wherein a group of operations from the plurality of operations is identified where the input data satisfies the one or more constraints on the one or more input arguments of each operation in the group of operations, and each operation of the group has at least one of a name, a description, and documentation, the method further comprising: receiving from the user a search string; and presenting on the display only those operations from the group of operations having the name, the description or the documentation that matches the search string from the user. | 0.505872 |
9,135,241 | 12 | 13 | 12. The system of claim 10 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, result in operations comprising: predicting the label for the target word based on a connectionist model. | 12. The system of claim 10 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, result in operations comprising: predicting the label for the target word based on a connectionist model. 13. The system of claim 12 , wherein the connectionist model comprises a learnable linear mapping which maps each word in the first natural language corpus to a low dimensional latent space. | 0.5 |
9,471,551 | 1 | 4 | 1. A computer-implemented method comprising: Receiving various requests for content items to be displayed in various content item slots on various web resources presented at various user devices, wherein the various requests include information related to an amount of space available in the various content item slots; and for at least some of the various requests: identifying, using one or more processors and in response to the request, a content item from a set of eligible content items that are responsive to the request, the content item including a title portion and a body portion, the title portion including original text and being distinct from the body portion, wherein the body portion includes a plurality of lines of text including a first line of text and a second line of text; determining, based on the amount of space available in a content item slot, that the identified content item is too long to fit in the content item slot; and in response to determining that the identified content item is too long to fit in the content item slot: evaluating the body portion including determining when the body portion includes a complete phrase that is included in the plurality of lines, the evaluating including applying a test to one or more words in the body portion, wherein the evaluation is based, at least in part, on a size of the complete phrase and the amount of horizontal space in the title portion, as specified in the request; dynamically creating a modified content item from the content item, including promoting, using the one or more processors, the complete phrase into the title portion of the modified content item, wherein the title portion of the modified content item includes both the original text and the complete phrase; and providing the modified content item for presentation in the content item slot and in response to the content item request. | 1. A computer-implemented method comprising: Receiving various requests for content items to be displayed in various content item slots on various web resources presented at various user devices, wherein the various requests include information related to an amount of space available in the various content item slots; and for at least some of the various requests: identifying, using one or more processors and in response to the request, a content item from a set of eligible content items that are responsive to the request, the content item including a title portion and a body portion, the title portion including original text and being distinct from the body portion, wherein the body portion includes a plurality of lines of text including a first line of text and a second line of text; determining, based on the amount of space available in a content item slot, that the identified content item is too long to fit in the content item slot; and in response to determining that the identified content item is too long to fit in the content item slot: evaluating the body portion including determining when the body portion includes a complete phrase that is included in the plurality of lines, the evaluating including applying a test to one or more words in the body portion, wherein the evaluation is based, at least in part, on a size of the complete phrase and the amount of horizontal space in the title portion, as specified in the request; dynamically creating a modified content item from the content item, including promoting, using the one or more processors, the complete phrase into the title portion of the modified content item, wherein the title portion of the modified content item includes both the original text and the complete phrase; and providing the modified content item for presentation in the content item slot and in response to the content item request. 4. The method of claim 1 wherein the test evaluates each word in the first line to determine if the word completes a sentence, and when so, promoting the portion of the first line including the word. | 0.694785 |
7,739,115 | 23 | 31 | 23. The method of claim 1 , further comprising identifying at least one instance of non-compliance with the script, wherein the agent did not adequately follow the script during at least one given interaction. | 23. The method of claim 1 , further comprising identifying at least one instance of non-compliance with the script, wherein the agent did not adequately follow the script during at least one given interaction. 31. The method of claim 23 , further comprising directing the agent to remedial materials related to improving performance of the agent. | 0.671498 |
9,275,042 | 10 | 18 | 10. A computing device comprising: a processor; a computer storage operationally coupled to the processor and configured to store a corpus of user utterances received by a conversational agent, configured to be processed computationally by the processor, through an interactive natural language dialog with a user; the conversational agent further configured to perform computationally a linguistics analysis of the corpus of user utterances to identify semantic graphs that match respective user utterances in the corpus; the executing conversational agent still further configured to: cluster computationally the semantic graphs of the utterances in the first corpus based on user intent to form one or more semantic clusters; and attach additional semantic graphs of user utterances to the one or more semantic clusters based on the user intent. | 10. A computing device comprising: a processor; a computer storage operationally coupled to the processor and configured to store a corpus of user utterances received by a conversational agent, configured to be processed computationally by the processor, through an interactive natural language dialog with a user; the conversational agent further configured to perform computationally a linguistics analysis of the corpus of user utterances to identify semantic graphs that match respective user utterances in the corpus; the executing conversational agent still further configured to: cluster computationally the semantic graphs of the utterances in the first corpus based on user intent to form one or more semantic clusters; and attach additional semantic graphs of user utterances to the one or more semantic clusters based on the user intent. 18. The computing device as claimed in claim 10 wherein the executing conversation agent is further configured to leverage the one or more semantic clusters in order to respond to interaction with the user. | 0.773128 |
9,928,267 | 1 | 2 | 1. A method for hierarchical database compression, comprising: applying, by a database management unit, a first level of a first type of compression to a first partition of a column of a database and storing data generated from applying the first level of the first type of compression to the first partition in a memory buffer external to the database; and applying, by the database management unit, a second level of the first type of compression to a subset of the data, wherein the first level of the first type of compression comprises a first first-level dictionary and the second level of the first type of compression comprises a first second-level dictionary, and wherein a code size of the first first-level dictionary is larger than a code size of the first second-level dictionary, wherein applying the second level of the first type of compression further comprises: adding a first data entry to a set of data corresponding to a page of the database; determining an amount of space saved by applying the second level of the first type of compression to the set of data; determining a size of the first second-level dictionary corresponding to the first type of compression; based on determining that the amount of space is larger than the size of the first second-level dictionary, adding a second data entry to the set of data corresponding to the page; determining, based on the adding of the second data entry to the set of data, that there is a change to at least one of size of the first second-level dictionary and the code size of the first second-level dictionary; calculating a size of the page based on the determined change; determining that the page is full based on the calculated size of the page; removing the second data entry from the set of data corresponding to the page; applying the second level of the first type of compression without the determined change to the set of data corresponding to the page; performing predicate evaluation on the subset of the first partition by converting a predicate value into a compressed predicate value using the first first-level dictionary and the first second-level dictionary, and comparing the predicate value directly to compressed data in the subset of the first partition, wherein the compressed data is compressed using the first level and the second level of the first type of compression; performing join/groupby processing on the subset of the first partition by converting of second-level codes to first-level codes using the first second-level dictionary, and performing the join/groupby processing on the first-level codes; and performing expression evaluation on the subset of the first partition by converting second-level codes to uncompressed data using the first first-level dictionary and the first second-level dictionary. | 1. A method for hierarchical database compression, comprising: applying, by a database management unit, a first level of a first type of compression to a first partition of a column of a database and storing data generated from applying the first level of the first type of compression to the first partition in a memory buffer external to the database; and applying, by the database management unit, a second level of the first type of compression to a subset of the data, wherein the first level of the first type of compression comprises a first first-level dictionary and the second level of the first type of compression comprises a first second-level dictionary, and wherein a code size of the first first-level dictionary is larger than a code size of the first second-level dictionary, wherein applying the second level of the first type of compression further comprises: adding a first data entry to a set of data corresponding to a page of the database; determining an amount of space saved by applying the second level of the first type of compression to the set of data; determining a size of the first second-level dictionary corresponding to the first type of compression; based on determining that the amount of space is larger than the size of the first second-level dictionary, adding a second data entry to the set of data corresponding to the page; determining, based on the adding of the second data entry to the set of data, that there is a change to at least one of size of the first second-level dictionary and the code size of the first second-level dictionary; calculating a size of the page based on the determined change; determining that the page is full based on the calculated size of the page; removing the second data entry from the set of data corresponding to the page; applying the second level of the first type of compression without the determined change to the set of data corresponding to the page; performing predicate evaluation on the subset of the first partition by converting a predicate value into a compressed predicate value using the first first-level dictionary and the first second-level dictionary, and comparing the predicate value directly to compressed data in the subset of the first partition, wherein the compressed data is compressed using the first level and the second level of the first type of compression; performing join/groupby processing on the subset of the first partition by converting of second-level codes to first-level codes using the first second-level dictionary, and performing the join/groupby processing on the first-level codes; and performing expression evaluation on the subset of the first partition by converting second-level codes to uncompressed data using the first first-level dictionary and the first second-level dictionary. 2. The method of claim 1 , further comprising: applying a first level of a second type of compression to a second partition of the column of the database; applying a second level of the second type of compression to a subset of the second partition, wherein the first level of the second type of compression comprises a second first-level dictionary and the second level of the second type of compression comprises a second second-level dictionary, and wherein a code size of the second first-level dictionary is larger than a code size of the second second-level dictionary. | 0.608311 |
9,754,192 | 3 | 4 | 3. The computing device of claim 1 , wherein the computer-executable instructions causing the computing device to perform the identifying, the selecting, and the determining, are part of a first classifier that generates a first classifier output identifying a first set of portions of the image as depicting physical objects of the first predefined type; and wherein further the computer-readable media comprise further computer-executable instructions, which, when executed by the one or more processing units, cause the computing device to: assign a first weight to the first classifier output to generate a weighted first classifier output; receive, from a second classifier, a second classifier output that identifies a second set of portions of the image as depicting physical objects of the first predefined type; assign a second weight to the second classifier output to generate a weighted second classifier output; and amalgamate the weighted first classifier output with the weighted second classifier output; wherein the automatically identifying the portions of the image of the physical scene as depicting the physical objects of the predefined types is based on the amalgamating. | 3. The computing device of claim 1 , wherein the computer-executable instructions causing the computing device to perform the identifying, the selecting, and the determining, are part of a first classifier that generates a first classifier output identifying a first set of portions of the image as depicting physical objects of the first predefined type; and wherein further the computer-readable media comprise further computer-executable instructions, which, when executed by the one or more processing units, cause the computing device to: assign a first weight to the first classifier output to generate a weighted first classifier output; receive, from a second classifier, a second classifier output that identifies a second set of portions of the image as depicting physical objects of the first predefined type; assign a second weight to the second classifier output to generate a weighted second classifier output; and amalgamate the weighted first classifier output with the weighted second classifier output; wherein the automatically identifying the portions of the image of the physical scene as depicting the physical objects of the predefined types is based on the amalgamating. 4. The computing device of claim 3 , wherein the computer-readable media comprise further computer-executable instructions, which, when executed by the one or more processing units, cause the computing device to: identify, utilizing the first and second classifiers, with their outputs weighted by the first and second weights, respectively, portions of a training image as depicting the physical objects of the predefined types; compare the identified portions of the training image to known portions of the training image verified to depict the physical objects of the predefined types; modify the first and second weights; repeat the identifying the portions of the training image and the comparing utilizing the modified first and second weights; and select, as selected first and second weights, those of the modified first and second weights that resulted in the identified portions of the training image being closest to the known portions. | 0.5 |
