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8,599,836 | 1 | 4 |
1. In a computer-implemented contact center enabling a user to create and launch on demand, automated outbound interactive voice calls to contacts based on a user-provided call script, a non-transitory computer-readable medium having program code embodied therein configured to cause the execution of the following steps: a. Providing a website application accessible by the user via a user computer equipped with a web browser, the website application comprising a visual user interface for a contact center, b. Prompting the user to create a user account for accessing and using the contact center by providing user information comprising a user password, c. Providing contact information comprising contact phone numbers, the contact information stored in a contact information database on a data server of the service provider of the contact center and accessible to the user via the user's account, d. Prompting the user to optionally input custom answers per a user-generated call script where the call script comprises at least one question anticipating a custom answer from a contact, the custom answers to be recognized b a speech application, e. Providing a built-in audio recording capability enabling the user to record and save voice recordings for each event of the call script, f. Via an Event Add Wizard and Logic Add Wizard, enabling the user to build and save a call sequence based on the call script by pointing and clicking to successively add previously saved prompts of each message event and each question event of the call script and a logic for controlling the sequencing of events dependent upon the contact's response to a question event, g. Providing a Transfer to Live Attendant functionality whereby the user optionally adds a Transfer to Live Attendant Event into a call sequence during the call sequence creation step f, the transfer to Live Attendant Event causing the call to be automatically transferred to a user-provided phone number upon a specified contact response to a question event in the call sequence, h. Creating a broadcast, the broadcast defined by a saved call sequence and a plurality of contacts who are the intended recipients of a call based on the call sequence, i. Launching the broadcast, j. Automatically capturing and saving exportable audio recordings of contact voice responses to open-ended questions in the call sequence, where the call script comprises at least one open-ended question, and k. Providing one or more reports comprising information from contact responses to question events in the call sequence of the broadcast.
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1. In a computer-implemented contact center enabling a user to create and launch on demand, automated outbound interactive voice calls to contacts based on a user-provided call script, a non-transitory computer-readable medium having program code embodied therein configured to cause the execution of the following steps: a. Providing a website application accessible by the user via a user computer equipped with a web browser, the website application comprising a visual user interface for a contact center, b. Prompting the user to create a user account for accessing and using the contact center by providing user information comprising a user password, c. Providing contact information comprising contact phone numbers, the contact information stored in a contact information database on a data server of the service provider of the contact center and accessible to the user via the user's account, d. Prompting the user to optionally input custom answers per a user-generated call script where the call script comprises at least one question anticipating a custom answer from a contact, the custom answers to be recognized b a speech application, e. Providing a built-in audio recording capability enabling the user to record and save voice recordings for each event of the call script, f. Via an Event Add Wizard and Logic Add Wizard, enabling the user to build and save a call sequence based on the call script by pointing and clicking to successively add previously saved prompts of each message event and each question event of the call script and a logic for controlling the sequencing of events dependent upon the contact's response to a question event, g. Providing a Transfer to Live Attendant functionality whereby the user optionally adds a Transfer to Live Attendant Event into a call sequence during the call sequence creation step f, the transfer to Live Attendant Event causing the call to be automatically transferred to a user-provided phone number upon a specified contact response to a question event in the call sequence, h. Creating a broadcast, the broadcast defined by a saved call sequence and a plurality of contacts who are the intended recipients of a call based on the call sequence, i. Launching the broadcast, j. Automatically capturing and saving exportable audio recordings of contact voice responses to open-ended questions in the call sequence, where the call script comprises at least one open-ended question, and k. Providing one or more reports comprising information from contact responses to question events in the call sequence of the broadcast. 4. The non-transitory computer-readable medium per claim 1 wherein the one or more reports per Step k are available in near real-time.
| 0.926211 |
9,685,171 | 5 | 11 |
5. A system comprising: a first microphone to detect a first sound; a second microphone to detect a second sound; memory; one or more processors; and one or more computer-executable instructions stored in the memory and executable by the one or more processors to perform operations comprising: determining that the first sound is representative of at least a portion of a target voice; determining that the second sound is representative of at least a portion of noise; implementing a delay with respect to a first audio signal that represents the noise and refraining from delaying a second audio signal that represents the target voice; terminating the delay based at least in part on detecting the noise; processing, by a first adaptive filter, the target voice to generate a target voice estimate, the target voice estimate representing a first estimate of the target voice of a user associated with the first sound; processing, by the first adaptive filter, the noise to generate a noise estimate, the noise estimate representing a second estimate of the noise within an environment associated with the user; and generating, by a second adaptive filter different from the first adaptive filter, an enhanced target voice based at least in part on the target voice estimate and the noise estimate.
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5. A system comprising: a first microphone to detect a first sound; a second microphone to detect a second sound; memory; one or more processors; and one or more computer-executable instructions stored in the memory and executable by the one or more processors to perform operations comprising: determining that the first sound is representative of at least a portion of a target voice; determining that the second sound is representative of at least a portion of noise; implementing a delay with respect to a first audio signal that represents the noise and refraining from delaying a second audio signal that represents the target voice; terminating the delay based at least in part on detecting the noise; processing, by a first adaptive filter, the target voice to generate a target voice estimate, the target voice estimate representing a first estimate of the target voice of a user associated with the first sound; processing, by the first adaptive filter, the noise to generate a noise estimate, the noise estimate representing a second estimate of the noise within an environment associated with the user; and generating, by a second adaptive filter different from the first adaptive filter, an enhanced target voice based at least in part on the target voice estimate and the noise estimate. 11. The system as recited in claim 5 , wherein the operations further comprise determining the enhanced target voice based at least in part on a suppression of the noise.
| 0.773333 |
8,924,409 | 8 | 13 |
8. A computer-implemented method, comprising: receiving a partial query from a user; identifying two or more query suggestions based on the partial query; determining a probability that each respective query suggestion is a query that the user intended to input; ranking the two or more query suggestions based on the probability of each respective query suggestion; establishing a top ranking query suggestion of the two or more query suggestions based upon the ranking; determining, based on the ranking, that the top ranking query suggestion is associated with a probability that is above a threshold; providing for display the two or more query suggestions; and providing an audible indication when the determination that the probability of the top ranking query suggestion exceeds the threshold.
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8. A computer-implemented method, comprising: receiving a partial query from a user; identifying two or more query suggestions based on the partial query; determining a probability that each respective query suggestion is a query that the user intended to input; ranking the two or more query suggestions based on the probability of each respective query suggestion; establishing a top ranking query suggestion of the two or more query suggestions based upon the ranking; determining, based on the ranking, that the top ranking query suggestion is associated with a probability that is above a threshold; providing for display the two or more query suggestions; and providing an audible indication when the determination that the probability of the top ranking query suggestion exceeds the threshold. 13. The method of claim 8 , wherein the determining, based on the ranking, that the top ranking query suggestion is associated with a probability that is above a threshold comprises: establish a second most highest ranking query suggestion from the two or more query suggestions; and determining that the top ranking query suggestion is associated with a probability that is above a threshold when compared with the second most highest ranking query suggestion probability.
| 0.5 |
8,904,465 | 6 | 10 |
6. The user electronic device of claim 5 , wherein the additional information is related to one or more products or services.
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6. The user electronic device of claim 5 , wherein the additional information is related to one or more products or services. 10. The user electronic device of claim 6 , wherein the additional information is related to a website associated with the one or more products or services.
| 0.52439 |
9,996,537 | 16 | 30 |
16. A method for transforming media elements into a narrative comprising: receiving, with a clustering module in communication with a processor and a memory, a dataset comprising a plurality of media elements each comprising metadata; organizing, with the clustering module, the plurality of media elements into a plurality of clusters based on the metadata, the plurality of clusters being organized into a clustering tree; and creating, with a narrative module in communication with the processor and the memory, a narrative comprising a plurality of the media elements arranged into a narrative sequence, the narrative sequence being structured according to the clustering tree and for a predetermined duration, the narrative sequence comprising a story introduction for introducing the narrative, a geographic introduction for contextualizing a cluster, a time introduction for identifying a cluster time period, a show of media elements for representing the media elements, and a story end, wherein the narrative module is configured to create the narrative sequence according to an algorithm comprising specific durations for at least the following entries: story introduction (SI), geographic introduction (GI), time introduction (TI), show of photos, with a minimum duration for photo representation (P min ), and story end, given (SE guess ), where T is a total duration of the narrative, N is a total number of media elements in the dataset, and the algorithm produces the following result:
T>SI+GI+TI+P min +SE guess .
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16. A method for transforming media elements into a narrative comprising: receiving, with a clustering module in communication with a processor and a memory, a dataset comprising a plurality of media elements each comprising metadata; organizing, with the clustering module, the plurality of media elements into a plurality of clusters based on the metadata, the plurality of clusters being organized into a clustering tree; and creating, with a narrative module in communication with the processor and the memory, a narrative comprising a plurality of the media elements arranged into a narrative sequence, the narrative sequence being structured according to the clustering tree and for a predetermined duration, the narrative sequence comprising a story introduction for introducing the narrative, a geographic introduction for contextualizing a cluster, a time introduction for identifying a cluster time period, a show of media elements for representing the media elements, and a story end, wherein the narrative module is configured to create the narrative sequence according to an algorithm comprising specific durations for at least the following entries: story introduction (SI), geographic introduction (GI), time introduction (TI), show of photos, with a minimum duration for photo representation (P min ), and story end, given (SE guess ), where T is a total duration of the narrative, N is a total number of media elements in the dataset, and the algorithm produces the following result:
T>SI+GI+TI+P min +SE guess . 30. The method of claim 16 , wherein the narrative sequence comprises a visual presentation displaying the plurality of the media elements included in the narrative sequence in a defined order over a defined duration to represent the narrative.
| 0.84788 |
8,375,052 | 8 | 9 |
8. A hardware computer-readable storage medium storing instructions which, when executed, cause one or more processors to perform actions, the actions comprising: receiving information about a proposed outgoing message stored in memory, the received information comprising text content of a body portion of the proposed outgoing message and metadata of the proposed outgoing message; using a first classifier to classify the proposed outgoing message into one of a plurality of specified classes, to obtain an expected class of the proposed outgoing message based on the metadata of the proposed outgoing message and not the text content of the body portion of the proposed outgoing message, the first classifier being a multi-way classifier comprising N*(N-1)/2 sub-classifiers where N is the number of the plurality of specified classes and each sub-classifier provides a one-to-one classification determination between two specified classes, the metadata comprising one or more of: information on whether the proposed outgoing message is part of an email thread; information associated with a file attached to the proposed outgoing message; information in a subject line of the proposed outgoing message; information on voting buttons associated with the proposed outgoing message; and information on one or more required receipts associated with the proposed outgoing message; using a second classifier different from the first classifier to obtain an actual class of the proposed outgoing message based on the text content of the body portion of the proposed outgoing message and not the metadata of the proposed outgoing message; comparing the expected class of the proposed outgoing message based on the metadata and the actual class of the proposed outgoing message based on the text content of the body portion; and triggering an alert in response to the comparison failing to yield a match.
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8. A hardware computer-readable storage medium storing instructions which, when executed, cause one or more processors to perform actions, the actions comprising: receiving information about a proposed outgoing message stored in memory, the received information comprising text content of a body portion of the proposed outgoing message and metadata of the proposed outgoing message; using a first classifier to classify the proposed outgoing message into one of a plurality of specified classes, to obtain an expected class of the proposed outgoing message based on the metadata of the proposed outgoing message and not the text content of the body portion of the proposed outgoing message, the first classifier being a multi-way classifier comprising N*(N-1)/2 sub-classifiers where N is the number of the plurality of specified classes and each sub-classifier provides a one-to-one classification determination between two specified classes, the metadata comprising one or more of: information on whether the proposed outgoing message is part of an email thread; information associated with a file attached to the proposed outgoing message; information in a subject line of the proposed outgoing message; information on voting buttons associated with the proposed outgoing message; and information on one or more required receipts associated with the proposed outgoing message; using a second classifier different from the first classifier to obtain an actual class of the proposed outgoing message based on the text content of the body portion of the proposed outgoing message and not the metadata of the proposed outgoing message; comparing the expected class of the proposed outgoing message based on the metadata and the actual class of the proposed outgoing message based on the text content of the body portion; and triggering an alert in response to the comparison failing to yield a match. 9. The hardware computer-readable storage medium as claimed in claim 8 further comprising pre-processing the text content of the body portion of the proposed outgoing message and inputting results of the pre-processing into the second classifier.
| 0.5 |
7,949,738 | 1 | 5 |
1. A computer-readable memory containing therein instructions that, when executed, generate on a display device a graphical user interface (GUI) for creating or revising a rule that contains multiple conditions and an action to be taken when the conditions are satisfied, the GUI comprising: first and second user-selectable elements; a rule-editing area that is configured to: (i) display, upon user selection of the first element, a condition input field set for accepting a first user specification of: (a) an attribute name for each of the conditions, (b) an attribute value for each of the conditions, and (c) a choice between an “and” logical operator and an “or” logical operator for logically connecting two or more of the conditions, wherein the condition input field set accepts user selection of the attribute name for each of the conditions from a list of options for the attribute name for each of the conditions and further accepts user input of text for the attribute value for each of the conditions, wherein, after the first user specification, the rule-editing area displays a user-specified attribute name and attribute value for each of the conditions while the condition input field set is displayed, and (ii) display, upon user selection of the second element, an action input field set for accepting a second user specification of: (d) an action name identifying the action, and (e) an action value for the action, wherein the action input field accepts user selection of the action name from a list of options for the action name and further accepts user input of text for the action value, wherein, after the second user specification, the rule-editing area displays a user-specified action name and action value while the action input field set is displayed, and wherein the condition input field set and the action input field set are not displayed concurrently with each other; and a rule preview area configured to provide, after the first and second user specifications, a display of a user-understandable representation of the rule comprising both the conditions and the action, the rule preview area being displayed both while the condition input field set is displayed and while the action input field set is displayed, the user-understandable representation including at least the user-specified attribute name and attribute value for each of the conditions after the first user specification, and including at least the user-specified action name and action value for the action after the second user specification.
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1. A computer-readable memory containing therein instructions that, when executed, generate on a display device a graphical user interface (GUI) for creating or revising a rule that contains multiple conditions and an action to be taken when the conditions are satisfied, the GUI comprising: first and second user-selectable elements; a rule-editing area that is configured to: (i) display, upon user selection of the first element, a condition input field set for accepting a first user specification of: (a) an attribute name for each of the conditions, (b) an attribute value for each of the conditions, and (c) a choice between an “and” logical operator and an “or” logical operator for logically connecting two or more of the conditions, wherein the condition input field set accepts user selection of the attribute name for each of the conditions from a list of options for the attribute name for each of the conditions and further accepts user input of text for the attribute value for each of the conditions, wherein, after the first user specification, the rule-editing area displays a user-specified attribute name and attribute value for each of the conditions while the condition input field set is displayed, and (ii) display, upon user selection of the second element, an action input field set for accepting a second user specification of: (d) an action name identifying the action, and (e) an action value for the action, wherein the action input field accepts user selection of the action name from a list of options for the action name and further accepts user input of text for the action value, wherein, after the second user specification, the rule-editing area displays a user-specified action name and action value while the action input field set is displayed, and wherein the condition input field set and the action input field set are not displayed concurrently with each other; and a rule preview area configured to provide, after the first and second user specifications, a display of a user-understandable representation of the rule comprising both the conditions and the action, the rule preview area being displayed both while the condition input field set is displayed and while the action input field set is displayed, the user-understandable representation including at least the user-specified attribute name and attribute value for each of the conditions after the first user specification, and including at least the user-specified action name and action value for the action after the second user specification. 5. The computer-readable memory of claim 1 , wherein the rule-editing area contains, for each particular condition of the multiple conditions: a first menu having a set of user-selectable options for determining the attribute name of the particular condition; a second menu having a set of user-selectable options for determining the operator of the particular condition; and a text-entry field to accept user input for determining the attribute value of the particular condition.
| 0.5 |
9,183,832 | 54 | 56 |
54. A display apparatus comprising: a display unit which displays a first display item; a text determination unit which determines a first text corresponding to the first display item; a voice recognition unit which recognizes a voice input from a user; and a controller which: couples the first text to the first display item, displays the first display item so as to distinguish the first display item from a second display item, determines if the recognized voice input corresponds to the first text, and selects the first display item in response to a determination that the recognized voice input corresponds to the first text, wherein the voice input comprises a voice of the user speaking at least a word from the first text, and wherein the determining the first text comprises extracting the first text comprising at least one word from the first display item such that the first text does not share common words with a second text coupled to the second display item.
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54. A display apparatus comprising: a display unit which displays a first display item; a text determination unit which determines a first text corresponding to the first display item; a voice recognition unit which recognizes a voice input from a user; and a controller which: couples the first text to the first display item, displays the first display item so as to distinguish the first display item from a second display item, determines if the recognized voice input corresponds to the first text, and selects the first display item in response to a determination that the recognized voice input corresponds to the first text, wherein the voice input comprises a voice of the user speaking at least a word from the first text, and wherein the determining the first text comprises extracting the first text comprising at least one word from the first display item such that the first text does not share common words with a second text coupled to the second display item. 56. The display apparatus of claim 54 , wherein the first display item comprises at least one of among a menu item, an application icon, and a link.
| 0.699187 |
7,598,942 | 3 | 106 |
3. A method comprising: automatically detecting a gesture of a body from gesture data received via an optical detector, wherein the gesture data is absolute three-space location data of an instantaneous state of the body at a point in time and space, the detecting comprising aggregating the gesture data, and identifying the gesture using only the gesture data; translating the gesture to a gesture signal; and controlling a component coupled to a computer in response to the gesture signal.
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3. A method comprising: automatically detecting a gesture of a body from gesture data received via an optical detector, wherein the gesture data is absolute three-space location data of an instantaneous state of the body at a point in time and space, the detecting comprising aggregating the gesture data, and identifying the gesture using only the gesture data; translating the gesture to a gesture signal; and controlling a component coupled to a computer in response to the gesture signal. 106. The method of claim 3 , wherein the controlling includes controlling a function of an application hosted on the computer.
| 0.802508 |
9,087,507 | 1 | 7 |
1. A computer-implemented method for aurally scrolling an information source, comprising: analyzing an information source; wherein the information source comprises a plurality of markup tags; wherein analyzing the information source comprises using the plurality of markup tags to identify a plurality of segments of the information source from which to derive corresponding marker texts; generating and storing, separate from the information source, a set of a plurality of marker texts based at least on the analyzing of the information source including generating each marker text in the set of marker texts based at least on an analysis of a corresponding segment, of the plurality of identified segments, of the information source; wherein the analysis of a particular segment, of the plurality of identified segments, corresponding to a particular marker text of the set of marker texts comprises applying a summarization technique to the particular segment to derive the particular marker text; wherein the analysis of the particular segment comprises determining a significance of the particular segment based at least in part on a relative amount of text content of the particular segment; generating and storing data that comprises, for each marker text in the set of marker texts, an association between the marker text and a location within the information source, the location corresponding to the segment of the information source that corresponds to the marker text; arranging the plurality of marker texts in a sequence, the particular marker text having an order in the sequence; wherein the order of the particular marker text in the sequence is dependent on the determined significance of the particular segment that was determined based at least in part on the relative amount of text content of the particular segment; initiating an aural presentation of the sequence, the aural presentation comprising computerized text-to-speech synthesis of at least a portion of the sequence; during the aural presentation of the sequence, receiving input while the particular marker text of the set of marker texts is being aurally presented; and in response to the input: ceasing the aural presentation of the particular marker text; inspecting the data to identify the location associated with the particular marker text; and initiating an aural presentation of the information source at the location associated with the particular marker text, the aural presentation comprising computerized text-to-speech synthesis of at least a portion of the information source; wherein the method is performed by one or more computing devices.
