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9,495,638 | 4 | 6 | 4. The method of claim 1 where any of the trigger rules are organized into a group of trigger rules, where the group serves as a workflow control block. | 4. The method of claim 1 where any of the trigger rules are organized into a group of trigger rules, where the group serves as a workflow control block. 6. The method of claim 4 further comprising: iteratively evaluating the trigger rules in the group. | 0.660959 |
8,543,981 | 10 | 11 | 10. A computer program product embodied in a computer readable medium in communication with a computer and a database and comprising computer instructions for: providing a state stack that includes a plurality of consecutive states, each state includes a at least one test object; providing a test script that lists actions that the software under test is to execute, the test script including test methods; receiving a request to modify the test script; creating a modified state stack based on the modified test script; checking the integrity of the modified test script by ensuring that the modified state stack can be integrated with at least a portion of the state stack subsequent to the modified portion; and if the modified test script maintains integrity, allowing the test script to be edited. | 10. A computer program product embodied in a computer readable medium in communication with a computer and a database and comprising computer instructions for: providing a state stack that includes a plurality of consecutive states, each state includes a at least one test object; providing a test script that lists actions that the software under test is to execute, the test script including test methods; receiving a request to modify the test script; creating a modified state stack based on the modified test script; checking the integrity of the modified test script by ensuring that the modified state stack can be integrated with at least a portion of the state stack subsequent to the modified portion; and if the modified test script maintains integrity, allowing the test script to be edited. 11. The computer program product of claim 10 , wherein the test methods are each associated with a state transition and checking the integrity of the modified test script is accomplished with the state transitions. | 0.5 |
8,539,359 | 1 | 67 | 1. A non-abstract machine system that is structured to automatically present as first presentations to a first user of the system, user-acceptable invitations to join in on telecommunications-mediated information exchange forums and/or to automatically present in the first presentations to the first user, user-acceptable suggestions of additional telecommunications-conveyed informational content to investigate, wherein the presented invitations and/or suggestions are based on content that the first user is presented with and are based on automatically repeated determinations by the machine system of what specific sub-portion or specific sub-portions of the presented content the first user more recently centered his or her attention upon, wherein the automatically repeated determinations regarding attention are carried out transparently by the machine system without need for diverted centering of attention by the user directed to aiding the automatically repeated transparent determinations by the machine system, the machine system comprising: a presentation format controller that determines or controls at least one of: whether or not a given user-acceptable invitation or user-acceptable suggestion is presented to the first user; when a given first presentation is presented; what order of presentation is used for multiple ones of the first presentations; at what rate multiple ones of the first presentations are automatically presented; and in what format are the given one or multiple ones of the first presentations automatically presented to the first user; wherein at least a portion of the machine system includes a data processing machine, and wherein said automatically determined and more recent centerings of attention by the first user occurred no more than at least one of: 3 hours prior to said presentation of the first presentations to the first user; and a determined time duration prior to said presentation of the first presentations to the first user, the determined time duration being determined based on a currently active profile characterizing the first user. | 1. A non-abstract machine system that is structured to automatically present as first presentations to a first user of the system, user-acceptable invitations to join in on telecommunications-mediated information exchange forums and/or to automatically present in the first presentations to the first user, user-acceptable suggestions of additional telecommunications-conveyed informational content to investigate, wherein the presented invitations and/or suggestions are based on content that the first user is presented with and are based on automatically repeated determinations by the machine system of what specific sub-portion or specific sub-portions of the presented content the first user more recently centered his or her attention upon, wherein the automatically repeated determinations regarding attention are carried out transparently by the machine system without need for diverted centering of attention by the user directed to aiding the automatically repeated transparent determinations by the machine system, the machine system comprising: a presentation format controller that determines or controls at least one of: whether or not a given user-acceptable invitation or user-acceptable suggestion is presented to the first user; when a given first presentation is presented; what order of presentation is used for multiple ones of the first presentations; at what rate multiple ones of the first presentations are automatically presented; and in what format are the given one or multiple ones of the first presentations automatically presented to the first user; wherein at least a portion of the machine system includes a data processing machine, and wherein said automatically determined and more recent centerings of attention by the first user occurred no more than at least one of: 3 hours prior to said presentation of the first presentations to the first user; and a determined time duration prior to said presentation of the first presentations to the first user, the determined time duration being determined based on a currently active profile characterizing the first user. 67. The machine system of claim 1 wherein: the presentation format controller is configured to automatically successively present the invitations and/or suggestions over time to the first user in accordance with a predetermined order; and the order of presentation is based on at least one of: a chronological ordering of the presented invitations and/or suggestions; and which presented invitations and/or suggestions are most highly scored in terms of topic and chat co-compatibility. | 0.874093 |
7,783,135 | 2 | 4 | 2. The method of claim 1 , wherein performing an action includes displaying a content in response to detecting the selection. | 2. The method of claim 1 , wherein performing an action includes displaying a content in response to detecting the selection. 4. The method of claim 2 , wherein displaying a content in response to detecting the selection includes displaying additional information about the selected object, wherein the additional information is identified from the information that identifies the one or more objects. | 0.5 |
7,962,790 | 2 | 7 | 2. The system of claim 1 , wherein the error handling management module comprises: an inference rule storage unit storing inference rules which are used to infer the error type and the error handling rules; an error recognition information analyzer analyzing the collected information from the error recognition modules and extracting from the collected information needed for error inference; an inference engine inferring the error type and the error handling rules for correcting the error from the information extracted by the error recognition information analyzer on the basis of the inference rules stored in the inference rule storage unit; and an error handling execution manager guiding error occurrence information and error handling operations to the user, and performing error handing according to the error handling rule selected by the user. | 2. The system of claim 1 , wherein the error handling management module comprises: an inference rule storage unit storing inference rules which are used to infer the error type and the error handling rules; an error recognition information analyzer analyzing the collected information from the error recognition modules and extracting from the collected information needed for error inference; an inference engine inferring the error type and the error handling rules for correcting the error from the information extracted by the error recognition information analyzer on the basis of the inference rules stored in the inference rule storage unit; and an error handling execution manager guiding error occurrence information and error handling operations to the user, and performing error handing according to the error handling rule selected by the user. 7. The system of claim 2 , wherein the home network system includes a plurality of services, and when the recognized irregularity is caused by an error of the device, the error handling management module retrieves services used by the device from the plurality of services, provides a list of the services to the user, and stops one of the services on the list selected by the user. | 0.5 |
9,542,820 | 25 | 26 | 25. A device comprising: a tactile output generator; a touch-sensitive surface; and memory storing one or more programs that include instructions for: detecting an occurrence of a first event; and in response to detecting the occurrence of the first event: in accordance with a determination that the first event is a first type of event of a plurality of types of events that are affected by the alert-salience setting, providing a first alert with the tactile output generator that includes a first haptic output selected based at least in part on an alert-salience setting of the device; and in accordance with a determination that the first event is a second type of event of a plurality of types of events that are not affected by the alert-salience setting, providing a second alert with the tactile output generator that includes a second haptic output selected without regard to the alert-salience setting of the device. | 25. A device comprising: a tactile output generator; a touch-sensitive surface; and memory storing one or more programs that include instructions for: detecting an occurrence of a first event; and in response to detecting the occurrence of the first event: in accordance with a determination that the first event is a first type of event of a plurality of types of events that are affected by the alert-salience setting, providing a first alert with the tactile output generator that includes a first haptic output selected based at least in part on an alert-salience setting of the device; and in accordance with a determination that the first event is a second type of event of a plurality of types of events that are not affected by the alert-salience setting, providing a second alert with the tactile output generator that includes a second haptic output selected without regard to the alert-salience setting of the device. 26. The device of claim 25 , wherein the first alert is different from the second alert. | 0.939973 |
9,183,299 | 12 | 13 | 12. The apparatus of claim 10 , the executed method further comprising: receiving a plurality of origin pages with the search query, wherein each origin page is chosen based on information associated with the search query calculating normalized click distances for each page in the set of search results for each of the plurality of origin pages; and summing the calculated normalized click distances for each page in the set of search results. | 12. The apparatus of claim 10 , the executed method further comprising: receiving a plurality of origin pages with the search query, wherein each origin page is chosen based on information associated with the search query calculating normalized click distances for each page in the set of search results for each of the plurality of origin pages; and summing the calculated normalized click distances for each page in the set of search results. 13. The apparatus of claim 12 , the executed method further comprising: calculating the click distance from each origin page in the plurality of origin pages to each page in the set of search results. | 0.5 |
8,631,504 | 14 | 19 | 14. A non-transitory computer readable medium having stored thereon a data structure for protecting a document, the document being stored in a computer-controlled repository, the data structure comprising: data records defining each of, two or more management groups, one or more relationship link each associated between a pair of the management groups, and the document; wherein each management group record having a management group type and a management subtype; wherein each relationship record associates a first management group to a second management group for defining a hierarchy of an enterprise organisation, each relationship record includes a relationship link type selected from a predefined set including at least two relationship link types; wherein each document record has respective document properties, the document properties being indicative of an access restriction to the document, the document properties being indicative of a first management group having ownership of the document, the document properties being further indicative of an access restriction to the document for another management group on the basis of the hierarchy of the enterprise organisation being dependant on a relationship link type associating such management group to the first management group, wherein the document properties comprise a respective access restriction associated with each of the at least two relationship link types included in the predefined set; and wherein the document properties are reviewed and access rights including a level of access is associated to the respective document, the access rights stored with the document properties further granting access to a second management group in accordance with the hierarchy of the enterprise organisation and relationship link type associating the second management group through to the first management group; wherein access to a document is granted to an employee belonging to the second management group when at least the second management group satisfies respective access rights associated with the document. | 14. A non-transitory computer readable medium having stored thereon a data structure for protecting a document, the document being stored in a computer-controlled repository, the data structure comprising: data records defining each of, two or more management groups, one or more relationship link each associated between a pair of the management groups, and the document; wherein each management group record having a management group type and a management subtype; wherein each relationship record associates a first management group to a second management group for defining a hierarchy of an enterprise organisation, each relationship record includes a relationship link type selected from a predefined set including at least two relationship link types; wherein each document record has respective document properties, the document properties being indicative of an access restriction to the document, the document properties being indicative of a first management group having ownership of the document, the document properties being further indicative of an access restriction to the document for another management group on the basis of the hierarchy of the enterprise organisation being dependant on a relationship link type associating such management group to the first management group, wherein the document properties comprise a respective access restriction associated with each of the at least two relationship link types included in the predefined set; and wherein the document properties are reviewed and access rights including a level of access is associated to the respective document, the access rights stored with the document properties further granting access to a second management group in accordance with the hierarchy of the enterprise organisation and relationship link type associating the second management group through to the first management group; wherein access to a document is granted to an employee belonging to the second management group when at least the second management group satisfies respective access rights associated with the document. 19. The non-transitory computer readable medium of claim 14 wherein: access rights to a document for a management group and management subgroup are defined such that access to the document by a employee is granted only if the employee is a member of the management group and management subgroup. | 0.63125 |
9,280,583 | 1 | 13 | 1. A method for multi-query optimization, the method comprising: identifying an input query set comprising a plurality of input queries over a given data set, each query comprising a graph pattern comprising at least one subject node, predicate edge and object node triple; and clustering the plurality of input queries though incremental pair-wise merging based on structural similarities between graph patterns and query search cost optimization realized by a given merged graph pattern to generate an optimized query set comprising at least one query cluster by using linegraphs, wherein clustering the plurality of inputs further comprises: identifying a plurality of candidate merger inputs, each candidate merger input comprising an input query or an existing query cluster resulting from a previous pair-wise merging, a merger input graph pattern and a set of predicate edges contained in the merger input graph pattern; and selecting a pair of merger inputs from the plurality of candidate merger inputs having a maximum overlap in the sets of predicate edges associated with the selected pair of merger inputs; and each linegraph comprises: linegraph nodes, each linegraph node corresponding to a given predicate edge in the input queries; linegraph edges between pairs of linegraph nodes that are associated with predicate edges sharing a common subject node or object node in the input queries; and a label associated with each linegraph edge and indicating a type of join between subject nodes and object nodes. | 1. A method for multi-query optimization, the method comprising: identifying an input query set comprising a plurality of input queries over a given data set, each query comprising a graph pattern comprising at least one subject node, predicate edge and object node triple; and clustering the plurality of input queries though incremental pair-wise merging based on structural similarities between graph patterns and query search cost optimization realized by a given merged graph pattern to generate an optimized query set comprising at least one query cluster by using linegraphs, wherein clustering the plurality of inputs further comprises: identifying a plurality of candidate merger inputs, each candidate merger input comprising an input query or an existing query cluster resulting from a previous pair-wise merging, a merger input graph pattern and a set of predicate edges contained in the merger input graph pattern; and selecting a pair of merger inputs from the plurality of candidate merger inputs having a maximum overlap in the sets of predicate edges associated with the selected pair of merger inputs; and each linegraph comprises: linegraph nodes, each linegraph node corresponding to a given predicate edge in the input queries; linegraph edges between pairs of linegraph nodes that are associated with predicate edges sharing a common subject node or object node in the input queries; and a label associated with each linegraph edge and indicating a type of join between subject nodes and object nodes. 13. The method of claim 1 , wherein the input queries comprise SPARQL queries and the data set comprises a resource description framework dataset. | 0.90806 |
7,848,971 | 20 | 23 | 20. The non transitory computer usable medium of claim 19 , wherein facilitating the discussion comprises: transmitting a first message to the support agent about the first page of the online financial document using the chat window; and receiving a second message from the support agent about the first page of the online financial document using the chat window. | 20. The non transitory computer usable medium of claim 19 , wherein facilitating the discussion comprises: transmitting a first message to the support agent about the first page of the online financial document using the chat window; and receiving a second message from the support agent about the first page of the online financial document using the chat window. 23. The non transitory computer usable medium of claim 20 , wherein the support agent is viewing the first page of the online financial document while receiving the first message from the user and sending the second message to the user. | 0.5 |
9,020,947 | 17 | 18 | 17. The one or more computer-readable storage media of claim 14 , wherein the actions further comprise clustering the plurality of semi-structured pages based at least in part on at least one similarity of at least some of the plurality of semi-structured pages. | 17. The one or more computer-readable storage media of claim 14 , wherein the actions further comprise clustering the plurality of semi-structured pages based at least in part on at least one similarity of at least some of the plurality of semi-structured pages. 18. The one or more computer-readable storage media of claim 17 , wherein the at least one similarity is in tag path text data of at least some of the plurality of semi-structured pages. | 0.5 |
10,120,942 | 1 | 11 | 1. In a server, a method of rating a list of resource links indexed by a plurality of categories, the resource links pointing to resources on a network, the method comprising: receiving data representing user interactions by a plurality of users with resource links from a plurality of clients over the network, the resource links being associated with the plurality of categories; generating a usage table that includes a plurality of usage entries, wherein each of the plurality of usage entries includes a set of activity parameters that identifies a usage activity by one of the plurality of users of one of the resource links; calculating a user rating for each of the plurality of users in each of the plurality of categories using the usage table, wherein the rating for the user in said category is calculated as a function of the plurality of categories of the usage entries for the user within said category divided by the total number of usage entries within said category for the user; and rating the resource links using the calculated user ratings. | 1. In a server, a method of rating a list of resource links indexed by a plurality of categories, the resource links pointing to resources on a network, the method comprising: receiving data representing user interactions by a plurality of users with resource links from a plurality of clients over the network, the resource links being associated with the plurality of categories; generating a usage table that includes a plurality of usage entries, wherein each of the plurality of usage entries includes a set of activity parameters that identifies a usage activity by one of the plurality of users of one of the resource links; calculating a user rating for each of the plurality of users in each of the plurality of categories using the usage table, wherein the rating for the user in said category is calculated as a function of the plurality of categories of the usage entries for the user within said category divided by the total number of usage entries within said category for the user; and rating the resource links using the calculated user ratings. 11. A method according to claim 1 , wherein the user rating is a floating point number with a minimum value of 1.0 for users with no usage entries within one of the plurality of categories, and a higher value for users with usage entries within one of the plurality of categories, and each of the resource links ratings are a multiplication of the user ratings of all users that have accessed said resource link. | 0.5 |
9,171,263 | 1 | 6 | 1. A computer-implemented method, comprising: accessing a plurality of topics that each have an association with, or a potential association with, one or more automatically-determined expertise levels that are associated with a plurality of users of one or more computer-implemented systems; identifying computer-implemented content published by one user of the plurality of users; and inferring automatically an expertise level of the one user of the plurality of users that is associated with one topic of the plurality of topics, wherein the expertise level is inferred by a computer-implemented function executed on a processor-based device in accordance with an automatic analysis of the computer-implemented content. | 1. A computer-implemented method, comprising: accessing a plurality of topics that each have an association with, or a potential association with, one or more automatically-determined expertise levels that are associated with a plurality of users of one or more computer-implemented systems; identifying computer-implemented content published by one user of the plurality of users; and inferring automatically an expertise level of the one user of the plurality of users that is associated with one topic of the plurality of topics, wherein the expertise level is inferred by a computer-implemented function executed on a processor-based device in accordance with an automatic analysis of the computer-implemented content. 6. The method of claim 1 , further comprising: inferring automatically the expertise level of the one user of the plurality of users that is associated with the one topic of the plurality of topics, wherein the expertise level is further inferred by the computer-implemented function executed on the processor-based device in accordance with a plurality of usage behaviors associated with one or more other users. | 0.552061 |
