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8,290,741 | 1 | 4 | 1. A method comprising: receiving a first sensor data set and a second sensor data set generated in response to sensing one or more structures, the sensor data sets describing a plurality of structural features of the structures; generating a plurality of first delta vector sets for the first sensor data set and a plurality of second delta vector sets for the second sensor data set, each delta vector set comprising one or more delta vectors for a structural feature, a delta vector indicating one or more relative geometrical relationships between the structural feature and one or more other structural features of the each sensor data set; and determining a plurality of association scores for a plurality of delta pairs, a delta pair comprising a first delta vector set and a second delta vector set; and identifying a plurality of same feature delta pairs according to the association scores, a same feature delta vector set comprising a delta pair corresponding to the same structural feature. | 1. A method comprising: receiving a first sensor data set and a second sensor data set generated in response to sensing one or more structures, the sensor data sets describing a plurality of structural features of the structures; generating a plurality of first delta vector sets for the first sensor data set and a plurality of second delta vector sets for the second sensor data set, each delta vector set comprising one or more delta vectors for a structural feature, a delta vector indicating one or more relative geometrical relationships between the structural feature and one or more other structural features of the each sensor data set; and determining a plurality of association scores for a plurality of delta pairs, a delta pair comprising a first delta vector set and a second delta vector set; and identifying a plurality of same feature delta pairs according to the association scores, a same feature delta vector set comprising a delta pair corresponding to the same structural feature. 4. The method of claim 1 , the determining the plurality of association scores further comprising performing the following for one or more iterations: identifying a plurality of candidate pairs for an iteration according to the association scores, a candidate pair indicating a mapping of a first feature to a second feature for the iteration; and rotating the first delta vector sets with respect to the second delta vector sets. | 0.719687 |
7,624,277 | 11 | 12 | 11. The method of claim 1 wherein altering the characters includes applying a displacement field to each of the characters to distort the characters. | 11. The method of claim 1 wherein altering the characters includes applying a displacement field to each of the characters to distort the characters. 12. The method of claim 11 wherein the displacement field is random. | 0.981153 |
8,209,688 | 9 | 13 | 9. The method enabling security and secured access to printable documents comprising the steps of: accessing a Web interface having a multi-tier enterprise development security application program interface, and a multi-tier enterprise development collaborative authoring program to create a secured enterprise print bean document, wherein said secured enterprise print bean document comprises a reusable software component that conforms to design and naming conventions that permit said secured enterprise print bean document to be combined to create an application; routing said secured enterprise print bean document to a multi-tier enterprise development application programming-enabled container wherein said secured enterprise print bean document is stored for subsequent access by an authorized customer; requesting access to said secured enterprise print bean document stored within said multi-tier enterprise development application programming-enabled container by a customer; receiving said request using a multi-tier enterprise development application programming-enabled container to access said secured enterprise print bean document and verifying authorization to access said secured enterprise print bean document; checking said secured enterprise print bean document upon said secured enterprise print bean document's receipt to verify that multi-tier enterprise development application program-type security is applied to said secured enterprise print bean document by said multi-tier enterprise development application programming-enabled container; accessing said secured enterprise print bean document from within said multi-tier enterprise development application programming-enabled container if an access controller authorizes access to said secured enterprise print bean document to said customer; and establishing print and access limitations such as printer feedback, memory of an actual print process, printing security options, document size limitations, a record of how many times a document is printed, and a limitation on number of printing, as part of authoring said enterprise print bean. | 9. The method enabling security and secured access to printable documents comprising the steps of: accessing a Web interface having a multi-tier enterprise development security application program interface, and a multi-tier enterprise development collaborative authoring program to create a secured enterprise print bean document, wherein said secured enterprise print bean document comprises a reusable software component that conforms to design and naming conventions that permit said secured enterprise print bean document to be combined to create an application; routing said secured enterprise print bean document to a multi-tier enterprise development application programming-enabled container wherein said secured enterprise print bean document is stored for subsequent access by an authorized customer; requesting access to said secured enterprise print bean document stored within said multi-tier enterprise development application programming-enabled container by a customer; receiving said request using a multi-tier enterprise development application programming-enabled container to access said secured enterprise print bean document and verifying authorization to access said secured enterprise print bean document; checking said secured enterprise print bean document upon said secured enterprise print bean document's receipt to verify that multi-tier enterprise development application program-type security is applied to said secured enterprise print bean document by said multi-tier enterprise development application programming-enabled container; accessing said secured enterprise print bean document from within said multi-tier enterprise development application programming-enabled container if an access controller authorizes access to said secured enterprise print bean document to said customer; and establishing print and access limitations such as printer feedback, memory of an actual print process, printing security options, document size limitations, a record of how many times a document is printed, and a limitation on number of printing, as part of authoring said enterprise print bean. 13. The method of claim 9 further comprising extending said secured enterprise print bean document's application programming interface to provide all multi-tier enterprise development application programming capabilities of said secured enterprise print bean document as applied to a print job. | 0.609043 |
8,812,540 | 19 | 25 | 19. One or more non-transitory media storing instructions that, when executed by one or more computing devices, cause performance of: based on first content that has been opened within a content presentation application executing on a client device, the client device automatically selecting context information to submit to a server; responsive to automatically selecting the context information for submission to the server, the client device automatically sending the context information from the client device to the server; responsive to sending the context information to the server, the client device receiving a first search result from the server; responsive to activation input activating a search interface, displaying the search interface; after receiving the activation input, and prior to receiving any user input of a query term via the activated search interface, displaying the first search result within a preview section of the search interface; subsequent to displaying the first search result in the preview section, receiving user input entering one or more query terms via the search interface, the one or more query terms including at least one term that is not found in the context information; sending the one or more query terms to the server; responsive to sending the one or more query terms to the server, the client device receiving a second search result from the server; displaying the second search result in the search interface at the client device. | 19. One or more non-transitory media storing instructions that, when executed by one or more computing devices, cause performance of: based on first content that has been opened within a content presentation application executing on a client device, the client device automatically selecting context information to submit to a server; responsive to automatically selecting the context information for submission to the server, the client device automatically sending the context information from the client device to the server; responsive to sending the context information to the server, the client device receiving a first search result from the server; responsive to activation input activating a search interface, displaying the search interface; after receiving the activation input, and prior to receiving any user input of a query term via the activated search interface, displaying the first search result within a preview section of the search interface; subsequent to displaying the first search result in the preview section, receiving user input entering one or more query terms via the search interface, the one or more query terms including at least one term that is not found in the context information; sending the one or more query terms to the server; responsive to sending the one or more query terms to the server, the client device receiving a second search result from the server; displaying the second search result in the search interface at the client device. 25. The one or more non-transitory media of claim 19 , wherein the client device is a handheld device, the method further comprising: displaying the first content in the content presentation application; providing a particular input key designated for initiating a queryless search based on the first content; wherein the first search result is displayed responsive to receiving input via the particular input key. | 0.602687 |
7,890,452 | 1 | 8 | 1. In an enterprise system having a presentation agent for presenting enterprise data of the enterprise system in accordance with one of a plurality of working modes selectable via a user device communicably interfaced with the enterprise system, a method comprising: determining, via a determine context feature of the presentation agent, a working mode associated with the user device based on a user preference indicated by the user device, the working mode to affect the manner in which the enterprise data is presented to and displayed via the user device; de-coupling, via a composite application framework of the enterprise system, one or more composite application components from an underlying one or more enterprise application platforms of the enterprise system, wherein the composite application framework provides an integration infrastructure for creating a composite application from the one or more composite application components, and wherein the one or more composite application components comprise functionality to be integrated by the composite application framework; creating the composite application, via the composite application framework, by integrating the one or more composite application components; associating, via an associate presentation feature of the presentation agent, a presentation paradigm with the composite application based at least in part on the determined working mode associated with the user device; and presenting, via a provide display feature of the presentation agent, the enterprise data to the user device in accordance with the presentation paradigm associated with the composite application in the context of the composite application, wherein presenting the enterprise data in the context of the composite application comprises presenting a project event and/or alert to the user device pursuant to functionality of the composite application, wherein the presentation of the project event and/or alert is presented to the user device in accordance with the presentation paradigm associated with the composite application. | 1. In an enterprise system having a presentation agent for presenting enterprise data of the enterprise system in accordance with one of a plurality of working modes selectable via a user device communicably interfaced with the enterprise system, a method comprising: determining, via a determine context feature of the presentation agent, a working mode associated with the user device based on a user preference indicated by the user device, the working mode to affect the manner in which the enterprise data is presented to and displayed via the user device; de-coupling, via a composite application framework of the enterprise system, one or more composite application components from an underlying one or more enterprise application platforms of the enterprise system, wherein the composite application framework provides an integration infrastructure for creating a composite application from the one or more composite application components, and wherein the one or more composite application components comprise functionality to be integrated by the composite application framework; creating the composite application, via the composite application framework, by integrating the one or more composite application components; associating, via an associate presentation feature of the presentation agent, a presentation paradigm with the composite application based at least in part on the determined working mode associated with the user device; and presenting, via a provide display feature of the presentation agent, the enterprise data to the user device in accordance with the presentation paradigm associated with the composite application in the context of the composite application, wherein presenting the enterprise data in the context of the composite application comprises presenting a project event and/or alert to the user device pursuant to functionality of the composite application, wherein the presentation of the project event and/or alert is presented to the user device in accordance with the presentation paradigm associated with the composite application. 8. A method according to claim 1 , wherein the underlying one or more enterprise application platforms of the enterprise system comprises at least office productivity software, and wherein determining the working mode further comprises determining an environment of the office productivity software selectable at the user device to determine the working mode. | 0.588303 |
9,069,854 | 20 | 21 | 20. The system of claim 19 wherein the network interface comprises a Hypertext Transfer Protocol (HTTP) based interface. | 20. The system of claim 19 wherein the network interface comprises a Hypertext Transfer Protocol (HTTP) based interface. 21. The system of claim 20 wherein the network is the Internet. | 0.986043 |
7,716,576 | 3 | 4 | 3. The method of claim 1 , further comprising: reading an unrecognized XML tag, wherein an unrecognized XML tag is an XML tag not in said LUT; and including said unrecognized XML tag in said pcode file, wherein said unrecognized XML tag is not converted into a pcode. | 3. The method of claim 1 , further comprising: reading an unrecognized XML tag, wherein an unrecognized XML tag is an XML tag not in said LUT; and including said unrecognized XML tag in said pcode file, wherein said unrecognized XML tag is not converted into a pcode. 4. The method of claim 3 , further comprising: marking said unrecognized XML tag with a specialized pcode, wherein said specialized pcode demarcates said unrecognized XML tag in said pcode file. | 0.922338 |
9,275,641 | 1 | 6 | 1. A method, comprising: enabling a developer, by a first server comprising at least one processor and a memory storing processor-executable codes, to create a developer profile; receiving, by the first server, one or more developer example requests, wherein each of the developer example requests is associated with one or more phrases; determining, by the first server, one or more dialog system entities from the one or more example requests using a machine-learning technique, wherein the one or more dialog system entities are associated with the developer profile; determining, by the first server, one or more dialog system intents from the one or more developer example requests using a machine-learning technique, wherein the one or more dialog system intents are associated with the developer profile; associating, by the first server, the one or more dialog system entities with the one or more dialog system intents to form a custom dialog system engine; linking, by the first server, the custom dialog system engine with a dialog system interface using the developer profile, wherein the dialog system interface is provided on a client user device or a web server; receiving, by the first server or a second server, a user request from the dialog system interface, wherein the dialog system interface is installed on a user device or a third server; identifying, by the first server or the second server, the dialog system interface based on the user request; based on the identification of the dialog system interface, activating, by the first server or the second server, the custom dialog system engine and retrieving the one or more dialog system entities and the one or more dialog system intents; processing, by the first server or the second server, the user request by applying the one or more dialog system entities and the one or more dialog system intents; and generating, by the first server or the second server, a response to the user request based on the processing and sending the response to the dialog system interface. | 1. A method, comprising: enabling a developer, by a first server comprising at least one processor and a memory storing processor-executable codes, to create a developer profile; receiving, by the first server, one or more developer example requests, wherein each of the developer example requests is associated with one or more phrases; determining, by the first server, one or more dialog system entities from the one or more example requests using a machine-learning technique, wherein the one or more dialog system entities are associated with the developer profile; determining, by the first server, one or more dialog system intents from the one or more developer example requests using a machine-learning technique, wherein the one or more dialog system intents are associated with the developer profile; associating, by the first server, the one or more dialog system entities with the one or more dialog system intents to form a custom dialog system engine; linking, by the first server, the custom dialog system engine with a dialog system interface using the developer profile, wherein the dialog system interface is provided on a client user device or a web server; receiving, by the first server or a second server, a user request from the dialog system interface, wherein the dialog system interface is installed on a user device or a third server; identifying, by the first server or the second server, the dialog system interface based on the user request; based on the identification of the dialog system interface, activating, by the first server or the second server, the custom dialog system engine and retrieving the one or more dialog system entities and the one or more dialog system intents; processing, by the first server or the second server, the user request by applying the one or more dialog system entities and the one or more dialog system intents; and generating, by the first server or the second server, a response to the user request based on the processing and sending the response to the dialog system interface. 6. The method of claim 1 , further comprising displaying the response to the user. | 0.874233 |
8,200,700 | 1 | 6 | 1. A system comprising: a database including a plurality of syndicated resources and at least one representation of the syndicated resources, the representation expressed in an outline markup language wherein the content encoded in the outline markup language defines a relationship between data distributed in plurality of locations; a database management system for the database; a syndication input to the database that subscribes to at least one syndicated feed and writes items in the syndicated feed to the database; and a syndicated output that publishes results of a database function to an output data feed. | 1. A system comprising: a database including a plurality of syndicated resources and at least one representation of the syndicated resources, the representation expressed in an outline markup language wherein the content encoded in the outline markup language defines a relationship between data distributed in plurality of locations; a database management system for the database; a syndication input to the database that subscribes to at least one syndicated feed and writes items in the syndicated feed to the database; and a syndicated output that publishes results of a database function to an output data feed. 6. The system of claim 1 , wherein the database management system encrypts contents of the database. | 0.593496 |
7,483,831 | 1 | 13 | 1. A method of enhancing intelligibility of speech contained in an audio signal perceived by a subject via a communications path, where the communications path includes an intelligibility enhancing device having an adjustable gain, comprising: A. generating a candidate frequency-wise gain which, if applied to the intelligibility enhancing device, would maximize an intelligibility metric of the communications path, where the intelligibility metric is a function of the relation:
AI=V×E×F×H where, AI is the intelligibility metric, V is a measure of audibility of the speech contained in the audio signal and is associated with a speech-to-noise ratio in the audio signal, E is a loudness limit associated the speech contained in the audio signal, F is a measure of spectral balance of the speech contained in the audio signal, H is a measure of any of (i) intermodulation distortion introduced by an ear of the subject, (ii) reverberation in the medium, (iii) frequency-compression in the communications path, (iv) frequency-shifting in the communications path and (v) peak-clipping in the communications path, (vi) amplitude compression in the communications path, (vii) any other noise or distortion in the communications path not otherwise associated with V, E and F, and B. adjusting the gain of the intelligibility enhancing device in accord with the candidate frequency-wise gain and outputting the audio signal with the intelligibility enhancing device utilizing that adjusted gain. | 1. A method of enhancing intelligibility of speech contained in an audio signal perceived by a subject via a communications path, where the communications path includes an intelligibility enhancing device having an adjustable gain, comprising: A. generating a candidate frequency-wise gain which, if applied to the intelligibility enhancing device, would maximize an intelligibility metric of the communications path, where the intelligibility metric is a function of the relation:
AI=V×E×F×H where, AI is the intelligibility metric, V is a measure of audibility of the speech contained in the audio signal and is associated with a speech-to-noise ratio in the audio signal, E is a loudness limit associated the speech contained in the audio signal, F is a measure of spectral balance of the speech contained in the audio signal, H is a measure of any of (i) intermodulation distortion introduced by an ear of the subject, (ii) reverberation in the medium, (iii) frequency-compression in the communications path, (iv) frequency-shifting in the communications path and (v) peak-clipping in the communications path, (vi) amplitude compression in the communications path, (vii) any other noise or distortion in the communications path not otherwise associated with V, E and F, and B. adjusting the gain of the intelligibility enhancing device in accord with the candidate frequency-wise gain and outputting the audio signal with the intelligibility enhancing device utilizing that adjusted gain. 13. The method of claim 1 , wherein the intelligibility enhancing device is any of a hearing aid, loudspeaker, assistive listening device, telephone, personal music delivery systems, public-address system, speech delivery system, speech generating system. | 0.538043 |
8,983,211 | 16 | 17 | 16. The computer implemented method of claim 8 , wherein the language scores are based on a probability of a character in the corrected character sequence following a pre-determined sequence of one or more characters. | 16. The computer implemented method of claim 8 , wherein the language scores are based on a probability of a character in the corrected character sequence following a pre-determined sequence of one or more characters. 17. The computer implemented method of claim 16 , wherein the language scores are based on a product of the probability of each character in the corrected character sequence following the pre-determined sequence of one or more characters for the entire corrected character sequence. | 0.875989 |
8,699,676 | 15 | 16 | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing performing operations comprising: receiving a voice message intended for delivery to a device associated with a recipient, the voice message being in a first language; receiving, from the recipient, an access number specific to a second language; translating the voice message into the second language, to yield a translated voice message; and transmitting the translated voice message to the device associated with the recipient. | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing performing operations comprising: receiving a voice message intended for delivery to a device associated with a recipient, the voice message being in a first language; receiving, from the recipient, an access number specific to a second language; translating the voice message into the second language, to yield a translated voice message; and transmitting the translated voice message to the device associated with the recipient. 16. The computer-readable storage device of claim 15 , wherein the voice message comprises a telephone number. | 0.831288 |
8,577,883 | 3 | 4 | 3. The method of claim 2 , the method further comprising: characterizing a set of authors, specifying a mapping from the first and second set identifiers to the targeted unrefinement, and using an unrefinement rule that restricts the second audience to the second reference for the set of authors. | 3. The method of claim 2 , the method further comprising: characterizing a set of authors, specifying a mapping from the first and second set identifiers to the targeted unrefinement, and using an unrefinement rule that restricts the second audience to the second reference for the set of authors. 4. The method of claim 3 , the method further comprising a default unrefinement. | 0.981752 |
8,375,017 | 1 | 4 | 1. A computerized method of automatically identifying keywords relevant to a document invisible to search engines comprising: analyzing at a computer the document invisible to search engine crawlers to obtain a keyword starter set from the document, the keyword starter set obtained by: (1) applying at said computer an automated parser to the document to obtain keywords; and (2) applying a frequency prominence analysis to the keywords to select one or more frequently occurring keywords to add to the keyword starter set; expanding at the computer the keyword starter set by applying a computerized taxonomy to the keyword starter set to form a keyword super set; applying at the computer a keyword stop list to keywords in the keyword super set to remove keywords included in the keyword stop list; refining at the computer the keyword super set to form a keyword final set by applying keyword demand data to the keyword super set to remove one or more additional keywords from the keyword super set, wherein the demand data reflects the frequency of use of the keywords as search terms in internet search engines; adding at the computer the keyword final set to a web page for accessing the document; storing the document invisible to search engines for retrieval via the web page for accessing the document; adding the web page with the keyword final set to a web site to facilitate location by internet search engines of the web page for accessing the document according to the keywords added to the web page; and providing internet users with access via the web page to the document invisible to search engines. | 1. A computerized method of automatically identifying keywords relevant to a document invisible to search engines comprising: analyzing at a computer the document invisible to search engine crawlers to obtain a keyword starter set from the document, the keyword starter set obtained by: (1) applying at said computer an automated parser to the document to obtain keywords; and (2) applying a frequency prominence analysis to the keywords to select one or more frequently occurring keywords to add to the keyword starter set; expanding at the computer the keyword starter set by applying a computerized taxonomy to the keyword starter set to form a keyword super set; applying at the computer a keyword stop list to keywords in the keyword super set to remove keywords included in the keyword stop list; refining at the computer the keyword super set to form a keyword final set by applying keyword demand data to the keyword super set to remove one or more additional keywords from the keyword super set, wherein the demand data reflects the frequency of use of the keywords as search terms in internet search engines; adding at the computer the keyword final set to a web page for accessing the document; storing the document invisible to search engines for retrieval via the web page for accessing the document; adding the web page with the keyword final set to a web site to facilitate location by internet search engines of the web page for accessing the document according to the keywords added to the web page; and providing internet users with access via the web page to the document invisible to search engines. 4. The method of claim 1 , wherein the keyword starter set comprises a plurality of user provided words. | 0.907473 |