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1. A computer-implemented method for aurally scrolling an information source, comprising: analyzing an information source; wherein the information source comprises a plurality of markup tags; wherein analyzing the information source comprises using the plurality of markup tags to identify a plurality of segments of the information source from which to derive corresponding marker texts; generating and storing, separate from the information source, a set of a plurality of marker texts based at least on the analyzing of the information source including generating each marker text in the set of marker texts based at least on an analysis of a corresponding segment, of the plurality of identified segments, of the information source; wherein the analysis of a particular segment, of the plurality of identified segments, corresponding to a particular marker text of the set of marker texts comprises applying a summarization technique to the particular segment to derive the particular marker text; wherein the analysis of the particular segment comprises determining a significance of the particular segment based at least in part on a relative amount of text content of the particular segment; generating and storing data that comprises, for each marker text in the set of marker texts, an association between the marker text and a location within the information source, the location corresponding to the segment of the information source that corresponds to the marker text; arranging the plurality of marker texts in a sequence, the particular marker text having an order in the sequence; wherein the order of the particular marker text in the sequence is dependent on the determined significance of the particular segment that was determined based at least in part on the relative amount of text content of the particular segment; initiating an aural presentation of the sequence, the aural presentation comprising computerized text-to-speech synthesis of at least a portion of the sequence; during the aural presentation of the sequence, receiving input while the particular marker text of the set of marker texts is being aurally presented; and in response to the input: ceasing the aural presentation of the particular marker text; inspecting the data to identify the location associated with the particular marker text; and initiating an aural presentation of the information source at the location associated with the particular marker text, the aural presentation comprising computerized text-to-speech synthesis of at least a portion of the information source; wherein the method is performed by one or more computing devices. 7. The computer-implemented method as recited in claim 1 , wherein the set of marker texts comprises a first set of marker texts and a second set of marker texts, the method further comprising: storing metadata that indicates that the first set of marker texts have a first logical significance and that the at least second set of marker texts have at least a second logical significance.
| 0.786344 |
9,141,964 | 1 | 8 |
1. A computer-implemented method for generating an electronic content item, the method comprising: receiving, at a server, a request from a content sponsor to generate an electronic content item associated with a concept, wherein the electronic content item is of the form of a creative and being generated automatically by the server; automatically determining, by the server and based on the concept, an image for inclusion in the electronic content item, wherein the determining includes comparing the concept to a title associated with the image and/or metadata associated with the image; suggesting, by the server and based on the determining, presentation content to the content sponsor for inclusion in the electronic content item including presenting at least a portion of the determined image responsive to the received request; receiving, at the server and from the content sponsor, a selection from the suggested presentation content; automatically generating, at the server, the electronic content item for the content sponsor using the selection; associating one or more keywords with the electronic content item; and storing the electronic content item and the associated one or more keywords such that it may be retrieved in response to a user query received in the future upon comparison with the associated one or more keywords.
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1. A computer-implemented method for generating an electronic content item, the method comprising: receiving, at a server, a request from a content sponsor to generate an electronic content item associated with a concept, wherein the electronic content item is of the form of a creative and being generated automatically by the server; automatically determining, by the server and based on the concept, an image for inclusion in the electronic content item, wherein the determining includes comparing the concept to a title associated with the image and/or metadata associated with the image; suggesting, by the server and based on the determining, presentation content to the content sponsor for inclusion in the electronic content item including presenting at least a portion of the determined image responsive to the received request; receiving, at the server and from the content sponsor, a selection from the suggested presentation content; automatically generating, at the server, the electronic content item for the content sponsor using the selection; associating one or more keywords with the electronic content item; and storing the electronic content item and the associated one or more keywords such that it may be retrieved in response to a user query received in the future upon comparison with the associated one or more keywords. 8. The method of claim 1 , wherein the electronic content item comprises at least one of an email or a web page.
| 0.859296 |
9,740,635 | 1 | 6 |
1. A computing device comprising: a file cache; and a file cache manager coupled with the file cache, to implement a context-aware eviction policy to identify a candidate file for deletion from the file cache, from a plurality of individual files contained within the file cache, based at least in part on file-level context information associated with the individual files, wherein the file-level context information includes an indication of access recency and access frequency associated with the individual files, and wherein to identify the candidate file for deletion from the file cache is based, at least in part, on both the indication of access recency and the indication of access frequency of the individual files; wherein the file-level context information further includes an indication of application-level relationships between the individual files, including a file access pattern of an application under execution on the computing device; wherein the file cache manager is further to identify the candidate file for deletion from the file cache based at least in part on the indication of application-level relationships; and wherein to identify a candidate file for deletion from the file cache, based at least in part on the indication of application-level relationships, the file cache manager is further to eliminate for consideration those individual files that are indicated, by the file access pattern, as being accessed after an individual file that was recently accessed by the application.
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1. A computing device comprising: a file cache; and a file cache manager coupled with the file cache, to implement a context-aware eviction policy to identify a candidate file for deletion from the file cache, from a plurality of individual files contained within the file cache, based at least in part on file-level context information associated with the individual files, wherein the file-level context information includes an indication of access recency and access frequency associated with the individual files, and wherein to identify the candidate file for deletion from the file cache is based, at least in part, on both the indication of access recency and the indication of access frequency of the individual files; wherein the file-level context information further includes an indication of application-level relationships between the individual files, including a file access pattern of an application under execution on the computing device; wherein the file cache manager is further to identify the candidate file for deletion from the file cache based at least in part on the indication of application-level relationships; and wherein to identify a candidate file for deletion from the file cache, based at least in part on the indication of application-level relationships, the file cache manager is further to eliminate for consideration those individual files that are indicated, by the file access pattern, as being accessed after an individual file that was recently accessed by the application. 6. The computing device of claim 1 , wherein the file cache manager is to implement the context-aware eviction policy in response to a determination that the file cache has reached a threshold of available capacity.
| 0.842836 |
7,703,040 | 6 | 7 |
6. The method of responding to a user input as claimed in claim 5 further comprising: in response to user input selecting one of said one or more active files including said active filter in said search engine query; and displaying information identifying said active filter in said Active Query Box.
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6. The method of responding to a user input as claimed in claim 5 further comprising: in response to user input selecting one of said one or more active files including said active filter in said search engine query; and displaying information identifying said active filter in said Active Query Box. 7. The method of responding to a user input as claimed in claim 6 further comprising: wherein said active filters including at least one of custom tags or file paths.
| 0.5 |
7,912,874 | 1 | 2 |
1. An apparatus for defining a metadata schema to facilitate passing data between an eXtensible Markup Language (XML) document and a hierarchical database, the apparatus comprising: a storage device storing executable code; a processor executing the executable code, the executable code comprising: a database accessor accessing a database schema indicative of database field names and a hierarchical structure for a hierarchical database; a document accessor accessing a document schema that defines the hierarchical structure, content data syntax, and semantics of valid, well-formed, XML documents that can be passed into and out of the hierarchical database, the document schema comprising an XML element name that maps to a database field name in the database schema, the document schema comprising at least one directive metadata element not interfering with third-party applications using the document schema and facilitating passing data between the XML document and the hierarchical database; and an association module relating the database schema and the document schema to provide a metadata schema that enables data to be passed between an XML document and the hierarchical database.
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1. An apparatus for defining a metadata schema to facilitate passing data between an eXtensible Markup Language (XML) document and a hierarchical database, the apparatus comprising: a storage device storing executable code; a processor executing the executable code, the executable code comprising: a database accessor accessing a database schema indicative of database field names and a hierarchical structure for a hierarchical database; a document accessor accessing a document schema that defines the hierarchical structure, content data syntax, and semantics of valid, well-formed, XML documents that can be passed into and out of the hierarchical database, the document schema comprising an XML element name that maps to a database field name in the database schema, the document schema comprising at least one directive metadata element not interfering with third-party applications using the document schema and facilitating passing data between the XML document and the hierarchical database; and an association module relating the database schema and the document schema to provide a metadata schema that enables data to be passed between an XML document and the hierarchical database. 2. The apparatus of claim 1 , wherein the document schema comprises an XML schema that complies with an industry standard for XML schemas.
| 0.829208 |
9,106,621 | 3 | 5 |
3. The method of claim 2 , wherein the attention types additionally includes “bcc.”
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3. The method of claim 2 , wherein the attention types additionally includes “bcc.” 5. The method of claim 3 , wherein the attention-rights rule defines that a recipient with the attention type “to” is to be granted view and edit rights only, and a recipient with the attention type “cc” or “bcc” is to be granted view right only.
| 0.656425 |
8,374,983 | 13 | 15 |
13. Non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a request to classify an object, the request including at least one attribute value representing a characteristic of the object; selecting two or more different models that are each configured to classify the object based on the at least one attribute value; providing the at least one attribute value to each of the two or more different models; identifying, for a particular model among the two or more different models, one or more additional attributes and corresponding additional attribute values; providing the identified additional attribute values to the particular model; receiving classification data from the two or more selected models, the classification data received from one of the models specifying, for the object, a different presentation availability than the classification data received from at least one other model among the two or more different models; and assigning a final classification to the object based on the received classification data, the final classification specifying a presentation availability of the object.
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13. Non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a request to classify an object, the request including at least one attribute value representing a characteristic of the object; selecting two or more different models that are each configured to classify the object based on the at least one attribute value; providing the at least one attribute value to each of the two or more different models; identifying, for a particular model among the two or more different models, one or more additional attributes and corresponding additional attribute values; providing the identified additional attribute values to the particular model; receiving classification data from the two or more selected models, the classification data received from one of the models specifying, for the object, a different presentation availability than the classification data received from at least one other model among the two or more different models; and assigning a final classification to the object based on the received classification data, the final classification specifying a presentation availability of the object. 15. The computer program of claim 13 , wherein receiving classification data comprises receiving, from each of the two or more different models, a classification score and a confidence factor, the classification score received from each of the two or more models being indicative of an initial classification of the object by each of the models, the confidence factor specifying a likelihood that the initial classification of the object by each of the models is accurate.
| 0.5 |
9,218,334 | 4 | 6 |
4. The computer-implemented method of claim 2 , wherein building the phonetic model further comprises: preparing a library of source words comprising pronounceable words and non-pronounceable words; and providing the library of source words to a learning model algorithm to train the learning model algorithm to determine characteristics of pronounceable and characteristics of non-pronounceable words.
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4. The computer-implemented method of claim 2 , wherein building the phonetic model further comprises: preparing a library of source words comprising pronounceable words and non-pronounceable words; and providing the library of source words to a learning model algorithm to train the learning model algorithm to determine characteristics of pronounceable and characteristics of non-pronounceable words. 6. The computer-implemented method of claim 4 , wherein preparing the library comprises: building an attribute relationship file format (ARFF) based on the library of source words; and associating one or more attributes of pronounceable words and non-pronounceable words with the ARFF.
| 0.5 |
9,171,204 | 9 | 10 |
9. The non-transitory computer-readable storage medium of claim 8 wherein: the portion is a strip extracted from a location below a y-coordinate of a peak in a histogram, of counts of pixels of a common binary value in each row among a plurality of rows in the region.
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9. The non-transitory computer-readable storage medium of claim 8 wherein: the portion is a strip extracted from a location below a y-coordinate of a peak in a histogram, of counts of pixels of a common binary value in each row among a plurality of rows in the region. 10. The non-transitory computer-readable storage medium of claim 9 wherein: each line in the plurality of lines is detected for satisfying a test on having a length within the portion larger than a predetermined fraction of a height of the portion.
| 0.5 |
8,612,468 | 18 | 19 |
18. The method of claim 17 , further comprising: creating a partition for each variable in the expression tree; identifying equivalent variables in the expression tree; and merging partitions containing equivalent variables.
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18. The method of claim 17 , further comprising: creating a partition for each variable in the expression tree; identifying equivalent variables in the expression tree; and merging partitions containing equivalent variables. 19. The method of claim 18 , further comprising determining if any remaining partitions contain non-null unique keys.
| 0.5 |
8,396,820 | 16 | 23 |
16. A computer-implemented method for using a sentiment thesaurus stored according to the computer-readable storage medium of claim 1 to retrieve sentiment words for use with online content, comprising: receiving an indication of an adjective; determining from the sentiment thesaurus one or more related sentiment adjective word-senses that relate to the indicated adjective, by looking up the indicated adjective and retrieving related sentiment adjective word-senses; and returning indications to the retrieved related sentiment adjective word-senses.
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16. A computer-implemented method for using a sentiment thesaurus stored according to the computer-readable storage medium of claim 1 to retrieve sentiment words for use with online content, comprising: receiving an indication of an adjective; determining from the sentiment thesaurus one or more related sentiment adjective word-senses that relate to the indicated adjective, by looking up the indicated adjective and retrieving related sentiment adjective word-senses; and returning indications to the retrieved related sentiment adjective word-senses. 23. The method of claim 16 wherein the returned indicated related sentiment adjective word-senses are presented in a list of viable sentiment words.
| 0.811705 |
9,875,234 | 1 | 15 |
1. A method programmed in a non-transitory memory of a device comprising: a. capturing social networking information, including the social networking information of a user, from a social networking system; b. analyzing the social networking information of the user, including: i. determining interests of the user; and ii. storing the interests of the user in a data structure; c. processing the social networking information, including parsing the social networking information into parsed information; d. fact checking, with the device, the social networking information by comparing the parsed information with source information to generate fact checking results, including indicating when the parsed information is factually accurate and indicating when the parsed information is factually inaccurate; e. summarizing the social networking information to generate a summary of the social networking information, including determining total strengths of sentences within the social networking information, wherein a total strength of a sentence is based on a strength of a lexical chain, the interests of the user, and factual accuracy of the sentence based on the fact checking results generated by fact checking the social networking information, wherein summarizing the social networking information utilizes the interests of the user stored in the data structure by increasing the strength of the lexical chain when a word in the lexical chain matches at least one of the interests in the data structure, wherein lexical chaining includes selecting a set of candidate words or phrases, finding an appropriate chain using relatedness criteria among members of chains for each candidate word, and inserting a word in the lexical chain when the word is found, wherein the total strength of the sentence is increased when the sentence is factually accurate, wherein the summary of the social networking information includes the fact checking results; and f. providing the summary of the social networking information in real-time.
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1. A method programmed in a non-transitory memory of a device comprising: a. capturing social networking information, including the social networking information of a user, from a social networking system; b. analyzing the social networking information of the user, including: i. determining interests of the user; and ii. storing the interests of the user in a data structure; c. processing the social networking information, including parsing the social networking information into parsed information; d. fact checking, with the device, the social networking information by comparing the parsed information with source information to generate fact checking results, including indicating when the parsed information is factually accurate and indicating when the parsed information is factually inaccurate; e. summarizing the social networking information to generate a summary of the social networking information, including determining total strengths of sentences within the social networking information, wherein a total strength of a sentence is based on a strength of a lexical chain, the interests of the user, and factual accuracy of the sentence based on the fact checking results generated by fact checking the social networking information, wherein summarizing the social networking information utilizes the interests of the user stored in the data structure by increasing the strength of the lexical chain when a word in the lexical chain matches at least one of the interests in the data structure, wherein lexical chaining includes selecting a set of candidate words or phrases, finding an appropriate chain using relatedness criteria among members of chains for each candidate word, and inserting a word in the lexical chain when the word is found, wherein the total strength of the sentence is increased when the sentence is factually accurate, wherein the summary of the social networking information includes the fact checking results; and f. providing the summary of the social networking information in real-time. 15. The method of claim 1 wherein summarizing the social networking information utilizes confidence scores of the fact checking results to generate the summary of the social networking information.
| 0.889821 |
7,958,136 | 11 | 12 |
11. A system for identifying similar documents, comprising: a processor and a memory; a query processor using the processor and the memory; a compound likelihood database, that stores bigram probabilities for a first set of words; a descriptive database, that stores descriptiveness scores for a second set of words, wherein the first set of words and the second set of words includes common words; and a similar document identifier configured to receive document text for a current document, wherein the document text includes at least two document words, wherein the similar document identifier uses the query processor, the query processor configured to identify at least one similar document based on prominence scores and descriptiveness scores for each document word and pair of consecutive document words, wherein the prominence scores are based on results from a query to the compound likelihood database and the descriptiveness scores are received based on a query to the descriptive database, and wherein the prominence score for each word is further based on a term weight and a non-compound likelihood for each word; the prominence score for each pair of consecutive words is based on a term weight and a compound probability for each pair of consecutive words; the descriptiveness score for each word is based on a corpus, and the descriptiveness score for each pair of consecutive words is based on the corpus.
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11. A system for identifying similar documents, comprising: a processor and a memory; a query processor using the processor and the memory; a compound likelihood database, that stores bigram probabilities for a first set of words; a descriptive database, that stores descriptiveness scores for a second set of words, wherein the first set of words and the second set of words includes common words; and a similar document identifier configured to receive document text for a current document, wherein the document text includes at least two document words, wherein the similar document identifier uses the query processor, the query processor configured to identify at least one similar document based on prominence scores and descriptiveness scores for each document word and pair of consecutive document words, wherein the prominence scores are based on results from a query to the compound likelihood database and the descriptiveness scores are received based on a query to the descriptive database, and wherein the prominence score for each word is further based on a term weight and a non-compound likelihood for each word; the prominence score for each pair of consecutive words is based on a term weight and a compound probability for each pair of consecutive words; the descriptiveness score for each word is based on a corpus, and the descriptiveness score for each pair of consecutive words is based on the corpus. 12. The system of claim 11 , wherein the query processor is further configured to: find at least one potential document, wherein document text for each potential document includes at least one of the document words from the current document, analyze each potential document to identify each similar document as a function of a comparison metric for the respective potential document and a comparison metric for the current document, and output a signal representing each similar document to a user via a communication network; and the similar document identifier further comprises: a feature extractor, configured to determine the comparison metric for the current document and the potential document, wherein the comparison metric is based on a combination of the prominence scores and the descriptiveness scores for each document word and pair of consecutive document words; and a prominence calculator, configured to calculate the prominence scores based on the results from the compound likelihood database.
| 0.5 |
8,103,646 | 13 | 19 |
13. A computer-implemented system of information management executed by a processor, comprising: a search component for searching information sources containing audio data from which text is transcribed for tag and content relationship data; a tag classification model for producing tag information based on the relationship data comprising taxonomy between tags and an associated corpus of tagged content; a tag classifier for obtaining tag information from the produced tag information of the tag classification model and for applying at least one of probabilistic or statistical analysis to the transcribed text in order to classify the text for tagging, to implement a confidence threshold to reduce the likelihood of an inappropriate tag being selected for the transcribed text; a tag for new content based on the taxonomy employed in the tag classification model; and a processor that executes computer-executable instructions associated with at least one of the search component, the tag classification model, the tag classifier, or the tag.
