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9,350,623 | 14 | 17 |
14. A system for automated deployment of a multi-component computer environment, the system comprising: at least one physical deployment machine of servers and virtual machines operable on servers; a graphical user interface module to enable a user to design a desired topology of components including deployed products, target physical and virtual deployment machines, and the connections between them in the multi-component computer environment; a deployment processing module to convert the desired topology to a set of deployment actions represented in a workflow script onto one or more virtual machines to enable a proof of concept of the desired topology; and an orchestration engine to use the set of deployment actions in the workflow script to execute an automated deployment of the multi-component computer environment on the at least one physical deployment machine, wherein the orchestration engine further: performs a set of pre-deployment validations of component specifications; deploys the-components and virtual appliances; integrates the components and virtual appliances; and validates the integration of the components and virtual appliances in the multi-component computer system.
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14. A system for automated deployment of a multi-component computer environment, the system comprising: at least one physical deployment machine of servers and virtual machines operable on servers; a graphical user interface module to enable a user to design a desired topology of components including deployed products, target physical and virtual deployment machines, and the connections between them in the multi-component computer environment; a deployment processing module to convert the desired topology to a set of deployment actions represented in a workflow script onto one or more virtual machines to enable a proof of concept of the desired topology; and an orchestration engine to use the set of deployment actions in the workflow script to execute an automated deployment of the multi-component computer environment on the at least one physical deployment machine, wherein the orchestration engine further: performs a set of pre-deployment validations of component specifications; deploys the-components and virtual appliances; integrates the components and virtual appliances; and validates the integration of the components and virtual appliances in the multi-component computer system. 17. The system of claim 14 , wherein the deployment processing module reports the execution progress of the automated deployment of the multi-component computer environment back to the graphical user interface module in order to provide graphic execution feedback.
| 0.5 |
8,505,105 | 49 | 50 |
49. A system according to claim 30 , further comprising: means for tracking information related to the deal.
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49. A system according to claim 30 , further comprising: means for tracking information related to the deal. 50. A system according to claim 49 , wherein the information includes at least one of a contact list including contact information for each user on the list, deal dates, billing codes, wire instructions, deal definitions, and an audit log of user activity on the grid, and a status report presented as news feed of any changes made to the grid.
| 0.5 |
9,043,423 | 1 | 8 |
1. A method comprising: maintaining information characterizing one or more of an appearance, a voice, or a behavior of a person; receiving information indicative of (a) content that is to be part of a message to be delivered to a recipient on behalf of the person, (b) a relationship between the person and the recipient, and (c) a delivery time for delivery of the message, in which the content, the delivery time, or both are not present in the received information; inferring one or more of (i) the content based on the received information indicative of the content, including inferring at least some of the content at the delivery time, (ii) an identity of the recipient based on the received information indicative of the relationship between the person and the recipient, or (iii) the delivery time based on the received information indicative of the delivery time; and delivering the message to the recipient at the delivery time on behalf of the person, the message including the content, the delivering including providing a customized natural language response to an input received from the recipient, the providing of the response comprising using a digital representation of the person generated based on one or more of the appearance, the voice, or the behavior of the person.
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1. A method comprising: maintaining information characterizing one or more of an appearance, a voice, or a behavior of a person; receiving information indicative of (a) content that is to be part of a message to be delivered to a recipient on behalf of the person, (b) a relationship between the person and the recipient, and (c) a delivery time for delivery of the message, in which the content, the delivery time, or both are not present in the received information; inferring one or more of (i) the content based on the received information indicative of the content, including inferring at least some of the content at the delivery time, (ii) an identity of the recipient based on the received information indicative of the relationship between the person and the recipient, or (iii) the delivery time based on the received information indicative of the delivery time; and delivering the message to the recipient at the delivery time on behalf of the person, the message including the content, the delivering including providing a customized natural language response to an input received from the recipient, the providing of the response comprising using a digital representation of the person generated based on one or more of the appearance, the voice, or the behavior of the person. 8. The method of claim 1 , in which receiving the information indicative of an identity of the recipient includes receiving a specification of the identity of the recipient.
| 0.725397 |
7,836,436 | 18 | 21 |
18. A compiler for compiling instructions in an asynchronous transactional messaging language, said compiler comprising: a code generator for: compiling said instructions in said asynchronous transactional messaging language for providing compilation units, wherein said act of compiling comprises: iteratively compiling said instructions a predetermined number of times; and said predetermined number is determined in accordance with a level of dependency of variables within said asynchronous transactional messaging language; organizing said compilation units into a tree; and traversing said tree in depth first traversal order; and a transformer for transforming selected encountered compilation units into corresponding second instructions compatible with web services.
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18. A compiler for compiling instructions in an asynchronous transactional messaging language, said compiler comprising: a code generator for: compiling said instructions in said asynchronous transactional messaging language for providing compilation units, wherein said act of compiling comprises: iteratively compiling said instructions a predetermined number of times; and said predetermined number is determined in accordance with a level of dependency of variables within said asynchronous transactional messaging language; organizing said compilation units into a tree; and traversing said tree in depth first traversal order; and a transformer for transforming selected encountered compilation units into corresponding second instructions compatible with web services. 21. A compiler in accordance with claim 18 , wherein: upon encountering all types associated with a service, said transformer transforms method message types and class based port types appearing in service link types in said asynchronous transactional messaging language into corresponding types compatible with said web services; and upon encountering subsequent services, said transformer transforms method based messages and class based ports in said asynchronous transactional messaging language into types compatible with said web services.
| 0.5 |
9,058,808 | 12 | 13 |
12. The system of claim 11 , wherein each identified word in the identified words is assigned a respective time stamp.
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12. The system of claim 11 , wherein each identified word in the identified words is assigned a respective time stamp. 13. The system of claim 12 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, result in operations comprising adding an identified word of the identified words to the modified dynamic language model based on the respective time stamp assigned to the identified word.
| 0.5 |
9,251,297 | 4 | 5 |
4. A system comprising: one or more computer processors; a computer-readable storage medium having stored therein instructions which, when executed by the one or more computer processors, cause the one or more computer processors to: receive a comment to a note that is published on a first website, the first note published according to an initial audience level that defines restrictions relating to users that can access the note, wherein only a first set of users can access the note while the note is published according to the initial audience level; determine, based on the comment, an updated audience level for the note, the updated audience level defining updated restrictions relating to users that can access the note; and publish the note according to the updated audience level, wherein only a second set of users can access the note while the note is published according to the second audience level and the first set of users and the second set of users are different.
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4. A system comprising: one or more computer processors; a computer-readable storage medium having stored therein instructions which, when executed by the one or more computer processors, cause the one or more computer processors to: receive a comment to a note that is published on a first website, the first note published according to an initial audience level that defines restrictions relating to users that can access the note, wherein only a first set of users can access the note while the note is published according to the initial audience level; determine, based on the comment, an updated audience level for the note, the updated audience level defining updated restrictions relating to users that can access the note; and publish the note according to the updated audience level, wherein only a second set of users can access the note while the note is published according to the second audience level and the first set of users and the second set of users are different. 5. The system of claim 4 , wherein the note comprises at least one of text, audio media, visual media, audio-visual media, recorded data, a weblink, or a pointer to an information source.
| 0.5 |
7,831,580 | 6 | 17 |
6. The process of claim 1 , wherein the step (g) further comprises the step of: prompting the second user to add a message for the first user.
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6. The process of claim 1 , wherein the step (g) further comprises the step of: prompting the second user to add a message for the first user. 17. The computer readable storage medium of claim 6 , wherein the step (g) further comprises the step of: prompting the second user to publish the chosen listed knowledge object.
| 0.5 |
8,447,785 | 16 | 23 |
16. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of: a server analyzing portions of data, including a particular portion of data, that are stored in an unstructured database column in a database to determine whether or not the data includes marked up text-, wherein, prior to analyzing the portions of data, the portions of data, as stored, were not defined as marked up text; without changing the particular portion of data that is stored in the unstructured database column, the server determining that the particular portion contains a marked up text node is a descendant of an ancestor node, and the server storing a location of the marked up text node and an indication that the marked up text node is a descendant of the ancestor node; the server receiving an expression that specifies a value and a hierarchical path; the server evaluating the expression against the unstructured database column at least in part by: the server accessing the marked up text node from the location without scanning the particular portion of data; the server determining that the marked up text node contains the specified value; and the server determining that the marked up text node is under the hierarchical path based at least in part on the indication.
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16. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of: a server analyzing portions of data, including a particular portion of data, that are stored in an unstructured database column in a database to determine whether or not the data includes marked up text-, wherein, prior to analyzing the portions of data, the portions of data, as stored, were not defined as marked up text; without changing the particular portion of data that is stored in the unstructured database column, the server determining that the particular portion contains a marked up text node is a descendant of an ancestor node, and the server storing a location of the marked up text node and an indication that the marked up text node is a descendant of the ancestor node; the server receiving an expression that specifies a value and a hierarchical path; the server evaluating the expression against the unstructured database column at least in part by: the server accessing the marked up text node from the location without scanning the particular portion of data; the server determining that the marked up text node contains the specified value; and the server determining that the marked up text node is under the hierarchical path based at least in part on the indication. 23. One or more non-transitory storage media as recited in claim 16 , wherein the particular portion is at least part of a first document, wherein the instructions, when executed by the one or more computing devices, cause performance of: determining that the unstructured database column in the database stores a second document of non-marked up text; in response to determining that the unstructured database column in the database stores the second document of non-marked up text, skipping the second document when evaluating the expression.
| 0.624828 |
7,496,599 | 34 | 36 |
34. A system for mapping hierarchical data from a relational table comprising: a schema stored in a memory for a hierarchical data structure wherein the schema defines a hierarchical relationship of data elements; processing means coupled to said memory for identifying from the schema a node within the hierarchical data structure corresponding to a column in the relational table; and processing means for copying a data value from the relational table to the hierarchical data structure wherein the first data value is selected from the relational table in a sort order specified by the schema.
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34. A system for mapping hierarchical data from a relational table comprising: a schema stored in a memory for a hierarchical data structure wherein the schema defines a hierarchical relationship of data elements; processing means coupled to said memory for identifying from the schema a node within the hierarchical data structure corresponding to a column in the relational table; and processing means for copying a data value from the relational table to the hierarchical data structure wherein the first data value is selected from the relational table in a sort order specified by the schema. 36. The system as recited in claim 34 wherein the relational table comprises a table in a structured query language (SQL) database.
| 0.507519 |
9,298,437 | 15 | 19 |
15. A computer comprising: a memory including instructions stored thereon; and a processor communicatively coupled to the memory when the computer is in operation, wherein the instructions, when executed by the processor, cause the processor to: identify a quantification in a regular expression of source code; rewrite the quantification to be implemented by at least one of a counter state machine element of a target device or a set of general purpose state machine elements; identify portions of the rewritten quantification that can be implemented by the counter state machine element; determine whether the target device has an available counter state machine element for the identified portions; and unroll the identified portions if there is no available counter state machine element and assigning the identified portions to the available counter state machine element otherwise.
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15. A computer comprising: a memory including instructions stored thereon; and a processor communicatively coupled to the memory when the computer is in operation, wherein the instructions, when executed by the processor, cause the processor to: identify a quantification in a regular expression of source code; rewrite the quantification to be implemented by at least one of a counter state machine element of a target device or a set of general purpose state machine elements; identify portions of the rewritten quantification that can be implemented by the counter state machine element; determine whether the target device has an available counter state machine element for the identified portions; and unroll the identified portions if there is no available counter state machine element and assigning the identified portions to the available counter state machine element otherwise. 19. The computer of claim 15 , wherein unrolling the identified portions includes the processor to: determine that the identified portions match a multiple numbers of loops including at least a first number and a second number; create a first new quantification of the first number minus one; create a second new quantification with a ranged between one and the second number minus the first number plus one; and concatenate the result of repeating a sub-expression of the first new quantification for the first number minus one times to an unrolling of the second new quantification.
| 0.5 |
8,938,449 | 15 | 17 |
15. A system, comprising: a data processing apparatus; a data store storing instructions executable by the data processing apparatus and upon execution by the data processing apparatus cause the data processing apparatus to perform operations comprising: accessing, by the data processing apparatus, images stored in an image data store, the images being associated with respective sets of labels, each label describing content depicted in an image and having a respective confidence score that is a measure of confidence that the label accurately describes the content depicted in the image; accessing, by the data processing apparatus, one or more proximity metric values associated with a first image of the images; accessing, by the data processing apparatus, one or more proximity metric values associated with a second image of the images; determining, by the data processing apparatus, a proximity score for the second image based on a comparison of the proximity metric values of the first image and corresponding proximity metric values of the second image, the proximity score being a measure of a relatedness of the second image to the first image; and identifying, by the data processing apparatus, a second label associated with the second image, the second label having a second confidence score that is a measure of confidence that the second label accurately describes the content depicted in the second image; generating, by the data processing apparatus, a first label for the first image based on the second label, the proximity score for the second image, and the second confidence score for the second label; and determining, by the data processing apparatus and for the first label, a first confidence score based on the proximity score for the second image and the second confidence score for the second label, the first confidence score being a measure of confidence that the first label accurately describes the content depicted in the first image.
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15. A system, comprising: a data processing apparatus; a data store storing instructions executable by the data processing apparatus and upon execution by the data processing apparatus cause the data processing apparatus to perform operations comprising: accessing, by the data processing apparatus, images stored in an image data store, the images being associated with respective sets of labels, each label describing content depicted in an image and having a respective confidence score that is a measure of confidence that the label accurately describes the content depicted in the image; accessing, by the data processing apparatus, one or more proximity metric values associated with a first image of the images; accessing, by the data processing apparatus, one or more proximity metric values associated with a second image of the images; determining, by the data processing apparatus, a proximity score for the second image based on a comparison of the proximity metric values of the first image and corresponding proximity metric values of the second image, the proximity score being a measure of a relatedness of the second image to the first image; and identifying, by the data processing apparatus, a second label associated with the second image, the second label having a second confidence score that is a measure of confidence that the second label accurately describes the content depicted in the second image; generating, by the data processing apparatus, a first label for the first image based on the second label, the proximity score for the second image, and the second confidence score for the second label; and determining, by the data processing apparatus and for the first label, a first confidence score based on the proximity score for the second image and the second confidence score for the second label, the first confidence score being a measure of confidence that the first label accurately describes the content depicted in the first image. 17. The system of claim 15 , wherein the first label is generated in response to the proximity score of the second image being above a proximity score threshold and a confidence score of the second label of the second image being above a confidence score threshold.
| 0.5 |
9,146,997 | 9 | 10 |
9. The system of claim 8 , wherein execution of the instructions cause the one or more data processing apparatus to perform operations further comprising selecting the first performance data to rank the plurality of image search results when the result similarity meets a specified level of similarity.
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9. The system of claim 8 , wherein execution of the instructions cause the one or more data processing apparatus to perform operations further comprising selecting the first performance data to rank the plurality of image search results when the result similarity meets a specified level of similarity. 10. The system of claim 9 , wherein execution of the instructions cause the one or more data processing apparatus to perform operations further comprising: selecting the second performance data to rank the image search results when the result similarity does not meet the specified level.
| 0.5 |
8,478,732 | 1 | 5 |
1. A computer-implemented method for aliasing a collection of data, comprising: extracting, by a computing device, names and associated terms from a collection of data; normalizing, by the computing device, the extracted names and associated terms; parsing, by the computing device, the normalized names and associated terms in conjunction with a grammar to produce meaning fragments, the grammar representing how words and their component parts combine to form sentences; and mapping, by the computing device, the meaning fragments to a collection of concepts stored in an aliasing file, the concepts representing general ideas inferred or derived from specific instances, wherein alias entries are stored in the aliasing file when a determination is made that multiple normalized names and associated terms map to a single concept, and the aliasing file is used for resolving variations in the extracted names and associated terms during the normalizing step.
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1. A computer-implemented method for aliasing a collection of data, comprising: extracting, by a computing device, names and associated terms from a collection of data; normalizing, by the computing device, the extracted names and associated terms; parsing, by the computing device, the normalized names and associated terms in conjunction with a grammar to produce meaning fragments, the grammar representing how words and their component parts combine to form sentences; and mapping, by the computing device, the meaning fragments to a collection of concepts stored in an aliasing file, the concepts representing general ideas inferred or derived from specific instances, wherein alias entries are stored in the aliasing file when a determination is made that multiple normalized names and associated terms map to a single concept, and the aliasing file is used for resolving variations in the extracted names and associated terms during the normalizing step. 5. The computer-implemented method of claim 1 wherein the collection of data is a relational database.
| 0.75122 |
9,014,480 | 17 | 19 |
17. One or more non-transitory computer readable storage media comprising a sequence of instructions, which, when executed cause a processor to perform operations, the sequence of instructions comprising: first instructions to create a plurality of sets of positions automatically, by at least performing comparisons using multiple pluralities of pixels hereinafter compared pixels that are located in an image at corresponding positions comprised in the plurality of sets of positions; wherein a first set in the plurality of sets of positions is created without using in any comparison, a plurality of pixels hereinafter skipped pixels that are located in the image at additional positions comprised in the first set; wherein a first region identified by the first set is contiguous in the image, the first region comprising the compared pixels and the skipped pixels identified respectively by the corresponding positions and the additional positions; wherein a second region is contiguous in the image, the second region being identified by positions in a second set, in the plurality of sets of positions created by the creating; second instructions to check, whether a test is satisfied by a first attribute of the first region and a second attribute of the second region; third instructions to prepare a merged set comprising the positions in the first set and the positions in the second set, based on at least an outcome of said test; and fourth instructions to store in at least one memory, the merged set.
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17. One or more non-transitory computer readable storage media comprising a sequence of instructions, which, when executed cause a processor to perform operations, the sequence of instructions comprising: first instructions to create a plurality of sets of positions automatically, by at least performing comparisons using multiple pluralities of pixels hereinafter compared pixels that are located in an image at corresponding positions comprised in the plurality of sets of positions; wherein a first set in the plurality of sets of positions is created without using in any comparison, a plurality of pixels hereinafter skipped pixels that are located in the image at additional positions comprised in the first set; wherein a first region identified by the first set is contiguous in the image, the first region comprising the compared pixels and the skipped pixels identified respectively by the corresponding positions and the additional positions; wherein a second region is contiguous in the image, the second region being identified by positions in a second set, in the plurality of sets of positions created by the creating; second instructions to check, whether a test is satisfied by a first attribute of the first region and a second attribute of the second region; third instructions to prepare a merged set comprising the positions in the first set and the positions in the second set, based on at least an outcome of said test; and fourth instructions to store in at least one memory, the merged set. 19. The one or more non-transitory computer readable storage media of claim 17 wherein: comparisons performed by execution of the first instructions are between a pair of pixels that are separated in the first region from one another by one or more of the skipped pixels; the comparisons are performed repeatedly; and a number of pixels to be skipped in a next comparison at a next iteration are determined at least partially based on a predetermined threshold being not exceeded by a difference in intensities, between one compared pixel used in a current comparison at a current iteration and another compared pixel used in a prior comparison at a prior iteration.
| 0.5 |
9,747,897 | 3 | 5 |
3. The computer-implemented method of claim 1 , wherein selecting further comprises: providing, on a user interface, a representation of the one or more terms to the particular user; receiving a confirmation from the particular user that the representation of the one or more terms correspond to the actual phonetic transcription; and associating the one or more terms with the actual phonetic transcription.