8,406,063 | 1 | 2 | 1. A method for programming non-volatile storage including a set of word lines connected to a group of connected non-volatile storage elements, the set of word lines include a selected word line, a set of unselected word lines that are adjacent to the selected word line and a set of other unselected word lines, the method comprising: raising the selected word line and the set of other unselected word lines to a first voltage during a first time period from a first time to a second time; raising the set of unselected word lines that are adjacent to the selected word line to one or more second voltages different from the first voltage during the first time period; raising the selected word line to a program voltage causing at least one of the non-volatile storage elements to experience programming during a second time period from the second time to a third time; raising the set of unselected word lines that are adjacent to the selected word line to a third voltage during the second time period; and maintaining the set of other unselected word lines at the first voltage during the second time period. | 1. A method for programming non-volatile storage including a set of word lines connected to a group of connected non-volatile storage elements, the set of word lines include a selected word line, a set of unselected word lines that are adjacent to the selected word line and a set of other unselected word lines, the method comprising: raising the selected word line and the set of other unselected word lines to a first voltage during a first time period from a first time to a second time; raising the set of unselected word lines that are adjacent to the selected word line to one or more second voltages different from the first voltage during the first time period; raising the selected word line to a program voltage causing at least one of the non-volatile storage elements to experience programming during a second time period from the second time to a third time; raising the set of unselected word lines that are adjacent to the selected word line to a third voltage during the second time period; and maintaining the set of other unselected word lines at the first voltage during the second time period. 2. The method of claim 1 further comprising: the set of unselected word lines that are adjacent to the selected word line includes more than two word lines. | 0.851992 |
10,078,504 | 5 | 8 | 5. A computer-implemented method for automated internationalization and localization of program source code, the method comprising: receiving a request at a network service to internationalize and localize the program source code; and responsive to the request, identifying one or more text strings contained in the program source code, extracting the one or more text strings from the program source code, generating one or more translated text strings by translating the one or more text strings from a first human readable language to at least one second human readable language, generating internationalized and localized program source code by replacing the one or more text strings with program code for obtaining the one or more translated text strings, returning, by way of the network service, the internationalized and localized program source code in a reply to the request, determining whether one or more internationalization or localization issues are present in the program source code, responsive to determining that no internationalization or localization issues are present in the program source code, causing the program source code to be compiled to create an executable internationalized and localized program, and causing the internationalized and localized program to be deployed to at least one computing resource operating in a service provider network, and responsive to determining that internationalization or localization issues are present in the program source code, determining whether a developer has indicated that the internationalized and localized program is to be deployed even if internationalization or localization issues are present in the program source code, and causing the program source code to be compiled to create an executable internationalized and localized program if the developer has indicated that the internationalized and localized program is to be deployed even if internationalization or localization issues are present in the program source code, and causing the internationalized and localized program to be deployed to at least one computing resource operating in a service provider network. | 5. A computer-implemented method for automated internationalization and localization of program source code, the method comprising: receiving a request at a network service to internationalize and localize the program source code; and responsive to the request, identifying one or more text strings contained in the program source code, extracting the one or more text strings from the program source code, generating one or more translated text strings by translating the one or more text strings from a first human readable language to at least one second human readable language, generating internationalized and localized program source code by replacing the one or more text strings with program code for obtaining the one or more translated text strings, returning, by way of the network service, the internationalized and localized program source code in a reply to the request, determining whether one or more internationalization or localization issues are present in the program source code, responsive to determining that no internationalization or localization issues are present in the program source code, causing the program source code to be compiled to create an executable internationalized and localized program, and causing the internationalized and localized program to be deployed to at least one computing resource operating in a service provider network, and responsive to determining that internationalization or localization issues are present in the program source code, determining whether a developer has indicated that the internationalized and localized program is to be deployed even if internationalization or localization issues are present in the program source code, and causing the program source code to be compiled to create an executable internationalized and localized program if the developer has indicated that the internationalized and localized program is to be deployed even if internationalization or localization issues are present in the program source code, and causing the internationalized and localized program to be deployed to at least one computing resource operating in a service provider network. 8. The computer-implemented method of claim 5 , wherein the one or more text strings contained in the program source code are identified by a network service configured to perform static analysis on the program source code to identify the one or more text strings. | 0.76087 |
10,114,818 | 12 | 15 | 12. A system comprising: a processor; a computer-readable storage memory having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: performing a generic web crawl to identify a first webpage in a first language having a link thereon which points to a second webpage in a second language, wherein the first webpage and the second webpage comprise a bilingual website; based on an analysis of parameters on the first webpage comprising at least two of: the link pointing to the second webpage, a title, a link neighborhood, a link context and data indicating a separate version of the first webpage, classifying the first webpage as a root page and as an entry point for the bilingual website via the link to the second webpage; performing a bidirectional web crawl between the first webpage and the second webpage to identify the first webpage and the second webpage as the bilingual website, the bidirectional web crawl utilizing classifications of links to avoid links having a low respective relevance; extracting information pairs from the first webpage and the second webpage for use in a language translation model, the information pairs comprising at least one of a word pair, a paragraph pair and a sentence pair; and updating a statistical model with domain representative data using the information pairs. | 12. A system comprising: a processor; a computer-readable storage memory having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: performing a generic web crawl to identify a first webpage in a first language having a link thereon which points to a second webpage in a second language, wherein the first webpage and the second webpage comprise a bilingual website; based on an analysis of parameters on the first webpage comprising at least two of: the link pointing to the second webpage, a title, a link neighborhood, a link context and data indicating a separate version of the first webpage, classifying the first webpage as a root page and as an entry point for the bilingual website via the link to the second webpage; performing a bidirectional web crawl between the first webpage and the second webpage to identify the first webpage and the second webpage as the bilingual website, the bidirectional web crawl utilizing classifications of links to avoid links having a low respective relevance; extracting information pairs from the first webpage and the second webpage for use in a language translation model, the information pairs comprising at least one of a word pair, a paragraph pair and a sentence pair; and updating a statistical model with domain representative data using the information pairs. 15. The system of claim 12 , the computer-readable storage memory storing additional instructions stored which, when executed by the processor, cause the processor to perform operations comprising: bootstrapping the language translation model using the information pairs. | 0.793445 |
4,763,278 | 1 | 3 | 1. A method for recognizing speech independent of the speaker thereof, said method comprising: receiving an analog input speech signal; conditioning said analog speech signal to produce a sequence of rectangular waveforms of polarity signs alternating between plus and minus polarities as a digital waveform signal; counting the number of polarity transitions in the digital waveform signal to obtain a zero-crossing count for each frame of the digital waveform signal; measuring the time duration intervals between zero-crossings of the digital waveform signal; providing a sequence of binary feature vectors based upon the measurements of the time duration intervals between zero-crossings of the digital waveform signal and corresponding to respective frames of the digital waveform signal; providing a vocabulary consisting of a relatively small number of words, wherein each of the words included in the vocabulary is represented by a plurality of binary reference vectors which have been organized in sequences with each of said binary reference vector sequences corresponding to a word acoustically distinct from the other words included in the vocabulary; comparing each of said binary feature vectors with each of said plurality of binary reference vectors; determining a distance measure with respect to each of said binary reference vectors for each successive binary feature vector in said sequence of binary feature vectors in response to the comparison therebetween; and recognizing words in accordance with the distance measures between each of said binary reference vector sequences and successively received binary feature vectors corresponding to respective frames of the digital waveform signal. | 1. A method for recognizing speech independent of the speaker thereof, said method comprising: receiving an analog input speech signal; conditioning said analog speech signal to produce a sequence of rectangular waveforms of polarity signs alternating between plus and minus polarities as a digital waveform signal; counting the number of polarity transitions in the digital waveform signal to obtain a zero-crossing count for each frame of the digital waveform signal; measuring the time duration intervals between zero-crossings of the digital waveform signal; providing a sequence of binary feature vectors based upon the measurements of the time duration intervals between zero-crossings of the digital waveform signal and corresponding to respective frames of the digital waveform signal; providing a vocabulary consisting of a relatively small number of words, wherein each of the words included in the vocabulary is represented by a plurality of binary reference vectors which have been organized in sequences with each of said binary reference vector sequences corresponding to a word acoustically distinct from the other words included in the vocabulary; comparing each of said binary feature vectors with each of said plurality of binary reference vectors; determining a distance measure with respect to each of said binary reference vectors for each successive binary feature vector in said sequence of binary feature vectors in response to the comparison therebetween; and recognizing words in accordance with the distance measures between each of said binary reference vector sequences and successively received binary feature vectors corresponding to respective frames of the digital waveform signal. 3. A method for recognizing speech as set forth in claim 1, further including establishing the identity of an end of word prior to the recognition of a word as a precondition thereto, the establishing of said end of word identification including: monitoring the zero-crossing count for the digital waveform signal, and declaring an end of word condition whenever the average frequency of said zero-crossings exceeds an end point target zero-crossing frequency for a time duration longer than a predetermined reference time duration. | 0.669154 |