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13. A computer-implemented system of information management executed by a processor, comprising: a search component for searching information sources containing audio data from which text is transcribed for tag and content relationship data; a tag classification model for producing tag information based on the relationship data comprising taxonomy between tags and an associated corpus of tagged content; a tag classifier for obtaining tag information from the produced tag information of the tag classification model and for applying at least one of probabilistic or statistical analysis to the transcribed text in order to classify the text for tagging, to implement a confidence threshold to reduce the likelihood of an inappropriate tag being selected for the transcribed text; a tag for new content based on the taxonomy employed in the tag classification model; and a processor that executes computer-executable instructions associated with at least one of the search component, the tag classification model, the tag classifier, or the tag. 19. The system of claim 13 , further comprising a machine learning and reasoning component for automating at least one feature of modeling and tagging.
| 0.667401 |
4,724,523 | 54 | 55 |
54. A method according to claim 39 in which said third pattern storing step comprises storing a signal representative of at least one addressable other elemental expression of a paradigm of which said corresponding stored entry is an element.
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54. A method according to claim 39 in which said third pattern storing step comprises storing a signal representative of at least one addressable other elemental expression of a paradigm of which said corresponding stored entry is an element. 55. A method according to claim 54 in which said third pattern storing step comprises storing a signal indicative of at least one of a grammatical nominal classification and a grammatical verbal classification.
| 0.5 |
8,543,913 | 5 | 11 |
5. A computer program product stored on a non-transitory computer readable medium, which when executed, accesses textual widgets, the computer readable medium comprising program code for: invoking a spell-checker to check a spelling of a string expression, wherein the string expression includes one of a predefined prefix, a predefined suffix or a predefined formula; marking the string expression as misspelled based upon the predefined prefix, the predefined suffix or the predefined formula; executing one of a plurality of textual widgets for performing a non-spellchecking function, wherein the executed textual widget is associated with the string expression via the predefined prefix, the predefined suffix or the predefined formula, and wherein each different textual widget performs a different function/operation upon the marked string expression; returning at least one result of the non-spellchecking function; and displaying the at least one result.
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5. A computer program product stored on a non-transitory computer readable medium, which when executed, accesses textual widgets, the computer readable medium comprising program code for: invoking a spell-checker to check a spelling of a string expression, wherein the string expression includes one of a predefined prefix, a predefined suffix or a predefined formula; marking the string expression as misspelled based upon the predefined prefix, the predefined suffix or the predefined formula; executing one of a plurality of textual widgets for performing a non-spellchecking function, wherein the executed textual widget is associated with the string expression via the predefined prefix, the predefined suffix or the predefined formula, and wherein each different textual widget performs a different function/operation upon the marked string expression; returning at least one result of the non-spellchecking function; and displaying the at least one result. 11. The computer program product of claim 5 , further comprising program code for: selecting a result; and replacing the string expression in the document with the selected result.
| 0.554455 |
7,660,705 | 36 | 37 |
36. A computer implemented system for predicting future observations of time series data having a set of associated variables, comprising: means for making predictions relative to the time series data, the predictions related to nontrivial extractions of implicit, previously unknown information obtained by data mining within large amounts of data; means for data mining within the large amounts of data; means for learning a model structure via a greedy Bayesian model selection approach for data corresponding to time series data for which a set of potential regressor variables have been created, the model structure comprising a decision graph that includes a plurality of leaves, at least one of the plurality of leaves including at least one linear regression on at least one continuous variable of the set of associated variables, wherein the potential regressors associated with the at least one linear regression are arranged in the set based on a descending order of their correlation for the at least one continuous variable; means for learning model parameters at the leaves of the model structure by adjusting the at least one variable on which the at least one linear regression is implemented for the at least one of the plurality of leaves, wherein the means for learning model parameters further comprising means for one of either adding or removing a potential regressor of the set of associated variables relative to a given leaf to provide a submodel and the means for learning a model structure further comprising means for merging at least two leaves based on regressors contained in the least two leaves so that at least one non-root node of the decision graph has more than one parent node; means for scoring the model in order to select a most suitable model to facilitate prediction; means for generating one or more future observations within the time series data by employing a highest scoring model as the most suitable model to predict the future observations; means for storing the one or more predicted future observations obtained during the data mining; and means for splitting a leaf into a non-leaf node associated with one of the variables and a pair of leaves, wherein the means for splitting being applied iteratively to respective leaves of the model to grow the model so long as the means for scoring provides an improved model score.
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36. A computer implemented system for predicting future observations of time series data having a set of associated variables, comprising: means for making predictions relative to the time series data, the predictions related to nontrivial extractions of implicit, previously unknown information obtained by data mining within large amounts of data; means for data mining within the large amounts of data; means for learning a model structure via a greedy Bayesian model selection approach for data corresponding to time series data for which a set of potential regressor variables have been created, the model structure comprising a decision graph that includes a plurality of leaves, at least one of the plurality of leaves including at least one linear regression on at least one continuous variable of the set of associated variables, wherein the potential regressors associated with the at least one linear regression are arranged in the set based on a descending order of their correlation for the at least one continuous variable; means for learning model parameters at the leaves of the model structure by adjusting the at least one variable on which the at least one linear regression is implemented for the at least one of the plurality of leaves, wherein the means for learning model parameters further comprising means for one of either adding or removing a potential regressor of the set of associated variables relative to a given leaf to provide a submodel and the means for learning a model structure further comprising means for merging at least two leaves based on regressors contained in the least two leaves so that at least one non-root node of the decision graph has more than one parent node; means for scoring the model in order to select a most suitable model to facilitate prediction; means for generating one or more future observations within the time series data by employing a highest scoring model as the most suitable model to predict the future observations; means for storing the one or more predicted future observations obtained during the data mining; and means for splitting a leaf into a non-leaf node associated with one of the variables and a pair of leaves, wherein the means for splitting being applied iteratively to respective leaves of the model to grow the model so long as the means for scoring provides an improved model score. 37. The system of claim 36 , the means for scoring computing a Bayesian score for the model, which corresponds to a sum of the scores at the respective leaves of the model.
| 0.75 |
9,037,568 | 9 | 10 |
9. The system of claim 8 , wherein the search system is further configured to: receive a query from a user; determine that the query includes a first portion that matches a particular, generalized query pattern; and based on determining that the query includes the first portion that matches the particular, generalized query pattern, retrieving a value of the particular attribute of one of the other topics referenced by the query.
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9. The system of claim 8 , wherein the search system is further configured to: receive a query from a user; determine that the query includes a first portion that matches a particular, generalized query pattern; and based on determining that the query includes the first portion that matches the particular, generalized query pattern, retrieving a value of the particular attribute of one of the other topics referenced by the query. 10. The system of claim 9 , wherein the interface is further configured to filter the received queries to remove queries that occur with a frequency that does satisfy a predetermined threshold.
| 0.5 |
8,949,357 | 1 | 10 |
1. A method of conducting a real-time private group chat conversation using a social networking service to connect users to the conversation, the method comprising: monitoring, using a controller, a stream of text strings published by a public social networking service; scanning the text strings to determine whether any of the text strings include an action tag that includes a predetermined combination of characters; responsive to determining that a first of the text strings includes the action tag, determining a creator user account name that is attempting to initiate a private conversation and reading at least one user account name in the first text string and a title for the private conversation to be initiated, the creator user account name being associated with an externally published creator user account in the social networking service and the user account name being associated with an externally published user account in the social networking service; causing a request to be sent to the user account in the social networking service, the request including an indication of the request for the private conversation and the creator user account name and a uniform resource locator (URL) for joining the private conversation; responsive to the user account accepting the request by directing a browser to access the URL provided in the request from the social networking service, connecting the user account with a creator user account associated with the creator user account name in a private conversation; and communicating, using the controller, messages of the private conversation between the user account and the creator user account, wherein the action tag starts with at least one non-alphanumeric character, includes at least one alphanumeric character, and is at the beginning of the text string such that the predetermined combination of characters are the first characters of the text string, and wherein the user account names are preceded by a hashtag.
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1. A method of conducting a real-time private group chat conversation using a social networking service to connect users to the conversation, the method comprising: monitoring, using a controller, a stream of text strings published by a public social networking service; scanning the text strings to determine whether any of the text strings include an action tag that includes a predetermined combination of characters; responsive to determining that a first of the text strings includes the action tag, determining a creator user account name that is attempting to initiate a private conversation and reading at least one user account name in the first text string and a title for the private conversation to be initiated, the creator user account name being associated with an externally published creator user account in the social networking service and the user account name being associated with an externally published user account in the social networking service; causing a request to be sent to the user account in the social networking service, the request including an indication of the request for the private conversation and the creator user account name and a uniform resource locator (URL) for joining the private conversation; responsive to the user account accepting the request by directing a browser to access the URL provided in the request from the social networking service, connecting the user account with a creator user account associated with the creator user account name in a private conversation; and communicating, using the controller, messages of the private conversation between the user account and the creator user account, wherein the action tag starts with at least one non-alphanumeric character, includes at least one alphanumeric character, and is at the beginning of the text string such that the predetermined combination of characters are the first characters of the text string, and wherein the user account names are preceded by a hashtag. 10. The method of claim 1 , further comprising: responsive to the user account accepting the request, storing credential information associated with the user account including the user account name; and retrieving the stored credential information associated with the user account in connection with a second request to join a second private conversation without requiring authorization of the user account to join the second private conversation.
| 0.61399 |
8,359,302 | 1 | 4 |
1. A computer-implemented method comprising: receiving a query comprising a search term; determining a location on a page that is responsive to the query, wherein the page has a native appearance; determining a contextual area associated with the location on the page, wherein determining a contextual area comprises: determining a plurality of lines of text associated with the location on the page, wherein determining a plurality of lines of text associated with the location on the page comprises: extracting a line of text above the line of text containing the search term; and extracting a line of text below the line of text containing the search term; identifying coordinates of a polygon including the lines of text; rendering the contextual area into an image; and in response to the query, and without requiring any additional user action, causing the image to be output in a hi-fidelity result set displaying one or more results of the query, wherein the image has an appearance the same as the native appearance of the page.
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1. A computer-implemented method comprising: receiving a query comprising a search term; determining a location on a page that is responsive to the query, wherein the page has a native appearance; determining a contextual area associated with the location on the page, wherein determining a contextual area comprises: determining a plurality of lines of text associated with the location on the page, wherein determining a plurality of lines of text associated with the location on the page comprises: extracting a line of text above the line of text containing the search term; and extracting a line of text below the line of text containing the search term; identifying coordinates of a polygon including the lines of text; rendering the contextual area into an image; and in response to the query, and without requiring any additional user action, causing the image to be output in a hi-fidelity result set displaying one or more results of the query, wherein the image has an appearance the same as the native appearance of the page. 4. The method of claim 1 , further comprising highlighting the search term in the contextual area.
| 0.856305 |
9,418,124 | 1 | 5 |
1. A computer-implemented method for processing a set of data records having time conflicts, the data records representing respective versions of an entity for which there can be only one preferred value at any given point in time, wherein each of the data records has an n-dimensional time record, the computer-implemented method comprising: defining a policy from among a plurality of candidate policies, said defined policy designed to resolve time conflicts between those data records having time conflicts; comparing all data records in a cumulative, pair-wise fashion; identifying time-based conflicts between pairs of records and identifying time-conflicted pairs; determining which record in every time-conflicted pair of records is to be adjusted in accordance with said defined policy; adjusting the time interval of every said determined record in accordance with said defined policy; and outputting a modified set of data records having said adjusted time intervals, wherein (i) said modified set of data records contains no time conflicts and (ii) said adjusted time intervals in the modified set of data records do not depend on the order in which the data records are processed by said computer-implemented method.
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1. A computer-implemented method for processing a set of data records having time conflicts, the data records representing respective versions of an entity for which there can be only one preferred value at any given point in time, wherein each of the data records has an n-dimensional time record, the computer-implemented method comprising: defining a policy from among a plurality of candidate policies, said defined policy designed to resolve time conflicts between those data records having time conflicts; comparing all data records in a cumulative, pair-wise fashion; identifying time-based conflicts between pairs of records and identifying time-conflicted pairs; determining which record in every time-conflicted pair of records is to be adjusted in accordance with said defined policy; adjusting the time interval of every said determined record in accordance with said defined policy; and outputting a modified set of data records having said adjusted time intervals, wherein (i) said modified set of data records contains no time conflicts and (ii) said adjusted time intervals in the modified set of data records do not depend on the order in which the data records are processed by said computer-implemented method. 5. The computer-implemented method of claim 1 , wherein said outputted modified set of records comprise a concise and complete temporal history of all data records such that a history of said entity is retrievable via a standard XML manipulation language.
| 0.5 |
9,699,439 | 1 | 6 |
1. A method for displaying a three-dimensional (3D) caption in a 3D display apparatus, the method comprising: receiving a broadcast signal including 3D caption data based on a code space; acquiring 3D command and caption text from the 3D caption data, wherein the 3D command is delivered in a C3 code set contained in the code space, wherein the C3 code set is accessed by using an ‘EXT1’ code in a base code set, wherein the 3D command provides disparity data which applies to a caption window; and processing the disparity data and the caption text such that the caption text is written to the caption window for 3D captioning.
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1. A method for displaying a three-dimensional (3D) caption in a 3D display apparatus, the method comprising: receiving a broadcast signal including 3D caption data based on a code space; acquiring 3D command and caption text from the 3D caption data, wherein the 3D command is delivered in a C3 code set contained in the code space, wherein the C3 code set is accessed by using an ‘EXT1’ code in a base code set, wherein the 3D command provides disparity data which applies to a caption window; and processing the disparity data and the caption text such that the caption text is written to the caption window for 3D captioning. 6. The method of claim 1 , wherein the 3D command specifies an amount of disparity for the caption window.
| 0.75576 |
8,463,766 | 9 | 10 |
9. The computer readable medium of claim 8 wherein an interaction is creation or deletion of a bookmark for the location in the first document by a user of the plurality of users.
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9. The computer readable medium of claim 8 wherein an interaction is creation or deletion of a bookmark for the location in the first document by a user of the plurality of users. 10. The computer readable medium of claim 9 wherein the document usage information includes data indicating a portion of the plurality of users that created a bookmark for the location in the first document.
| 0.5 |
6,160,536 | 51 | 52 |
51. The apparatus of claim 50 wherein the indicator is further operative to modify in a second manner the appearance of a second indicator on the display area responsive to the first quantity not equalling or exceeding the first predetermined quantity.
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51. The apparatus of claim 50 wherein the indicator is further operative to modify in a second manner the appearance of a second indicator on the display area responsive to the first quantity not equalling or exceeding the first predetermined quantity. 52. The apparatus of claim 51 wherein the modification in the first manner includes a marked modification and the modification in the second manner includes a slight modification.
| 0.5 |
7,817,855 | 16 | 17 |
16. A method of detecting text in real-world images comprising: dividing an image representing a real-world scene into one or more regions; calculating a cascade of classifiers, the cascade comprising a plurality of stages, each stage including one or more weak classifiers, the plurality of stages organized to start out with classifiers that are most useful for ruling out non-text regions of the image; receiving training images; feeding the training images into the cascade; comparing classifier results to known training image results; and adapting one or more of an order of stages in the cascade, an order of classifiers in the stages, one or more classifier confidence level thresholds, and the classifiers by selecting features for each classifier that reduce a number of false positive and false negative detections by a reduced number of tests; feeding the one or more regions into the cascade; and removing regions of the image classified as the non-text regions from the cascade prior to completion of the cascade to avoid subsequent processing of the removed regions; and displaying a result.
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16. A method of detecting text in real-world images comprising: dividing an image representing a real-world scene into one or more regions; calculating a cascade of classifiers, the cascade comprising a plurality of stages, each stage including one or more weak classifiers, the plurality of stages organized to start out with classifiers that are most useful for ruling out non-text regions of the image; receiving training images; feeding the training images into the cascade; comparing classifier results to known training image results; and adapting one or more of an order of stages in the cascade, an order of classifiers in the stages, one or more classifier confidence level thresholds, and the classifiers by selecting features for each classifier that reduce a number of false positive and false negative detections by a reduced number of tests; feeding the one or more regions into the cascade; and removing regions of the image classified as the non-text regions from the cascade prior to completion of the cascade to avoid subsequent processing of the removed regions; and displaying a result. 17. The method of claim 16 , further comprising: utilizing a binarization process including classifying individual pixels as one of: non-text, light potential-text, and dark potential-text based on one or more factors including: a number of pixels in the connected component; a number of pixels on the border of the connected component; a height of the connected component; a width of the connected component; a ratio of the height of the connected component to the width of the connected component; a ratio of the pixels in the connected component to the width of the connected component multiplied by the height of the connected component; a local size of text in the connected component.
| 0.5 |
7,909,326 | 1 | 7 |
1. A method for producing a lottery product providing a story, the method comprising: printing a first page that embodies a first instant game, the first page including a first removable covering concealing a first element of a story, and the first page being associated with a first predetermined sub-payout, and the first page indicating a first predetermined running value of the lottery product; printing a second page that embodies a second instant game, the second page including a second removable covering concealing a second element of the story, and the second page being associated with a second predetermined sub-payout, and the second page indicating a second predetermined running value of the lottery product, the second predetermined running value being based on the first predetermined sub-payout and the second predetermined sub-payout; printing a table that (1) identifies a third element of the story and indicates a first potential prize for the first instant game if the third element matches the first element and (2) identifies a fourth element of the story and indicates a second potential prize for the second instant game if the fourth element matches the second element; and assembling the first page, the second page, and the table into a lottery product.
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1. A method for producing a lottery product providing a story, the method comprising: printing a first page that embodies a first instant game, the first page including a first removable covering concealing a first element of a story, and the first page being associated with a first predetermined sub-payout, and the first page indicating a first predetermined running value of the lottery product; printing a second page that embodies a second instant game, the second page including a second removable covering concealing a second element of the story, and the second page being associated with a second predetermined sub-payout, and the second page indicating a second predetermined running value of the lottery product, the second predetermined running value being based on the first predetermined sub-payout and the second predetermined sub-payout; printing a table that (1) identifies a third element of the story and indicates a first potential prize for the first instant game if the third element matches the first element and (2) identifies a fourth element of the story and indicates a second potential prize for the second instant game if the fourth element matches the second element; and assembling the first page, the second page, and the table into a lottery product. 7. The method of claim 1 , in which the story comprises educational information.
| 0.935897 |
4,881,197 | 39 | 55 |
39. In a data processing system for composing documents, said data processing system including means for entering data and commands relating to a document to be composed, data processor means for processing said data and executing commands, and at least one output means for presenting the document, said at least one output means including a first display device, a method for composing on a display device by a document composer a document comprising multiple lines of alphanumeric characters comprising the steps of: a. assigning a first name to represent and be associated with data presentation characteristics for a predetermined portion of said document upon entry of said first name via said means for entering; b. selecting by a document composer a first set of data presentation characteristics to be associated with a first field associated with said first name and defining the text character attributes used to produce the text characters appearing in said first field, said first field being associated with one part of said predetermined portion; c. selecting by a document composer an independent second set of data presentation characteristics to be associated with a second field associated with said first name and defining the text character attributes used to produce the text characters appearing in said second field, said second field being associated with another part of said predetermined portion; and d. responding to the entry of said first name by presenting the data in said one part of said predetermined portion with said first set of characteristics on the composer's display device and presenting the data in said other part of said predetermined portion with said second set of data presentation characteristics on the composer's display device, whereby the document composer may independently define a set of data presentation characteristics to be associated with each of a plurality of fields associated with said first name.