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3. The computer-implemented method of claim 1 , wherein selecting further comprises: providing, on a user interface, a representation of the one or more terms to the particular user; receiving a confirmation from the particular user that the representation of the one or more terms correspond to the actual phonetic transcription; and associating the one or more terms with the actual phonetic transcription. 5. The computer-implemented method of claim 3 , wherein the representation of the one or more terms is provided in response to receiving the audio corresponding to the particular user speaking the one or more terms in the natural language.
| 0.531373 |
8,239,366 | 67 | 68 |
67. A system comprising: at least one tangible memory that stores processor-executable instructions for performing a search for content via the Internet; and at least one hardware computer processor, coupled to the at least one tangible memory, that executes the processor-executable instructions to: receive voice input provided from a user; and generate at least one text search query for a plurality of Internet-accessible search engines that search for content on the Internet, wherein the at least one text search query is generated, at least in part, by performing speech recognition on the voice input; wherein the at least one text search query comprises at least two text search queries; wherein the at least one hardware computer processor generates the at least one text search query by: generating a first of the at least two text search queries, at least in part by performing speech recognition on the voice input using a first language model associated with a first of the plurality of search engines; and generating a second of the at least two text search queries, at least in part, by performing speech recognition on the voice input using a second language model, different from the first language model, associated with a second of the plurality of search engines; wherein the first language model is one that was trained on content indexed by the first of the plurality of search engines; wherein the first of the plurality of search engines is a site-specific search engine; and wherein the second of the plurality of search engines is a general search engine.
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67. A system comprising: at least one tangible memory that stores processor-executable instructions for performing a search for content via the Internet; and at least one hardware computer processor, coupled to the at least one tangible memory, that executes the processor-executable instructions to: receive voice input provided from a user; and generate at least one text search query for a plurality of Internet-accessible search engines that search for content on the Internet, wherein the at least one text search query is generated, at least in part, by performing speech recognition on the voice input; wherein the at least one text search query comprises at least two text search queries; wherein the at least one hardware computer processor generates the at least one text search query by: generating a first of the at least two text search queries, at least in part by performing speech recognition on the voice input using a first language model associated with a first of the plurality of search engines; and generating a second of the at least two text search queries, at least in part, by performing speech recognition on the voice input using a second language model, different from the first language model, associated with a second of the plurality of search engines; wherein the first language model is one that was trained on content indexed by the first of the plurality of search engines; wherein the first of the plurality of search engines is a site-specific search engine; and wherein the second of the plurality of search engines is a general search engine. 68. The system of claim 67 , wherein the at least one hardware computer processor executes the processor-executable instructions to: issue the first of the at least two text search queries to the first of the plurality of search engines; and issue the second of the at least two text search queries to the second of the plurality of search engines.
| 0.792363 |
8,055,597 | 11 | 12 |
11. A computer program product comprising a computer usable medium storing a set of instructions adapted to be executed by a processor to perform the steps of: receiving a plurality of records corresponding to media content at a computer, the records each containing categorical data; obtaining a categorical dataset by mapping each of the plurality of records onto predefined fields of a system ontology, wherein the ontology fields correspond to an attribute space comprising a plurality of attributes each characterized by a plurality of terms, the dataset characterized by the attribute space, the dataset being unsorted; modifying the dataset, wherein the modifying the dataset comprises modifying one or more of the plurality of terms characterizing one or more of the plurality of attributes; decomposing the attribute space into a plurality of attribute subspaces each comprising one or more of the plurality of attributes; generating a parent taxonomy of the modified dataset with respect to one of the plurality of attribute subspaces, the parent taxonomy organizing the modified dataset into a plurality of data subsets; generating a child taxonomy with respect to another one of the plurality of attribute subspaces, the child taxonomy organizing each of the plurality of data subsets within the parent taxonomy into at least one data subset; iteratively repeating generating the child taxonomy until a predetermined termination condition is satisfied, wherein the child taxonomy of a preceding iteration is the parent taxonomy of the current iteration; and assigning category labels to the data subsets.
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11. A computer program product comprising a computer usable medium storing a set of instructions adapted to be executed by a processor to perform the steps of: receiving a plurality of records corresponding to media content at a computer, the records each containing categorical data; obtaining a categorical dataset by mapping each of the plurality of records onto predefined fields of a system ontology, wherein the ontology fields correspond to an attribute space comprising a plurality of attributes each characterized by a plurality of terms, the dataset characterized by the attribute space, the dataset being unsorted; modifying the dataset, wherein the modifying the dataset comprises modifying one or more of the plurality of terms characterizing one or more of the plurality of attributes; decomposing the attribute space into a plurality of attribute subspaces each comprising one or more of the plurality of attributes; generating a parent taxonomy of the modified dataset with respect to one of the plurality of attribute subspaces, the parent taxonomy organizing the modified dataset into a plurality of data subsets; generating a child taxonomy with respect to another one of the plurality of attribute subspaces, the child taxonomy organizing each of the plurality of data subsets within the parent taxonomy into at least one data subset; iteratively repeating generating the child taxonomy until a predetermined termination condition is satisfied, wherein the child taxonomy of a preceding iteration is the parent taxonomy of the current iteration; and assigning category labels to the data subsets. 12. The computer program product claim 11 , wherein the computer usable medium has computer readable code embodied therein for causing a computer to effect: decomposing the attribute space into a plurality of attribute subspaces such that two attribute subspaces share an attribute.
| 0.534653 |
9,111,011 | 1 | 6 |
1. A computer-implemented method comprising: responsive to obtaining a first query including one or more characters and a first user location where the first query was issued: identifying a first point of interest within a first predefined proximity to the first user location; identifying a second point of interest within a second predefined proximity to the first user location; determining a first category of the first point of interest and a second category of the second point of interest; identifying, using a database that maps categories to queries issued by users at locations within predefined proximities to points of interest having the first category, a first category-specific query suggestion in accordance with the first category and a second category-specific query suggest in accordance with the second category, including: determining a first category-specific count representing a total number of times the first query was issued by users from user locations having the first category; determining a second category-specific count representing a total number of times the first query was issued by users from user locations having the second category; and providing the first category-specific query suggestion in accordance with the first category-specific count and the second category-specific query suggestion in accordance with the second category-specific count, wherein the first category-specific query suggestion includes the one or more characters included in the first query, and the second category-specific query suggestion includes the one or more characters included in the first query; and providing, to a user, one or more query suggestions including the first category-specific query suggestion and the second category-specific query suggestion.
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1. A computer-implemented method comprising: responsive to obtaining a first query including one or more characters and a first user location where the first query was issued: identifying a first point of interest within a first predefined proximity to the first user location; identifying a second point of interest within a second predefined proximity to the first user location; determining a first category of the first point of interest and a second category of the second point of interest; identifying, using a database that maps categories to queries issued by users at locations within predefined proximities to points of interest having the first category, a first category-specific query suggestion in accordance with the first category and a second category-specific query suggest in accordance with the second category, including: determining a first category-specific count representing a total number of times the first query was issued by users from user locations having the first category; determining a second category-specific count representing a total number of times the first query was issued by users from user locations having the second category; and providing the first category-specific query suggestion in accordance with the first category-specific count and the second category-specific query suggestion in accordance with the second category-specific count, wherein the first category-specific query suggestion includes the one or more characters included in the first query, and the second category-specific query suggestion includes the one or more characters included in the first query; and providing, to a user, one or more query suggestions including the first category-specific query suggestion and the second category-specific query suggestion. 6. The method of claim 1 , wherein determining a first category of the first point of interest comprises: identifying the first category in accordance with a database that maps points of interest to categories.
| 0.641638 |
8,375,299 | 8 | 14 |
8. A computer-readable storage medium containing a program, which, when executed, performs an operation comprising: receiving a request to paste text into a document; segmenting the text into sequential sections; generating a twistie for each section of the sequential sections, based on the text and by operation of one or more computer processors when executing the program; prompting for confirmation of twistie headings of the generated twisties; and upon receiving confirmation of the twistie headings, inserting the generated twisties into the document, responsive to the request to paste text into the document.
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8. A computer-readable storage medium containing a program, which, when executed, performs an operation comprising: receiving a request to paste text into a document; segmenting the text into sequential sections; generating a twistie for each section of the sequential sections, based on the text and by operation of one or more computer processors when executing the program; prompting for confirmation of twistie headings of the generated twisties; and upon receiving confirmation of the twistie headings, inserting the generated twisties into the document, responsive to the request to paste text into the document. 14. The computer-readable storage medium of claim 8 , wherein at least one of the generated twisties includes a nested twistie.
| 0.721491 |
8,046,368 | 6 | 9 |
6. A document retrieval method comprising: receiving a designation of a document as a retrieval input; reading from data on documents stored in the document database, numeric value data for which numeric value intervals are to be generated; calculating a similarity between the document designated as the retrieval input and each of the documents stored in the document database by use of indices of the designated document and indices of each document stored in the document database, the indices used for indexing numeric values and texts in a corresponding document, each of the indices used for indexing the text being a group of a term constituting the text and a frequency of the term in the corresponding document, each of the indices used for indexing the numeric value being a group of a label describing a feature represented by the numeric value, an interval including the numeric value, and a frequency of the numeric value in the corresponding document; presenting the documents stored in the document database in order of similarity; deciding the numeric value intervals from distribution percentages of numeric values based on a distribution of the numeric value data; and generating the numeric value intervals based on distribution percentages inputted by the numeric value distribution percentage designating unit; wherein the generating the numeric value intervals generates numeric value intervals whose numeric value widths are so adjusted that each of the numeric value intervals includes an equal number of numeric values.
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6. A document retrieval method comprising: receiving a designation of a document as a retrieval input; reading from data on documents stored in the document database, numeric value data for which numeric value intervals are to be generated; calculating a similarity between the document designated as the retrieval input and each of the documents stored in the document database by use of indices of the designated document and indices of each document stored in the document database, the indices used for indexing numeric values and texts in a corresponding document, each of the indices used for indexing the text being a group of a term constituting the text and a frequency of the term in the corresponding document, each of the indices used for indexing the numeric value being a group of a label describing a feature represented by the numeric value, an interval including the numeric value, and a frequency of the numeric value in the corresponding document; presenting the documents stored in the document database in order of similarity; deciding the numeric value intervals from distribution percentages of numeric values based on a distribution of the numeric value data; and generating the numeric value intervals based on distribution percentages inputted by the numeric value distribution percentage designating unit; wherein the generating the numeric value intervals generates numeric value intervals whose numeric value widths are so adjusted that each of the numeric value intervals includes an equal number of numeric values. 9. The document retrieval method according to claim 6 , further comprising: extracting a group of a feature and a numeric value from each of the documents stored in the document database; and indexing the extracted group of the feature and the numeric value in accordance with a numeric conversion table for converting a numeric value into an interval, the numeric conversion table is dedicated to each feature type.
| 0.5 |
8,775,158 | 3 | 9 |
3. The data processing device, as claimed in claim 2 , wherein the association node joint unit has a function of connecting the weak association nodes by a semantic association branch, and the characteristic structure extraction unit has a function in which a partial structure of the graph is not extracted as the characteristic structure when the partial structure includes nodes connected by the semantic association branch, in addition, at least one of those nodes is not connected with another node by the dependency branch.
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3. The data processing device, as claimed in claim 2 , wherein the association node joint unit has a function of connecting the weak association nodes by a semantic association branch, and the characteristic structure extraction unit has a function in which a partial structure of the graph is not extracted as the characteristic structure when the partial structure includes nodes connected by the semantic association branch, in addition, at least one of those nodes is not connected with another node by the dependency branch. 9. The data processing device, as claimed in claim 3 , wherein the association node extraction unit has a function of designated related word node extraction for extracting designated related word nodes including related words designated by a user as the association nodes, the association node joint unit has a function of node categorization for categorizing the designated related word nodes as the weak association nodes.
| 0.502342 |
8,935,152 | 4 | 7 |
4. The method of claim 1 , wherein the step of merging further comprises: determining, performed at least in part with a configuration of computing hardware and programmable memory, a first and second logical form for the first and second candidate representative role values; determining, performed at least in part with a configuration of computing hardware and programmable memory, the first and second meanings to be sufficiently similar if the first and second logical forms are sufficiently similar.
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4. The method of claim 1 , wherein the step of merging further comprises: determining, performed at least in part with a configuration of computing hardware and programmable memory, a first and second logical form for the first and second candidate representative role values; determining, performed at least in part with a configuration of computing hardware and programmable memory, the first and second meanings to be sufficiently similar if the first and second logical forms are sufficiently similar. 7. The method of claim 4 , wherein the step of determining, the first and second meanings to be sufficiently similar, further comprises: comparing, performed at least in part with a configuration of computing hardware and programmable memory, using synonym matching, the first and second logical forms.
| 0.5 |
6,122,361 | 29 | 30 |
29. A method as defined in claim 28, wherein said at least a portion of a telephone number dialed by the user is an NPA portion of a telephone number permitting access to the directory assistance function.
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29. A method as defined in claim 28, wherein said at least a portion of a telephone number dialed by the user is an NPA portion of a telephone number permitting access to the directory assistance function. 30. A method as defined in claim 29, comprising the step of determining a probability value for a plurality of vocabulary items.
| 0.5 |
8,738,356 | 10 | 13 |
10. A computer-implemented process for increasing the speed of text entry, comprising: using a computing device for: receiving text in the form of a phonetic string; determining the language and the script of the phonetic string; generating a list of candidates in the determined language and the determined script to replace the phonetic string, while performing automatic script changing when a user changes from typing the text in a first script to typing text in a second script; ranking the candidates in the list of candidates; sending the ranked list of candidates back to the user; the user selecting one of the candidates on the ranked list of candidates to replace the input phonetic string; and replacing the input phonetic string with the user-selected candidate in the text the user is typing.
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10. A computer-implemented process for increasing the speed of text entry, comprising: using a computing device for: receiving text in the form of a phonetic string; determining the language and the script of the phonetic string; generating a list of candidates in the determined language and the determined script to replace the phonetic string, while performing automatic script changing when a user changes from typing the text in a first script to typing text in a second script; ranking the candidates in the list of candidates; sending the ranked list of candidates back to the user; the user selecting one of the candidates on the ranked list of candidates to replace the input phonetic string; and replacing the input phonetic string with the user-selected candidate in the text the user is typing. 13. The computer-implemented process of claim 10 , further comprising displaying the ranked candidates with additional information comprising translation of words and usage examples.
| 0.604348 |
8,554,716 | 11 | 13 |
11. The method of claim 2 , further comprising applying targeted document identification to the plurality of documents.
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11. The method of claim 2 , further comprising applying targeted document identification to the plurality of documents. 13. The method of claim 11 , wherein applying further comprises identifying a candidate key document based on sampling based on one or more phrases.
| 0.5 |
7,941,745 | 22 | 23 |
22. A service providing device comprising: a processor; a memory device which stores a plurality of instructions, which when executed by the processor, performs: a storing step of storing a database including at least one of electronic documents and tagged electronic documents tagged according to a markup language; a receiving step of receiving, via a receiver and from a terminal device, specification information specifying at least one of an electronic document without a tag and a tagged electronic document and receiving request information indicating a request for said tagged electronic document including a tag indicating the structure of the electronic document without a tag; a transmitting step of transmitting via a transmitter; a determining step of determining, when said receiver receives said request information, whether (i) said tagged electronic document corresponding to the received specification information is stored in said database, (ii) said electronic document corresponding to the received specification information is stored in said database, or (iii) no document corresponding to the received specification information is stored in said database; and a control step of reading said tagged electronic document from said database and transmitting it to said terminal device via the transmitter when said determining step has determined that said database includes said tagged electronic document of the electronic document specified by said specification information, and when said determining step has determined that said database includes no document corresponding to the received specification information, transmitting data to said user terminal to request transmission of the electronic document indicated by said specification information.
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22. A service providing device comprising: a processor; a memory device which stores a plurality of instructions, which when executed by the processor, performs: a storing step of storing a database including at least one of electronic documents and tagged electronic documents tagged according to a markup language; a receiving step of receiving, via a receiver and from a terminal device, specification information specifying at least one of an electronic document without a tag and a tagged electronic document and receiving request information indicating a request for said tagged electronic document including a tag indicating the structure of the electronic document without a tag; a transmitting step of transmitting via a transmitter; a determining step of determining, when said receiver receives said request information, whether (i) said tagged electronic document corresponding to the received specification information is stored in said database, (ii) said electronic document corresponding to the received specification information is stored in said database, or (iii) no document corresponding to the received specification information is stored in said database; and a control step of reading said tagged electronic document from said database and transmitting it to said terminal device via the transmitter when said determining step has determined that said database includes said tagged electronic document of the electronic document specified by said specification information, and when said determining step has determined that said database includes no document corresponding to the received specification information, transmitting data to said user terminal to request transmission of the electronic document indicated by said specification information. 23. A service providing device according to claim 22 , wherein said transmitter and said receiver are capable of transmitting and receiving information to and from an authoring device, and when said determining step determines that said database includes the electronic document specified by said specification information, said control step requests via said transmitter said authoring device to produce a tagged electronic document of said electronic document, and when said tagged electronic document is received from said authoring device via said receiver, said control step transmits said tagged electronic document to said terminal device via said transmitter.
| 0.5 |
7,548,934 | 1 | 9 |
1. A computer-implemented method of generating a list, comprising: receiving a candidate item comprising at least one of an artist name or a title of the candidate item; for each reference item of a plurality of reference items, comparing at least a portion of respective characters of the at least one of the artist name or the title of the candidate item to at least a portion of respective reference-item characters of at least one of a reference-item artist name or a reference-item title of the reference item to facilitate determining a respective matching score, relating to each of the at least one of the artist name or the title of the candidate item, for each reference item based at least in part on a respective number of matches between the at least a portion of the respective characters and the at least a portion of the respective reference-item characters for each reference item; identifying the candidate item based at least in part on a best reference item, the best reference item is a reference item of the plurality of reference items having a matching score that at least meets a predetermined threshold amount and has a highest matching score as compared to other reference items of the plurality of reference items; associating a plurality of metadata relating to the best reference item with the candidate item, wherein the associated plurality of metadata is a plurality of candidate item metadata relating to the candidate item, to facilitate comparing similarity between the candidate item and a seed item; retrieving a plurality of seed item metadata relating to the seed item identified by a received seed item identifier; comparing the plurality of seed item metadata to the plurality of candidate item metadata; computing a similarity score between the seed item and the candidate item based at least in part on a similarity of the plurality of seed item metadata to the plurality of candidate item metadata, wherein the similarity score is computed using a list-generation computer system; determining whether to add the candidate item to the list based at least in part on the similarity score; and generating the list, which is provided to a user.