9,190,049 | 1 | 29 | 1. A system comprising: one or more processors; a computer-readable memory; and a module comprising computer executable instructions stored in the memory, wherein the one or more processors, when executing the module, are configured to: receive, from a client device, user selection data regarding a first content source and a second content source, wherein the first content source is different from the second content source; retrieve a first content item from the first content source and a second content item from the second content source; determine, based at least in part on an association between a characteristic of the first content item and a characteristic of first voice data, to use the first voice data to generate a first text-to-speech presentation of the first content item; determine, based at least in part on an association between a characteristic of the second content item and a characteristic of second voice data, to use the second voice data to generate a second text-to-speech presentation of the second content item; generate the first text-to-speech presentation of the first content item based at least in part on the first voice data; generate the second text-to-speech presentation of the second content item based at least in part on the second voice data; assemble an audio program comprising the first text-to-speech presentation and the second text-to-speech presentation; and transmit the audio program to the client device. | 1. A system comprising: one or more processors; a computer-readable memory; and a module comprising computer executable instructions stored in the memory, wherein the one or more processors, when executing the module, are configured to: receive, from a client device, user selection data regarding a first content source and a second content source, wherein the first content source is different from the second content source; retrieve a first content item from the first content source and a second content item from the second content source; determine, based at least in part on an association between a characteristic of the first content item and a characteristic of first voice data, to use the first voice data to generate a first text-to-speech presentation of the first content item; determine, based at least in part on an association between a characteristic of the second content item and a characteristic of second voice data, to use the second voice data to generate a second text-to-speech presentation of the second content item; generate the first text-to-speech presentation of the first content item based at least in part on the first voice data; generate the second text-to-speech presentation of the second content item based at least in part on the second voice data; assemble an audio program comprising the first text-to-speech presentation and the second text-to-speech presentation; and transmit the audio program to the client device. 29. The system of claim 1 , wherein the characteristic of the first content item comprises at least one of a subject matter, a vocabulary, a length, a source, or an author. | 0.779487 |
8,615,732 | 2 | 8 | 2. The method of claim 1 , further comprising: generating a pseudo-language build with the pseudo-translated locale-dependant code using the integrated build application; testing the pseudo-language build; and identifying at least one internationalization bug. | 2. The method of claim 1 , further comprising: generating a pseudo-language build with the pseudo-translated locale-dependant code using the integrated build application; testing the pseudo-language build; and identifying at least one internationalization bug. 8. The method of claim 2 , wherein the generating the pseudo-language build comprises: generating a pseudo-language database, wherein the integrated build application comprises at least one seed data file specific utility, and the locale-dependant code comprises at least one seed data file. | 0.5 |
9,747,267 | 14 | 15 | 14. In a digital medium environment for synchronized editing of simultaneously displayed document portions in a user interface, a system comprising: at least one module implemented at least partially in hardware, the at least one module configured to perform operations comprising: outputting the user interface configured to support editing of a document to perform a translation of another document; opening and displaying the document and the other document being translated in the user interface; indicating correspondence between a portion of the document to a portion of the other document being translated and synchronizing the portion of the document and the portion of the other document being translated, the indicating and synchronizing occurring automatically and without user intervention; and responsive to receiving an input via the user interface to edit a subsequent portion of the document, synchronizing the subsequent portion of the document with a subsequent portion of the other document being translated relative to the portion of the other document being translated and indicating correspondence in the user interface between the subsequent portion of the document and the subsequent portion of the other document being translated. | 14. In a digital medium environment for synchronized editing of simultaneously displayed document portions in a user interface, a system comprising: at least one module implemented at least partially in hardware, the at least one module configured to perform operations comprising: outputting the user interface configured to support editing of a document to perform a translation of another document; opening and displaying the document and the other document being translated in the user interface; indicating correspondence between a portion of the document to a portion of the other document being translated and synchronizing the portion of the document and the portion of the other document being translated, the indicating and synchronizing occurring automatically and without user intervention; and responsive to receiving an input via the user interface to edit a subsequent portion of the document, synchronizing the subsequent portion of the document with a subsequent portion of the other document being translated relative to the portion of the other document being translated and indicating correspondence in the user interface between the subsequent portion of the document and the subsequent portion of the other document being translated. 15. A system as described in claim 14 , wherein the portions are paragraphs. | 0.88125 |
8,694,959 | 12 | 14 | 12. The system of claim 6 , wherein the editor component comprises a stencil editor component configured to create at least one of a stencil, or a shape associated with a stencil, as a function of the third programming language being created. | 12. The system of claim 6 , wherein the editor component comprises a stencil editor component configured to create at least one of a stencil, or a shape associated with a stencil, as a function of the third programming language being created. 14. The system of claim 12 , wherein the stencil editor component comprises at least one object with at least one functionality respective to the third programming language. | 0.737082 |
9,618,919 | 14 | 15 | 14. The method according to claim 12 , wherein interpolation using lookup tables for each element of the linear model comprises generation of a set of linear model element lookup tables rectangular with respect to the scheduling variables if the residual set of linear models are not rectangular with respect to the scheduling variables. | 14. The method according to claim 12 , wherein interpolation using lookup tables for each element of the linear model comprises generation of a set of linear model element lookup tables rectangular with respect to the scheduling variables if the residual set of linear models are not rectangular with respect to the scheduling variables. 15. The method according to claim 14 , wherein generation of the set of linear model element lookup tables rectangular with respect to the scheduling variables is based on using linear interpolation of elements of the residual set of linear models. | 0.5 |
9,922,029 | 13 | 14 | 13. The computer-readable storage medium of claim 10 , wherein the overall score for a selected n-gram, of the one or more n-grams, is based on a combination of: a frequency score indicating a frequency the selected n-gram appears in the low scoring content items, the user score corresponding to the low scoring content items the selected n-gram appears in, and a confidence factor for the selected n-gram. | 13. The computer-readable storage medium of claim 10 , wherein the overall score for a selected n-gram, of the one or more n-grams, is based on a combination of: a frequency score indicating a frequency the selected n-gram appears in the low scoring content items, the user score corresponding to the low scoring content items the selected n-gram appears in, and a confidence factor for the selected n-gram. 14. The computer-readable storage medium of claim 13 , wherein the confidence factor for the selected n-gram is based on one or more of: a determination of how well the selected n-gram conforms to an identified set of grammatical rules; how rare portions of the selected n-gram are in an identified language corpus; how users of a social media system have reacted to or interacted with one or more of the content items the selected n-gram was taken from; or any combination thereof. | 0.5 |
8,214,363 | 11 | 13 | 11. The system of claim 10 wherein a bag of words model for an entity class is created by: supplying an entity class name and a plurality of instances belonging to the entity class; submitting each instance to a search engine; extracting and storing a plurality of html documents from the search results for each instance; converting each html document to a text document; extracting well formed sentences from the text documents; stemming non stop words in the well formed sentences; constructing an entity network for the entity class comprised of an entity class name, the plurality of instances, and stemmed non stop words obtained from well formed sentences containing words in the entity network; assigning a likelihood score to each word in the entity network based on the frequency with which that word appeared in the well formed sentences; creating the bag of words model for the entity class using the words in the entity network along with their respective likelihood scores; and refining the bag of words models for the entity classes by reducing likelihood scores of words shared by bag of words models of various entity classes and by removing proper nouns from the models. | 11. The system of claim 10 wherein a bag of words model for an entity class is created by: supplying an entity class name and a plurality of instances belonging to the entity class; submitting each instance to a search engine; extracting and storing a plurality of html documents from the search results for each instance; converting each html document to a text document; extracting well formed sentences from the text documents; stemming non stop words in the well formed sentences; constructing an entity network for the entity class comprised of an entity class name, the plurality of instances, and stemmed non stop words obtained from well formed sentences containing words in the entity network; assigning a likelihood score to each word in the entity network based on the frequency with which that word appeared in the well formed sentences; creating the bag of words model for the entity class using the words in the entity network along with their respective likelihood scores; and refining the bag of words models for the entity classes by reducing likelihood scores of words shared by bag of words models of various entity classes and by removing proper nouns from the models. 13. The system of claim 11 wherein the extracted and stored sampling of snippets from the search results for each query phrase does not exceed ten snippets. | 0.52439 |
8,782,777 | 1 | 6 | 1. A processor-implemented method for securing data stores, the processor-implemented method comprising: associating, by one or more hardware processors, a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, wherein the context object is selected from a plurality of context objects stored in a context object database, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object, and wherein data within the non-contextual data object is generic until said data is matched to a specific context object from the context object database; associating, by the one or more hardware processors, the synthetic context-based object with at least one specific data store in a data structure, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; receiving, by the one or more hardware processors, a string of binary data, wherein the string of binary data describes an ambiguous request from a user for data related to an ambiguous subject-matter; determining, by the one or more hardware processors, a context of the ambiguous request from the user to create a contextual request; associating, by the one or more hardware processors, the context of the contextual request from the user with the synthetic context-based object, wherein said at least one specific data store contains data that is related to the context of the contextual request from the user; receiving, by the one or more hardware processors, the user input that describes the purpose of the ambiguous request; determining, by the one or more hardware processors, the context of the ambiguous request from the user according to a purpose of the ambiguous request; providing, by the one or more hardware processors, the user with access to said at least one specific data store while blocking access to other data stores in the data structure; constructing, by the one or more hardware processors, a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; receiving, from the user, the ambiguous request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and returning, to the user, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library. | 1. A processor-implemented method for securing data stores, the processor-implemented method comprising: associating, by one or more hardware processors, a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, wherein the context object is selected from a plurality of context objects stored in a context object database, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object, and wherein data within the non-contextual data object is generic until said data is matched to a specific context object from the context object database; associating, by the one or more hardware processors, the synthetic context-based object with at least one specific data store in a data structure, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; receiving, by the one or more hardware processors, a string of binary data, wherein the string of binary data describes an ambiguous request from a user for data related to an ambiguous subject-matter; determining, by the one or more hardware processors, a context of the ambiguous request from the user to create a contextual request; associating, by the one or more hardware processors, the context of the contextual request from the user with the synthetic context-based object, wherein said at least one specific data store contains data that is related to the context of the contextual request from the user; receiving, by the one or more hardware processors, the user input that describes the purpose of the ambiguous request; determining, by the one or more hardware processors, the context of the ambiguous request from the user according to a purpose of the ambiguous request; providing, by the one or more hardware processors, the user with access to said at least one specific data store while blocking access to other data stores in the data structure; constructing, by the one or more hardware processors, a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; receiving, from the user, the ambiguous request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and returning, to the user, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library. 6. The processor-implemented method of claim 1 , further comprising: determining, by the one or more hardware processors, the purpose of the ambiguous request by data mining a database that describes an employment history of the user. | 0.724706 |