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39. In a data processing system for composing documents, said data processing system including means for entering data and commands relating to a document to be composed, data processor means for processing said data and executing commands, and at least one output means for presenting the document, said at least one output means including a first display device, a method for composing on a display device by a document composer a document comprising multiple lines of alphanumeric characters comprising the steps of: a. assigning a first name to represent and be associated with data presentation characteristics for a predetermined portion of said document upon entry of said first name via said means for entering; b. selecting by a document composer a first set of data presentation characteristics to be associated with a first field associated with said first name and defining the text character attributes used to produce the text characters appearing in said first field, said first field being associated with one part of said predetermined portion; c. selecting by a document composer an independent second set of data presentation characteristics to be associated with a second field associated with said first name and defining the text character attributes used to produce the text characters appearing in said second field, said second field being associated with another part of said predetermined portion; and d. responding to the entry of said first name by presenting the data in said one part of said predetermined portion with said first set of characteristics on the composer's display device and presenting the data in said other part of said predetermined portion with said second set of data presentation characteristics on the composer's display device, whereby the document composer may independently define a set of data presentation characteristics to be associated with each of a plurality of fields associated with said first name. 55. A method according to claim 39 wherein the document is stored in the memory means as at least one record and further including the step of: defining the beginning and ending of at least one range delineating the document portions for which the first set of characteristics are desired by associating place marks with the document text defining at least the beginning and end of the range without displaying such place marks to the document composer with the text during composition; associating control information with each record relating to the points in which a name associated with a set of data presentation characteristics begins or ends; said control information including an offset defining the bytes of the record, relative to the first record byte, that the characteristics begin and end; and an identifier that identifies said name.
| 0.5 |
9,455,945 | 14 | 19 |
14. One or more computer-readable non-transitory storage media in one or more computing systems, the media embodying logic that is operable when executed to: access a social graph of a social-networking system, the social graph comprising a plurality of nodes and edges connecting the nodes, the nodes comprising user nodes that are each associated with a particular user of the social-networking system; determine, from the social graph, that a user “likes” a first page associated with a particular version of a media content; determine that one or more other versions of the media content exist, wherein each of the one or more other versions of the media content has one or more associated pages; determine that a main page is associated with the particular version and the one or more other versions of the media content; and aggregate the user's “like” of the first page to the main page.
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14. One or more computer-readable non-transitory storage media in one or more computing systems, the media embodying logic that is operable when executed to: access a social graph of a social-networking system, the social graph comprising a plurality of nodes and edges connecting the nodes, the nodes comprising user nodes that are each associated with a particular user of the social-networking system; determine, from the social graph, that a user “likes” a first page associated with a particular version of a media content; determine that one or more other versions of the media content exist, wherein each of the one or more other versions of the media content has one or more associated pages; determine that a main page is associated with the particular version and the one or more other versions of the media content; and aggregate the user's “like” of the first page to the main page. 19. The media of claim 14 , wherein the main page is a Wikipedia page associated with the media content.
| 0.859459 |
8,266,131 | 23 | 24 |
23. The method of claim 22 , wherein a category selection question is generated if the rank of the root cube-category is greater than the rank of each dimension in the list of dimensions.
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23. The method of claim 22 , wherein a category selection question is generated if the rank of the root cube-category is greater than the rank of each dimension in the list of dimensions. 24. The method of claim 23 , wherein a composite question is generated, if the rank of the cube-category is similar to rank of at least one dimension having highest rank in the list of dimensions, wherein the composite question is a combination of the category selection question and one of a dimension selection question and dimension navigation question.
| 0.5 |
8,719,016 | 1 | 10 |
1. A method for determining structured speech, the method comprising: translating an audio recording into text using a text-to-speech communication processing system; receiving a transcript of the audio recording; analyzing text in the transcript to determine repetitions within the text, the repetitions being indicative of structured speech, wherein the text is analyzed using Large Vocabulary Continuous Speech Recognition (LVCSR); determining a duration distribution of the repetitions to ascertain a first type of structured speech; and determining a length of the repetitions to ascertain a second type of structured speech; comparing probability of correct translation of the text-to-speech communication for each word in the text to an appropriate occurrence table, wherein the occurrence table is selected based upon dialect or language of the speech, and domain in which the speech was obtained; and modifying the occurrence table based on the probability of correct translation for each word in the text.
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1. A method for determining structured speech, the method comprising: translating an audio recording into text using a text-to-speech communication processing system; receiving a transcript of the audio recording; analyzing text in the transcript to determine repetitions within the text, the repetitions being indicative of structured speech, wherein the text is analyzed using Large Vocabulary Continuous Speech Recognition (LVCSR); determining a duration distribution of the repetitions to ascertain a first type of structured speech; and determining a length of the repetitions to ascertain a second type of structured speech; comparing probability of correct translation of the text-to-speech communication for each word in the text to an appropriate occurrence table, wherein the occurrence table is selected based upon dialect or language of the speech, and domain in which the speech was obtained; and modifying the occurrence table based on the probability of correct translation for each word in the text. 10. The method of claim 1 , wherein modification of the occurrence table changes the occurrence probability by a fixed percentage or a variable percentage based on the probability of correct translation of a given word.
| 0.5 |
9,632,985 | 55 | 69 |
55. A method for electronic learning comprising: retrieving, at a first electronic reading device executing a first execution environment, a digital specification in a first language that is one of a plurality of heterogeneous execution environments, wherein the first execution environment has platform-dependent capabilities and user interface elements, and pre-processed media data of at least one interactive content presentation object for the electronic reading device, wherein the at least one interactive content presentation object is presented with a look and feel of a user interface of the electronic reading device, and wherein the media data is pre-processed to adjust for the platform-dependent capabilities of the execution environment and to ensure a consistent layout within and around the at least one interactive content presentation object across heterogeneous execution environments; parsing the digital specification, and responsive to instructions contained in the digital specification, presenting in the first execution environment of the first electronic reading device one or more interactive content presentation objects and one or more interactive assessment objects by converting the instructions in the digital specification to a second language which is executed by one or more computer processors of the first electronic reading device; receiving content interaction data corresponding to user interactions with the interactive content presentation objects and sending the interaction data to an interaction server; receiving a second content interaction data corresponding to a second user's interactions with the interactive content presentation objects from the interaction server, the second user's interactions having been received at the interaction server from a second electronic reading device executing a second execution environment different from the first execution environment and within which the digital specification was presented with a consistent layout within and around the interactive content presentation objects and interactive assessment objects in comparison to the digital specification in the first execution environment of the first electronic reading device; presenting, in the first execution environment, the second content interaction data; and sending to the interaction server, assessment data corresponding to user interactions with the interactive assessment objects.
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55. A method for electronic learning comprising: retrieving, at a first electronic reading device executing a first execution environment, a digital specification in a first language that is one of a plurality of heterogeneous execution environments, wherein the first execution environment has platform-dependent capabilities and user interface elements, and pre-processed media data of at least one interactive content presentation object for the electronic reading device, wherein the at least one interactive content presentation object is presented with a look and feel of a user interface of the electronic reading device, and wherein the media data is pre-processed to adjust for the platform-dependent capabilities of the execution environment and to ensure a consistent layout within and around the at least one interactive content presentation object across heterogeneous execution environments; parsing the digital specification, and responsive to instructions contained in the digital specification, presenting in the first execution environment of the first electronic reading device one or more interactive content presentation objects and one or more interactive assessment objects by converting the instructions in the digital specification to a second language which is executed by one or more computer processors of the first electronic reading device; receiving content interaction data corresponding to user interactions with the interactive content presentation objects and sending the interaction data to an interaction server; receiving a second content interaction data corresponding to a second user's interactions with the interactive content presentation objects from the interaction server, the second user's interactions having been received at the interaction server from a second electronic reading device executing a second execution environment different from the first execution environment and within which the digital specification was presented with a consistent layout within and around the interactive content presentation objects and interactive assessment objects in comparison to the digital specification in the first execution environment of the first electronic reading device; presenting, in the first execution environment, the second content interaction data; and sending to the interaction server, assessment data corresponding to user interactions with the interactive assessment objects. 69. The method of claim 55 , wherein presenting one or more interactive content presentation objects and one or more interactive assessment objects includes presenting a matching object, which comprises at least two categories of interactive objects and allows users to associate items in the at least two categories of interactive objects to each other.
| 0.5 |
8,924,211 | 7 | 11 |
7. At least one computer-readable storage medium having encoded thereon computer-executable instructions that, when executed by at least one computer, cause the at least one computer to carry out a method of processing results of a recognition by an automatic speech recognition (ASR) system on an utterance, the results comprising two or more results identified by the ASR system as likely to be accurate recognition results for the utterance, the two or more results comprising a first result and a second result, wherein the first result is identified by the ASR system as most likely among the two or more results to be an accurate recognition result, the method comprising: evaluating the first result using a medical fact extractor to extract a first set of one or more medical facts; evaluating the second result using the medical fact extractor to extract a second set of one or more medical facts; determining whether the first set of one or more medical facts has a meaning that is different in a medically significant way from a meaning of the second set of one or more medical facts; and in response to determining that the first set of one or more medical facts has a meaning that is different in a medically significant way from the meaning of the second set of one or more medical facts, triggering an alert, wherein the determining whether the first set of one or more medical facts has a meaning that is different in a medically significant way from the second set of one or more medical facts comprises: determining whether the first set comprises a medical fact having a fact type that is marked as significant; when it is determined that the first set comprises the medical fact having the fact type that is marked as significant, determining whether the second set comprises the medical fact; and in response to determining that the second set does not comprise the medical fact, determining that the second set has a meaning that differs from a meaning of the first set in a medically significant way.
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7. At least one computer-readable storage medium having encoded thereon computer-executable instructions that, when executed by at least one computer, cause the at least one computer to carry out a method of processing results of a recognition by an automatic speech recognition (ASR) system on an utterance, the results comprising two or more results identified by the ASR system as likely to be accurate recognition results for the utterance, the two or more results comprising a first result and a second result, wherein the first result is identified by the ASR system as most likely among the two or more results to be an accurate recognition result, the method comprising: evaluating the first result using a medical fact extractor to extract a first set of one or more medical facts; evaluating the second result using the medical fact extractor to extract a second set of one or more medical facts; determining whether the first set of one or more medical facts has a meaning that is different in a medically significant way from a meaning of the second set of one or more medical facts; and in response to determining that the first set of one or more medical facts has a meaning that is different in a medically significant way from the meaning of the second set of one or more medical facts, triggering an alert, wherein the determining whether the first set of one or more medical facts has a meaning that is different in a medically significant way from the second set of one or more medical facts comprises: determining whether the first set comprises a medical fact having a fact type that is marked as significant; when it is determined that the first set comprises the medical fact having the fact type that is marked as significant, determining whether the second set comprises the medical fact; and in response to determining that the second set does not comprise the medical fact, determining that the second set has a meaning that differs from a meaning of the first set in a medically significant way. 11. The at least one computer-readable storage medium of claim 7 , wherein the results of the recognition by the ASR system comprise a plurality of results identified by the ASR system as likely to be an accurate recognition result for the speech input, and wherein the method further comprises selecting, from the plurality of results, the two or more results to be evaluated by the medical fact extractor.
| 0.665296 |
6,163,775 | 41 | 43 |
41. A method for storing and retrieving data in a computer system having a memory, a central processing unit and a display, comprising the steps of: configuring said memory according to a logical table, said logical table including: a plurality of cells, each said cell having a first address segment and a second address segment; a plurality of attribute sets, each said attribute set including a series of cells having the same second address segment, each said attribute set including an object identification number (OID) to identify each said attribute set; a plurality of records, each said record including a series of cells having the same first address segment, each said record including an OID to identify each said record, wherein at least one of said records has an OID equal to the OID of a corresponding one of said attribute sets, and at least one of said records includes attribute set information defining each of said attribute sets; and searching said table for said pointer.
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41. A method for storing and retrieving data in a computer system having a memory, a central processing unit and a display, comprising the steps of: configuring said memory according to a logical table, said logical table including: a plurality of cells, each said cell having a first address segment and a second address segment; a plurality of attribute sets, each said attribute set including a series of cells having the same second address segment, each said attribute set including an object identification number (OID) to identify each said attribute set; a plurality of records, each said record including a series of cells having the same first address segment, each said record including an OID to identify each said record, wherein at least one of said records has an OID equal to the OID of a corresponding one of said attribute sets, and at least one of said records includes attribute set information defining each of said attribute sets; and searching said table for said pointer. 43. The method of claim 41 wherein at least one of said records is a folder type record, said folder type record including at least one cell that contains data and a plurality of pointers to a plurality of other records included within said folder.
| 0.535581 |
7,698,315 | 3 | 4 |
3. The method of claim 1 further comprising: receiving a grouping indication from an advertiser along with an indication of advertisements associated with the advertiser to which the grouping indication should apply to group the advertisements according to the grouping indication.
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3. The method of claim 1 further comprising: receiving a grouping indication from an advertiser along with an indication of advertisements associated with the advertiser to which the grouping indication should apply to group the advertisements according to the grouping indication. 4. The method of claim 3 wherein receiving a grouping indication comprises receiving a category name entered by the advertiser in an input text box of a web page displayed to the advertiser.
| 0.5 |
8,788,270 | 1 | 3 |
1. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring, via one or more processors, one or more acoustic characteristics of the subject utterance of speech; comparing, via the one or more processors, each acoustic characteristic of the one or more acoustic characteristics of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining, via the one or more processors, an emotion state of the speaker based on the comparison, wherein determining the emotion state of the speaker based on the comparison occurs within one day of receiving the subject utterance of speech by the speaker.
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1. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring, via one or more processors, one or more acoustic characteristics of the subject utterance of speech; comparing, via the one or more processors, each acoustic characteristic of the one or more acoustic characteristics of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining, via the one or more processors, an emotion state of the speaker based on the comparison, wherein determining the emotion state of the speaker based on the comparison occurs within one day of receiving the subject utterance of speech by the speaker. 3. The method according to claim 1 , wherein determining the emotion state of speaker based on the comparison comprises determining one or more emotions of the speaker based on the comparison.
| 0.862464 |
9,176,958 | 4 | 5 |
4. The method according to claim 1 , wherein said constructing the tempo word set comprises: generating a fault-tolerant tempo word corresponding to each of the tempo words.
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4. The method according to claim 1 , wherein said constructing the tempo word set comprises: generating a fault-tolerant tempo word corresponding to each of the tempo words. 5. The method according to claim 4 , wherein said generating the fault-tolerant tempo word comprises: selecting one or more tempo scales contained in a corresponding tempo word; and replacing the selected tempo scales in said corresponding tempo word with corresponding fault-tolerant tempo scales to generate the fault-tolerant tempo word.
| 0.5 |
8,311,796 | 1 | 2 |
1. A system for recognizing an input signal entered via a shorthand-on-keyboard interface and for allowing a stem and an affix of an input text to be combined, the system comprising: a memory; a concatenation module stored on the memory that is configured, when executed, to recognize the input signal as an input affix, wherein the concatenation module further recognizes a candidate word as a neighboring candidate word; a compound word module stored on the memory that is configured, when executed, to retrieve a set of words in a lexicon containing the input affix; a ranking module stored on the memory that is configured, when executed, to rank the set of words containing the input affix according to a similarity function that compares each lexicon word in the set of words containing the input affix, with a string containing the candidate word and the input affix, and wherein the compound word module outputs a highest ranked lexicon word in the set of words containing the input affix; and a module stored on the memory that is configured, when executed, to separately display at least two words or affixes and concatenate the at least two words or affixes in response to a circular motion touching inner edges of the at least two words or affixes, wherein the at least two words or affixes correspond to the candidate word and the input affix.
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1. A system for recognizing an input signal entered via a shorthand-on-keyboard interface and for allowing a stem and an affix of an input text to be combined, the system comprising: a memory; a concatenation module stored on the memory that is configured, when executed, to recognize the input signal as an input affix, wherein the concatenation module further recognizes a candidate word as a neighboring candidate word; a compound word module stored on the memory that is configured, when executed, to retrieve a set of words in a lexicon containing the input affix; a ranking module stored on the memory that is configured, when executed, to rank the set of words containing the input affix according to a similarity function that compares each lexicon word in the set of words containing the input affix, with a string containing the candidate word and the input affix, and wherein the compound word module outputs a highest ranked lexicon word in the set of words containing the input affix; and a module stored on the memory that is configured, when executed, to separately display at least two words or affixes and concatenate the at least two words or affixes in response to a circular motion touching inner edges of the at least two words or affixes, wherein the at least two words or affixes correspond to the candidate word and the input affix. 2. The system of claim 1 , wherein the input affix is a suffix.
| 0.5 |
8,954,539 | 8 | 9 |
8. The system of claim 7 , wherein the predictive information includes behavioral information and information associated with the one or more requests for the one or more web pages.
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8. The system of claim 7 , wherein the predictive information includes behavioral information and information associated with the one or more requests for the one or more web pages. 9. The system of claim 8 , wherein the behavioral information includes a time of one or more previous visits in a domain that includes a requested web page, a time that the web page was last requested, a number of visits in the domain, a number of times that the object has been presented, and a number of times that the object has been selected.
| 0.5 |
7,529,685 | 1 | 8 |
1. A method of querying a computer database that comprises a plurality of electronic data records containing strings of terms in a natural human language format, to retrieve a final result set comprising a selection of data records that satisfy a search query, comprising the steps of: receiving input from a user corresponding to a creation of at least one initial inclusion rule, the initial inclusion rule comprising one or more descriptive search terms that are required to occur in each record in the final result set; receiving input from a user corresponding to a creation of at least one initial exclusion rule, the initial exclusion rule comprising one or more descriptive search terms that are required to not occur in the final result set; storing the at least one initial inclusion rule and the at least one initial exclusion rule as an initial descriptive taxonomy; querying the computer database utilizing the initial descriptive taxonomy as a search query to generate an initial inclusion result set and an initial exclusion result set; displaying the initial inclusion result set and the initial exclusion result set to the user, for inspection by the user to assess whether the initial inclusion result set and the initial exclusion result set comprise records desired by the user, the display of the initial inclusion result set including an exclusion flag identifying data records that also appear in the initial exclusion result set; receiving input from the user corresponding to a provision of additional descriptive search terms for addition to the descriptive search terms in the initial inclusion rule such that further data records containing such additional descriptive search terms will be included in the final result set; storing the additional descriptive search terms for the initial inclusion rule as an updated inclusion rule; receiving input from the user removing the exclusion flag for a particular data record that the user has determined should occur in the final result set notwithstanding its occurrence in the initial exclusion result set; storing information relating to a data record for which an exclusion flag has been removed as an updated exclusion rule, such that the data record will henceforth occur in the final result set; storing the updated inclusion rule and the updated exclusion rule as an updated descriptive taxonomy; and querying the computer database utilizing the updated descriptive taxonomy as a search query to generate the final result set, whereby data records that satisfy the updated inclusion rule are included in the data records in the final result set and data records for which the exclusion flag has been removed also are included in the final result set.