8,055,603 | 16 | 17 | 16. A data processing system comprising: a bus; a processor connected to the bus; a memory connected to the bus, wherein the memory contains a set of instructions, and wherein the processor can execute the set of instructions to: receive a first synthetic event, wherein the first synthetic event is derived from a first cohort comprising a first set of data and a second cohort comprising a second set of data, wherein the first synthetic event comprises a third set of data representing a result of a mathematical computation defined by the operation S(p1)==>F(p2), wherein S comprises a set of input facts with probability p1, wherein the set of input facts comprise the first cohort and the second cohort, wherein F comprises an inferred event with probability p2, wherein the term “event” means a particular set of data that represents, encodes, or records at least one of a thing or happening, and wherein each of the first set of data, the second set of data, the first cohort, the second cohort, the first synthetic event, and subcomponents thereof all comprise different events; create a first rule set, wherein the first synthetic event is expected as a result of application of the first rule set to the first cohort and the second cohort; apply the first rule set to the first cohort and the second cohort, wherein a first result is achieved, and wherein the first result comprises a second event; compare the second event to the first synthetic event, wherein a comparison is formed, the comparison comprising additional data that can be used to describe a difference between the second event and the first synthetic event; and store the comparison. | 16. A data processing system comprising: a bus; a processor connected to the bus; a memory connected to the bus, wherein the memory contains a set of instructions, and wherein the processor can execute the set of instructions to: receive a first synthetic event, wherein the first synthetic event is derived from a first cohort comprising a first set of data and a second cohort comprising a second set of data, wherein the first synthetic event comprises a third set of data representing a result of a mathematical computation defined by the operation S(p1)==>F(p2), wherein S comprises a set of input facts with probability p1, wherein the set of input facts comprise the first cohort and the second cohort, wherein F comprises an inferred event with probability p2, wherein the term “event” means a particular set of data that represents, encodes, or records at least one of a thing or happening, and wherein each of the first set of data, the second set of data, the first cohort, the second cohort, the first synthetic event, and subcomponents thereof all comprise different events; create a first rule set, wherein the first synthetic event is expected as a result of application of the first rule set to the first cohort and the second cohort; apply the first rule set to the first cohort and the second cohort, wherein a first result is achieved, and wherein the first result comprises a second event; compare the second event to the first synthetic event, wherein a comparison is formed, the comparison comprising additional data that can be used to describe a difference between the second event and the first synthetic event; and store the comparison. 17. The data processing system of claim 16 wherein the second event is different than the first synthetic event, and wherein the processor can further execute the set of instructions to: after comparing, modify the first rule set to form a second rule set, wherein modifying is based at least in part on the comparison; apply the second rule set to the first cohort and the second cohort, wherein a second result is achieved, and wherein the second result comprises a third event; compare the third event to the first synthetic event, wherein a second comparison is formed, the second comparison comprising further data that can be used to describe a second difference between the third event and the first synthetic event; and store the second comparison. | 0.505882 |
8,831,957 | 1 | 2 | 1. A computer-implemented method comprising: receiving, at a processing system, data corresponding to an utterance; obtaining, at the processing system, location indicia for an area within a building where the utterance was spoken; determining, at the processing system, a set of likelihoods based on the location indicia, each likelihood in the set corresponding to a likelihood that the utterance was spoken in a particular area of the building from a plurality of candidate areas of the building; selecting, at the processing system, one or more candidate areas of the building from the plurality of candidate areas of the building based on the set of likelihoods; accessing, for each selected candidate area of the building, a model for speech recognition associated with the respective candidate area of the building; generating, at the processing system, a composite model using the accessed models for speech recognition and the likelihoods associated with the corresponding candidate areas of the building; and generating, at the processing system, a transcription of the utterance using the composite model. | 1. A computer-implemented method comprising: receiving, at a processing system, data corresponding to an utterance; obtaining, at the processing system, location indicia for an area within a building where the utterance was spoken; determining, at the processing system, a set of likelihoods based on the location indicia, each likelihood in the set corresponding to a likelihood that the utterance was spoken in a particular area of the building from a plurality of candidate areas of the building; selecting, at the processing system, one or more candidate areas of the building from the plurality of candidate areas of the building based on the set of likelihoods; accessing, for each selected candidate area of the building, a model for speech recognition associated with the respective candidate area of the building; generating, at the processing system, a composite model using the accessed models for speech recognition and the likelihoods associated with the corresponding candidate areas of the building; and generating, at the processing system, a transcription of the utterance using the composite model. 2. The method of claim 1 , wherein receiving data corresponding to the utterance comprises receiving data corresponding to the utterance from a client device, and wherein obtaining location indicia for an area within a building where the utterance was spoken comprises receiving location indicia for the area within the building where the utterance was spoken from the client device. | 0.547281 |
9,191,510 | 23 | 24 | 23. The computer program product of claim 14 , further comprising computer readable code to analyze a telephonic communication associated with the electronic customer communication, wherein analyzing the telephonic voice communication includes: receiving a telephonic communication between a first communicant to the telephonic communication and a second communicant to the telephonic communication; separating the telephonic communication into at least first constituent voice data, the first constituent voice data being generated by the first communicant and the second constituent voice data being generated by the second communicant; analyzing one of the separated first and second constituent voice data by mining the separated one of the first and second constituent voice data and applying a predetermined linguistic-based psychological behavioral model to the one of the separated first and second constituent voice data; and, generating behavioral assessment data including a personality type corresponding to the analyzed one of the separated first and second constituent voice data based on the analyzing of constituent voice data and based on behavioral assessment data for the electronic customer communication data. | 23. The computer program product of claim 14 , further comprising computer readable code to analyze a telephonic communication associated with the electronic customer communication, wherein analyzing the telephonic voice communication includes: receiving a telephonic communication between a first communicant to the telephonic communication and a second communicant to the telephonic communication; separating the telephonic communication into at least first constituent voice data, the first constituent voice data being generated by the first communicant and the second constituent voice data being generated by the second communicant; analyzing one of the separated first and second constituent voice data by mining the separated one of the first and second constituent voice data and applying a predetermined linguistic-based psychological behavioral model to the one of the separated first and second constituent voice data; and, generating behavioral assessment data including a personality type corresponding to the analyzed one of the separated first and second constituent voice data based on the analyzing of constituent voice data and based on behavioral assessment data for the electronic customer communication data. 24. The computer program product of claim 23 , wherein at least one of the first and second constituent voice data is aggregated with the electronic communication data, and a text file is generated from aggregated data for applying the predetermined linguistic-based psychological behavioral model. | 0.5 |
8,635,058 | 12 | 15 | 12. A method of increasing the relevance of a media content communicated to consumers who are consuming the media content, the media content being displayed on a media device, the media device being public display advertising signage fixed in a public view location and typically only visually accessible to consumers, the method comprising: associating a consumer with a personal device and the personal device with a human language preference of the consumer: affixing the media device, in public view, visually accessible by the consumer; syncing the personal device with the media device, when the consumer, in possession of the personal device, is within viewable proximity of the media device; determining a preferred human language, by way of data communicating the human language preference associated with the personal device synced with the media device or synced with a network resource which manages the media content associated with the media device, preferably the preferred human language being determined based in part on closest match with the human language preference of the consumer; and communicating at least portion of audio or video of the media content in the preferred human language, on the media device, to all consumers visually proximate the media device, wherein communicating the media content in the preferred human language increases relevance of the media content with the consumer. | 12. A method of increasing the relevance of a media content communicated to consumers who are consuming the media content, the media content being displayed on a media device, the media device being public display advertising signage fixed in a public view location and typically only visually accessible to consumers, the method comprising: associating a consumer with a personal device and the personal device with a human language preference of the consumer: affixing the media device, in public view, visually accessible by the consumer; syncing the personal device with the media device, when the consumer, in possession of the personal device, is within viewable proximity of the media device; determining a preferred human language, by way of data communicating the human language preference associated with the personal device synced with the media device or synced with a network resource which manages the media content associated with the media device, preferably the preferred human language being determined based in part on closest match with the human language preference of the consumer; and communicating at least portion of audio or video of the media content in the preferred human language, on the media device, to all consumers visually proximate the media device, wherein communicating the media content in the preferred human language increases relevance of the media content with the consumer. 15. The method in accordance with claim 12 , further comprising: receiving at least portion of audio or video associated with the media content on the personal device. | 0.688433 |
9,767,788 | 1 | 4 | 1. A method for speech synthesis based on a large Chinese corpus, comprising: utilizing a prosodic structure prediction model to carry out prosodic structure prediction processing on input text to provide at least two alternative prosodic boundary partitioning solutions, prosodic units located at a same location in the at least two alternative prosodic boundary partitioning solutions being different; acquiring structure probability information about a prosodic unit in the at least two alternative prosodic boundary partitioning solutions according to statistics taken beforehand on data in a Chinese speech corpus, wherein the structure probability information includes a structure probability that the prosodic unit appears at a head or a tail of a prosodic word, a prosodic phrase or an intonation phrase in the Chinese speech corpus; calculating output probabilities of the at least two alternative prosodic boundary partitioning solutions utilizing an output probability calculation function according to the structure probability information; and determining, in the at least two alternative prosodic boundary partitioning solutions, an alternative prosodic boundary partitioning solution of which the output probability is the maximum as a prosodic boundary partitioning solution; and carrying out speech synthesis by acoustic processing to convert the input text into a speech having a pause point and a pause time length according to the determined alternative prosodic boundary partitioning solution. | 1. A method for speech synthesis based on a large Chinese corpus, comprising: utilizing a prosodic structure prediction model to carry out prosodic structure prediction processing on input text to provide at least two alternative prosodic boundary partitioning solutions, prosodic units located at a same location in the at least two alternative prosodic boundary partitioning solutions being different; acquiring structure probability information about a prosodic unit in the at least two alternative prosodic boundary partitioning solutions according to statistics taken beforehand on data in a Chinese speech corpus, wherein the structure probability information includes a structure probability that the prosodic unit appears at a head or a tail of a prosodic word, a prosodic phrase or an intonation phrase in the Chinese speech corpus; calculating output probabilities of the at least two alternative prosodic boundary partitioning solutions utilizing an output probability calculation function according to the structure probability information; and determining, in the at least two alternative prosodic boundary partitioning solutions, an alternative prosodic boundary partitioning solution of which the output probability is the maximum as a prosodic boundary partitioning solution; and carrying out speech synthesis by acoustic processing to convert the input text into a speech having a pause point and a pause time length according to the determined alternative prosodic boundary partitioning solution. 4. The method of claim 1 , wherein prosodic boundaries partitioned by the at least two alternative prosodic boundary partitioning solutions comprise a prosodic word boundary, a prosodic phrase boundary and an intonation phrase boundary, or a combination thereof. | 0.816269 |
9,020,923 | 11 | 17 | 11. A system, comprising: at least one processor; and memory storing instructions configured to instruct the at least one processor to provide a first webpage to configure a web browser to show a user interface in a window, the user interface configured to search music, the user interface comprising a plurality of search tools including a keyword search tool having a first user interface element configured to receive a set of keywords from a user, the keyword search tool configured to identify a set of music search results based on matching with the keywords, a set of filter tools having at least one second user interface element separate from the first user interface element and configured to receive a set of filtering options, the set of filter tools configured to filter the set of music search results based on the filter options specified in the at least one second user interface element, wherein the at least one second user interface element of the set of filter tools is capable of receiving the set of filtering options without the user providing input to the first user interface element of the keyword search tool, wherein the keyword search tool is configured to cause the set of filter tools to apply filter options corresponding to keywords received from the user in the keyword search tool, and wherein the set of filter tools are configured to cause the keyword search tool to receive keywords corresponding to filter options applied by user in the set filter tools; and a result panel configured to show the set of music search results as a list of items in the first webpage, each of the items corresponding to a music piece; wherein when an item in the list corresponding to a search result of the set of music search results is selected by the user in the user interface, the selected item within the list corresponding to the music search result expands within the result panel to present, inside the list at a location near the selected search result, an explore-more button, an action button, an audio player showing a waveform representation of audio of the selected music search result, a description of the selected music search result, and artwork associated with the search result; wherein when the filter tools are used to modify search criteria, the result panel updates search results displayed within the result panel without leaving the first webpage; and wherein a selection of the explore-more button causes, determining acoustic attributes of a piece of music in the search result in which the explore-more button is presented, the acoustic attributes based on numerical measurements of audio signals in the piece of music, initiating a new search using at least the acoustic attributes, wherein the acoustic attributes cannot be searched using the keyword search tool, and presenting results of the new search in a list ordered according to a degree of acoustic similarity with the piece of music. | 11. A system, comprising: at least one processor; and memory storing instructions configured to instruct the at least one processor to provide a first webpage to configure a web browser to show a user interface in a window, the user interface configured to search music, the user interface comprising a plurality of search tools including a keyword search tool having a first user interface element configured to receive a set of keywords from a user, the keyword search tool configured to identify a set of music search results based on matching with the keywords, a set of filter tools having at least one second user interface element separate from the first user interface element and configured to receive a set of filtering options, the set of filter tools configured to filter the set of music search results based on the filter options specified in the at least one second user interface element, wherein the at least one second user interface element of the set of filter tools is capable of receiving the set of filtering options without the user providing input to the first user interface element of the keyword search tool, wherein the keyword search tool is configured to cause the set of filter tools to apply filter options corresponding to keywords received from the user in the keyword search tool, and wherein the set of filter tools are configured to cause the keyword search tool to receive keywords corresponding to filter options applied by user in the set filter tools; and a result panel configured to show the set of music search results as a list of items in the first webpage, each of the items corresponding to a music piece; wherein when an item in the list corresponding to a search result of the set of music search results is selected by the user in the user interface, the selected item within the list corresponding to the music search result expands within the result panel to present, inside the list at a location near the selected search result, an explore-more button, an action button, an audio player showing a waveform representation of audio of the selected music search result, a description of the selected music search result, and artwork associated with the search result; wherein when the filter tools are used to modify search criteria, the result panel updates search results displayed within the result panel without leaving the first webpage; and wherein a selection of the explore-more button causes, determining acoustic attributes of a piece of music in the search result in which the explore-more button is presented, the acoustic attributes based on numerical measurements of audio signals in the piece of music, initiating a new search using at least the acoustic attributes, wherein the acoustic attributes cannot be searched using the keyword search tool, and presenting results of the new search in a list ordered according to a degree of acoustic similarity with the piece of music. 17. The system of claim 11 , wherein the expanded search result further comprises at least one of: itemized information relating to the music search result; and additional results by either a composer or full score of the search result. | 0.740088 |
8,874,589 | 10 | 11 | 10. A system for setting a threshold similarity score value for a first plurality of network device identifiers, comprising: a hardware processing circuit operable to: receive the first plurality of network device identifiers and characteristic data associated with network activity of each of the first plurality of network device identifiers; receive a second plurality of network device identifiers that do not appear in the first plurality of network device identifiers and characteristic data associated with network activity of each of the second plurality of network device identifiers; calculate, for each network device of the second plurality of network device identifiers, a similarity score that represents a degree of similarity between the characteristic data for the network device identifier of the second plurality and the characteristic data for the network device identifiers of the first plurality; designate a performance target relating to a factor indicative of an interest in or usefulness of content placed on a webpage, the performance target used to identify a smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; designate a threshold similarity score value selected as a starting value for determining a lowest similarity score value that is used to identify the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; identify a first number of network device identifiers from the second plurality that have similarity scores above the threshold similarity score value; receive, for each of the identified network device identifiers of the second plurality that have a similarity score above the threshold similarity score value, performance statistics data corresponding to the factor related to the designated performance target; aggregate the performance statistics data of each of the identified network device identifiers to determine an aggregate performance statistics data; determine, from the aggregate performance statistics data, that the first number of network device identifiers is not the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; iteratively adjust, responsive to determining that the first number of network device identifiers is not the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target, the threshold similarity score value to identify the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; and set the adjusted threshold similarity score value to an experimental threshold similarity score value that represents the lowest similarity score value that identifies the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target. | 10. A system for setting a threshold similarity score value for a first plurality of network device identifiers, comprising: a hardware processing circuit operable to: receive the first plurality of network device identifiers and characteristic data associated with network activity of each of the first plurality of network device identifiers; receive a second plurality of network device identifiers that do not appear in the first plurality of network device identifiers and characteristic data associated with network activity of each of the second plurality of network device identifiers; calculate, for each network device of the second plurality of network device identifiers, a similarity score that represents a degree of similarity between the characteristic data for the network device identifier of the second plurality and the characteristic data for the network device identifiers of the first plurality; designate a performance target relating to a factor indicative of an interest in or usefulness of content placed on a webpage, the performance target used to identify a smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; designate a threshold similarity score value selected as a starting value for determining a lowest similarity score value that is used to identify the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; identify a first number of network device identifiers from the second plurality that have similarity scores above the threshold similarity score value; receive, for each of the identified network device identifiers of the second plurality that have a similarity score above the threshold similarity score value, performance statistics data corresponding to the factor related to the designated performance target; aggregate the performance statistics data of each of the identified network device identifiers to determine an aggregate performance statistics data; determine, from the aggregate performance statistics data, that the first number of network device identifiers is not the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; iteratively adjust, responsive to determining that the first number of network device identifiers is not the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target, the threshold similarity score value to identify the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; and set the adjusted threshold similarity score value to an experimental threshold similarity score value that represents the lowest similarity score value that identifies the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target. 11. The system of claim 10 , wherein the designated performance target is at least one of a number of devices that qualify as a similar device to the first plurality of network device identifiers, a click through rate for content, a number of conversions, a conversion per dollar and a total revenue. | 0.673203 |
5,526,407 | 1 | 8 | 1. A method for recording, categorizing, organizing, managing and retrieving speech information, said method comprising, a. obtaining a speech stream, b. storing the speech stream in at least a temporary storage, c. extracting multiple, selected features from the speech stream, wherein the multiple features include the speaker's identity or location, duration of speech phrases, and pauses in speaking, d. constructing a visual representation of the selected features of the speech stream, e. providing the visual representation to a user, f. categorizing portions of the speech stream, with or without the aid of the representation, by at least one of the following categorization techniques: user command and, automatic recognition of speech qualities, including tempo, fundamental pitch, and phonemes, and g. storing, in at least a temporary storage, data structure which represents the categorized portions of the speech stream. | 1. A method for recording, categorizing, organizing, managing and retrieving speech information, said method comprising, a. obtaining a speech stream, b. storing the speech stream in at least a temporary storage, c. extracting multiple, selected features from the speech stream, wherein the multiple features include the speaker's identity or location, duration of speech phrases, and pauses in speaking, d. constructing a visual representation of the selected features of the speech stream, e. providing the visual representation to a user, f. categorizing portions of the speech stream, with or without the aid of the representation, by at least one of the following categorization techniques: user command and, automatic recognition of speech qualities, including tempo, fundamental pitch, and phonemes, and g. storing, in at least a temporary storage, data structure which represents the categorized portions of the speech stream. 8. The invention defined in claim 1 wherein the categorization determines which portions of the speech stream are saved in permanent storage. | 0.821519 |
8,024,372 | 15 | 24 | 15. A computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for constructing a model that generates text, the method comprising: representing a concept as a cluster node; representing a word as a terminal node; assigning a weight to a link between two nodes; and training the model based on a set of documents, comprising: for each cluster node, computing a probabilistic cost of a corresponding concept existing in a document but not triggering any words. | 15. A computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for constructing a model that generates text, the method comprising: representing a concept as a cluster node; representing a word as a terminal node; assigning a weight to a link between two nodes; and training the model based on a set of documents, comprising: for each cluster node, computing a probabilistic cost of a corresponding concept existing in a document but not triggering any words. 24. The computer-readable storage medium of claim 15 , wherein the method further comprises computing an activation for each cluster node in each document, wherein the activation indicates how many terminal nodes the cluster node can trigger. | 0.657224 |