7,475,093 | 7 | 14 | 7. A computer-implemented method of performing data management, comprising: receiving data representative of a schema; providing a common cache interface for consumers of a cache memory that facilitates dynamic control of the cache memory; caching in the cache memory selected schema components to perform instance validation; shredding the selected schema components into selected tables of metadata and selectively loaded and caching only the most frequently used schema components; loading only selected components of the schema components to perform the validation and during validation loading and caching only the selected components that are used; utilizing a mechanism for cache cleanup that keeps the most frequently used schema components in memory while less frequently used schema components are removed periodically, the mechanism for cache cleanup is driven by memory pressure and based upon a number of Input/Output (I/O) reads to compute a cache entry and total memory required to compute the cache entry, such that if the system is overloaded, schema components will be more aggressively removed from the cache, and wherein the cache is not allowed to keep unused data permanently, and thus, the cache supports forced cleanup; and expressing cost in the same quantities for all caches and implementing aging and cleanup via a costing mechanism, the costing mechanism is based on Central Processing Unit (CPU) and I/O time required to extract type information from the cache, and wherein lifetime of an entry in the cache is defined by usage and cost. | 7. A computer-implemented method of performing data management, comprising: receiving data representative of a schema; providing a common cache interface for consumers of a cache memory that facilitates dynamic control of the cache memory; caching in the cache memory selected schema components to perform instance validation; shredding the selected schema components into selected tables of metadata and selectively loaded and caching only the most frequently used schema components; loading only selected components of the schema components to perform the validation and during validation loading and caching only the selected components that are used; utilizing a mechanism for cache cleanup that keeps the most frequently used schema components in memory while less frequently used schema components are removed periodically, the mechanism for cache cleanup is driven by memory pressure and based upon a number of Input/Output (I/O) reads to compute a cache entry and total memory required to compute the cache entry, such that if the system is overloaded, schema components will be more aggressively removed from the cache, and wherein the cache is not allowed to keep unused data permanently, and thus, the cache supports forced cleanup; and expressing cost in the same quantities for all caches and implementing aging and cleanup via a costing mechanism, the costing mechanism is based on Central Processing Unit (CPU) and I/O time required to extract type information from the cache, and wherein lifetime of an entry in the cache is defined by usage and cost. 14. The method of claim 7 , further comprising an act of managing the cache memory with an internal SQL server memory management architecture. | 0.749117 |
8,538,912 | 19 | 20 | 19. A non-transitory, tangible computer readable medium comprising: an executable computer program code configured to instruct a system to automatically optimize an information integration flow, the executable computer program code comprising the steps of: receiving a tool-specific input file representing a physical information integration flow; parsing the tool-specific input file to identify semantics of the physical information integration flow; creating a tool-agnostic input file containing rich semantics of at least one of datasets, implementations, schema, operators, database management systems, or ETL tools; transforming the tool-agnostic input file into an input directed acyclic graph (DAG); providing the input DAG to a quality objective (QoX) driven optimizer unit; and applying one or more heuristic algorithms to the input DAG to develop an optimum information integration flow design based on the rich semantics. | 19. A non-transitory, tangible computer readable medium comprising: an executable computer program code configured to instruct a system to automatically optimize an information integration flow, the executable computer program code comprising the steps of: receiving a tool-specific input file representing a physical information integration flow; parsing the tool-specific input file to identify semantics of the physical information integration flow; creating a tool-agnostic input file containing rich semantics of at least one of datasets, implementations, schema, operators, database management systems, or ETL tools; transforming the tool-agnostic input file into an input directed acyclic graph (DAG); providing the input DAG to a quality objective (QoX) driven optimizer unit; and applying one or more heuristic algorithms to the input DAG to develop an optimum information integration flow design based on the rich semantics. 20. The non-transitory, tangible computer readable medium of claim 19 , wherein the executable computer program code further comprises the steps of: choosing among one or more specific execution instances related to a dataset to be processed by the physical information integration flow; partitioning a dataset to be processed by the physical information integration flow based on schema properties; and optimizing the physical information integration flow based on implementation properties presented in the tool-agnostic input file. | 0.5 |
9,117,006 | 11 | 13 | 11. A method for recommending keywords, comprising: receiving a set of product information including a product title; extracting and parsing the product title into a set of parsed elements; finding a plurality of candidate keywords corresponding to at least a subset of the set of parsed elements based at least in part on stored predetermined mappings between parsed data and keywords; determining a plurality of composite correlation scores for corresponding ones of the plurality of candidate keywords, wherein determining the plurality of composite correlation scores includes determining a first composite correlation score associated with a first candidate keyword of the plurality of candidate keywords, wherein determining the first composite correlation score associated with the first candidate keyword includes determining an industry index value associated with the first candidate keyword, including: determining a first similarity value between one or more industries associated with the first candidate keyword and one or more industries associated with sets of product information that are relevant to the first candidate keyword; determining a second similarity value between the one or more industries associated with the first candidate keyword and one or more industries of one or more seller users associated with the sets of product information that are relevant to the first candidate keyword; and determining the industry index value associated with the first candidate keyword based at least in part on a combination of the first similarity value and the second similarity value; and sorting at least a subset of the plurality of candidate keywords into a ranked list based on at least a subset of the plurality of composite correlation scores; and selecting a set of one or more keywords to recommend from the plurality of candidate keywords based at least in part on the ranked list. | 11. A method for recommending keywords, comprising: receiving a set of product information including a product title; extracting and parsing the product title into a set of parsed elements; finding a plurality of candidate keywords corresponding to at least a subset of the set of parsed elements based at least in part on stored predetermined mappings between parsed data and keywords; determining a plurality of composite correlation scores for corresponding ones of the plurality of candidate keywords, wherein determining the plurality of composite correlation scores includes determining a first composite correlation score associated with a first candidate keyword of the plurality of candidate keywords, wherein determining the first composite correlation score associated with the first candidate keyword includes determining an industry index value associated with the first candidate keyword, including: determining a first similarity value between one or more industries associated with the first candidate keyword and one or more industries associated with sets of product information that are relevant to the first candidate keyword; determining a second similarity value between the one or more industries associated with the first candidate keyword and one or more industries of one or more seller users associated with the sets of product information that are relevant to the first candidate keyword; and determining the industry index value associated with the first candidate keyword based at least in part on a combination of the first similarity value and the second similarity value; and sorting at least a subset of the plurality of candidate keywords into a ranked list based on at least a subset of the plurality of composite correlation scores; and selecting a set of one or more keywords to recommend from the plurality of candidate keywords based at least in part on the ranked list. 13. The method of claim 11 , wherein at least a subset of the keywords included in the predetermined mappings between parsed data and keywords is determined from historical search logs. | 0.841065 |
9,733,821 | 1 | 7 | 1. A method, comprising: at an electronic device comprising a processor and memory storing instructions for execution by the processor: while the device is operating with a first setting in a first state, detecting, at a first time, a change in settings of the device to change the first setting from the first state to a second state that is different from the first state; while the device is operating with the first setting in the second state, receiving, at a second time that is after the first time, a user input that corresponds to a pattern of user behavior, wherein the user input is a user voice input; in response to receiving the user input: comparing the pattern of user behavior to a plurality of predefined conditions that, when met, indicate that the user is having difficulty with operating the device, wherein a predefined condition of the plurality of predefined conditions includes the user voice input containing one or more predetermined words associated with user difficulty; in accordance with a determination, based on the comparison of the pattern of user behavior to the plurality of predefined conditions, that the device changed the first setting from the first state to the second state within a predetermined time period prior to receiving the user input, restoring the first setting to the first state; and in accordance with a determination, based on the comparison of the pattern of user behavior to the plurality of predefined conditions, that the user is not having difficulty with operating the device, maintaining the first setting in the second state. | 1. A method, comprising: at an electronic device comprising a processor and memory storing instructions for execution by the processor: while the device is operating with a first setting in a first state, detecting, at a first time, a change in settings of the device to change the first setting from the first state to a second state that is different from the first state; while the device is operating with the first setting in the second state, receiving, at a second time that is after the first time, a user input that corresponds to a pattern of user behavior, wherein the user input is a user voice input; in response to receiving the user input: comparing the pattern of user behavior to a plurality of predefined conditions that, when met, indicate that the user is having difficulty with operating the device, wherein a predefined condition of the plurality of predefined conditions includes the user voice input containing one or more predetermined words associated with user difficulty; in accordance with a determination, based on the comparison of the pattern of user behavior to the plurality of predefined conditions, that the device changed the first setting from the first state to the second state within a predetermined time period prior to receiving the user input, restoring the first setting to the first state; and in accordance with a determination, based on the comparison of the pattern of user behavior to the plurality of predefined conditions, that the user is not having difficulty with operating the device, maintaining the first setting in the second state. 7. The method of claim 1 , further comprising: prior to restoring the first setting to the first state, prompting the user with an indication that the first setting has changed from the first state to the second state. | 0.771488 |
9,465,985 | 1 | 7 | 1. A non-transitory computer-readable media comprising instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: receiving a first handwriting input from a user, the first handwriting input comprising a plurality of handwritten strokes distributed along a respective writing direction associated with a handwriting input area of a handwriting input interface; rendering each of the plurality of handwritten strokes in the handwriting input area as the handwritten stroke is provided by the user; starting a respective fading process for the plurality of handwritten strokes of the first handwriting input, wherein during the respective fading process, the rendering of the plurality of handwritten strokes in the handwriting input area becomes increasingly faded; receiving a second handwriting input from the user over a region of the handwriting input area occupied by a faded plurality of handwritten strokes of the first handwriting input; and in response to receiving the second handwriting input: rendering the second handwriting input in the handwriting input area; and clearing all the faded plurality of handwritten strokes of the first handwriting input from the handwriting input area. | 1. A non-transitory computer-readable media comprising instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: receiving a first handwriting input from a user, the first handwriting input comprising a plurality of handwritten strokes distributed along a respective writing direction associated with a handwriting input area of a handwriting input interface; rendering each of the plurality of handwritten strokes in the handwriting input area as the handwritten stroke is provided by the user; starting a respective fading process for the plurality of handwritten strokes of the first handwriting input, wherein during the respective fading process, the rendering of the plurality of handwritten strokes in the handwriting input area becomes increasingly faded; receiving a second handwriting input from the user over a region of the handwriting input area occupied by a faded plurality of handwritten strokes of the first handwriting input; and in response to receiving the second handwriting input: rendering the second handwriting input in the handwriting input area; and clearing all the faded plurality of handwritten strokes of the first handwriting input from the handwriting input area. 7. The media of claim 1 , wherein an end state of the respective fading process for each recognition unit is a state with zero visibility for the recognition unit. | 0.889865 |