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1. A method of querying a computer database that comprises a plurality of electronic data records containing strings of terms in a natural human language format, to retrieve a final result set comprising a selection of data records that satisfy a search query, comprising the steps of: receiving input from a user corresponding to a creation of at least one initial inclusion rule, the initial inclusion rule comprising one or more descriptive search terms that are required to occur in each record in the final result set; receiving input from a user corresponding to a creation of at least one initial exclusion rule, the initial exclusion rule comprising one or more descriptive search terms that are required to not occur in the final result set; storing the at least one initial inclusion rule and the at least one initial exclusion rule as an initial descriptive taxonomy; querying the computer database utilizing the initial descriptive taxonomy as a search query to generate an initial inclusion result set and an initial exclusion result set; displaying the initial inclusion result set and the initial exclusion result set to the user, for inspection by the user to assess whether the initial inclusion result set and the initial exclusion result set comprise records desired by the user, the display of the initial inclusion result set including an exclusion flag identifying data records that also appear in the initial exclusion result set; receiving input from the user corresponding to a provision of additional descriptive search terms for addition to the descriptive search terms in the initial inclusion rule such that further data records containing such additional descriptive search terms will be included in the final result set; storing the additional descriptive search terms for the initial inclusion rule as an updated inclusion rule; receiving input from the user removing the exclusion flag for a particular data record that the user has determined should occur in the final result set notwithstanding its occurrence in the initial exclusion result set; storing information relating to a data record for which an exclusion flag has been removed as an updated exclusion rule, such that the data record will henceforth occur in the final result set; storing the updated inclusion rule and the updated exclusion rule as an updated descriptive taxonomy; and querying the computer database utilizing the updated descriptive taxonomy as a search query to generate the final result set, whereby data records that satisfy the updated inclusion rule are included in the data records in the final result set and data records for which the exclusion flag has been removed also are included in the final result set. 8. The method of claim 1 , wherein the descriptive search terms include groups of clinical descriptions, the clinical descriptions having multiple related medical terms.
| 0.669922 |
9,594,756 | 10 | 11 |
10. The method of claim 9 , wherein the calculating of the personal network factor for a particular contributor is based at least in part on respective ranking values of the one or more followers in the follower network of which the particular contributor is the target contributor.
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10. The method of claim 9 , wherein the calculating of the personal network factor for a particular contributor is based at least in part on respective ranking values of the one or more followers in the follower network of which the particular contributor is the target contributor. 11. The method of claim 10 , wherein the calculating of the personal network factor comprises summing the ranking values of the one or more followers in the follower network of the particular contributor.
| 0.542601 |
9,336,256 | 17 | 22 |
17. At least one non-transitory computer-readable medium storing computer-readable instructions that, when executed by one or more computing devices, cause at least one of the one or more computing devices to: receive a request directed to a tokenized database, wherein the tokenized database contains one or more tokenized data values and wherein the request does not include any tokenized data values; apply one or more rules to the request; rewrite the request based on at least one of the one or more rules, wherein the rewritten request is configured to cause one or more non-tokenized data values specified in the request to be tokenized by a software agent resident on the tokenized database when data is added to the tokenized database as a result of the request and wherein the rewritten request is configured to cause the tokenized database to return non-tokenized data values when data is received from the tokenized database as a result of the request; and transmit the rewritten request to the tokenized database.
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17. At least one non-transitory computer-readable medium storing computer-readable instructions that, when executed by one or more computing devices, cause at least one of the one or more computing devices to: receive a request directed to a tokenized database, wherein the tokenized database contains one or more tokenized data values and wherein the request does not include any tokenized data values; apply one or more rules to the request; rewrite the request based on at least one of the one or more rules, wherein the rewritten request is configured to cause one or more non-tokenized data values specified in the request to be tokenized by a software agent resident on the tokenized database when data is added to the tokenized database as a result of the request and wherein the rewritten request is configured to cause the tokenized database to return non-tokenized data values when data is received from the tokenized database as a result of the request; and transmit the rewritten request to the tokenized database. 22. The at least one non-transitory computer-readable medium of claim 17 , wherein applying one or more rules and rewriting the request comprises: selecting an incomplete request rule when the request is determined to be incomplete; transmitting a request for missing data to the tokenized database, wherein the missing data is the incomplete portion of the request; receiving the missing data from the tokenized database; and rewriting the request to include missing data.
| 0.745699 |
8,984,386 | 44 | 45 |
44. The one or more non-transitory computer-readable media of claim 38 wherein a given view, of the one or more views, is associated with the particular interaction at least in that the particular interaction includes interaction with the given view; and a given link, of the one or more links, provides access to the given view.
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44. The one or more non-transitory computer-readable media of claim 38 wherein a given view, of the one or more views, is associated with the particular interaction at least in that the particular interaction includes interaction with the given view; and a given link, of the one or more links, provides access to the given view. 45. The one or more non-transitory computer-readable media of claim 44 wherein the one or more views include the given view and a particular view, and the particular view is associated with the particular interaction at least in that particular view provides context of the particular interaction.
| 0.5 |
7,483,947 | 21 | 33 |
21. A method of filtering a message, comprising: pre-rendering the message into a final format, the message including one or more compressed images, for each of the one or more compressed images a first hash is generated, wherein the one or more compressed images are rendered in an uncompressed mode, for each of the one or more compressed images rendered in the uncompressed mode a second hash is generated, the first and second hashes are compared to determine if the message contains junk indicia; converting the message of the final format into a text-only message; processing the text-only message for predetermined content; and routing the message based upon the predetermined content.
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21. A method of filtering a message, comprising: pre-rendering the message into a final format, the message including one or more compressed images, for each of the one or more compressed images a first hash is generated, wherein the one or more compressed images are rendered in an uncompressed mode, for each of the one or more compressed images rendered in the uncompressed mode a second hash is generated, the first and second hashes are compared to determine if the message contains junk indicia; converting the message of the final format into a text-only message; processing the text-only message for predetermined content; and routing the message based upon the predetermined content. 33. The method of claim 21 , wherein rendered text and unrendered text is paused to a junk filter.
| 0.87037 |
9,069,847 | 25 | 27 |
25. The article of claim 19 wherein the initially processing generates a forward index comprising the initial representations, and the subsequently processing comprises adding the subsequent representations to the forward index.
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25. The article of claim 19 wherein the initially processing generates a forward index comprising the initial representations, and the subsequently processing comprises adding the subsequent representations to the forward index. 27. The article of claim 25 wherein the initially processing generates a reverse index which includes one list of the features and the initial documents which include respective ones of the features.
| 0.658076 |
8,517,742 | 12 | 13 |
12. The method of claim 11 , wherein the labor resource is rejected based on exceeding the compensation rate threshold.
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12. The method of claim 11 , wherein the labor resource is rejected based on exceeding the compensation rate threshold. 13. The method of claim 12 , wherein the method further includes providing a status of the answer associated with the labor resource.
| 0.5 |
7,970,783 | 7 | 12 |
7. A computer-readable storage medium encoded with instructions for causing one or more programmable processors to: define one or more macro functions to prompt for user inputs and accept the user inputs during execution of the one or more macro functions; produce a report layout containing one or more macrotized database language expressions, the one or more macrotized database language expressions having at least one of the macro functions; produce one or more valid database language expressions for a database query by at least modifying the one or more macrotized database language expressions of the report layout, wherein the one or more macrotized database language expressions are modified based upon a return value of the at least one of the macro functions, and wherein the return value of the at least one of the macro functions includes at least one of the user inputs accepted during execution of the one or more macro functions; and apply the one or more valid database language expressions to one or more databases to produce the business report, wherein the business report is based on the report layout.
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7. A computer-readable storage medium encoded with instructions for causing one or more programmable processors to: define one or more macro functions to prompt for user inputs and accept the user inputs during execution of the one or more macro functions; produce a report layout containing one or more macrotized database language expressions, the one or more macrotized database language expressions having at least one of the macro functions; produce one or more valid database language expressions for a database query by at least modifying the one or more macrotized database language expressions of the report layout, wherein the one or more macrotized database language expressions are modified based upon a return value of the at least one of the macro functions, and wherein the return value of the at least one of the macro functions includes at least one of the user inputs accepted during execution of the one or more macro functions; and apply the one or more valid database language expressions to one or more databases to produce the business report, wherein the business report is based on the report layout. 12. The computer-readable storage medium of claim 7 , wherein the user inputs include at least one of a set of user-selected prompt responses, an indication of a language in which to produce a business report, and database connection information.
| 0.810185 |
6,044,365 | 1 | 2 |
1. A system for indexing and retrieving information for social expression cards comprising: means for linking said information for each social expression card to a set of descriptors; means for allowing a user to enter one or more search descriptors; thesaurus means for expanding the list of search descriptors by including equivalent words for the search descriptors; and means for retrieving said information for social expression cards linked to said search descriptors or equivalent words for said search descriptors in said expanded list.
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1. A system for indexing and retrieving information for social expression cards comprising: means for linking said information for each social expression card to a set of descriptors; means for allowing a user to enter one or more search descriptors; thesaurus means for expanding the list of search descriptors by including equivalent words for the search descriptors; and means for retrieving said information for social expression cards linked to said search descriptors or equivalent words for said search descriptors in said expanded list. 2. The system of claim 1, wherein said information for each social expression card comprises one or more data files containing the images, text, and formatting information linked to an identifier.
| 0.5625 |
8,719,176 | 21 | 23 |
21. A computer-implemented method, said computer comprising at least a processor and a memory and being connected to a first computer network, said memory comprising at least a first news database for storing a plurality of news submissions, the method comprising: registering a first user account; receiving, via said first computer network, a URL and a first term, said first term comprising a word or phrase; providing, via said first computer network, at least one of said URL and said first term to a community of users; determining, by computer, a first score, said first score pertaining to at least one of said URL and said first term, said first score being based at least partly on a measurement of popularity; and at least partly causing, via said first computer network, display of a first real-time news feed or ticker, said first real-time news feed or ticker comprising or conveying a plurality of real-time news items, said plurality of real-time news items comprising at least a first item, said first item relating to said first user account.
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21. A computer-implemented method, said computer comprising at least a processor and a memory and being connected to a first computer network, said memory comprising at least a first news database for storing a plurality of news submissions, the method comprising: registering a first user account; receiving, via said first computer network, a URL and a first term, said first term comprising a word or phrase; providing, via said first computer network, at least one of said URL and said first term to a community of users; determining, by computer, a first score, said first score pertaining to at least one of said URL and said first term, said first score being based at least partly on a measurement of popularity; and at least partly causing, via said first computer network, display of a first real-time news feed or ticker, said first real-time news feed or ticker comprising or conveying a plurality of real-time news items, said plurality of real-time news items comprising at least a first item, said first item relating to said first user account. 23. The method in claim 21 additionally comprising: at least partly causing, by computer, display of first indicia, said first indicia indicating a quantity that is at least partly based on said measurement of popularity.
| 0.728501 |
8,533,274 | 12 | 14 |
12. A non-transitory computer readable storage medium and one or more computer programs embedded therein the one or more computer programs comprising instructions which, when executed by a computer system, cause the computer system to: receive a plurality of messages directed to a particular user, each message having a unique message identifier; determining a respective conversation for each of the plurality of messages, each conversation having a respective conversation identifier; wherein each conversation comprises a set of one or more messages sharing a common set of characteristics that meet first predefined criteria; send to a client system for display a first list of conversations including the respective conversation in an order determined in accordance with second predefined criteria, as a set of rows, each row corresponding to one of the listed conversations and including at least a sender list, a conversation topic and a date/time value, the sender list configured by the computer system to include only identifiers of senders of messages in the conversation corresponding to the row; enable the particular user to identify one or more conversations in the first list of conversations, and to mark the identified one or more conversations as belonging to a particular category while continuing to display the first list of conversations, which includes the identified one or more conversations; update attributes of the identified one or more conversations to indicate that the identified one or more conversations belong to the particular category; and send to the client system for display a second list of conversations, the second list comprising only conversations marked as belonging to the particular category, wherein a plurality of the conversations listed in the second list each have a plurality of messages, and wherein the second list includes only a single row for each distinct conversation listed in the second list.
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12. A non-transitory computer readable storage medium and one or more computer programs embedded therein the one or more computer programs comprising instructions which, when executed by a computer system, cause the computer system to: receive a plurality of messages directed to a particular user, each message having a unique message identifier; determining a respective conversation for each of the plurality of messages, each conversation having a respective conversation identifier; wherein each conversation comprises a set of one or more messages sharing a common set of characteristics that meet first predefined criteria; send to a client system for display a first list of conversations including the respective conversation in an order determined in accordance with second predefined criteria, as a set of rows, each row corresponding to one of the listed conversations and including at least a sender list, a conversation topic and a date/time value, the sender list configured by the computer system to include only identifiers of senders of messages in the conversation corresponding to the row; enable the particular user to identify one or more conversations in the first list of conversations, and to mark the identified one or more conversations as belonging to a particular category while continuing to display the first list of conversations, which includes the identified one or more conversations; update attributes of the identified one or more conversations to indicate that the identified one or more conversations belong to the particular category; and send to the client system for display a second list of conversations, the second list comprising only conversations marked as belonging to the particular category, wherein a plurality of the conversations listed in the second list each have a plurality of messages, and wherein the second list includes only a single row for each distinct conversation listed in the second list. 14. The non-transitory computer readable storage medium of claim 12 , wherein the second list of conversations is produced by executing a corresponding search query.
| 0.770195 |
8,943,083 | 1 | 6 |
1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: a. providing a set of content items, each content item having at least one associated descriptive term to describe the content item; b. receiving incremental input entered by the user for incrementally identifying desired content items; c. in response to the incremental input entered by the user, presenting a subset of content items; d. receiving selection actions of content items of the subset from the user; e. analyzing the descriptive terms associated with the selected content items to learn the preferred descriptive terms of the user; f. expressing the learned preferred descriptive terms as a segmented measurement collection having at least one fine grain segment, wherein the segmented measurement collection is a segmented probability distribution function that associates probability weights with the preferred descriptive terms, and wherein the fine grain segment has relatively fine grain differentiation of measurements associated with preferred descriptive terms within the segment, and further wherein the segmented measurement collection further includes an overflow segment, such that the measurements within the overflow segment are not differentiated from other measurements within the overflow segment, and wherein measurements within the overflow segment are differentiated from the measurements within the fine grain segment; and g. in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented measurement collection; h. wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device.
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1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: a. providing a set of content items, each content item having at least one associated descriptive term to describe the content item; b. receiving incremental input entered by the user for incrementally identifying desired content items; c. in response to the incremental input entered by the user, presenting a subset of content items; d. receiving selection actions of content items of the subset from the user; e. analyzing the descriptive terms associated with the selected content items to learn the preferred descriptive terms of the user; f. expressing the learned preferred descriptive terms as a segmented measurement collection having at least one fine grain segment, wherein the segmented measurement collection is a segmented probability distribution function that associates probability weights with the preferred descriptive terms, and wherein the fine grain segment has relatively fine grain differentiation of measurements associated with preferred descriptive terms within the segment, and further wherein the segmented measurement collection further includes an overflow segment, such that the measurements within the overflow segment are not differentiated from other measurements within the overflow segment, and wherein measurements within the overflow segment are differentiated from the measurements within the fine grain segment; and g. in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented measurement collection; h. wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device. 6. The method of claim 1 , wherein the learned preferred descriptive terms are further based on: analyzing the date, day, and time of the user selection actions and analyzing the descriptive terms associated with the selected content items to learn a periodicity of user selections of similar content items, wherein similarity is determined by comparing the descriptive terms of the selected content item with the previously selected content item, and wherein the periodicity indicates the amount of time between user selections of similar content items relative to a reference point; and associating the learned periodicity with descriptive terms associated with the similar content items; wherein the selecting and ordering the collection of content items is further based on promoting the ranking of those content items associated with descriptive terms further associated with periodicities similar to the date, day, and time of the subsequent incremental input.
| 0.5 |
9,633,082 | 11 | 19 |
11. A search result ranking device, comprising: at least one processor configured to: record user action information on displayed objects in search results obtained using one or more query words, wherein the displayed objects relate to products or product information; upon receiving a switch-page request or switch-screen request, determine two or more commonality levels of one or more attribute characteristics in objects subjected to user actions, wherein the determining of the two or more commonality levels is based on the user action information on the displayed objects, wherein the one or more attribute characteristics include: title of a product, price of a product, image or image address of a product, number of recent transactions of a product, shipping costs of a product, area where product is located, seller's name of a product, self-defined tags provided by a product publisher, service tags provided by a product publisher, or any combination thereof, and wherein the determining of the two or more commonality levels comprises to: calculate first commonality levels of attribute characteristics of objects in a selected set based on the recorded user action information on the displayed objects, wherein the selected set includes user-selected objects of the displayed objects, a first commonality level corresponding to a ratio of a number of objects having the same or similar attribute characteristic of the user-selected objects and a total number of the user-selected objects; and calculate second commonality levels of attribute characteristics of objects in an unselected set, wherein the unselected set includes displayed objects that have not been selected, a second commonality level corresponding to a ratio of a number of objects having the same or similar attribute characteristic of the displayed objects that have not been selected and a total number of the displayed objects that have not been selected; select attribute characteristics that comply with predetermined requirements to serve as reference norms for ranking objects that are to be displayed or ranked, wherein the selecting of the attribute characteristics is based on the first commonality level of the calculated first commonality levels and the second commonality level of the calculated second commonality levels; and adjust rank of objects that are to be displayed or to be ranked and whose attribute characteristics comply with the reference norms, wherein the objects that are to be displayed or to be ranked have not yet been displayed and are on a separate page from the displayed objects; and at least one memory coupled to the at least one processor and configured to provide the at least one processor with instructions.
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11. A search result ranking device, comprising: at least one processor configured to: record user action information on displayed objects in search results obtained using one or more query words, wherein the displayed objects relate to products or product information; upon receiving a switch-page request or switch-screen request, determine two or more commonality levels of one or more attribute characteristics in objects subjected to user actions, wherein the determining of the two or more commonality levels is based on the user action information on the displayed objects, wherein the one or more attribute characteristics include: title of a product, price of a product, image or image address of a product, number of recent transactions of a product, shipping costs of a product, area where product is located, seller's name of a product, self-defined tags provided by a product publisher, service tags provided by a product publisher, or any combination thereof, and wherein the determining of the two or more commonality levels comprises to: calculate first commonality levels of attribute characteristics of objects in a selected set based on the recorded user action information on the displayed objects, wherein the selected set includes user-selected objects of the displayed objects, a first commonality level corresponding to a ratio of a number of objects having the same or similar attribute characteristic of the user-selected objects and a total number of the user-selected objects; and calculate second commonality levels of attribute characteristics of objects in an unselected set, wherein the unselected set includes displayed objects that have not been selected, a second commonality level corresponding to a ratio of a number of objects having the same or similar attribute characteristic of the displayed objects that have not been selected and a total number of the displayed objects that have not been selected; select attribute characteristics that comply with predetermined requirements to serve as reference norms for ranking objects that are to be displayed or ranked, wherein the selecting of the attribute characteristics is based on the first commonality level of the calculated first commonality levels and the second commonality level of the calculated second commonality levels; and adjust rank of objects that are to be displayed or to be ranked and whose attribute characteristics comply with the reference norms, wherein the objects that are to be displayed or to be ranked have not yet been displayed and are on a separate page from the displayed objects; and at least one memory coupled to the at least one processor and configured to provide the at least one processor with instructions. 19. The search result ranking device as described in claim 11 , wherein the at least one processor is further configured to: classify objects that were displayed among the search results but not yet selected with the unselected set, wherein the adjusting of the rank of objects that are to be displayed or to be ranked and whose attribute characteristics comply with the reference norms comprises: calculate a commonality level of each attribute characteristic in the unselected set based on the user action information on the objects in the unselected set; rank various attribute characteristics in the selected set and the unselected set in order of highest to lowest commonality level; select a pre-established quantity of top-ranked attribute characteristics to serve as the reference norms; and lower the rank of objects that are to be displayed or to be ranked and whose attribute characteristics comply with the reference norms.
| 0.6316 |
9,922,654 | 9 | 16 |
9. The incremental speech recognition system of claim 8 , wherein the computer-executable instructions are further executable by the at least one processor for: merging results from the first speech decoding model and the second speech decoding model.