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1. A computer-implemented method of generating a list, comprising: receiving a candidate item comprising at least one of an artist name or a title of the candidate item; for each reference item of a plurality of reference items, comparing at least a portion of respective characters of the at least one of the artist name or the title of the candidate item to at least a portion of respective reference-item characters of at least one of a reference-item artist name or a reference-item title of the reference item to facilitate determining a respective matching score, relating to each of the at least one of the artist name or the title of the candidate item, for each reference item based at least in part on a respective number of matches between the at least a portion of the respective characters and the at least a portion of the respective reference-item characters for each reference item; identifying the candidate item based at least in part on a best reference item, the best reference item is a reference item of the plurality of reference items having a matching score that at least meets a predetermined threshold amount and has a highest matching score as compared to other reference items of the plurality of reference items; associating a plurality of metadata relating to the best reference item with the candidate item, wherein the associated plurality of metadata is a plurality of candidate item metadata relating to the candidate item, to facilitate comparing similarity between the candidate item and a seed item; retrieving a plurality of seed item metadata relating to the seed item identified by a received seed item identifier; comparing the plurality of seed item metadata to the plurality of candidate item metadata; computing a similarity score between the seed item and the candidate item based at least in part on a similarity of the plurality of seed item metadata to the plurality of candidate item metadata, wherein the similarity score is computed using a list-generation computer system; determining whether to add the candidate item to the list based at least in part on the similarity score; and generating the list, which is provided to a user. 9. The computer-implemented method of claim 1 , wherein the seed item identifier is at least one of a GUID or a database table index.
| 0.916247 |
9,424,351 | 19 | 20 |
19. A system for utilizing a hybrid-distribution system for identifying relevant documents based on a search query, the system comprising: a hardware processor and a memory configured for providing computer program instructions to the processor; a hybrid distribution server configured for: allocating a group of documents to a segment, the group of documents being indexed by atom in a reverse index and indexed by document in a forward index, atoms in the reverse index are accessed in a matching process and a preliminary ranking process and documents in the forward index are accessed in a final ranking process; storing a different portion of the reverse index and the forward index on each of a plurality of nodes that form the segment; first, accessing the reverse index portion stored on each of a first set of nodes having portions of the reverse index; identifying a first set of documents that is relevant to the search query, wherein the first set of documents is identified as being relevant to the search query by way of the matching process and the preliminary ranking process; second, based on document identifications associated with the first set of documents, accessing the forward index portion stored on each of a second set of nodes having portions of the forward index; identifying a second set of documents from the first set of documents, wherein the second set of documents is identified by way of the final ranking process; limiting a quantity of relevant documents in the first set of documents identified to the second set of documents; and communicating for presentation search results for the search query based on the second set of documents.
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19. A system for utilizing a hybrid-distribution system for identifying relevant documents based on a search query, the system comprising: a hardware processor and a memory configured for providing computer program instructions to the processor; a hybrid distribution server configured for: allocating a group of documents to a segment, the group of documents being indexed by atom in a reverse index and indexed by document in a forward index, atoms in the reverse index are accessed in a matching process and a preliminary ranking process and documents in the forward index are accessed in a final ranking process; storing a different portion of the reverse index and the forward index on each of a plurality of nodes that form the segment; first, accessing the reverse index portion stored on each of a first set of nodes having portions of the reverse index; identifying a first set of documents that is relevant to the search query, wherein the first set of documents is identified as being relevant to the search query by way of the matching process and the preliminary ranking process; second, based on document identifications associated with the first set of documents, accessing the forward index portion stored on each of a second set of nodes having portions of the forward index; identifying a second set of documents from the first set of documents, wherein the second set of documents is identified by way of the final ranking process; limiting a quantity of relevant documents in the first set of documents identified to the second set of documents; and communicating for presentation search results for the search query based on the second set of documents. 20. The system of claim 19 , wherein the preliminary ranking process is a simplified scoring function compared to the final ranking process, wherein the preliminary ranking process employs a subset of ranking features used by the final ranking process, the final ranking process using a full set of ranking features.
| 0.5 |
8,671,364 | 31 | 33 |
31. An article of manufacture comprising a storage medium containing instructions that when executed enable a system 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; receive a control directive indicating selection of the selectable GUI element of the hierarchical level for decomposition into decomposed GUI elements of the different hierarchical level; and present the selectable GUI element of the hierarchical level adjoining with the decomposed GUI elements of the different hierarchical level in response to the control directive.
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31. An article of manufacture comprising a storage medium containing instructions that when executed enable a system 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; receive a control directive indicating selection of the selectable GUI element of the hierarchical level for decomposition into decomposed GUI elements of the different hierarchical level; and present the selectable GUI element of the hierarchical level adjoining with the decomposed GUI elements of the different hierarchical level in response to the control directive. 33. The article of manufacture of claim 31 , further comprising instructions that when executed enable the system to expand an information pipe for the multivariable decomposition visualization in response to a pipe expand control directive.
| 0.613782 |
8,484,675 | 1 | 7 |
1. A system comprising: a user behavior analyzer to which an end-user can couple, said user behavior analyzer being adapted to analyze the behavior of said end-user with respect to a plurality of content providers adapted to transmit first multimedia data to said end-user via a first content selector controllable by said end-user to transmit the first multimedia data from a selected one of said content providers, wherein said user behavior analyzer is adapted to transmit input controls signals to an opportunities selector, adapted (i) to receive additional input control signals from a plurality of additional content providers adapted to transmit second multimedia data to said end-user via a second content selector and (ii) to cause said second content selector to transmit to said end-user said second multimedia data from a selected one of said additional content providers; and a multimedia data combiner adapted to combine said second multimedia data with the first multimedia data into a combined multimedia data signal and to transmit said combined multimedia data signal to said end-user.
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1. A system comprising: a user behavior analyzer to which an end-user can couple, said user behavior analyzer being adapted to analyze the behavior of said end-user with respect to a plurality of content providers adapted to transmit first multimedia data to said end-user via a first content selector controllable by said end-user to transmit the first multimedia data from a selected one of said content providers, wherein said user behavior analyzer is adapted to transmit input controls signals to an opportunities selector, adapted (i) to receive additional input control signals from a plurality of additional content providers adapted to transmit second multimedia data to said end-user via a second content selector and (ii) to cause said second content selector to transmit to said end-user said second multimedia data from a selected one of said additional content providers; and a multimedia data combiner adapted to combine said second multimedia data with the first multimedia data into a combined multimedia data signal and to transmit said combined multimedia data signal to said end-user. 7. The system according to claim 1 , wherein said user behavior analyzer is adapted to be coupled to said end-user via a set-top box located at the end-user's premises.
| 0.869969 |
8,417,854 | 1 | 7 |
1. A computer-implemented method comprising: receiving, at an integration layer, a connection request from an auto-id component to be connected to an auto-id node, the connection request specifying one or more communication parameters of the auto-id component; instantiating a generic adaptor class for effecting communication between the auto-id node and the auto-id component, the generic adaptor implementing functionality common to multiple different, specific adaptor classes stored in a class repository of the integration layer; instantiating a generic communicator class for effecting a data transport aspect of the communication between the auto-id node and the auto-id component, the generic communicator class implementing functionality common to multiple different, specific communicator classes stored in the class repository, and the generic communicator class being a component of the generic adaptor class; instantiating a generic converter class for effecting a data conversion aspect of the communication between the auto-id node and the auto-id component, the generic converter class implementing functionality common to multiple different, specific converter classes stored in the class repository, and the generic converter class being a component of the generic adaptor class; identifying, from among the multiple different adaptor, communicator, and converter classes stored in the class repository, a specific adaptor, a specific communicator class, and a specific converter class, respectively, based on the specified communication parameters; instantiating the identified specific adaptor, communicator, and converter classes; adding the identified specific adaptor, communicator, and converter classes to an instance list and effecting the communication between the auto-id component and the auto-id node using the instantiated generic adaptor, communicator, and converter classes and the instantiated specific adaptor, communicator, and converter classes.
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1. A computer-implemented method comprising: receiving, at an integration layer, a connection request from an auto-id component to be connected to an auto-id node, the connection request specifying one or more communication parameters of the auto-id component; instantiating a generic adaptor class for effecting communication between the auto-id node and the auto-id component, the generic adaptor implementing functionality common to multiple different, specific adaptor classes stored in a class repository of the integration layer; instantiating a generic communicator class for effecting a data transport aspect of the communication between the auto-id node and the auto-id component, the generic communicator class implementing functionality common to multiple different, specific communicator classes stored in the class repository, and the generic communicator class being a component of the generic adaptor class; instantiating a generic converter class for effecting a data conversion aspect of the communication between the auto-id node and the auto-id component, the generic converter class implementing functionality common to multiple different, specific converter classes stored in the class repository, and the generic converter class being a component of the generic adaptor class; identifying, from among the multiple different adaptor, communicator, and converter classes stored in the class repository, a specific adaptor, a specific communicator class, and a specific converter class, respectively, based on the specified communication parameters; instantiating the identified specific adaptor, communicator, and converter classes; adding the identified specific adaptor, communicator, and converter classes to an instance list and effecting the communication between the auto-id component and the auto-id node using the instantiated generic adaptor, communicator, and converter classes and the instantiated specific adaptor, communicator, and converter classes. 7. The method of claim 1 , wherein the specific adaptor class further comprises a SOAP (Simple Object Access Protocol) or a JSP (Java Server Pages) adaptor class.
| 0.722603 |
6,038,531 | 31 | 33 |
31. A similar word discrimination apparatus, comprising: means for receiving voice data of input words; means for creating a learning dynamic recurrent neural networks (DRNN) sub-voice model, that uses a DRNN voice model, to obtain a specified DRNN output for the characteristic components of respective similar words showing a level of correctness in response to the voice data of input words; means for processing the DRNN output to establish a specified period in which the characteristic components of the input words are included in the DRNN output, when the DRNN output shows a level of correctness of a predetermined amount or greater; means for examining the characteristics of the voice data of said input words during the specified period; and means for discriminating between the input words and words that are similar to the input words on the basis of the examination.
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31. A similar word discrimination apparatus, comprising: means for receiving voice data of input words; means for creating a learning dynamic recurrent neural networks (DRNN) sub-voice model, that uses a DRNN voice model, to obtain a specified DRNN output for the characteristic components of respective similar words showing a level of correctness in response to the voice data of input words; means for processing the DRNN output to establish a specified period in which the characteristic components of the input words are included in the DRNN output, when the DRNN output shows a level of correctness of a predetermined amount or greater; means for examining the characteristics of the voice data of said input words during the specified period; and means for discriminating between the input words and words that are similar to the input words on the basis of the examination. 33. The similar word discrimination apparatus of claim 31, wherein: the DRNN voice model creates correspondence between groups of words having similar word groups and generates a DRNN output showing the level of correctness at a predetermined level or greater for each of the similar word groups of the group of words.
| 0.5 |
7,895,232 | 10 | 12 |
10. The apparatus according to claim 9 , wherein the tag associated with the root annotation operator is a first tag, which specifies a first span, and wherein the intermediate operator comprises a intermediate annotation operator with which a second tag, specifying a second span, is associated.
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10. The apparatus according to claim 9 , wherein the tag associated with the root annotation operator is a first tag, which specifies a first span, and wherein the intermediate operator comprises a intermediate annotation operator with which a second tag, specifying a second span, is associated. 12. The apparatus according to claim 10 , wherein the processor is configured to find multiple occurrences of the second span that overlap the first span at least partially and in which the first annotation operator is satisfied.
| 0.630645 |
9,552,346 | 6 | 8 |
6. The method as set forth in claim 1 further comprising: breaking the meta-data records by a computer into segments of the work of literature; and marking by a computer the sequential graph according to the segments.
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6. The method as set forth in claim 1 further comprising: breaking the meta-data records by a computer into segments of the work of literature; and marking by a computer the sequential graph according to the segments. 8. The method as set forth in claim 6 further comprising: determining by a computer system a dominant genre of each segment; and annotating by a computer each segment on the sequential graph according to the dominant genre corresponding to each segment.
| 0.610769 |
9,876,848 | 1 | 8 |
1. A computer-executed method comprising: accessing an image comprising an unidentified key phrase in image format; processing a portion of the image associated with the unidentified key phrase using a character recognition algorithm to generate a list of candidate key phrases in text format; accessing, by a computer processor, a plurality of social media content items in text format authored by users of a social networking system, the social media content items each comprising at least one key phrase previously associated with the image and at least one of the candidate key phrases; determining, by the computer processor, for each candidate key phrase, a count of the number of the content items comprising that candidate key phrase and at least one of the key phrases previously associated with the image; selecting, by the computer processor, one of the candidate key phrases as being the unidentified key phrase based on the determined count of the content items in each set; and sending content associated with the image to one or more users of the social networking system based on the social media content items including the selected candidate key phrase.
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1. A computer-executed method comprising: accessing an image comprising an unidentified key phrase in image format; processing a portion of the image associated with the unidentified key phrase using a character recognition algorithm to generate a list of candidate key phrases in text format; accessing, by a computer processor, a plurality of social media content items in text format authored by users of a social networking system, the social media content items each comprising at least one key phrase previously associated with the image and at least one of the candidate key phrases; determining, by the computer processor, for each candidate key phrase, a count of the number of the content items comprising that candidate key phrase and at least one of the key phrases previously associated with the image; selecting, by the computer processor, one of the candidate key phrases as being the unidentified key phrase based on the determined count of the content items in each set; and sending content associated with the image to one or more users of the social networking system based on the social media content items including the selected candidate key phrase. 8. The computer-executed method of claim 1 , wherein the second key phrase is not previously known to be associated with the image.
| 0.772569 |
9,516,154 | 9 | 10 |
9. The apparatus of claim 3 , wherein the management unit is further configured to preserve the conversational information associated with the one contact by making the conversational messages associated with the all numbers of the one contact corresponding to a same conversational identification.
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9. The apparatus of claim 3 , wherein the management unit is further configured to preserve the conversational information associated with the one contact by making the conversational messages associated with the all numbers of the one contact corresponding to a same conversational identification. 10. The apparatus of claim 9 , wherein the management unit comprises: a number updating unit configured to: preserve a correspondence relationship among the conversational identification, the number and the name of the one contact of each conversational message in a time sequence, and update the preserved correspondence relationship depending on a change in the corresponding number of the one contact; a message updating unit configured to: preserve a correspondence relationship among the conversational identification, the number of the one contact, the detailed content and the time of occurrence of each conversational message, and update the preserved correspondence relationship depending on the change in the corresponding number of the one contact; a conversational entry updating unit configured to: preserve a correspondence relationship among the conversational identification of each single conversational content and the time of occurrence and the detailed content of a latest conversational message in the single conversational content, and update the preserved correspondence relationship depending on the change in the corresponding number of the one contact; and a conversational content forming unit configured to form the conversational content associated with the one contact including a conversational entry message list and a conversational message list based on the correspondence relationships preserved by the number updating unit, the message updating unit and the conversational entry updating unit respectively and the contact information stored by the storage unit.
| 0.5 |
9,747,899 | 12 | 13 |
12. An audio device comprising: one or more processors; a plurality of microphones; an audio speaker configured to produce output audio; memory storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform acts comprising: receiving, from the plurality of microphones, a plurality of audio signals representing input audio; generating, by the one or more processors for each of the plurality of audio signals, an indication indicating whether a corresponding audio signal contains a predefined expression; generating a parameter that indicates at least one of whether or not the output audio is currently being produced, whether or not the output audio contains speech, loudness of the output audio, or an echo characteristic of one or more of the plurality of audio signals; identifying, based at least in part on the indications, two or more audio signals, of the plurality of audio signals, that include the predefined expression; determining, based at least in part on the two or more audio signals and the parameter, that an occurrence of the predefined expression in the input audio is a result of an utterance of the predefined expression by a user; and in response to the determining, providing a wake notification corresponding to the predefined expression to the one or more processors to change a state of the audio device.
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12. An audio device comprising: one or more processors; a plurality of microphones; an audio speaker configured to produce output audio; memory storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform acts comprising: receiving, from the plurality of microphones, a plurality of audio signals representing input audio; generating, by the one or more processors for each of the plurality of audio signals, an indication indicating whether a corresponding audio signal contains a predefined expression; generating a parameter that indicates at least one of whether or not the output audio is currently being produced, whether or not the output audio contains speech, loudness of the output audio, or an echo characteristic of one or more of the plurality of audio signals; identifying, based at least in part on the indications, two or more audio signals, of the plurality of audio signals, that include the predefined expression; determining, based at least in part on the two or more audio signals and the parameter, that an occurrence of the predefined expression in the input audio is a result of an utterance of the predefined expression by a user; and in response to the determining, providing a wake notification corresponding to the predefined expression to the one or more processors to change a state of the audio device. 13. The audio device of claim 12 , wherein each of the indications comprises a binary parameter indicating whether the predefined expression occurs in the corresponding audio signal.
| 0.76178 |
7,664,313 | 1 | 5 |
1. A computer-implemented method of generating a set of tuple-term pairs from a corpus of text, comprising: compiling via a processor a set of concordance lines for a set of terms in the corpus; storing a first set of verb-argument tuples and associated terms from the set of concordance lines; computing via the processor a numerical quantification of a strength of association between each verb-argument tuple and associated term in the first set; selecting, from the first set, each verb-argument tuple and associated term whose numerical quantification of strength of association is greater than a predetermined threshold, wherein the selected verb-argument tuples and associated terms form the set of the tuple-term pairs representing most likely actions associated with the set of terms; identifying each tuple-term pair in the set of tuple-term pairs having a verb that matches a verb in a sentence input to a text-to-scene conversion system that constructs an arbitrary three-dimensional scene from input text without using previously stored images; and storing the identified tuple-term pairs in a database.
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1. A computer-implemented method of generating a set of tuple-term pairs from a corpus of text, comprising: compiling via a processor a set of concordance lines for a set of terms in the corpus; storing a first set of verb-argument tuples and associated terms from the set of concordance lines; computing via the processor a numerical quantification of a strength of association between each verb-argument tuple and associated term in the first set; selecting, from the first set, each verb-argument tuple and associated term whose numerical quantification of strength of association is greater than a predetermined threshold, wherein the selected verb-argument tuples and associated terms form the set of the tuple-term pairs representing most likely actions associated with the set of terms; identifying each tuple-term pair in the set of tuple-term pairs having a verb that matches a verb in a sentence input to a text-to-scene conversion system that constructs an arbitrary three-dimensional scene from input text without using previously stored images; and storing the identified tuple-term pairs in a database. 5. The method of claim 1 , wherein computing the numerical quantification of the strength of association comprises: computing a ratio of a likelihood of a first and a second hypothesis, wherein: the first hypothesis indicates that a probability of the verb-argument tuple occurring given the associated term is indistinguishable from a probability of the verb-argument tuple occurring given something other than the associated term, and the second hypothesis indicates that the probability of the verb-argument tuple occurring given the associated term is distinguishable from the probability of the verb-argument tuple occurring given something other than the associated term.
| 0.5 |
10,055,457 | 1 | 4 |
1. A computer-implemented method, comprising: obtaining one or more query terms in a first query; and for each of the one or more query terms: searching a standardized entity taxonomy to locate a standardized entity that most closely matches the query term, the standardized entity taxonomy comprising an entity identification for each of a plurality of different standardized entities; calculating a confidence score for a query term-standardized entity pair for the standardized entity that most closely matches the query term; in response to a determination that the confidence score transgresses a threshold, associating the query term with the entity identification corresponding to the standardized entity that most closely matches the query term; retrieving one or more query rewriting rules corresponding to an entity type of the standardized entity having the entity identification; and executing the one or more query rewriting rules to rewrite the first query such that the rewritten query is more restrictive than the first query.