7,756,851 | 1 | 9 | 1. A computer-implemented method for providing a full text search index, comprising: determining an active subset of a set of content items, wherein each content item in said active subset of said set of content items is associated with a respective one of a plurality of content item idle timers; determining an idle subset of said set of content items at least in part by reclassifying content items from said active subset of said set of content items to said idle subset of said set of content items responsive to expiration of their associated content item idle timers; making said idle subset of said set of content items available for indexing into said full text index, wherein said active subset of said set of content is not available for indexing; and resetting respective ones of said content item idle timers responsive to detecting that an operation is performed on said associated one of said content items in said active subset of said set of content items. | 1. A computer-implemented method for providing a full text search index, comprising: determining an active subset of a set of content items, wherein each content item in said active subset of said set of content items is associated with a respective one of a plurality of content item idle timers; determining an idle subset of said set of content items at least in part by reclassifying content items from said active subset of said set of content items to said idle subset of said set of content items responsive to expiration of their associated content item idle timers; making said idle subset of said set of content items available for indexing into said full text index, wherein said active subset of said set of content is not available for indexing; and resetting respective ones of said content item idle timers responsive to detecting that an operation is performed on said associated one of said content items in said active subset of said set of content items. 9. The method of claim 1 , further comprising: monitoring user behavior to determine at least one use pattern; and adjusting a time remaining of said content item idle timers responsive, at least in part, to said at least one use pattern. | 0.820513 |
9,412,365 | 1 | 6 | 1. A method performed by one or more computers, the method comprising: receiving, by the one or more computers, data indicating a candidate transcription for an utterance and a particular context for the utterance; obtaining, by the one or more computers, a maximum entropy language model that includes (i) scores for one or more n-gram features that each correspond to a respective n-gram and (ii) scores for one or more backoff features that each correspond to a set of n-grams for which there are no corresponding n-gram features in the maximum entropy language model; determining, by the one or more computers, based on the candidate transcription and the particular context, a feature value for (i) each of the one or more n-gram features of the maximum entropy language model and (ii) each of the one or more backoff features of the maximum entropy language model; inputting, by the one or more computers, the feature values for the n-gram features and the feature values for the backoff features to the maximum entropy language model; and receiving, by the one or more computers, from the maximum entropy language model, an output indicative of a likelihood of occurrence of the candidate transcription; selecting, by the one or more computers, based on the output of the maximum entropy language model, a transcription for the utterance from among a plurality of candidate transcriptions; and providing, by the one or more computers, the selected transcription to a client device. | 1. A method performed by one or more computers, the method comprising: receiving, by the one or more computers, data indicating a candidate transcription for an utterance and a particular context for the utterance; obtaining, by the one or more computers, a maximum entropy language model that includes (i) scores for one or more n-gram features that each correspond to a respective n-gram and (ii) scores for one or more backoff features that each correspond to a set of n-grams for which there are no corresponding n-gram features in the maximum entropy language model; determining, by the one or more computers, based on the candidate transcription and the particular context, a feature value for (i) each of the one or more n-gram features of the maximum entropy language model and (ii) each of the one or more backoff features of the maximum entropy language model; inputting, by the one or more computers, the feature values for the n-gram features and the feature values for the backoff features to the maximum entropy language model; and receiving, by the one or more computers, from the maximum entropy language model, an output indicative of a likelihood of occurrence of the candidate transcription; selecting, by the one or more computers, based on the output of the maximum entropy language model, a transcription for the utterance from among a plurality of candidate transcriptions; and providing, by the one or more computers, the selected transcription to a client device. 6. The method of claim 1 , wherein the scores of the maximum entropy language model comprise, for each context in a set of different contexts that each comprise a different sequence of one or more words, respective scores for: multiple different n-gram features that each correspond to a respective language sequence that includes the one or more words of the context, each of the respective language sequences being formed of a same, particular number of words, and one or more backoff features that each correspond to a set of multiple language sequences, wherein, for each backoff feature, each language sequence in the set of language sequences (i) is formed of the particular number of words, (ii) comprises a particular subset of the one or more words of the context, and (iii) omits a particular sub-sequence of words within the context. | 0.577154 |
7,835,999 | 14 | 19 | 14. At a computer system including a multi-touch input display surface, a method for recognizing input gesture data entered at the multi-touch input display surface as a specified symbol, the method comprising: an act of accessing input gesture data representing detected contact on the multi-touch input display surface over a period of time, the input gesture data including at least: first direction movement data, the first direction movement data being a first calculated graph including a directional axis corresponding to a first axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the first calculated graph indicating the position of detected contact on the multi-touch input display surface relative to the first axis over the time period; and second direction movement data, the second direction movement data being a second calculated graph including a directional axis corresponding to a second axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the second calculated graph indicating the position of detected contact on the multi-touch input display surface relative to a second different axis over the time period; an act of taking a plurality of samples of each of the first direction movement data and the second direction movement data at a plurality of designated intervals between the beginning of the time period and the end of the time period; an act of submitting the plurality of samples, including submitting real values, each real value corresponding to a time value from the period of time contact was detected on the multi-touch input display surface and including a directional axis value, to a corresponding plurality of input nodes of a neural network, the neural network having previously trained link weights from the input nodes to a plurality of hidden nodes and the neural network having previously trained link weights from the plurality of hidden nodes to a plurality of output nodes, each output node assigned to a specified symbol such that an output node being activated to a specified threshold value is indicative of the neural network recognizing input gesture data as the specified symbol; an act of the neural network processing the plurality of samples based on the previously trained link weights to activate values at each of the plurality of output nodes; an act of determining that the activated value at the specified output node assigned to the specified symbol is at least the specified threshold value; and an act of indicating that the specified symbol has been recognized from the input gesture data. | 14. At a computer system including a multi-touch input display surface, a method for recognizing input gesture data entered at the multi-touch input display surface as a specified symbol, the method comprising: an act of accessing input gesture data representing detected contact on the multi-touch input display surface over a period of time, the input gesture data including at least: first direction movement data, the first direction movement data being a first calculated graph including a directional axis corresponding to a first axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the first calculated graph indicating the position of detected contact on the multi-touch input display surface relative to the first axis over the time period; and second direction movement data, the second direction movement data being a second calculated graph including a directional axis corresponding to a second axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the second calculated graph indicating the position of detected contact on the multi-touch input display surface relative to a second different axis over the time period; an act of taking a plurality of samples of each of the first direction movement data and the second direction movement data at a plurality of designated intervals between the beginning of the time period and the end of the time period; an act of submitting the plurality of samples, including submitting real values, each real value corresponding to a time value from the period of time contact was detected on the multi-touch input display surface and including a directional axis value, to a corresponding plurality of input nodes of a neural network, the neural network having previously trained link weights from the input nodes to a plurality of hidden nodes and the neural network having previously trained link weights from the plurality of hidden nodes to a plurality of output nodes, each output node assigned to a specified symbol such that an output node being activated to a specified threshold value is indicative of the neural network recognizing input gesture data as the specified symbol; an act of the neural network processing the plurality of samples based on the previously trained link weights to activate values at each of the plurality of output nodes; an act of determining that the activated value at the specified output node assigned to the specified symbol is at least the specified threshold value; and an act of indicating that the specified symbol has been recognized from the input gesture data. 19. The method as recited in claim 14 , further comprising an act of presenting the specified symbol on the multi-touch input display surface. | 0.848936 |
8,019,793 | 25 | 26 | 25. The computer program of claim 11 , further comprising a code segment for generating a relationship database that includes each object explicit relationship included in the information files. | 25. The computer program of claim 11 , further comprising a code segment for generating a relationship database that includes each object explicit relationship included in the information files. 26. The computer program of claim 25 , wherein the relationship database includes the at least one implicit relationship. | 0.967438 |
7,642,932 | 9 | 11 | 9. Apparatus for entering text in a mobile communications device comprising: a mobile communications keypad having a standard array of keys available for entering data; a memory for storing a list of the characters used in a language based on a Thai alphabet to be entered by using the standard array of keys of the mobile communications device, the memory storing said list divided into at least first and second groups; a microprocessor controller of the mobile communications device having computer executable code contained therein for mapping each of the alphabetic characters of the first group to the keys of the keypad and for mapping each of the alphabetic characters of the second group to the keys of the keypad; a dedicated key for selectably switching the keypad between at least a first and second mode of operation; and wherein the microprocessor controller is adapted to switch the characters mapped to said keys between the first group and second group according to the first or second modes of operation respectively in response to operation of the dedicated switch; and wherein the first group is comprised only of consonant characters and the second group comprises only non-consonant characters. | 9. Apparatus for entering text in a mobile communications device comprising: a mobile communications keypad having a standard array of keys available for entering data; a memory for storing a list of the characters used in a language based on a Thai alphabet to be entered by using the standard array of keys of the mobile communications device, the memory storing said list divided into at least first and second groups; a microprocessor controller of the mobile communications device having computer executable code contained therein for mapping each of the alphabetic characters of the first group to the keys of the keypad and for mapping each of the alphabetic characters of the second group to the keys of the keypad; a dedicated key for selectably switching the keypad between at least a first and second mode of operation; and wherein the microprocessor controller is adapted to switch the characters mapped to said keys between the first group and second group according to the first or second modes of operation respectively in response to operation of the dedicated switch; and wherein the first group is comprised only of consonant characters and the second group comprises only non-consonant characters. 11. The apparatus according to claim 9 further comprising a display screen for displaying the characters mapped to each key of said keypad according to the mode of operation. | 0.719355 |
9,348,579 | 1 | 6 | 1. A method of integrating social networks with integrated development environment (IDE), the method comprising: downloading social information; filtering and displaying the downloaded social information; performing software development using the displayed social information, wherein the performing software development comprises creating a topic related to a source file, wherein the topic comprises an identifier that identifies the source file, a location reference of the source file, one or more user comments and a source file snapshot that includes a read-only copy of the source file; and storing updated social information in a database, wherein the updated social information comprises the created topic. | 1. A method of integrating social networks with integrated development environment (IDE), the method comprising: downloading social information; filtering and displaying the downloaded social information; performing software development using the displayed social information, wherein the performing software development comprises creating a topic related to a source file, wherein the topic comprises an identifier that identifies the source file, a location reference of the source file, one or more user comments and a source file snapshot that includes a read-only copy of the source file; and storing updated social information in a database, wherein the updated social information comprises the created topic. 6. The method according to claim 1 , wherein the social information is attached and displayed through an icon in a user interface. | 0.886957 |
9,620,109 | 1 | 2 | 1. A guide sentence generating method implemented by one or more processors, the guide sentence generating method comprising: receiving speech data corresponding to user speech from an electronic apparatus; analyzing the speech data, determining a category of the speech data from among a plurality of categories, and storing the analyzed speech data in the determined category; determining a usage frequency and a global popularity of each of the plurality of categories, wherein the usage frequency comprises a count of speech data of an individual user and the global popularity comprises a count of speech data of a plurality of users; selecting a category from among the plurality of categories based on the usage frequency and the global popularity; generating a guide sentence corresponding to the selected category; transmitting the guide sentence to the electronic apparatus; and providing the guide sentence to the user in at least one of visual and audio form, so that the user may command the electronic apparatus using the guide sentence. | 1. A guide sentence generating method implemented by one or more processors, the guide sentence generating method comprising: receiving speech data corresponding to user speech from an electronic apparatus; analyzing the speech data, determining a category of the speech data from among a plurality of categories, and storing the analyzed speech data in the determined category; determining a usage frequency and a global popularity of each of the plurality of categories, wherein the usage frequency comprises a count of speech data of an individual user and the global popularity comprises a count of speech data of a plurality of users; selecting a category from among the plurality of categories based on the usage frequency and the global popularity; generating a guide sentence corresponding to the selected category; transmitting the guide sentence to the electronic apparatus; and providing the guide sentence to the user in at least one of visual and audio form, so that the user may command the electronic apparatus using the guide sentence. 2. The method of claim 1 , wherein the selecting comprises selecting a category whose usage frequency is lowest and global popularity is highest from among the plurality of categories. | 0.779376 |
7,545,981 | 8 | 12 | 8. A method of rearranging a display of text within an image containing text, said method comprising: acquiring an image containing text by a solid-state image sensor; using a computer processor to: identify distinct regions of text within said image; generate sub-images from said image according to said distinct regions of text; and order said sub-images according to a predetermined order; and displaying said sub-images in said predetermined order on a graphical display device, wherein if said computer identifies side-by-side columns, said computer changes a presentation of said columns such that said columns are displayed on said graphical display device above and below each other instead of side-by-side. | 8. A method of rearranging a display of text within an image containing text, said method comprising: acquiring an image containing text by a solid-state image sensor; using a computer processor to: identify distinct regions of text within said image; generate sub-images from said image according to said distinct regions of text; and order said sub-images according to a predetermined order; and displaying said sub-images in said predetermined order on a graphical display device, wherein if said computer identifies side-by-side columns, said computer changes a presentation of said columns such that said columns are displayed on said graphical display device above and below each other instead of side-by-side. 12. The method according to claim 8 , wherein said computer displays by: comparing a size of a graphic user interface display with a size of said distinct regions of text; and changing a magnification of said distinct regions of text to compensate for size differences between said graphic user interface display and said distinct regions of text. | 0.723285 |
8,095,476 | 1 | 9 | 1. A method, comprising: displaying a plurality of web page fields; monitoring actions associated with entering information into the plurality of web page fields; in response to observing a predetermined characteristic associated with a monitored action of a web page field of a first subset of the plurality of web page fields, causing a first level of on-line support to be provided responsive to the occurrence of the respective monitored action; wherein the first level of on-line support includes human support; and in response to observing the same predetermined characteristic associated with a monitored action of a web page field of a second different subset of the plurality of fields, causing a second different level of on-line support to be provided responsive to the occurrence of the respective monitored action; wherein the second different level of on-line support does not include human support. | 1. A method, comprising: displaying a plurality of web page fields; monitoring actions associated with entering information into the plurality of web page fields; in response to observing a predetermined characteristic associated with a monitored action of a web page field of a first subset of the plurality of web page fields, causing a first level of on-line support to be provided responsive to the occurrence of the respective monitored action; wherein the first level of on-line support includes human support; and in response to observing the same predetermined characteristic associated with a monitored action of a web page field of a second different subset of the plurality of fields, causing a second different level of on-line support to be provided responsive to the occurrence of the respective monitored action; wherein the second different level of on-line support does not include human support. 9. The method according to claim 1 , wherein the web page fields of the first subset of the plurality of web page fields are assigned a different label, tag, value, or index in a table or index than the web page fields of the second subset of the plurality of web page fields. | 0.764103 |
6,155,834 | 3 | 15 | 3. The computer implemented, data driven method of teaching a student to read according to claim 2, wherein the whole word recognition test; the partial word recognition test; and the word sequence recognition test represent three interactive process types respectively corresponding to choosing a target word from a list of displayed words by first communicating the target then choosing the target word from a list of subsequently displayed words; filling in letter blanks by first communicating a target word and then filling in letter blanks of a displayed, partial target word having blanked letters; and determining a correct sequence of words by individually communicating a plurality of words that includes the target word in a first sequence one word at a time, then simultaneously displaying the plurality of words including the target word in a second sequence, and then selecting words from the displayed plurality of words in the first sequence, said presenting step presenting the student with at least one of nine interactive processes wherein each interactive process type includes three interactive processes, the three interactive processes including a show only process which communicates the target word by displaying the target word for a show interval, a say only process which communicates the target word by audibly announcing the target word, and a show and say process that communicates the target word by displaying the target word for a show interval and by audibly announcing the target word. | 3. The computer implemented, data driven method of teaching a student to read according to claim 2, wherein the whole word recognition test; the partial word recognition test; and the word sequence recognition test represent three interactive process types respectively corresponding to choosing a target word from a list of displayed words by first communicating the target then choosing the target word from a list of subsequently displayed words; filling in letter blanks by first communicating a target word and then filling in letter blanks of a displayed, partial target word having blanked letters; and determining a correct sequence of words by individually communicating a plurality of words that includes the target word in a first sequence one word at a time, then simultaneously displaying the plurality of words including the target word in a second sequence, and then selecting words from the displayed plurality of words in the first sequence, said presenting step presenting the student with at least one of nine interactive processes wherein each interactive process type includes three interactive processes, the three interactive processes including a show only process which communicates the target word by displaying the target word for a show interval, a say only process which communicates the target word by audibly announcing the target word, and a show and say process that communicates the target word by displaying the target word for a show interval and by audibly announcing the target word. 15. The computer implemented, data driven method of teaching a student to read according to claim 3, said adjusting step adjusting the difficulty level of the choosing a target word from a list interactive process presented in said presenting step by adjusting the number of words in the list based on student age and student performance; said adjusting step adjusting the difficulty level of the determining a correct sequence of words interactive process presented in said presenting step by adjusting the number of the words in the sequence according to student age and student performance; said calculating step calculating student performance based on the number of words in the list or sequence. | 0.683092 |
8,881,101 | 6 | 11 | 6. A computer-implemented method comprising: creating at least one layout engine object in a layout engine memory space; creating at least one scripting language object in a scripting engine memory space, the at least one scripting language object bound to the at least one layout engine object via a linkage, wherein the linkage utilizes a custom object in the scripting engine memory space that is configured to include: information associated with relationships between objects in the scripting engine memory space and the at least one scripting language object, including at least one hierarchical relationship between the at least one scripting language object and at least a second scripting language object, the at least one hierarchical relationship based, at least in part, on a hierarchical relationship associated with the at least one scripting layout engine object; and information associated with the at least one layout engine object in the layout engine memory space; and using at least one binding module to enable unified programming access between the at least one layout engine object and the at least one scripting language object. | 6. A computer-implemented method comprising: creating at least one layout engine object in a layout engine memory space; creating at least one scripting language object in a scripting engine memory space, the at least one scripting language object bound to the at least one layout engine object via a linkage, wherein the linkage utilizes a custom object in the scripting engine memory space that is configured to include: information associated with relationships between objects in the scripting engine memory space and the at least one scripting language object, including at least one hierarchical relationship between the at least one scripting language object and at least a second scripting language object, the at least one hierarchical relationship based, at least in part, on a hierarchical relationship associated with the at least one scripting layout engine object; and information associated with the at least one layout engine object in the layout engine memory space; and using at least one binding module to enable unified programming access between the at least one layout engine object and the at least one scripting language object. 11. The computer-implemented method of claim 6 , wherein using the at least one binding module comprises enabling calls to be bridged between the scripting language object and the layout engine object using native access associated with the scripting engine object. | 0.832066 |
9,251,294 | 1 | 2 | 1. A method of approximate string matching of a target string to a trie data structure, the trie data structure having a root node and generations of child nodes, each node representing at least one character in an alphabet, the method comprising: traversing the trie data structure starting from the root node by comparing each node of a branch of the trie data structure to at least one character in the target string; determining, at each node, if there is a correction rule for one or more characters in the remainder of the target string from the current node, and, if so, applying the correction rule to the target string to modify the target string to obtain a modified target string, wherein applying the correction rule includes performing a sequence to sequence character substitution on the target string to obtain the modified target string, and continuing to traverse the trie data structure from the current node using the modified target string, wherein no additional modifications of the modified target string are allowed within its modified parts; and providing, responsive to the traversing, at least one suggestion from the trie data structure. | 1. A method of approximate string matching of a target string to a trie data structure, the trie data structure having a root node and generations of child nodes, each node representing at least one character in an alphabet, the method comprising: traversing the trie data structure starting from the root node by comparing each node of a branch of the trie data structure to at least one character in the target string; determining, at each node, if there is a correction rule for one or more characters in the remainder of the target string from the current node, and, if so, applying the correction rule to the target string to modify the target string to obtain a modified target string, wherein applying the correction rule includes performing a sequence to sequence character substitution on the target string to obtain the modified target string, and continuing to traverse the trie data structure from the current node using the modified target string, wherein no additional modifications of the modified target string are allowed within its modified parts; and providing, responsive to the traversing, at least one suggestion from the trie data structure. 2. A method as in claim 1 , further comprising: adding characters traversed in a branch of the trie data structure to a gathered string; and reaching a node flagged as a node for a word or a word fragment, comparing the length of the target string to the length of the gathered string, and, if the target string is longer than the gathered string, looping back to the root node, and continuing the traverse from the root node. | 0.674809 |