9,880,696 | 4 | 5 | 4. The computer system of claim 3 , wherein the one or more hardware computer processors are further configured to execute code in order to cause the system to: write the new information to the one or more data sources. | 4. The computer system of claim 3 , wherein the one or more hardware computer processors are further configured to execute code in order to cause the system to: write the new information to the one or more data sources. 5. The computer system of claim 4 , wherein the one or more hardware computer processors are further configured to execute code in order to cause the system to: process the parameter according to the function call before executing the second section of code. | 0.5 |
7,933,863 | 6 | 10 | 6. The database management system according to claim 1 , wherein the at least one artificial intelligence frame includes a plurality of slots in which entities involved in the situation are stored. | 6. The database management system according to claim 1 , wherein the at least one artificial intelligence frame includes a plurality of slots in which entities involved in the situation are stored. 10. The database management system according to claim 6 , wherein the at least one entity in at least one of the slots carries a value indicating that the relationship of the entity in the slot with respect to another entity in a related slot is at least one of causal and dependent, and the context modeler is arranged to assess the value. | 0.505814 |
8,694,483 | 1 | 12 | 1. A method for assisting a user to develop a query in a natural language, comprising: storing logs comprising information derived from prior user search sessions in which user queries were input to a search engine for retrieving responsive instances from a knowledge base; storing a collection of query suggestions, each of the query suggestions formulated to retrieve at least one responsive instance in the knowledge base, each query suggestion being constructed from an index of the knowledge base and comprising a linguistically coherent expression which includes one or a group of syntactically related words, the query suggestion having a surface form which is presented to a user and an underlying form, and wherein at least one instance of each query suggestion is present in the knowledge base; ranking the query suggestions in the collection, based at least in part on the stored logs and the frequency of instances of the query suggestion in the knowledge base; receiving a user's query in a natural language; and while the user's query is being entered, with a computer processor, generating a subset of the ranked collection of query suggestions and presenting at least one of the subset to the user as a candidate for a user query, the subset being based on that portion of the user's query already entered, the presentation of query suggestions in the subset of query suggestions being based on their respective rankings in the collection, whereby at least some of the presented query suggestions are alternate queries rather than extensions of the user's query. | 1. A method for assisting a user to develop a query in a natural language, comprising: storing logs comprising information derived from prior user search sessions in which user queries were input to a search engine for retrieving responsive instances from a knowledge base; storing a collection of query suggestions, each of the query suggestions formulated to retrieve at least one responsive instance in the knowledge base, each query suggestion being constructed from an index of the knowledge base and comprising a linguistically coherent expression which includes one or a group of syntactically related words, the query suggestion having a surface form which is presented to a user and an underlying form, and wherein at least one instance of each query suggestion is present in the knowledge base; ranking the query suggestions in the collection, based at least in part on the stored logs and the frequency of instances of the query suggestion in the knowledge base; receiving a user's query in a natural language; and while the user's query is being entered, with a computer processor, generating a subset of the ranked collection of query suggestions and presenting at least one of the subset to the user as a candidate for a user query, the subset being based on that portion of the user's query already entered, the presentation of query suggestions in the subset of query suggestions being based on their respective rankings in the collection, whereby at least some of the presented query suggestions are alternate queries rather than extensions of the user's query. 12. The method of claim 1 , wherein the ranking of query suggestions is based at least in part on a relationship between one of the query suggestions and the knowledge base, the ranking of each query suggestion optionally being based at least in part on scores of responsive instances in the knowledge base. | 0.5 |
7,565,350 | 9 | 12 | 9. A web page classification method, comprising: crawling, via a processor, a corpus of web pages and providing the web page to a feature extractor; extracting at least one feature, from the received web page using a feature extractor, wherein the at least one feature comprises one or more of the following: a count of the number of occurrences of a blog-related word in the web page, a first uniform resource locator (URL) corresponding to the host of the web page, a second URL contained inside the web page that is indicative of a hyperlink to a blog site, at least one substring that is a part of the first URL, and whether the web page contains an ATOM feed or an RSS feed, the feature extractor further configured for extracting the contents of the web page and generating therefrom a set of observed values, wherein each observed value is associated with a feature in the web rage that provides an indication that the web page is a blog page, the set of observed values including a first observed value that is generated based on the number of occurrences in the web page of a non-markup word indicative of a blog; and classifying the web page as being a blog page or not based on an evaluation of the at least one extracted feature, the evaluation comprising application of i) a heavier classifier weight to the first URL than to the second URL contained inside the web page, and ii) a heavier classifier weight to the second URL than the substring that is a part of the first URL. | 9. A web page classification method, comprising: crawling, via a processor, a corpus of web pages and providing the web page to a feature extractor; extracting at least one feature, from the received web page using a feature extractor, wherein the at least one feature comprises one or more of the following: a count of the number of occurrences of a blog-related word in the web page, a first uniform resource locator (URL) corresponding to the host of the web page, a second URL contained inside the web page that is indicative of a hyperlink to a blog site, at least one substring that is a part of the first URL, and whether the web page contains an ATOM feed or an RSS feed, the feature extractor further configured for extracting the contents of the web page and generating therefrom a set of observed values, wherein each observed value is associated with a feature in the web rage that provides an indication that the web page is a blog page, the set of observed values including a first observed value that is generated based on the number of occurrences in the web page of a non-markup word indicative of a blog; and classifying the web page as being a blog page or not based on an evaluation of the at least one extracted feature, the evaluation comprising application of i) a heavier classifier weight to the first URL than to the second URL contained inside the web page, and ii) a heavier classifier weight to the second URL than the substring that is a part of the first URL. 12. The method of claim 9 , further comprising: forming a set of web pages that are classified as being a blog page; and identifying a top level blog in the set of web pages. | 0.599078 |
9,542,392 | 10 | 13 | 10. A non-transitory computer readable storage medium storing executable computer program instructions for mapping supplemental content layers to an electronic source document stored by an electronic publishing platform, the source document being a later edition of an electronic target document, the computer program instructions comprising instructions for: accessing the target document, the target document having an electronic supplemental content layer including electronic content associated with content of the target document, wherein portions of the electronic content of the supplemental content layer are mapped to respective content items in the target document, and wherein the target document is an earlier edition of the source document; for each of a plurality of content items in the target document: identifying a content item in the source document similar to the content item in the target document; adding, to an index stored by the electronic publishing platform, a mapping between the identified content item in the source document and the content item in the target document; and associating the portion of the electronic content of the supplemental content layer mapped to the content item in the target document with the identified content item in the source document based on the index; and storing the portions of electronic content of the supplemental content layer mapped to content items in the source document as a supplemental content layer associated with the source document. | 10. A non-transitory computer readable storage medium storing executable computer program instructions for mapping supplemental content layers to an electronic source document stored by an electronic publishing platform, the source document being a later edition of an electronic target document, the computer program instructions comprising instructions for: accessing the target document, the target document having an electronic supplemental content layer including electronic content associated with content of the target document, wherein portions of the electronic content of the supplemental content layer are mapped to respective content items in the target document, and wherein the target document is an earlier edition of the source document; for each of a plurality of content items in the target document: identifying a content item in the source document similar to the content item in the target document; adding, to an index stored by the electronic publishing platform, a mapping between the identified content item in the source document and the content item in the target document; and associating the portion of the electronic content of the supplemental content layer mapped to the content item in the target document with the identified content item in the source document based on the index; and storing the portions of electronic content of the supplemental content layer mapped to content items in the source document as a supplemental content layer associated with the source document. 13. The non-transitory computer readable storage medium of claim 10 , wherein adding the mapping between an identified source document content item and a target document content item to the index stored by the electronic publishing platform comprises: identifying a location of the identified source document content item in the source document; identifying a location of the target document content item in the target document; and storing a mapping from the identified location of the source document content item to the identified location of the target document content item. | 0.5 |
9,032,343 | 19 | 21 | 19. A device formed by the process comprising: generating a hardware description language (HDL) implementation of a first circuit design; receiving an HDL or netlist implementation of a public portion of a second circuit design, the second circuit design also including a secret portion not included with the public portion; receiving an HDL or netlist implementation of an interface between the public portion and the secret portion, the interface including one or more boundary locations between the secret portion and the public portion; generating an HDL implementation of an integrated design formed by integrating the HDL implementation of the first circuit design with the public portion of the second design and the interface; receiving an exclusion list of resources to be reserved for a secret portion of the second circuit design; generating a programming file for the integrated design including programming bits for configuring the integrated design into the device; programming the programming bits in the programming file for the integrated design into the device; receiving programming bits for the secret portion of the second circuit design; and programming the programming bits for the secret portion of the second circuit design into the device after the programming bits for the integrated circuit design have been programmed into the device. | 19. A device formed by the process comprising: generating a hardware description language (HDL) implementation of a first circuit design; receiving an HDL or netlist implementation of a public portion of a second circuit design, the second circuit design also including a secret portion not included with the public portion; receiving an HDL or netlist implementation of an interface between the public portion and the secret portion, the interface including one or more boundary locations between the secret portion and the public portion; generating an HDL implementation of an integrated design formed by integrating the HDL implementation of the first circuit design with the public portion of the second design and the interface; receiving an exclusion list of resources to be reserved for a secret portion of the second circuit design; generating a programming file for the integrated design including programming bits for configuring the integrated design into the device; programming the programming bits in the programming file for the integrated design into the device; receiving programming bits for the secret portion of the second circuit design; and programming the programming bits for the secret portion of the second circuit design into the device after the programming bits for the integrated circuit design have been programmed into the device. 21. The device of claim 19 , wherein the interface includes one or more boundary lookup tables (LUTs) for mapping signals from the secret portion to the public portion and from the public portion to the secret portion. | 0.5 |
9,535,506 | 1 | 4 | 1. At least one non-transitory computer readable storage medium having instructions stored thereon that, when executed on a machine, cause the machine to: receive data from a motion sensor; select a subset of one or more gesture recognition algorithms from a plurality of gesture recognition algorithms based, at least in part, on an amplitude of the data; determine an energy magnitude of the data based on the amplitude of the data; and determine a gesture from the data based, at least in part, on applying the subset of gesture recognition algorithm(s) to the data. | 1. At least one non-transitory computer readable storage medium having instructions stored thereon that, when executed on a machine, cause the machine to: receive data from a motion sensor; select a subset of one or more gesture recognition algorithms from a plurality of gesture recognition algorithms based, at least in part, on an amplitude of the data; determine an energy magnitude of the data based on the amplitude of the data; and determine a gesture from the data based, at least in part, on applying the subset of gesture recognition algorithm(s) to the data. 4. The at least one computer readable storage medium of claim 1 , the machine to further: determine a frequency spectrum of the data based, at least in part, on the amplitude of the data and a phase of the data. | 0.695965 |
8,145,472 | 15 | 18 | 15. The system of claim 1 , further comprising a dialog manager, wherein the dialog manager manages an ongoing dialog between a plurality of dialog participants who require language translation services, wherein the dialog manager obtains the needed translations by communicating with the request distribution and response assembly systems, and wherein the dialog manager presents translation output to dialog participants using any available user-interface, including the use of fonts, color, shading, grayscale, animation, and sound to display or otherwise communicate the source and translated text fragments, translation confidence levels, other metadata, and/or alerts. | 15. The system of claim 1 , further comprising a dialog manager, wherein the dialog manager manages an ongoing dialog between a plurality of dialog participants who require language translation services, wherein the dialog manager obtains the needed translations by communicating with the request distribution and response assembly systems, and wherein the dialog manager presents translation output to dialog participants using any available user-interface, including the use of fonts, color, shading, grayscale, animation, and sound to display or otherwise communicate the source and translated text fragments, translation confidence levels, other metadata, and/or alerts. 18. The system of claim 15 , wherein the dialog manager, translation request system, response assembly system, and the database generation system include abilities to identify, predict, and make use of a dialectical suite comprising a collection of colloquialisms, phrasings, or communication conventions that cluster, and wherein individual translation responses as well as translations assembled by the response assembly system are adjusted for correctness and comprehension based on the dialectical suite and an association of predicting words, phrases, and other conversational fragments. | 0.5 |
10,007,748 | 13 | 19 | 13. A system comprising: one or more memory devices storing non-transitory processor-executable code configured to implement instructions; one or more processors to execute the processor-executable code to cause the one or more processors to: identify at least one programming language construct associated with a safety data type of an algorithmic description representation of a circuit design, wherein the algorithmic description representation is specified in a first language; generate a second representation of the circuit design based on the algorithmic description representation and the safety data type, wherein the second representation being provided in a second language and including at least one safety feature that is based at least in part on the safety data type; and configuring a programmable logic device after the programmable logic device has been manufactured. | 13. A system comprising: one or more memory devices storing non-transitory processor-executable code configured to implement instructions; one or more processors to execute the processor-executable code to cause the one or more processors to: identify at least one programming language construct associated with a safety data type of an algorithmic description representation of a circuit design, wherein the algorithmic description representation is specified in a first language; generate a second representation of the circuit design based on the algorithmic description representation and the safety data type, wherein the second representation being provided in a second language and including at least one safety feature that is based at least in part on the safety data type; and configuring a programmable logic device after the programmable logic device has been manufactured. 19. The system of claim 13 , wherein the at least one programming language construct includes at least one function including at least one parameter defined using the safety data type. | 0.630522 |
8,798,996 | 16 | 17 | 16. One or more storage media storing instructions which, when executed by one or more processors, cause: determining a first context from among a plurality of contexts; based on the first context, identifying a first technique for analyzing text data, wherein each context of the plurality of contexts is associated with a different technique for analyzing text data; using the first technique to analyze a string of text that was generated based on audio data; wherein using the first technique comprises identifying a plurality of text segments based on one or more criteria, wherein each segment of the plurality of text segments comprises one or more words in the string of text, wherein at least one text segment of the plurality of text segments comprises a plurality of words; organizing the plurality of text segments into a list of items, wherein each text segment is a separate item in the list. | 16. One or more storage media storing instructions which, when executed by one or more processors, cause: determining a first context from among a plurality of contexts; based on the first context, identifying a first technique for analyzing text data, wherein each context of the plurality of contexts is associated with a different technique for analyzing text data; using the first technique to analyze a string of text that was generated based on audio data; wherein using the first technique comprises identifying a plurality of text segments based on one or more criteria, wherein each segment of the plurality of text segments comprises one or more words in the string of text, wherein at least one text segment of the plurality of text segments comprises a plurality of words; organizing the plurality of text segments into a list of items, wherein each text segment is a separate item in the list. 17. The one or more storage media of claim 16 , wherein the instructions, when executed by the one or more processors, further cause causing the list to be displayed on a computer display device. | 0.763923 |
8,433,569 | 8 | 13 | 8. A system comprising: a processor; and a non-transitory computer-readable storage medium having stored therein instructions which, when executed by the processor, cause the processor to perform a method comprising: receiving a first speech signal and a second speech signal; generating feature coefficients based at least in part on the first speech signal and the second speech signal; comparing the feature coefficients to a codebook to yield an utterance similarity value, wherein the codebook is associated with a database of reference speech signals; if the utterance similarity value is above a threshold, providing access to a service and adding at least one of the first speech signal and the second speech signal to the database of reference signals. | 8. A system comprising: a processor; and a non-transitory computer-readable storage medium having stored therein instructions which, when executed by the processor, cause the processor to perform a method comprising: receiving a first speech signal and a second speech signal; generating feature coefficients based at least in part on the first speech signal and the second speech signal; comparing the feature coefficients to a codebook to yield an utterance similarity value, wherein the codebook is associated with a database of reference speech signals; if the utterance similarity value is above a threshold, providing access to a service and adding at least one of the first speech signal and the second speech signal to the database of reference signals. 13. The system of claim 8 , the non-transitory computer-readable storage medium storing further instructions which, when executed by the processor, cause the processor to perform a method further comprising, if the utterance similarity value is below the threshold, requesting a user to repeat at least one of the first speech signal and the second speech signal. | 0.5 |
9,031,844 | 16 | 18 | 16. A computing device comprising a computer-readable medium, the computer-readable medium comprising instructions that, when executed by a processor, cause the processor to perform acts comprising: greedily learning weights between hidden layers of a deep belief network (DBN) that is configured for employment in an automatic speech recognition (ASR) system, wherein the DBN is temporally parameter-tied and an uppermost layer in the DBN is a linear-chain conditional random field (CRF), the linear chain CRF comprises a plurality of output units that are representative of respective output states, each output state being one of a phone or senone; providing training data to the DBN to optimize a log of conditional probabilities of output sequences of the DBN, an output sequence comprising a sequence of output states represented by the output units; and jointly optimizing the weights between the DBN, transition probabilities between the output units in the CRF, and language model scores in the DBN based upon the log of the conditional probabilities of output sequences produced by the DBN. | 16. A computing device comprising a computer-readable medium, the computer-readable medium comprising instructions that, when executed by a processor, cause the processor to perform acts comprising: greedily learning weights between hidden layers of a deep belief network (DBN) that is configured for employment in an automatic speech recognition (ASR) system, wherein the DBN is temporally parameter-tied and an uppermost layer in the DBN is a linear-chain conditional random field (CRF), the linear chain CRF comprises a plurality of output units that are representative of respective output states, each output state being one of a phone or senone; providing training data to the DBN to optimize a log of conditional probabilities of output sequences of the DBN, an output sequence comprising a sequence of output states represented by the output units; and jointly optimizing the weights between the DBN, transition probabilities between the output units in the CRF, and language model scores in the DBN based upon the log of the conditional probabilities of output sequences produced by the DBN. 18. The computing device of claim 16 , wherein greedily learning the weights between the hidden layers comprises treating pairs of adjacent hidden layers in the DBN as a Restricted Boltzmann Machine. | 0.53066 |
7,689,927 | 51 | 54 | 51. A computer-readable medium including computer-executable instructions for performing a method for managing a view-size of an electronic document and useful for displaying information on a display device, the method comprising: providing a user interface window; displaying at least a portion of the electronic document in the user interface window; storing a viewable document section corresponding to the view-size of the electronic document, wherein the viewable document section includes boundary information cumulative of only portions of the electronic document that have previously been displayed in the user interface window; providing a first system that enables a user to change a displayed portion of the electronic document in the user interface window when at least a portion of information indicated by the stored boundary information in the viewable document section does not appear in the user interface window and the stored boundary information in the viewable document section is adjusted based on a registering activity of any digitizing user-input at an outer portion of the user interface window, wherein the first system enables a user only to change the displayed portion to include information that is indicated by the stored boundary information in the viewable document section; providing the viewable document section with an additional input to include information indicative of a registering activity of any digitizing user-input at an outer portion of the user interface window that associates a user-input extending beyond the outer portion of the user interface window, while suppressing any scrolling view handle display or similar scroll bar display; and providing a second system that enables a user to change a size of the user interface window, and responsive to the user interface window being enlarged, the stored boundary information in the viewable document section is adjusted based on any portion of the electronic document displayed for a first time within the user interface window. | 51. A computer-readable medium including computer-executable instructions for performing a method for managing a view-size of an electronic document and useful for displaying information on a display device, the method comprising: providing a user interface window; displaying at least a portion of the electronic document in the user interface window; storing a viewable document section corresponding to the view-size of the electronic document, wherein the viewable document section includes boundary information cumulative of only portions of the electronic document that have previously been displayed in the user interface window; providing a first system that enables a user to change a displayed portion of the electronic document in the user interface window when at least a portion of information indicated by the stored boundary information in the viewable document section does not appear in the user interface window and the stored boundary information in the viewable document section is adjusted based on a registering activity of any digitizing user-input at an outer portion of the user interface window, wherein the first system enables a user only to change the displayed portion to include information that is indicated by the stored boundary information in the viewable document section; providing the viewable document section with an additional input to include information indicative of a registering activity of any digitizing user-input at an outer portion of the user interface window that associates a user-input extending beyond the outer portion of the user interface window, while suppressing any scrolling view handle display or similar scroll bar display; and providing a second system that enables a user to change a size of the user interface window, and responsive to the user interface window being enlarged, the stored boundary information in the viewable document section is adjusted based on any portion of the electronic document displayed for a first time within the user interface window. 54. A computer-readable medium according to claim 51 , wherein the second system enables the size of the user interface window to be changed through a user input device drag operation. | 0.744444 |