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9. The incremental speech recognition system of claim 8 , wherein the computer-executable instructions are further executable by the at least one processor for: merging results from the first speech decoding model and the second speech decoding model. 16. The incremental speech recognition system of claim 9 , wherein the computer-executable instructions are further executable by the at least one processor for: building a statistical classifier based on results obtained by decoding training data using the series of speech decoding models.
| 0.644254 |
9,916,379 | 11 | 14 |
11. The computer-readable storage medium of claim 10 , wherein said instructions further comprise instructions that when executed by the processor, cause the processor to: identify a first set of fields in the unstructured data to obtain field identification data from the unstructured data source, the unstructured data including text records, each of the fields in the first set of fields corresponding to a portion of text extracted from a portion of at least one of the text records; wherein generating the second query in the second query language associated with the unstructured data store includes generating the second query by using the identified first set of fields.
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11. The computer-readable storage medium of claim 10 , wherein said instructions further comprise instructions that when executed by the processor, cause the processor to: identify a first set of fields in the unstructured data to obtain field identification data from the unstructured data source, the unstructured data including text records, each of the fields in the first set of fields corresponding to a portion of text extracted from a portion of at least one of the text records; wherein generating the second query in the second query language associated with the unstructured data store includes generating the second query by using the identified first set of fields. 14. The computer-readable storage medium of claim 11 , wherein querying of the unstructured data to identify the first set of fields is performed on a subset of the unstructured data, and wherein the subset of the unstructured data is of a definable size.
| 0.5 |
9,478,057 | 1 | 4 |
1. A method for chaining animations, the method comprising: receiving image data that is representative of captured motion; selecting a pre-canned animation; identifying at least one parameter that is indicative of a transition point, wherein a parameter of the transition point is set based at least in part on a gesture difficulty; and chaining an animation of the captured motion and the pre-canned animation by at least displaying the captured motion and the pre-canned animation in sequence, wherein chaining the animation of the captured motion and the pre-canned animation comprises blending the animation of the captured motion to the pre-canned animation or blending the pre-canned animation to the animation of the captured motion, wherein determining that the at least one parameter is satisfied triggers the chaining the animation of the captured motion and the pre-canned animation.
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1. A method for chaining animations, the method comprising: receiving image data that is representative of captured motion; selecting a pre-canned animation; identifying at least one parameter that is indicative of a transition point, wherein a parameter of the transition point is set based at least in part on a gesture difficulty; and chaining an animation of the captured motion and the pre-canned animation by at least displaying the captured motion and the pre-canned animation in sequence, wherein chaining the animation of the captured motion and the pre-canned animation comprises blending the animation of the captured motion to the pre-canned animation or blending the pre-canned animation to the animation of the captured motion, wherein determining that the at least one parameter is satisfied triggers the chaining the animation of the captured motion and the pre-canned animation. 4. The method in accordance with claim 1 , further comprising modifying parameters of the pre-canned animation in response to history data associated with a user.
| 0.72449 |
7,729,920 | 2 | 5 |
2. An automated system, comprising: a command processing system that processes input commands; and a command execution system that executes an input command based on command processing results provided by the command processing system, wherein the command processing system evaluates consequences of executing input commands and take preventative actions for execution of input commands that could result in undesirable consequences, and wherein the command processing system, comprises: an automatic recognition system for recognizing input patterns associated with the input command; a command interpretation system to interpret input commands based on recognition results generated by the automatic recognition system; a consequence evaluation system to determine a potential consequence of executing input commands based on interpretation results generated by the command interpretation system and determine a likelihood that the potential consequences can occur; and a feedback system to perform preventative actions for executing input commands when consequence evaluation results of an input command indicate at the likelihood of the potential consequence is greater than a threshold, wherein the potential consequence is an undesirable consequence of executing the input command.
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2. An automated system, comprising: a command processing system that processes input commands; and a command execution system that executes an input command based on command processing results provided by the command processing system, wherein the command processing system evaluates consequences of executing input commands and take preventative actions for execution of input commands that could result in undesirable consequences, and wherein the command processing system, comprises: an automatic recognition system for recognizing input patterns associated with the input command; a command interpretation system to interpret input commands based on recognition results generated by the automatic recognition system; a consequence evaluation system to determine a potential consequence of executing input commands based on interpretation results generated by the command interpretation system and determine a likelihood that the potential consequences can occur; and a feedback system to perform preventative actions for executing input commands when consequence evaluation results of an input command indicate at the likelihood of the potential consequence is greater than a threshold, wherein the potential consequence is an undesirable consequence of executing the input command. 5. The system of claim 2 , wherein the feedback system comprises a notification system to generate an alert signal or notification message to provide notification of the undesirable consequence of executing an input command.
| 0.5 |
9,063,960 | 2 | 3 |
2. The computer-implemented method of claim 1 , further comprising performing the online analytical processing operation.
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2. The computer-implemented method of claim 1 , further comprising performing the online analytical processing operation. 3. The computer-implemented method of claim 2 , wherein performing the online analytical processing operation comprises: generating a database query based on the request and the logical data model; performing the database query.
| 0.5 |
7,917,771 | 9 | 16 |
9. A computer program product, comprising a computer readable storage device containing instructions that, upon being executed by a processor of a data processing system, implement a method for selective encryption within a document, said method comprising: detecting a first section of a document, said first section having been selected and marked for encryption; detecting a second section of the document, said second section having been selected and marked for encryption; encrypting the first section with one encryption key; encrypting the second section with two different encryption keys, wherein the first section is not embedded in any other section of the document that has been encrypted and/or marked for encryption and no other section of the document that has been encrypted and/or marked for encryption is embedded in the first section, and wherein the second section is not embedded in any other section of the document that has been encrypted and/or marked for encryption and no other section of the document that has been encrypted and/or marked for encryption is embedded in the second section, receiving an access request to access the encrypted first section of the document; responsive to said receiving the access request, determining that a received decryption key for the encrypted first section of the document is proper for the encrypted first section, by attempting to decrypt the encrypted first section with the received decryption key by determining that a defined character string is in the encrypted first section; responsive to said determining that the received decryption key is proper for the encrypted first section of the document, retrieving and decrypting the encrypted first section of the document for which the access request was made to generate a first decrypted section of the document corresponding to the encrypted first section; and displaying the first decrypted section of the document.
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9. A computer program product, comprising a computer readable storage device containing instructions that, upon being executed by a processor of a data processing system, implement a method for selective encryption within a document, said method comprising: detecting a first section of a document, said first section having been selected and marked for encryption; detecting a second section of the document, said second section having been selected and marked for encryption; encrypting the first section with one encryption key; encrypting the second section with two different encryption keys, wherein the first section is not embedded in any other section of the document that has been encrypted and/or marked for encryption and no other section of the document that has been encrypted and/or marked for encryption is embedded in the first section, and wherein the second section is not embedded in any other section of the document that has been encrypted and/or marked for encryption and no other section of the document that has been encrypted and/or marked for encryption is embedded in the second section, receiving an access request to access the encrypted first section of the document; responsive to said receiving the access request, determining that a received decryption key for the encrypted first section of the document is proper for the encrypted first section, by attempting to decrypt the encrypted first section with the received decryption key by determining that a defined character string is in the encrypted first section; responsive to said determining that the received decryption key is proper for the encrypted first section of the document, retrieving and decrypting the encrypted first section of the document for which the access request was made to generate a first decrypted section of the document corresponding to the encrypted first section; and displaying the first decrypted section of the document. 16. The computer program product of claim 9 , said first section consisting of text, said method further comprising: after said encrypting the first section and said encrypting the second section, displaying the document with the encrypted first section being displayed with the text being blanked out and with diagonal red lines drawn under the blanked out text.
| 0.559466 |
8,635,071 | 16 | 17 |
16. The method of generating the record sentence of claim 14 , further comprising: generating a weight for the sentence having the unseen unit, wherein the weight for the sentence is determined according to a linguistic criterion for the unseen unit and/or a phonetic criterion for the unseen unit.
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16. The method of generating the record sentence of claim 14 , further comprising: generating a weight for the sentence having the unseen unit, wherein the weight for the sentence is determined according to a linguistic criterion for the unseen unit and/or a phonetic criterion for the unseen unit. 17. The method of generating the record sentence of claim 16 , wherein the weight for the sentence is determined according to at least one of the weight of the unseen unit included in the sentence, the weight of the word included in the sentence, and a type of the sentence.
| 0.5 |
9,588,961 | 11 | 20 |
11. A computer program product comprising a non-transitory computer readable medium having a computer readable program stored therein, wherein the computer readable program, when executed in a data processing system, configures the data processing system to implement a natural language processing system that performs natural language processing on natural language content at least by processing logical relationships in the natural language content, wherein the natural language processing system operates to: generate a logical parse hierarchical representation of a first parse of a natural language content by identifying latent logical operators within the first parse indicative of logical relationships between elements of the natural language content, wherein the logical parse hierarchical representation comprises nodes and edges linking nodes; associate at least one knowledge value with each node in the logical parse hierarchical representation; propagate the at least one knowledge value of at least a subset of the nodes in the logical parse hierarchical representation to one or more other nodes in the logical parse hierarchical representation based on propagation rules; and perform a reasoning operation on the logical parse hierarchical representation to generate a knowledge output indicative of knowledge associated with one or more of the logical relationships between elements of the natural language content.
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11. A computer program product comprising a non-transitory computer readable medium having a computer readable program stored therein, wherein the computer readable program, when executed in a data processing system, configures the data processing system to implement a natural language processing system that performs natural language processing on natural language content at least by processing logical relationships in the natural language content, wherein the natural language processing system operates to: generate a logical parse hierarchical representation of a first parse of a natural language content by identifying latent logical operators within the first parse indicative of logical relationships between elements of the natural language content, wherein the logical parse hierarchical representation comprises nodes and edges linking nodes; associate at least one knowledge value with each node in the logical parse hierarchical representation; propagate the at least one knowledge value of at least a subset of the nodes in the logical parse hierarchical representation to one or more other nodes in the logical parse hierarchical representation based on propagation rules; and perform a reasoning operation on the logical parse hierarchical representation to generate a knowledge output indicative of knowledge associated with one or more of the logical relationships between elements of the natural language content. 20. The computer program product of claim 11 , wherein the computer readable program further causes the computing device to propagate the at least one knowledge value of at least a subset of the nodes in the logical parse hierarchical representation to one or more other nodes in the logical parse hierarchical representation based on propagation rules at least by applying different propagation rules for different logical operator nodes in the logical parse hierarchical representation to propagate the at least one knowledge value upwards, downwards, and sideways in the hierarchical representation.
| 0.714962 |
9,691,031 | 12 | 14 |
12. The method of claim 1 further comprising utilizing a plurality of fact checking implementations initially, wherein each fact checking implementation utilizes a different set of source information, and comparing results of each fact checking implementation, and iteratively eliminating a fact checking implementation of the plurality of fact checking implementations with a lowest confidence score until a single fact checking implementation remains.
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12. The method of claim 1 further comprising utilizing a plurality of fact checking implementations initially, wherein each fact checking implementation utilizes a different set of source information, and comparing results of each fact checking implementation, and iteratively eliminating a fact checking implementation of the plurality of fact checking implementations with a lowest confidence score until a single fact checking implementation remains. 14. The method of claim 12 wherein the single fact checking implementation determined by eliminating other fact checking implementations is utilized for a specific type of content and is reused for future content that is the same type of content as the specific type of content.
| 0.5 |
9,418,060 | 19 | 22 |
19. One or more non-transitory computer-readable storage media storing computer-readable instructions that, when executed, instruct one or more processors to perform operations comprising: sending a portion of a work to a translator having an experience level for translating into a language that is less than a predetermined experience level; receiving a translation of the portion of the work from the translator; sending the translation to an electronic book (eBook) reader device; receiving consumption statistics from the eBook reader device regarding the translation, the consumption statistics comprising one or more of a reading rate, a reading duration, or a stopping point for reading; causing a survey to be displayed on the eBook reader device, the survey associated with the translation; receiving a completed survey from the eBook reader device; and causing the translator to be evaluated based at least in part on the consumption statistics and the completed survey.
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19. One or more non-transitory computer-readable storage media storing computer-readable instructions that, when executed, instruct one or more processors to perform operations comprising: sending a portion of a work to a translator having an experience level for translating into a language that is less than a predetermined experience level; receiving a translation of the portion of the work from the translator; sending the translation to an electronic book (eBook) reader device; receiving consumption statistics from the eBook reader device regarding the translation, the consumption statistics comprising one or more of a reading rate, a reading duration, or a stopping point for reading; causing a survey to be displayed on the eBook reader device, the survey associated with the translation; receiving a completed survey from the eBook reader device; and causing the translator to be evaluated based at least in part on the consumption statistics and the completed survey. 22. The one or more non-transitory computer-readable storage media of claim 19 , wherein: the causing the translator to be evaluated results in creation of an evaluation for the translator, the evaluation indicating that the translation of the portion of the work satisfies one or more criteria, and the operations further comprise: causing an additional portion of the work to be translated by the translator based at least in part on the evaluation of the translator.
| 0.5 |
9,659,097 | 9 | 14 |
9. 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: receiving, at a computer system, a request to classify a first query; obtaining, by the computer system, session data for the first query, wherein: the session data for the first query identifies a plurality of sessions in which the first query occurs, each session of the plurality of sessions includes (i) one or more queries submitted in succession by a single respective user for the session and (ii) one or more search entities returned in response to executing the one or more queries, and each search entity is assigned one or more classifications; selecting, by the computer system from the session data for the first query, a first plurality of search entities, wherein the first plurality of search entities are the search entities that frequently occur in the plurality of query sessions in response to executing the first query; identifying, by the computer system, one or more potential classifications for the first query; for each potential classification of the one or more potential classifications, determining a first measure of how many of the first plurality of search entities have been assigned the potential classification; determining that the first measure have been assigned the classification satisfies a classification threshold; and in response to determining that the first measure have been assigned the classification satisfies the classification threshold, assigning the potential classification to the first query, determining that a second query occurs in the same first session with the first query; and assigning the potential classification to the second query.
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9. 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: receiving, at a computer system, a request to classify a first query; obtaining, by the computer system, session data for the first query, wherein: the session data for the first query identifies a plurality of sessions in which the first query occurs, each session of the plurality of sessions includes (i) one or more queries submitted in succession by a single respective user for the session and (ii) one or more search entities returned in response to executing the one or more queries, and each search entity is assigned one or more classifications; selecting, by the computer system from the session data for the first query, a first plurality of search entities, wherein the first plurality of search entities are the search entities that frequently occur in the plurality of query sessions in response to executing the first query; identifying, by the computer system, one or more potential classifications for the first query; for each potential classification of the one or more potential classifications, determining a first measure of how many of the first plurality of search entities have been assigned the potential classification; determining that the first measure have been assigned the classification satisfies a classification threshold; and in response to determining that the first measure have been assigned the classification satisfies the classification threshold, assigning the potential classification to the first query, determining that a second query occurs in the same first session with the first query; and assigning the potential classification to the second query. 14. The system of claim 9 , wherein the queries in the plurality of query sessions comprise one or more refinements to the first query, and assigning the potential classification to a second query that occurs in the same first session with the first query comprises assigning the potential classification to the one or more refinements to the first query.
| 0.52027 |
8,578,266 | 3 | 20 |
3. The method of claim 1 , comprising providing a command language set allowing selection, viewing and other processing of the one or more portions of the first markup language file, the command language set comprising a plurality of commands for selection.
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3. The method of claim 1 , comprising providing a command language set allowing selection, viewing and other processing of the one or more portions of the first markup language file, the command language set comprising a plurality of commands for selection. 20. The method of claim 3 , wherein said command language set comprises a command for setting a file value.
| 0.784274 |
7,917,924 | 1 | 4 |
1. A computer implemented method for tracking commercials that are provided to an audience by a content provider, wherein all steps are performed by the computer, the computer comprising a processor, a memory device and control logic stored therein, said method comprising: presenting a plurality of advertisement campaigns to a user through a computer interface, each advertising campaign comprising a plurality of fillable video segment slots, each fillable segment slot arranged at a specific time point within said advertisement campaign, in response to receiving a campaign selection input, presenting the user with a first set of semantic criteria associated with the selected advertisement campaign, the first set of criteria comprising a plurality of criterions; receiving a first criterion selection from the user; populating a second criterion of first set of criteria automatically based upon the selection of the first criterion; accessing a library of media segments stored in the memory device, each of the media segments comprising a portion of an advertisement, each media segment associated with metadata defining the media segment; transmitting the first and second criterion selections to an assembly component; searching the memory device for media segments having metadata correlating with the first and second criterion selections; retrieving at least one correlating media segment from the memory device; inserting the correlating media segment into one of the fillable media slots into the advertisement campaign, thereby generating a completed commercial; and presenting a preview of the completed commercial on a display to the user.
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1. A computer implemented method for tracking commercials that are provided to an audience by a content provider, wherein all steps are performed by the computer, the computer comprising a processor, a memory device and control logic stored therein, said method comprising: presenting a plurality of advertisement campaigns to a user through a computer interface, each advertising campaign comprising a plurality of fillable video segment slots, each fillable segment slot arranged at a specific time point within said advertisement campaign, in response to receiving a campaign selection input, presenting the user with a first set of semantic criteria associated with the selected advertisement campaign, the first set of criteria comprising a plurality of criterions; receiving a first criterion selection from the user; populating a second criterion of first set of criteria automatically based upon the selection of the first criterion; accessing a library of media segments stored in the memory device, each of the media segments comprising a portion of an advertisement, each media segment associated with metadata defining the media segment; transmitting the first and second criterion selections to an assembly component; searching the memory device for media segments having metadata correlating with the first and second criterion selections; retrieving at least one correlating media segment from the memory device; inserting the correlating media segment into one of the fillable media slots into the advertisement campaign, thereby generating a completed commercial; and presenting a preview of the completed commercial on a display to the user. 4. The method of claim 1 , further comprising transmitting a first version of the completed commercial to a first delivery point and a second version of the media content to a second delivery point, wherein the first version and the second version of the completed commercial comprise at least one different media segment.
| 0.5 |
9,715,657 | 5 | 9 |
5. A medical diagnosis support apparatus comprising: at least one processor; and at least one memory, said processor and memory being operatively coupled to function as: a training data obtainment unit configured to obtain training data; a candidate creating unit configured to create a plurality of inference means candidates based on the training data; an inference performance evaluation unit configured to evaluate an accuracy or likelihood of the plurality of inference means candidates based on an inference result and correct diagnosis included in the training data; an information validity evaluation unit configured to evaluate the validity of information presented by each of the plurality of inference means candidates based on reason information and correct reason information included in the training data; and a selection unit configured to select an inference means from the plurality of inference means candidates based on (1) the accuracy or likelihood of the plurality of inference means candidates and (2) the validity of the information presented by each of the plurality of inference means candidates.