8,645,138 | 9 | 14 | 9. A computing system, comprising: a processor; and a non-transitory computer-readable storage medium having stored thereon program instructions that, upon execution by the processor, cause the computing device to perform operations comprising: receiving input speech, during a first pass of speech recognition, determining a plurality of outputs from a plurality of language models by: providing the input speech as an input to each of a plurality of language models, wherein the plurality of language models comprises a query language model and an action language model, and receiving an output from each language model, determining a selected language model of the plurality of language models based on a classifier operating on the plurality of outputs from the plurality of language models, wherein the classifier is configured to utilize a support vector machine (SVM) to select the selected language model, and wherein the SVM is configured to determine a plane or hyperplane related to the plurality of language-model outputs and to select the selected language model based on the plane or hyperplane, during a second pass of speech recognition, determining a revised output by: providing the input speech and the output from the selected language model as inputs to the selected language model, receiving a revised output from the selected language model, and generating a result based on the revised output. | 9. A computing system, comprising: a processor; and a non-transitory computer-readable storage medium having stored thereon program instructions that, upon execution by the processor, cause the computing device to perform operations comprising: receiving input speech, during a first pass of speech recognition, determining a plurality of outputs from a plurality of language models by: providing the input speech as an input to each of a plurality of language models, wherein the plurality of language models comprises a query language model and an action language model, and receiving an output from each language model, determining a selected language model of the plurality of language models based on a classifier operating on the plurality of outputs from the plurality of language models, wherein the classifier is configured to utilize a support vector machine (SVM) to select the selected language model, and wherein the SVM is configured to determine a plane or hyperplane related to the plurality of language-model outputs and to select the selected language model based on the plane or hyperplane, during a second pass of speech recognition, determining a revised output by: providing the input speech and the output from the selected language model as inputs to the selected language model, receiving a revised output from the selected language model, and generating a result based on the revised output. 14. The computing system of claim 9 , wherein the operation of generating the result comprises: after selecting the action language model as the selected language model: generating an action request based on the revised output, and generating the result by providing the action request to an action engine; and after selecting the query language model as the selected language model: generating a query based on the revised output, and generating the result by providing the action request to a query engine. | 0.500982 |
9,619,467 | 1 | 5 | 1. A computer-implemented method executed by one or more computing devices for building a dynamic classification dictionary, the method comprising: extracting, by at least one of the one or more computing devices, one or more terms from information that characterizes a document; applying, by at least one of the one or more computing devices, a first pattern matching rule to the one or more terms to identify one or more taxonomic nouns in the one or more terms, the first pattern matching rule including comparing sequences of consecutive words in the document with known terms and, if a match exists, merging matching consecutive words into a multi-word term and, if a match does not exist, assigning a single word term as the one or more taxonomic nouns; applying, by at least one of the one or more computing devices, a second pattern matching rule to the one or more terms to determine at least one of a part-of-speech and a noun type associated with at least one taxonomic noun of the one or more taxonomic nouns, the second pattern matching rule being different from the first pattern matching rule; and building, by at least one of the one or more computing devices, a dynamic classification dictionary based on the one or more taxonomic nouns and at least one of the part-of-speech and noun type associated with the at least one taxonomic noun. | 1. A computer-implemented method executed by one or more computing devices for building a dynamic classification dictionary, the method comprising: extracting, by at least one of the one or more computing devices, one or more terms from information that characterizes a document; applying, by at least one of the one or more computing devices, a first pattern matching rule to the one or more terms to identify one or more taxonomic nouns in the one or more terms, the first pattern matching rule including comparing sequences of consecutive words in the document with known terms and, if a match exists, merging matching consecutive words into a multi-word term and, if a match does not exist, assigning a single word term as the one or more taxonomic nouns; applying, by at least one of the one or more computing devices, a second pattern matching rule to the one or more terms to determine at least one of a part-of-speech and a noun type associated with at least one taxonomic noun of the one or more taxonomic nouns, the second pattern matching rule being different from the first pattern matching rule; and building, by at least one of the one or more computing devices, a dynamic classification dictionary based on the one or more taxonomic nouns and at least one of the part-of-speech and noun type associated with the at least one taxonomic noun. 5. The method of claim 1 , wherein the second pattern matching rule is a contextual pattern matching rule and wherein applying the second pattern matching rule comprises: comparing the context of the at least one taxonomic noun to one or more known contexts which are indicative of at least one of a part-of-speech and a noun type, wherein the context of the at least one taxonomic noun includes terms surrounding the at least one taxonomic noun; and marking the at least one taxonomic noun as being associated with at least one of a part-of-speech and a noun type corresponding to a matching context in the one or more known contexts. | 0.60754 |
10,050,842 | 12 | 14 | 12. An apparatus in a computer network, comprising: a memory element for storing data; and a processor, wherein the processor executes instructions associated with the data, wherein the processor and the memory element cooperate, wherein the apparatus is configured for: generating a fully populated semantics model of the computer network from network data according to a base network ontology of the computer network, wherein the semantics model comprises a representation of the computer network in a framework of semantically related terms comprising properties of network features of components of the computer network; mapping the fully populated semantics model to a network knowledge base; feeding contents of the network knowledge base to a semantic reasoner; and controlling and managing the network using the semantic reasoner, wherein generating the fully populated semantics model of the network comprises: receiving the network data from the network; parsing the network data; loading the parsed network data into in-memory data structures; accessing a manifest specifying binding between a network data definition format and ontology components of the base network ontology; identifying ontology components associated with the network data based on the manifest; and populating the identified ontology components with individuals and properties from the corresponding data structures; wherein the network data definition format comprises a selection from a group consisting of Structure of Management Information (SMI), YANG, and Extensible Markup Language (XML); and wherein the manifest comprises: mapping of at least one of SMI managed object, YANG leaf and XML element to a Web Ontology Language Description Logics (OWL-DL) class to which an individual belongs; mapping of at least one of SMI object hierarchy, YANG leafref and XML element hierarchy to an OWL-DL object property asserted over a pair of individuals; mapping of a value of at least one of SMI object, YANG leaf and XML element to an OWL-DL individual of a corresponding class; and asserting a data property on an individual. | 12. An apparatus in a computer network, comprising: a memory element for storing data; and a processor, wherein the processor executes instructions associated with the data, wherein the processor and the memory element cooperate, wherein the apparatus is configured for: generating a fully populated semantics model of the computer network from network data according to a base network ontology of the computer network, wherein the semantics model comprises a representation of the computer network in a framework of semantically related terms comprising properties of network features of components of the computer network; mapping the fully populated semantics model to a network knowledge base; feeding contents of the network knowledge base to a semantic reasoner; and controlling and managing the network using the semantic reasoner, wherein generating the fully populated semantics model of the network comprises: receiving the network data from the network; parsing the network data; loading the parsed network data into in-memory data structures; accessing a manifest specifying binding between a network data definition format and ontology components of the base network ontology; identifying ontology components associated with the network data based on the manifest; and populating the identified ontology components with individuals and properties from the corresponding data structures; wherein the network data definition format comprises a selection from a group consisting of Structure of Management Information (SMI), YANG, and Extensible Markup Language (XML); and wherein the manifest comprises: mapping of at least one of SMI managed object, YANG leaf and XML element to a Web Ontology Language Description Logics (OWL-DL) class to which an individual belongs; mapping of at least one of SMI object hierarchy, YANG leafref and XML element hierarchy to an OWL-DL object property asserted over a pair of individuals; mapping of a value of at least one of SMI object, YANG leaf and XML element to an OWL-DL individual of a corresponding class; and asserting a data property on an individual. 14. The apparatus of claim 12 , further configured for performing machine reasoning over the network data in the network knowledge base using the semantic reasoner. | 0.872075 |
8,935,346 | 10 | 11 | 10. The method of claim 5 , wherein determining the candidate score for each candidate group comprises: for each user in a candidate group, determining a product of an affinity between a user in the candidate group and the target user and a level of activity of the user; and summing the products. | 10. The method of claim 5 , wherein determining the candidate score for each candidate group comprises: for each user in a candidate group, determining a product of an affinity between a user in the candidate group and the target user and a level of activity of the user; and summing the products. 11. The method of claim 10 , wherein determining the candidate score for each candidate group further comprises: modifying candidate scores associated with candidate groups based on characteristics of the candidate groups stored by the social networking system. | 0.879724 |
7,522,925 | 1 | 13 | 1. A method of finding locally-relevant information in a physical or electronic document already possessed by a user, the method comprising the steps of: (a) sending a query message from a mobile entity associated with the user via a mobile radio infrastructure to a service system, the query message identifying the document to the system; (b) providing location data regarding the location of the mobile entity to the service system; (c) under the control of the service system, obtaining a document reference indicating where, in the document, information can be found that is relevant to the locality of the mobile entity as indicated by said location data; (d) returning the document reference to the mobile entity. | 1. A method of finding locally-relevant information in a physical or electronic document already possessed by a user, the method comprising the steps of: (a) sending a query message from a mobile entity associated with the user via a mobile radio infrastructure to a service system, the query message identifying the document to the system; (b) providing location data regarding the location of the mobile entity to the service system; (c) under the control of the service system, obtaining a document reference indicating where, in the document, information can be found that is relevant to the locality of the mobile entity as indicated by said location data; (d) returning the document reference to the mobile entity. 13. A method according to claim 1 , wherein the service system also looks up additional data, not in the document, about the locality of the user and returns, or offers to return, this data to the user. | 0.873908 |
8,140,566 | 1 | 20 | 1. A method, comprising: adding, to a page, information items from an information feed that contains information about a particular entity; wherein adding information items from the information feed includes: displaying one or more content objects for selection by a user; receiving input that selects a selected content object from the one or more content objects; in response to the input that selects the selected content object, performing the steps of: determining that the selected content object is associated with the particular entity; determining one or more information sources that contain information about the particular entity; creating the information feed for the particular entity based, at least in part, on information items from the one or more information sources; modifying the page to cause the page to display one or more of the information items from the information feed; wherein the method is performed by one or more computing devices. | 1. A method, comprising: adding, to a page, information items from an information feed that contains information about a particular entity; wherein adding information items from the information feed includes: displaying one or more content objects for selection by a user; receiving input that selects a selected content object from the one or more content objects; in response to the input that selects the selected content object, performing the steps of: determining that the selected content object is associated with the particular entity; determining one or more information sources that contain information about the particular entity; creating the information feed for the particular entity based, at least in part, on information items from the one or more information sources; modifying the page to cause the page to display one or more of the information items from the information feed; wherein the method is performed by one or more computing devices. 20. The method of claim 1 , wherein the input that selects the selected content object is a spoken command from the user. | 0.930857 |
9,880,989 | 14 | 15 | 14. A computer-readable storage, which is non-transitory, including instructions thereon for executing a method of annotating a document, the method comprising: uploading a text-based first document to a service; transforming the first document to a coordinate-based second document; receiving annotations to the second document; mapping the annotations onto the first document; and downloading the first document with the annotations incorporated therein; converting a highlight that does not contain any words or objects to a comment in the first document. | 14. A computer-readable storage, which is non-transitory, including instructions thereon for executing a method of annotating a document, the method comprising: uploading a text-based first document to a service; transforming the first document to a coordinate-based second document; receiving annotations to the second document; mapping the annotations onto the first document; and downloading the first document with the annotations incorporated therein; converting a highlight that does not contain any words or objects to a comment in the first document. 15. The computer-readable storage of claim 14 , further including placing the comment either adjacent a first line, a last line or in a middle of a paragraph depending on the relative location of the highlight with respect to the paragraph. | 0.908257 |
7,849,042 | 11 | 14 | 11. A computer-implemented information searching device, comprising: a non-content characteristics extractor configured to extract one or more non-content characteristics of a document from a document set; an analyzer configured to analyze the extracted non-content characteristics and generate an optimizing tool based on analyzing results; and an optimizer configured to optimize a preliminary search result with the generated optimizing tool, wherein the optimizer comprises: a reliable result selector configured to select, from the preliminary search result, a resulting document sequence having relatively high reliability; a distance calculator configured to calculate a distance from each of the documents to each document of the selected resulting document sequence; an adjusting unit configured to adjust the reliability values of the documents; and an ordering unit configured to arrange the documents in descending order of the adjusted reliability values to obtain optimized results, and wherein the distance from each of the documents in the preliminary search results to the document of the resulting document sequence equals a sum of weights of sides passed through by a directional path between two documents, the distance is infinite when there is no path between the document in the preliminary search results and the document in the resulting document sequence, the distance from one document to itself is zero, the distance L between the document in the preliminary search results and the document in the resulting document sequence is expressed by the following equation when there are plural paths between the two documents, L=1/((1/L 1 )+(1/L 2 )+ . . . +(1/LX)) where, L represents the distance between the two documents, L 1 represents the distance of a path 1 , L 1 represents the distance of a path 2 , and LX represents the distance of a path X. | 11. A computer-implemented information searching device, comprising: a non-content characteristics extractor configured to extract one or more non-content characteristics of a document from a document set; an analyzer configured to analyze the extracted non-content characteristics and generate an optimizing tool based on analyzing results; and an optimizer configured to optimize a preliminary search result with the generated optimizing tool, wherein the optimizer comprises: a reliable result selector configured to select, from the preliminary search result, a resulting document sequence having relatively high reliability; a distance calculator configured to calculate a distance from each of the documents to each document of the selected resulting document sequence; an adjusting unit configured to adjust the reliability values of the documents; and an ordering unit configured to arrange the documents in descending order of the adjusted reliability values to obtain optimized results, and wherein the distance from each of the documents in the preliminary search results to the document of the resulting document sequence equals a sum of weights of sides passed through by a directional path between two documents, the distance is infinite when there is no path between the document in the preliminary search results and the document in the resulting document sequence, the distance from one document to itself is zero, the distance L between the document in the preliminary search results and the document in the resulting document sequence is expressed by the following equation when there are plural paths between the two documents, L=1/((1/L 1 )+(1/L 2 )+ . . . +(1/LX)) where, L represents the distance between the two documents, L 1 represents the distance of a path 1 , L 1 represents the distance of a path 2 , and LX represents the distance of a path X. 14. The information searching device as claimed in claim 11 , wherein the optimizing tool includes one of a classification-based optimizing tool, a time-based optimizing tool, and a document relationship-based optimizing tool. | 0.884576 |
7,908,281 | 1 | 2 | 1. A method comprising: receiving, with a context assembly device, a request to assemble a pedigree that describes a history of origin of a primary resource, wherein the requested pedigree of the primary resource represents the history as a set of statements that describe relationships between the primary resource and a plurality of other resources from which an asserted fact of the primary resource was derived; submitting, from the context assembly device to a set of one or more pedigree management servers, a first query for a first set of pedigree fragments that each include one or more statements that specify direct relationships between the primary resource and a first set of resources, wherein the direct relationships indicate that the asserted fact of the primary resource was derived from data of the first set of the resources; receiving, in response to the first query, a first set of pedigree fragments, each of which includes one or more of the statements that specify the direct relationships between the primary resource and the first set of resources; submitting, with the context assembly device to the pedigree management servers, a second query for a second set of pedigree fragments that include one or more statements that specify direct relationships between the first set of resources and a second set of resources, wherein the direct relationships of the second set of pedigree fragments indicate that the data of the first set of resources was derived from data of the second set of the resources; receiving, in response to the second query, the second set of pedigree fragments, each of which includes one or more of the statements that specify the direct relationships between the first set of resources and the second set of resources; and assembling, with the context assembly device, the pedigree of the primary resource from the statements of the first set of pedigree fragments and the second set of pedigree fragments received from the pedigree management servers. | 1. A method comprising: receiving, with a context assembly device, a request to assemble a pedigree that describes a history of origin of a primary resource, wherein the requested pedigree of the primary resource represents the history as a set of statements that describe relationships between the primary resource and a plurality of other resources from which an asserted fact of the primary resource was derived; submitting, from the context assembly device to a set of one or more pedigree management servers, a first query for a first set of pedigree fragments that each include one or more statements that specify direct relationships between the primary resource and a first set of resources, wherein the direct relationships indicate that the asserted fact of the primary resource was derived from data of the first set of the resources; receiving, in response to the first query, a first set of pedigree fragments, each of which includes one or more of the statements that specify the direct relationships between the primary resource and the first set of resources; submitting, with the context assembly device to the pedigree management servers, a second query for a second set of pedigree fragments that include one or more statements that specify direct relationships between the first set of resources and a second set of resources, wherein the direct relationships of the second set of pedigree fragments indicate that the data of the first set of resources was derived from data of the second set of the resources; receiving, in response to the second query, the second set of pedigree fragments, each of which includes one or more of the statements that specify the direct relationships between the first set of resources and the second set of resources; and assembling, with the context assembly device, the pedigree of the primary resource from the statements of the first set of pedigree fragments and the second set of pedigree fragments received from the pedigree management servers. 2. The method of claim 1 , wherein the method further comprises receiving a request from a user to perform an action that requires the pedigree of the primary resource. | 0.813333 |
8,701,141 | 1 | 2 | 1. A method comprising: arranging on a mosaic page a plurality of cells; receiving a selection from a user of a first of the plurality of cells; receiving an input from the user specifying a criterion for the user selected first cell; determining a plurality of video assets matching the user specified criterions; determining a video asset from the plurality of video assets which is relevant to the user; and generating a display of the relevant video asset in the user selected first cell on the user equipment device. | 1. A method comprising: arranging on a mosaic page a plurality of cells; receiving a selection from a user of a first of the plurality of cells; receiving an input from the user specifying a criterion for the user selected first cell; determining a plurality of video assets matching the user specified criterions; determining a video asset from the plurality of video assets which is relevant to the user; and generating a display of the relevant video asset in the user selected first cell on the user equipment device. 2. The method of claim 1 , wherein the relevance of the video asset to the user is associated with the user's viewing frequency of the asset. | 0.756055 |
10,042,884 | 14 | 15 | 14. The system of claim 10 , wherein the injector relations are mutually disjoint. | 14. The system of claim 10 , wherein the injector relations are mutually disjoint. 15. The system of claim 14 , the operations further comprising: determining that an alternative subtype from the alternative subtypes that is an argument in an expression invocation is incompatible with an expected alternative subtype from the alternative subtypes as the argument in the expression invocation; and in response to determining that an alternative subtype from the alternative subtypes that is an argument in an expression invocation is incompatible with an expected alternative subtype from the alternative subtypes as the argument in the expression invocation, generating a type error. | 0.901314 |
9,081,769 | 2 | 3 | 2. A computer-implemented method comprising: storing, in a translation repository and by a computing device having one or more processors, translation data representing changes to translations during a time interval between a first time and a second time, the translation data identifying text messages in a first language, respective identifiers for each of the text messages, and corresponding translations of a plurality of the text messages into a second language; including, by the computing device, one or more of the respective identifiers in a source code project; building, by the computing device, the source code project into a reference application in the second language, comprising: replacing the identifier of each text message in the source code project with a translation of the text message in the second language made at the second time, and for a text message whose translation has changed during the time interval, inserting the identifier of the text message whose translation has changed as hidden information associated with the translation of the text message, wherein the identifier for a text message whose translation has not changed during the time window is not inserted as hidden information associated with the translation of the text message in the reference application; and rendering, by the computing device, the reference application for presentation to a user for translation checking, including highlighting the text messages that have an associated hidden identifier. | 2. A computer-implemented method comprising: storing, in a translation repository and by a computing device having one or more processors, translation data representing changes to translations during a time interval between a first time and a second time, the translation data identifying text messages in a first language, respective identifiers for each of the text messages, and corresponding translations of a plurality of the text messages into a second language; including, by the computing device, one or more of the respective identifiers in a source code project; building, by the computing device, the source code project into a reference application in the second language, comprising: replacing the identifier of each text message in the source code project with a translation of the text message in the second language made at the second time, and for a text message whose translation has changed during the time interval, inserting the identifier of the text message whose translation has changed as hidden information associated with the translation of the text message, wherein the identifier for a text message whose translation has not changed during the time window is not inserted as hidden information associated with the translation of the text message in the reference application; and rendering, by the computing device, the reference application for presentation to a user for translation checking, including highlighting the text messages that have an associated hidden identifier. 3. The method of claim 2 , wherein the translation data is represented as a list. | 0.919162 |