9,471,566 | 8 | 19 | 8. The system as recited in claim 7 , wherein each syllable segmentation corresponds to one or more of the sentences. | 8. The system as recited in claim 7 , wherein each syllable segmentation corresponds to one or more of the sentences. 19. The system as recited in claim 8 , wherein words that are in the history cache are not pruned from the sentences. | 0.5 |
9,264,764 | 1 | 2 | 1. A media content based survey distribution and collection processor-implemented method, comprising: obtaining local TV program schedule listing data including a plurality of ad tags at a server, wherein a personal user mobile device provides indication of its geographical locality and the server obtains local TV program schedule listing data automatically responsive for the indicated geographical locality; providing the obtained TV program schedule listing data to the personal user mobile device; receiving a real-time user media program selection message from the personal user mobile device; retrieving an ad tag associated with the user selected media program from the local TV program schedule listing data; determining a timestamp associated with the retrieved ad tag indicating an air time of an ad segment played during the user selected media program; extracting key terms from the ad tag by parsing ad contents; querying a survey question list based on the extracted key terms; generating and providing a real-time survey question from the query to the personal user mobile device in synchronization with the ad segment based on the timestamp when the ad segment is being performed during the user selected media program, wherein the real-time survey question is provided to the user mobile device for real-time display around when the ad segment is being performed; and obtaining a user reaction to the survey question. | 1. A media content based survey distribution and collection processor-implemented method, comprising: obtaining local TV program schedule listing data including a plurality of ad tags at a server, wherein a personal user mobile device provides indication of its geographical locality and the server obtains local TV program schedule listing data automatically responsive for the indicated geographical locality; providing the obtained TV program schedule listing data to the personal user mobile device; receiving a real-time user media program selection message from the personal user mobile device; retrieving an ad tag associated with the user selected media program from the local TV program schedule listing data; determining a timestamp associated with the retrieved ad tag indicating an air time of an ad segment played during the user selected media program; extracting key terms from the ad tag by parsing ad contents; querying a survey question list based on the extracted key terms; generating and providing a real-time survey question from the query to the personal user mobile device in synchronization with the ad segment based on the timestamp when the ad segment is being performed during the user selected media program, wherein the real-time survey question is provided to the user mobile device for real-time display around when the ad segment is being performed; and obtaining a user reaction to the survey question. 2. The method of claim 1 , wherein the ad tag is related to an advertisement played during a commercial break associated with the user selected media program. | 0.5 |
9,262,506 | 7 | 9 | 7. The computer program product of claim 1 , wherein the computer readable program code is further configured to: evaluate the outlier documents having a classification in one or more categories other than the corresponding category of the master taxonomy to determine whether to create at least one new category; and create the at least one new category in the master taxonomy for the outlier documents in response to results of the evaluation. | 7. The computer program product of claim 1 , wherein the computer readable program code is further configured to: evaluate the outlier documents having a classification in one or more categories other than the corresponding category of the master taxonomy to determine whether to create at least one new category; and create the at least one new category in the master taxonomy for the outlier documents in response to results of the evaluation. 9. The computer program product of claim 7 , wherein the computer readable program code is further configured to: perform a classification to determine a mapping to the at least one new category of the master taxonomy utilizing documents of the taxonomy. | 0.5 |
8,904,281 | 1 | 6 | 1. A method of providing a multi-dimensional multi-user element vector interface on a display, the method comprising: generating, with a processor, a first element vector including a first group of elements, the first element vector corresponding to a first user, elements having at least one attribute from a set of characterization attributes; generating, with the processor, a second element vector including a second group of elements, the second element vector corresponding to a second user, elements having at least one attribute from the set of characterization attributes; displaying, on the display, the first element vector and the second element vector in the multi-user element interface such that the second element vector is substantially parallel to the first element vector; receiving an input including a selected attribute from the set of characterization attributes; generating, in response to the input, a third group of elements having the selected attribute from the first element vector and the second element vector; and displaying the third group of elements as an axis of elements, the axis of elements being at a non-zero angle to the first element vector and the second element vector. | 1. A method of providing a multi-dimensional multi-user element vector interface on a display, the method comprising: generating, with a processor, a first element vector including a first group of elements, the first element vector corresponding to a first user, elements having at least one attribute from a set of characterization attributes; generating, with the processor, a second element vector including a second group of elements, the second element vector corresponding to a second user, elements having at least one attribute from the set of characterization attributes; displaying, on the display, the first element vector and the second element vector in the multi-user element interface such that the second element vector is substantially parallel to the first element vector; receiving an input including a selected attribute from the set of characterization attributes; generating, in response to the input, a third group of elements having the selected attribute from the first element vector and the second element vector; and displaying the third group of elements as an axis of elements, the axis of elements being at a non-zero angle to the first element vector and the second element vector. 6. The method of claim 1 , wherein at least some of the elements are computer files. | 0.896552 |
7,949,648 | 9 | 10 | 9. The method according to claim 1 , wherein the filtering further comprises monitoring a depth for each said link, the depth being a reflection of relevance to said predefined particular subject. | 9. The method according to claim 1 , wherein the filtering further comprises monitoring a depth for each said link, the depth being a reflection of relevance to said predefined particular subject. 10. The method according to claim 9 , wherein said monitoring comprises: for a given said object being visited resulting from said link, setting a said depth of any links leading from said object to other objects to a depth of a link traversed to reach the given object; wherein said given object is determined to be relevant to said predefined particular subject, setting the depths of the links leading from said object to zero; and wherein said given object is determined not to be relevant to said predefined particular subject, incrementing the depths of the links leading from said object. | 0.5 |
8,751,477 | 12 | 19 | 12. A computer-based method of providing results in response to queries, comprising: transmitting the challenge keyword to a remote search engine computer system; receiving at least one reference result from the remote search engine computer system in response to the transmission of the challenge keyword to the remote search engine computer system; calculating a reference score, wherein the reference score is calculated based on the reference search result; entering a challenge keyword into at least a first engine; receiving at least one challenge result from the first engine in response to the challenge keyword; calculating a challenge answer score based on the challenge result; calculating a challenge reference score for the first engine based on a comparison of the challenge answer score for the first engine with the reference score; publishing the challenge reference score for the first engine; receiving a live query having a user keyword over a network from at least one live remote computer system; entering the user keyword into the first engine; receiving at least one live result from the first engine based on the user keyword; and transmitting the live result from the first engine over the network to the at least one live remote computer system. | 12. A computer-based method of providing results in response to queries, comprising: transmitting the challenge keyword to a remote search engine computer system; receiving at least one reference result from the remote search engine computer system in response to the transmission of the challenge keyword to the remote search engine computer system; calculating a reference score, wherein the reference score is calculated based on the reference search result; entering a challenge keyword into at least a first engine; receiving at least one challenge result from the first engine in response to the challenge keyword; calculating a challenge answer score based on the challenge result; calculating a challenge reference score for the first engine based on a comparison of the challenge answer score for the first engine with the reference score; publishing the challenge reference score for the first engine; receiving a live query having a user keyword over a network from at least one live remote computer system; entering the user keyword into the first engine; receiving at least one live result from the first engine based on the user keyword; and transmitting the live result from the first engine over the network to the at least one live remote computer system. 19. The method of claim 12 , further comprising: entering the challenge keyword into at least a second engine; receiving at least one challenge result from the second engine in response to the challenge keyword; calculating a challenge answer score based on the challenge result received from the second engine; calculating a challenge reference score for the second engine based on a comparison of the challenge answer score received from the second engine with the challenge reference score; publishing the challenge reference score for the second engine for analysis; entering the user keyword into the second engine; receiving at least on live result from the second engine based on the user keyword; and transmitting the live result received from the second engine over the network to the at least one live remote computer system. | 0.5 |
8,417,528 | 13 | 17 | 13. The method of claim 12 , further comprising: converting the phoneme graph to a word-phoneme graph, the word-phoneme graph assigning a word and associated phonetic transcription to each edge. | 13. The method of claim 12 , further comprising: converting the phoneme graph to a word-phoneme graph, the word-phoneme graph assigning a word and associated phonetic transcription to each edge. 17. The method according to claim 13 , wherein the word-phoneme graph includes time-synchronous information, the method further comprising: removing from the word-phoneme graph based, at least in part, on the time-synchronous information, words having no connection either forward or backward in time. | 0.5 |
9,652,227 | 8 | 9 | 8. The method of claim 1 , further comprising creating a refined data dictionary from the data dictionary by eliminating false positives for the variables present in the data dictionary. | 8. The method of claim 1 , further comprising creating a refined data dictionary from the data dictionary by eliminating false positives for the variables present in the data dictionary. 9. The method of claim 8 , wherein the false positives comprises two or more descriptions for the variable. | 0.5 |
9,600,460 | 13 | 14 | 13. The method of claim 11 , wherein the attribute of each note specifies the location in the document with which the note is associated. | 13. The method of claim 11 , wherein the attribute of each note specifies the location in the document with which the note is associated. 14. The method of claim 13 , further comprising: determining a page order of the locations in the document associated with the notes in the aggregated set; determining an order of the notes in the aggregated set based on the locations in the document with which the notes are associated and the determined page order of the locations within the document; and displaying the notes in the aggregated set in the determined order. | 0.5 |
8,037,164 | 1 | 9 | 1. A network service configuration management system for network addressing management by remotely managing the configuration of at least one network service, comprising: a management server; a database for forming a dynamic network address directory by storing a representation of the configuration of the network service an agent software component for accessing to the configuration in a native language of the network service wherein: the management server is adapted to access to the database; the management server and the agent software component are adapted to communicate synchronization information to each other and to synchronize the representation of the configuration of the network service in the database and the native language configuration of the network service with each other based on the synchronization information, the synchronization information being in a language different from the native language of the configuration of the network service; wherein the agent software component is adapted to convert the configuration in native language of the network service into a tree representation; wherein the agent software component is adapted to make a differential analysis of the configuration in tree representation between a new state and an older state and to provide a stream of elementary operations allowing a tree representation of the configuration in the new state to be built up by applying the stream of elementary operations to the tree representation of the configuration in the older state. | 1. A network service configuration management system for network addressing management by remotely managing the configuration of at least one network service, comprising: a management server; a database for forming a dynamic network address directory by storing a representation of the configuration of the network service an agent software component for accessing to the configuration in a native language of the network service wherein: the management server is adapted to access to the database; the management server and the agent software component are adapted to communicate synchronization information to each other and to synchronize the representation of the configuration of the network service in the database and the native language configuration of the network service with each other based on the synchronization information, the synchronization information being in a language different from the native language of the configuration of the network service; wherein the agent software component is adapted to convert the configuration in native language of the network service into a tree representation; wherein the agent software component is adapted to make a differential analysis of the configuration in tree representation between a new state and an older state and to provide a stream of elementary operations allowing a tree representation of the configuration in the new state to be built up by applying the stream of elementary operations to the tree representation of the configuration in the older state. 9. The system according to claim 1 for IP addressing management, wherein: the at least one network service is one among a DNS service, a DHCP service or a VLAN service; and the database is adapted to form a dynamic IP network address directory by storing a representation of the configuration of the network service. | 0.872786 |
6,100,890 | 28 | 30 | 28. The method of claim 21, further comprising: removing the entry film the bookmark list when the viewed page is not subsequently visited within a pre-determined time. | 28. The method of claim 21, further comprising: removing the entry film the bookmark list when the viewed page is not subsequently visited within a pre-determined time. 30. The method of claim 28, wherein the removing step further comprises moving the entry to an archive folder. | 0.517544 |
9,946,510 | 12 | 13 | 12. The mobile terminal of claim 1 , wherein a position of the displayed recording indicator is changed progressively as additional text is input onto the execution screen. | 12. The mobile terminal of claim 1 , wherein a position of the displayed recording indicator is changed progressively as additional text is input onto the execution screen. 13. The mobile terminal of claim 12 , wherein the controller is further configured to cause the touch screen to display a playback icon instead of the recording indicator when the recording of the voice memo is completed. | 0.5 |
9,729,479 | 9 | 11 | 9. A computer program product for providing contextual hints in an electronic message, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions when executed by a processor direct the processor to perform a method comprising: receiving a command to create a reply message to an original electronic message, the original electronic message comprising original text; determining one or more topics in the original text, the one or more topics summarizing one or more contexts in the original text; displaying the reply message with the one or more topics as contextual hints for the original text displayed as temporary text in a body of the reply message; receiving response text into the body of the reply message, corresponding to the one or more topics displayed as temporary text in the body of the reply message, from a user using the contextual hints while composing the reply message; receiving a command to send the reply message; removing the one or more topics displayed as temporary text from the body of the reply message; and sending the reply message with only the response text in the body of the reply message. | 9. A computer program product for providing contextual hints in an electronic message, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions when executed by a processor direct the processor to perform a method comprising: receiving a command to create a reply message to an original electronic message, the original electronic message comprising original text; determining one or more topics in the original text, the one or more topics summarizing one or more contexts in the original text; displaying the reply message with the one or more topics as contextual hints for the original text displayed as temporary text in a body of the reply message; receiving response text into the body of the reply message, corresponding to the one or more topics displayed as temporary text in the body of the reply message, from a user using the contextual hints while composing the reply message; receiving a command to send the reply message; removing the one or more topics displayed as temporary text from the body of the reply message; and sending the reply message with only the response text in the body of the reply message. 11. The computer program product of claim 9 , wherein the determining of the one or more topics in the original text comprises: scanning the original text; and identifying the one or more topics in the original text using an analysis including at least one of keyword matching and semantic analysis. | 0.736796 |
8,194,983 | 16 | 20 | 16. The system of claim 13 , wherein the first set of characteristic parameters is at least one of a line height, a word spacing, a line spacing, a number of pixels corresponding to each component, a width of each component, a height of each component, coordinates of each component, density of each component, and the aspect ratio of each component. | 16. The system of claim 13 , wherein the first set of characteristic parameters is at least one of a line height, a word spacing, a line spacing, a number of pixels corresponding to each component, a width of each component, a height of each component, coordinates of each component, density of each component, and the aspect ratio of each component. 20. The system of claim 16 , wherein for calculating the line spacing the processor is further configured to: create a histogram of a plurality of horizontal projections of the plurality of components, wherein a horizontal projection of the plurality of horizontal projections indicates a number of pixels associated with the plurality of components corresponding to each sweep of the raster scan; calculate an average distance between two consecutive maximum horizontal projections; and compute the line spacing based on the average distance. | 0.5 |
7,840,546 | 64 | 70 | 64. A method for optimizing data queries for related records in a reliable fashion, to be used with a system having a first computing device communicatively coupled with a second computing device, and communicatively coupled to a first database that stores real-world entity data, having said second computing device communicatively coupled with said first computing device, and communicatively coupled to a second database that stores real-world entity data, a first end-user interface communicatively coupled to said first database, and a second end-user interface communicatively coupled to said second database, comprising: providing a hierarchical system of Consolidation Strings for said first database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said first database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said first database, acting as a first data-source node in the overall system, by periodically communicating its Consolidation Strings to a second data-source node; providing a hierarchical system of Consolidation Strings for said second database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said second database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said second database, acting as a second data-source node in the overall system, by periodically communicating its Consolidation Strings to said first data-source node; providing the capability of said first end-user interface to allow a first end-user to query said first data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said second data-source node, wherein said first data-source node communicates consolidation information to said second data-source node, wherein said consolidation information is applied against a consolidation algorithm in said second data-source node, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view; and providing the capability of said second end-user interface to allow a second end-user to query said second data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said first data-source node, wherein said second data-source node communicates consolidation information to said first data-source node, wherein said consolidation information is applied against a consolidation algorithm in said first data-source node, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view. | 64. A method for optimizing data queries for related records in a reliable fashion, to be used with a system having a first computing device communicatively coupled with a second computing device, and communicatively coupled to a first database that stores real-world entity data, having said second computing device communicatively coupled with said first computing device, and communicatively coupled to a second database that stores real-world entity data, a first end-user interface communicatively coupled to said first database, and a second end-user interface communicatively coupled to said second database, comprising: providing a hierarchical system of Consolidation Strings for said first database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said first database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said first database, acting as a first data-source node in the overall system, by periodically communicating its Consolidation Strings to a second data-source node; providing a hierarchical system of Consolidation Strings for said second database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said second database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said second database, acting as a second data-source node in the overall system, by periodically communicating its Consolidation Strings to said first data-source node; providing the capability of said first end-user interface to allow a first end-user to query said first data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said second data-source node, wherein said first data-source node communicates consolidation information to said second data-source node, wherein said consolidation information is applied against a consolidation algorithm in said second data-source node, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view; and providing the capability of said second end-user interface to allow a second end-user to query said second data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said first data-source node, wherein said second data-source node communicates consolidation information to said first data-source node, wherein said consolidation information is applied against a consolidation algorithm in said first data-source node, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view. 70. The method in claim 64 , wherein said Inter-Node Consolidation is set up by communicating updated Consolidation Strings to another data-source node in a peer-to-peer fashion. | 0.804825 |