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1. A computer-implemented method, comprising: obtaining one or more query terms in a first query; and for each of the one or more query terms: searching a standardized entity taxonomy to locate a standardized entity that most closely matches the query term, the standardized entity taxonomy comprising an entity identification for each of a plurality of different standardized entities; calculating a confidence score for a query term-standardized entity pair for the standardized entity that most closely matches the query term; in response to a determination that the confidence score transgresses a threshold, associating the query term with the entity identification corresponding to the standardized entity that most closely matches the query term; retrieving one or more query rewriting rules corresponding to an entity type of the standardized entity having the entity identification; and executing the one or more query rewriting rules to rewrite the first query such that the rewritten query is more restrictive than the first query. 4. The method of claim 1 , wherein the entity type is a skill and the one or more query rewriting rules include determining if there are any standardized titles having an affinity score with the standardized entity that most closely matches the query term higher than a preset threshold, and adding any such standardized titles to the first query with an AND connector.
| 0.551095 |
8,538,912 | 10 | 11 |
10. A method for automatically optimizing an information integration flow, the method 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.
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10. A method for automatically optimizing an information integration flow, the method 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. 11. The method of claim 10 , further including the steps of: searching possible information integration design space guided by forecasting metrics of quality objectives identified for a proposed information integration flow design; and selecting the optimized information integration flow design based on evaluating the metrics.
| 0.5 |
9,213,707 | 1 | 14 |
1. A computer implemented method for interrelating a plurality of source data files and providing access to said interrelated source data files, said computer implemented method comprising: providing an interrelated data integration application comprising an interlinear sort component and an interrelated data access component executable by at least one processor, wherein said interrelated data integration application is configured to sort and access a plurality of records in said source data files according to a graphical representation of a lineage relationship between said source data files defined in a configuration language; providing a parsing component executable by at least one processor, said parsing component configured to compile said configuration language and generate file descriptors usable by said interlinear sort component and said interrelated data access component of said interrelated data integration application, said configuration language configured to define: said lineage relationship between said source data files, each of said source data files containing one or more of said records, wherein said source data files are graphically related to each other in a tree structure using an array of symbols; one or more adopt key fields, wherein a common one of said one or more adopt key fields is configured to relate each child file containing one or more child file records to a corresponding parent file containing one or more parent file records in said tree structure; one or more order key fields configured to define ordering criteria for said records of one or more of said source data files; and one or more predetermined subprograms configured to process instances of one or more of said records from said source data files, a start point of one of a sequence and a subsequence of said records of said source data files, and an end point of said one of said sequence and said subsequence of said records of said source data files; sorting said each of said source data files based on one or more of said lineage relationship, said one or more order key fields, and said one or more adopt key fields defined in said configuration language, and attaching a position number to each of said records of said each of said source data files, by said interlinear sort component of said interrelated data integration application; accessing said records in said source data files reordered by said interlinear sort component based on said lineage relationship between said source data files, and using said position number to determine access of a subsequent one of said records, by said interrelated data access component of said interrelated data integration application; and outputting on a user device responsive to a user request at runtime a set of records comprising a common lineage relationship.
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1. A computer implemented method for interrelating a plurality of source data files and providing access to said interrelated source data files, said computer implemented method comprising: providing an interrelated data integration application comprising an interlinear sort component and an interrelated data access component executable by at least one processor, wherein said interrelated data integration application is configured to sort and access a plurality of records in said source data files according to a graphical representation of a lineage relationship between said source data files defined in a configuration language; providing a parsing component executable by at least one processor, said parsing component configured to compile said configuration language and generate file descriptors usable by said interlinear sort component and said interrelated data access component of said interrelated data integration application, said configuration language configured to define: said lineage relationship between said source data files, each of said source data files containing one or more of said records, wherein said source data files are graphically related to each other in a tree structure using an array of symbols; one or more adopt key fields, wherein a common one of said one or more adopt key fields is configured to relate each child file containing one or more child file records to a corresponding parent file containing one or more parent file records in said tree structure; one or more order key fields configured to define ordering criteria for said records of one or more of said source data files; and one or more predetermined subprograms configured to process instances of one or more of said records from said source data files, a start point of one of a sequence and a subsequence of said records of said source data files, and an end point of said one of said sequence and said subsequence of said records of said source data files; sorting said each of said source data files based on one or more of said lineage relationship, said one or more order key fields, and said one or more adopt key fields defined in said configuration language, and attaching a position number to each of said records of said each of said source data files, by said interlinear sort component of said interrelated data integration application; accessing said records in said source data files reordered by said interlinear sort component based on said lineage relationship between said source data files, and using said position number to determine access of a subsequent one of said records, by said interrelated data access component of said interrelated data integration application; and outputting on a user device responsive to a user request at runtime a set of records comprising a common lineage relationship. 14. The computer implemented method of claim 1 , further comprising generating a composite data file comprising said interrelated source data files according to said graphical representation of said lineage relationship between said source data files, wherein said each child file is sorted and reordered in said corresponding parent file in said composite data file based on said lineage relationship between said source data files for direct and enhanced access to said each child file in said corresponding parent file.
| 0.700344 |
8,370,342 | 1 | 7 |
1. A computer-implemented method comprising: receiving, at a server system from a computing device, a search query that includes multiple search query terms; determining, by the server system, a plurality of documents that are relevant to the search query terms; returning, by the server system to the computing device, a list of search results that identify the plurality of documents; receiving, by the server system from the computing device, an indication of a first search result that was selected from the list of search results by a user of the computing device, the selection of the first search result including a selection of a link that is associated with a first document rather than a sub-page of the first document; dividing, by the server system, the first document from the plurality of documents that corresponds to the first search result that was selected into multiple sub-pages; determining, by the server system, a score for each of the multiple sub-pages based at least on presence of the search query terms in the sub-pages; identifying, by the server system, a first sub-page that is determined to be most relevant to the search query from among the sub-pages based on the scores for the sub-pages; providing, by the server system for display by the computing device, the first sub-page; providing, by the server system, code in the first sub-page so as to cause the computing device to display as part of the first sub-page a control for replacing the display of the first sub-page with a display of a second sub-page upon user selection of the control; receiving an indication of user input requesting navigation to a next most relevant sub-page of the sub-pages, wherein user selection of the control causes the receiving of the indication of the user input; identifying, by the server system, that the second sub-page is determined to be next most relevant to the search query from among the sub-pages based on the scores for the sub-pages; and providing, by the server system for display by the computing device so as to replace the display of the first sub-page upon receipt of the user input, the second sub-page.
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1. A computer-implemented method comprising: receiving, at a server system from a computing device, a search query that includes multiple search query terms; determining, by the server system, a plurality of documents that are relevant to the search query terms; returning, by the server system to the computing device, a list of search results that identify the plurality of documents; receiving, by the server system from the computing device, an indication of a first search result that was selected from the list of search results by a user of the computing device, the selection of the first search result including a selection of a link that is associated with a first document rather than a sub-page of the first document; dividing, by the server system, the first document from the plurality of documents that corresponds to the first search result that was selected into multiple sub-pages; determining, by the server system, a score for each of the multiple sub-pages based at least on presence of the search query terms in the sub-pages; identifying, by the server system, a first sub-page that is determined to be most relevant to the search query from among the sub-pages based on the scores for the sub-pages; providing, by the server system for display by the computing device, the first sub-page; providing, by the server system, code in the first sub-page so as to cause the computing device to display as part of the first sub-page a control for replacing the display of the first sub-page with a display of a second sub-page upon user selection of the control; receiving an indication of user input requesting navigation to a next most relevant sub-page of the sub-pages, wherein user selection of the control causes the receiving of the indication of the user input; identifying, by the server system, that the second sub-page is determined to be next most relevant to the search query from among the sub-pages based on the scores for the sub-pages; and providing, by the server system for display by the computing device so as to replace the display of the first sub-page upon receipt of the user input, the second sub-page. 7. The computer-implemented method of claim 1 , wherein the second sub-page is immediately displayed upon receipt of the user input without additional user input subsequent to the receipt of the user input.
| 0.810313 |
8,612,359 | 33 | 39 |
33. The client device of claim 32 , wherein the online social network enables multiple degrees of separation in relationships among members of the online social network.
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33. The client device of claim 32 , wherein the online social network enables multiple degrees of separation in relationships among members of the online social network. 39. The client device of claim 33 , wherein the machine instructions further cause the processor to perform the operation of enabling the online portal subscriber to create a subscriber-definable category of online social network members, each with a first degree relationship with the online portal subscriber through the online social network.
| 0.757384 |
7,979,452 | 12 | 13 |
12. A computer program product for retrieving task information as set forth in claim 11 , further comprising instruction means for causing a computer to receive task-descriptive symbols to cause the system to retrieve a document having task information pertaining to the task-descriptive symbols.
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12. A computer program product for retrieving task information as set forth in claim 11 , further comprising instruction means for causing a computer to receive task-descriptive symbols to cause the system to retrieve a document having task information pertaining to the task-descriptive symbols. 13. A computer program product for retrieving task information as set forth in claim 12 , wherein the computer program product is further configured to receive task-descriptive symbols over a computer network.
| 0.5 |
8,773,733 | 1 | 11 |
1. A digital image capture device, comprising: an image sensor for capturing a digital image; an optical system for forming an image of a scene onto the image sensor; a data processing system; a storage memory; and a program memory communicatively connected to the data processing system and storing instructions configured to cause the data processing system to implement a method for extracting textual information from a document containing text characters, wherein the method includes: capturing a plurality of digital images of the document using the image sensor, wherein all of the digital images include substantially the same image content; automatically analyzing each of the captured digital images using an optical character recognition process to determine extracted textual data for each captured digital image; and merging the extracted textual data for the captured digital images to determine the textual information for the document, wherein differences between the extracted textual data for corresponding portions of the captured digital images are analyzed to determine the textual information for corresponding portions of the document; and storing the textual information in the storage memory.
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1. A digital image capture device, comprising: an image sensor for capturing a digital image; an optical system for forming an image of a scene onto the image sensor; a data processing system; a storage memory; and a program memory communicatively connected to the data processing system and storing instructions configured to cause the data processing system to implement a method for extracting textual information from a document containing text characters, wherein the method includes: capturing a plurality of digital images of the document using the image sensor, wherein all of the digital images include substantially the same image content; automatically analyzing each of the captured digital images using an optical character recognition process to determine extracted textual data for each captured digital image; and merging the extracted textual data for the captured digital images to determine the textual information for the document, wherein differences between the extracted textual data for corresponding portions of the captured digital images are analyzed to determine the textual information for corresponding portions of the document; and storing the textual information in the storage memory. 11. The digital image capture device of claim 1 , wherein one or more image capture settings are adjusted between capturing successive digital images.
| 0.905063 |
8,090,620 | 11 | 14 |
11. A computer-implemented method that facilitates searching within an online classifieds site comprising: monitoring updated items posted to the online classifieds site; determining, by a processing unit, that a match is present between at least one updated item and at least a user's geo-tag preferences, wherein the user's geo-tag preferences include at least two separate locations, and wherein the match is based on a detailed location description associated with the at least one updated item; alerting the user that at least one match is determined; and presenting a filtered location description comprising a mapped portion of the detailed location description associated with the at least one updated item to the user, wherein the mapped portion of the detailed location description illustrates a neighborhood associated with the at least one updated item.
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11. A computer-implemented method that facilitates searching within an online classifieds site comprising: monitoring updated items posted to the online classifieds site; determining, by a processing unit, that a match is present between at least one updated item and at least a user's geo-tag preferences, wherein the user's geo-tag preferences include at least two separate locations, and wherein the match is based on a detailed location description associated with the at least one updated item; alerting the user that at least one match is determined; and presenting a filtered location description comprising a mapped portion of the detailed location description associated with the at least one updated item to the user, wherein the mapped portion of the detailed location description illustrates a neighborhood associated with the at least one updated item. 14. The method of claim 11 , further comprising receiving and storing user preferences.
| 0.81087 |
8,443,278 | 1 | 19 |
1. A non-transitory machine readable medium storing a program which when executed by at least one processing unit analyzes a document comprising a plurality of primitive elements, the program comprising sets of instructions for: identifying regions that comprise sets of primitive elements, the regions arranged in a hierarchy such that a first region at a first level of the hierarchy comprising a first set of primitive elements encompasses a second region at a second lower level of the hierarchy comprising a second set of primitive elements, the second set of primitive elements a subset of the first set of primitive elements, the first and second regions linked in the hierarchy; determining that a particular region at a particular level in the hierarchy does not share a border with any linked region at a higher level than the particular level and encompasses at least two additional linked regions at a lower level in the hierarchy than the particular level; identifying the particular region as a table and the encompassed regions as cells of the table; and defining a tabular structural element for the table, the tabular structural element comprising a plurality of cells arranged in a plurality of rows and columns, each cell comprising an associated set of primitive elements.
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1. A non-transitory machine readable medium storing a program which when executed by at least one processing unit analyzes a document comprising a plurality of primitive elements, the program comprising sets of instructions for: identifying regions that comprise sets of primitive elements, the regions arranged in a hierarchy such that a first region at a first level of the hierarchy comprising a first set of primitive elements encompasses a second region at a second lower level of the hierarchy comprising a second set of primitive elements, the second set of primitive elements a subset of the first set of primitive elements, the first and second regions linked in the hierarchy; determining that a particular region at a particular level in the hierarchy does not share a border with any linked region at a higher level than the particular level and encompasses at least two additional linked regions at a lower level in the hierarchy than the particular level; identifying the particular region as a table and the encompassed regions as cells of the table; and defining a tabular structural element for the table, the tabular structural element comprising a plurality of cells arranged in a plurality of rows and columns, each cell comprising an associated set of primitive elements. 19. The non-transitory machine readable medium of claim 1 , wherein the document is a portable document format (PDF) file.
| 0.797342 |
7,702,623 | 14 | 16 |
14. The one or more volatile machine-readable media or non-volatile machine-readable media of claim 11 , wherein the instructions, when executed by the one or more processors, further cause: in response to determining that compiling the current query would not produce an execution plan that satisfies the certain criteria, generating a current cursor for the current query.
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14. The one or more volatile machine-readable media or non-volatile machine-readable media of claim 11 , wherein the instructions, when executed by the one or more processors, further cause: in response to determining that compiling the current query would not produce an execution plan that satisfies the certain criteria, generating a current cursor for the current query. 16. The one or more volatile machine-readable media or non-volatile machine-readable media of claim 14 , wherein the instructions, when executed by the one or more processors, further cause: determining that an execution plan associated with the current cursor does not satisfy the certain criteria; and executing the current query using the current cursor that was generated for the current query.
| 0.5 |
9,134,798 | 14 | 19 |
14. A method comprising: detecting, by a first computing device, a gesture performed on a touch-screen display of the first computing device; determining that the gesture is excluded from a set of gestures stored on the first computing device; requesting a set of user gestures from a second computing device; performing an action corresponding to the gesture based at least partly on the set of user gestures; determining that a second gesture input received from the touch-screen display within a predetermined time period comprises a duplicate gesture, wherein the gesture and the second gesture are sent to a same software application executing on the first computing device; and ignoring the duplicate gesture.
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14. A method comprising: detecting, by a first computing device, a gesture performed on a touch-screen display of the first computing device; determining that the gesture is excluded from a set of gestures stored on the first computing device; requesting a set of user gestures from a second computing device; performing an action corresponding to the gesture based at least partly on the set of user gestures; determining that a second gesture input received from the touch-screen display within a predetermined time period comprises a duplicate gesture, wherein the gesture and the second gesture are sent to a same software application executing on the first computing device; and ignoring the duplicate gesture. 19. The method of claim 14 , further comprising: in response to determining that a fourth gesture is excluded from the set of user gestures, receiving user input selecting a fourth action; associating the fourth action with the fourth gesture; and storing the fourth action and the fourth gesture in the set of user gestures.
| 0.5 |
9,460,076 | 1 | 16 |
1. A method for unsupervised learning of a grammatical parser and the use thereof, wherein the method comprises: providing a processor on a computer, wherein the processor runs a content acquisition system to obtain a corpus of text documents over a computer network; storing the corpus of text documents from the content acquisition system on a storage device; providing a processor on the computer which runs a text analytics engine, wherein the text analytics engine comprise a core algorithm, and a factorization algorithm; using the core algorithm to: divide the corpus of text documents into a plurality of sentences; divide the sentences from the plurality of sentences into a plurality of text units; join the text units from the plurality of text units into a plurality of grammatical links; and using the factorization algorithm to factorize a matrix or a tensor for each of the grammatical links of the plurality of grammatical links to respectively generate a plurality of factorized matrices or a plurality of factorized tensors; and additionally using the core algorithm to: generate parses from a corpus of a novel document, comprising: divide the corpus from the novel document into a plurality of sentences; divide the sentences from the plurality of sentences from the novel document into a plurality of text units; identify a subset of all possible grammatical links from the plurality of text units from the novel document; and determine the relative likelihood of the grammatical links in the corpus of the novel document by using the factorized matrices or the factorized tensors to compute a score representing the likelihood of the grammatical links.
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1. A method for unsupervised learning of a grammatical parser and the use thereof, wherein the method comprises: providing a processor on a computer, wherein the processor runs a content acquisition system to obtain a corpus of text documents over a computer network; storing the corpus of text documents from the content acquisition system on a storage device; providing a processor on the computer which runs a text analytics engine, wherein the text analytics engine comprise a core algorithm, and a factorization algorithm; using the core algorithm to: divide the corpus of text documents into a plurality of sentences; divide the sentences from the plurality of sentences into a plurality of text units; join the text units from the plurality of text units into a plurality of grammatical links; and using the factorization algorithm to factorize a matrix or a tensor for each of the grammatical links of the plurality of grammatical links to respectively generate a plurality of factorized matrices or a plurality of factorized tensors; and additionally using the core algorithm to: generate parses from a corpus of a novel document, comprising: divide the corpus from the novel document into a plurality of sentences; divide the sentences from the plurality of sentences from the novel document into a plurality of text units; identify a subset of all possible grammatical links from the plurality of text units from the novel document; and determine the relative likelihood of the grammatical links in the corpus of the novel document by using the factorized matrices or the factorized tensors to compute a score representing the likelihood of the grammatical links. 16. The method of claim 1 , further comprising sorting the corpus of text documents into individual document classes, and generating a factorized matrix or a factorized tensor from each of the individual document classes, sorting the corpus of the novel document into individual document classes, and using the factorized matrix or the factorized tensor generated from each of the individual document classes to parse the novel document.
| 0.5 |
9,736,488 | 8 | 10 |
8. The method of claim 1 , further comprising: parsing, performed by a third parser processor, a second full row of coding blocks of the same plurality of coding blocks of the picture in the raster scan order by using the list of identified coding blocks and the plurality of subsets of entropy coding state data stored in the data repository to produce a second portion of the parsed video bitstream, wherein the second full row is a neighboring row of a first full row parsed by the second processor, the parsing of the second full row by the third parser processor begins after the second parser processor has parsed a first and second coding block in the first full row, and the parsing by the third parser processor continues in parallel with the parsing by the second parser processor; and parsing, performed by the second parser processor, a third full row of coding blocks of the same plurality of coding blocks in the raster scan order to produce a third portion of the parsed video bitstream, wherein the third full row is a neighboring row of the second full row, the parsing of the third full row by the second parser processor begins after the third parser processor has parsed a first and second coding block in the second full row, and the parsing by the second parser processor continues in parallel with the parsing by the third parser processor.