9,940,581 | 1 | 8 | 1. A method of distinguishing a business rule from a non-business rule in a computer program, the method comprising the steps of: a computer identifying a first rule in the computer program based on a conditional statement within the first rule; the computer determining whether the first rule performs an underlying operation of the program, the underlying operating being independent of a business function of the program, by determining whether the first rule includes a first key word which indicates the underlying operation, which is a housekeeping process, exception handling, error checking, data validation, parameter cleanup, a reservation of computer memory, or a buffer setup; the computer determining whether a sequence of program steps in the first rule matches a predetermined sequence of program steps indicative of the underlying operation of the program independent of the business function of the program; if the first rule includes the first key word or the sequence of program steps in the first rule matches the predetermined sequence of steps indicative of the underlying operation of the program independent of the business function of the program, the computer determining the first rule is a non-business rule, or if the first rule does not include the first key word and no sequence of program steps in the first rule matches the predetermined sequence of program steps indicative of the underlying operation of the program independent of the business function of the program, the computer: searching the first rule and metadata of the first rule for a second key word which indicates part of a business transaction with a customer of a business using the computer program; determining whether a sequence of program steps in the first rule matches a predetermined sequence of program steps indicative of a business rule; and if the first rule includes the second key word, the metadata of the first rule includes the second key word, or the sequence of program steps in the first rule matches the predetermined sequence of program steps indicative of the business rule, determining the first rule is the business rule, or if the first rule and the metadata of the first rule do not include the second key word and no sequence of program steps in the first rule matches the predetermined sequence of program steps indicative of the business rule, determining the first rule is not classifiable as the business rule or the non-business rule; the computer receiving a first set of one or more semantic tags specifying a first candidate business rule in the computer program, the first candidate business rule being initially not classifiable as a first actual business rule or a first actual non-business rule; based on the first set of one or more semantic tags, the computer determining the first candidate business rule is specified by a pattern expressed in a context-free grammar for a programming language of the computer program, the pattern specifying a code structure included in the first candidate business rule, the pattern being included in a class of an ontology, and the class identifying a concept of the programming language; the computer determining that a confidence level of the pattern is less than a first threshold, the confidence level indicating how likely the first candidate business rule is the first actual business rule, and the ontology associating the pattern with the confidence level; based on the confidence level being less than the first threshold, the computer determining a lack of confidence in the first candidate business rule being the first actual business rule; the computer receiving other sets of one or more semantic tags specifying other candidate business rules, each of the other sets of one or more semantic tags being identical to the first set of one or more semantic tags, and each of the other candidate business rules being not classifiable as an actual business rule or an actual non-business rule; based on the other sets of one or more semantic tags being identical to the first set of one or more semantic tags, the computer determining the other candidate business rules are specified by the pattern that also specifies the first candidate business rule; based on the other candidate business rules being specified by the pattern that also specifies the first candidate business rule, the computer determining that the other candidate business rules include the code structure specified by the pattern; the computer determining a count of candidate business rules among the first candidate business rule and the other candidate business rules that include the code structure specified by the pattern; the computer determining that the count of the candidate business rules exceeds a second threshold; based on the count of the candidate business rules exceeding the second threshold, the computer increasing the confidence level of the pattern which indicates an increase in a likelihood that the candidate business rules are actual business rules; the computer updating the ontology to associate the pattern with the increased confidence level; the computer determining the increased confidence level of the pattern is greater than the first threshold; subsequent to the step of determining the increased confidence level is greater than the first threshold, the computer receiving a second set of one or more semantic tags specifying a second candidate business rule in the computer program or in another computer program; the computer determining that the second candidate business rule includes the code structure specified by the pattern and determining that the second set of one or more semantic tags matches the first set of one or more semantic tags; and based on the second candidate business rule including the code structure specified by the pattern, the second set of one or more semantic tags matching the first set of one or more semantic tags, and the updated ontology associating the pattern with the increased confidence level, the computer automatically determining that the second candidate business rule is a second actual business rule, without a manual classification of the second candidate business rule as the second actual business rule by a human expert; and the computer displaying the second candidate business rule as the second actual business rule. | 1. A method of distinguishing a business rule from a non-business rule in a computer program, the method comprising the steps of: a computer identifying a first rule in the computer program based on a conditional statement within the first rule; the computer determining whether the first rule performs an underlying operation of the program, the underlying operating being independent of a business function of the program, by determining whether the first rule includes a first key word which indicates the underlying operation, which is a housekeeping process, exception handling, error checking, data validation, parameter cleanup, a reservation of computer memory, or a buffer setup; the computer determining whether a sequence of program steps in the first rule matches a predetermined sequence of program steps indicative of the underlying operation of the program independent of the business function of the program; if the first rule includes the first key word or the sequence of program steps in the first rule matches the predetermined sequence of steps indicative of the underlying operation of the program independent of the business function of the program, the computer determining the first rule is a non-business rule, or if the first rule does not include the first key word and no sequence of program steps in the first rule matches the predetermined sequence of program steps indicative of the underlying operation of the program independent of the business function of the program, the computer: searching the first rule and metadata of the first rule for a second key word which indicates part of a business transaction with a customer of a business using the computer program; determining whether a sequence of program steps in the first rule matches a predetermined sequence of program steps indicative of a business rule; and if the first rule includes the second key word, the metadata of the first rule includes the second key word, or the sequence of program steps in the first rule matches the predetermined sequence of program steps indicative of the business rule, determining the first rule is the business rule, or if the first rule and the metadata of the first rule do not include the second key word and no sequence of program steps in the first rule matches the predetermined sequence of program steps indicative of the business rule, determining the first rule is not classifiable as the business rule or the non-business rule; the computer receiving a first set of one or more semantic tags specifying a first candidate business rule in the computer program, the first candidate business rule being initially not classifiable as a first actual business rule or a first actual non-business rule; based on the first set of one or more semantic tags, the computer determining the first candidate business rule is specified by a pattern expressed in a context-free grammar for a programming language of the computer program, the pattern specifying a code structure included in the first candidate business rule, the pattern being included in a class of an ontology, and the class identifying a concept of the programming language; the computer determining that a confidence level of the pattern is less than a first threshold, the confidence level indicating how likely the first candidate business rule is the first actual business rule, and the ontology associating the pattern with the confidence level; based on the confidence level being less than the first threshold, the computer determining a lack of confidence in the first candidate business rule being the first actual business rule; the computer receiving other sets of one or more semantic tags specifying other candidate business rules, each of the other sets of one or more semantic tags being identical to the first set of one or more semantic tags, and each of the other candidate business rules being not classifiable as an actual business rule or an actual non-business rule; based on the other sets of one or more semantic tags being identical to the first set of one or more semantic tags, the computer determining the other candidate business rules are specified by the pattern that also specifies the first candidate business rule; based on the other candidate business rules being specified by the pattern that also specifies the first candidate business rule, the computer determining that the other candidate business rules include the code structure specified by the pattern; the computer determining a count of candidate business rules among the first candidate business rule and the other candidate business rules that include the code structure specified by the pattern; the computer determining that the count of the candidate business rules exceeds a second threshold; based on the count of the candidate business rules exceeding the second threshold, the computer increasing the confidence level of the pattern which indicates an increase in a likelihood that the candidate business rules are actual business rules; the computer updating the ontology to associate the pattern with the increased confidence level; the computer determining the increased confidence level of the pattern is greater than the first threshold; subsequent to the step of determining the increased confidence level is greater than the first threshold, the computer receiving a second set of one or more semantic tags specifying a second candidate business rule in the computer program or in another computer program; the computer determining that the second candidate business rule includes the code structure specified by the pattern and determining that the second set of one or more semantic tags matches the first set of one or more semantic tags; and based on the second candidate business rule including the code structure specified by the pattern, the second set of one or more semantic tags matching the first set of one or more semantic tags, and the updated ontology associating the pattern with the increased confidence level, the computer automatically determining that the second candidate business rule is a second actual business rule, without a manual classification of the second candidate business rule as the second actual business rule by a human expert; and the computer displaying the second candidate business rule as the second actual business rule. 8. The method of claim 1 , wherein the step of determining whether the first rule includes the first key word which indicates the underlying operation includes determining the first rule includes the first key word, which indicates a check that a statement in the program is successfully executed or a check that the program was abnormally terminated, wherein the step of determining the first rule is the non-business rule is based in part on the first rule including the first key word indicating the check that the statement in the program is successfully executed or the check that the program was abnormally terminated. | 0.911212 |
6,023,670 | 4 | 5 | 4. The method as recited in claim 2, wherein one sample count is produced for each matching word in the document and the sample counts and reference counts comprise counts for individual words in a plurality of candidate languages. | 4. The method as recited in claim 2, wherein one sample count is produced for each matching word in the document and the sample counts and reference counts comprise counts for individual words in a plurality of candidate languages. 5. The method as recited in claim 4, wherein a count for a word is dropped from the correlating step if the count for the word in the reference count and the sample count are both zero. | 0.917115 |
4,400,828 | 7 | 8 | 7. A method for recognizing an input word as one of a set of reference words comprising the steps of storing a plurality of reference word feature templates representative of said reference words; generating an input word feature template responsive to said input word; identifying said input word as one of said reference words responsive to said reference word feature templates and said input word feature template, characterized in that said input word identifying step comprises generating a set of word distance signals responsive to said reference word feature templates and said input word feature template; said reference word feature templates and said input word feature template each have a plurality of frames; said step for generating a set of word distance signals comprises generating a set of frame distance signals representative of the similarity between frames of said reference word feature templates and said input word feature template responsive to said reference word feature templates and said input word feature template, and combining said frame distance signals to produce said word distance signals; generating a set of weighted word distance signals responsive to said reference word feature templates and said input word feature template; and selecting the reference word which most corresponds to said input word responsive to said word distance signals and said weighted word distance signals. | 7. A method for recognizing an input word as one of a set of reference words comprising the steps of storing a plurality of reference word feature templates representative of said reference words; generating an input word feature template responsive to said input word; identifying said input word as one of said reference words responsive to said reference word feature templates and said input word feature template, characterized in that said input word identifying step comprises generating a set of word distance signals responsive to said reference word feature templates and said input word feature template; said reference word feature templates and said input word feature template each have a plurality of frames; said step for generating a set of word distance signals comprises generating a set of frame distance signals representative of the similarity between frames of said reference word feature templates and said input word feature template responsive to said reference word feature templates and said input word feature template, and combining said frame distance signals to produce said word distance signals; generating a set of weighted word distance signals responsive to said reference word feature templates and said input word feature template; and selecting the reference word which most corresponds to said input word responsive to said word distance signals and said weighted word distance signals. 8. A method for recognizing an input word as one of a set of reference words according to claim 7 further characterized in that said reference words for which feature templates are stored belong to a predetermined set of equivalence classes, each class being representative of reference words which are within a prescribed degree of similarity; and said step for generating a set of weighted word distance signals comprises storing a plurality of weight templates representative of the expected similarity between frames of reference word feature templates for reference words which belong to the same equivalence class; generating weighted frame distance signals responsive to said frame distance signals and said weight templates; and combining said weighted frame distance signals to obtain said weighted word distance signals. | 0.7132 |
9,336,271 | 1 | 2 | 1. A method of optimizing a query, comprising: determining a cost estimate for a query; determining a budget for optimizing the query based on the cost estimate; determining a normalized complexity of the query; determining a strategy based on the normalized complexity and the budget, wherein the strategy specifies a limit to a search space enumerated during optimization of the query; and optimizing the query based on the strategy. | 1. A method of optimizing a query, comprising: determining a cost estimate for a query; determining a budget for optimizing the query based on the cost estimate; determining a normalized complexity of the query; determining a strategy based on the normalized complexity and the budget, wherein the strategy specifies a limit to a search space enumerated during optimization of the query; and optimizing the query based on the strategy. 2. The method recited in claim 1 , wherein the strategy comprises: a maximum pass parameter specifying a limit to a number of passes performed by a multi-pass optimizer, wherein the multi-pass optimizer optimizes the query; and a potential threshold, wherein a portion of the search space exceeding the potential threshold is not enumerated during optimization. | 0.851195 |
7,921,390 | 23 | 24 | 23. The program storage device of claim 20 including representing said output as part of said software layer of said design tool, and deleting said output when no longer required. | 23. The program storage device of claim 20 including representing said output as part of said software layer of said design tool, and deleting said output when no longer required. 24. The program storage device of claim 23 including having said software layer presented in a pop-up window display. | 0.948184 |
8,627,210 | 14 | 16 | 14. An apparatus comprising: a network interface unit that is configured to enable communication over a network with a user interface and display device associated with each of a plurality of meeting participants; a memory configured to store data for a plurality of meeting participants involved in a meeting; and a data processor configured to: obtain a meeting context for the meeting; identify expert knowledge associated with the meeting context; determine the expert knowledge of each meeting participant with regard to the meeting context; generate data representing social network relationships between the meeting participants; calculate degrees of associations between meeting participants based on the expert knowledge of the meeting participants and the social network relationships, wherein to calculate the degrees of associations, the social network relationships between the meeting participants are dynamically weighted with reference to the meeting context to produce a single degree of association quantity between two meeting participants with respect to the meeting context; and generate, for each meeting participant, data that represents single degree of association quantities between the meeting participant and the other meeting participants. | 14. An apparatus comprising: a network interface unit that is configured to enable communication over a network with a user interface and display device associated with each of a plurality of meeting participants; a memory configured to store data for a plurality of meeting participants involved in a meeting; and a data processor configured to: obtain a meeting context for the meeting; identify expert knowledge associated with the meeting context; determine the expert knowledge of each meeting participant with regard to the meeting context; generate data representing social network relationships between the meeting participants; calculate degrees of associations between meeting participants based on the expert knowledge of the meeting participants and the social network relationships, wherein to calculate the degrees of associations, the social network relationships between the meeting participants are dynamically weighted with reference to the meeting context to produce a single degree of association quantity between two meeting participants with respect to the meeting context; and generate, for each meeting participant, data that represents single degree of association quantities between the meeting participant and the other meeting participants. 16. The apparatus of claim 14 , wherein the data processor is configured to obtain the meeting context based on meeting agenda information associated with the meeting. | 0.853251 |
9,009,149 | 12 | 20 | 12. One or more computing devices associated with a server computing system for determining one or more ranked candidate media in response to media query data generated at a mobile client device corresponding to a query media, the computing devices comprising: one or more processors; and one or more computer-readable non-transitory storage media embodying software that is configured when executed by one or more of the processors to: receive the media query data from the mobile device, the media query data comprising feature data of one or more features of a query media encoded by a similarity preserving hashing function into a plurality of hash bits and coordinate data for each of the one or more features; match the one or more of the features with one or more corresponding features of an media database using the feature data to identify one or more features of the query media within a predetermined hamming distance in a hash table from the one or more corresponding features of the media database to obtain one or more matched features in the media database, the features of the query media and the features of the media database each being assigned to one of a plurality of entries of the one or more hash tables using the plurality of hash bits as table indexes; determine one or more candidate media whose number of matched features exceed a matched feature threshold; generate a geometry similarity score between the query media and each of the one or more candidate media using the feature data and the coordinate data; rank the one or more candidate media based on the numbers of matched features and the geometry similarity score; and send the ranked candidate media to the mobile client device. | 12. One or more computing devices associated with a server computing system for determining one or more ranked candidate media in response to media query data generated at a mobile client device corresponding to a query media, the computing devices comprising: one or more processors; and one or more computer-readable non-transitory storage media embodying software that is configured when executed by one or more of the processors to: receive the media query data from the mobile device, the media query data comprising feature data of one or more features of a query media encoded by a similarity preserving hashing function into a plurality of hash bits and coordinate data for each of the one or more features; match the one or more of the features with one or more corresponding features of an media database using the feature data to identify one or more features of the query media within a predetermined hamming distance in a hash table from the one or more corresponding features of the media database to obtain one or more matched features in the media database, the features of the query media and the features of the media database each being assigned to one of a plurality of entries of the one or more hash tables using the plurality of hash bits as table indexes; determine one or more candidate media whose number of matched features exceed a matched feature threshold; generate a geometry similarity score between the query media and each of the one or more candidate media using the feature data and the coordinate data; rank the one or more candidate media based on the numbers of matched features and the geometry similarity score; and send the ranked candidate media to the mobile client device. 20. The computing devices of claim 12 , wherein the software is further configured to generate the geometry similarity score by determining a length ratio between the one or more features of the query media and corresponding matched features of the candidate media using the coordinate data. | 0.745184 |
8,631,318 | 10 | 11 | 10. A software product including instructions tangibly embodied in a non-transitory computer readable medium to cause a client device to perform operations for managing electronic documents including metadata related to broadcasting multimedia content, the operations comprising: receiving an electronic document at the client device, the electronic document including metadata related to broadcasting multimedia content and having a defined structure including two or more structural elements, each of the two or more structural elements associated with a respective identifier and a respective version value representing a corresponding date; sending a request from the client device to a server for an update to the electronic document, wherein the request includes a first version value representing a first date; receiving an update document at the client device in response to the request, wherein the update document includes both updated information and invalidity information for the electronic document, wherein the updated information includes one or more structural elements updated after the first date, and the invalidity information includes a first identifier and a second version value representing a second date to indicate invalidity of a first structural element that has the first identifier and is associated with the second date, and wherein the first identifier is reused in the update to the electronic document for identifying a second structural element other than the first structural element; and processing the received invalidity information at the client device to identify the invalid first structural element based on the first identifier and the corresponding second version value. | 10. A software product including instructions tangibly embodied in a non-transitory computer readable medium to cause a client device to perform operations for managing electronic documents including metadata related to broadcasting multimedia content, the operations comprising: receiving an electronic document at the client device, the electronic document including metadata related to broadcasting multimedia content and having a defined structure including two or more structural elements, each of the two or more structural elements associated with a respective identifier and a respective version value representing a corresponding date; sending a request from the client device to a server for an update to the electronic document, wherein the request includes a first version value representing a first date; receiving an update document at the client device in response to the request, wherein the update document includes both updated information and invalidity information for the electronic document, wherein the updated information includes one or more structural elements updated after the first date, and the invalidity information includes a first identifier and a second version value representing a second date to indicate invalidity of a first structural element that has the first identifier and is associated with the second date, and wherein the first identifier is reused in the update to the electronic document for identifying a second structural element other than the first structural element; and processing the received invalidity information at the client device to identify the invalid first structural element based on the first identifier and the corresponding second version value. 11. The software product of claim 10 , wherein said electronic document is in XML format. | 0.505556 |
8,977,614 | 1 | 8 | 1. A method of providing search results and advertisements to a user, the method comprising: maintaining a user profile associated with the user; receiving a search request comprising a search argument from the user; searching at least one contextual database based on the search argument to produce at least one search result; selecting at least one advertisement from an advertisement database based on the user profile and the search argument; providing the at least one search result and the at least one advertisement to the user; receiving search refinement input from the user; producing at least one modified search result based on at least the search refinement input; updating the at least one advertisement selected from the advertisement database based on the user profile and the search refinement input; and providing at least one of the at least one modified search result and the updated at least one advertisement to the user. | 1. A method of providing search results and advertisements to a user, the method comprising: maintaining a user profile associated with the user; receiving a search request comprising a search argument from the user; searching at least one contextual database based on the search argument to produce at least one search result; selecting at least one advertisement from an advertisement database based on the user profile and the search argument; providing the at least one search result and the at least one advertisement to the user; receiving search refinement input from the user; producing at least one modified search result based on at least the search refinement input; updating the at least one advertisement selected from the advertisement database based on the user profile and the search refinement input; and providing at least one of the at least one modified search result and the updated at least one advertisement to the user. 8. The method of claim 1 , wherein the search refinement input is based on selection by the user of at least one of the at least one search result and the at least one advertisement provided to the user. | 0.79901 |