9,554,150 | 19 | 24 | 19. A non-transitory computer-readable data storage medium having instructions stored thereon that when executed cause a video coding device to code three-dimensional (3D) video data, the instructions causing the video coding device to: generate a current list of merging candidates for coding a video block of the 3D video data, wherein a maximum number of merging candidates in the current list of merging candidates is equal to 6, there are 20 possible combinations of list 0 and list 1 motion vectors of different bi-predictive merging candidates in lists of merging candidates having 5 bi-predictive merging candidates, and as part of generating the current list of merging candidates, the one or more processors: determine that a number of merging candidates initially in the current list of merging candidates is less than 5, wherein each respective value of a combination index from 0 to 11 corresponds to a respective pre-defined combination of values from 0 to 3; and in response to determining that the number of merging candidates in the current list of merging candidates is less than 5, performing the following for each respective value of the combination index from 0 to 11 until at least one of the following conditions is true: the respective value of the combination index is equal to the number of merging candidates initially in the current list of merging candidates multiplied by one less than the number of merging candidates initially in the current list of merging candidates, and the current list of merging candidates has 6 merging candidates: determine whether a first merging candidate in the current list of merging candidates has a list 0 motion vector and whether a second merging candidate in the current list of merging candidates has a list 1 motion vector, wherein the first merging candidate and the second merging candidate are at positions in the current list of merging candidates indicated by the pre-defined combination of values corresponding to the respective value of the combination index; responsive to determining the first merging candidate has a list 0 motion vector and the second merging candidate has a list 1 motion vector, derive a respective combined bi-predictive merging candidate, wherein the respective combined bi-predictive merging candidate is a combination of the list 0 motion vector of the first merging candidate and the list 1 motion vector of the second merging candidate, wherein the motion vector of the first merging candidate and the motion vector of the second merging candidate refer to pictures in different reference picture lists; and include the respective combined bi-predictive merging candidate in the current list of merging candidates. | 19. A non-transitory computer-readable data storage medium having instructions stored thereon that when executed cause a video coding device to code three-dimensional (3D) video data, the instructions causing the video coding device to: generate a current list of merging candidates for coding a video block of the 3D video data, wherein a maximum number of merging candidates in the current list of merging candidates is equal to 6, there are 20 possible combinations of list 0 and list 1 motion vectors of different bi-predictive merging candidates in lists of merging candidates having 5 bi-predictive merging candidates, and as part of generating the current list of merging candidates, the one or more processors: determine that a number of merging candidates initially in the current list of merging candidates is less than 5, wherein each respective value of a combination index from 0 to 11 corresponds to a respective pre-defined combination of values from 0 to 3; and in response to determining that the number of merging candidates in the current list of merging candidates is less than 5, performing the following for each respective value of the combination index from 0 to 11 until at least one of the following conditions is true: the respective value of the combination index is equal to the number of merging candidates initially in the current list of merging candidates multiplied by one less than the number of merging candidates initially in the current list of merging candidates, and the current list of merging candidates has 6 merging candidates: determine whether a first merging candidate in the current list of merging candidates has a list 0 motion vector and whether a second merging candidate in the current list of merging candidates has a list 1 motion vector, wherein the first merging candidate and the second merging candidate are at positions in the current list of merging candidates indicated by the pre-defined combination of values corresponding to the respective value of the combination index; responsive to determining the first merging candidate has a list 0 motion vector and the second merging candidate has a list 1 motion vector, derive a respective combined bi-predictive merging candidate, wherein the respective combined bi-predictive merging candidate is a combination of the list 0 motion vector of the first merging candidate and the list 1 motion vector of the second merging candidate, wherein the motion vector of the first merging candidate and the motion vector of the second merging candidate refer to pictures in different reference picture lists; and include the respective combined bi-predictive merging candidate in the current list of merging candidates. 24. The non-transitory computer-readable data storage medium of claim 19 , wherein the instructions cause the video coding device to derive the one or more combined bi-predictive merging candidates after inserting an inter-view prediction motion vector candidate (IPMVC), if available, in the current list of merging candidates, after performing a derivation process for spatial merging candidates, and after performing a derivation process for a temporal merging candidate, wherein the derivation process for spatial merging candidates derives and inserts up to four spatial motion vector candidates in the current list of merging candidates, and wherein the derivation process for the temporal merging candidate adds a temporal motion vector predictor (TMVP) candidate, if available, to the current list of merging candidates. | 0.5 |
8,074,176 | 1 | 14 | 1. A method for an electronic communications dialog between a plurality of users using digital images via a web portal, comprising the steps of: selecting a template for entering a plurality of words and associated images that constitute an initial electronic message; entering a plurality of words into the template corresponding to the initial electronic message; selecting a plurality of images from a visual dictionary associated with a user of the plurality of users, each of the plurality of images having a direct correspondence with the plurality of words entered into the template such that the plurality of images are configured to convey a message represented by the plurality of words to one or more of the plurality of users, and each of the plurality of images is associated with a definition provided by the user such that each of the plurality of images conveys one or more words based on the definition; inserting each image into the template in a sequence corresponding to the initial electronic message; and sending the initial electronic message containing the sequenced images to at least one other user via the web portal. | 1. A method for an electronic communications dialog between a plurality of users using digital images via a web portal, comprising the steps of: selecting a template for entering a plurality of words and associated images that constitute an initial electronic message; entering a plurality of words into the template corresponding to the initial electronic message; selecting a plurality of images from a visual dictionary associated with a user of the plurality of users, each of the plurality of images having a direct correspondence with the plurality of words entered into the template such that the plurality of images are configured to convey a message represented by the plurality of words to one or more of the plurality of users, and each of the plurality of images is associated with a definition provided by the user such that each of the plurality of images conveys one or more words based on the definition; inserting each image into the template in a sequence corresponding to the initial electronic message; and sending the initial electronic message containing the sequenced images to at least one other user via the web portal. 14. The method for an electronic communications dialog of claim 1 wherein selecting the plurality of images comprises linking to a website external to the web portal and selecting a plurality of digital images for insertion into the template, wherein each of the plurality of images are associated with a search term comprising the definition provided by the user, and the plurality of images are marked as private or public with the private images only accessible by the user and the public images accessible by any user. | 0.5 |
9,760,634 | 10 | 15 | 10. A method for defining a content relevance model for a particular category, the method comprising: identifying a set of key word sets for the particular category based on an analysis of (i) a first set of content segments previously defined as relevant to the particular category and (ii) a second set of content segments previously defined as not relevant to the particular category; identifying (i) a set of pairs of word sets that each comprise a key word set and a word set that appears in a defined context of the key word set and (ii) a score for each of the word set pairs, the score for a particular word set pair quantifying a likelihood that a content segment containing the particular word set pair is relevant to the particular category, wherein appearances of the particular word set pair in the first set of content segments increase the score for the particular word set pair and appearances of the particular word set pair in the second set of content segments decrease the score for the particular word set pair; and defining a content relevance model for the particular category, the content relevance model comprising (i) a context definition that indicates when a second word set appears within a context of a key word set and (ii) the set of word set pairs and corresponding scores. | 10. A method for defining a content relevance model for a particular category, the method comprising: identifying a set of key word sets for the particular category based on an analysis of (i) a first set of content segments previously defined as relevant to the particular category and (ii) a second set of content segments previously defined as not relevant to the particular category; identifying (i) a set of pairs of word sets that each comprise a key word set and a word set that appears in a defined context of the key word set and (ii) a score for each of the word set pairs, the score for a particular word set pair quantifying a likelihood that a content segment containing the particular word set pair is relevant to the particular category, wherein appearances of the particular word set pair in the first set of content segments increase the score for the particular word set pair and appearances of the particular word set pair in the second set of content segments decrease the score for the particular word set pair; and defining a content relevance model for the particular category, the content relevance model comprising (i) a context definition that indicates when a second word set appears within a context of a key word set and (ii) the set of word set pairs and corresponding scores. 15. The method of claim 10 , wherein determining a score for the particular word set pair comprises comparing a function calculated for the particular word set pair in the first set of content segments to the same function calculated for the particular word set pair in the second set of content segments. | 0.5 |
9,852,215 | 6 | 13 | 6. A method comprising: under control of one or more processors configured with executable instructions, receiving a content item comprising a first body of text, the first body of text comprising at least a first text portion and a second text portion; training a classifier based at least in part on an annotated text portion of a second body of text, the annotated text portion having been associated with a first reason through a user interaction received by a computing device associated with a first user, wherein the first body of text is different from the second body of text, and wherein, once trained, the classifier is configured to assign scores indicating a probability that a corresponding portion of the first text portion will be annotated by a second user based on the annotated text portion of the second body of text; assigning, using the trained classifier, and to the first text portion, a first score that indicates the probability that the first text portion will be annotated by the second user; assigning, using the trained classifier, and to the second text portion, a second score that indicates the probability that the second text portion will be annotated by the second user, wherein the first score and the second score are assigned based at least in part on the annotated text portion; ranking, based at least in part on the first score and the second score, the at least the first text portion and the second text portion of the first body of text; And selecting at least one of the first text portion or the second text portion based at least in part on the raking. | 6. A method comprising: under control of one or more processors configured with executable instructions, receiving a content item comprising a first body of text, the first body of text comprising at least a first text portion and a second text portion; training a classifier based at least in part on an annotated text portion of a second body of text, the annotated text portion having been associated with a first reason through a user interaction received by a computing device associated with a first user, wherein the first body of text is different from the second body of text, and wherein, once trained, the classifier is configured to assign scores indicating a probability that a corresponding portion of the first text portion will be annotated by a second user based on the annotated text portion of the second body of text; assigning, using the trained classifier, and to the first text portion, a first score that indicates the probability that the first text portion will be annotated by the second user; assigning, using the trained classifier, and to the second text portion, a second score that indicates the probability that the second text portion will be annotated by the second user, wherein the first score and the second score are assigned based at least in part on the annotated text portion; ranking, based at least in part on the first score and the second score, the at least the first text portion and the second text portion of the first body of text; And selecting at least one of the first text portion or the second text portion based at least in part on the raking. 13. The method as recited in claim 6 , wherein assigning the first score and the second score is based at least in part on comparing sentence structures of the at least the first text portion and the second text portion of the first body of text with a sentence structure of the annotated text portion. | 0.752864 |
8,239,380 | 34 | 36 | 34. A computer-implemented method to automatically customize a general-purpose search engine for an entry point, comprising: identifying the entry point; executing a query search via the entry point that includes a link employed to route to the general-purpose search engine; recording a first query result from a ranked list of query results returned from the executed query as relevant when a user views the document associated with the first query result; recording at least one second query result whose associated document was not viewed by the user but that is ranked higher than the first query result as non-relevant when the first result is selected for viewing by the user; and providing the recorded results to automatically train the filter for the entry point, in order to discriminate between results relevant to a search context of the user for the entry point and results non-relevant to the search context. | 34. A computer-implemented method to automatically customize a general-purpose search engine for an entry point, comprising: identifying the entry point; executing a query search via the entry point that includes a link employed to route to the general-purpose search engine; recording a first query result from a ranked list of query results returned from the executed query as relevant when a user views the document associated with the first query result; recording at least one second query result whose associated document was not viewed by the user but that is ranked higher than the first query result as non-relevant when the first result is selected for viewing by the user; and providing the recorded results to automatically train the filter for the entry point, in order to discriminate between results relevant to a search context of the user for the entry point and results non-relevant to the search context. 36. The method of claim 34 , the set of non-relevant data comprising data unrelated to the search context of the user for the entry point. | 0.653266 |
8,098,939 | 1 | 9 | 1. A method of identifying inappropriate text content in images, the method to be performed using a computer and comprising: selecting an expression from a listing of expressions; extracting an image from a message; using the selected expression as a reference, finding a section of the image that corresponds to a start point and an end point of the selected expression; comparing the section of the image to the selected expression to determine how well the section of the image matches the selected expression; and determining if the selected expression is present in the section of the image based on the comparison of the image to the selected expression; wherein comparing the section of the image to the selected expression comprises assigning, to pixel blocks between the start point and the end point of the section of the image, probabilities of being characters of the selected expression, and further comprising deeming the message as spam based on presence of the selected expression in the section of the image. | 1. A method of identifying inappropriate text content in images, the method to be performed using a computer and comprising: selecting an expression from a listing of expressions; extracting an image from a message; using the selected expression as a reference, finding a section of the image that corresponds to a start point and an end point of the selected expression; comparing the section of the image to the selected expression to determine how well the section of the image matches the selected expression; and determining if the selected expression is present in the section of the image based on the comparison of the image to the selected expression; wherein comparing the section of the image to the selected expression comprises assigning, to pixel blocks between the start point and the end point of the section of the image, probabilities of being characters of the selected expression, and further comprising deeming the message as spam based on presence of the selected expression in the section of the image. 9. The method of claim 1 wherein the message comprises an email and the selected expression comprises a word or phrase indicative of spam. | 0.722892 |
8,121,962 | 1 | 8 | 1. A computer-implemented method comprising: defining a first subset of entities belonging to one or more entity classes; constructing at least one historical profile for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities; based on the historical profiles, selecting a second subset of entities having transaction behavior associated with a transaction, the transaction behavior being predictive of at least one targeted outcome from a set of possible outcomes; redefining the first subset of entities with the second subset of entities; and monitoring the historical profiles for the entities to find entities for which the behavior is so significantly different than normal as to indicate a high probability that the entity is involved in a fraud process that is to be reported to humans. | 1. A computer-implemented method comprising: defining a first subset of entities belonging to one or more entity classes; constructing at least one historical profile for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities; based on the historical profiles, selecting a second subset of entities having transaction behavior associated with a transaction, the transaction behavior being predictive of at least one targeted outcome from a set of possible outcomes; redefining the first subset of entities with the second subset of entities; and monitoring the historical profiles for the entities to find entities for which the behavior is so significantly different than normal as to indicate a high probability that the entity is involved in a fraud process that is to be reported to humans. 8. The computer-implemented method of claim 1 , further comprising generating an estimate of the probability of the targeted outcome based only on the historical profiles. | 0.75289 |
9,773,156 | 15 | 16 | 15. At least one computer-readable media storing computer-executable instructions that, when executed by a computing device, cause the computing device to perform actions comprising: determining, by the computing device for each image in a set of images, facial recognition data that, for each face detected by the computing device in the image, comprises a face identifier that uniquely identifies the each face, a set of facial feature descriptors, a face score that is based on an open/closed state of the each face's eyes and mouth and that indicates an overall quality of the each face, and a face signature that, across the images in the set, uniquely identifies an entity that the each face represents; and grouping, by the computing device based at least on the face signatures and the face scores, images of the set into one or more groups, where each group comprises one or more images that each show a detected face that represents a same entity as that represented by any other detected face shown in any image in the each group. | 15. At least one computer-readable media storing computer-executable instructions that, when executed by a computing device, cause the computing device to perform actions comprising: determining, by the computing device for each image in a set of images, facial recognition data that, for each face detected by the computing device in the image, comprises a face identifier that uniquely identifies the each face, a set of facial feature descriptors, a face score that is based on an open/closed state of the each face's eyes and mouth and that indicates an overall quality of the each face, and a face signature that, across the images in the set, uniquely identifies an entity that the each face represents; and grouping, by the computing device based at least on the face signatures and the face scores, images of the set into one or more groups, where each group comprises one or more images that each show a detected face that represents a same entity as that represented by any other detected face shown in any image in the each group. 16. The at least one computer-readable media of claim 15 where the grouping is further based on the face scores, or where a face with a face score below a particular threshold is not included in the grouping. | 0.5 |
9,207,666 | 1 | 10 | 1. A method to display localized process control objects, the method comprising: in response to a request to monitor a process control object associated with a process control system, selecting a device description file based on the process control object, the device description file including a first tag and instructions for displaying information generated by the process control object; selecting a set of locale templates based on a locale associated with the request, wherein each of the locale templates includes a reference to process control information; selecting a locale template from the set of locale templates by: determining which of the set of locale templates includes a second tag matching the first tag; identifying a type of the process control object; and matching the type to the locale template by identifying an indicator that specifies the locale template is configured to display the type of the process control object; and processing, via a logic circuit, the process control object for display by inserting portions of the selected locale template into the first tag in the device description file. | 1. A method to display localized process control objects, the method comprising: in response to a request to monitor a process control object associated with a process control system, selecting a device description file based on the process control object, the device description file including a first tag and instructions for displaying information generated by the process control object; selecting a set of locale templates based on a locale associated with the request, wherein each of the locale templates includes a reference to process control information; selecting a locale template from the set of locale templates by: determining which of the set of locale templates includes a second tag matching the first tag; identifying a type of the process control object; and matching the type to the locale template by identifying an indicator that specifies the locale template is configured to display the type of the process control object; and processing, via a logic circuit, the process control object for display by inserting portions of the selected locale template into the first tag in the device description file. 10. A method as defined in claim 1 , wherein the locale template is a locale resource file that includes translated information. | 0.842752 |
9,665,650 | 5 | 6 | 5. The method of claim 1 , wherein the extent to which the reference uniform resource identifier is related to one or more of the context uniform resource identifiers is based on a combination of two or more factors. | 5. The method of claim 1 , wherein the extent to which the reference uniform resource identifier is related to one or more of the context uniform resource identifiers is based on a combination of two or more factors. 6. The method of claim 5 , wherein the two or more factors include a text-based similarity analysis and a non-text based similarity analysis. | 0.5 |
8,352,913 | 13 | 14 | 13. The computer program product of claim 12 , wherein accessing a series of mappings comprises: accessing the component application file. | 13. The computer program product of claim 12 , wherein accessing a series of mappings comprises: accessing the component application file. 14. The computer program product of claim 13 , wherein accessing a series of mappings further comprises: accessing the administrator interface, the administrator interface including mappings of software components. | 0.5 |