8,326,033 | 1 | 8 | 1. A color management module which builds a color transformation workflow for transforming source-side color image data into corresponding destination-side color image data, the color management module comprising: a module library which includes plural module entries each corresponding to a respective function module which implements color processing functionality, wherein each module entry comprises at least a module locator specifying a location for the function module; a profile library which includes plural profile entries each corresponding to a respective source of parameters that characterize a function module, wherein each profile entry comprises at least a profile locator specifying a location for the source of parameters, and a profile interface definition which specifies an interface for supply of the parameters to the function module characterized thereby; wherein for at least some of the module entries of the module library, the module entry further comprises a profile interface definition which specifies an interface for supply of parameters which characterize the function module; a rule library which includes entries for plural external rules and entries for plural internal rules, wherein each such external rule is associated with function modules located by module entries in the module library, and wherein the external rules and the internal rules characterize color transformation workflows of the color management module; an interface constructed to receive factual input including factual input derived from the source-side color image data; and a rule engine constructed to determine a sequence of function modules and sources of parameters from the module library and profile library, respectively, by using the factual input from the interface and the plural internal and external rules in the rule library, wherein the rule engine builds the color transformation workflow from the determined sequence of function modules and sources of parameters. | 1. A color management module which builds a color transformation workflow for transforming source-side color image data into corresponding destination-side color image data, the color management module comprising: a module library which includes plural module entries each corresponding to a respective function module which implements color processing functionality, wherein each module entry comprises at least a module locator specifying a location for the function module; a profile library which includes plural profile entries each corresponding to a respective source of parameters that characterize a function module, wherein each profile entry comprises at least a profile locator specifying a location for the source of parameters, and a profile interface definition which specifies an interface for supply of the parameters to the function module characterized thereby; wherein for at least some of the module entries of the module library, the module entry further comprises a profile interface definition which specifies an interface for supply of parameters which characterize the function module; a rule library which includes entries for plural external rules and entries for plural internal rules, wherein each such external rule is associated with function modules located by module entries in the module library, and wherein the external rules and the internal rules characterize color transformation workflows of the color management module; an interface constructed to receive factual input including factual input derived from the source-side color image data; and a rule engine constructed to determine a sequence of function modules and sources of parameters from the module library and profile library, respectively, by using the factual input from the interface and the plural internal and external rules in the rule library, wherein the rule engine builds the color transformation workflow from the determined sequence of function modules and sources of parameters. 8. A color management module according to claim 1 , wherein the factual input received at the interface includes at least one of color data, environmental information, geographical information, and a desired output. | 0.730576 |
9,384,731 | 1 | 8 | 1. On a computing system comprising a processor, a method of detecting phrase confusion risk in a proposed speech grammar for a computer program, the method comprising: providing, by downloading to a remote computing device, via the processor a speech grammar development tool executable by the remote computing device to receive input of a text representation of each of a plurality of proposed speech grammar terms, for each proposed speech grammar term, convert the text representation to a phonetic representation of the speech grammar term, determine whether a portion of the proposed speech grammar term has a spoken duration below a threshold duration, and if the portion of the proposed speech grammar term has a spoken duration below the threshold duration, then omit the portion from the phonetic representation of the proposed speech grammar term, compare via a speech recognition engine the phonetic representation of the speech grammar term to the phonetic representations of other speech grammar terms using a weighted similarity matrix, and provide an output regarding risk of confusion between two proposed speech grammar terms based upon a comparison by the speech recognition engine of the phonetic representations of the two proposed speech grammar terms; receiving via the processor data regarding incorrect speech grammar term identification; and modifying via the processor speech grammar used by the speech recognition engine, wherein modifying the speech grammar comprises modifying one or more weights in the weighted similarity matrix based upon the data. | 1. On a computing system comprising a processor, a method of detecting phrase confusion risk in a proposed speech grammar for a computer program, the method comprising: providing, by downloading to a remote computing device, via the processor a speech grammar development tool executable by the remote computing device to receive input of a text representation of each of a plurality of proposed speech grammar terms, for each proposed speech grammar term, convert the text representation to a phonetic representation of the speech grammar term, determine whether a portion of the proposed speech grammar term has a spoken duration below a threshold duration, and if the portion of the proposed speech grammar term has a spoken duration below the threshold duration, then omit the portion from the phonetic representation of the proposed speech grammar term, compare via a speech recognition engine the phonetic representation of the speech grammar term to the phonetic representations of other speech grammar terms using a weighted similarity matrix, and provide an output regarding risk of confusion between two proposed speech grammar terms based upon a comparison by the speech recognition engine of the phonetic representations of the two proposed speech grammar terms; receiving via the processor data regarding incorrect speech grammar term identification; and modifying via the processor speech grammar used by the speech recognition engine, wherein modifying the speech grammar comprises modifying one or more weights in the weighted similarity matrix based upon the data. 8. The method of claim 1 , wherein the data regarding incorrect speech grammar term identification comprises data regarding an actual pronunciation for a selected speech grammar term that is different than the expected pronunciation of the selected speech grammar term; and further comprising storing a phonetic representation of the actual pronunciation of the selected speech grammar term. | 0.5 |
8,096,477 | 1 | 5 | 1. A method for collecting information, enriching the information, and binding the information to services, said method comprising: (a) providing a note taking function to allow a user to create a note on a user device, wherein said created note is stored, wherein said note is a shared note, wherein said shared note is accessible by multiple users, wherein said shared note comprises a conversation between said multiple users, and wherein said shared note comprises a chronological list of comments of said conversation; (b) providing a categorizing function to label said note with one or more categories, wherein one or more of said categories of said note is changeable; (c) generating a code to label a physical object, wherein said code is associated with said note; (d) imaging said code, wherein said code is placed on or near said physical object; and (e) linking said physical object with said note based on said imaged code. | 1. A method for collecting information, enriching the information, and binding the information to services, said method comprising: (a) providing a note taking function to allow a user to create a note on a user device, wherein said created note is stored, wherein said note is a shared note, wherein said shared note is accessible by multiple users, wherein said shared note comprises a conversation between said multiple users, and wherein said shared note comprises a chronological list of comments of said conversation; (b) providing a categorizing function to label said note with one or more categories, wherein one or more of said categories of said note is changeable; (c) generating a code to label a physical object, wherein said code is associated with said note; (d) imaging said code, wherein said code is placed on or near said physical object; and (e) linking said physical object with said note based on said imaged code. 5. The method as set forth in claim 1 , wherein said code is a two-dimensional code. | 0.8 |
6,081,261 | 8 | 12 | 8. A method comprising: tracking a location of a pen instrument when the pen instrument is used to modify a physical document, wherein sensors within the pen instrument track the location of the pen instrument; generating signals describing movement of the pen instrument based on the location of the pen instrument; transmitting the signals to a receiving device, wherein the signals are used to modify an electronic document corresponding to the physical document, and further wherein strokes made with the pen instrument are displayed when the electronic document is displayed. | 8. A method comprising: tracking a location of a pen instrument when the pen instrument is used to modify a physical document, wherein sensors within the pen instrument track the location of the pen instrument; generating signals describing movement of the pen instrument based on the location of the pen instrument; transmitting the signals to a receiving device, wherein the signals are used to modify an electronic document corresponding to the physical document, and further wherein strokes made with the pen instrument are displayed when the electronic document is displayed. 12. The method of claim 8 wherein generating electrical signals describing the series of strokes comprises generating the electrical signals with at least one accelerometer and at least one gyroscope. | 0.738903 |
8,881,180 | 9 | 10 | 9. A non-transitory machine-readable storage medium storing instructions that, when executed, cause a device to perform a method comprising: executing a cross-platform application programming interface (API), wherein the cross-platform API includes functionality to support a plurality of applications, wherein execution of one of the plurality of the applications includes interaction between a plurality of entities within a local network, and wherein the cross-platform API implements a request from the application for the device to participate in a unique conversation, wherein the unique conversation is identified by a topic and independent of a unique identifier for entities, the cross-platform API provides the application an abstracted discovery mechanism by which the application causes the device to discover an entity that is accessible on the local network participating in the unique conversation, wherein the abstracted discovery mechanism performs said discovery by: sending a first message according to a first of the plurality of underlying discovery protocols, monitoring for a second message utilizing the first discovery protocol from the entity, determining that the second message has not been received, sending, in response to determining that the second message has not been received, a third message according to a second of the plurality of underlying discovery protocols, and receiving a fourth message utilizing the second discovery protocol from the entity, and the cross-platform API provides the application with a message passing mechanism by which the application causes the device to exchange messages related to the unique conversation with the entity. | 9. A non-transitory machine-readable storage medium storing instructions that, when executed, cause a device to perform a method comprising: executing a cross-platform application programming interface (API), wherein the cross-platform API includes functionality to support a plurality of applications, wherein execution of one of the plurality of the applications includes interaction between a plurality of entities within a local network, and wherein the cross-platform API implements a request from the application for the device to participate in a unique conversation, wherein the unique conversation is identified by a topic and independent of a unique identifier for entities, the cross-platform API provides the application an abstracted discovery mechanism by which the application causes the device to discover an entity that is accessible on the local network participating in the unique conversation, wherein the abstracted discovery mechanism performs said discovery by: sending a first message according to a first of the plurality of underlying discovery protocols, monitoring for a second message utilizing the first discovery protocol from the entity, determining that the second message has not been received, sending, in response to determining that the second message has not been received, a third message according to a second of the plurality of underlying discovery protocols, and receiving a fourth message utilizing the second discovery protocol from the entity, and the cross-platform API provides the application with a message passing mechanism by which the application causes the device to exchange messages related to the unique conversation with the entity. 10. The machine-readable storage medium of claim 9 , wherein message passing mechanism populates values in a static byte array to be sent as an Internet Protocol (IP) packet. | 0.789855 |
9,298,770 | 1 | 6 | 1. A computer-implemented method for generating a repository, the method comprising: receiving a language meta-model to provide a received language meta-model; receiving annotations, each annotation including meta-data; annotating the received language meta-model based on the annotations to provide an annotated language meta-model; determining that a repository has not been previously generated that is associated with the received language meta-model, and in response, processing the annotated language meta-model using a first and a second generator to generate a first and a second repository module, respectively; identifying a dependency of the first repository module on the second repository module; and based on the identified dependency, providing, by the first repository module, one or more functions based on i) the first generator and ii) the second repository module. | 1. A computer-implemented method for generating a repository, the method comprising: receiving a language meta-model to provide a received language meta-model; receiving annotations, each annotation including meta-data; annotating the received language meta-model based on the annotations to provide an annotated language meta-model; determining that a repository has not been previously generated that is associated with the received language meta-model, and in response, processing the annotated language meta-model using a first and a second generator to generate a first and a second repository module, respectively; identifying a dependency of the first repository module on the second repository module; and based on the identified dependency, providing, by the first repository module, one or more functions based on i) the first generator and ii) the second repository module. 6. The method of claim 1 , wherein the one or more functions comprise persisting an instance of a model within the repository, searching instances of models within the repository, updating an instance of a model in the repository, retrieving an instance of a model from the repository, enabling concurrent access to an instance of a model within the repository, and enabling version management between instances of a model within the repository. | 0.5 |