7,565,606 | 1 | 2 | 1. A method of spell checking a document, the method comprising: spell checking the document by comparing terms in the document against an electronic dictionary; and in response to determining during spell checking that a term from the document is not in the electronic dictionary, automatically scanning a plurality of documents from the Internet to identify at least one acceptable usage of the term. | 1. A method of spell checking a document, the method comprising: spell checking the document by comparing terms in the document against an electronic dictionary; and in response to determining during spell checking that a term from the document is not in the electronic dictionary, automatically scanning a plurality of documents from the Internet to identify at least one acceptable usage of the term. 2. The method of claim 1 , further comprising: tracking relative occurrences of a plurality of variants of the term found in the plurality of documents; and displaying results of such tracking to a user. | 0.603516 |
7,844,502 | 19 | 34 | 19. An automated shopping method for automated management of a process in which a user places an order for at least one provider, a degree of matching between each order-provider pairing is computed, and a score is reported to at least the user and optionally to at least one provider, the automated shopping method comprising: providing (a) at least one processor to receive and process information including at least one of (i) user information from at least one user including information that specifies provider criteria and order information that specifies order criteria for that particular order, (ii) provider information, and (iii) third party information; (b) at least one data storage device that communicates with the at least one processor, that includes at least one database, and that receives and stores the information in the at least one database; and (c) a knowledge base that is stored in a data storage device which may be said at least one data storage device, and that contains information on which to base requests for information by the automated shopping method; receiving information (a) from the user including information that specifies provider criteria and order information that specifies order criteria for that particular order, and (b) from the at least one provider; creating at least one virtual provider with program code within the at least one processor by pairing provider information of a particular provider with order information of a particular order to create an informational pair, and storing the at least one virtual provider within the at least one database; determining a score that reflects a degree of matching for each respective informational pair using a scoring system that resides in program code within the at least one processor, and that compares the provider information of a particular provider and the order information of a particular order within each respective informational pair in at least one step; and tracking each order-provider pairing through multiple steps using a management system that resides in program code within the at least one processor, and that uses sequencing to specify contents of each step of the multiple steps, the contents at least including instructions to at least one of (a) the user regarding the input of user information, (b) the provider regarding the input of provider information, and (c) third parties regarding the input of information. | 19. An automated shopping method for automated management of a process in which a user places an order for at least one provider, a degree of matching between each order-provider pairing is computed, and a score is reported to at least the user and optionally to at least one provider, the automated shopping method comprising: providing (a) at least one processor to receive and process information including at least one of (i) user information from at least one user including information that specifies provider criteria and order information that specifies order criteria for that particular order, (ii) provider information, and (iii) third party information; (b) at least one data storage device that communicates with the at least one processor, that includes at least one database, and that receives and stores the information in the at least one database; and (c) a knowledge base that is stored in a data storage device which may be said at least one data storage device, and that contains information on which to base requests for information by the automated shopping method; receiving information (a) from the user including information that specifies provider criteria and order information that specifies order criteria for that particular order, and (b) from the at least one provider; creating at least one virtual provider with program code within the at least one processor by pairing provider information of a particular provider with order information of a particular order to create an informational pair, and storing the at least one virtual provider within the at least one database; determining a score that reflects a degree of matching for each respective informational pair using a scoring system that resides in program code within the at least one processor, and that compares the provider information of a particular provider and the order information of a particular order within each respective informational pair in at least one step; and tracking each order-provider pairing through multiple steps using a management system that resides in program code within the at least one processor, and that uses sequencing to specify contents of each step of the multiple steps, the contents at least including instructions to at least one of (a) the user regarding the input of user information, (b) the provider regarding the input of provider information, and (c) third parties regarding the input of information. 34. The automated shopping method of claim 19 , wherein requests for additional information continue until sufficient information is received. | 0.844298 |
9,171,272 | 9 | 16 | 9. One or more computer-readable storage memory storing computer-executable instructions for executing on a computer system a computer process, wherein the computer-readable storage memory is an article of manufacture, the computer process comprising: providing a first data feed and a first plurality of applications associated with the first data feed; obtaining a second data feed; automatically without user intervention: determining applicability of the first data feed to the second data feed according to an applicability criterion; extracting expressions from the first plurality of applications associated with the first data feed based on the applicability criterion relative to the second data feed, wherein the extracted expressions satisfy the applicability criterion relative to the second data feed; and generating one or more new applications to evaluate data from the second data feed, wherein the one or more new applications include the extracted expressions, wherein the generated one or more new applications are executable at a user device allowing a user to interact with the data of the second data feed; and adjusting availability of individual ones of the generated one or more new applications to a plurality of users based on a plurality of instances of feedback received from the plurality of users who used the generated one or more of the new applications in association with the second data feed, each instance of feedback indicating which of the generated one or more new applications met one or more interests of the user in association with the second data feed. | 9. One or more computer-readable storage memory storing computer-executable instructions for executing on a computer system a computer process, wherein the computer-readable storage memory is an article of manufacture, the computer process comprising: providing a first data feed and a first plurality of applications associated with the first data feed; obtaining a second data feed; automatically without user intervention: determining applicability of the first data feed to the second data feed according to an applicability criterion; extracting expressions from the first plurality of applications associated with the first data feed based on the applicability criterion relative to the second data feed, wherein the extracted expressions satisfy the applicability criterion relative to the second data feed; and generating one or more new applications to evaluate data from the second data feed, wherein the one or more new applications include the extracted expressions, wherein the generated one or more new applications are executable at a user device allowing a user to interact with the data of the second data feed; and adjusting availability of individual ones of the generated one or more new applications to a plurality of users based on a plurality of instances of feedback received from the plurality of users who used the generated one or more of the new applications in association with the second data feed, each instance of feedback indicating which of the generated one or more new applications met one or more interests of the user in association with the second data feed. 16. The one or more computer-readable storage memory of claim 9 wherein the adjusting operation comprises: identifying a generated new application for manual adjustment, if the plurality of instances of feedback are negative. | 0.595324 |
8,244,649 | 1 | 5 | 1. A method for training a control system using structured differential learning, the method comprising: analyzing, by a plurality of analyzing components, a set of features extracted from a set of input data; generating, by each analyzing component in the plurality of analyzing components, for each feature an output response regarding whether the each feature has an acceptable value associated therewith relative to a value of a parameter associated with the each analyzing component; associating a confidence score with the each output response; combining each output response and each confidence score into a single final output response and single final confidence score; and identifying, based at least on the confidence score, which analyzing component in the plurality of analyzing components is a strongest candidate for generating an incorrect final output response. | 1. A method for training a control system using structured differential learning, the method comprising: analyzing, by a plurality of analyzing components, a set of features extracted from a set of input data; generating, by each analyzing component in the plurality of analyzing components, for each feature an output response regarding whether the each feature has an acceptable value associated therewith relative to a value of a parameter associated with the each analyzing component; associating a confidence score with the each output response; combining each output response and each confidence score into a single final output response and single final confidence score; and identifying, based at least on the confidence score, which analyzing component in the plurality of analyzing components is a strongest candidate for generating an incorrect final output response. 5. The method of claim 1 , wherein identifying which analyzing component in the plurality of analyzing components is a strongest candidate for generating an incorrect final output response further comprises: analyzing the confidence score for each output response; and identifying, based on the analyzing, the analyzing component associated with a lowest confidence score. | 0.798483 |
5,579,416 | 42 | 43 | 42. A method according to claim 41, wherein the graphic patterns corresponding to the character patterns represent a variety of kinds of modifying information. | 42. A method according to claim 41, wherein the graphic patterns corresponding to the character patterns represent a variety of kinds of modifying information. 43. A method according to claim 42, wherein the graphic patterns corresponding to the character patterns represent various modifications of the same character. | 0.950835 |
9,811,937 | 1 | 9 | 1. A method, comprising: generating a data model for a first conversational gesture type, by analyzing captured video data to determine motion attribute data for a plurality of conversational gestures; upon receiving a request to splice a gesture of the first conversational gesture type into a first animation, determining a locomotion of a first virtual character, while the first virtual character is interacting with a second virtual character within the first animation; stylizing, by operation of one or more computer processors, a gesture of the first conversational gesture type to match style criteria associated with the locomotion of the first virtual character based on the motion attribute data of the generated data model for the first conversational gesture type; and splicing the stylized gesture into the locomotion of the first virtual character within the first animation. | 1. A method, comprising: generating a data model for a first conversational gesture type, by analyzing captured video data to determine motion attribute data for a plurality of conversational gestures; upon receiving a request to splice a gesture of the first conversational gesture type into a first animation, determining a locomotion of a first virtual character, while the first virtual character is interacting with a second virtual character within the first animation; stylizing, by operation of one or more computer processors, a gesture of the first conversational gesture type to match style criteria associated with the locomotion of the first virtual character based on the motion attribute data of the generated data model for the first conversational gesture type; and splicing the stylized gesture into the locomotion of the first virtual character within the first animation. 9. The method of claim 1 , further comprising: rendering a plurality of frames of video data, based on the first animation containing the spliced gesture of the first conversational gesture type into the movement of the first virtual character. | 0.820852 |
9,356,574 | 26 | 32 | 26. The method of claim 23 , further comprising: receiving the first search query at a search engine service; constructing, in response to receiving the first search query, the first set of one or more response snippets using information from the first server content version of the sourced document; generating the first query response document comprising the first set of one or more response snippets; transmitting the second query response document from the search engine service to the user agent; receiving the second search query at the search engine service; constructing, in response to receiving the second search query, the second set of one or more response snippets using information from the second server content version of the sourced document; generating the second query response document comprising the second set of one or more response snippets; and transmitting the second query response document from the search engine service to the user agent. | 26. The method of claim 23 , further comprising: receiving the first search query at a search engine service; constructing, in response to receiving the first search query, the first set of one or more response snippets using information from the first server content version of the sourced document; generating the first query response document comprising the first set of one or more response snippets; transmitting the second query response document from the search engine service to the user agent; receiving the second search query at the search engine service; constructing, in response to receiving the second search query, the second set of one or more response snippets using information from the second server content version of the sourced document; generating the second query response document comprising the second set of one or more response snippets; and transmitting the second query response document from the search engine service to the user agent. 32. The method of claim 26 , further comprising: retrieving the first server content version of the sourced document from a document source to the search engine service; and retrieving, in response to the first selection input, the first client content version from the document source to the user agent. | 0.934483 |
8,650,181 | 9 | 13 | 9. A system comprising: one or more computers; a database; an online analytic processor (OLAP), executing on the one or more computers, to receive a first query; a model, the model specifying a graph defining a plurality of nodes on a plurality of tiers, each node corresponding to a different operation on data, wherein the OLAP generates a second query based on the model, the second query including a plurality of layered subqueries each corresponding to one of the nodes in the graph for specifying the different operations on data; and a relational engine coupled to a datastore to receive the second query, wherein the relational engine executes the second query, and in accordance therewith, retrieves data, wherein the plurality of nodes includes a root node on a first tier, a plurality of second tier nodes on a second tier, and one or more higher tier nodes on a plurality of tiers above the first tier and the second tier, wherein the root node has a corresponding first subquery to operate on raw data in the database to retrieve first data, wherein the first data comprises all the data required to answer the first query, wherein the plurality of second tier nodes are coupled to the root node in the graph and each have corresponding subqueries that perform different operations on the first data, wherein at least one of the second tier nodes is coupled to the one or more higher tier nodes, wherein each higher tier node has a corresponding subquery for operating on data generated by the subquery of the at least one second tier node; wherein the OLAP generates an answer to the first query by operating the plurality of layered subqueries on the first data only, according to the graph. | 9. A system comprising: one or more computers; a database; an online analytic processor (OLAP), executing on the one or more computers, to receive a first query; a model, the model specifying a graph defining a plurality of nodes on a plurality of tiers, each node corresponding to a different operation on data, wherein the OLAP generates a second query based on the model, the second query including a plurality of layered subqueries each corresponding to one of the nodes in the graph for specifying the different operations on data; and a relational engine coupled to a datastore to receive the second query, wherein the relational engine executes the second query, and in accordance therewith, retrieves data, wherein the plurality of nodes includes a root node on a first tier, a plurality of second tier nodes on a second tier, and one or more higher tier nodes on a plurality of tiers above the first tier and the second tier, wherein the root node has a corresponding first subquery to operate on raw data in the database to retrieve first data, wherein the first data comprises all the data required to answer the first query, wherein the plurality of second tier nodes are coupled to the root node in the graph and each have corresponding subqueries that perform different operations on the first data, wherein at least one of the second tier nodes is coupled to the one or more higher tier nodes, wherein each higher tier node has a corresponding subquery for operating on data generated by the subquery of the at least one second tier node; wherein the OLAP generates an answer to the first query by operating the plurality of layered subqueries on the first data only, according to the graph. 13. The system of claim 9 wherein each subquery is a database view containing a SQL statement. | 0.916519 |
8,103,691 | 25 | 26 | 25. The system as claimed in claim 16 , wherein user's Human Operating System (HOS) adapted to customize, personalize and configure as per survey data including customize, personalize and configure one or more applications, services, shared contents and profile(s) for other one or more connected users. | 25. The system as claimed in claim 16 , wherein user's Human Operating System (HOS) adapted to customize, personalize and configure as per survey data including customize, personalize and configure one or more applications, services, shared contents and profile(s) for other one or more connected users. 26. The system as claimed in claim 25 , wherein one or more other connected users comprise one or more personal and social networks or groups. | 0.972671 |
7,706,616 | 1 | 22 | 1. A method of recognizing words, comprising: accepting a stroke as an input on a virtual keyboard coupled to a computer, the computer programmed to perform the steps of: defining word patterns of a plurality of known words by a plurality of paths, wherein each path connects elements in the known word on the virtual keyboard, wherein the virtual keyboard comprises virtual keys, each virtual key representing a letter in a word without a temporary target letter being placed adjacent to a location of a stroke; processing the stroke using a combination of a plurality of channels, each channel selectively measuring a different aspect of a similarity of the stroke to a plurality of possible paths on the virtual keyboard; converting each different aspect of the stroke's similarity to probability estimates; a shape channel of the plurality of channels measuring a shape aspect of the stroke, and outputting a probability estimate; a location channel of the plurality of channels measuring location aspect of the stroke, and outputting a probability estimate, wherein the location channel measures the location aspect of the stroke concurrently with the shape channel measuring the shape aspect of the stroke; mathematically integrating, using Bayes' theorem, the probability estimates of the plurality of channels to produce integrated probability estimates of candidate words corresponding to the stroke; and based on the integrated probability estimates of the candidate words, recognizing the stroke as a known word. | 1. A method of recognizing words, comprising: accepting a stroke as an input on a virtual keyboard coupled to a computer, the computer programmed to perform the steps of: defining word patterns of a plurality of known words by a plurality of paths, wherein each path connects elements in the known word on the virtual keyboard, wherein the virtual keyboard comprises virtual keys, each virtual key representing a letter in a word without a temporary target letter being placed adjacent to a location of a stroke; processing the stroke using a combination of a plurality of channels, each channel selectively measuring a different aspect of a similarity of the stroke to a plurality of possible paths on the virtual keyboard; converting each different aspect of the stroke's similarity to probability estimates; a shape channel of the plurality of channels measuring a shape aspect of the stroke, and outputting a probability estimate; a location channel of the plurality of channels measuring location aspect of the stroke, and outputting a probability estimate, wherein the location channel measures the location aspect of the stroke concurrently with the shape channel measuring the shape aspect of the stroke; mathematically integrating, using Bayes' theorem, the probability estimates of the plurality of channels to produce integrated probability estimates of candidate words corresponding to the stroke; and based on the integrated probability estimates of the candidate words, recognizing the stroke as a known word. 22. The method of claim 1 , including: determining a time spent inputting the stroke; and modifying at least one probability estimate according to a path of the stroke on the virtual keyboard and the time spent inputting the stroke, to produce an output of at least one channel of the plurality of channels. | 0.772593 |
8,284,922 | 1 | 11 | 1. A method for changing a communication quality of a communication session based on a meaning of speech data, the method comprising: parsing speech data exchanged between clients participating in a communication session; determining a meaning of the parsed speech data; and performing an action to change a communication quality of the communication session based on the meaning of the parsed speech data, wherein at least one of the preceding actions is performed on at least one electronic hardware component. | 1. A method for changing a communication quality of a communication session based on a meaning of speech data, the method comprising: parsing speech data exchanged between clients participating in a communication session; determining a meaning of the parsed speech data; and performing an action to change a communication quality of the communication session based on the meaning of the parsed speech data, wherein at least one of the preceding actions is performed on at least one electronic hardware component. 11. The method of claim 1 wherein performing an action to change a communication quality of the communication session includes performing an action by a server used in the communication session, wherein the action includes one of: sending an indication to a communication device used in the communication session to adjust a signal received from a microphone of the communication device; sending an indication to a communication device used in the communication session to adjust a signal sent to a speaker of the communication device; sending an indication to a communication device used in the communication session to adjust a transmission power of the communication device; providing for adjusting a transmission power of signals sent to the communication device; sending an indication to a communication device used in the communication session to adjust a receiver sensitivity of the communication device; providing for a handoff from one communication base station to another for the communication session; providing for adjusting the quality of service for the communication session; providing for changing communication paths for the communication session; providing for performing an error analysis for the communication session; and providing for changing an error correction scheme for the communication session. | 0.500377 |
8,150,841 | 13 | 14 | 13. A computer-implemented method of identifying and clustering queries that are increasing in popularity using a computing system having memory, processor, and data storage subsystems, the computer-implemented method comprising: receiving a search query request from a user input device; identifying a spike in incoming query stream activity comprising the search query request; temporally correlating the spike in the incoming query stream activity with relevant content from a plurality of historical indices as a result of searching said historical indices; correlating the spike in the incoming query stream activity with relevant content from a plurality of fresh indices as a result of searching said fresh indices, wherein the fresh indices contain information and results from recently crawled content sources; analyzing results from searching the historical indices and the fresh indices to determine if the search query request should be clustered with an existing group of search query results; prioritizing results of the search query request according to an age and size of identified cyclic clustered results; and communicating the prioritized results of the search query request to a user output device. | 13. A computer-implemented method of identifying and clustering queries that are increasing in popularity using a computing system having memory, processor, and data storage subsystems, the computer-implemented method comprising: receiving a search query request from a user input device; identifying a spike in incoming query stream activity comprising the search query request; temporally correlating the spike in the incoming query stream activity with relevant content from a plurality of historical indices as a result of searching said historical indices; correlating the spike in the incoming query stream activity with relevant content from a plurality of fresh indices as a result of searching said fresh indices, wherein the fresh indices contain information and results from recently crawled content sources; analyzing results from searching the historical indices and the fresh indices to determine if the search query request should be clustered with an existing group of search query results; prioritizing results of the search query request according to an age and size of identified cyclic clustered results; and communicating the prioritized results of the search query request to a user output device. 14. The computer-implemented method of claim 13 , wherein the searching a plurality of historical indices comprises extracting information from previously stored cyclic clustered results with similar characteristics to the search query request. | 0.880039 |
7,613,731 | 70 | 89 | 70. A computer system for presenting an electronic document to a viewer to facilitate comprehension and control display and speed of delivery, the computer system including a computer program product, the computer program product comprising: program instructions that group selected words into a cognitive cluster to be treated as a single word; program instructions that assign an emphasis value to each word and cognitive cluster in the electronic document using a knowledge database thereby generating a first tagged file of assigned emphasis values for each word and cognitive cluster; program instructions that process the first tagged file, including deriving emphasis values for recognizability and comprehensibility, to generate a second tagged file of derived emphasis values; program instructions that process the second tagged file, including facilitating editing of properties of selected words and cognitive clusters in the electronic document, to generate a property deliverable file that dynamically controls the presentation of the electronic document to the viewer; a printer or an electronic display device; and program instructions that present the electronic document to the viewer on the electronic display device or to the printer. | 70. A computer system for presenting an electronic document to a viewer to facilitate comprehension and control display and speed of delivery, the computer system including a computer program product, the computer program product comprising: program instructions that group selected words into a cognitive cluster to be treated as a single word; program instructions that assign an emphasis value to each word and cognitive cluster in the electronic document using a knowledge database thereby generating a first tagged file of assigned emphasis values for each word and cognitive cluster; program instructions that process the first tagged file, including deriving emphasis values for recognizability and comprehensibility, to generate a second tagged file of derived emphasis values; program instructions that process the second tagged file, including facilitating editing of properties of selected words and cognitive clusters in the electronic document, to generate a property deliverable file that dynamically controls the presentation of the electronic document to the viewer; a printer or an electronic display device; and program instructions that present the electronic document to the viewer on the electronic display device or to the printer. 89. The computer system for presenting an electronic document of claim 70 wherein the computer program product further comprises program instructions that enable editing of the derived recognizability value and the derived comprehensibility value for each word or a portion of the electronic document. | 0.800926 |