8,914,276 | 14 | 15 | 14. A computer system for providing a dynamic video caption translation player, the system comprising: a processor and memory configured to execute software instructions embodied within the following components; a video receiving component that receives an identification of a digital video; a caption identification component that identifies captions associated with the identified digital video without playing the identified digital video, wherein the captions have a source language; a language selection component that selects a target language associated with a user requesting playback of the identified digital video; a caption translation component that receives the captions identified by the caption identification component in the source language, receives the selected target language, and performs an automated translation; a caption storage component that stores translated captions in a caption format that can be read by at least one video playback application; a video package component that packages information for playing back the identified digital video using the translated captions for access by a client; and a video playback component that includes an application that plays digital video and can display the translated captions to a user using hardware of a computing device associated with the user. | 14. A computer system for providing a dynamic video caption translation player, the system comprising: a processor and memory configured to execute software instructions embodied within the following components; a video receiving component that receives an identification of a digital video; a caption identification component that identifies captions associated with the identified digital video without playing the identified digital video, wherein the captions have a source language; a language selection component that selects a target language associated with a user requesting playback of the identified digital video; a caption translation component that receives the captions identified by the caption identification component in the source language, receives the selected target language, and performs an automated translation; a caption storage component that stores translated captions in a caption format that can be read by at least one video playback application; a video package component that packages information for playing back the identified digital video using the translated captions for access by a client; and a video playback component that includes an application that plays digital video and can display the translated captions to a user using hardware of a computing device associated with the user. 15. The system of claim 14 wherein the video receiving component operates as part of a web browser and receives the identification of the video after a user directs the browser to a web page containing the video. | 0.5 |
7,970,822 | 19 | 20 | 19. The non-transitory computer-readable medium of claim 18 , wherein the instructions for extracting media objects and further generating media object descriptions further comprise: segmenting the content of each multimedia type in the multimedia object into segments within the multimedia object by media segmentation processing; and generating at least one feature description for at least one of the segments by feature extraction and annotation, wherein the generated media object descriptions comprise the at least one feature description for the at least one of the segments. | 19. The non-transitory computer-readable medium of claim 18 , wherein the instructions for extracting media objects and further generating media object descriptions further comprise: segmenting the content of each multimedia type in the multimedia object into segments within the multimedia object by media segmentation processing; and generating at least one feature description for at least one of the segments by feature extraction and annotation, wherein the generated media object descriptions comprise the at least one feature description for the at least one of the segments. 20. The non-transitory computer-readable medium of claim 19 , wherein extracting the multi-media objects further comprises selecting the at least one feature description from the group consisting of media, semantic and temporal. | 0.762994 |
7,693,720 | 31 | 37 | 31. A method responsive to a user generated natural language speech utterance, comprising: receiving, at a speech unit connected to a computer device on a vehicle, a natural language speech utterance from a user, wherein the speech unit converts the received natural language speech utterance into an electronic signal; recognizing, at a speech recognition engine connected to the computer device on the vehicle, at least one of words or phrases from the electronic signal, wherein the speech recognition engine uses at least data received from a plurality of domain agents to recognize the words or phrases, wherein the data used by the speech recognition engine includes a plurality of dictionary and phrase entries that are dynamically updated based on at least a history of a current dialog and one or more prior dialogs associated with the user; determining, at a parser connected to the computer device on the vehicle, a context for the natural language speech utterance; selecting, at the parser connected to the computer device on the vehicle, at least one of the plurality of domain agents based on the determined context; transforming, at the parser connected to the computer device on the vehicle, the recognized words or phrases into at least one of a question or a command, wherein the at least one question or command is formulated in a grammar that the selected domain agent uses to process the formulated question or command; and forwarding the formulated question or command to an agent architecture connected to the computer device on the vehicle, wherein the agent architecture communicatively couples services of each of an agent manager, a system agent, the plurality of domain agents, and an agent library that includes one or more utilities that can be used by the system agent and the plurality of domain agents, wherein the selected domain agent uses the communicatively coupled services to create a response to the formulated question or command and format the response for presentation to the user. | 31. A method responsive to a user generated natural language speech utterance, comprising: receiving, at a speech unit connected to a computer device on a vehicle, a natural language speech utterance from a user, wherein the speech unit converts the received natural language speech utterance into an electronic signal; recognizing, at a speech recognition engine connected to the computer device on the vehicle, at least one of words or phrases from the electronic signal, wherein the speech recognition engine uses at least data received from a plurality of domain agents to recognize the words or phrases, wherein the data used by the speech recognition engine includes a plurality of dictionary and phrase entries that are dynamically updated based on at least a history of a current dialog and one or more prior dialogs associated with the user; determining, at a parser connected to the computer device on the vehicle, a context for the natural language speech utterance; selecting, at the parser connected to the computer device on the vehicle, at least one of the plurality of domain agents based on the determined context; transforming, at the parser connected to the computer device on the vehicle, the recognized words or phrases into at least one of a question or a command, wherein the at least one question or command is formulated in a grammar that the selected domain agent uses to process the formulated question or command; and forwarding the formulated question or command to an agent architecture connected to the computer device on the vehicle, wherein the agent architecture communicatively couples services of each of an agent manager, a system agent, the plurality of domain agents, and an agent library that includes one or more utilities that can be used by the system agent and the plurality of domain agents, wherein the selected domain agent uses the communicatively coupled services to create a response to the formulated question or command and format the response for presentation to the user. 37. The method according to claim 31 , wherein the communicatively coupled services include at least one remotely located service and the selected domain agent includes data for controlling or communicating with the remotely located service. | 0.797479 |
9,549,042 | 3 | 4 | 3. The method of claim 2 , wherein the wireless sensor data comprises at least one of time, media access control (MAC) address, device name, device class and received signal strength indication (RSSI). | 3. The method of claim 2 , wherein the wireless sensor data comprises at least one of time, media access control (MAC) address, device name, device class and received signal strength indication (RSSI). 4. The method of claim 3 , wherein the wireless sensor data is filtered based on at least one of an RSSI signal threshold and duration of sensed device. | 0.5 |
8,001,152 | 5 | 7 | 5. A system for computerized searching comprising: an input unit to receive a search query including a plurality of features; a processor to: assign to each of said plurality of features a respective weight, and retrieve a first plurality of retrieved items based on said features and said weights, a display unit for displaying at least a portion of said retrieved items to a user, wherein said input unit is further to receive a user selection of at least one of said first plurality of retrieved items, and wherein said processor is further to: modify said weights based on features of said at least one selected retrieved item, and retrieve a second plurality of retrieved items based on said modified weights, wherein after receiving said user selection of said retrieved item, said processor is further to: suggest at least one additional feature based on features of said selected retrieved item; and assign at least one respective weight to said at least one additional feature, wherein said processor is to retrieve said second plurality of retrieved items by retrieving said second plurality of retrieved items on said features and modified weights, and based on said additional features and said weights. | 5. A system for computerized searching comprising: an input unit to receive a search query including a plurality of features; a processor to: assign to each of said plurality of features a respective weight, and retrieve a first plurality of retrieved items based on said features and said weights, a display unit for displaying at least a portion of said retrieved items to a user, wherein said input unit is further to receive a user selection of at least one of said first plurality of retrieved items, and wherein said processor is further to: modify said weights based on features of said at least one selected retrieved item, and retrieve a second plurality of retrieved items based on said modified weights, wherein after receiving said user selection of said retrieved item, said processor is further to: suggest at least one additional feature based on features of said selected retrieved item; and assign at least one respective weight to said at least one additional feature, wherein said processor is to retrieve said second plurality of retrieved items by retrieving said second plurality of retrieved items on said features and modified weights, and based on said additional features and said weights. 7. The system of claim 5 , wherein said display is further to display a plurality of scales, each said scale associated with a respective feature and representing said respective weight associated with said feature, wherein said processor is to assign said respective weights by assigning said respective weights to features based on a user selection of said weight on said scale. | 0.5 |
9,892,151 | 1 | 7 | 1. A computer-implemented method comprising: generating, by a computing device, metadata associated with data stored in a database to retrieve the data without searching all of the database; storing, by the computing device, the generated metadata in a data structure in memory; inspecting, by the computing device, the generated metadata for updates; updating, by the computing device, the data stored in the database based upon, at least in part, the updates of the generated metadata; receiving, by the computing device, a query for the data stored in the database; executing, by the computing device, the query using the generated metadata to generate a metadata result set, wherein the generated metadata result set includes metadata specifying a path to the data in the database, and wherein generating the metadata result set includes combining a plurality of indexes in response to the query, wherein combining the plurality of indexes includes combining the plurality of indexes using one or more bitwise operations on the plurality of indexes; generating, by the computing device, a result set using the plurality of indexes of the generated metadata result set including retrieving the data in the database from one or more devices using the metadata result set; and transmitting, by the computing device, the result set to a requesting client, wherein the result set includes at least one of a link to the data stored in the database and a copy of the data stored in the database. | 1. A computer-implemented method comprising: generating, by a computing device, metadata associated with data stored in a database to retrieve the data without searching all of the database; storing, by the computing device, the generated metadata in a data structure in memory; inspecting, by the computing device, the generated metadata for updates; updating, by the computing device, the data stored in the database based upon, at least in part, the updates of the generated metadata; receiving, by the computing device, a query for the data stored in the database; executing, by the computing device, the query using the generated metadata to generate a metadata result set, wherein the generated metadata result set includes metadata specifying a path to the data in the database, and wherein generating the metadata result set includes combining a plurality of indexes in response to the query, wherein combining the plurality of indexes includes combining the plurality of indexes using one or more bitwise operations on the plurality of indexes; generating, by the computing device, a result set using the plurality of indexes of the generated metadata result set including retrieving the data in the database from one or more devices using the metadata result set; and transmitting, by the computing device, the result set to a requesting client, wherein the result set includes at least one of a link to the data stored in the database and a copy of the data stored in the database. 7. The computer-implemented method of claim 1 , further comprising: storing, by the computing device, a database schema associated with a first instance of the database to a file; and generating, by the computing device, a second instance of the database based upon the database schema. | 0.5 |
9,111,144 | 5 | 7 | 5. The method of claim 1 , wherein the eye color of the at least one of the male parental candidate, the female parental candidate, and the child candidate is selected by a user from the set of predefined human eye colors. | 5. The method of claim 1 , wherein the eye color of the at least one of the male parental candidate, the female parental candidate, and the child candidate is selected by a user from the set of predefined human eye colors. 7. The method of claim 5 , wherein the eye color of the at least one of a male parental candidate, a female parental candidate, and a child candidate is determined automatically. | 0.589862 |
7,831,582 | 1 | 12 | 1. A computer-implemented method, comprising: identifying a result set including one or more of a plurality of online content sources, wherein each of the included one or more online content sources satisfies a keyword query including one or more keywords; for a given one of the online content sources included in said result set, identifying and generating corresponding representations of one or more aggregate paths including said given online content source, wherein each of the one or more aggregate paths includes one or more navigation paths among said plurality of online content sources, wherein each of the one or more navigation paths is indicative of an access request by one or more users that originates from a corresponding originating one of said online content sources to access a corresponding destination one of said online content sources, wherein each such access request indicated by a navigation path occurs prior to generating representations of said one or more aggregate paths, wherein a representation of a given one of said one or more aggregate paths is indicative of multiple ones of said online content sources; detecting a selection of a particular online content source from one of said identified aggregate paths, wherein prior to said detecting, said particular online content source does not satisfy said keyword query; and in response to detecting said selection of said particular online content source, associating said one or more keywords included in said keyword query with said particular online content source, such that after said associating, said particular online content source satisfies said keyword query; wherein each of said identifying a result set, said identifying and generating corresponding representations, said detecting a selection, and said associating said one or more keywords is performed by one or more computer systems, each comprising at least a memory and a processor. | 1. A computer-implemented method, comprising: identifying a result set including one or more of a plurality of online content sources, wherein each of the included one or more online content sources satisfies a keyword query including one or more keywords; for a given one of the online content sources included in said result set, identifying and generating corresponding representations of one or more aggregate paths including said given online content source, wherein each of the one or more aggregate paths includes one or more navigation paths among said plurality of online content sources, wherein each of the one or more navigation paths is indicative of an access request by one or more users that originates from a corresponding originating one of said online content sources to access a corresponding destination one of said online content sources, wherein each such access request indicated by a navigation path occurs prior to generating representations of said one or more aggregate paths, wherein a representation of a given one of said one or more aggregate paths is indicative of multiple ones of said online content sources; detecting a selection of a particular online content source from one of said identified aggregate paths, wherein prior to said detecting, said particular online content source does not satisfy said keyword query; and in response to detecting said selection of said particular online content source, associating said one or more keywords included in said keyword query with said particular online content source, such that after said associating, said particular online content source satisfies said keyword query; wherein each of said identifying a result set, said identifying and generating corresponding representations, said detecting a selection, and said associating said one or more keywords is performed by one or more computer systems, each comprising at least a memory and a processor. 12. The method as recited in claim 1 , wherein said given online content source includes a web page. | 0.856734 |
7,571,145 | 9 | 22 | 9. The method of claim 1 , wherein performing the action based on the score comprises adjusting, based on the score, an order in which the particular submission will appear within an ordered list of submissions. | 9. The method of claim 1 , wherein performing the action based on the score comprises adjusting, based on the score, an order in which the particular submission will appear within an ordered list of submissions. 22. A volatile or non-volatile computer-readable storage medium that stores instructions which, when executed by one or more processors, cause the one or more processors to perform the method of claim 9 . | 0.5 |
6,112,304 | 11 | 12 | 11. The method of claim 10, wherein the modifying step uses a neural net learning method. | 11. The method of claim 10, wherein the modifying step uses a neural net learning method. 12. The method of claim 11, wherein the modifying step uses back propagation. | 0.5 |
7,640,497 | 19 | 20 | 19. The method of claim 17 , wherein said traversing upward comprises copying the output container created for the object type node to the scope dictionary associated with the parent node of the object node. | 19. The method of claim 17 , wherein said traversing upward comprises copying the output container created for the object type node to the scope dictionary associated with the parent node of the object node. 20. The method of claim 19 , wherein said traversing upward traverses to the root node of the input data structure tree, the scope dictionary associated with the root node comprising the output data structure. | 0.5 |
9,256,644 | 6 | 8 | 6. A computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to index a plurality of documents into a document library stored in a database; computer readable program code configured to receive a query document; computer readable program code configured to compare the query document with each indexed document to generate a score for each indexed document, the score representing a measure of similarity between the query document and each indexed document; computer readable program code configured to display a query result based on the score for each indexed document; computer readable program code configured to calculate hash values for each indexed document over each of a plurality of alternative windows; computer readable program code configured to store the hash values for each indexed document over each of the plurality of alternative windows; computer readable program code configured to receive user input selecting a particular one of the plurality of alternative windows; computer readable program code configured to, response to receiving the selection of that particular one of the plurality of alternative windows, calculate hash values for the query document using the particular one of the plurality of alternative windows; and computer readable program code configured to compare the hash values of the query document with the hash values corresponding to the particular one of the plurality of alternative windows for each of the indexed documents to determine a measure of similarity between the query document and each indexed document. | 6. A computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to index a plurality of documents into a document library stored in a database; computer readable program code configured to receive a query document; computer readable program code configured to compare the query document with each indexed document to generate a score for each indexed document, the score representing a measure of similarity between the query document and each indexed document; computer readable program code configured to display a query result based on the score for each indexed document; computer readable program code configured to calculate hash values for each indexed document over each of a plurality of alternative windows; computer readable program code configured to store the hash values for each indexed document over each of the plurality of alternative windows; computer readable program code configured to receive user input selecting a particular one of the plurality of alternative windows; computer readable program code configured to, response to receiving the selection of that particular one of the plurality of alternative windows, calculate hash values for the query document using the particular one of the plurality of alternative windows; and computer readable program code configured to compare the hash values of the query document with the hash values corresponding to the particular one of the plurality of alternative windows for each of the indexed documents to determine a measure of similarity between the query document and each indexed document. 8. The computer program product of claim 6 , wherein a first indexed document has a higher score than a second stored document if the query document is more similar to the first indexed document than the second stored document. | 0.5 |
8,239,418 | 11 | 15 | 11. A system comprising: a computer system; an interface of the computer system to receive social network information associated with users of a social network and media accessed by the users; a data structure generator of the computer system to generate a graph that includes representations of entities associated with the social network and that links the representations based on relationships derived from the social network information, wherein the representations comprise nodes in the graph that are linked by edges; an inferred label generator of the computer system i) to select one or more advertising labels that are descriptive of one or more advertisements, and ii) to iteratively propagate values for the one or more advertising labels among the representations of the entities associated with the social network using the graph; and an advertisement server of the computer system to identify an advertisement to provide in association with a particular representation based, at least in part, on magnitudes of one or more advertising label values for the particular representation that were determined by the iterative propagation, wherein the magnitudes of the one or more advertising label values indicate how likely a user is to select one or more corresponding advertisements, wherein the particular representation comprises a representation of a particular video, and wherein the advertisement is selected for presentation in a document that includes the particular video. | 11. A system comprising: a computer system; an interface of the computer system to receive social network information associated with users of a social network and media accessed by the users; a data structure generator of the computer system to generate a graph that includes representations of entities associated with the social network and that links the representations based on relationships derived from the social network information, wherein the representations comprise nodes in the graph that are linked by edges; an inferred label generator of the computer system i) to select one or more advertising labels that are descriptive of one or more advertisements, and ii) to iteratively propagate values for the one or more advertising labels among the representations of the entities associated with the social network using the graph; and an advertisement server of the computer system to identify an advertisement to provide in association with a particular representation based, at least in part, on magnitudes of one or more advertising label values for the particular representation that were determined by the iterative propagation, wherein the magnitudes of the one or more advertising label values indicate how likely a user is to select one or more corresponding advertisements, wherein the particular representation comprises a representation of a particular video, and wherein the advertisement is selected for presentation in a document that includes the particular video. 15. The system of claim 11 , wherein the user information associated with the media accessed by the users includes information about videos watched by users, genres associated with the videos, advertisements (ads) selected by or displayed to users, email communications sent or received by the users, and comments posted or read by the users. | 0.686239 |