9,305,547 | 15 | 16 | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: identifying an acoustic model, wherein the acoustic model is trained on native speech in a target dialect; and replacing a phoneme in the acoustic model with a modified phoneme, wherein the modified phoneme is a weighted sum of plausible phonemes in a lattice of plausible phonemes associated with a class of a speaker. | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: identifying an acoustic model, wherein the acoustic model is trained on native speech in a target dialect; and replacing a phoneme in the acoustic model with a modified phoneme, wherein the modified phoneme is a weighted sum of plausible phonemes in a lattice of plausible phonemes associated with a class of a speaker. 16. The computer-readable storage device of claim 15 , wherein upon replacing the phoneme in the acoustic model, the acoustic model becomes a Gaussian mixture model. | 0.5 |
8,127,220 | 26 | 27 | 26. The method of claim 22 , wherein determining the scores includes: receiving input from the user, determining a score for each of the linked documents based on the received input, and associating the determined scores for the linked documents with the corresponding links in the identified document. | 26. The method of claim 22 , wherein determining the scores includes: receiving input from the user, determining a score for each of the linked documents based on the received input, and associating the determined scores for the linked documents with the corresponding links in the identified document. 27. The method of claim 26 , wherein determining the score for each of the linked documents includes: for each of the linked documents, comparing one or more words of the received input with a content of the linked document, and determining a score for the linked document based on a degree of match between the one or more words and the content of the linked document. | 0.5 |
9,881,003 | 11 | 14 | 11. An electronic device comprising: at least one processor; and a non-transitory computer-readable storage medium storing instructions executable by the at least one processor for: receiving digital graphic novel content; producing a numerical map that represents an image extracted from the digital graphic novel content; responsive to inputting the numerical map into a first artificial neural network of a machine learning model configured to determine regions of the digital graphic novel content that are likely to include speech bubbles, receiving, from the first artificial neural network, a plurality of candidate regions of the digital graphic novel content that are likely to include speech bubbles; and responsive to in putting the plurality of candidate regions into a second artificial neural network of the machine learning model, receiving, from the second artificial neural network, features of the digital graphic novel content that include a plurality of speech bubbles containing text; generating, based on the features of the digital graphic novel content, contextual information associated with the features of the digital graphic novel content, the contextual information including the text of the plurality of speech bubbles in an intended reading order of the plurality of speech bubbles; and automatically translating, based at least in part on the contextual information, from a first natural language to a second natural language, the text contained in the plurality of speech bubbles to produce translated text. | 11. An electronic device comprising: at least one processor; and a non-transitory computer-readable storage medium storing instructions executable by the at least one processor for: receiving digital graphic novel content; producing a numerical map that represents an image extracted from the digital graphic novel content; responsive to inputting the numerical map into a first artificial neural network of a machine learning model configured to determine regions of the digital graphic novel content that are likely to include speech bubbles, receiving, from the first artificial neural network, a plurality of candidate regions of the digital graphic novel content that are likely to include speech bubbles; and responsive to in putting the plurality of candidate regions into a second artificial neural network of the machine learning model, receiving, from the second artificial neural network, features of the digital graphic novel content that include a plurality of speech bubbles containing text; generating, based on the features of the digital graphic novel content, contextual information associated with the features of the digital graphic novel content, the contextual information including the text of the plurality of speech bubbles in an intended reading order of the plurality of speech bubbles; and automatically translating, based at least in part on the contextual information, from a first natural language to a second natural language, the text contained in the plurality of speech bubbles to produce translated text. 14. The electronic device of claim 11 , wherein the executable computer program code further includes instructions for: creating a packaged digital graphic novel including the digital graphic novel content and presentation metadata, the presentation metadata including the translated text and an indication of the at least one feature of the features of the digital graphic novel to which the translated text corresponds; and providing, by the at least one processor, the packaged digital graphic novel to a reader device that is configured to present the digital graphic novel content in a manner in accordance with the presentation metadata. | 0.5 |
6,134,532 | 78 | 80 | 78. A method of selecting advertisements in a computer including a data storage, comprising: providing a database of electronic advertisements; converting an observed behavior of a user computing device in the computer to a behavior vector; comparing the behavior vector to a plurality of entity vectors, the entity vectors indicative of the electronic advertisements, so as to identify at least one entity vector closely associated with the observed behavior; accessing the electronic database with the identified entity vector, and selecting at least one electronic advertisement to communicate to the user computing device. | 78. A method of selecting advertisements in a computer including a data storage, comprising: providing a database of electronic advertisements; converting an observed behavior of a user computing device in the computer to a behavior vector; comparing the behavior vector to a plurality of entity vectors, the entity vectors indicative of the electronic advertisements, so as to identify at least one entity vector closely associated with the observed behavior; accessing the electronic database with the identified entity vector, and selecting at least one electronic advertisement to communicate to the user computing device. 80. The method as defined in claim 78, wherein the selecting includes selecting the entity vector based upon a presentation delivery schedule. | 0.767213 |
8,671,364 | 1 | 21 | 1. An apparatus, comprising: a logic device; and an information visualization application operative on the logic device, the information visualization application comprising a multivariable presentation component arranged to generate a multivariable decomposition visualization to present hierarchical information for a response variable and multiple reporting variables defined for the response variable in a single user interface view, the multivariable decomposition visualization comprising multiple graphical user interface (GUI) elements each representing a reporting variable value of multiple reporting variables for multiple hierarchical levels, with a GUI element of a reporting variable value of a reporting variable of a hierarchical level selectable for decomposition into multiple GUI elements representing reporting variable values of a different reporting variable for a different hierarchical level, the selectable GUI element of the hierarchical level positioned adjacent to the decomposed GUI elements of the different hierarchical level when the selectable GUI element is selected for decomposition. | 1. An apparatus, comprising: a logic device; and an information visualization application operative on the logic device, the information visualization application comprising a multivariable presentation component arranged to generate a multivariable decomposition visualization to present hierarchical information for a response variable and multiple reporting variables defined for the response variable in a single user interface view, the multivariable decomposition visualization comprising multiple graphical user interface (GUI) elements each representing a reporting variable value of multiple reporting variables for multiple hierarchical levels, with a GUI element of a reporting variable value of a reporting variable of a hierarchical level selectable for decomposition into multiple GUI elements representing reporting variable values of a different reporting variable for a different hierarchical level, the selectable GUI element of the hierarchical level positioned adjacent to the decomposed GUI elements of the different hierarchical level when the selectable GUI element is selected for decomposition. 21. The apparatus of claim 1 , the multivariable presentation component operative to receive a trace path control directive, and highlight a hierarchical path of reporting variable values for different reporting variables for an information pipe for the multivariable decomposition visualization in response to the trace path control directive. | 0.733333 |
9,692,865 | 12 | 18 | 12. A method of controlling a mobile terminal having a display and a controller, the method comprising: activating, via the controller, a mode for voice recognition in response to a touch input to a soft button displayed on the display or to a hard button on the mobile terminal; receiving, via the controller, a first voice input associated with an executable menu relating operation of the mobile terminal; displaying, via the controller, an indicator on the display indicating the first voice input is being recognized by the mobile terminal; determining, via the controller, a meaning of a voice command in the first voice input based on information stored in the at least one database (DB); displaying, via the controller, information corresponding to the determined meaning; receiving, via the controller, a second voice input associated with a user's confirmation about the displayed information; if the received second voice input matches an affirmative received response, executing, via the controller a menu relating operation corresponding to the displayed information; if the received second voice input matches a negative received response, performing, via the controller, a learning process based on a third voice input for learning the meaning of the voice command in the first voice input and executing a menu relating operation corresponding to the learned meaning; and updating, via the controller, the at least one database (DB) to store the learned meaning according to the third voice input. | 12. A method of controlling a mobile terminal having a display and a controller, the method comprising: activating, via the controller, a mode for voice recognition in response to a touch input to a soft button displayed on the display or to a hard button on the mobile terminal; receiving, via the controller, a first voice input associated with an executable menu relating operation of the mobile terminal; displaying, via the controller, an indicator on the display indicating the first voice input is being recognized by the mobile terminal; determining, via the controller, a meaning of a voice command in the first voice input based on information stored in the at least one database (DB); displaying, via the controller, information corresponding to the determined meaning; receiving, via the controller, a second voice input associated with a user's confirmation about the displayed information; if the received second voice input matches an affirmative received response, executing, via the controller a menu relating operation corresponding to the displayed information; if the received second voice input matches a negative received response, performing, via the controller, a learning process based on a third voice input for learning the meaning of the voice command in the first voice input and executing a menu relating operation corresponding to the learned meaning; and updating, via the controller, the at least one database (DB) to store the learned meaning according to the third voice input. 18. The method of claim 12 , further comprising: executing a call relating operation only if there is a single contact in a phonebook that matches the voice command in the first voice input; if there is no single contact that matches the voice command of the first voice input, displaying a plurality of candidates that is analyzed based on the voice command; and displaying a selected candidate according to a user's input when the user's input is received while displaying the plurality of candidates. | 0.5 |
8,209,663 | 1 | 7 | 1. A method comprising: receiving an indication of at least one set operation; receiving an indication of a selected group of entities, the selected group comprising a plurality of entities, the entities: being associated with one or more properties, including at least one entity from a first object, and including at least one entity from a second object; determining, using a processor, a group of properties for the plurality of entities, where the group of properties is at least one of: common properties associated with each of the entities of the selected group of entities, properties associated with at least one of the entities of the selected group of entities, or properties associated with only one of the entities of the selected group of entities; providing a representation of the group of properties; receiving, an instruction to perform an edit operation on at least one of the properties of the group of properties; and applying the edit operation to the entities associated with the at least one property. | 1. A method comprising: receiving an indication of at least one set operation; receiving an indication of a selected group of entities, the selected group comprising a plurality of entities, the entities: being associated with one or more properties, including at least one entity from a first object, and including at least one entity from a second object; determining, using a processor, a group of properties for the plurality of entities, where the group of properties is at least one of: common properties associated with each of the entities of the selected group of entities, properties associated with at least one of the entities of the selected group of entities, or properties associated with only one of the entities of the selected group of entities; providing a representation of the group of properties; receiving, an instruction to perform an edit operation on at least one of the properties of the group of properties; and applying the edit operation to the entities associated with the at least one property. 7. The method of claim 1 , wherein the first and second objects include respective models in a software environment. | 0.610738 |