8,180,787 | 4 | 6 | 4. The method of claim 1 , wherein each access method is selected from at least two different access method types; wherein each of the different access methods types defines a different manner of exposing the physical data corresponding to the logical field name of the respective logical field definition. | 4. The method of claim 1 , wherein each access method is selected from at least two different access method types; wherein each of the different access methods types defines a different manner of exposing the physical data corresponding to the logical field name of the respective logical field definition. 6. The method of claim 4 , wherein the different access methods types include at least a simple access method type and a filtered access method type; wherein simple access methods map a corresponding logical field name directly to a particular physical data field of the physical data, and wherein filtered access methods map a corresponding logical field name to a subset of physical data corresponding to a particular physical data field of the physical data. | 0.891886 |
7,526,471 | 6 | 9 | 6. A computer-implemented method of processing an abstract query that includes a group of logical fields specified by a field-to-field join constraint, comprising, by operation of a least one processor: receiving, the abstract query from a requesting entity having an interface in which the abstract query was composed, wherein the abstract query is composed from a plurality of logical fields specified in a database abstraction model, and wherein each logical field defines at least an access method that maps the logical field to data in an underlying physical database; generating, from the abstract query, a resolved query of the underlying physical database; the generating being performed by a runtime component; issuing the resolved query to the underlying physical database to retrieve a set of query results; grouping the query results according to the field-to-field join constraint, wherein the field-to-field join constraint specifies how query results retrieved for the group of logical fields should be joined together for purposes of being output; and returning the grouped query results to the requesting entity. | 6. A computer-implemented method of processing an abstract query that includes a group of logical fields specified by a field-to-field join constraint, comprising, by operation of a least one processor: receiving, the abstract query from a requesting entity having an interface in which the abstract query was composed, wherein the abstract query is composed from a plurality of logical fields specified in a database abstraction model, and wherein each logical field defines at least an access method that maps the logical field to data in an underlying physical database; generating, from the abstract query, a resolved query of the underlying physical database; the generating being performed by a runtime component; issuing the resolved query to the underlying physical database to retrieve a set of query results; grouping the query results according to the field-to-field join constraint, wherein the field-to-field join constraint specifies how query results retrieved for the group of logical fields should be joined together for purposes of being output; and returning the grouped query results to the requesting entity. 9. The method of claim 6 , wherein the interface is further configured to allow a user to specify an additional field-to-field join constraint for a group of logical fields. | 0.809471 |
8,843,580 | 1 | 13 | 1. A computer-implemented method of criteria-based message publication control and feedback in a publish/subscribe messaging environment, comprising: receiving, at a message broker, a message published by a message publisher, the message having associated therewith a topic and classification criteria, the classification criteria specifying requirements for determining whether publication of the message is successful; consulting, by the message broker, a subscription registry to locate registered subscriptions of a plurality of message subscribers that have registered with the message broker to receive published messages having the topic, each of the registered subscriptions further specifying subscriber classification information pertaining to the topic; selecting, by the message broker from the located subscriptions, each of at least one of the located subscriptions for which the registered subscriber classification information matches the classification criteria associated with the message, wherein the registered subscriber classification information for at least one of the located subscriptions does not match the classification criteria associated with the message; identifying, for each of the at least one selected subscription, the subscriber that registered the selected subscription; sending the message, by the message broker, to the each identified subscriber; comparing, by the message broker, the subscriber classification information in the at least one selected subscription to the classification criteria associated with the message to determine whether the requirements specified in the classification criteria are met by the at least one selected subscription; and responsive to determining, by the comparing, that the requirements are not met, performing controlled failure handling, the controlled failure handling comprising: responsive to determining that a mode of failure handling applicable for the message indicates a warning mode, sending the message, by the message broker, to each of the message subscribers that registered one of the located subscriptions which was not selected by the selecting and warning the message publisher that publication of the message was not successful; and responsive to determining that the mode of failure handling indicates a failure mode, notifying the message publisher that publication of the message failed while omitting the sending of the message to each of the message subscribers that registered one of the located subscriptions which was not selected by the selecting. | 1. A computer-implemented method of criteria-based message publication control and feedback in a publish/subscribe messaging environment, comprising: receiving, at a message broker, a message published by a message publisher, the message having associated therewith a topic and classification criteria, the classification criteria specifying requirements for determining whether publication of the message is successful; consulting, by the message broker, a subscription registry to locate registered subscriptions of a plurality of message subscribers that have registered with the message broker to receive published messages having the topic, each of the registered subscriptions further specifying subscriber classification information pertaining to the topic; selecting, by the message broker from the located subscriptions, each of at least one of the located subscriptions for which the registered subscriber classification information matches the classification criteria associated with the message, wherein the registered subscriber classification information for at least one of the located subscriptions does not match the classification criteria associated with the message; identifying, for each of the at least one selected subscription, the subscriber that registered the selected subscription; sending the message, by the message broker, to the each identified subscriber; comparing, by the message broker, the subscriber classification information in the at least one selected subscription to the classification criteria associated with the message to determine whether the requirements specified in the classification criteria are met by the at least one selected subscription; and responsive to determining, by the comparing, that the requirements are not met, performing controlled failure handling, the controlled failure handling comprising: responsive to determining that a mode of failure handling applicable for the message indicates a warning mode, sending the message, by the message broker, to each of the message subscribers that registered one of the located subscriptions which was not selected by the selecting and warning the message publisher that publication of the message was not successful; and responsive to determining that the mode of failure handling indicates a failure mode, notifying the message publisher that publication of the message failed while omitting the sending of the message to each of the message subscribers that registered one of the located subscriptions which was not selected by the selecting. 13. The method according to claim 1 , further comprising: forwarding the message, by the message broker, to each of at least one additional message broker to which the message broker is communicably coupled in a cluster environment, each additional message broker having a plurality of registered message subscribers that have registered subscriptions therewith to receive messages, each registered subscription specifying a topic and subscriber classification information; receiving, at the message broker from each of the at least one additional message brokers, feedback regarding sending of the forwarded message by the additional message broker to selected ones of the subscribers registered therewith responsive to the registered topic matching the topic associated with the forwarded message and the registered subscriber classification information matching the classification criteria associated with the forwarded message; and consolidating the feedback received from each of the at least one additional message brokers with feedback created by the message broker regarding the sending of the message to the each identified subscriber; and wherein the notification sent to the message publisher comprises the consolidated feedback. | 0.500403 |
9,483,474 | 17 | 19 | 17. One or more computer storage media with device-executable instructions that, when executed by a computing system, direct the computing system to perform steps comprising: storing, at a memory, a graphical structure comprising a first plurality of nodes each representing a person, and a second plurality of nodes each representing a document in the document repository, the nodes being connected by edges according to automatically observed interactions between the represented people and documents, at least some of the nodes having one or more annotations each denoting a topic, an interaction of the interactions at least partially based on at least one of: a consumption activity by a person represented by a first node of the first plurality of nodes of a document represented by a first node of the second plurality of nodes, or a relationship between a first person represented by the first node of the first plurality of nodes, and a second person represented by a second node of the first plurality of nodes; computing, at a processor, distances between nodes of the graphical structure using the topic annotations; receiving, at an input/output controller, an identifier of a user who is represented by one of the first plurality of nodes; and automatically identifying one or more documents from the document repository, or people from the graphical structure, by using the identifier and using the computed distances between nodes. | 17. One or more computer storage media with device-executable instructions that, when executed by a computing system, direct the computing system to perform steps comprising: storing, at a memory, a graphical structure comprising a first plurality of nodes each representing a person, and a second plurality of nodes each representing a document in the document repository, the nodes being connected by edges according to automatically observed interactions between the represented people and documents, at least some of the nodes having one or more annotations each denoting a topic, an interaction of the interactions at least partially based on at least one of: a consumption activity by a person represented by a first node of the first plurality of nodes of a document represented by a first node of the second plurality of nodes, or a relationship between a first person represented by the first node of the first plurality of nodes, and a second person represented by a second node of the first plurality of nodes; computing, at a processor, distances between nodes of the graphical structure using the topic annotations; receiving, at an input/output controller, an identifier of a user who is represented by one of the first plurality of nodes; and automatically identifying one or more documents from the document repository, or people from the graphical structure, by using the identifier and using the computed distances between nodes. 19. The one or more computer storage media of claim 17 with device-executable instructions that, when executed by a computing system, direct the computing system to perform steps comprising identifying the one or more documents by using the identifier to locate one of the first plurality of nodes by comparing the identifier and data stored with the first plurality of nodes. | 0.501326 |
9,613,149 | 10 | 11 | 10. The method of claim 9 , further comprising, identifying the set of semantic types, each of which corresponds to one or more of the subset of the multiple tags; and updating the mapping stored in the machine-readable storage medium to include each of the set of semantic types. | 10. The method of claim 9 , further comprising, identifying the set of semantic types, each of which corresponds to one or more of the subset of the multiple tags; and updating the mapping stored in the machine-readable storage medium to include each of the set of semantic types. 11. The method of claim 10 , further comprising, indexing the location identifier as being mapped to each of the set of semantic types. | 0.954392 |
8,799,234 | 2 | 6 | 2. The process of claim 1 , wherein each input item and output item comprises a character string, and wherein the library of parses comprises a plurality of semantic entities each comprising an entity class and a collection of fields, and wherein the process action of parsing the input items and the output items to produce a weighted set of parses, comprises the actions of: for each character string representing the input and output items and each semantic entity found in the library of parses, identifying a set of field matches wherein each field match comprising the longest sub-string in the input or output item character string that matches a field of a semantic entity from the library of parses, constructing a parse graph from the set of field matches such that a node exists for each character in the character string, and for each field match a field edge is directed from the node representing the starting character of the field match to the node representing the ending character of the field match, and a delimiter edge is established from each node representing a character in the character string and a node representing any next character in the character string, identifying parse paths through the parse graph, wherein each parse path comprises a sequence of nodes that starts with the node representing the first character in the character string and ends with the node representing the last character in the character string, and whose nodes are alternately connected by an edge that alternates between a field edge and a delimiter edge, such that each identified parse path comprises a sequence of semantic entity field and delimiter pairs, and for each parse path identified, computing a constraint weight factor for each identified parse path which is proportional to the number of constraints associated with the semantic entity under consideration that the parse path satisfies and the constraint weight assigned to each of the satisfied constraints, wherein each semantic entity is associated with a set of weighted constraints specifying field assignments and ordering between fields or delimiters for the semantic entity with the constraint weight of such a constraint being greater for constraints that are more likely to be exhibited by the semantic entity, computing a measure of the similarity between the parse path and each of a set of valid parse descriptors which are associated with the semantic entity, wherein each of the valid parse descriptors comprises a sequence of semantic entity field and delimiter pairs that represents a valid parsing of the semantic entity, computing a weight value for the parse path based on the constraint weight factor and valid parse descriptor similarity measure computed for the parse path, and designating the parse path to be a designated parse descriptor of the semantic entity and associating the designated parse descriptor and the computed weight value with the semantic entity to form a weighted semantic entity and parse descriptor tuple. | 2. The process of claim 1 , wherein each input item and output item comprises a character string, and wherein the library of parses comprises a plurality of semantic entities each comprising an entity class and a collection of fields, and wherein the process action of parsing the input items and the output items to produce a weighted set of parses, comprises the actions of: for each character string representing the input and output items and each semantic entity found in the library of parses, identifying a set of field matches wherein each field match comprising the longest sub-string in the input or output item character string that matches a field of a semantic entity from the library of parses, constructing a parse graph from the set of field matches such that a node exists for each character in the character string, and for each field match a field edge is directed from the node representing the starting character of the field match to the node representing the ending character of the field match, and a delimiter edge is established from each node representing a character in the character string and a node representing any next character in the character string, identifying parse paths through the parse graph, wherein each parse path comprises a sequence of nodes that starts with the node representing the first character in the character string and ends with the node representing the last character in the character string, and whose nodes are alternately connected by an edge that alternates between a field edge and a delimiter edge, such that each identified parse path comprises a sequence of semantic entity field and delimiter pairs, and for each parse path identified, computing a constraint weight factor for each identified parse path which is proportional to the number of constraints associated with the semantic entity under consideration that the parse path satisfies and the constraint weight assigned to each of the satisfied constraints, wherein each semantic entity is associated with a set of weighted constraints specifying field assignments and ordering between fields or delimiters for the semantic entity with the constraint weight of such a constraint being greater for constraints that are more likely to be exhibited by the semantic entity, computing a measure of the similarity between the parse path and each of a set of valid parse descriptors which are associated with the semantic entity, wherein each of the valid parse descriptors comprises a sequence of semantic entity field and delimiter pairs that represents a valid parsing of the semantic entity, computing a weight value for the parse path based on the constraint weight factor and valid parse descriptor similarity measure computed for the parse path, and designating the parse path to be a designated parse descriptor of the semantic entity and associating the designated parse descriptor and the computed weight value with the semantic entity to form a weighted semantic entity and parse descriptor tuple. 6. The process of claim 2 , wherein the process action of computing the weight value for the parse path based on the constraint weight factor and valid parse descriptor similarity measure computed for the parse path, comprises an action of taking the product of the constraint weight factor and the similarity measure. | 0.895326 |
9,377,930 | 1 | 4 | 1. An emoticon input method adapted for a mobile terminal, comprising the steps of: receiving a request of message writing; displaying a plurality of input menus including an emoticon input menu for inputting emoticons along with a message writing display; when the emoticon input menu is selected from the plurality of input menus, entering an emoticon input mode, the plurality of input menus comprises at least two or more input menus selected from a group of an English capital input menu, an English small input menu, a special character input menu, and the emoticon input menu; displaying a plurality of emoticon groups in the emoticon input mode, each of the plurality of emoticon groups including a plurality of emoticons; when an emoticon group is selected from among the plurality of emoticon groups, displaying a plurality of emoticons included in the selected emoticon group; when at least one emoticon is selected from among the plurality of emoticons included in the selected emoticon group, displaying as part of a message the at least one emoticon; receiving an identification of another mobile terminal to receive the message; and transmitting the message including the at least one emoticon to the another mobile terminal based on the identification of the another mobile terminal. | 1. An emoticon input method adapted for a mobile terminal, comprising the steps of: receiving a request of message writing; displaying a plurality of input menus including an emoticon input menu for inputting emoticons along with a message writing display; when the emoticon input menu is selected from the plurality of input menus, entering an emoticon input mode, the plurality of input menus comprises at least two or more input menus selected from a group of an English capital input menu, an English small input menu, a special character input menu, and the emoticon input menu; displaying a plurality of emoticon groups in the emoticon input mode, each of the plurality of emoticon groups including a plurality of emoticons; when an emoticon group is selected from among the plurality of emoticon groups, displaying a plurality of emoticons included in the selected emoticon group; when at least one emoticon is selected from among the plurality of emoticons included in the selected emoticon group, displaying as part of a message the at least one emoticon; receiving an identification of another mobile terminal to receive the message; and transmitting the message including the at least one emoticon to the another mobile terminal based on the identification of the another mobile terminal. 4. The method of claim 1 , wherein the plurality of emoticons are bitmap images. | 0.891599 |
9,753,546 | 17 | 18 | 17. A system comprising: a machine having at least one module, the at least one module comprising at least one processor and being configured to: process a plurality of data frames, each data frame of the plurality of data frames comprising one or more body point locations of each of a plurality of collaborating users that are interfacing with an application at each of a plurality of time intervals; define a spatial volume for each of the plurality of collaborating users based on the plurality of processed data frames; detect a gesture performed by a first collaborating user of the plurality of collaborating users based on the plurality of processed data frames; determine the gesture to be an input gesture based on the gesture performed by the first collaborating user in a first spatial volume; interpret the input gesture based on a context of the first spatial volume, the context of the first spatial volume comprising an intersection volume between the first spatial volume and a second spatial volume for a second collaborating user; and provide an input command to the application based on the interpreted input gesture, the input command being different for the gesture being within the intersection volume than for the gesture being outside of the intersection volume. | 17. A system comprising: a machine having at least one module, the at least one module comprising at least one processor and being configured to: process a plurality of data frames, each data frame of the plurality of data frames comprising one or more body point locations of each of a plurality of collaborating users that are interfacing with an application at each of a plurality of time intervals; define a spatial volume for each of the plurality of collaborating users based on the plurality of processed data frames; detect a gesture performed by a first collaborating user of the plurality of collaborating users based on the plurality of processed data frames; determine the gesture to be an input gesture based on the gesture performed by the first collaborating user in a first spatial volume; interpret the input gesture based on a context of the first spatial volume, the context of the first spatial volume comprising an intersection volume between the first spatial volume and a second spatial volume for a second collaborating user; and provide an input command to the application based on the interpreted input gesture, the input command being different for the gesture being within the intersection volume than for the gesture being outside of the intersection volume. 18. The system of claim 17 , wherein the context of the first spatial volume further comprises a role of the first collaborating user, and the at least one module is further configured to determine the role of the first collaborating user based on an identification of the first collaborating user. | 0.501672 |
9,411,889 | 25 | 33 | 25. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for: partitioning a set of monotonically ordered document identification tags into a plurality of segments, each segment associated with a respective subset of the set of monotonically ordered document identification tags; subdividing each of the segments into a plurality of tiers, wherein each tier is associated with a respective subset of the set of document identification tags, and wherein the plurality of tiers are monotonically ordered with respect to a query-independent document importance metric; receiving query-independent information about a new document, the information including a value of the query-independent document importance metric and a globally unique document identifier for the new document; selecting, based at least in part on the globally unique document identifier, one of the segments; selecting, based at least on the query-independent information, one of the tiers associated with the selected segment; assigning to the new document a document identification tag from the respective subset of document identification tags associated with the selected tier, the assigned document identification tag not previously assigned to any of the documents in a collection of documents; repeating the receiving, selecting a segment, selecting a tier, and assigning, with respect to one or more additional new documents; and wherein the assigned document identification tags are assigned to documents in the collection of documents having globally unique document identifiers associated with the respective segment. | 25. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for: partitioning a set of monotonically ordered document identification tags into a plurality of segments, each segment associated with a respective subset of the set of monotonically ordered document identification tags; subdividing each of the segments into a plurality of tiers, wherein each tier is associated with a respective subset of the set of document identification tags, and wherein the plurality of tiers are monotonically ordered with respect to a query-independent document importance metric; receiving query-independent information about a new document, the information including a value of the query-independent document importance metric and a globally unique document identifier for the new document; selecting, based at least in part on the globally unique document identifier, one of the segments; selecting, based at least on the query-independent information, one of the tiers associated with the selected segment; assigning to the new document a document identification tag from the respective subset of document identification tags associated with the selected tier, the assigned document identification tag not previously assigned to any of the documents in a collection of documents; repeating the receiving, selecting a segment, selecting a tier, and assigning, with respect to one or more additional new documents; and wherein the assigned document identification tags are assigned to documents in the collection of documents having globally unique document identifiers associated with the respective segment. 33. The non-transitory computer readable storage medium of claim 25 , instructions for: when a flush condition is satisfied, performing a flush operation, the flush operation including building a first sorted map and a second sorted map; wherein the first sorted map is keyed and sorted by globally unique identifiers, and includes for each globally unique identifier a corresponding document identification tag; and wherein the second sorted map is keyed and sorted by document identification tags assigned to documents since a prior flush operation, and includes for each such document identification tag a corresponding globally unique identifier. | 0.576271 |