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8. The method of claim 1 , further comprising: parsing, performed by a third parser processor, a second full row of coding blocks of the same plurality of coding blocks of the picture in the raster scan order by using the list of identified coding blocks and the plurality of subsets of entropy coding state data stored in the data repository to produce a second portion of the parsed video bitstream, wherein the second full row is a neighboring row of a first full row parsed by the second processor, the parsing of the second full row by the third parser processor begins after the second parser processor has parsed a first and second coding block in the first full row, and the parsing by the third parser processor continues in parallel with the parsing by the second parser processor; and parsing, performed by the second parser processor, a third full row of coding blocks of the same plurality of coding blocks in the raster scan order to produce a third portion of the parsed video bitstream, wherein the third full row is a neighboring row of the second full row, the parsing of the third full row by the second parser processor begins after the third parser processor has parsed a first and second coding block in the second full row, and the parsing by the second parser processor continues in parallel with the parsing by the third parser processor. 10. The method of claim 8 , wherein the second parser processor and the third parser processor continue to parse neighboring full rows in an alternating manner until all full rows of the picture are parsed in the raster scan order.
| 0.692 |
9,032,338 | 1 | 5 |
1. An electronic device, comprising: a display; a touch-sensitive surface; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying text of an electronic document on the display; displaying an insertion marker at a first position in the text of the electronic document; detecting a first horizontal gesture at a location on the touch-sensitive surface, the location on the touch-sensitive surface corresponding to a location on the display where the text of the electronic document is displayed; in response to a determination that the first horizontal gesture at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a first set of one or more predefined conditions: translating the electronic document on the display in accordance with a direction of the first horizontal gesture, and maintaining the insertion marker at the first position in the text; and, in response to a determination that the first horizontal gesture at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a second set of one or more predefined conditions that is distinct from the first set of one or more predefined conditions, moving the insertion marker by one character in the text from the first position to a second position in the text in accordance with the direction of the first horizontal gesture.
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1. An electronic device, comprising: a display; a touch-sensitive surface; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying text of an electronic document on the display; displaying an insertion marker at a first position in the text of the electronic document; detecting a first horizontal gesture at a location on the touch-sensitive surface, the location on the touch-sensitive surface corresponding to a location on the display where the text of the electronic document is displayed; in response to a determination that the first horizontal gesture at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a first set of one or more predefined conditions: translating the electronic document on the display in accordance with a direction of the first horizontal gesture, and maintaining the insertion marker at the first position in the text; and, in response to a determination that the first horizontal gesture at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a second set of one or more predefined conditions that is distinct from the first set of one or more predefined conditions, moving the insertion marker by one character in the text from the first position to a second position in the text in accordance with the direction of the first horizontal gesture. 5. The device of claim 1 , including instructions for: while displaying the insertion marker at the second position in the text of the electronic document: detecting a vertical gesture on the touch-sensitive surface; in response to a determination that the vertical gesture satisfies a third set of one or more predefined conditions: translating the electronic document on the display in accordance with a direction of the vertical gesture, and maintaining the insertion marker at the second position in the text; and, in response to a determination that the vertical gesture satisfies a fourth set of one or more predefined conditions that is distinct from the third set of one or more predefined conditions, moving the insertion marker from a line in the text containing the second position to a vertically adjacent line in the text in accordance with the direction of the vertical gesture.
| 0.5 |
8,364,690 | 1 | 7 |
1. A method for managing Resource Description Framework (“RDF”) graphs in a distributed system, the method on a client information processing system comprising: receiving at least one modification request for modifying an RDF graph in a shared data store, wherein the modification request includes at least one precondition query created based on a change set generated on a local shared data store associated with the shared data store, an expected result set, and the change set, wherein the precondition query comprises a set of preconditions that test a state of the RDF graph before executing the change set, wherein at least one precondition in the set of preconditions is based on a state of the local shared data store prior to the change set being applied at the local data store, wherein the expected result set is a set of results expected by the precondition query in response to applying the set of preconditions to the RDF graph, and wherein the change set is at least one statement that changes a set of data elements in the RDF graph; applying the precondition query to the RDF graph at the shared data store; analyzing a set of results of the precondition query; and sending, in response to the set of results of the precondition query matching the expected result set, a transaction request associated with the modification request to a server information processing system communicatively coupled to the shared data storage, wherein the transaction request comprises the change set.
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1. A method for managing Resource Description Framework (“RDF”) graphs in a distributed system, the method on a client information processing system comprising: receiving at least one modification request for modifying an RDF graph in a shared data store, wherein the modification request includes at least one precondition query created based on a change set generated on a local shared data store associated with the shared data store, an expected result set, and the change set, wherein the precondition query comprises a set of preconditions that test a state of the RDF graph before executing the change set, wherein at least one precondition in the set of preconditions is based on a state of the local shared data store prior to the change set being applied at the local data store, wherein the expected result set is a set of results expected by the precondition query in response to applying the set of preconditions to the RDF graph, and wherein the change set is at least one statement that changes a set of data elements in the RDF graph; applying the precondition query to the RDF graph at the shared data store; analyzing a set of results of the precondition query; and sending, in response to the set of results of the precondition query matching the expected result set, a transaction request associated with the modification request to a server information processing system communicatively coupled to the shared data storage, wherein the transaction request comprises the change set. 7. The method of claim 1 , further comprising: notifying, in response to the set of results of the precondition query failing to match the expected result set, a user associated with the at least one modification set that a data conflict has been detected.
| 0.5 |
7,587,309 | 47 | 48 |
47. A system according to claim 46 , further comprising: a description identifier to retrieve a description from the item description and to supplement the advertising creative with the description subject to space restrictions.
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47. A system according to claim 46 , further comprising: a description identifier to retrieve a description from the item description and to supplement the advertising creative with the description subject to space restrictions. 48. A system according to claim 47 , further comprising: a description summarizer to summarize the description.
| 0.5 |
8,610,755 | 10 | 14 |
10. A method for enabling electronic communication between a hearing-capable user and a hearing-impaired user, comprising: selecting an identified entry from a database comprising one or more entries, wherein each of the one or more entries is associated with a contact of the hearing-impaired user and includes one or more connection indicators for the contact and one or more spoken languages for the contact, and the identified entry is selected responsive to the one or more connection indicators for the hearing-capable user; routing a calling connection from the hearing-capable user to a translator capable in a gesture language and the one or more spoken languages of the hearing-capable user; and establishing a video-capable connection between the translator and the hearing-impaired user over a video-capable network.
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10. A method for enabling electronic communication between a hearing-capable user and a hearing-impaired user, comprising: selecting an identified entry from a database comprising one or more entries, wherein each of the one or more entries is associated with a contact of the hearing-impaired user and includes one or more connection indicators for the contact and one or more spoken languages for the contact, and the identified entry is selected responsive to the one or more connection indicators for the hearing-capable user; routing a calling connection from the hearing-capable user to a translator capable in a gesture language and the one or more spoken languages of the hearing-capable user; and establishing a video-capable connection between the translator and the hearing-impaired user over a video-capable network. 14. The method of claim 10 , wherein establishing the voice-capable connection is selected from the group consisting of establishing an Internet connection and establishing a connection to a public switched telephone network.
| 0.608014 |
9,299,339 | 6 | 7 |
6. The computer-implemented method of claim 1 , wherein determining the co-occurrence measure for the first input sentence comprises: grouping second input sentences that are determined to be similar to each other; grouping, from the identified pairs of first and second input sentences that include a second input sentence belonging to the group of second input sentences, first input sentences that are determined to be similar to each other; and determining that a cardinality of the group of first input sentences meets a threshold cardinality.
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6. The computer-implemented method of claim 1 , wherein determining the co-occurrence measure for the first input sentence comprises: grouping second input sentences that are determined to be similar to each other; grouping, from the identified pairs of first and second input sentences that include a second input sentence belonging to the group of second input sentences, first input sentences that are determined to be similar to each other; and determining that a cardinality of the group of first input sentences meets a threshold cardinality. 7. The computer-implemented method of claim 6 , wherein grouping second input sentences that are determined to be similar to each other comprises grouping second input sentences that are successfully parsed by a same rule.
| 0.54878 |
7,917,847 | 51 | 52 |
51. The terminal device according to claim 49 , wherein the controller further performs a function of judging whether or not predetermined user operation is performed, wherein the predetermined user operation includes operation for canceling the switching of the onscreen representation, and wherein the switching of the onscreen representation is cancelled if it is judged by the judging that the predetermined user operation is performed, and the switching of the onscreen representation is performed if it is judged by the judging that the predetermined user operation is not performed.
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51. The terminal device according to claim 49 , wherein the controller further performs a function of judging whether or not predetermined user operation is performed, wherein the predetermined user operation includes operation for canceling the switching of the onscreen representation, and wherein the switching of the onscreen representation is cancelled if it is judged by the judging that the predetermined user operation is performed, and the switching of the onscreen representation is performed if it is judged by the judging that the predetermined user operation is not performed. 52. The terminal device according to claim 51 , wherein the switching is controlled in three stages including a first stage from a start of the obtaining operation of the page to a time of completion of acquisition of text data of the page, a second stage from the time of the completion of acquisition of the text data of the page to a time of completion of acquisition of the definition information, and a third stage after the completion of acquisition of the definition information, and wherein the onscreen representation in the first browsing mode is made during the first stage, notification notifying execution of the switching is added to the onscreen representation in the first browsing mode during the second stage, and the onscreen representation in which the definition information is applied is made during the third stage if the predetermined user operation is not performed.
| 0.5 |
9,020,866 | 11 | 13 |
11. A computing device, comprising: at least one processor; and memory including instructions that, when executed by the processor, cause the computing device to: train a first ranking function that uses online data computed at a time of receiving a search request and stored in an index to produce a first ranking score for an item among a plurality of items, the online data includes a set of search results including at least information about a product; train a second ranking function to produce a second ranking score for the item, the second ranking function trained using a boost method, the second ranking function using offline data unavailable in the index in combination with the first ranking score produced by the first ranking function; and rank the item among a plurality of items based at least in part on both the first ranking score and the second ranking score, the item is the product in a database of products accessible on a network, wherein ranking the item is performed to determine a relevance of the item among the search results in a context of the search request.
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11. A computing device, comprising: at least one processor; and memory including instructions that, when executed by the processor, cause the computing device to: train a first ranking function that uses online data computed at a time of receiving a search request and stored in an index to produce a first ranking score for an item among a plurality of items, the online data includes a set of search results including at least information about a product; train a second ranking function to produce a second ranking score for the item, the second ranking function trained using a boost method, the second ranking function using offline data unavailable in the index in combination with the first ranking score produced by the first ranking function; and rank the item among a plurality of items based at least in part on both the first ranking score and the second ranking score, the item is the product in a database of products accessible on a network, wherein ranking the item is performed to determine a relevance of the item among the search results in a context of the search request. 13. The computing device of claim 11 , wherein the boosting method is a gradient boosting method.
| 0.858601 |
7,703,024 | 1 | 2 |
1. A computer-implemented method comprising: requesting access to a remote computing system from a local computing system, the remote computing system having a message server to service messages formulated according to a messaging protocol, wherein requesting access includes querying the message server of the remote computing system to identify and obtain a Graphical User Interface (GUI) with which to access the remote computing system, the querying including sending a message to the message server of the remote computing system, the message including a location indicator to specify a location of another local computing system from which the local computer system can download the identified GUI using a fast connection; receiving in the local computing system connection information from the message server of the remote computing system responsive to requesting access, the received connection information to identify and instruct how to obtain the GUI with which to access the remote computing system, the receiving including receiving a return of the message from the message server, the message server having overwritten a GUI version indicator into the message to specify a version of the identified GUI for accessing the remote computing system; forwarding the received connection information from the local computing system to the other local computing system from which the identified GUI can be downloaded to the local computing system using the fast connection, based, at least in part, on the received connection information to identify and instruct how to obtain the GUI, the forwarding including sending to the other local computing system the returned message containing the GUI version indicator using the location indicator included in the message, the location indicator specifying the location of the other local computing system, the other local computing system having a code base for generating a file describing the identified GUI based, at least in part, on the returned message; receiving from the other local computing system a Java Network Launching Protocol (JNLP) file describing the identified GUI corresponding to the GUI version indicator, wherein the code base for generating the file generates the JNLP file; downloading the identified GUI to the local computing system from the other local computing system using the fast connection, the downloading based, at least in part, on the received connection information to identify and instruct how to obtain the identified GUI; and accessing the remote computing system via the identified GUI.
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1. A computer-implemented method comprising: requesting access to a remote computing system from a local computing system, the remote computing system having a message server to service messages formulated according to a messaging protocol, wherein requesting access includes querying the message server of the remote computing system to identify and obtain a Graphical User Interface (GUI) with which to access the remote computing system, the querying including sending a message to the message server of the remote computing system, the message including a location indicator to specify a location of another local computing system from which the local computer system can download the identified GUI using a fast connection; receiving in the local computing system connection information from the message server of the remote computing system responsive to requesting access, the received connection information to identify and instruct how to obtain the GUI with which to access the remote computing system, the receiving including receiving a return of the message from the message server, the message server having overwritten a GUI version indicator into the message to specify a version of the identified GUI for accessing the remote computing system; forwarding the received connection information from the local computing system to the other local computing system from which the identified GUI can be downloaded to the local computing system using the fast connection, based, at least in part, on the received connection information to identify and instruct how to obtain the GUI, the forwarding including sending to the other local computing system the returned message containing the GUI version indicator using the location indicator included in the message, the location indicator specifying the location of the other local computing system, the other local computing system having a code base for generating a file describing the identified GUI based, at least in part, on the returned message; receiving from the other local computing system a Java Network Launching Protocol (JNLP) file describing the identified GUI corresponding to the GUI version indicator, wherein the code base for generating the file generates the JNLP file; downloading the identified GUI to the local computing system from the other local computing system using the fast connection, the downloading based, at least in part, on the received connection information to identify and instruct how to obtain the identified GUI; and accessing the remote computing system via the identified GUI. 2. The computer-implemented method of claim 1 , wherein requesting access to the remote computing system further comprises: receiving input selecting a hyperlink displayed in a browser of the local computer system, the hyperlink representing the remote computing system.
| 0.684579 |
9,483,518 | 7 | 12 |
7. One or more computer-readable hardware storage devices storing instructions that, when executed by a processor, configure the processor to perform acts that generate a combined display of presented content and contextually-related search results, comprising: detecting a single search indication comprising an action performed by a user on a user device while media content is being presented via one or more of a webpage or a television program on the user device, wherein the single search indication A) captures, on the user device, media content being presented on the user device, B) defines a search scope corresponding to only a portion of the media content being presented, wherein the portion of the media content being presented comprises a region of content defined by the single search indication, C) includes a specific item of interest within the content being presented, and D) initiates a search related to the media content being presented; in response to detecting the single search indication, automatically obtaining contextual information related to the media content at or near detection of the single search indication; automatically communicating the contextual information at least to a remote search service that formulates a query based on the contextual information; and receiving one or more search results related to the obtained contextual information related to the media content; and modifying a display of the presented content on the user device, such that the one or more search results are presented on the user device with the content.
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7. One or more computer-readable hardware storage devices storing instructions that, when executed by a processor, configure the processor to perform acts that generate a combined display of presented content and contextually-related search results, comprising: detecting a single search indication comprising an action performed by a user on a user device while media content is being presented via one or more of a webpage or a television program on the user device, wherein the single search indication A) captures, on the user device, media content being presented on the user device, B) defines a search scope corresponding to only a portion of the media content being presented, wherein the portion of the media content being presented comprises a region of content defined by the single search indication, C) includes a specific item of interest within the content being presented, and D) initiates a search related to the media content being presented; in response to detecting the single search indication, automatically obtaining contextual information related to the media content at or near detection of the single search indication; automatically communicating the contextual information at least to a remote search service that formulates a query based on the contextual information; and receiving one or more search results related to the obtained contextual information related to the media content; and modifying a display of the presented content on the user device, such that the one or more search results are presented on the user device with the content. 12. The devices of claim 7 , wherein the contextual information comprises at least user activity associated with a remote user device.
| 0.815427 |
8,078,554 | 2 | 3 |
2. The system of claim 1 wherein the graphical model comprises a Bayesian network with links from a tumor load node to a T-stage node, a N-stage, and a survival node, from the T-stage node to a number of lymph node stations node, from the N-stage node to the number of lymph node stations node, from a WHO score node to the survival node, and from the number of lymph node stations node to the survival node.
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2. The system of claim 1 wherein the graphical model comprises a Bayesian network with links from a tumor load node to a T-stage node, a N-stage, and a survival node, from the T-stage node to a number of lymph node stations node, from the N-stage node to the number of lymph node stations node, from a WHO score node to the survival node, and from the number of lymph node stations node to the survival node. 3. The system of claim 2 wherein the graphical representation shows the nodes and the links.
| 0.5 |
9,514,118 | 10 | 13 |
10. A system for database implementation of electronic checklists, the system comprising: a processor; a template editor controller configured to: display at a user interface, a first electronic checklist template within a template editor define a modified electronic checklist template, wherein the modified electronic checklist template comprises the first electronic checklist template modified based on inputs received at the template editor; an electronic checklist application controller configured to generate a database implemented electronic checklist template, the database implemented electronic checklist template comprising: a markup language encoding of the modified electronic checklist template; and at least one system controlled column, wherein data input within data fields of the at least one system controlled column is determined by: one or more system information parameters; and one or more predefined rules of system behaviour associated with the at least one system controlled column.
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10. A system for database implementation of electronic checklists, the system comprising: a processor; a template editor controller configured to: display at a user interface, a first electronic checklist template within a template editor define a modified electronic checklist template, wherein the modified electronic checklist template comprises the first electronic checklist template modified based on inputs received at the template editor; an electronic checklist application controller configured to generate a database implemented electronic checklist template, the database implemented electronic checklist template comprising: a markup language encoding of the modified electronic checklist template; and at least one system controlled column, wherein data input within data fields of the at least one system controlled column is determined by: one or more system information parameters; and one or more predefined rules of system behaviour associated with the at least one system controlled column. 13. The system according to claim 10 , wherein the electronic checklist application controller is configured to: parse content of the modified electronic checklist template; generate a markup language encoded checklist template comprising columns and column descriptors corresponding to columns and column descriptors parsed from the modified electronic checklist template; and for each checklist item parsed from the modified electronic checklist template, add a template row to the markup language encoded checklist template and populate the added template row with data fields extracted from the parsed checklist item.
| 0.635563 |
9,123,259 | 15 | 16 |
15. The method of claim 14 , wherein the topic model framework uses the section as a document, uses each function of the distribution of functions as a topic, uses the mobility patterns as words, and uses a point of interest (POI) feature vector of the POIs in the section as metadata.