9,056,256 | 1 | 5 | 1. A method comprising: capturing, using one or more computing devices, actions taken by a user within an online environment; wherein capturing actions includes at least one of: determining which type of items are purchased online by the user; determining which type of computer programs are downloaded and/or used by the user; determining topics reflected in electronic communications of the user; determining topics reflected in items purchased online by the user; determining to which online social communities the user belongs; determining interests reflected in comments made by the user in online social applications; determining persons to whom the user is socially connected in online social applications; capturing how an avatar of the user interacts with one or more other characters in the online environment; randomly inserting questions that relate to play personality with other questions presented to the user within an online game environment; capturing one or more images of the user as the user engages in an activity within the online environment; detecting eye movement of the user as the user engages in an activity within the online environment; detecting pupil size changes of the user as the user engages in an activity within the online environment; or monitoring how the user makes purchases at or interacts with virtual stores or venues; wherein capturing actions further comprises presenting an online assessment that includes a series of questions designed to assess which play type, of a plurality of play types, satisfies the user's need for play; automatically determining a play personality of the user based, at least in part, on the actions of the user that are captured using the one or more computing devices; wherein automatically determining the play personality of the user comprises: estimating a degree to which each of the plurality of play types satisfies the user's need for play; and determining that one or more particular play types, of the plurality of play types, best satisfy the user's need for play; wherein the plurality of play types includes two or more of: Object, Pretend, Social, Rough and Tumble, Body, Exploratory, Celebratory, Competitive, Ritual, Narrative, Fantasy or Games/Gaming; storing play personality data that reflects the play personality of the user; and wherein the method is performed by one or more computing devices. | 1. A method comprising: capturing, using one or more computing devices, actions taken by a user within an online environment; wherein capturing actions includes at least one of: determining which type of items are purchased online by the user; determining which type of computer programs are downloaded and/or used by the user; determining topics reflected in electronic communications of the user; determining topics reflected in items purchased online by the user; determining to which online social communities the user belongs; determining interests reflected in comments made by the user in online social applications; determining persons to whom the user is socially connected in online social applications; capturing how an avatar of the user interacts with one or more other characters in the online environment; randomly inserting questions that relate to play personality with other questions presented to the user within an online game environment; capturing one or more images of the user as the user engages in an activity within the online environment; detecting eye movement of the user as the user engages in an activity within the online environment; detecting pupil size changes of the user as the user engages in an activity within the online environment; or monitoring how the user makes purchases at or interacts with virtual stores or venues; wherein capturing actions further comprises presenting an online assessment that includes a series of questions designed to assess which play type, of a plurality of play types, satisfies the user's need for play; automatically determining a play personality of the user based, at least in part, on the actions of the user that are captured using the one or more computing devices; wherein automatically determining the play personality of the user comprises: estimating a degree to which each of the plurality of play types satisfies the user's need for play; and determining that one or more particular play types, of the plurality of play types, best satisfy the user's need for play; wherein the plurality of play types includes two or more of: Object, Pretend, Social, Rough and Tumble, Body, Exploratory, Celebratory, Competitive, Ritual, Narrative, Fantasy or Games/Gaming; storing play personality data that reflects the play personality of the user; and wherein the method is performed by one or more computing devices. 5. The method of claim 1 wherein: capturing actions taken by the user includes monitoring actions of the user within an online game environment; and automatically determining a play personality of the user is based, at least in part, on the actions of the user within the online game environment. | 0.568513 |
9,383,911 | 11 | 13 | 11. One or more storage media storing instructions which, when executed by one or more processors, cause: presenting a window comprising at least: a graphical presentation of contents of a document, one or more graphical user interface controls configured to receive edits to the contents of the document, and a save interface comprising an editable text box; wherein the save interface is configured to permit save operations on the document to different locations without creating a modal window for the save operations; while displaying the save interface in the application window, receiving, via the one or more graphical user interface controls, one or more edit commands to add to or modify the contents of the document; in response to the one or more edit commands, changing the graphical presentation of the contents of the document and changing an appearance of the entire save interface to indicate that the document contains unsaved modifications; receiving, in the save interface, input in the editable text box that indicates a location at which to save the document; in response to termination of the input that specifies a location at which to save the document, storing the document at the location, wherein termination of the input that specifies a location at which to save the document is a change in focus away from the editable text box. | 11. One or more storage media storing instructions which, when executed by one or more processors, cause: presenting a window comprising at least: a graphical presentation of contents of a document, one or more graphical user interface controls configured to receive edits to the contents of the document, and a save interface comprising an editable text box; wherein the save interface is configured to permit save operations on the document to different locations without creating a modal window for the save operations; while displaying the save interface in the application window, receiving, via the one or more graphical user interface controls, one or more edit commands to add to or modify the contents of the document; in response to the one or more edit commands, changing the graphical presentation of the contents of the document and changing an appearance of the entire save interface to indicate that the document contains unsaved modifications; receiving, in the save interface, input in the editable text box that indicates a location at which to save the document; in response to termination of the input that specifies a location at which to save the document, storing the document at the location, wherein termination of the input that specifies a location at which to save the document is a change in focus away from the editable text box. 13. The one or more storage media of claim 11 , wherein changing the appearance of the entire save interface comprises oscillating between two different appearances for the save interface, wherein the first appearance of the two different appearances comprises a glow effect around the editable text box for specifying the location in the save interface, wherein the second appearance of the two different appearances does not comprise the glow effect around the editable text box. | 0.734547 |
8,423,359 | 30 | 31 | 30. A system comprising: a server system that includes one or more machine-readable storage devices that are programmed with instructions that, when executed by one or more programmable processors, receive information that identifies when queries that include a particular word were received, wherein the time when the queries were received is a time of transmission of the queries by a plurality of computerized devices to a search engine system, or a time of audio recordings of the queries; and means for modifying a speech recognition model to revise occurrence data for the particular word based on when the particular word was received in queries so that a first occurrence of the particular word in a recent query of the queries more strongly influences the occurrence data for the particular word than a second occurrence of the particular word in a second query of the queries based on the information identifying that the recent query was received after the second query. | 30. A system comprising: a server system that includes one or more machine-readable storage devices that are programmed with instructions that, when executed by one or more programmable processors, receive information that identifies when queries that include a particular word were received, wherein the time when the queries were received is a time of transmission of the queries by a plurality of computerized devices to a search engine system, or a time of audio recordings of the queries; and means for modifying a speech recognition model to revise occurrence data for the particular word based on when the particular word was received in queries so that a first occurrence of the particular word in a recent query of the queries more strongly influences the occurrence data for the particular word than a second occurrence of the particular word in a second query of the queries based on the information identifying that the recent query was received after the second query. 31. The system of claim 30 , further comprising a search engine system that includes one or more machine-readable storage devices that are programmed for execution by one or more programmable processors to receive the queries as search requests. | 0.5 |
8,819,021 | 4 | 6 | 4. A method comprising: inputting a user specified criterion which correlates to high relevance; preparing a data set for processing; de-duplicating the data set; extracting the data set; determining, prior to indexing the data set, where to prioritize the data set in a processing queue by evaluating how well the data set matches the user specified criterion relative to other data sets that have been processed based on inputs received from users relating to their review of the already processed other electronic data sets; having a user do a complete or sample assessment of initially processed data sets that outranks the initial user specified criterion in the event of conflict; permitting a user to override prioritization of specific data sets or its schemes for determining prioritization; indexing the data set; and iteratively repeating the process based on user feedback and the desired quality and quantity of relevant data until all data sets have been exhausted. | 4. A method comprising: inputting a user specified criterion which correlates to high relevance; preparing a data set for processing; de-duplicating the data set; extracting the data set; determining, prior to indexing the data set, where to prioritize the data set in a processing queue by evaluating how well the data set matches the user specified criterion relative to other data sets that have been processed based on inputs received from users relating to their review of the already processed other electronic data sets; having a user do a complete or sample assessment of initially processed data sets that outranks the initial user specified criterion in the event of conflict; permitting a user to override prioritization of specific data sets or its schemes for determining prioritization; indexing the data set; and iteratively repeating the process based on user feedback and the desired quality and quantity of relevant data until all data sets have been exhausted. 6. The method of claim 4 , wherein said preparing a data set for processing comprises: preparing interconnected sets of data that are present on the same media or hardware, are associated with the same person(s) or topic(s), or were collected together. | 0.724289 |
8,909,591 | 9 | 12 | 9. A processing system for identifying business listings, the processing system comprising: one or more computing devices, each of the one or more computing devices having one or more processors; and a memory, coupled to the one or more processors, for storing business listings; wherein the one or more computing devices is configured to: determine a first frequency value of a business listing characteristic within a first plurality of business listings received from a first source, the first plurality of business listings being associated with a particular business listing context; determine a second frequency value of the business listing characteristic within a second plurality of business listings received from a second source, the second plurality of business listings being associated with the particular business listing context; determine a frequency differential between the first frequency value and the second frequency value; in response to the frequency differential exceeding a threshold differential, identify the business listing characteristic as a differential characteristic; and identify a particular business listing of the plurality of business listings as a spam listing using the differential characteristic. | 9. A processing system for identifying business listings, the processing system comprising: one or more computing devices, each of the one or more computing devices having one or more processors; and a memory, coupled to the one or more processors, for storing business listings; wherein the one or more computing devices is configured to: determine a first frequency value of a business listing characteristic within a first plurality of business listings received from a first source, the first plurality of business listings being associated with a particular business listing context; determine a second frequency value of the business listing characteristic within a second plurality of business listings received from a second source, the second plurality of business listings being associated with the particular business listing context; determine a frequency differential between the first frequency value and the second frequency value; in response to the frequency differential exceeding a threshold differential, identify the business listing characteristic as a differential characteristic; and identify a particular business listing of the plurality of business listings as a spam listing using the differential characteristic. 12. The processing system of claim 9 , wherein the business listing characteristic is at least one of a title length, a text term, a phone number, and an address. | 0.749226 |