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5. A medical diagnosis support apparatus comprising: at least one processor; and at least one memory, said processor and memory being operatively coupled to function as: a training data obtainment unit configured to obtain training data; a candidate creating unit configured to create a plurality of inference means candidates based on the training data; an inference performance evaluation unit configured to evaluate an accuracy or likelihood of the plurality of inference means candidates based on an inference result and correct diagnosis included in the training data; an information validity evaluation unit configured to evaluate the validity of information presented by each of the plurality of inference means candidates based on reason information and correct reason information included in the training data; and a selection unit configured to select an inference means from the plurality of inference means candidates based on (1) the accuracy or likelihood of the plurality of inference means candidates and (2) the validity of the information presented by each of the plurality of inference means candidates. 9. The medical diagnosis support apparatus according to claim 5 , wherein the candidate creating unit is operable to create the plurality of inference means candidates through processing using a genetic algorithm, and the selection unit is operable to select the inference means from the plurality of inference means candidates through the processing.
| 0.708955 |
7,921,357 | 12 | 13 |
12. A method as recited in claim 11 , wherein said first emphasis element comprises a first color used to highlight said selected portions selected by said first user.
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12. A method as recited in claim 11 , wherein said first emphasis element comprises a first color used to highlight said selected portions selected by said first user. 13. A method as recited in claim 12 , further comprising providing a means for said first user to annotate said selections of material by adding additional text explaining said first user's motive for making said selection.
| 0.5 |
8,068,092 | 13 | 15 |
13. The handheld electronic device of claim 12 wherein the plurality of objects further include a plurality of frequency objects each having a frequency value, at least some of the word objects each being associated with an associated frequency object, and wherein the operations further comprise outputting the first character permutations in descending order of frequency value.
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13. The handheld electronic device of claim 12 wherein the plurality of objects further include a plurality of frequency objects each having a frequency value, at least some of the word objects each being associated with an associated frequency object, and wherein the operations further comprise outputting the first character permutations in descending order of frequency value. 15. The handheld electronic device of claim 13 wherein the ambiguous input comprises a number of initial actuations and a current actuation, and wherein the operations further comprise: responsive to the number of initial actuations, identifying at least one word object that corresponds with a particular character permutation of the number of initial actuations; and outputting as one of the second character permutations the particular character permutation plus a character assigned to the input member of the current actuation.
| 0.687059 |
7,949,517 | 15 | 21 |
15. A digital device for classifying at least two languages in an automatic dialogue system which processes digitized speech, comprising a digital processing arrangement including a speech recognizer and a language identification system, the digital processing arrangement being configured to recognize a language of the digitized speech input through logical evaluation of results of a speech recognition method carried out by the speech recognizer and a language identification method applied, by the language identification system, to the speech input, wherein the digital processing arrangement is configured such that, if the speech recognition method is unable to recognize the speech input, the language identification method is used to classify the speech input and, if the classification was successful, at least one of the speech recognition method and a parameter of the speech recognition method is changed so that the speech recognition is carried out with the changed speech recognition method.
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15. A digital device for classifying at least two languages in an automatic dialogue system which processes digitized speech, comprising a digital processing arrangement including a speech recognizer and a language identification system, the digital processing arrangement being configured to recognize a language of the digitized speech input through logical evaluation of results of a speech recognition method carried out by the speech recognizer and a language identification method applied, by the language identification system, to the speech input, wherein the digital processing arrangement is configured such that, if the speech recognition method is unable to recognize the speech input, the language identification method is used to classify the speech input and, if the classification was successful, at least one of the speech recognition method and a parameter of the speech recognition method is changed so that the speech recognition is carried out with the changed speech recognition method. 21. The device according to claim 15 , wherein the digital processing arrangement is configured such that a result of the evaluation logic affects subsequent dialogue with a user.
| 0.714058 |
7,647,415 | 11 | 20 |
11. A system, comprising: a processor; and a memory comprising program instructions, wherein the program instructions are executable by the processor to implement a Web services stack configured to: communicate with another Web services stack on another system according to a markup language protocol, wherein the markup language protocol is based on XML (eXtensible Markup Language); and dynamically switch to communicate with the other Web services stack according to the binary encoding protocol, wherein communication according to the binary encoding protocol comprises mapping from an XML schema to a binary encoding schema and generating a binary encoding from the binary encoding schema; wherein the Web services stack supports the markup language protocol and the binary encoding protocol with a single API (application programming interface).
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11. A system, comprising: a processor; and a memory comprising program instructions, wherein the program instructions are executable by the processor to implement a Web services stack configured to: communicate with another Web services stack on another system according to a markup language protocol, wherein the markup language protocol is based on XML (eXtensible Markup Language); and dynamically switch to communicate with the other Web services stack according to the binary encoding protocol, wherein communication according to the binary encoding protocol comprises mapping from an XML schema to a binary encoding schema and generating a binary encoding from the binary encoding schema; wherein the Web services stack supports the markup language protocol and the binary encoding protocol with a single API (application programming interface). 20. The system as recited in claim 11 , wherein, to communicate with the other Web services stack according to the binary encoding protocol, the Web services stack is further configured to serialize the markup language protocol to generate binary encoding protocol messages according to a schema-optimized binary format for transmitting data described by markup language schema.
| 0.569476 |
8,538,957 | 9 | 16 |
9. A non-transitory computer storage medium storing a program, the program comprising instructions that, when executed by a data processing apparatus, cause the data processing apparatus to perform operations comprising: receiving a plurality of candidate translations for a phrase, wherein the phrase is in a first language and each candidate translation is a translation of the phrase into a different language from the first language; obtaining a first group of visual media search results, wherein the first group of visual media search results are responsive to a first visual media search query with text corresponding to the phrase; obtaining a respective second group of visual media search results for each of the candidate translations, wherein the second group of visual media search results are responsive to a second visual media search query with text corresponding to the candidate translation; generating a respective quality of results statistic for each of the candidate translations, wherein the quality of results statistic for each of the candidate translations is a value that represents a quality of search results that are responsive to the second visual media search query with text corresponding to the candidate translation; calculating a respective similarity score for each of the candidate translations, wherein the similarity score is an estimate of visual similarity between the first group of visual media search results and the second group of visual media search results for the candidate translation; selecting one or more of the candidate translations based on, for each candidate translation, the similarity score for the candidate translation and the quality of results statistic for the candidate translation; and associating each of the one or more selected candidate translations with the phrase as a valid translation for the phrase.
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9. A non-transitory computer storage medium storing a program, the program comprising instructions that, when executed by a data processing apparatus, cause the data processing apparatus to perform operations comprising: receiving a plurality of candidate translations for a phrase, wherein the phrase is in a first language and each candidate translation is a translation of the phrase into a different language from the first language; obtaining a first group of visual media search results, wherein the first group of visual media search results are responsive to a first visual media search query with text corresponding to the phrase; obtaining a respective second group of visual media search results for each of the candidate translations, wherein the second group of visual media search results are responsive to a second visual media search query with text corresponding to the candidate translation; generating a respective quality of results statistic for each of the candidate translations, wherein the quality of results statistic for each of the candidate translations is a value that represents a quality of search results that are responsive to the second visual media search query with text corresponding to the candidate translation; calculating a respective similarity score for each of the candidate translations, wherein the similarity score is an estimate of visual similarity between the first group of visual media search results and the second group of visual media search results for the candidate translation; selecting one or more of the candidate translations based on, for each candidate translation, the similarity score for the candidate translation and the quality of results statistic for the candidate translation; and associating each of the one or more selected candidate translations with the phrase as a valid translation for the phrase. 16. The non-transitory computer storage medium of claim 9 , wherein selecting one or more of the candidate translations comprises selecting only candidate translations having a similarity score that satisfies a first threshold value and a quality of results statistic that satisfies a second threshold value.
| 0.772189 |
6,047,992 | 1 | 2 |
1. A system for distinguishing between a shampoo container and a hair conditioner container, said system comprising: first and second raised letters, said first raised letter being configured to resemble the letter S, said second raised letter being configured to resemble the letter C; said first raised letter being adapted for attachment to a shampoo container, said second raised letter being adapted for attachment to a hair conditioner container; said first letter having an outwardly facing surface when said first letter is coupled to the shampoo container, an entirety of said outwardly facing surface of said first letter being smooth to the touch of a user; and said second letter having an outwardly facing surface when said second letter is coupled to the hair conditioner container, an entirety of said outwardly facing surface of said second letter being rough to the touch of the user whereby said outwardly facing surface of said first letter is tactilely distinguishable from said outwardly facing surface of said second letter.
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1. A system for distinguishing between a shampoo container and a hair conditioner container, said system comprising: first and second raised letters, said first raised letter being configured to resemble the letter S, said second raised letter being configured to resemble the letter C; said first raised letter being adapted for attachment to a shampoo container, said second raised letter being adapted for attachment to a hair conditioner container; said first letter having an outwardly facing surface when said first letter is coupled to the shampoo container, an entirety of said outwardly facing surface of said first letter being smooth to the touch of a user; and said second letter having an outwardly facing surface when said second letter is coupled to the hair conditioner container, an entirety of said outwardly facing surface of said second letter being rough to the touch of the user whereby said outwardly facing surface of said first letter is tactilely distinguishable from said outwardly facing surface of said second letter. 2. The system of claim 1, wherein said first and second raised letters each have spaced apart front and back faces, each of said first and second raised letters further having a perimeter side extending between the front and back faces.
| 0.5 |
9,406,089 | 1 | 30 |
1. A computer-implemented method for populating an electronic tax return, the computer-implemented method being executed by a mobile communication device comprising a data store comprising a tax return preparation application operable to prepare an electronic tax return, a first camera that is a front facing camera, a second camera that is a rear facing camera, a microphone and a video/voice processor, each of the data store, the first camera, the second camera and the microphone being in communication with the video/voice processor, the method comprising: the mobile communication device, by the first camera, recording a video of a tax document, the recorded video comprising a plurality of video frames and voice data generated based on a user of the mobile communication device speaking into the microphone during recording of the video, the voice data comprising a user-spoken description of how the tax document is relevant to the electronic tax return; converting, by the video/voice processor of the mobile communication device, the voice data from a voice format into a text format; analyzing, by the video/voice processor, at least one video frame of the video and the voice data in the text format to determine a document type and tax data contained within the at least one video frame; identifying, by the tax return preparation application executed by a processor of the mobile communication device, a field of the electronic tax return to be populated with determined tax data of the determined document type; populating, by the tax return preparation application, the field of the electronic tax return with the determined tax data to prepare at least a portion of the electronic tax return without the user typing tax data of the tax document that was captured in the video into the field of the electronic tax return; detecting, by the second camera, a facial expression or gesture of the user during preparation of the electronic tax return; determining, by the video/voice processor, a first response based at least in part on the detected facial expression or gesture; and presenting, by the tax return preparation application, the first response to the user during preparation of the electronic tax return.
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1. A computer-implemented method for populating an electronic tax return, the computer-implemented method being executed by a mobile communication device comprising a data store comprising a tax return preparation application operable to prepare an electronic tax return, a first camera that is a front facing camera, a second camera that is a rear facing camera, a microphone and a video/voice processor, each of the data store, the first camera, the second camera and the microphone being in communication with the video/voice processor, the method comprising: the mobile communication device, by the first camera, recording a video of a tax document, the recorded video comprising a plurality of video frames and voice data generated based on a user of the mobile communication device speaking into the microphone during recording of the video, the voice data comprising a user-spoken description of how the tax document is relevant to the electronic tax return; converting, by the video/voice processor of the mobile communication device, the voice data from a voice format into a text format; analyzing, by the video/voice processor, at least one video frame of the video and the voice data in the text format to determine a document type and tax data contained within the at least one video frame; identifying, by the tax return preparation application executed by a processor of the mobile communication device, a field of the electronic tax return to be populated with determined tax data of the determined document type; populating, by the tax return preparation application, the field of the electronic tax return with the determined tax data to prepare at least a portion of the electronic tax return without the user typing tax data of the tax document that was captured in the video into the field of the electronic tax return; detecting, by the second camera, a facial expression or gesture of the user during preparation of the electronic tax return; determining, by the video/voice processor, a first response based at least in part on the detected facial expression or gesture; and presenting, by the tax return preparation application, the first response to the user during preparation of the electronic tax return. 30. The computer-implemented method of claim 1 , further comprising the mobile communication device, by the tax return preparation application, transmitting a completed electronic tax return through a network to a computer of a tax authority to electronically file the completed electronic tax return with the tax authority.
| 0.748837 |
8,024,320 | 19 | 22 |
19. The apparatus of claim 17 , wherein the operations comprise: accumulating query fragments associated with the rule scope; accumulating query fragments associated with the desired state; and merging the accumulated query fragments into a query for applying the rule to data corresponding to the network, wherein at least one query fragment, the query, or both the query and the at least one query fragment, includes the path expression for one of the identified paths.
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19. The apparatus of claim 17 , wherein the operations comprise: accumulating query fragments associated with the rule scope; accumulating query fragments associated with the desired state; and merging the accumulated query fragments into a query for applying the rule to data corresponding to the network, wherein at least one query fragment, the query, or both the query and the at least one query fragment, includes the path expression for one of the identified paths. 22. The apparatus of claim 19 , wherein the operations comprise: executing the query to apply the rule to data corresponding to the IT infrastructure to determine compliance of the network.
| 0.729226 |
8,909,810 | 74 | 75 |
74. The method of claim 60 , comprising the step of E. providing one or more items of content to the shared content server from one or more of the nodes.
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74. The method of claim 60 , comprising the step of E. providing one or more items of content to the shared content server from one or more of the nodes. 75. The method of claim 74 , wherein step (E) includes (i) acquiring an item of multimedia content from any of a camera, web site, networked computer, hard drive memory stick, DVD, CD or other device or system coupled to one of the nodes and transmitting that item of content to the shared content server, and (ii) transmitting that item of content to one or more of the nodes via step (B).
| 0.5 |
10,068,033 | 11 | 18 |
11. A device, applied to query of graph data in a graph data whole set, wherein the graph data whole set comprises multiple vertices and an edge between every two vertices that have a connection relationship; partitioning and layering are performed on the multiple vertices in the graph data whole set; a number of a partition in which a vertex is located is used as a partition number of the vertex; a shortest distance between a vertex and a partition border of a partition in which the vertex is located is used as a layer number of the vertex; the device comprising: a memory configured to store instructions; and a processor coupled to the memory and configured to execute the instructions to: acquire a query condition, and a partition number and a layer number of a query vertex indicated by the query condition; determine, based on the partition number and the layer number of the query vertex, a partition number and a layer number of a candidate vertex indicated by the query condition, and use the partition number and the layer number of the candidate vertex respectively as a candidate partition number and a candidate layer number, wherein the candidate vertex is a vertex that needs to be queried according to the query condition; form a candidate set using a vertex whose partition number and layer number satisfy any group of a candidate partition number and a candidate layer number; and perform graph data query in the candidate set according to the query condition.
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11. A device, applied to query of graph data in a graph data whole set, wherein the graph data whole set comprises multiple vertices and an edge between every two vertices that have a connection relationship; partitioning and layering are performed on the multiple vertices in the graph data whole set; a number of a partition in which a vertex is located is used as a partition number of the vertex; a shortest distance between a vertex and a partition border of a partition in which the vertex is located is used as a layer number of the vertex; the device comprising: a memory configured to store instructions; and a processor coupled to the memory and configured to execute the instructions to: acquire a query condition, and a partition number and a layer number of a query vertex indicated by the query condition; determine, based on the partition number and the layer number of the query vertex, a partition number and a layer number of a candidate vertex indicated by the query condition, and use the partition number and the layer number of the candidate vertex respectively as a candidate partition number and a candidate layer number, wherein the candidate vertex is a vertex that needs to be queried according to the query condition; form a candidate set using a vertex whose partition number and layer number satisfy any group of a candidate partition number and a candidate layer number; and perform graph data query in the candidate set according to the query condition. 18. The device according to claim 11 , when acquiring the query condition, and the partition number and the layer number of the query vertex indicated by the query condition, the processor is configured to execute the instructions to: acquire the query condition; and when the query condition indicates that a shortest path between a first query vertex and a second query vertex needs to be queried, acquire a partition number and a layer number of the first query vertex and a partition number and a layer number of the second query vertex; and if the first query vertex and the second query vertex are located in a same partition, when determining the partition number and the layer number of the candidate vertex indicated by the query condition, the processor is configured to execute the instructions to: determine that the partition number of the candidate vertex is the partition number of the first query vertex and the second query vertex; and determine a layer number within a closed interval from the layer number of the first query vertex to the layer number of the second query vertex as the layer number of the candidate vertex; if the first query vertex and the second query vertex are located in different partitions, when determining the partition number and a layer number of a candidate vertex indicated by the query condition, the processor is configured to execute the instructions to: determine that the partition number of the candidate vertex is the partition number of the first query vertex and the partition number of the second query vertex; for a partition in which the first query vertex is located, determine a layer number within a closed interval from zero to the layer number of the first query vertex as the layer number that is of the candidate vertex and that belongs to a same group as the partition number of the first query vertex; and for a partition in which the second query vertex is located, determine a layer number within a closed interval from zero to the layer number of the second query vertex as the layer number that is of the candidate vertex and that belongs to a same group as the partition number of the second query vertex.
| 0.5 |
9,405,773 | 15 | 26 |
15. A computer-readable hardware storage device having embedded therein a set of instructions which, when executed by one or more processors of a computer, causes the computer to execute operations comprising: receiving a query comprising a query image that is sent via a user interface at a client machine operating over a wireless communication channel; responsive to receiving the query image, searching a database and obtaining from the database a set of images that are similar to the query image, the searching a database and obtaining a set of images that are similar to the query image comprising a two-pass search, a first pass resulting in a plurality of images that are similar to the query image and ranking the plurality of images that are similar to the query image to form a similarity score, and a second pass comprising ranking fewer than all of the resulting plurality of images from the first pass against pre-computed digests of image-based listings comprising textual information, wherein the ranking of fewer than all of the resulting plurality of images is performed using a best match procedure that comprises weighting the resulting plurality of images by color similarity, by edge similarity, and by the similarity score; providing, over the wireless communication channel, for display at the user interface at the client machine, results of the searching, the results comprising image members of the obtained set of images that are similar to the query image; detecting a request via the user interface at the client machine for a similarity search for more images similar to one of the image members of the set of images displayed at the user interface at the client machine; responsive to detecting the request via the user interface at the client machine for the similarity searching for more images similar to one of the image members of the set of images displayed at the user interface at the client machine, searching the database and obtaining from the database more images similar to the one of the image members of the set of images; and responsive to the searching the database and obtaining from the database more images similar to the one of the image members of the set of images, providing, over the wireless communication channel for display at the user interface at the client machine, at least some of the obtained more images similar to the one of the image members of the set of images.
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15. A computer-readable hardware storage device having embedded therein a set of instructions which, when executed by one or more processors of a computer, causes the computer to execute operations comprising: receiving a query comprising a query image that is sent via a user interface at a client machine operating over a wireless communication channel; responsive to receiving the query image, searching a database and obtaining from the database a set of images that are similar to the query image, the searching a database and obtaining a set of images that are similar to the query image comprising a two-pass search, a first pass resulting in a plurality of images that are similar to the query image and ranking the plurality of images that are similar to the query image to form a similarity score, and a second pass comprising ranking fewer than all of the resulting plurality of images from the first pass against pre-computed digests of image-based listings comprising textual information, wherein the ranking of fewer than all of the resulting plurality of images is performed using a best match procedure that comprises weighting the resulting plurality of images by color similarity, by edge similarity, and by the similarity score; providing, over the wireless communication channel, for display at the user interface at the client machine, results of the searching, the results comprising image members of the obtained set of images that are similar to the query image; detecting a request via the user interface at the client machine for a similarity search for more images similar to one of the image members of the set of images displayed at the user interface at the client machine; responsive to detecting the request via the user interface at the client machine for the similarity searching for more images similar to one of the image members of the set of images displayed at the user interface at the client machine, searching the database and obtaining from the database more images similar to the one of the image members of the set of images; and responsive to the searching the database and obtaining from the database more images similar to the one of the image members of the set of images, providing, over the wireless communication channel for display at the user interface at the client machine, at least some of the obtained more images similar to the one of the image members of the set of images. 26. The computer-readable hardware storage device of claim 15 wherein the first pass is made using a TF-IDF algorithm.
| 0.856098 |
4,600,320 | 3 | 4 |
3. A printer as claimed in claim 2 wherein said platen is secured to an axial rod, a left platen knob and a right platen knob, the left platen knob is held in place by bolt means to contrain its movement and wherein roller means are provided on the inside of the platen adjacent said left platen knob to facilitate the turning movement of the platen.