7,650,276 | 15 | 22 | 15. A machine readable medium having instructions stored thereon that when executed by a processor cause a system to: display a user interface, wherein the user interface is operable to display information in a web page, wherein the information is stored in a data source on a business object, collect additional information from a user, and store the additional information in the data source on the business object; provide a data binding tag that defines a rendering boundary within the web page for rendering the information, and rules to be applied when the information is rendered, wherein the data binding tag includes a plurality of attributes; specify, by the data binding tag, a first action which includes reading or updating the information stored in the data source, wherein at least one of the attributes is associated with the first action; specify, using a script, at least one attribute on the data binding tag to reference the data source associated with the first action; and render each item in the first data source on the web page in the user interface with a markup language according to the boundary and the rules defined by the data binding tag and based at least partially on the first action, including evaluation of the script. | 15. A machine readable medium having instructions stored thereon that when executed by a processor cause a system to: display a user interface, wherein the user interface is operable to display information in a web page, wherein the information is stored in a data source on a business object, collect additional information from a user, and store the additional information in the data source on the business object; provide a data binding tag that defines a rendering boundary within the web page for rendering the information, and rules to be applied when the information is rendered, wherein the data binding tag includes a plurality of attributes; specify, by the data binding tag, a first action which includes reading or updating the information stored in the data source, wherein at least one of the attributes is associated with the first action; specify, using a script, at least one attribute on the data binding tag to reference the data source associated with the first action; and render each item in the first data source on the web page in the user interface with a markup language according to the boundary and the rules defined by the data binding tag and based at least partially on the first action, including evaluation of the script. 22. The machine readable medium of claim 15 wherein: the first action can have at least one child action. | 0.816434 |
7,936,339 | 7 | 9 | 7. The method as described in claim 6 wherein a height of said first interface region is dependent on a height of said marking. | 7. The method as described in claim 6 wherein a height of said first interface region is dependent on a height of said marking. 9. The method as described in claim 7 wherein a width of said first interface region is fixed. | 0.97508 |
8,818,984 | 2 | 8 | 2. The method of claim 1 , wherein the generating the search result comprises: converting the search term into a tag vector, wherein the entity is found based on a distance measure of the tag vector of the entity to the tag vector of the search term. | 2. The method of claim 1 , wherein the generating the search result comprises: converting the search term into a tag vector, wherein the entity is found based on a distance measure of the tag vector of the entity to the tag vector of the search term. 8. The method of claim 2 , wherein the distance measure is an earth mover distance measure. | 0.965399 |
8,407,178 | 1 | 5 | 1. A computer-implemented method, comprising: retrieving item preference data for a target user from computer storage, said item preference data reflective of item preferences of the target user; generating a recommendation set using the retrieved item preference data, said recommendation set comprising a computer representation of items predicted to be of interest to the target user; filtering the recommendation set, wherein filtering the recommendation set comprises filtering out a first item from the recommendation set based at least partly on a determination that the first item has at least a threshold degree of similarity to a second item in the recommendation set, said first and second items not being duplicates of each other, said filtering producing a filtered recommendation set that has a higher degree of item diversity than the recommendation set; and outputting at least a portion of the filtered recommendation set for presentation to the target user with a display element that enables the target user to initiate a display of one or more items, including said first item, that were filtered from the recommendation set; said method performed by a computer system that comprises one or more computers. | 1. A computer-implemented method, comprising: retrieving item preference data for a target user from computer storage, said item preference data reflective of item preferences of the target user; generating a recommendation set using the retrieved item preference data, said recommendation set comprising a computer representation of items predicted to be of interest to the target user; filtering the recommendation set, wherein filtering the recommendation set comprises filtering out a first item from the recommendation set based at least partly on a determination that the first item has at least a threshold degree of similarity to a second item in the recommendation set, said first and second items not being duplicates of each other, said filtering producing a filtered recommendation set that has a higher degree of item diversity than the recommendation set; and outputting at least a portion of the filtered recommendation set for presentation to the target user with a display element that enables the target user to initiate a display of one or more items, including said first item, that were filtered from the recommendation set; said method performed by a computer system that comprises one or more computers. 5. The method of claim 1 , wherein the method comprises (1) generating a similarity score that represents a degree of similarity between the first and second items, said similarity score reflecting a degree to which attributes of the first and second items are the same, and (2) using the similarity score to determine whether to filter out one of said first and second items. | 0.740331 |
9,830,311 | 1 | 3 | 1. A method comprising: outputting, by a computing device and for display, a graphical keyboard comprising a plurality of keys; receiving, by the computing device, a plurality of indications of input, each respective indication of input from the plurality of indications of input corresponding to a respective location of the graphical keyboard; and for each respective indication of input from the plurality of indications of input, incrementally: determining, by the computing device and based at least in part on both physical cost values from a spatial model and lexical cost values from a language model, at least one predicted current word based on a set of characters that correspond to the plurality of indications of input, wherein the spatial model comprises at least one respective distribution of touch points that corresponds to at least one respective key of the graphical keyboard, and wherein the at least one predicted current word is determined based on a physical cost value from the spatial model that is modified by a lexical cost value from the language model, the physical cost value representing a first likelihood that the plurality of indications of input correspond to the set of characters, and the lexical cost value representing a second likelihood that the set of characters are included in any word in a lexicon of the language model; determining, by the computing device and based at least in part on the at least one predicted current word, at least one predicted next word that follows the at least one predicted current word; and outputting, by the computing device and for display, the at least one predicted current word and the at least one predicted next word as a soft commit word in a text entry area of a graphical user interface by at least: outputting, for display in a first visual style, characters of the at least one predicted current word and the at least one predicted next word that are from the set of characters that correspond to the plurality of indications of input; and outputting, for display in a second visual style that is different than the first visual style, characters of the at least one predicted current word and the at least one predicted next word that are not from the set of characters that correspond to the plurality of indications of input. | 1. A method comprising: outputting, by a computing device and for display, a graphical keyboard comprising a plurality of keys; receiving, by the computing device, a plurality of indications of input, each respective indication of input from the plurality of indications of input corresponding to a respective location of the graphical keyboard; and for each respective indication of input from the plurality of indications of input, incrementally: determining, by the computing device and based at least in part on both physical cost values from a spatial model and lexical cost values from a language model, at least one predicted current word based on a set of characters that correspond to the plurality of indications of input, wherein the spatial model comprises at least one respective distribution of touch points that corresponds to at least one respective key of the graphical keyboard, and wherein the at least one predicted current word is determined based on a physical cost value from the spatial model that is modified by a lexical cost value from the language model, the physical cost value representing a first likelihood that the plurality of indications of input correspond to the set of characters, and the lexical cost value representing a second likelihood that the set of characters are included in any word in a lexicon of the language model; determining, by the computing device and based at least in part on the at least one predicted current word, at least one predicted next word that follows the at least one predicted current word; and outputting, by the computing device and for display, the at least one predicted current word and the at least one predicted next word as a soft commit word in a text entry area of a graphical user interface by at least: outputting, for display in a first visual style, characters of the at least one predicted current word and the at least one predicted next word that are from the set of characters that correspond to the plurality of indications of input; and outputting, for display in a second visual style that is different than the first visual style, characters of the at least one predicted current word and the at least one predicted next word that are not from the set of characters that correspond to the plurality of indications of input. 3. The method of claim 1 , wherein determining the at least one predicted current word comprises performing, based at least in part on both the spatial model and the language model, error correction and word completion for each respective indication of input to determine the at least one predicted current word. | 0.690476 |
9,959,259 | 18 | 22 | 18. An apparatus comprising: a set of processing units; and a machine readable medium storing a program which when executed by at least one processing unit analyzes a document, the program comprising sets of instructions for: receiving a document that comprises a plurality of primitive graphic elements defined separately within the document; based on values calculated for pairs of primitive graphic elements, defining a set of successive primitive graphic elements; when bounds of primitive graphic elements in the set of successive primitive graphic elements at least partially overlap each other, identifying overlapping primitive graphic elements as subsets of primitive graphic elements within the set of successive primitive elements; calculating, for each of the subsets that have one or more primitive graphic elements, a total spread using bounds of the one or more primitive graphic elements and dimensions of a page containing the primitive graphic elements; and for each of the subsets that have one or more primitive graphic elements and that have a total spread less than a predetermined value, defining a single structural graphic element within the document, the single structural graphic element comprising the primitive graphic elements in the subset. | 18. An apparatus comprising: a set of processing units; and a machine readable medium storing a program which when executed by at least one processing unit analyzes a document, the program comprising sets of instructions for: receiving a document that comprises a plurality of primitive graphic elements defined separately within the document; based on values calculated for pairs of primitive graphic elements, defining a set of successive primitive graphic elements; when bounds of primitive graphic elements in the set of successive primitive graphic elements at least partially overlap each other, identifying overlapping primitive graphic elements as subsets of primitive graphic elements within the set of successive primitive elements; calculating, for each of the subsets that have one or more primitive graphic elements, a total spread using bounds of the one or more primitive graphic elements and dimensions of a page containing the primitive graphic elements; and for each of the subsets that have one or more primitive graphic elements and that have a total spread less than a predetermined value, defining a single structural graphic element within the document, the single structural graphic element comprising the primitive graphic elements in the subset. 22. The apparatus of claim 18 , wherein the document comprises an unstructured vector graphics document. | 0.908772 |
9,727,637 | 1 | 4 | 1. A method, in a question and answer (QA) system comprising a processor and a memory, for retrieving candidate answers from a corpus of documents, the method comprising: receiving, by the QA system, an input question for which an answer is sought; extracting, by the QA system, features of the input question based on a natural language processing of the input question; executing, by the QA system, a first search of the corpus of documents based on a first subset of the extracted features of the input question and an initial evaluation of a utility of the first subset of extracted features to generate a subset of documents matching the first subset of extracted features, wherein the utility of the first subset of extracted features identifies a degree to which each feature of the first subset of extracted features of the input question discriminates between documents in the corpus of documents that are sources of candidate answers to the input question; executing, by the QA system, a second search of a set of passages extracted from the subset of documents based on a second subset of the extracted features of the input question and a reevaluation of the utility of the second subset of extracted features thereby forming a subset of passages, wherein the utility of the second subset of extracted features identifies a degree to which each feature of the second subset of extracted features of the input question discriminates between passages in the set of passages that are sources of candidate answers to the input question; and generating, by the QA system, query results from the subset of passages from which a set of candidate answers for the input question are identified. | 1. A method, in a question and answer (QA) system comprising a processor and a memory, for retrieving candidate answers from a corpus of documents, the method comprising: receiving, by the QA system, an input question for which an answer is sought; extracting, by the QA system, features of the input question based on a natural language processing of the input question; executing, by the QA system, a first search of the corpus of documents based on a first subset of the extracted features of the input question and an initial evaluation of a utility of the first subset of extracted features to generate a subset of documents matching the first subset of extracted features, wherein the utility of the first subset of extracted features identifies a degree to which each feature of the first subset of extracted features of the input question discriminates between documents in the corpus of documents that are sources of candidate answers to the input question; executing, by the QA system, a second search of a set of passages extracted from the subset of documents based on a second subset of the extracted features of the input question and a reevaluation of the utility of the second subset of extracted features thereby forming a subset of passages, wherein the utility of the second subset of extracted features identifies a degree to which each feature of the second subset of extracted features of the input question discriminates between passages in the set of passages that are sources of candidate answers to the input question; and generating, by the QA system, query results from the subset of passages from which a set of candidate answers for the input question are identified. 4. The method of claim 1 , wherein executing the second search of the set of passages extracted from the subset of documents based on the second subset of the extracted features of the input question and the reevaluation of the utility of the second subset of extracted features comprises: generating, by the QA system, a second statistical data structure for the set of passages; and identifying, by the QA system, the query results from the subset of passages comprised within the second statistical data structure relevant to the second subset of the extracted features utilizing the reevaluation of the utility of the second subset of extracted features. | 0.54558 |
9,298,703 | 1 | 17 | 1. A system comprising: means for selecting, from a data store, a word or phrase associated with a failure to translate a message from a first language to a second language; means for selecting a person from whom to solicit user feedback for the translation failure; means for generating a query to request user feedback from the person; means for offering an incentive to the person; means for receiving the user feedback, the user feedback potentially assisting to translate the word or phrase; and means for rewarding the person with the incentive wherein the incentive is determined based on a complexity of the word or phrase or an importance of the word or phrase. | 1. A system comprising: means for selecting, from a data store, a word or phrase associated with a failure to translate a message from a first language to a second language; means for selecting a person from whom to solicit user feedback for the translation failure; means for generating a query to request user feedback from the person; means for offering an incentive to the person; means for receiving the user feedback, the user feedback potentially assisting to translate the word or phrase; and means for rewarding the person with the incentive wherein the incentive is determined based on a complexity of the word or phrase or an importance of the word or phrase. 17. The system of claim 1 , wherein the incentive is rewarded only if the user feedback is approved. | 0.789916 |
8,719,701 | 3 | 4 | 3. The machine readable medium of claim 1 , wherein the set of instructions for identifying the group of aligned words comprises a set of instructions for performing cluster analysis on data derived from coordinates of the particular glyphs of the words along one axis. | 3. The machine readable medium of claim 1 , wherein the set of instructions for identifying the group of aligned words comprises a set of instructions for performing cluster analysis on data derived from coordinates of the particular glyphs of the words along one axis. 4. The machine readable medium of claim 3 , wherein the cluster analysis comprises density clustering in order to identify large groups of glyphs at the edges of words with similar location coordinate values in the first direction. | 0.90678 |
8,819,052 | 8 | 19 | 8. A method to find at least one picture in one or more files, the method comprising: configuring storage to receive and store a query from a client machine, the query comprising a user-generated key word; responsive to the query from the client machine, using an auto-complete server to process the query to generate an auto-suggestion key word in response to detecting fewer than all of letters of the user-generated key word; and using a search engine coupled to the auto-complete server to use a first search argument and a second search argument to search at least one of the one or more files, using the user- generated key word and the auto-suggestion key word to find the at least one picture, wherein the auto-suggestion key word is used automatically and without response to a new search query, the search engine searches one of the one or more files using the user-generated key word as a search argument and, responsive to the at least one picture being found, transmits the at least one picture, and responsive to the at least one picture not being found, automatically searches, without response to a new search query from the client machine, the one of the one or more files using the auto-suggestion key word as a search argument. | 8. A method to find at least one picture in one or more files, the method comprising: configuring storage to receive and store a query from a client machine, the query comprising a user-generated key word; responsive to the query from the client machine, using an auto-complete server to process the query to generate an auto-suggestion key word in response to detecting fewer than all of letters of the user-generated key word; and using a search engine coupled to the auto-complete server to use a first search argument and a second search argument to search at least one of the one or more files, using the user- generated key word and the auto-suggestion key word to find the at least one picture, wherein the auto-suggestion key word is used automatically and without response to a new search query, the search engine searches one of the one or more files using the user-generated key word as a search argument and, responsive to the at least one picture being found, transmits the at least one picture, and responsive to the at least one picture not being found, automatically searches, without response to a new search query from the client machine, the one of the one or more files using the auto-suggestion key word as a search argument. 19. The method of claim 8 further comprising, responsive to the query, using the search engine to find a plurality of different pictures for the user to select. | 0.852126 |
9,544,318 | 17 | 18 | 17. A computer system for web page security, comprising: one or more processors; and a memory coupled to the one or more processors, on which are stored instructions, comprising instructions that when executed cause one or more of the processors to: transmit a request for a web page; receive a rewritten web page in response to transmitting the request, wherein the rewritten web page includes a first content file that is marked executable and a second content file that is marked non-executable, wherein the first content file includes client-side instructions and the second content file includes hypertext markup text and style sheets, and wherein the first content file and the second content file are split from the web page; inspect the rewritten web page for vulnerable content; and parse the rewritten web page for display on a web browser. | 17. A computer system for web page security, comprising: one or more processors; and a memory coupled to the one or more processors, on which are stored instructions, comprising instructions that when executed cause one or more of the processors to: transmit a request for a web page; receive a rewritten web page in response to transmitting the request, wherein the rewritten web page includes a first content file that is marked executable and a second content file that is marked non-executable, wherein the first content file includes client-side instructions and the second content file includes hypertext markup text and style sheets, and wherein the first content file and the second content file are split from the web page; inspect the rewritten web page for vulnerable content; and parse the rewritten web page for display on a web browser. 18. The computer system of claim 17 , wherein the computer system is a client-side gateway device. | 0.822464 |
8,209,598 | 1 | 4 | 1. A computer-implemented method comprising: running a rich internet application on a rich internet application platform at a client device, the rich internet application platform having an export resource that is compatible with the rich internet application and a plurality of other rich internet applications; generating a display object based at least in part on the rich internet application interpreting an application data object formatted for the rich internet application, the display object defining displayable features of a first graphical representation of the application data object and non-displayable features associated with the displayable features; and exporting the display object to a document format using the export resource, wherein exporting the display object includes: identifying components of the display object and an arrangement of the components; and generating an electronic document having the document format based at least in part on the identified components of the display object and the identified arrangement, the electronic document including data that, when interpreted by a document reader application, generate a second graphical representation that includes the displayable features of the first graphical representation and additional data defining the non-displayable features. | 1. A computer-implemented method comprising: running a rich internet application on a rich internet application platform at a client device, the rich internet application platform having an export resource that is compatible with the rich internet application and a plurality of other rich internet applications; generating a display object based at least in part on the rich internet application interpreting an application data object formatted for the rich internet application, the display object defining displayable features of a first graphical representation of the application data object and non-displayable features associated with the displayable features; and exporting the display object to a document format using the export resource, wherein exporting the display object includes: identifying components of the display object and an arrangement of the components; and generating an electronic document having the document format based at least in part on the identified components of the display object and the identified arrangement, the electronic document including data that, when interpreted by a document reader application, generate a second graphical representation that includes the displayable features of the first graphical representation and additional data defining the non-displayable features. 4. The method of claim 1 , wherein the export resource generates the electronic document by: sending each of the identified components and information on the identified arrangement to a document object library; and receiving at least a portion of the electronic document from the document object library. | 0.82786 |
7,496,854 | 50 | 51 | 50. A computer system related to information handling within a document operated on by a first application program, the document containing first information that can be utilized in a second application program, comprising: means for identifying without user intervention or designation the first information; and means for responding to a user selection by inserting a second information into the document, the second information associated with the first information from a second application program. | 50. A computer system related to information handling within a document operated on by a first application program, the document containing first information that can be utilized in a second application program, comprising: means for identifying without user intervention or designation the first information; and means for responding to a user selection by inserting a second information into the document, the second information associated with the first information from a second application program. 51. The computer system of claim 50 , wherein the means for user selection further comprises means for an activation of a device selected from a group consisting of a touch screen, a keyboard button, a screen button, an icon, a menu, and a voice command device. | 0.694379 |
8,214,242 | 11 | 15 | 11. A computer program product for signaling correspondence between a meeting agenda and a meeting discussion, the computer program product disposed upon a computer readable medium that comprises a recordable medium, the computer program product comprising computer program instructions capable of: receiving a meeting agenda specifying one or more topics for a meeting; analyzing, for each topic, one or more documents to identify topic keywords for that topic; receiving meeting discussions among participants for the meeting, wherein said receiving the meeting discussions among participants for the meeting comprises receiving voice utterances for the meeting of participants; generating a textual representation of the meeting discussions in a current meeting transcription; identifying a current topic for the meeting in dependence upon the meeting agenda; tracking a frequency at which the topic keywords for the current topic appear in the current meeting transcription; determining a correspondence indicator in dependence upon the tracked frequency at which the topic keywords for the current topic appear in the current meeting transcription, the correspondence indicator specifying the correspondence between the meeting agenda and the meeting discussion; and rendering the correspondence indicator to the participants of the meeting. | 11. A computer program product for signaling correspondence between a meeting agenda and a meeting discussion, the computer program product disposed upon a computer readable medium that comprises a recordable medium, the computer program product comprising computer program instructions capable of: receiving a meeting agenda specifying one or more topics for a meeting; analyzing, for each topic, one or more documents to identify topic keywords for that topic; receiving meeting discussions among participants for the meeting, wherein said receiving the meeting discussions among participants for the meeting comprises receiving voice utterances for the meeting of participants; generating a textual representation of the meeting discussions in a current meeting transcription; identifying a current topic for the meeting in dependence upon the meeting agenda; tracking a frequency at which the topic keywords for the current topic appear in the current meeting transcription; determining a correspondence indicator in dependence upon the tracked frequency at which the topic keywords for the current topic appear in the current meeting transcription, the correspondence indicator specifying the correspondence between the meeting agenda and the meeting discussion; and rendering the correspondence indicator to the participants of the meeting. 15. The computer program product of claim 11 wherein analyzing, for each topic, one or more documents to identify topic keywords for that topic further comprises: identifying a first set of documents related to that topic; identifying a second set of documents related to the other topics; calculating a first frequency at which a particular word appears in the first set of documents; calculating a second frequency at which the particular word appears in both the first set of documents and the second set of document; and designating the particular word as one of the topic keywords in dependence upon the first frequency and the second frequency. | 0.584399 |