8,600,736 | 1 | 10 | 1. A method of operating a computer to perform linguistic analysis, comprising the steps of: splitting an input text into words and sentences; for each sentence, comparing phrases in each sentence with known phrases stored in a database, as follows: for each word in the sentence, comparing a value thereof and values of the words following it with values of words of stored phrases; in the event a match is found between the value of at least two consecutive words and the value of words of a stored phrase, labelling the matched at least two consecutive words with an overphrase that describes the matched value; after a penultimate word has been compared, recasting the sentence by replacing the matched phrases by respective overphrases; and then repeating the step of comparing phrases with the recast sentence until there is no further recasting by the step of using the overphrase in the comparison as a word until there is no further match found. | 1. A method of operating a computer to perform linguistic analysis, comprising the steps of: splitting an input text into words and sentences; for each sentence, comparing phrases in each sentence with known phrases stored in a database, as follows: for each word in the sentence, comparing a value thereof and values of the words following it with values of words of stored phrases; in the event a match is found between the value of at least two consecutive words and the value of words of a stored phrase, labelling the matched at least two consecutive words with an overphrase that describes the matched value; after a penultimate word has been compared, recasting the sentence by replacing the matched phrases by respective overphrases; and then repeating the step of comparing phrases with the recast sentence until there is no further recasting by the step of using the overphrase in the comparison as a word until there is no further match found. 10. A method according to claim 1 , wherein phrases and words in the input text are converted to their overphrases according to a predetermined conversion order associated with the phrases and words. | 0.683121 |
9,122,681 | 1 | 4 | 1. A system for classifying documents in a document collection into one or more classes or subclasses using a continuous active learning process for the purpose of conducting e-discovery in legal proceedings, the system comprising: a memory adapted to store the document collection; a computing device coupled to the memory, the computing device comprising: a display; a physical input interface; a processor coupled to the display and the input interface, the processor being adapted to: generate a document information profile for the documents in the collection, each document information profile corresponding to a particular document and representing features of that document; select a document from the collection to present to a human reviewer; display a portion of the selected document on the display; receive, through the input interface, one or more user coding decisions associated with the selected document; for at least one class or subclass, incrementally update a classifier using at least one received user coding decision and the document information profile for the document associated with the at least one received user coding decision; for at least one classifier, compute a set of scores for the documents in the collection by applying the at least one classifier to the document information profile associated with each document to be scored; for at least one class or subclass, estimate the number of documents in that class or subclass by fitting the scores calculated using the classifier that corresponds to that class or subclass to a standard distribution; validate at least one of the estimates using the received user coding decisions; in response to determining that one of the estimates is valid, indicate, on the display or the input interface, that the review is complete for the class or subclass associated with that estimate; classify documents in the document collection into the classes or subclasses using the scores and the received user coding decisions; and repeat the steps of selecting a document, receiving user coding decisions associated with the selected document, calculating a classifier, computing a set of scores, estimating the number of documents in at least one class or subclass, and validating at least one estimate. | 1. A system for classifying documents in a document collection into one or more classes or subclasses using a continuous active learning process for the purpose of conducting e-discovery in legal proceedings, the system comprising: a memory adapted to store the document collection; a computing device coupled to the memory, the computing device comprising: a display; a physical input interface; a processor coupled to the display and the input interface, the processor being adapted to: generate a document information profile for the documents in the collection, each document information profile corresponding to a particular document and representing features of that document; select a document from the collection to present to a human reviewer; display a portion of the selected document on the display; receive, through the input interface, one or more user coding decisions associated with the selected document; for at least one class or subclass, incrementally update a classifier using at least one received user coding decision and the document information profile for the document associated with the at least one received user coding decision; for at least one classifier, compute a set of scores for the documents in the collection by applying the at least one classifier to the document information profile associated with each document to be scored; for at least one class or subclass, estimate the number of documents in that class or subclass by fitting the scores calculated using the classifier that corresponds to that class or subclass to a standard distribution; validate at least one of the estimates using the received user coding decisions; in response to determining that one of the estimates is valid, indicate, on the display or the input interface, that the review is complete for the class or subclass associated with that estimate; classify documents in the document collection into the classes or subclasses using the scores and the received user coding decisions; and repeat the steps of selecting a document, receiving user coding decisions associated with the selected document, calculating a classifier, computing a set of scores, estimating the number of documents in at least one class or subclass, and validating at least one estimate. 4. The system of claim 1 , wherein the classifier is updated using a gradient ascent or descent technique. | 0.822148 |
9,444,773 | 10 | 15 | 10. A method comprising based on information in one or more documents, automatically inferring, by one or more computers, abilities of users associated with the documents to perform language translations, the abilities including language capabilities and non-language capabilities; maintaining a database of the abilities of the respective users; receiving, by at least one of the computers, an indication of a language translation to be performed for a user; in response to the indication of the language translation to be performed for the user, querying, by at least one of the computers, the database to identify one or more candidate users to perform the language translation; and determining, by the database, the one or more candidate users to perform the language translation using the language capabilities and non-language capabilities of the one or more candidate users. | 10. A method comprising based on information in one or more documents, automatically inferring, by one or more computers, abilities of users associated with the documents to perform language translations, the abilities including language capabilities and non-language capabilities; maintaining a database of the abilities of the respective users; receiving, by at least one of the computers, an indication of a language translation to be performed for a user; in response to the indication of the language translation to be performed for the user, querying, by at least one of the computers, the database to identify one or more candidate users to perform the language translation; and determining, by the database, the one or more candidate users to perform the language translation using the language capabilities and non-language capabilities of the one or more candidate users. 15. The method of claim 10 , wherein: receiving, by at least one of the computers, the indication of the language translation to be performed for the user comprises receiving the indication of the language translation to be performed for the user and a technical skill required for the language translation; and determining, by the database, the one or more candidate users to perform the language translation using the language capabilities and non-language capabilities of the one or more candidate users comprises determining the one or more candidate users to perform the language translation using the technical skills of the one or more candidate users. | 0.5 |
7,707,168 | 14 | 15 | 14. The system according to claim 13 , wherein said search manager formulates said task request based on at least one of said data source owner and said data source types. | 14. The system according to claim 13 , wherein said search manager formulates said task request based on at least one of said data source owner and said data source types. 15. The system according to claim 14 , wherein said data source owner uses said configure element to configure said data source types. | 0.5 |
8,631,048 | 1 | 2 | 1. A method of incorporating one or more sets of new data and adapting existing data based on the new data, comprising: extracting, using an extraction module, a data model from a new data set, wherein the extraction module comprises instructions stored on at least one computer-readable medium that are executable by a processor; generating, using the extraction module, one or more sets of schema ontology assertions based on the extracted data model, wherein a common schema alignment ontology is used to represent the extracted data model; and aligning, using an alignment module, the extracted data model represented using the common schema alignment ontology with at least one existing aligned ontology, wherein the extracted data model is aligned with the at least one existing aligned ontology based on one or more ontology equivalence assertions configured to link schema ontology assertions with the existing aligned ontology, wherein the alignment module comprises one or more alignment agents having been trained, using one or more training sets, to identify the one or more ontology equivalence assertions, and wherein the alignment module comprises instructions stored on the at least one computer-readable medium that are executable by the processor; wherein aligning the extracted data model with the at least one existing aligned ontology comprises: determining the existence of one or more semantically equivalent elements contained within the schema ontology assertions; generating one or more new schema ontology assertions based on the schema ontology assertions containing the semantically equivalent elements, wherein the one or more new schema ontology assertions comprise new assertions relating elements found in the schema ontology assertions containing the semantically equivalent elements, and wherein the one or more new schema ontology assertions were not previously included within either the one or more sets of schema ontology assertions or the existing aligned ontology; and generating a set of aligned ontology assertions based on the one or more new schema ontology assertions. | 1. A method of incorporating one or more sets of new data and adapting existing data based on the new data, comprising: extracting, using an extraction module, a data model from a new data set, wherein the extraction module comprises instructions stored on at least one computer-readable medium that are executable by a processor; generating, using the extraction module, one or more sets of schema ontology assertions based on the extracted data model, wherein a common schema alignment ontology is used to represent the extracted data model; and aligning, using an alignment module, the extracted data model represented using the common schema alignment ontology with at least one existing aligned ontology, wherein the extracted data model is aligned with the at least one existing aligned ontology based on one or more ontology equivalence assertions configured to link schema ontology assertions with the existing aligned ontology, wherein the alignment module comprises one or more alignment agents having been trained, using one or more training sets, to identify the one or more ontology equivalence assertions, and wherein the alignment module comprises instructions stored on the at least one computer-readable medium that are executable by the processor; wherein aligning the extracted data model with the at least one existing aligned ontology comprises: determining the existence of one or more semantically equivalent elements contained within the schema ontology assertions; generating one or more new schema ontology assertions based on the schema ontology assertions containing the semantically equivalent elements, wherein the one or more new schema ontology assertions comprise new assertions relating elements found in the schema ontology assertions containing the semantically equivalent elements, and wherein the one or more new schema ontology assertions were not previously included within either the one or more sets of schema ontology assertions or the existing aligned ontology; and generating a set of aligned ontology assertions based on the one or more new schema ontology assertions. 2. The method of claim 1 , wherein the one or more new sets of data comprise a plurality of new data sets, and wherein: extracting a data model from a new data set comprises extracting a plurality of data models, wherein each of the plurality of data models corresponds to one of the plurality of new data sets; generating one or more sets of schema ontology assertions based on the extracted data model comprises generating one or more ontology assertions based on each of the plurality of data models using the common schema alignment ontology; the method further comprises aligning, using the alignment module, the separate generated schema ontology assertions to generate a set of interschema aligned ontology assertions; and aligning the extracted data model represented using the common schema alignment ontology with at least one existing aligned ontology comprises aligning the set of interschema aligned ontology assertions with the at least one existing aligned ontology based on one or more equivalent elements identified between the interschema aligned ontology assertions and the at least one existing aligned ontology. | 0.5 |
9,847,964 | 13 | 14 | 13. The non-transitory, computer-readable medium of claim 11 , the instructions executable by the processor to configure the joining device to: receive a successful pair message from the remote service, the successful pair message indicating that: the joining device has been authenticated to the remote service within an expected period of time; and the remote service has added the joining device to a list of devices paired with an account that is associated with a structure in which the joining device is to be added. | 13. The non-transitory, computer-readable medium of claim 11 , the instructions executable by the processor to configure the joining device to: receive a successful pair message from the remote service, the successful pair message indicating that: the joining device has been authenticated to the remote service within an expected period of time; and the remote service has added the joining device to a list of devices paired with an account that is associated with a structure in which the joining device is to be added. 14. The non-transitory, computer-readable medium of claim 13 , the instructions executable by the processor to configure the joining device to: upon receipt of the successful pair message, store the received service configuration details in persistent memory; and use the persistently-stored service configuration details to communicate with the remote service unless the remote service updates the persistently-stored service configuration details. | 0.5 |
9,436,674 | 13 | 14 | 13. The computer program product of claim 9 , wherein each sentiment value comprises a sentiment polarity and magnitude. | 13. The computer program product of claim 9 , wherein each sentiment value comprises a sentiment polarity and magnitude. 14. The computer program product of claim 13 , wherein the at least one processor is further configured to sort entities in a document by sentiment. | 0.5 |
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