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3. A printer as claimed in claim 2 wherein said platen is secured to an axial rod, a left platen knob and a right platen knob, the left platen knob is held in place by bolt means to contrain its movement and wherein roller means are provided on the inside of the platen adjacent said left platen knob to facilitate the turning movement of the platen. 4. A printer as claimed in claim 3 wherein the left end of the axial rod adjacent said left platen knob is provided with a screw means.
| 0.5 |
7,784,036 | 1 | 5 |
1. A method comprising: extracting, with a processing system, macroinstructions that are hard-coded into parser code of a command line interface (CLI) parser, wherein the macroinstructions define parse nodes utilized by the CLI parser to analyze whether one or more CLI commands input to a CLI prompt have a proper CLI syntax; generating a parse graph from the macroinstructions with the processing system, wherein the parse graph includes a representation of the parse nodes defined by the macroinstructions; hiding selected information within the parse nodes to create condensed parse nodes with the processing system, wherein the hiding prevents further processing of the selected information; simplifying selected complex patterns in the parse graph to create simplified parse graph patterns with the processing system; creating, with the processing system, branches on an AND/OR command tree from the parse nodes, the condensed parse nodes, and the simplified parse graph patterns; and creating an exportable representation of the AND/OR command tree with the processing system.
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1. A method comprising: extracting, with a processing system, macroinstructions that are hard-coded into parser code of a command line interface (CLI) parser, wherein the macroinstructions define parse nodes utilized by the CLI parser to analyze whether one or more CLI commands input to a CLI prompt have a proper CLI syntax; generating a parse graph from the macroinstructions with the processing system, wherein the parse graph includes a representation of the parse nodes defined by the macroinstructions; hiding selected information within the parse nodes to create condensed parse nodes with the processing system, wherein the hiding prevents further processing of the selected information; simplifying selected complex patterns in the parse graph to create simplified parse graph patterns with the processing system; creating, with the processing system, branches on an AND/OR command tree from the parse nodes, the condensed parse nodes, and the simplified parse graph patterns; and creating an exportable representation of the AND/OR command tree with the processing system. 5. The method of claim 1 , further comprising collecting the parse nodes that terminate in a common end of line.
| 0.681818 |
7,497,778 | 1 | 21 |
1. A method of conducting a word based lottery game having a plurality of players, comprising the steps of: for each game, the players wagering on an entry defined by a set of words; in a random draw process, randomly generating an outcome that is a concatenation of characters, the draw being such that each outcome can be assigned a probability of occurrence; defining a rule that confers the words in the player entry a win status based on the outcome of the draw producing characters that are used to form the respective words in the player entry; selecting winning entries based on the words in an entry that are conferred a win status; and assigning a prize for each winning entry as a function of a value assigned to each of the words in the player entry formed by the randomly drawn characters, the value based on the commonality of the characters that form the words in the player entry.
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1. A method of conducting a word based lottery game having a plurality of players, comprising the steps of: for each game, the players wagering on an entry defined by a set of words; in a random draw process, randomly generating an outcome that is a concatenation of characters, the draw being such that each outcome can be assigned a probability of occurrence; defining a rule that confers the words in the player entry a win status based on the outcome of the draw producing characters that are used to form the respective words in the player entry; selecting winning entries based on the words in an entry that are conferred a win status; and assigning a prize for each winning entry as a function of a value assigned to each of the words in the player entry formed by the randomly drawn characters, the value based on the commonality of the characters that form the words in the player entry. 21. The method of claim 1 , further comprising the step of memorializing each entry on a game card.
| 0.782895 |
7,987,180 | 7 | 8 |
7. The system of claim 6 , wherein the instructions for constructing a histogram include: instructions for counting each value in the document; instructions for outputting a collection of value-count pairs sorted by said counting; and instructions for partitioning the collection of sorted value-count pairs into said buckets.
|
7. The system of claim 6 , wherein the instructions for constructing a histogram include: instructions for counting each value in the document; instructions for outputting a collection of value-count pairs sorted by said counting; and instructions for partitioning the collection of sorted value-count pairs into said buckets. 8. The system of claim 7 wherein the instructions are such that the synopsis of each bucket includes data reflecting occurrence counts of q-grams of the values that are associated with the bucket.
| 0.5 |
7,814,125 | 12 | 16 |
12. A method in a data processing system for presenting a response based upon an application of business logic in accordance with a request, where the data processing system comprises a modified model-view-controller architecture that includes a user interface controller, a user interface builder implementing a first interface, an application layer implementing a second interface, a data access manager implementing a third interface, and at least one data access utility implementing a fourth interface, wherein the interface controller interacts with the user interface builder via the first interface, the user interface builder interacts with the application layer via the second interface, the application layer interacts with the data access manager via the third interface, the method comprising: initializing, by the data processing system, a page token in response to receiving a request, the page token comprising an abstract model component containing a specification for obtaining data designated to be sent in a response to the request or a specification for updating data obtained from the request, and a view component for providing referential format specifications for the data provided in the abstract model component, wherein the response comprises an entire web page including a current panel; passing, by the data processing system, the page token between at least two components of the modified model-view-controller architecture via an interface; applying, by the application layer, business logic to contents of the page token as a result of the passing; and presenting, by the data processing system, a response to the request based upon results of the applying business logic; wherein the data access manager sends at least a portion of the page token, including the specification, to the at least one data access utility via the fourth interface for use by the at least one data access utility in accessing data in a data store.
|
12. A method in a data processing system for presenting a response based upon an application of business logic in accordance with a request, where the data processing system comprises a modified model-view-controller architecture that includes a user interface controller, a user interface builder implementing a first interface, an application layer implementing a second interface, a data access manager implementing a third interface, and at least one data access utility implementing a fourth interface, wherein the interface controller interacts with the user interface builder via the first interface, the user interface builder interacts with the application layer via the second interface, the application layer interacts with the data access manager via the third interface, the method comprising: initializing, by the data processing system, a page token in response to receiving a request, the page token comprising an abstract model component containing a specification for obtaining data designated to be sent in a response to the request or a specification for updating data obtained from the request, and a view component for providing referential format specifications for the data provided in the abstract model component, wherein the response comprises an entire web page including a current panel; passing, by the data processing system, the page token between at least two components of the modified model-view-controller architecture via an interface; applying, by the application layer, business logic to contents of the page token as a result of the passing; and presenting, by the data processing system, a response to the request based upon results of the applying business logic; wherein the data access manager sends at least a portion of the page token, including the specification, to the at least one data access utility via the fourth interface for use by the at least one data access utility in accessing data in a data store. 16. The method of claim 12 , further comprising managing panel flow via the user interface controller, wherein the panel flow is managed using specification information in the page token and machine status information tracked by the user interface controller.
| 0.688702 |
9,946,750 | 18 | 19 |
18. A computer-implemented system for generating statistics for a database system, the system comprising: a computer processor; and a computer-readable storage medium storing instructions thereon, the instructions for execution by a computer processor to cause the computer processor to perform: receiving, by a query compiler, from a client device, a plurality of database queries by a database system, the database queries processing data stored in database tables of the database system; identifying, by the query compiler, missing statistics while generating execution plans for database queries, the identifying comprising, for each of the plurality of database queries: requesting a statistical information useful for generating an execution plan for a database query; determining that the requested statistical information is not available; and storing information describing the requested statistical information as missing statistics, responsive to determining that the requested statistical information is not available; ranking the identified missing statistics based on a number of times each missing statistics was identified as being not available during generation of execution plan; determining a subset of the identified missing statistics for use in generating execution plans for subsequent database queries, wherein determining the subset comprises selecting identified missing statistics based on the ranking; receiving, by the query compiler, the subsequent database queries; generating, by the query compiler, an execution plan for the one of the subsequent database queries using at least one of the identified missing statistics from the subset; executing, by an execution engine, the generated execution plan for the one of the subsequent queries to determine a result set; and sending the determined result set to the client device.
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18. A computer-implemented system for generating statistics for a database system, the system comprising: a computer processor; and a computer-readable storage medium storing instructions thereon, the instructions for execution by a computer processor to cause the computer processor to perform: receiving, by a query compiler, from a client device, a plurality of database queries by a database system, the database queries processing data stored in database tables of the database system; identifying, by the query compiler, missing statistics while generating execution plans for database queries, the identifying comprising, for each of the plurality of database queries: requesting a statistical information useful for generating an execution plan for a database query; determining that the requested statistical information is not available; and storing information describing the requested statistical information as missing statistics, responsive to determining that the requested statistical information is not available; ranking the identified missing statistics based on a number of times each missing statistics was identified as being not available during generation of execution plan; determining a subset of the identified missing statistics for use in generating execution plans for subsequent database queries, wherein determining the subset comprises selecting identified missing statistics based on the ranking; receiving, by the query compiler, the subsequent database queries; generating, by the query compiler, an execution plan for the one of the subsequent database queries using at least one of the identified missing statistics from the subset; executing, by an execution engine, the generated execution plan for the one of the subsequent queries to determine a result set; and sending the determined result set to the client device. 19. The computer-implemented system of claim 18 , wherein instructions for identifying the missing statistics for a database query comprise instructions for: determining that the database query processes a plurality of columns; and responsive to determining that the database query processes a plurality of columns, identifying the statistical information to be a multi-column NDV of the plurality of columns.
| 0.5 |
5,577,165 | 34 | 35 |
34. The method of claim 33, wherein the length of the speech response for making the confirmation is determined from information items to be confirmed by the confirmation.
|
34. The method of claim 33, wherein the length of the speech response for making the confirmation is determined from information items to be confirmed by the confirmation. 35. The method of claim 34, wherein the full speech responses mentions all of the information items to be confirmed while the simplified speech response does not directly mention the information items to be confirmed.
| 0.5 |
7,953,720 | 10 | 12 |
10. The method of claim 6 , further comprising: identifying a fifth answer of the possible answers that is unrelated to the third answer; and determining a supported score for the fifth answer.
|
10. The method of claim 6 , further comprising: identifying a fifth answer of the possible answers that is unrelated to the third answer; and determining a supported score for the fifth answer. 12. The method of claim 10 , wherein determining the supported score for the fifth answer includes: identifying answers of the possible answers that support the fifth answer; and determining the supported score for the fifth answer by mathematically combining the score of the fifth answer and the scores of the answers that support the fifth answer.
| 0.5 |
10,089,549 | 8 | 12 |
8. A computer implemented method for estimating ego-motion from video scenes, the method comprising an act of: causing one or more processers to execute instructions encoded on a non-transitory computer-readable medium, such that upon execution, the one or more processors perform operations of: for consecutive frames in a video captured by a moving camera, determining a first ego-translation estimate between the consecutive frames from a first local minimum (h 0 ,v 0 ); determining a second ego-translation estimate from a second local minimum (h′ 0 ,v′ 0 ); if the second ego-translation estimate does not equal the first ego-translation estimate, determining an optimal solution by minimizing a cost function until the first ego-translation estimate and the second ego-translation estimate are a matching estimate; estimating ego-motion of the camera using the optimal solution; and detecting independent moving objects in the video after compensating for ego-motion of the camera.
|
8. A computer implemented method for estimating ego-motion from video scenes, the method comprising an act of: causing one or more processers to execute instructions encoded on a non-transitory computer-readable medium, such that upon execution, the one or more processors perform operations of: for consecutive frames in a video captured by a moving camera, determining a first ego-translation estimate between the consecutive frames from a first local minimum (h 0 ,v 0 ); determining a second ego-translation estimate from a second local minimum (h′ 0 ,v′ 0 ); if the second ego-translation estimate does not equal the first ego-translation estimate, determining an optimal solution by minimizing a cost function until the first ego-translation estimate and the second ego-translation estimate are a matching estimate; estimating ego-motion of the camera using the optimal solution; and detecting independent moving objects in the video after compensating for ego-motion of the camera. 12. The method as set forth in claim 8 , wherein the cost function to be minimized is based en differences between initial pixel values in an initial frame and shifted pixel values in a consecutive frame.
| 0.888035 |
9,633,371 | 4 | 6 |
4. The method of claim 1 , further comprising: receiving a selection of at least one aggregate experience category to which the uploaded target audio reference belongs; and linking the selected aggregate experience category to the one or more bids to deliver one or more promotional content items.
|
4. The method of claim 1 , further comprising: receiving a selection of at least one aggregate experience category to which the uploaded target audio reference belongs; and linking the selected aggregate experience category to the one or more bids to deliver one or more promotional content items. 6. The method of claim 4 , wherein the selected aggregate experience category is multiple renditions by multiple artists of a selected song, further including identifying multiple renditions by multiple artists of the selected song and linking the selected song aggregate experience category to delivery of promotional content responsive to recognizing an audio query that matches any audio reference of the multiple renditions a particular song.
| 0.5 |
8,762,390 | 10 | 11 |
10. The system as recited in claim 9 , wherein the link analysis module is further configured to iteratively expand the maximum weighted subgraph by adding an image to the subgraph with a greatest weight that is connected to the subgraph.
|
10. The system as recited in claim 9 , wherein the link analysis module is further configured to iteratively expand the maximum weighted subgraph by adding an image to the subgraph with a greatest weight that is connected to the subgraph. 11. The system as recited in claim 10 , wherein the link analysis module is further configured to rank images according to an order they were added to the subgraph.
| 0.5 |
10,115,440 | 1 | 7 |
1. An apparatus comprising: a stack of word line layers comprising word lines for a three-dimensional non-volatile memory array, the stack of word line layers comprising a plurality of tiers; a plurality of word line switch transistors for transferring word line bias voltages to the word lines; a plurality of word line contact regions for coupling the word line switch transistors to the word lines, a word line contact region comprising a stepped structure for a tier of the word line layers, wherein a level region separates a word line contact region for a first tier from a word line contact region for a second tier; and a plurality of connectors coupling the word line switch transistors to the word lines, the connectors comprising vertical conductors, wherein connectors for a single word line contact region comprise vertical conductors disposed within the single word line contact region, at a first side of the single word line contact region, and at a second side of the single word line contact region.
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1. An apparatus comprising: a stack of word line layers comprising word lines for a three-dimensional non-volatile memory array, the stack of word line layers comprising a plurality of tiers; a plurality of word line switch transistors for transferring word line bias voltages to the word lines; a plurality of word line contact regions for coupling the word line switch transistors to the word lines, a word line contact region comprising a stepped structure for a tier of the word line layers, wherein a level region separates a word line contact region for a first tier from a word line contact region for a second tier; and a plurality of connectors coupling the word line switch transistors to the word lines, the connectors comprising vertical conductors, wherein connectors for a single word line contact region comprise vertical conductors disposed within the single word line contact region, at a first side of the single word line contact region, and at a second side of the single word line contact region. 7. The apparatus of claim 1 , wherein the word line contact region for the first tier and the word line contact region for the second tier are disposed at a first side of the array.
| 0.768542 |
9,015,284 | 10 | 11 |
10. A method comprising: communicating over a first interface with end-points operationally connected to the apparatus using a binary web service, the end-points comprising one or more resources; communicating with web applications making use of the resources over a second interface; forming a group comprising one or more end-points or other groups; creating a first abstract universal resource identifier (URI) for the group to be used over the second interface, the abstract URI comprising a domain name and a group identifier and being independent of the protocol used to access the resources of the end-points of the group; creating a second abstract universal resource identifier (URI) for the end-points to be used over the second interface, the abstract URI comprising an end-point and domain name and being independent of the protocol used to access the end-point; receiving over the second interface a look-up URI, the look-up URI comprising a tag identifying the look-up URI as a group look-up, the address of the apparatus, optional domain and group parameters; and resolving the look-up URI to one or more first or second abstract URIs.
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10. A method comprising: communicating over a first interface with end-points operationally connected to the apparatus using a binary web service, the end-points comprising one or more resources; communicating with web applications making use of the resources over a second interface; forming a group comprising one or more end-points or other groups; creating a first abstract universal resource identifier (URI) for the group to be used over the second interface, the abstract URI comprising a domain name and a group identifier and being independent of the protocol used to access the resources of the end-points of the group; creating a second abstract universal resource identifier (URI) for the end-points to be used over the second interface, the abstract URI comprising an end-point and domain name and being independent of the protocol used to access the end-point; receiving over the second interface a look-up URI, the look-up URI comprising a tag identifying the look-up URI as a group look-up, the address of the apparatus, optional domain and group parameters; and resolving the look-up URI to one or more first or second abstract URIs. 11. The method of claim 10 , further comprising: creating universal resource locators (URL) for resources of the end-points to be used over the first interface, the URLs comprising the protocol used to access the resource, the Internet Protocol address, port and path of the resource; and linking the URLs and the second abstract URIs together.
| 0.5 |
9,275,635 | 3 | 7 |
3. The method of claim 1 , comprising: selecting the multiple speech recognizers that are each trained on a different dialect or accent of a same language.
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3. The method of claim 1 , comprising: selecting the multiple speech recognizers that are each trained on a different dialect or accent of a same language. 7. The method of claim 3 , wherein selecting the multiple speech recognizers that are each trained on a different dialect or accent of a same language based on input from a user comprises: identifying a language associated with the utterance based on previously received audio data; providing, for display at a user interface, information indicating the identified language; receiving data indicating one or more selections corresponding to one or more dialects or accents of the identified language, wherein the selections are made from the user interface; and selecting multiple speech recognizers that are each trained on one of the selected dialects or accents of the identified language.
| 0.5 |
9,756,039 | 15 | 18 |
15. A computer program product comprising computer-readable program code capable of being executed by one or more processors when retrieved from a non-transitory computer-readable medium, the program code comprising instructions configurable to cause: processing a document request identifying markup language content; providing the markup language content to a rendering engine configured to: identify one or more resources in the markup language content, and communicate one or more resource requests for the one or more resources; processing the one or more resource requests as communicated by the rendering engine; retrieving the one or more resources; providing the one or more resources to the rendering engine, the rendering engine further configured to generate a platform-independent document based on the markup language content and the one or more resources; and communicating the platform-independent document to a computing device.
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15. A computer program product comprising computer-readable program code capable of being executed by one or more processors when retrieved from a non-transitory computer-readable medium, the program code comprising instructions configurable to cause: processing a document request identifying markup language content; providing the markup language content to a rendering engine configured to: identify one or more resources in the markup language content, and communicate one or more resource requests for the one or more resources; processing the one or more resource requests as communicated by the rendering engine; retrieving the one or more resources; providing the one or more resources to the rendering engine, the rendering engine further configured to generate a platform-independent document based on the markup language content and the one or more resources; and communicating the platform-independent document to a computing device. 18. The computer program product of claim 15 , the instructions further configurable to cause: generating a renderable web document comprising the markup language content; communicating the document request to a document-rendering service; and communicating the one or more resources to the document-rendering service.
| 0.5 |
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