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15. The method of claim 14 , wherein the topic model framework uses the section as a document, uses each function of the distribution of functions as a topic, uses the mobility patterns as words, and uses a point of interest (POI) feature vector of the POIs in the section as metadata. 16. The method of claim 15 , wherein the POI feature vector is based at least in part on calculating a frequency density of each of a plurality of POI categories.
| 0.5 |
8,768,693 | 1 | 12 |
1. A method comprising: receiving, by a server computer, an image file captured by a client device, the image file comprising an associated audio component, the audio component spoken by a user of the client device as a tag of the image file; determining, by the server computer, metadata associated with the image file; identifying, by the server computer, a dictionary of potential textual tags from the metadata; determining, by the server computer, a textual tag from the audio component using the dictionary of potential textual tags in conjunction with speech-to-text technology; and associating, by the server computer, the textual tag with the image file as additional metadata.
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1. A method comprising: receiving, by a server computer, an image file captured by a client device, the image file comprising an associated audio component, the audio component spoken by a user of the client device as a tag of the image file; determining, by the server computer, metadata associated with the image file; identifying, by the server computer, a dictionary of potential textual tags from the metadata; determining, by the server computer, a textual tag from the audio component using the dictionary of potential textual tags in conjunction with speech-to-text technology; and associating, by the server computer, the textual tag with the image file as additional metadata. 12. The method of claim 1 , further comprising enabling playing of the audio component at one or more of the client device and a digital photograph web site.
| 0.651111 |
7,890,928 | 3 | 6 |
3. A system, stored in a non-transitory computer readable medium, called Knowledge Base System (KB), including computer usable program code for processing static or dynamic information, wherein, fields which represent an atomic entity, or an object or a structure, are adorned with special attributes called colors, which imply variations, and a special type of entity called conceptual class, which is a sequence of tags separated by dot characters, and implies, a logical grouping of fields, and wherein, fields of rules or equations are represented using special field names called KB fields, which are a sequence of class names and field names, and are adorned with said colors, and wherein, said class names of said KB fields may be represented by said conceptual classes, such that said KB fields in said rules are parametric with respect to said colors and said conceptual classes, and may be specialized based on application requirement, comprises: a) A tool called KB translator, Means for translating—said field descriptions, utilizing said colors and said conceptual classes, which are contained in said collaboration object descriptions, and, said rules in method descriptions, wherein said rules contain uniquely identifiable tags called KB prefixes and commands, to equivalent statements of a predetermined host language; b) A plurality of tables called KB tables, Means for storing—predefined configurations and associations, of said colors and said conceptual classes; c) A plurality of modules called KB Runtime, Means for supporting code generated by said KB Translator, for said rules, for a predefined host language; d) Means for storing State-Noun mappings of said fields of said objects in a predefined table called State-Noun mapping table; e) Means for storing State-Noun mappings of said fields specified in said rules, in a predefined table called working State-Noun mapping table; f) Means for storing conceptual class mappings in a table called Indirect Conceptual class table; g) Means for storing navigation paths of an object, and an array of sequence numbers, made up of depth first traversal sequence numbers of iteratable structures within the object, and the associated auxiliary verb colors; h) Means for storing the KB field names associated with temporary variables, and the collaboration object id, in whose method the temporary variable is created, in a table called the Symbol table; i) Means for storing the value of the temporary variable, the noun value, the reference of the object, which can determine the noun, called noun container, the class name of the said noun container, the field name, in a table called the value table; j) Means for storing the associations between the verb on the left hand side of the equation, with the verbs on the right hand side of the equation, in a table called the verb distribution table; k) Means for storing the association between said special color and an object and method, along with its return type, in a table called the special color table; l) Means for storing the association between said constant color function and the value of the verb, from which the said constant color function maps, and the value of the verb, to which the said constant color function maps, as a table called the constant color table; m) Means for storing the association between said constant source function and the value of the source, from which the said constant source function maps, and the value of the source, to which the said constant source function maps, as a table called the constant source table; n) Means for storing the association between the field specified on the left hand side of the equation and the expression specified on the right hand side of the equation, along with an identifier called the type of the equation, an optional conditional equation, called the guard, and an optional structural rule, in a table called the rules table.
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3. A system, stored in a non-transitory computer readable medium, called Knowledge Base System (KB), including computer usable program code for processing static or dynamic information, wherein, fields which represent an atomic entity, or an object or a structure, are adorned with special attributes called colors, which imply variations, and a special type of entity called conceptual class, which is a sequence of tags separated by dot characters, and implies, a logical grouping of fields, and wherein, fields of rules or equations are represented using special field names called KB fields, which are a sequence of class names and field names, and are adorned with said colors, and wherein, said class names of said KB fields may be represented by said conceptual classes, such that said KB fields in said rules are parametric with respect to said colors and said conceptual classes, and may be specialized based on application requirement, comprises: a) A tool called KB translator, Means for translating—said field descriptions, utilizing said colors and said conceptual classes, which are contained in said collaboration object descriptions, and, said rules in method descriptions, wherein said rules contain uniquely identifiable tags called KB prefixes and commands, to equivalent statements of a predetermined host language; b) A plurality of tables called KB tables, Means for storing—predefined configurations and associations, of said colors and said conceptual classes; c) A plurality of modules called KB Runtime, Means for supporting code generated by said KB Translator, for said rules, for a predefined host language; d) Means for storing State-Noun mappings of said fields of said objects in a predefined table called State-Noun mapping table; e) Means for storing State-Noun mappings of said fields specified in said rules, in a predefined table called working State-Noun mapping table; f) Means for storing conceptual class mappings in a table called Indirect Conceptual class table; g) Means for storing navigation paths of an object, and an array of sequence numbers, made up of depth first traversal sequence numbers of iteratable structures within the object, and the associated auxiliary verb colors; h) Means for storing the KB field names associated with temporary variables, and the collaboration object id, in whose method the temporary variable is created, in a table called the Symbol table; i) Means for storing the value of the temporary variable, the noun value, the reference of the object, which can determine the noun, called noun container, the class name of the said noun container, the field name, in a table called the value table; j) Means for storing the associations between the verb on the left hand side of the equation, with the verbs on the right hand side of the equation, in a table called the verb distribution table; k) Means for storing the association between said special color and an object and method, along with its return type, in a table called the special color table; l) Means for storing the association between said constant color function and the value of the verb, from which the said constant color function maps, and the value of the verb, to which the said constant color function maps, as a table called the constant color table; m) Means for storing the association between said constant source function and the value of the source, from which the said constant source function maps, and the value of the source, to which the said constant source function maps, as a table called the constant source table; n) Means for storing the association between the field specified on the left hand side of the equation and the expression specified on the right hand side of the equation, along with an identifier called the type of the equation, an optional conditional equation, called the guard, and an optional structural rule, in a table called the rules table. 6. The system of claim 3 , further comprises: a) means for receiving as input, an XML document called collaboration descriptor, wherein— a set of objects called collaboration objects, are described, such that the chronological sequence number of the collaboration objects called collaboration object id, may be used for uniquely identifying the objects, and wherein, each collaboration object provides a table called the auxiliary verb table, which contains the associations of the auxiliary verbs and navigation paths, and wherein, each collaboration object creates and provides access to a set of vectors for navigation node and navigation index vectors, and wherein, a set of methods on said collaboration objects, are organized as groups, called collaboration cycles, such that each collaboration method is uniquely identifiable with a pair of numbers called cycle number and cycle order number, and wherein, each said collaboration cycle may be structured by said structural rule, and wherein, each collaboration method may specify, any valid permutation of a subset of said collaboration objects, as its view of said application context, called collaboration sequence, such that, said KB fields contained in said rules invoked from said collaboration methods, may be searched in the said collaboration sequence; b) means for analyzing said rules embedded in said collaboration methods, and identifying said KB commands; c) means for translating said KB commands, wherein said KB commands in said collaboration method, are commented out after translation, and are replaced by method calls to helper methods in a helper class, and wherein, said helper method in said helper class is invoked via an interface, which is a collection of method signatures, such that the generated method invocation is generic over a set of helper methods, which may exist in plurality for any of said KB commands, whenever, the said collaboration method being translated exists in different collaboration descriptors, or cycles or cycle orders.
| 0.72043 |
9,195,635 | 14 | 18 |
14. A system for visualizing content change of a data collection over time, comprising: a processor; a document pre-processing module operable to execute on the processor, and further operable to extract text and associated meta data from a collection of documents; a topic summarization module operable to automatically extract a set of topics based on the extracted text and associated meta data; a topic segmentation module operable to split a topic in the set of topics into multiple, non-overlapping temporal segments, wherein content for visualization is generated; and a text visualization module operable to generate a time-based, interactive visual text summary based on the content, wherein the topic segmentation module is operable to generate temporal and visual constraints, the topic segmentation module further operable to derive from the collection of documents a set of document clusters that satisfy the temporal and visual constraints, a document cluster in the set of document clusters identified with a sub-topic, the topic segmentation module further operable to determine a temporal segment boundary associated with said document cluster, wherein the temporal segment boundary identifies a temporal segment for the sub-topic, the topic segmentation module further operable to select a set of representative keywords from the document cluster to summarize the temporal segment.
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14. A system for visualizing content change of a data collection over time, comprising: a processor; a document pre-processing module operable to execute on the processor, and further operable to extract text and associated meta data from a collection of documents; a topic summarization module operable to automatically extract a set of topics based on the extracted text and associated meta data; a topic segmentation module operable to split a topic in the set of topics into multiple, non-overlapping temporal segments, wherein content for visualization is generated; and a text visualization module operable to generate a time-based, interactive visual text summary based on the content, wherein the topic segmentation module is operable to generate temporal and visual constraints, the topic segmentation module further operable to derive from the collection of documents a set of document clusters that satisfy the temporal and visual constraints, a document cluster in the set of document clusters identified with a sub-topic, the topic segmentation module further operable to determine a temporal segment boundary associated with said document cluster, wherein the temporal segment boundary identifies a temporal segment for the sub-topic, the topic segmentation module further operable to select a set of representative keywords from the document cluster to summarize the temporal segment. 18. The system of claim 14 , wherein the topic segmentation module determines a temporal segment boundary by at least: sorting all documents in the set of document clusters on a timeline based on time stamps associated with the documents; employing a sliding window of size N to examine N documents at a time; identifying one or more documents from the examined documents whose cluster labels do not conform to a main cluster; and reassigning the identified one or more documents to the main cluster within the sliding window, wherein the temporal boundary is determined in response to identifying a change of cluster labels between two adjacent documents on the time line.
| 0.5 |
8,819,812 | 7 | 8 |
7. A computer-implemented method, comprising: under control of one or more computing devices including executable instructions, acquiring image information from at least one image captured using at least one image sensor of a computing device, the image information being stored for a duration of time on a rolling basis; analyzing the image information to detect a hand gesture performed by a user; determining, in the image information, movement of one or more fingers, the movement corresponding to a first portion of a candidate hand gesture; analyzing the image information stored for the duration of time to detect a second portion of the candidate hand gesture; comparing the first portion of the candidate hand gesture and the second portion of the candidate hand gesture to at least one gesture associated with the user, the second portion of the candidate hand gesture having been performed before the first portion; and providing an input to an application executing on the computing device in response to the first portion of the candidate hand gesture and the second portion of the candidate hand gesture being determined to correspond to the at least one gesture associated with the user, the at least one gesture associated with the user being specific to the user for providing the input to the application.
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7. A computer-implemented method, comprising: under control of one or more computing devices including executable instructions, acquiring image information from at least one image captured using at least one image sensor of a computing device, the image information being stored for a duration of time on a rolling basis; analyzing the image information to detect a hand gesture performed by a user; determining, in the image information, movement of one or more fingers, the movement corresponding to a first portion of a candidate hand gesture; analyzing the image information stored for the duration of time to detect a second portion of the candidate hand gesture; comparing the first portion of the candidate hand gesture and the second portion of the candidate hand gesture to at least one gesture associated with the user, the second portion of the candidate hand gesture having been performed before the first portion; and providing an input to an application executing on the computing device in response to the first portion of the candidate hand gesture and the second portion of the candidate hand gesture being determined to correspond to the at least one gesture associated with the user, the at least one gesture associated with the user being specific to the user for providing the input to the application. 8. The computer-implemented method of claim 7 , wherein the at least one gesture associated with the user is one of a plurality of gestures stored on the computing device.
| 0.760504 |
9,037,452 | 19 | 22 |
19. A non-transitory computer readable storage medium readable by a computerized device, said non-transitory computer readable storage medium storing instructions executable by said computerized device to perform a method comprising: method comprising: automatically collecting training data from manually created semantic relations; automatically extracting rules from said training data to produce extracted rules, said extracting rules comprising automatically removing noisy data from said semantic relations by filtering out ones of rules that do not occur in said training data; automatically characterizing existing semantic relations in said training data based on co-occurrence of said extracted rules in said existing semantic relations; automatically constructing semantic relation topics based on said characterizing of said existing semantic relations; and grouping instances of said training data into said semantic relation topics to detect new semantic relations.
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19. A non-transitory computer readable storage medium readable by a computerized device, said non-transitory computer readable storage medium storing instructions executable by said computerized device to perform a method comprising: method comprising: automatically collecting training data from manually created semantic relations; automatically extracting rules from said training data to produce extracted rules, said extracting rules comprising automatically removing noisy data from said semantic relations by filtering out ones of rules that do not occur in said training data; automatically characterizing existing semantic relations in said training data based on co-occurrence of said extracted rules in said existing semantic relations; automatically constructing semantic relation topics based on said characterizing of said existing semantic relations; and grouping instances of said training data into said semantic relation topics to detect new semantic relations. 22. The non-transitory computer readable storage medium according to claim 19 , said characterizing of said existing semantic relations in said training data being based on a number of said extracted rules that are shared between corresponding ones of said existing semantic relations.
| 0.740437 |
4,204,343 | 1 | 3 |
1. A reading skills development kit comprising: (a) a background; (b) at least one permanent first phoneme set fixedly disposed on said background, being at least one phoneme and forming a portion of a word; (c) a different series of elements providing interchangeable second phoneme sets associated with each of said at least one first phoneme sets, each second phoneme set being at least one phoneme and forming an intelligible word with said at least one first phoneme set; (d) means on said background for selectively exposing said second phoneme sets, one at a time, adjacent their associated at least one first phoneme set to create different intelligible words that include said at least one first phoneme set; (e) said at least one first phoneme set having the same sound in each of said words so formed; and (f) coding means associated with said first and second phoneme sets to identify that series of interchangeable second phoneme sets singularly associated with said at least one permanent first phoneme set to indicate erroneous association of a particular interchangeable second phoneme set with a particular at least one permanent first phoneme set.
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1. A reading skills development kit comprising: (a) a background; (b) at least one permanent first phoneme set fixedly disposed on said background, being at least one phoneme and forming a portion of a word; (c) a different series of elements providing interchangeable second phoneme sets associated with each of said at least one first phoneme sets, each second phoneme set being at least one phoneme and forming an intelligible word with said at least one first phoneme set; (d) means on said background for selectively exposing said second phoneme sets, one at a time, adjacent their associated at least one first phoneme set to create different intelligible words that include said at least one first phoneme set; (e) said at least one first phoneme set having the same sound in each of said words so formed; and (f) coding means associated with said first and second phoneme sets to identify that series of interchangeable second phoneme sets singularly associated with said at least one permanent first phoneme set to indicate erroneous association of a particular interchangeable second phoneme set with a particular at least one permanent first phoneme set. 3. A reading skills development kit in accordance with claim 1 wherein each of said at least one permanent first phoneme sets forms the initial portion of a word, and each of said interchangeable second phoneme sets forms the terminal portion of a word.
| 0.711845 |
8,341,173 | 4 | 5 |
4. The method according to claim 2 , further comprising: configuring a relational graph from data in the form of instance role with respect to said named individual and said canonical individual according to said original data and said converted explicit data, and data in the form of instance type with respect to said canonical individual according to said original data and said converted explicit data; traversing said relational graph and computing a base path starting from said named individual and ending at said canonical individual according to said original data and said converted explicit data; and storing said base path in the form of triples of said base path, a tail of said base path, and nodes directly or indirectly located in said base path.
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4. The method according to claim 2 , further comprising: configuring a relational graph from data in the form of instance role with respect to said named individual and said canonical individual according to said original data and said converted explicit data, and data in the form of instance type with respect to said canonical individual according to said original data and said converted explicit data; traversing said relational graph and computing a base path starting from said named individual and ending at said canonical individual according to said original data and said converted explicit data; and storing said base path in the form of triples of said base path, a tail of said base path, and nodes directly or indirectly located in said base path. 5. The method according to claim 4 , wherein said node indirectly located in said base path is a named individual having a relationship in the form of instance role with said named individual from which said base path starts.
| 0.5 |
9,514,130 | 11 | 12 |
11. A non-transitory computer-readable medium comprising instructions that when executed by a processor cause the processor to: receive a first speech input from a first speaker; determine, by a speech translation system, a first recognized speech result based on the speech input; determine, by the speech translation system, whether there exists a recognition ambiguity in the first recognized speech result, wherein the recognition ambiguity indicates more than one possible match for the first recognized speech result; upon a determination that there is recognition ambiguity in the first recognized speech result of the first speaker, determine a confidence score based on the recognition ambiguity; and responsive to the confidence score being below a threshold, issue a first disambiguation query to the first speaker via the speech translation system, wherein a response to the first disambiguation query resolves the recognition ambiguity.
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11. A non-transitory computer-readable medium comprising instructions that when executed by a processor cause the processor to: receive a first speech input from a first speaker; determine, by a speech translation system, a first recognized speech result based on the speech input; determine, by the speech translation system, whether there exists a recognition ambiguity in the first recognized speech result, wherein the recognition ambiguity indicates more than one possible match for the first recognized speech result; upon a determination that there is recognition ambiguity in the first recognized speech result of the first speaker, determine a confidence score based on the recognition ambiguity; and responsive to the confidence score being below a threshold, issue a first disambiguation query to the first speaker via the speech translation system, wherein a response to the first disambiguation query resolves the recognition ambiguity. 12. The non-transitory computer-readable medium of claim 11 , further comprising instructions that cause the processor to: receive a second speech input from a second speaker; determine, by the speech translation system, a second recognized speech result based on the second speech input; extract information from the second recognized speech input from the second speaker; enter the extracted information into an electronic form; and display the electronic form.
| 0.5 |
9,092,479 | 8 | 12 |
8. A system, comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: identifying a seed query for a structured document based on a performance of the seed query with respect to the structured document; identifying one or more embedded coding fragments for the structured document using the seed query, each identified embedded coding fragment specifying a structure of a portion of the structured document that includes at least one term of the seed query; generating one or more query templates, each query template corresponding to at least one of the identified embedded coding fragments, the query template including the structure of the corresponding at least one embedded coding fragment and a generative rule to be used in generating one or more synthetic queries; generating the one or more synthetic queries using the one or more query templates and other structured documents, the generating comprising, for each query template: identifying a portion of a particular structured document that includes the structure specified by the corresponding embedded coding fragment; and generating a synthetic query using text contained in the portion of the particular structured document and specified by the generative rule; and storing at least one of the one or more synthetic queries in a query store.