9,438,741 | 1 | 2 | 1. A method for assigning a spoken tag in a telecom web platform, wherein the method comprises: receiving a spoken tag from a querying user; comparing the spoken tag to a set of one or more template tags, said comparing carried out by a distinct software module executing on a hardware processor; if the spoken tag is a match to a template tag, assigning the spoken tag and updating frequency of the spoken tag in the set of one or more template tags, said assigning carried out by a distinct software module executing on a hardware processor; if the spoken tag is not a match to a template tag, searching for a nearest match, and if the nearest match is within a pre-determined proximity threshold, assigning the spoken tag and updating frequency of the spoken tag in the set of one or more template tags with user confirmation, said assigning carried out by a distinct software module executing on a hardware processor; if the spoken tag is not a match to a template tag and if the nearest match is not within the pre-determined proximity threshold, assigning the spoken tag and registering the spoken tag as a new tag, said assigning carried out by a distinct software module executing on a hardware processor; and extracting one or more user attributes from the spoken tag and assigning one or more additional tags associated with the user's location, based on background noise in the spoken tag; wherein at least one of the foregoing operations is carried out by a computer device. | 1. A method for assigning a spoken tag in a telecom web platform, wherein the method comprises: receiving a spoken tag from a querying user; comparing the spoken tag to a set of one or more template tags, said comparing carried out by a distinct software module executing on a hardware processor; if the spoken tag is a match to a template tag, assigning the spoken tag and updating frequency of the spoken tag in the set of one or more template tags, said assigning carried out by a distinct software module executing on a hardware processor; if the spoken tag is not a match to a template tag, searching for a nearest match, and if the nearest match is within a pre-determined proximity threshold, assigning the spoken tag and updating frequency of the spoken tag in the set of one or more template tags with user confirmation, said assigning carried out by a distinct software module executing on a hardware processor; if the spoken tag is not a match to a template tag and if the nearest match is not within the pre-determined proximity threshold, assigning the spoken tag and registering the spoken tag as a new tag, said assigning carried out by a distinct software module executing on a hardware processor; and extracting one or more user attributes from the spoken tag and assigning one or more additional tags associated with the user's location, based on background noise in the spoken tag; wherein at least one of the foregoing operations is carried out by a computer device. 2. The method of claim 1 , further comprising performing pattern matching-based tag recognition if the spoken tag is not a match to a template tag. | 0.84751 |
8,959,103 | 19 | 25 | 19. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: accessing query log data that identifies, for an initial search query that includes a sequence of query terms: two or more particular query terms that are included in a particular order in the sequence of query terms of the initial search query, search results that were generated using the initial search query, and a particular search result selected by the user; determining, using the query log data, that the particular search result includes the two or more particular query terms in a different order than the particular order in which the two or more particular query terms are ordered in the sequence of query terms of the initial search query; in response to determining that the particular search result includes the two or more particular query terms in the different order, adjusting a click count for a query term reordering rule associated with the two or more particular query terms; and determining, based at least on the adjusted click count, whether to revise a search query using the query term reordering rule. | 19. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: accessing query log data that identifies, for an initial search query that includes a sequence of query terms: two or more particular query terms that are included in a particular order in the sequence of query terms of the initial search query, search results that were generated using the initial search query, and a particular search result selected by the user; determining, using the query log data, that the particular search result includes the two or more particular query terms in a different order than the particular order in which the two or more particular query terms are ordered in the sequence of query terms of the initial search query; in response to determining that the particular search result includes the two or more particular query terms in the different order, adjusting a click count for a query term reordering rule associated with the two or more particular query terms; and determining, based at least on the adjusted click count, whether to revise a search query using the query term reordering rule. 25. The system of claim 19 , wherein the query term reordering rule comprises a query term scoring rule for scoring occurrences of the two or more particular query terms that occur in the different order in search results that were generated using search queries. | 0.628531 |
7,496,834 | 26 | 27 | 26. The method of claim 25 , wherein said invalid attribute is defined in said prescribed syntax. | 26. The method of claim 25 , wherein said invalid attribute is defined in said prescribed syntax. 27. The method of claim 26 , wherein said syntax is XML schema. | 0.5 |
9,230,556 | 7 | 9 | 7. A non-transitory machine readable medium storing a program for providing navigation on an electronic device comprising a display screen, the program executable by at least one processing unit of the electronic device, the program comprising sets of instructions for: receiving a request to navigate to a destination; identifying a plurality of routes from a current location of the electronic device to the destination based on the received request; when the request is not a verbal request and the device is in an unlocked mode, (i) presenting the plurality of routes to a user to select one of the plurality of routes, (ii) receiving a selection of one of the routes, and (iii) providing navigational directions on the electronic device from the current location of the electronic device to the destination through the selected route; and when the request is a verbal request and the device is in a locked mode, (i) automatically selecting a single route from the plurality of routes without user input, (ii) displaying a map on the display screen with an overview of the selected route on the map, and (iii) after a predetermined delay and without any additional user input, transitioning from displaying the overview of the selected route to providing navigational directions on the electronic device from the current location of the electronic device to the destination through the selected route, wherein the route overview comprises the entire selected route from the current location of the device to the destination that is highlighted on the map. | 7. A non-transitory machine readable medium storing a program for providing navigation on an electronic device comprising a display screen, the program executable by at least one processing unit of the electronic device, the program comprising sets of instructions for: receiving a request to navigate to a destination; identifying a plurality of routes from a current location of the electronic device to the destination based on the received request; when the request is not a verbal request and the device is in an unlocked mode, (i) presenting the plurality of routes to a user to select one of the plurality of routes, (ii) receiving a selection of one of the routes, and (iii) providing navigational directions on the electronic device from the current location of the electronic device to the destination through the selected route; and when the request is a verbal request and the device is in a locked mode, (i) automatically selecting a single route from the plurality of routes without user input, (ii) displaying a map on the display screen with an overview of the selected route on the map, and (iii) after a predetermined delay and without any additional user input, transitioning from displaying the overview of the selected route to providing navigational directions on the electronic device from the current location of the electronic device to the destination through the selected route, wherein the route overview comprises the entire selected route from the current location of the device to the destination that is highlighted on the map. 9. The non-transitory machine readable medium of claim 7 , the program further comprising sets of instructions for, when the device is in the locked mode: determining whether audio data of the received verbal request is in a previously stored set of audio data; and providing turn-by-turn directions for navigating along the route from the current location of the electronic device to the destination only when the received audio data is in the previously stored set of audio data. | 0.558716 |
8,566,782 | 1 | 2 | 1. A method of generating an editor to be executed through a graphical user interface of a computer, for editing persistent data of an application, said persistent data being described and stored in a data object model using a modeling language defining a hierarchical organization of classes, class attributes and the relations between classes, said method comprising: retrieving a root class by reading the data object model wherein the root class is an only class in the data object model which is not referenced by any other class; starting from the root class, reading each class using the relations; creating a page for editing all instances of said current class, for each read class, wherein said each read class is identified as a current class, and responsive to a determination that said each read class is not an interface; storing a link between each current class and a corresponding created page; creating, in each created page, a first section comprising fields for editing attributes of the current class, a second section for listing all instances of the current class when the instances will be edited and, using said stored link, creating a third section for displaying pointers towards class page instances of the classes referenced in said current class, wherein the first section, the second section and the third section are displayable. | 1. A method of generating an editor to be executed through a graphical user interface of a computer, for editing persistent data of an application, said persistent data being described and stored in a data object model using a modeling language defining a hierarchical organization of classes, class attributes and the relations between classes, said method comprising: retrieving a root class by reading the data object model wherein the root class is an only class in the data object model which is not referenced by any other class; starting from the root class, reading each class using the relations; creating a page for editing all instances of said current class, for each read class, wherein said each read class is identified as a current class, and responsive to a determination that said each read class is not an interface; storing a link between each current class and a corresponding created page; creating, in each created page, a first section comprising fields for editing attributes of the current class, a second section for listing all instances of the current class when the instances will be edited and, using said stored link, creating a third section for displaying pointers towards class page instances of the classes referenced in said current class, wherein the first section, the second section and the third section are displayable. 2. The method of claim 1 wherein creating a page for each read class further comprises: providing an editor user an option to change a graphical view of the created page during creation. | 0.773171 |
4,817,036 | 34 | 35 | 34. A computer system for indexing and rapidly searching and retrieving individual records contained in a data base, said system comprising: a main CPU memory for controlling a CPU; a secondary storage means comprising: (a) a plurality of individual data base records each containing one or more keywords from which a vector for each said keyword is formed, each said vector comprising one or more array elements which together comprise a numerically sorted list of all record numbers which identify the terminal nodes of a hierarchal tree where the records containing the keyword for that vector are found; and (b) an index to said data base records comprising a plurality of randomly linked bit strings derived from said vectors, each said bit string being identified by one of said keywords and comprising a plurality of bit pairs, each said bit pair representing a level and a node of said hierarchal tree; an input/output terminal for entering one or more keywords to be logically joined; and a CPU adapted to (a) receive said entered keywords, (b) locate corresponding keywords in said index, (c) retrieve the bit string for each keyword found in said index, (d) combine the retrieved bit strings to form a new bit string, (e) transform the new bit string into a vector, and (f) output an identification of all records containing the logically joined keywords input at said terminal. | 34. A computer system for indexing and rapidly searching and retrieving individual records contained in a data base, said system comprising: a main CPU memory for controlling a CPU; a secondary storage means comprising: (a) a plurality of individual data base records each containing one or more keywords from which a vector for each said keyword is formed, each said vector comprising one or more array elements which together comprise a numerically sorted list of all record numbers which identify the terminal nodes of a hierarchal tree where the records containing the keyword for that vector are found; and (b) an index to said data base records comprising a plurality of randomly linked bit strings derived from said vectors, each said bit string being identified by one of said keywords and comprising a plurality of bit pairs, each said bit pair representing a level and a node of said hierarchal tree; an input/output terminal for entering one or more keywords to be logically joined; and a CPU adapted to (a) receive said entered keywords, (b) locate corresponding keywords in said index, (c) retrieve the bit string for each keyword found in said index, (d) combine the retrieved bit strings to form a new bit string, (e) transform the new bit string into a vector, and (f) output an identification of all records containing the logically joined keywords input at said terminal. 35. A system as defined in claim 34 wherein said individual records comprise a plurality of words and wherein said keywords comprise substantially all words contained in each said individual record. | 0.796715 |
9,582,548 | 1 | 12 | 1. A method, utilizing at least one computing processor and memory, of geocoding resources based on contained text, the method comprising: obtaining bodies of text included in resources; identifying, in the bodies of text, tokens referring to geographic locations, each geographic location being referred to by at least one token; identifying canonical identifiers of the geographic locations based on the tokens, each geographic location being associated with at least one canonical identifier; and for a given resource referencing a given geographic location: identifying off-page resources that refer to the given resource; scoring relevance of the given resource to the given geographic location as a function of (i) at least a quantity of first tokens in the given resource, the first tokens corresponding to a given canonical identifier of the given geographic location and (ii) at least a quantity of second tokens in the off-page resources, the second tokens corresponding to the given canonical identifier of the given geographic location; and responsive to the score exceeding a certain threshold, designating the given resource as relevant to the given geographic location in the memory. | 1. A method, utilizing at least one computing processor and memory, of geocoding resources based on contained text, the method comprising: obtaining bodies of text included in resources; identifying, in the bodies of text, tokens referring to geographic locations, each geographic location being referred to by at least one token; identifying canonical identifiers of the geographic locations based on the tokens, each geographic location being associated with at least one canonical identifier; and for a given resource referencing a given geographic location: identifying off-page resources that refer to the given resource; scoring relevance of the given resource to the given geographic location as a function of (i) at least a quantity of first tokens in the given resource, the first tokens corresponding to a given canonical identifier of the given geographic location and (ii) at least a quantity of second tokens in the off-page resources, the second tokens corresponding to the given canonical identifier of the given geographic location; and responsive to the score exceeding a certain threshold, designating the given resource as relevant to the given geographic location in the memory. 12. The method of claim 1 , wherein the scoring relevance of the given resource to the given geographic location includes: calculating an on-page relevance score using the first tokens, calculating an off-page relevance score using the second tokens, and calculating a product of the on-page relevance score and the off-page relevance score to generate the score. | 0.844206 |
7,835,729 | 6 | 9 | 6. An emoticon input method in a mobile terminal, comprising the steps of: creating, by a user, at least one emoticon within a range of a transmittable SMS (Short Message Service) message, which is formed by utilizing a plurality of typical characters and special characters in combination; storing the at least one emoticon in an emoticon group selected by a user among a plurality of emoticon groups comprised of previously grouped emoticons according to a specific reference; displaying a list of the plurality of emoticon groups in an emoticon input mode; displaying emoticons included in an emoticon group selected by a user among the plurality of emoticon groups; selecting, by a user, at least one emoticon from the displayed emoticons; transmitting an SMS message including the at least one emoticon selected by a user; and wherein the emoticons are downloaded into the mobile terminal from the Internet and stored in the mobile terminal. | 6. An emoticon input method in a mobile terminal, comprising the steps of: creating, by a user, at least one emoticon within a range of a transmittable SMS (Short Message Service) message, which is formed by utilizing a plurality of typical characters and special characters in combination; storing the at least one emoticon in an emoticon group selected by a user among a plurality of emoticon groups comprised of previously grouped emoticons according to a specific reference; displaying a list of the plurality of emoticon groups in an emoticon input mode; displaying emoticons included in an emoticon group selected by a user among the plurality of emoticon groups; selecting, by a user, at least one emoticon from the displayed emoticons; transmitting an SMS message including the at least one emoticon selected by a user; and wherein the emoticons are downloaded into the mobile terminal from the Internet and stored in the mobile terminal. 9. The emoticon input method of claim 6 , further comprising the step of changing and editing the emoticons by the user. | 0.558824 |
9,304,974 | 4 | 5 | 4. The method of claim 1 , wherein the additional data is based on one or more actions of the user. | 4. The method of claim 1 , wherein the additional data is based on one or more actions of the user. 5. The method of claim 4 , wherein the additional data is based on a submitted search query of a user search query action of the one or more actions. | 0.5 |
10,031,901 | 1 | 3 | 1. A computer-implemented method comprising: receiving, by a data processing engine of an aggregation server, a user selected content from the user via a client agent; receiving, by the data management engine of the aggregation server, a request from the user via the client agent requesting that a narrative associated with the selected content be generated; identifying, by the data management engine of the aggregation server, a topic from the content; obtaining, by the data management engine of the aggregation server, events associated with the topic from one or more sources; aggregating, by the data management engine of the aggregation server, the events from the one or more sources based on the identified topic; receiving the aggregated events by a data processing engine of the aggregation server from the data management engine of the aggregation server; processing, by the data processing engine, the aggregated events to remove duplicate content, wherein processing the aggregated events includes normalizing the aggregated events using timestamps and natural language processing; starting generation, by a narrative generation engine of a narrative generation server, the narrative of the topic using pattern recognition on the aggregated events; prior to finalizing the narrative for transmission, obtaining, by the narrative generation engine of the narrative generation server, a first time threshold associated the user that establishes whether the generation of the narrative is to continue or is to be finalized for transmission to the user, and detecting, by the narrative generation engine of the narrative generation server, that the first time threshold has been exceeded; in response to detecting that the first time threshold has been exceeded, finalizing, by the narrative generation engine of the narrative generation server, the narrative for transmission, and transmitting, by the narrative generation engine of the narrative generation server, the narrative for presentation to the user; after finalizing and transmitting the narrative, obtaining, by the narrative generation engine of the narrative generation server, a second time threshold associated with the user that establishes whether to update the narrative over a period of time after the narrative has been transmitted to the user, and detecting, by the narrative generation engine of the narrative generation server, that the second time threshold has not been exceeded; and in response to detecting that the second time threshold has not been exceeded, updating, by the narrative generation engine, the transmitted narrative over the period of time. | 1. A computer-implemented method comprising: receiving, by a data processing engine of an aggregation server, a user selected content from the user via a client agent; receiving, by the data management engine of the aggregation server, a request from the user via the client agent requesting that a narrative associated with the selected content be generated; identifying, by the data management engine of the aggregation server, a topic from the content; obtaining, by the data management engine of the aggregation server, events associated with the topic from one or more sources; aggregating, by the data management engine of the aggregation server, the events from the one or more sources based on the identified topic; receiving the aggregated events by a data processing engine of the aggregation server from the data management engine of the aggregation server; processing, by the data processing engine, the aggregated events to remove duplicate content, wherein processing the aggregated events includes normalizing the aggregated events using timestamps and natural language processing; starting generation, by a narrative generation engine of a narrative generation server, the narrative of the topic using pattern recognition on the aggregated events; prior to finalizing the narrative for transmission, obtaining, by the narrative generation engine of the narrative generation server, a first time threshold associated the user that establishes whether the generation of the narrative is to continue or is to be finalized for transmission to the user, and detecting, by the narrative generation engine of the narrative generation server, that the first time threshold has been exceeded; in response to detecting that the first time threshold has been exceeded, finalizing, by the narrative generation engine of the narrative generation server, the narrative for transmission, and transmitting, by the narrative generation engine of the narrative generation server, the narrative for presentation to the user; after finalizing and transmitting the narrative, obtaining, by the narrative generation engine of the narrative generation server, a second time threshold associated with the user that establishes whether to update the narrative over a period of time after the narrative has been transmitted to the user, and detecting, by the narrative generation engine of the narrative generation server, that the second time threshold has not been exceeded; and in response to detecting that the second time threshold has not been exceeded, updating, by the narrative generation engine, the transmitted narrative over the period of time. 3. The computer-implemented method of claim 1 further comprising: receiving an update event associated with the topic, wherein updating the transmitted narrative over the period of time includes updating the narrative using the update event; and transmitting a notification and the narrative to the user, wherein the notification is indicative that the narrative has been updated. | 0.5 |
8,700,998 | 15 | 17 | 15. The computer of claim 10 , wherein the second instance of the window comprises multiple translations of the text in the first natural language. | 15. The computer of claim 10 , wherein the second instance of the window comprises multiple translations of the text in the first natural language. 17. The computer of claim 15 , wherein the second instance of the window switches display between different resource strings for each of the multiple translations based on user input. | 0.5 |
8,155,962 | 1 | 7 | 1. A method for asynchronously processing natural language utterances, comprising: receiving a natural language utterance at a speech unit connected to a computer device, wherein the speech unit converts the received natural language utterance into an electronic signal; recognizing one or more words in the electronic signal with a speech recognition engine that operates on the computer device; identifying a request contained in the natural language utterance with a parser that further operates on the computer device, wherein the parser identifies the request contained in the natural language utterance from the one or more recognized words; and asynchronously processing the request contained in the natural language utterance in a multi-threaded environment with a domain agent associated with a context relating to the identified request, wherein asynchronously processing the request with the domain agent includes: submitting a plurality of asynchronous queries created with the domain agent to a plurality of information sources, wherein the plurality of information sources include one or more local information sources and one or more network information sources; asynchronously evaluating results that the plurality of information sources return to the domain agent in response to the plurality of asynchronous queries; scoring, at the domain agent, the asynchronously evaluated results returned from the plurality of information sources until one or more of the asynchronously evaluated results have a score that satisfies a predetermined confidence level; and presenting a single best response to the request on the computer device, wherein the domain agent extracts the single best response from the one or more of the asynchronously evaluated results having the score that satisfies the predetermined confidence level. | 1. A method for asynchronously processing natural language utterances, comprising: receiving a natural language utterance at a speech unit connected to a computer device, wherein the speech unit converts the received natural language utterance into an electronic signal; recognizing one or more words in the electronic signal with a speech recognition engine that operates on the computer device; identifying a request contained in the natural language utterance with a parser that further operates on the computer device, wherein the parser identifies the request contained in the natural language utterance from the one or more recognized words; and asynchronously processing the request contained in the natural language utterance in a multi-threaded environment with a domain agent associated with a context relating to the identified request, wherein asynchronously processing the request with the domain agent includes: submitting a plurality of asynchronous queries created with the domain agent to a plurality of information sources, wherein the plurality of information sources include one or more local information sources and one or more network information sources; asynchronously evaluating results that the plurality of information sources return to the domain agent in response to the plurality of asynchronous queries; scoring, at the domain agent, the asynchronously evaluated results returned from the plurality of information sources until one or more of the asynchronously evaluated results have a score that satisfies a predetermined confidence level; and presenting a single best response to the request on the computer device, wherein the domain agent extracts the single best response from the one or more of the asynchronously evaluated results having the score that satisfies the predetermined confidence level. 7. The method of claim 1 , wherein asynchronously processing the request with the domain agent further includes: formulating one or more new asynchronous queries if none of the asynchronously evaluated results returned from the plurality of information sources has the score that satisfies the predetermined confidence level or do not contain all information required to extract the single best response; and submitting the one or more new asynchronous queries to one or more of the plurality of information sources, wherein the domain agent infers the one or more of the plurality of information sources to query in the one or more new asynchronous queries based on the asynchronously evaluated results returned from the plurality of information sources. | 0.516645 |