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8. A system, comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: identifying a seed query for a structured document based on a performance of the seed query with respect to the structured document; identifying one or more embedded coding fragments for the structured document using the seed query, each identified embedded coding fragment specifying a structure of a portion of the structured document that includes at least one term of the seed query; generating one or more query templates, each query template corresponding to at least one of the identified embedded coding fragments, the query template including the structure of the corresponding at least one embedded coding fragment and a generative rule to be used in generating one or more synthetic queries; generating the one or more synthetic queries using the one or more query templates and other structured documents, the generating comprising, for each query template: identifying a portion of a particular structured document that includes the structure specified by the corresponding embedded coding fragment; and generating a synthetic query using text contained in the portion of the particular structured document and specified by the generative rule; and storing at least one of the one or more synthetic queries in a query store. 12. The system of claim 8 , wherein the instructions cause the data processing apparatus to perform further operations comprising: performing an augmented search operation using a particular synthetic query to identify one or more search results; and providing the one or more search results.
| 0.668934 |
8,825,481 | 10 | 14 |
10. One or more computer-readable storage media, storing instructions that enable a processor to perform actions comprising: determining, based on accented speech data for a word, pronunciation information for the word at a plurality of levels, each level corresponding to different respective subword types and including one or more subwords of the respective subword type; determining, based at least on the accented speech data, a set of probabilities at each level of the plurality of levels, each probability of the set of probabilities for a particular level being associated with a respective subword of the one or more of the subwords of the particular level; and combining the sets of probabilities to generate a model for accented speech recognition.
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10. One or more computer-readable storage media, storing instructions that enable a processor to perform actions comprising: determining, based on accented speech data for a word, pronunciation information for the word at a plurality of levels, each level corresponding to different respective subword types and including one or more subwords of the respective subword type; determining, based at least on the accented speech data, a set of probabilities at each level of the plurality of levels, each probability of the set of probabilities for a particular level being associated with a respective subword of the one or more of the subwords of the particular level; and combining the sets of probabilities to generate a model for accented speech recognition. 14. The one or more computer-readable storage media of claim 10 , wherein combining the sets employs a linear combination.
| 0.722727 |
9,966,064 | 1 | 8 |
1. A method for training acoustic models for automatic speech recognition comprising: building a dialect recognition system configured to identify at least one dialect of a standard form language in input data by distinguishing phones of the standard form language and the at least one dialect, the building the dialect recognition system further comprising generating a phone decoder for building an acoustic training data set; applying the dialect recognition system with at least one processor to identify portions of the acoustic training data set that conform to the at least one dialect based on distinguished phones of the at least one dialect in the training data set; and performing automatic speech recognition using at least one dialect language model trained based on the portions of the acoustic training data set that are identified as conforming to the at least one dialect.
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1. A method for training acoustic models for automatic speech recognition comprising: building a dialect recognition system configured to identify at least one dialect of a standard form language in input data by distinguishing phones of the standard form language and the at least one dialect, the building the dialect recognition system further comprising generating a phone decoder for building an acoustic training data set; applying the dialect recognition system with at least one processor to identify portions of the acoustic training data set that conform to the at least one dialect based on distinguished phones of the at least one dialect in the training data set; and performing automatic speech recognition using at least one dialect language model trained based on the portions of the acoustic training data set that are identified as conforming to the at least one dialect. 8. The method of claim 1 , wherein the building comprises building general phone representations for the standard form language and building phone representations for the at least one dialect by adapting the general phone representations.
| 0.5 |
7,817,630 | 1 | 6 |
1. A method for updating a dynamic dictionary for use in compressions and decompressions of messages, the method comprising the steps of: a. receiving at a compression/decompression module in a networking node a message containing individual expressions; b. determining at the compression/decompression module all matches between the individual expressions of the message and corresponding expressions in a first dictionary stored in a memory; c. among the determined matches of individual expressions, determining different sequences of matches of individual expressions which are contiguous to each other in the message, each of the different matching sequences including one or more contiguous individual expressions and the different sequences which are determined to be contiguous to each other forming at least one new combined expression; and d. creating in the dynamic dictionary the at least one new combined expression for exclusive use by the compression/decompression module.
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1. A method for updating a dynamic dictionary for use in compressions and decompressions of messages, the method comprising the steps of: a. receiving at a compression/decompression module in a networking node a message containing individual expressions; b. determining at the compression/decompression module all matches between the individual expressions of the message and corresponding expressions in a first dictionary stored in a memory; c. among the determined matches of individual expressions, determining different sequences of matches of individual expressions which are contiguous to each other in the message, each of the different matching sequences including one or more contiguous individual expressions and the different sequences which are determined to be contiguous to each other forming at least one new combined expression; and d. creating in the dynamic dictionary the at least one new combined expression for exclusive use by the compression/decompression module. 6. The method claimed in claim 1 , wherein the method is performed by a compression module at a sending node.
| 0.876697 |
5,546,517 | 1 | 2 |
1. Apparatus for allocating display items to each page of a hypermedia document containing display items that are to be laid out on several linked pages, comprising: means for automatically allocating said display items of said document to said pages by automatically specifying the assignment of said display items to each page by using a reduction to graph partitioning and an optimization technique for said graph partitioning and for automatically creating linkages between said pages including means for reducing said assigned display items and linkages to a graph partition to provide an optimized graph partition specifying assignments of display items and linkages, whereby a convenient document structure is automatically provided in which linkages and page content are automatically created, thus eliminating the necessity for the author to prespecify page content or linkage structure.
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1. Apparatus for allocating display items to each page of a hypermedia document containing display items that are to be laid out on several linked pages, comprising: means for automatically allocating said display items of said document to said pages by automatically specifying the assignment of said display items to each page by using a reduction to graph partitioning and an optimization technique for said graph partitioning and for automatically creating linkages between said pages including means for reducing said assigned display items and linkages to a graph partition to provide an optimized graph partition specifying assignments of display items and linkages, whereby a convenient document structure is automatically provided in which linkages and page content are automatically created, thus eliminating the necessity for the author to prespecify page content or linkage structure. 2. The Apparatus of claim 1 wherein said assigning means includes means for providing a list of display items, edges between display items and a numeric value corresponding to the importance thereof.
| 0.5 |
7,562,011 | 1 | 11 |
1. A computer-implemented method for building a template specifying an emotional response to a content stream, the method comprising: selecting a dictionary, the dictionary including a plurality of concepts to form a directed set, wherein only one concept is a maximal element; establishing directed links between pairs of concepts in the directed set, the directed links defining “is a” relationships between the concepts in the pairs of concepts, so that each concept is either a source or a sink of at least one directed link; establishing intentional stance basis chains in the directed set from the maximal element to each other concept along the directed links, where for each pair of concepts in each intentional stance basis chain, one of the pair of concepts is a lineal ancestor of the other of the pair of concepts; selecting a subset of the intentional stance basis chains to form a basis, the subset of the intentional stance basis chains including at least one intentional stance basis chain; selecting at least one concept in the dictionary; creating a state vector in a topological vector space corresponding to each selected concept within a computer, wherein each state vector in the topological vector space includes as at least one measure of how concretely the corresponding selected concept is represented in each intentional stance basis chain in the basis; assembling the state vectors in the topological vector space into a template; and associating an action with the template.
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1. A computer-implemented method for building a template specifying an emotional response to a content stream, the method comprising: selecting a dictionary, the dictionary including a plurality of concepts to form a directed set, wherein only one concept is a maximal element; establishing directed links between pairs of concepts in the directed set, the directed links defining “is a” relationships between the concepts in the pairs of concepts, so that each concept is either a source or a sink of at least one directed link; establishing intentional stance basis chains in the directed set from the maximal element to each other concept along the directed links, where for each pair of concepts in each intentional stance basis chain, one of the pair of concepts is a lineal ancestor of the other of the pair of concepts; selecting a subset of the intentional stance basis chains to form a basis, the subset of the intentional stance basis chains including at least one intentional stance basis chain; selecting at least one concept in the dictionary; creating a state vector in a topological vector space corresponding to each selected concept within a computer, wherein each state vector in the topological vector space includes as at least one measure of how concretely the corresponding selected concept is represented in each intentional stance basis chain in the basis; assembling the state vectors in the topological vector space into a template; and associating an action with the template. 11. A method according to claim 1 , wherein associating an action includes associating a plurality of actions to be performed if the content stream is within one of a plurality of threshold distances of the template, each of the associated actions to be performed if the content stream is within a unique range of distances of the template.
| 0.5 |
10,148,600 | 19 | 20 |
19. The computer implemented method of claim 18 further comprising accessing a plurality of attributes that identify a user's intention.
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19. The computer implemented method of claim 18 further comprising accessing a plurality of attributes that identify a user's intention. 20. The computer implemented method of claim 19 where the plurality of attributes are stored in a plurality of downloadable profiles.
| 0.5 |
8,949,122 | 1 | 8 |
1. A method of evaluating a plurality of stored audio phrases and at least one finite state grammar, wherein the at least one finite state grammar defines at least a first plurality of text phrases and wherein the plurality of stored audio phrases correspond to a second plurality of text phrases, the method comprising: determining, for each one text phrase of the first plurality of text phrases and based at least in part on phrase characteristics associated with the plurality of stored audio phrases, whether there is an audio phrase of the plurality of stored audio phrases that corresponds to the one text phrase, wherein the determining is performed using at least one programmed processor; and identifying a phrase coverage for the at least one finite state grammar based at least in part on the determining, the phrase coverage indicating whether there are one or more text phrases of the first plurality of text phrases defined by the at least one finite state grammar to which none of the plurality of stored audio phrases corresponds.
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1. A method of evaluating a plurality of stored audio phrases and at least one finite state grammar, wherein the at least one finite state grammar defines at least a first plurality of text phrases and wherein the plurality of stored audio phrases correspond to a second plurality of text phrases, the method comprising: determining, for each one text phrase of the first plurality of text phrases and based at least in part on phrase characteristics associated with the plurality of stored audio phrases, whether there is an audio phrase of the plurality of stored audio phrases that corresponds to the one text phrase, wherein the determining is performed using at least one programmed processor; and identifying a phrase coverage for the at least one finite state grammar based at least in part on the determining, the phrase coverage indicating whether there are one or more text phrases of the first plurality of text phrases defined by the at least one finite state grammar to which none of the plurality of stored audio phrases corresponds. 8. The method of claim 1 , further comprising: performing the determining and identifying in response to detecting a programmatically triggered event, wherein the programmatically triggered event results from a detection of a change in the at least one finite state grammar or a change in the plurality of stored audio phrases.
| 0.729752 |
8,914,758 | 5 | 7 |
5. The method of claim 2 further comprising reducing the bit-level data flow graph by finding adders, to produce a reduced bit-level data flow graph.
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5. The method of claim 2 further comprising reducing the bit-level data flow graph by finding adders, to produce a reduced bit-level data flow graph. 7. The method of claim 5 wherein the reducing includes identifying a current slice where the current slice includes partial products or a carry from a previous slice.
| 0.5 |
9,547,480 | 5 | 7 |
5. The method of claim 1 , wherein receiving the inputs identifying each of one or more semantic constructs of the application model with at least one of the application model subsets comprises receiving identifying constructs in the semantic constructs, wherein each of the identifying constructs contains an identifier of one of the application model subsets.
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5. The method of claim 1 , wherein receiving the inputs identifying each of one or more semantic constructs of the application model with at least one of the application model subsets comprises receiving identifying constructs in the semantic constructs, wherein each of the identifying constructs contains an identifier of one of the application model subsets. 7. The method of claim 5 , further comprising: identifying at least one additional semantic construct of the application model with a default application model subset from the application model subsets, in response to the at least one additional semantic construct lacking an identifying construct and lacking an ancestor semantic construct that contains an identifying construct.
| 0.580574 |
9,710,435 | 1 | 55 |
1. An apparatus comprising: a processor; a computer readable memory; a user interface to receive user inputs and to display outputs to a user; and wherein: the computer readable memory contains a series of computer-executable instructions to be executed by the processor which enable the formulation of a mathematical expression by the user via the user interface, the mathematical expression comprising a selection of objects from a library of object types contained in the computer readable memory, the object types comprising primitive objects and non-primitive objects, wherein non-primitive objects have at least one field which in turn can host additional objects, and primitive objects have no fields, and wherein: the mathematical expression formulated by the user is defined by a single computer readable data structure which is generated automatically by the series of computer-executable instructions in response to the user inputs, and is stored in the computer readable memory; each object and each field is defined by a mathematical significance assigned thereto within the single computer readable data structure; the single computer readable data structure combines functions of a content tree data structure, and of a presentation tree data structure, for the mathematical expression; the single computer readable data structure contains presentation data sufficient to enable complete, automatic formatting of the mathematical expression for the display; the single computer readable data structure contains content data sufficient to enable automatic computation of the mathematical expression by the processor; the user interface enables the user to edit the mathematical expression; editing of the mathematical expression by the user via the user interface results in automatic modification of the single computer readable data structure; and the series of computer-executable instructions include a series of steps to identify the user inputs with at least some of the objects, and to display the mathematical expression defined by the single computer readable data structure via the display.
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1. An apparatus comprising: a processor; a computer readable memory; a user interface to receive user inputs and to display outputs to a user; and wherein: the computer readable memory contains a series of computer-executable instructions to be executed by the processor which enable the formulation of a mathematical expression by the user via the user interface, the mathematical expression comprising a selection of objects from a library of object types contained in the computer readable memory, the object types comprising primitive objects and non-primitive objects, wherein non-primitive objects have at least one field which in turn can host additional objects, and primitive objects have no fields, and wherein: the mathematical expression formulated by the user is defined by a single computer readable data structure which is generated automatically by the series of computer-executable instructions in response to the user inputs, and is stored in the computer readable memory; each object and each field is defined by a mathematical significance assigned thereto within the single computer readable data structure; the single computer readable data structure combines functions of a content tree data structure, and of a presentation tree data structure, for the mathematical expression; the single computer readable data structure contains presentation data sufficient to enable complete, automatic formatting of the mathematical expression for the display; the single computer readable data structure contains content data sufficient to enable automatic computation of the mathematical expression by the processor; the user interface enables the user to edit the mathematical expression; editing of the mathematical expression by the user via the user interface results in automatic modification of the single computer readable data structure; and the series of computer-executable instructions include a series of steps to identify the user inputs with at least some of the objects, and to display the mathematical expression defined by the single computer readable data structure via the display. 55. The apparatus of claim 1 and wherein the user interface comprises a display device, the memory device contains an exemplary mathematical expression, and the series of computer-executable instructions include a series of steps to animate on the display a methodology for entering the mathematical expression using the user interface.
| 0.85567 |
7,747,655 | 1 | 15 |
1. A computer system for generating a representation of time-based media, the system comprising: a feature extraction module for: extracting, using a feature extraction technique, features from the time-based media, the feature extraction technique specified by a document format specification file; and generating a media representation of the time-based media that represents the extracted features, the media representation including a waveform representing the time based media including the extracted features, a corresponding timeline and a plurality of user-selectable identifiers indicating locations on the timeline corresponding to the extracted features; a formatting module communicatively coupled to the feature extraction module, the formatting module for: formatting the media representation according to layout parameters specified by the document format specification file; and a printer communicatively coupled to the formatting module, the printer for: printing the formatted media representation, wherein each of the plurality of user-selectable identifiers in the printed, formatted media representation can be selected to access a corresponding part of the time-based media.
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1. A computer system for generating a representation of time-based media, the system comprising: a feature extraction module for: extracting, using a feature extraction technique, features from the time-based media, the feature extraction technique specified by a document format specification file; and generating a media representation of the time-based media that represents the extracted features, the media representation including a waveform representing the time based media including the extracted features, a corresponding timeline and a plurality of user-selectable identifiers indicating locations on the timeline corresponding to the extracted features; a formatting module communicatively coupled to the feature extraction module, the formatting module for: formatting the media representation according to layout parameters specified by the document format specification file; and a printer communicatively coupled to the formatting module, the printer for: printing the formatted media representation, wherein each of the plurality of user-selectable identifiers in the printed, formatted media representation can be selected to access a corresponding part of the time-based media. 15. The system of claim 1 , wherein the formatting module is further adapted to format the media representation according to format specifications included in the document format specification file.
| 0.619231 |
8,359,472 | 1 | 3 |
1. A computer-implemented process for generating document fingerprints, the method being performed using a computer including at least a processor, data storage, and computer-readable instructions, and the method comprising: normalizing a document to create a normalized text string; applying a first hash function with a sliding hash window to the normalized text string to generate an array of hash values; applying a first filter to the array of hash values to select candidate anchoring points; applying a second filter to the candidate anchoring points to select anchoring points; and applying a second hash function to substrings located at the selected anchoring points to generate hash values for use as fingerprints of the document.
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1. A computer-implemented process for generating document fingerprints, the method being performed using a computer including at least a processor, data storage, and computer-readable instructions, and the method comprising: normalizing a document to create a normalized text string; applying a first hash function with a sliding hash window to the normalized text string to generate an array of hash values; applying a first filter to the array of hash values to select candidate anchoring points; applying a second filter to the candidate anchoring points to select anchoring points; and applying a second hash function to substrings located at the selected anchoring points to generate hash values for use as fingerprints of the document. 3. The process of claim 1 , wherein the first hash function comprises a Karp-Rabin function.
| 0.762887 |
9,307,003 | 17 | 18 |
17. The server of claim 16 wherein the memory is further configured to store a measure of success of the prefetching, wherein the measure of success is based on whether the children were later requested by the user machine.
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17. The server of claim 16 wherein the memory is further configured to store a measure of success of the prefetching, wherein the measure of success is based on whether the children were later requested by the user machine. 18. The server of claim 17 wherein the prefetch scanner is further configured to modify, based on the measure of success, a success rate for the children as associated with the node established as the root node for the requested HTTP object.
| 0.5 |
9,066,150 | 2 | 3 |
2. The method of claim 1 , wherein the time-independent axis orders the at least some of the plurality of search results based, at least in part, on the media content associated with the at least some of the plurality of search results.
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2. The method of claim 1 , wherein the time-independent axis orders the at least some of the plurality of search results based, at least in part, on the media content associated with the at least some of the plurality of search results. 3. The method of claim 2 , wherein the time-independent axis orders the at least some of the plurality of search results based, at least in part, on the type of media content associated with the at least some of the plurality of search results.
| 0.5 |
9,865,252 | 5 | 6 |
5. The dialogue type voice recognition apparatus according to claim 3 , wherein the at least one hardware processor is configured to: determine a user's intention from at least one of the extracted first and second utterance elements and the detected candidate domain to determine whether or not a context initialization occurred, and when it is determined that the context initialization has not occurred, determine at least one candidate domain from among the detected candidate domains as the final domain based on a previous domain, the previous domain being a domain determined from a user's previous utterance voice before receiving the text of the user's utterance voice signal.
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5. The dialogue type voice recognition apparatus according to claim 3 , wherein the at least one hardware processor is configured to: determine a user's intention from at least one of the extracted first and second utterance elements and the detected candidate domain to determine whether or not a context initialization occurred, and when it is determined that the context initialization has not occurred, determine at least one candidate domain from among the detected candidate domains as the final domain based on a previous domain, the previous domain being a domain determined from a user's previous utterance voice before receiving the text of the user's utterance voice signal. 6. The dialogue type voice recognition apparatus according to claim 5 , wherein the at least one hardware processor is configured to determine the previous domain as the final domain in response to one candidate domain from among the detected candidate domains and the previous domain corresponding to each other.
| 0.5 |
8,280,823 | 249 | 252 |
249. The system of claim 242 , wherein to satisfy the search criteria, the parsed resume associated with each said at least one matching resume includes, for each said at least one job requirement, either the required skill or experience-related phrase, or an alternative required skill or experience-related phrase, and wherein the term of experience for either the required skill or experience-related phrase, or the alternative required skill or experience-related phrase, is greater than or equal to the required term of experience.
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249. The system of claim 242 , wherein to satisfy the search criteria, the parsed resume associated with each said at least one matching resume includes, for each said at least one job requirement, either the required skill or experience-related phrase, or an alternative required skill or experience-related phrase, and wherein the term of experience for either the required skill or experience-related phrase, or the alternative required skill or experience-related phrase, is greater than or equal to the required term of experience. 252. The system of claim 249 , wherein the job description further comprises the alternative required skill or experience-related phrase.
| 0.5 |
9,195,937 | 3 | 6 |
3. The apparatus of claim 1 , wherein the flow processing module determines whether the state exists in a translation dictionary for the state request, and wherein the state is reproduced if it is not in the dictionary and a new state is added to the dictionary.
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3. The apparatus of claim 1 , wherein the flow processing module determines whether the state exists in a translation dictionary for the state request, and wherein the state is reproduced if it is not in the dictionary and a new state is added to the dictionary. 6. The apparatus of claim 3 , wherein during compilation, state expression descriptors are chained with a linked list.
| 0.791519 |
5,425,128 | 7 | 9 |
7. The automatic speech recognition management system of claim 2 including means for testing a vocabulary update flag associated with the application program to determine if the vocabulary file and corresponding characters have been updated, the transmitting means transmitting the compiled vocabulary file and speech template file to the speech recognition program if the vocabulary file and corresponding characters have not been updated.
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7. The automatic speech recognition management system of claim 2 including means for testing a vocabulary update flag associated with the application program to determine if the vocabulary file and corresponding characters have been updated, the transmitting means transmitting the compiled vocabulary file and speech template file to the speech recognition program if the vocabulary file and corresponding characters have not been updated. 9. The automatic speech recognition management system of claim 7 wherein the assembling means includes means for setting up a software structure for entry of a plurality of uncompiled input words and corresponding keystroke characters and means for sequentially entering the uncompiled input words and associated characters into the software structure according to syntax rules of the speech recognition program.
| 0.5 |
9,607,436 | 1 | 6 |
1. A system to display augmented data, comprising: a processor; and a memory communicatively coupled to the processor, the memory bearing processor instructions that, when executed by the processor, cause the system to at least: determine augmentation data based on a context associated with a user device, the augmentation data comprising a plurality of augmentations, each of the plurality of augmentations associated with one of a plurality of physical venues including a certain physical venue, and wherein the context includes information regarding the user's environment; generate one or more clusters, each cluster of the one or more clusters comprising a subset of the plurality of augmentations, wherein each cluster of the one or more clusters represents one of the plurality of physical venues; grouping each of the plurality of augmentations into one of the one or more clusters based on a respective location of the plurality of physical venues; determine rendering formats for each of the one or more clusters, wherein the rendering formats determine at least a look of conceptual representations of the one or more clusters, wherein the look of the conceptual representation of a cluster is based on at least a first property of the subset of the plurality of augmentations grouped into the cluster, and wherein the conceptual representation is different from individual augmentations within the cluster, and wherein a respective rendering format for a certain cluster of the one or more clusters associated with the certain physical venue is based on the subset of the plurality of augmentations associated with the certain physical venue, and wherein the certain cluster of the one or more clusters comprises at least one lower-level cluster, wherein the rendering formats for the at least one lower-level cluster is based on an at least one second property of a second subset of the subset of the plurality of augmentations.
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1. A system to display augmented data, comprising: a processor; and a memory communicatively coupled to the processor, the memory bearing processor instructions that, when executed by the processor, cause the system to at least: determine augmentation data based on a context associated with a user device, the augmentation data comprising a plurality of augmentations, each of the plurality of augmentations associated with one of a plurality of physical venues including a certain physical venue, and wherein the context includes information regarding the user's environment; generate one or more clusters, each cluster of the one or more clusters comprising a subset of the plurality of augmentations, wherein each cluster of the one or more clusters represents one of the plurality of physical venues; grouping each of the plurality of augmentations into one of the one or more clusters based on a respective location of the plurality of physical venues; determine rendering formats for each of the one or more clusters, wherein the rendering formats determine at least a look of conceptual representations of the one or more clusters, wherein the look of the conceptual representation of a cluster is based on at least a first property of the subset of the plurality of augmentations grouped into the cluster, and wherein the conceptual representation is different from individual augmentations within the cluster, and wherein a respective rendering format for a certain cluster of the one or more clusters associated with the certain physical venue is based on the subset of the plurality of augmentations associated with the certain physical venue, and wherein the certain cluster of the one or more clusters comprises at least one lower-level cluster, wherein the rendering formats for the at least one lower-level cluster is based on an at least one second property of a second subset of the subset of the plurality of augmentations. 6. The system of claim 1 , wherein the instructions to determine rendering formats for the generated clusters comprises deriving properties determined for the one or more clusters based on the grouped augmentation data and using the derived properties to create the conceptual representations of the one or more clusters.
| 0.613253 |
9,275,046 | 1 | 4 |
1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: providing an interface for selecting a vertical language text translation box corresponding to one or more words in the first language, wherein the first language is an Asian language comprising a plurality of characters having a vertical alignment; cropping a frame of the real-time video feed of the one or more words of the first language to fit inside the vertical language text translation box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments; performing character recognition on the merged character segments to produce a plurality of recognized characters; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language in augmented reality in the real-time video feed.
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1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: providing an interface for selecting a vertical language text translation box corresponding to one or more words in the first language, wherein the first language is an Asian language comprising a plurality of characters having a vertical alignment; cropping a frame of the real-time video feed of the one or more words of the first language to fit inside the vertical language text translation box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments; performing character recognition on the merged character segments to produce a plurality of recognized characters; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language in augmented reality in the real-time video feed. 4. The method of claim 1 , wherein the step of performing the character segment detection comprises additional steps of: storing text precursors in a memory device; performing merging of any two text precursors when the two text precursors are overlapping and/or neighboring; examining the text precursors' character size; and ending character segment detection for small text precursor characters.
| 0.647163 |
9,953,427 | 36 | 38 |
36. The method according to claim 32 , further comprising constructing a depth map of the scene, based on said sparse representation.
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36. The method according to claim 32 , further comprising constructing a depth map of the scene, based on said sparse representation. 38. The method according to claim 36 , further comprising generating a three-dimensional image based on said depth map.
| 0.531496 |
8,954,319 | 11 | 12 |
11. The system of claim 8 , wherein the set of allowed dialog actions comprises a set of business rules.
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11. The system of claim 8 , wherein the set of allowed dialog actions comprises a set of business rules. 12. The system of claim 11 , the computer-readable storage medium having additional instructions stored which result in operations comprising tailoring wordings in a natural language spoken dialog system based on a current context and the set of business rules.
| 0.5 |
8,606,775 | 4 | 12 |
4. A system for graphically representing one or more referents associated with a plurality of stories, the system comprising: a data store that stores data associated with a plurality of stories, wherein the data associated with each story comprises referent data identifying one or more referents associated with the story; and a computing device in communication with the data store, the computing device operative to: determine, for each of the plurality of stories, a score for the story based at least in part on a number of times that the one or more referents of interest are referenced in at least a portion of content of the story, wherein the number of times that the one or more referents of interest are referenced is derived at least in part from the referent data stored in the data store; and generate for display a graphical representation of a subset of the plurality of stories, the graphical representation comprising a plurality of indicia, wherein each indicium of the plurality of indicia is associated with a different story of the subset of the plurality of stories, wherein the indicium for each story of the subset graphically indicates a strength of association between the story and the one or more referents of interest, and wherein the strength of association is determined based at least in part on the score for the story.
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4. A system for graphically representing one or more referents associated with a plurality of stories, the system comprising: a data store that stores data associated with a plurality of stories, wherein the data associated with each story comprises referent data identifying one or more referents associated with the story; and a computing device in communication with the data store, the computing device operative to: determine, for each of the plurality of stories, a score for the story based at least in part on a number of times that the one or more referents of interest are referenced in at least a portion of content of the story, wherein the number of times that the one or more referents of interest are referenced is derived at least in part from the referent data stored in the data store; and generate for display a graphical representation of a subset of the plurality of stories, the graphical representation comprising a plurality of indicia, wherein each indicium of the plurality of indicia is associated with a different story of the subset of the plurality of stories, wherein the indicium for each story of the subset graphically indicates a strength of association between the story and the one or more referents of interest, and wherein the strength of association is determined based at least in part on the score for the story. 12. The system of claim 4 , wherein each referent of interest comprises at least one of an event, a character, an object, a subject, a time, a place and a person.
| 0.746875 |
9,047,464 | 1 | 8 |
1. A method for securing a computer device, the method comprising: receiving, by a security server, interaction data for a user interfacing with the computer device while the user is authenticated for accessing at least one computer resource, the interaction data including keyboard inputs, images taken of the user during the access and screen captures taken periodically; performing optical character recognition (OCR) to identify text in the screen captures; extracting semantic data from the interaction data and from the text in the screen captures, the semantic data identifying user activities associated with the interaction data; generating a schema based on the extracted semantic data, the schema including tags that are descriptive of at least one of the identified user activity and the associated interaction data; analyzing the schema based on a model to identify security threats associated with the user activities; creating an alarm when non-conforming behavior for at least one user activity is detected, the alarm including a binding of the one or more user activities, one or more tags, keyboard inputs, and screen captures associated with the one or more user activities; and sending a command from the security server to terminate access to the at least one computer resource in response to the alarm, wherein operations of the method are executed by a processor.
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1. A method for securing a computer device, the method comprising: receiving, by a security server, interaction data for a user interfacing with the computer device while the user is authenticated for accessing at least one computer resource, the interaction data including keyboard inputs, images taken of the user during the access and screen captures taken periodically; performing optical character recognition (OCR) to identify text in the screen captures; extracting semantic data from the interaction data and from the text in the screen captures, the semantic data identifying user activities associated with the interaction data; generating a schema based on the extracted semantic data, the schema including tags that are descriptive of at least one of the identified user activity and the associated interaction data; analyzing the schema based on a model to identify security threats associated with the user activities; creating an alarm when non-conforming behavior for at least one user activity is detected, the alarm including a binding of the one or more user activities, one or more tags, keyboard inputs, and screen captures associated with the one or more user activities; and sending a command from the security server to terminate access to the at least one computer resource in response to the alarm, wherein operations of the method are executed by a processor. 8. The method as recited in claim 1 , wherein the screen captures are performed periodically with a time interval between screen captures in a range from 1/30 of a second to 10 seconds, wherein the time interval between screen captures is decreased when a user operation for access to an external storage device or when the user performs a cut-and-paste operation.
| 0.65 |
7,865,494 | 12 | 17 |
12. A computer program product for personalized searching for information in a distributed data processing system, the computer program product disposed upon a recording medium, the computer program product comprising computer program instructions capable, when executed, of causing a computer to carry out the steps of: providing in a server-side search portal a personal search term list, wherein the personal search term list includes a user identifier that is associated with a search keyword; receiving from a user a navigation identification message comprising a user identification for the server-side search portal, a search keyword, a user identification, a password, and a navigation location; inserting an index record in a personalized search index in dependence upon the user identification, the navigation location, and the personal search term list, wherein the index record associates the user identification with the navigation location and with the one or more search keywords from the personal search term list; and assigning priority to index entries in the personalized search index including counting the number of times each navigation location is received in navigation identification messages.
|
12. A computer program product for personalized searching for information in a distributed data processing system, the computer program product disposed upon a recording medium, the computer program product comprising computer program instructions capable, when executed, of causing a computer to carry out the steps of: providing in a server-side search portal a personal search term list, wherein the personal search term list includes a user identifier that is associated with a search keyword; receiving from a user a navigation identification message comprising a user identification for the server-side search portal, a search keyword, a user identification, a password, and a navigation location; inserting an index record in a personalized search index in dependence upon the user identification, the navigation location, and the personal search term list, wherein the index record associates the user identification with the navigation location and with the one or more search keywords from the personal search term list; and assigning priority to index entries in the personalized search index including counting the number of times each navigation location is received in navigation identification messages. 17. The computer program product of claim 12 wherein providing a personal search term list further comprises receiving from the user and adding to the personal search term list a keyword selected by the user from within a document.
| 0.658284 |
10,102,851 | 1 | 2 |
1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain, from a remote device, audio data regarding an utterance of a user, the utterance comprising a plurality of words; determine a likely word boundary in the audio data; generate first incremental speech recognition results from a first portion of the audio data, the first portion comprising only audio data preceding the likely word boundary; generate a first semantic representation of the utterance using the first incremental speech recognition results and without using incremental speech recognition results representing any portion of the audio data following the likely word boundary; generate a first stability score indicating a degree to which the first semantic representation of the utterance is the same as a previously-generated semantic representation of the utterance; determine that the first stability score satisfies a first threshold; in response to determining that the first stability score satisfies the first threshold: determine a plurality of content items associated with the first intent; and initiate loading of the plurality of content items; generate second incremental speech recognition results from the first portion and a second portion of the audio data, the second portion comprising audio data preceding the likely word boundary and audio data subsequent to the likely word boundary; generate a second semantic representation of the utterance using the second incremental speech recognition results; generate a second stability score indicating a degree to which the first semantic representation of the utterance is the same as the second semantic representation of the utterance; determine that the second stability score satisfies a second threshold; and in response to determining that the second stability score satisfies the second threshold: determine a requested content item of the plurality of content items based at least partly on the second semantic representation; and cause presentation of the requested content item by the remote device.
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1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain, from a remote device, audio data regarding an utterance of a user, the utterance comprising a plurality of words; determine a likely word boundary in the audio data; generate first incremental speech recognition results from a first portion of the audio data, the first portion comprising only audio data preceding the likely word boundary; generate a first semantic representation of the utterance using the first incremental speech recognition results and without using incremental speech recognition results representing any portion of the audio data following the likely word boundary; generate a first stability score indicating a degree to which the first semantic representation of the utterance is the same as a previously-generated semantic representation of the utterance; determine that the first stability score satisfies a first threshold; in response to determining that the first stability score satisfies the first threshold: determine a plurality of content items associated with the first intent; and initiate loading of the plurality of content items; generate second incremental speech recognition results from the first portion and a second portion of the audio data, the second portion comprising audio data preceding the likely word boundary and audio data subsequent to the likely word boundary; generate a second semantic representation of the utterance using the second incremental speech recognition results; generate a second stability score indicating a degree to which the first semantic representation of the utterance is the same as the second semantic representation of the utterance; determine that the second stability score satisfies a second threshold; and in response to determining that the second stability score satisfies the second threshold: determine a requested content item of the plurality of content items based at least partly on the second semantic representation; and cause presentation of the requested content item by the remote device. 2. The system of claim 1 , wherein the one or more processors are further programmed by the executable instructions to generate the second incremental speech recognition results concurrently with generating the first semantic representation.
| 0.5 |
9,058,614 | 1 | 2 |
1. A computer-implemented method for dynamically clustering data items, the method comprising: receiving (a) a plurality of data items originating from at least two sources; (b) a plurality of distinct metadata details; (c) data indicative of associations between said data items and said metadata details, wherein each data item is associated with at least one metadata detail, and wherein at least a first data item originating from a first source and a second data item originating from a second source are related data items associated with at least one shared metadata detail; grading strengths of relationships between at least one of said data items and at least one of said metadata details; and clustering said data items into one or more clusters, based on the calculated grades wherein at least one of said clusters comprises related data items originating from more than one source, wherein said grading comprises applying weighting functions and the weighting functions are rule-based weighting functions.
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1. A computer-implemented method for dynamically clustering data items, the method comprising: receiving (a) a plurality of data items originating from at least two sources; (b) a plurality of distinct metadata details; (c) data indicative of associations between said data items and said metadata details, wherein each data item is associated with at least one metadata detail, and wherein at least a first data item originating from a first source and a second data item originating from a second source are related data items associated with at least one shared metadata detail; grading strengths of relationships between at least one of said data items and at least one of said metadata details; and clustering said data items into one or more clusters, based on the calculated grades wherein at least one of said clusters comprises related data items originating from more than one source, wherein said grading comprises applying weighting functions and the weighting functions are rule-based weighting functions. 2. The method of claim 1 , further comprising enabling sharing of at least one of said clusters with at least one other user or public list.
| 0.751773 |
7,529,763 | 6 | 11 |
6. A computer-implemented method for providing an application appropriate rendering to an application development environment, the application appropriate rendering provided via a dynamic client architecture platform hosted by a computing device, the dynamic client architecture platform used to create applications in response to a user-submitted programmatic request, the method comprising: defining an application framework with the dynamic client architecture platform, the application framework created using a plurality of elements selected from a configuration repository, at least one of the plurality of elements associated with a role category of a user, the application framework elements being development language-neutral; storing the application framework; receiving via the dynamic client architecture platform a request for an application appropriate rendering from a user; and generating the application appropriate rendering using the application framework and a rendering subsystem, the application appropriate rendering generated based on a role category of the user requesting the application appropriate rendering, the rendering subsystem selected based on a programmatic examination of the request by the dynamic client architecture platform.
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6. A computer-implemented method for providing an application appropriate rendering to an application development environment, the application appropriate rendering provided via a dynamic client architecture platform hosted by a computing device, the dynamic client architecture platform used to create applications in response to a user-submitted programmatic request, the method comprising: defining an application framework with the dynamic client architecture platform, the application framework created using a plurality of elements selected from a configuration repository, at least one of the plurality of elements associated with a role category of a user, the application framework elements being development language-neutral; storing the application framework; receiving via the dynamic client architecture platform a request for an application appropriate rendering from a user; and generating the application appropriate rendering using the application framework and a rendering subsystem, the application appropriate rendering generated based on a role category of the user requesting the application appropriate rendering, the rendering subsystem selected based on a programmatic examination of the request by the dynamic client architecture platform. 11. The method of claim 6 , further comprising: associating a GUI (Graphical User Interface) display element with an object property in the application framework; retrieving data referenced by the property in a language neutral manner; and displaying the data using the GUI display element.
| 0.586895 |
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