4,829,472 | 11 | 12 | 11. A spelling check module in accordance with claim 8 further comprising: personal dictionary memory means for storing and retrieving certain data; said control means further responsive to said register means for storing certain data in said personal dictionary means representing a correct spelling of a word in said register means; when said control means is commanded to store said certain data; means responsive to said detected typed word in said register means for comparing said detected typed word to said correct spelling data stored in said personal dictionary memory means and for providing a second output indication corresponding to whether said dictionary does not contain a digital code corresponding to said detected typed word; and indicator means responsive to said second output indication from said control means for indicating that said detected typed word is misspelled. | 11. A spelling check module in accordance with claim 8 further comprising: personal dictionary memory means for storing and retrieving certain data; said control means further responsive to said register means for storing certain data in said personal dictionary means representing a correct spelling of a word in said register means; when said control means is commanded to store said certain data; means responsive to said detected typed word in said register means for comparing said detected typed word to said correct spelling data stored in said personal dictionary memory means and for providing a second output indication corresponding to whether said dictionary does not contain a digital code corresponding to said detected typed word; and indicator means responsive to said second output indication from said control means for indicating that said detected typed word is misspelled. 12. A spelling check module in accordance with claim 11 wherein said control means is responsive to a simultaneous combination of two non-printing, non-control keystrokes for storing and correct spelling of said detected typed word in said personal dictionary memory means. | 0.5 |
7,502,781 | 1 | 2 | 1. A method implemented at least in part by a computing device, the method comprising: receiving a user-submitted search phrase having one or more words; (a) the computing device identifying any of a plurality of resources having keywords that match the user-submitted search phrase; (b) if step (a) identifies no resource, the computing device, without further input from a user, identifying any of the plurality of resources having keywords that phonetically match the user-submitted search phrase; and (c) if step (b) identifies no resource, the computing device, without further input from a user, performing any one or more of additional searches comprising: a modified phonetic search to identify any resources having keywords that phonetically match singularized or pluralized forms of one or more of the keywords that are contained in the user-submitted search phrase; a phonetic nearness search to identify any resources having keywords that are phonetically near the search phrase; and an alphabetic nearness search to identify any resources having keywords that are alphabetically near the search phrase. | 1. A method implemented at least in part by a computing device, the method comprising: receiving a user-submitted search phrase having one or more words; (a) the computing device identifying any of a plurality of resources having keywords that match the user-submitted search phrase; (b) if step (a) identifies no resource, the computing device, without further input from a user, identifying any of the plurality of resources having keywords that phonetically match the user-submitted search phrase; and (c) if step (b) identifies no resource, the computing device, without further input from a user, performing any one or more of additional searches comprising: a modified phonetic search to identify any resources having keywords that phonetically match singularized or pluralized forms of one or more of the keywords that are contained in the user-submitted search phrase; a phonetic nearness search to identify any resources having keywords that are phonetically near the search phrase; and an alphabetic nearness search to identify any resources having keywords that are alphabetically near the search phrase. 2. A method as recited in claim 1 , further comprising: upon identifying a particular resource, performing an action that is associated with one or more keywords of the resource. | 0.813808 |
7,764,202 | 15 | 21 | 15. A computing apparatus, comprising: a memory including instructions for a data compressor; and a processor, connected with the memory, to execute the instructions, wherein the instructions cause the processor to: receive an input stream of characters; parse the input stream into a plurality of strings each of which include one or more of the characters, wherein each parsed string is a longest match to a string entry in a data structure; and transform the input stream into an output stream that includes a first portion having literal values of the characters and a separate and distinct second portion having index values corresponding to string entries in the data structure that match parsed strings from the input stream. | 15. A computing apparatus, comprising: a memory including instructions for a data compressor; and a processor, connected with the memory, to execute the instructions, wherein the instructions cause the processor to: receive an input stream of characters; parse the input stream into a plurality of strings each of which include one or more of the characters, wherein each parsed string is a longest match to a string entry in a data structure; and transform the input stream into an output stream that includes a first portion having literal values of the characters and a separate and distinct second portion having index values corresponding to string entries in the data structure that match parsed strings from the input stream. 21. The computing apparatus of claim 15 , the processor further to add an additional string entry to the data structure that consists of a combination of a first parsed string and a subsequent parsed string. | 0.742537 |
9,846,840 | 6 | 7 | 6. The method as described in claim 4 , wherein: the communicating including communicating a contrastive activation relevancy map that is self-contrastive as describing a lack of relevancy of respective said neurons in a respective said layer to the semantic class; and the localizing is based at least in part on the aggregated patterns, the activation relevancy map, and the contrastive activation relevancy map. | 6. The method as described in claim 4 , wherein: the communicating including communicating a contrastive activation relevancy map that is self-contrastive as describing a lack of relevancy of respective said neurons in a respective said layer to the semantic class; and the localizing is based at least in part on the aggregated patterns, the activation relevancy map, and the contrastive activation relevancy map. 7. The method as described in claim 6 , wherein the localizing includes removing portions of the aggregated patterns in the activation relevancy map that are in common with corresponding said neurons of patterns in the contrastive activation relevancy map that describe the lack of relevancy of the respective said neurons in the respective said layer. | 0.5 |
7,505,040 | 1 | 12 | 1. A method for use in a computer system of generating a composite character configured for presentation by an output device, the composite character including a first component glyph and a second component glyph, each component glyph being defined by an outline, the method comprising: identifying, by the computer system, a first control point associated with the outline of the first component glyph and a second control point associated with the outline of the second component glyph, wherein identifying a first control point and a second control point comprises: determining one or more candidate control points for each of the first component glyph and the second component glyph; selecting the first control point from the one or more candidate control points determined for the first component glyph; and selecting the second control point from the one or more candidate control points determined for the second component glyph; receiving, by the computer system, a typographically relevant offset constraint associated with the composite character and relative to the first and second control points of the first and second component glyphs, the offset constraint including a vertical offset and a horizontal offset between the first component glyph and the second component glyph; scaling the outlines of the first and second component glyphs and the vertical and horizontal offsets of the offset constraint based at least in part on an output device resolution; assembling the scaled outline of the first component glyph and the scaled outline of the second component glyph to generate the composite character; and altering the assembled composite character to cause relative positions of the first control point and the second control point in the assembled composite character to satisfy the scaled offset constraint. | 1. A method for use in a computer system of generating a composite character configured for presentation by an output device, the composite character including a first component glyph and a second component glyph, each component glyph being defined by an outline, the method comprising: identifying, by the computer system, a first control point associated with the outline of the first component glyph and a second control point associated with the outline of the second component glyph, wherein identifying a first control point and a second control point comprises: determining one or more candidate control points for each of the first component glyph and the second component glyph; selecting the first control point from the one or more candidate control points determined for the first component glyph; and selecting the second control point from the one or more candidate control points determined for the second component glyph; receiving, by the computer system, a typographically relevant offset constraint associated with the composite character and relative to the first and second control points of the first and second component glyphs, the offset constraint including a vertical offset and a horizontal offset between the first component glyph and the second component glyph; scaling the outlines of the first and second component glyphs and the vertical and horizontal offsets of the offset constraint based at least in part on an output device resolution; assembling the scaled outline of the first component glyph and the scaled outline of the second component glyph to generate the composite character; and altering the assembled composite character to cause relative positions of the first control point and the second control point in the assembled composite character to satisfy the scaled offset constraint. 12. The method of claim 1 , wherein selecting the first control point and the second control point comprises applying ranked tests to the one or more candidate control points. | 0.648594 |
9,881,078 | 1 | 5 | 1. A method for determining a distribution pattern previously exhibited for a metric or a test, the method comprising: a computer receiving one or more keywords input by a user to describe the metric, or the test; the computer searching a plurality of documents for the one or more keywords; the computer identifying a first document that includes at least one of the one or more keywords based on the searching; the computer identifying a first distribution pattern specified in the first document for the metric or the test; the computer identifying other documents that include the one or more key words; and the computer determining and making an electronic record of a confidence level of the first distribution pattern based on the identifying the other documents. | 1. A method for determining a distribution pattern previously exhibited for a metric or a test, the method comprising: a computer receiving one or more keywords input by a user to describe the metric, or the test; the computer searching a plurality of documents for the one or more keywords; the computer identifying a first document that includes at least one of the one or more keywords based on the searching; the computer identifying a first distribution pattern specified in the first document for the metric or the test; the computer identifying other documents that include the one or more key words; and the computer determining and making an electronic record of a confidence level of the first distribution pattern based on the identifying the other documents. 5. The method of claim 1 further comprising the computer searching a knowledge repository for one or more known distribution patterns that are one or both of a) related to the one or more keywords, and b) is a result of an empirical observation or experiment that is identified by the one or more keywords. | 0.71875 |
8,756,058 | 6 | 7 | 6. The speech recognition system according to claim 1 , wherein the output unit changes a range of the segment determined by the segment determination unit by an instruction of a user. | 6. The speech recognition system according to claim 1 , wherein the output unit changes a range of the segment determined by the segment determination unit by an instruction of a user. 7. The speech recognition system according to claim 6 , wherein the output unit changes an output content in accordance with a new segment obtained by changing the range in accordance with the instruction of the user. | 0.5 |
8,520,982 | 19 | 20 | 19. The system of claim 18 , wherein associating one or more of the keywords from the reference advertisement with the first advertisement comprises: for each of the one or more keywords, determining a performance of the keyword with the reference advertisement; comparing the performances of the one or more keywords; and selecting a keyword from the one or more keywords to associate with the first advertisement based on the performances. | 19. The system of claim 18 , wherein associating one or more of the keywords from the reference advertisement with the first advertisement comprises: for each of the one or more keywords, determining a performance of the keyword with the reference advertisement; comparing the performances of the one or more keywords; and selecting a keyword from the one or more keywords to associate with the first advertisement based on the performances. 20. The system of claim 19 , wherein the selected keyword is a keyword associated with the reference advertisement having a highest performance. | 0.5 |
8,984,476 | 8 | 9 | 8. A computer program product for target application creation, the computer program product comprising: a non-transitory computer recordable-type media containing computer executable program code stored thereon, the computer executable program code comprising: computer executable program code for receiving a representation of a logical topology diagram for an application architecture to form a source input; computer executable program code for locating part type information in a part type dictionary using the source input; computer executable program code for locating application parts in an application parts repository for each located part type; computer executable program code for composing a subset of identified parts; computer executable program code for determining whether integration dependencies are met; computer executable program code responsive to a determination that the integration dependencies are met, for consolidating parts into a first application structure; computer executable program code for determining whether to exclude parts from the first application structure; and computer executable program code responsive to a determination to exclude parts, excluding the parts from the first application structure to create a second application structure; and computer executable program code for building a target application based on the second application structure. | 8. A computer program product for target application creation, the computer program product comprising: a non-transitory computer recordable-type media containing computer executable program code stored thereon, the computer executable program code comprising: computer executable program code for receiving a representation of a logical topology diagram for an application architecture to form a source input; computer executable program code for locating part type information in a part type dictionary using the source input; computer executable program code for locating application parts in an application parts repository for each located part type; computer executable program code for composing a subset of identified parts; computer executable program code for determining whether integration dependencies are met; computer executable program code responsive to a determination that the integration dependencies are met, for consolidating parts into a first application structure; computer executable program code for determining whether to exclude parts from the first application structure; and computer executable program code responsive to a determination to exclude parts, excluding the parts from the first application structure to create a second application structure; and computer executable program code for building a target application based on the second application structure. 9. The computer program product of claim 8 wherein computer executable program code for locating application parts in an application parts repository for each located part type further comprises: computer executable program code for determining whether part types representative of the source input are located in the part type dictionary; and computer executable program code responsive to a determination that part types representative of the source input are not located in the part type dictionary, for terminating. | 0.711024 |
8,380,486 | 17 | 18 | 17. A system for training a quality-prediction engine, the system comprising: a processor; a machine-translation engine stored in memory and executable by a processor to translate a document in a source language to a target language to obtain a machine-generated translation; a feature-comparison module stored in memory and executable by a processor to compare the machine-generated translation with a human-generated translation of the document, the human-generated translation in the target language; a mapping module stored in memory and executable by a processor to generate a mapping between features of the machine-generated translation and features of the human-generated translation based on the comparison, the mapping allowing determination of trust levels associated with translational accuracy of future machine-generated translations that lack corresponding human-generated translations; and a calibration module stored in memory and executable by a processor to calibrate the quality-prediction engine; wherein the calibration module: obtains a plurality of opinions for a plurality of sample translations generated by execution of the machine-translation engine, each of the opinions from a human and indicating a perceived trust level of corresponding sample translations; uses the quality-prediction engine to determine a trust level of each of the plurality of sample translations; determines a relationship between the plurality of opinions and the trust levels of the plurality of sample translations; and tunes the mapping to minimize any difference between the plurality of opinions and the trust levels of the plurality of sample translations; wherein the quality-prediction engine is automatically calibrated to ensure that determined trust levels are continually consistent with user feedback. | 17. A system for training a quality-prediction engine, the system comprising: a processor; a machine-translation engine stored in memory and executable by a processor to translate a document in a source language to a target language to obtain a machine-generated translation; a feature-comparison module stored in memory and executable by a processor to compare the machine-generated translation with a human-generated translation of the document, the human-generated translation in the target language; a mapping module stored in memory and executable by a processor to generate a mapping between features of the machine-generated translation and features of the human-generated translation based on the comparison, the mapping allowing determination of trust levels associated with translational accuracy of future machine-generated translations that lack corresponding human-generated translations; and a calibration module stored in memory and executable by a processor to calibrate the quality-prediction engine; wherein the calibration module: obtains a plurality of opinions for a plurality of sample translations generated by execution of the machine-translation engine, each of the opinions from a human and indicating a perceived trust level of corresponding sample translations; uses the quality-prediction engine to determine a trust level of each of the plurality of sample translations; determines a relationship between the plurality of opinions and the trust levels of the plurality of sample translations; and tunes the mapping to minimize any difference between the plurality of opinions and the trust levels of the plurality of sample translations; wherein the quality-prediction engine is automatically calibrated to ensure that determined trust levels are continually consistent with user feedback. 18. The system of claim 17 , further comprising an interface module stored in memory and executable by a processor to obtain user feedback. | 0.5 |
7,908,125 | 18 | 20 | 18. The computer-readable storage medium of claim 17 wherein the navigation service comprises: a plurality of navigation providers each associated with a specific type of navigation; a navigation service layer configured to transmit a navigation service request to one or more of the navigation providers; and a metadata service for providing the plurality of navigation providers with access to a metadata store, each navigation provider being configured to respond to a received data navigation request by interacting with the metadata service to identify at least one data navigation path. | 18. The computer-readable storage medium of claim 17 wherein the navigation service comprises: a plurality of navigation providers each associated with a specific type of navigation; a navigation service layer configured to transmit a navigation service request to one or more of the navigation providers; and a metadata service for providing the plurality of navigation providers with access to a metadata store, each navigation provider being configured to respond to a received data navigation request by interacting with the metadata service to identify at least one data navigation path. 20. The computer-readable storage medium of claim 18 wherein at least one of the plurality of navigation providers is associated with navigation from transaction data to related aggregated data. | 0.559091 |
9,779,014 | 1 | 4 | 1. A method for fault alerting in mock object supported unit testing, the method comprising: creating in memory of a computing system an instance of a mock object; proxying for an object under test by test code; proxying by method name an invocation of a method in the object under test to the mock object; determining absence in memory of a method corresponding to the method name for the mock object; and, responsive to the determination of the absence of the method name, invoking an exception handler for the mock object; and responsive to the invocation of the exception handler for the mock object, outputting error text indicating the absence of the method name; determining whether or not the method exists in memory for the mock object corresponding to the method name and a method signature. | 1. A method for fault alerting in mock object supported unit testing, the method comprising: creating in memory of a computing system an instance of a mock object; proxying for an object under test by test code; proxying by method name an invocation of a method in the object under test to the mock object; determining absence in memory of a method corresponding to the method name for the mock object; and, responsive to the determination of the absence of the method name, invoking an exception handler for the mock object; and responsive to the invocation of the exception handler for the mock object, outputting error text indicating the absence of the method name; determining whether or not the method exists in memory for the mock object corresponding to the method name and a method signature. 4. The method of claim 1 , wherein the determination of whether or not the method exists in memory for the mock object corresponding to the method name. | 0.5 |
7,818,663 | 39 | 40 | 39. A system according to claim 38 , wherein said storage means stores data relating to said plurality of different versions in a master file versions database table. | 39. A system according to claim 38 , wherein said storage means stores data relating to said plurality of different versions in a master file versions database table. 40. A system according to claim 39 , wherein the database additionally comprises a database table having a single record for said master file identifying a latest version of said master file. | 0.5 |
8,484,141 | 9 | 14 | 9. An apparatus comprising: a microprocessor coupled to a memory, wherein the microprocessor is configured to: load a first ontology associated with a first rule set, where an ontology is a formal representation of a set of concepts within a domain, and a set of relationships between the concepts; generate an extended ontology and an extended rule set based at least in part on the first ontology and the first rule set; apply the extended rule set to the extended ontology; determine a correctness of the extended ontology, where the correctness is a weighted measurement of errors of the ontology and where the correctness is weighted based at least in part on a type of the errors; and generating results comprising the correctness of the extended ontology. | 9. An apparatus comprising: a microprocessor coupled to a memory, wherein the microprocessor is configured to: load a first ontology associated with a first rule set, where an ontology is a formal representation of a set of concepts within a domain, and a set of relationships between the concepts; generate an extended ontology and an extended rule set based at least in part on the first ontology and the first rule set; apply the extended rule set to the extended ontology; determine a correctness of the extended ontology, where the correctness is a weighted measurement of errors of the ontology and where the correctness is weighted based at least in part on a type of the errors; and generating results comprising the correctness of the extended ontology. 14. The apparatus of claim 9 , where the results comprise an indication of whether stream contents are not variables; whether cardinality constraints are met; and whether all property values are in specified ranges. | 0.5 |
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