7,583,647 | 17 | 27 | 17. A method, comprising: determining, by a processor, that a server request is of a type that requires at least one token to be removed from a token pool for said server request to be handled; determining, by the processor, that said server request requires a predetermined number of tokens to be removed from said token pool for said server request to be handled; and handling, by the processor, said server request when said token pool contains said predetermined number of tokens for said request by removing said predetermined number of tokens when said server request is handled by a server with which said token pool is associated, wherein the processor is configured to receive tokens and to provide the tokens to, and remove tokens from a plurality of different pools that include said token pool, wherein each of the plurality of different pools is associated with a different server, and wherein the token pool is configured to hold M tokens. | 17. A method, comprising: determining, by a processor, that a server request is of a type that requires at least one token to be removed from a token pool for said server request to be handled; determining, by the processor, that said server request requires a predetermined number of tokens to be removed from said token pool for said server request to be handled; and handling, by the processor, said server request when said token pool contains said predetermined number of tokens for said request by removing said predetermined number of tokens when said server request is handled by a server with which said token pool is associated, wherein the processor is configured to receive tokens and to provide the tokens to, and remove tokens from a plurality of different pools that include said token pool, wherein each of the plurality of different pools is associated with a different server, and wherein the token pool is configured to hold M tokens. 27. A method as claimed in claim 17 , further comprising assigning, by the processor, each of a plurality of different request types to different pools of the plurality of different pools. | 0.585903 |
9,355,171 | 16 | 17 | 16. The computer-readable storage medium of claim 15 , wherein to access the document vector, the processor is to compute the document vector. | 16. The computer-readable storage medium of claim 15 , wherein to access the document vector, the processor is to compute the document vector. 17. The non-transitory computer-readable storage medium of claim 16 , wherein to compute the document vector for one of the documents, the processor is to: determine a number of occurrences within the document of each of a plurality of words from a dictionary; and for each of a plurality of subsets of the words from the dictionary, compute a hash function of a bit field representing the number of occurrences of each of the words in that subset. | 0.902269 |
8,928,502 | 1 | 7 | 1. A keyboard for entry of text characters, the keyboard comprising: eight keys, wherein the keys are arranged in first and second groups, with each group having only four keys, and wherein each of the keys in the first and second groups has an indicia marked on its surface, each indicia representing a portion of an alphanumeric character, and wherein the indicia are chosen such that all letters of the alphabet are formed from a combination of three or less of the indicia; and processing means for detecting when at least one of the plurality of keys is pressed and for outputting data corresponding to an alphanumeric character; wherein when the processor detects that two or more of the plurality of keys have been pressed within a predetermined time period of each other, data corresponding to a text character visually resembling the combination of the indicia marked on the two or more of the plurality of keys is output, and wherein all keyboard functions are accessed by a combination of one, two or three keys, and wherein the keys are positioned such that when three keys are required, two of the three keys are located adjacent each other. | 1. A keyboard for entry of text characters, the keyboard comprising: eight keys, wherein the keys are arranged in first and second groups, with each group having only four keys, and wherein each of the keys in the first and second groups has an indicia marked on its surface, each indicia representing a portion of an alphanumeric character, and wherein the indicia are chosen such that all letters of the alphabet are formed from a combination of three or less of the indicia; and processing means for detecting when at least one of the plurality of keys is pressed and for outputting data corresponding to an alphanumeric character; wherein when the processor detects that two or more of the plurality of keys have been pressed within a predetermined time period of each other, data corresponding to a text character visually resembling the combination of the indicia marked on the two or more of the plurality of keys is output, and wherein all keyboard functions are accessed by a combination of one, two or three keys, and wherein the keys are positioned such that when three keys are required, two of the three keys are located adjacent each other. 7. A keyboard according to claim 1 , wherein when two keys are required either one of the two keys is in the first group and the other of the two keys is in the second group or the two keys are located adjacent each other. | 0.574713 |
7,490,092 | 18 | 21 | 18. A method of indexing and searching timed media files, as recited in claim 1 , wherein said data extraction includes extracting meta-data about text visible on-screen within the timed media file. | 18. A method of indexing and searching timed media files, as recited in claim 1 , wherein said data extraction includes extracting meta-data about text visible on-screen within the timed media file. 21. A method of indexing and searching timed media files, as recited in claim 18 , wherein said meta-data includes font characteristics of said text visible on-screen within the timed media file. | 0.914021 |
8,335,694 | 8 | 9 | 8. The method of claim 1 , further comprising: storing results of said procedure in a database, using said computer system. | 8. The method of claim 1 , further comprising: storing results of said procedure in a database, using said computer system. 9. The method of claim 8 , further comprising: conducting an electronic consultation, using said computer system, between users at a plurality of client computers, regarding said results of said additional examination or procedure. | 0.936538 |
10,095,452 | 1 | 9 | 1. A method for providing assistance, by a multi-function device (MFD), for document preparation, said method comprising: processing, by one or more processors in said MFD, one or more portions for one or more field names in an electronic document, wherein said electronic document corresponds to a hand-filled document comprising a character string in a first format for a field name of said one or more field names in said hand-filled document, wherein said one or more portions are extracted from said electronic document to determine a second format and a location of said character string in said electronic document, wherein said extraction of said one or more portions from said electronic document is based on a user input that indicates a first ink color of said character string, wherein said first ink color of said character string in said electronic document is different from a second ink color of said one or more field names of said electronic document; receiving, by said one or more processors in said MFD, a set of information in a pre-specified format for said one or more field names from a user-computing device over a communication network, wherein said set of information comprises at least a plurality of key strings and corresponding values; determining, by said one or more processors in said MFD, a field value for each processed portion in said electronic document based on a match between said character string in said second format and at least one of said plurality of key strings associated with field names in said received set of information; and updating, by said one or more processors in said MFD, said electronic document based on replacement of said processed portion in said electronic document for each of said one or more field names with a corresponding determined field value at said location. | 1. A method for providing assistance, by a multi-function device (MFD), for document preparation, said method comprising: processing, by one or more processors in said MFD, one or more portions for one or more field names in an electronic document, wherein said electronic document corresponds to a hand-filled document comprising a character string in a first format for a field name of said one or more field names in said hand-filled document, wherein said one or more portions are extracted from said electronic document to determine a second format and a location of said character string in said electronic document, wherein said extraction of said one or more portions from said electronic document is based on a user input that indicates a first ink color of said character string, wherein said first ink color of said character string in said electronic document is different from a second ink color of said one or more field names of said electronic document; receiving, by said one or more processors in said MFD, a set of information in a pre-specified format for said one or more field names from a user-computing device over a communication network, wherein said set of information comprises at least a plurality of key strings and corresponding values; determining, by said one or more processors in said MFD, a field value for each processed portion in said electronic document based on a match between said character string in said second format and at least one of said plurality of key strings associated with field names in said received set of information; and updating, by said one or more processors in said MFD, said electronic document based on replacement of said processed portion in said electronic document for each of said one or more field names with a corresponding determined field value at said location. 9. The method of claim 1 , wherein said set of information further comprises a plurality of field names, wherein each of said plurality of field names is associated with a corresponding key string of said plurality of key strings, wherein each key string of said plurality of key strings has a corresponding value. | 0.608479 |
7,707,161 | 6 | 7 | 6. The method of claim 1 wherein a hyperlink-based object that encodes a hyperlink includes: a first-reference that references electronically encoded information; anchor-text that describes the referenced electronically encoded information; and a second reference that references the encoded information containing the hyperlink. | 6. The method of claim 1 wherein a hyperlink-based object that encodes a hyperlink includes: a first-reference that references electronically encoded information; anchor-text that describes the referenced electronically encoded information; and a second reference that references the encoded information containing the hyperlink. 7. The method of claim 6 wherein binding, to the semantic object, hyperlinks that reference the encoded information referenced by the semantic object to create a hyperlink context for each semantic object further includes binding, to the semantic object, hyperlink-based objects that include first references that reference the encoded information referenced by the semantic object. | 0.900052 |
8,005,832 | 14 | 15 | 14. The method of claim 13 , wherein using the similarity rating comprises: determining resources in a prior search document; and rating the resources based on the similarity rating. | 14. The method of claim 13 , wherein using the similarity rating comprises: determining resources in a prior search document; and rating the resources based on the similarity rating. 15. The method of claim 14 , wherein the resources are found in potential search results. | 0.983302 |
9,201,797 | 1 | 4 | 1. A computer-implemented method, comprising: compiling a first method call at a first call site in code of an object-oriented language, wherein the first call site is associated with a first method selector; referencing a plurality of per-selector caches, each per-selector cache being associated with a respective method selector and available to multiple call sites that use the respective method selector, wherein each per-selector cache is configured to be searched based on a corresponding class identification when called from a respective call site; identifying a first per-selector cache, from among the plurality of per-selector caches, using the first method selector; and invoking a method on a first object by performing a lookup in the first per-selector cache using a class associated with the first object to determine if a first target function exists in the first per-selector cache. | 1. A computer-implemented method, comprising: compiling a first method call at a first call site in code of an object-oriented language, wherein the first call site is associated with a first method selector; referencing a plurality of per-selector caches, each per-selector cache being associated with a respective method selector and available to multiple call sites that use the respective method selector, wherein each per-selector cache is configured to be searched based on a corresponding class identification when called from a respective call site; identifying a first per-selector cache, from among the plurality of per-selector caches, using the first method selector; and invoking a method on a first object by performing a lookup in the first per-selector cache using a class associated with the first object to determine if a first target function exists in the first per-selector cache. 4. The computer-implemented method of claim 1 , further comprising: performing a full lookup to locate the first target function, if the first target function is determined not to exist in the first per-selector cache; and adding the first target function to the first per-selector cache. | 0.794286 |
8,555,243 | 11 | 15 | 11. A computer-implemented method, comprising: utilizing a computer to perform: providing a graphical program development environment comprising a graphical specification and constraint language that allows specification of a model of computation and explicit declaration of constraints; creating a graphical program in a graphical specification and constraint language that allows specification of a model of computation and explicit declaration of constraints in response to user input, wherein the graphical program comprises: a specified model of computation; a plurality of interconnected functional blocks that visually indicate functionality of the graphical program; and graphically indicated specifications or constraints for at least one functional block of the functional blocks in the graphical program; wherein the specifications or constraints comprise: input count (IC), comprising a number of tokens consumed at an input terminal of the at least one functional block by one firing of the at least one functional block; output count (OC), comprising a number of tokens produced at an output terminal of the at least one functional block by one firing of the at least one functional block; execution time (ET), comprising a number of cycles needed by the functional block to complete firing; initiation interval (II), comprising a minimum number of cycles between firings of the functional block; input pattern (IP), comprising a sequence of Boolean values of length at most II, wherein the sequence of Boolean values aligns with the beginning of firing of the functional block, wherein each true value in the sequence denotes consumption of a token by the functional block; and output pattern (OP), comprising a sequence of Boolean values of length at most II, wherein the sequence of Boolean values aligns with the end of firing of the functional block, wherein each true value in the sequence denotes production of a token by the functional block; and analyzing the graphical program, including analyzing the specifications or constraints based on the specified model of computation; and automatically generating a timing accurate simulation of the graphical program. | 11. A computer-implemented method, comprising: utilizing a computer to perform: providing a graphical program development environment comprising a graphical specification and constraint language that allows specification of a model of computation and explicit declaration of constraints; creating a graphical program in a graphical specification and constraint language that allows specification of a model of computation and explicit declaration of constraints in response to user input, wherein the graphical program comprises: a specified model of computation; a plurality of interconnected functional blocks that visually indicate functionality of the graphical program; and graphically indicated specifications or constraints for at least one functional block of the functional blocks in the graphical program; wherein the specifications or constraints comprise: input count (IC), comprising a number of tokens consumed at an input terminal of the at least one functional block by one firing of the at least one functional block; output count (OC), comprising a number of tokens produced at an output terminal of the at least one functional block by one firing of the at least one functional block; execution time (ET), comprising a number of cycles needed by the functional block to complete firing; initiation interval (II), comprising a minimum number of cycles between firings of the functional block; input pattern (IP), comprising a sequence of Boolean values of length at most II, wherein the sequence of Boolean values aligns with the beginning of firing of the functional block, wherein each true value in the sequence denotes consumption of a token by the functional block; and output pattern (OP), comprising a sequence of Boolean values of length at most II, wherein the sequence of Boolean values aligns with the end of firing of the functional block, wherein each true value in the sequence denotes production of a token by the functional block; and analyzing the graphical program, including analyzing the specifications or constraints based on the specified model of computation; and automatically generating a timing accurate simulation of the graphical program. 15. The computer-implemented method of claim 11 , where at least some of the specified model of computation and specifications or constraints are projected onto a lower dimensional space to simplify or increase performance of the timing accurate simulation. | 0.608232 |
9,966,065 | 33 | 37 | 33. The electronic device of claim 25 , wherein determining the first intent associated with the first candidate substring and the second intent associated with the second candidate substring comprises: determining the first intent or the second intent based on information displayed on a display associated with the electronic device. | 33. The electronic device of claim 25 , wherein determining the first intent associated with the first candidate substring and the second intent associated with the second candidate substring comprises: determining the first intent or the second intent based on information displayed on a display associated with the electronic device. 37. The electronic device of claim 33 , wherein determining the first intent associated with the first candidate substring and the second intent associated with the second candidate substring comprises: determining one or more potential user requests based on the information displayed on the display; and determining the first intent or the second intent based on the one or more potential user requests. | 0.882336 |
9,323,738 | 7 | 12 | 7. A device comprising: a memory to store instructions; and a processor to execute the instructions to: identify a first phrase in a document as being geographically significant, the first phrase being identified as geographically significant based on previous occurrences of the first phrase being determined to be statistically significant to first geographic information; identify a second phrase in the document as being geographically significant, the second phrase being identified as geographically significant based on previous occurrences of the second phrase being determined to be statistically significant to second geographic information; receive information indicating that the first phrase is associated with a first plurality of geographic areas; receive information indicating that the second phrase is associated with a second plurality of geographic areas; determine that a geographic area of the first plurality of geographic areas matches a geographic area of the second plurality of geographic areas; associate, based on determining that the geographic area of the first plurality of geographic areas matches the geographic area of the second plurality of geographic areas, the document with a particular geographic area, the particular geographic area corresponding to the geographic area of the first plurality of geographic areas and the geographic area of the second plurality of geographic areas; store information indicating the association of the document with the particular geographic area, the stored information permitting a determination to be made as to whether the document is relevant to the particular geographic area; generate, based on located geographic information associated with a phrase in a respective document, a histogram for the phrase; and store the generated histogram. | 7. A device comprising: a memory to store instructions; and a processor to execute the instructions to: identify a first phrase in a document as being geographically significant, the first phrase being identified as geographically significant based on previous occurrences of the first phrase being determined to be statistically significant to first geographic information; identify a second phrase in the document as being geographically significant, the second phrase being identified as geographically significant based on previous occurrences of the second phrase being determined to be statistically significant to second geographic information; receive information indicating that the first phrase is associated with a first plurality of geographic areas; receive information indicating that the second phrase is associated with a second plurality of geographic areas; determine that a geographic area of the first plurality of geographic areas matches a geographic area of the second plurality of geographic areas; associate, based on determining that the geographic area of the first plurality of geographic areas matches the geographic area of the second plurality of geographic areas, the document with a particular geographic area, the particular geographic area corresponding to the geographic area of the first plurality of geographic areas and the geographic area of the second plurality of geographic areas; store information indicating the association of the document with the particular geographic area, the stored information permitting a determination to be made as to whether the document is relevant to the particular geographic area; generate, based on located geographic information associated with a phrase in a respective document, a histogram for the phrase; and store the generated histogram. 12. The device of claim 7 , where the processor, when determining that the geographic area of the first plurality of geographic areas matches the geographic area of the second plurality of geographic areas, executes the instructions to: determine that the geographic area of the first plurality of geographic areas matches the geographic area of the second plurality of geographic areas using the generated histogram. | 0.620909 |
9,396,269 | 1 | 3 | 1. A system comprising: one or more processors; a database that stores maps of associations between search-related information and entities that are members of a social network; and memory storing computer-readable instructions by the one or more processors to perform operations including: performing an analysis of at least one of terms or phrases of searches performed by a plurality of members of the social network to infer interests of the plurality of members; determining, based on the analysis, that a first number of the searches is associated with a first interest, the first number of the searches being performed by a first group of members included in the social network; determining, based on the analysis, that a second number of the searches is associated with a second interest, the second number of the searches being performed by a second group of members included in the social network; forming, in the database, a first subnetwork of the social network, the first subnetwork including the first group of members; forming, in the database, a second subnetwork of the social network, the second subnetwork including the second group of members; receiving a search query from a user; determining search results responsive to the search query; returning the determined search results; determining that the search query corresponds with the first interest; and returning, at least partly in response to determining that the search query corresponds with the first interest, a link to at least one member of the first group of members. | 1. A system comprising: one or more processors; a database that stores maps of associations between search-related information and entities that are members of a social network; and memory storing computer-readable instructions by the one or more processors to perform operations including: performing an analysis of at least one of terms or phrases of searches performed by a plurality of members of the social network to infer interests of the plurality of members; determining, based on the analysis, that a first number of the searches is associated with a first interest, the first number of the searches being performed by a first group of members included in the social network; determining, based on the analysis, that a second number of the searches is associated with a second interest, the second number of the searches being performed by a second group of members included in the social network; forming, in the database, a first subnetwork of the social network, the first subnetwork including the first group of members; forming, in the database, a second subnetwork of the social network, the second subnetwork including the second group of members; receiving a search query from a user; determining search results responsive to the search query; returning the determined search results; determining that the search query corresponds with the first interest; and returning, at least partly in response to determining that the search query corresponds with the first interest, a link to at least one member of the first group of members. 3. The system of claim 1 , wherein the operations further include facilitating execution of a background search in connection with interaction between the user and an entity of the entities of the social network. | 0.870416 |
8,977,540 | 1 | 3 | 1. A method for automatically generating Contextual Mapping without human intervention, said method comprising acts of: using a processor to perform the steps of: processing and indexing one or more documents to identify topics for each document; storing the topics identified for each document in a predetermined order as a Topical List (TL) and removing duplicate topics from the TL; extracting a predefined number of results for each Topic in the TL by searching one Topic at a time in the corresponding index; extracting a corresponding Topic and Content for each of the retrieved result and storing the extracted Topic and Content in a predetermined order as a Result-List (RL) for analysis; analyzing the RL for the corresponding topic to extract Related Topics, analyzing Document Content of the corresponding Related Topic to extract “how they are related” phrases from the content; and clustering the resultant “Related Topics” along with their respective sentences that describe their contextual relationship with a given Topic in TL to represent Contextual Mapping. | 1. A method for automatically generating Contextual Mapping without human intervention, said method comprising acts of: using a processor to perform the steps of: processing and indexing one or more documents to identify topics for each document; storing the topics identified for each document in a predetermined order as a Topical List (TL) and removing duplicate topics from the TL; extracting a predefined number of results for each Topic in the TL by searching one Topic at a time in the corresponding index; extracting a corresponding Topic and Content for each of the retrieved result and storing the extracted Topic and Content in a predetermined order as a Result-List (RL) for analysis; analyzing the RL for the corresponding topic to extract Related Topics, analyzing Document Content of the corresponding Related Topic to extract “how they are related” phrases from the content; and clustering the resultant “Related Topics” along with their respective sentences that describe their contextual relationship with a given Topic in TL to represent Contextual Mapping. 3. The method as claimed in claim 1 , wherein identifying topic for each document comprises comparing each Important Words (IW) in the document with its file name and Title name, if any of the IW's matches than that is defined as a Topic. | 0.502092 |
9,690,935 | 1 | 14 | 1. A method comprising: obtaining, by a visual algorithm stored in memory and executed by at least one processor of a first computer, a candidate character string associated with a potentially malicious computer item operating on a second computer; generating, by the visual algorithm during execution by the at least one processor, a first visual identifier (ID) by at least translating the candidate character string into the first visual ID in accordance with one or more translation rules stored on the first computer, the first visual ID is different from the candidate character string; generating a value representing a characteristic of the potentially malicious computer item, the characteristic being associated with a size of the potentially malicious computer item or a memory location associated with the potentially malicious computer item; analyzing the first virtual ID with a reference ID where a comparison between the first virtual ID and the reference ID is used to determine whether the potentially malicious computer item should be identified as a malicious computer item; and in response to the comparison between the first virtual ID and the reference ID being indeterminate as to whether the potentially malicious computer item is to be identified as a malicious computer item, further analyzing the characteristic of the potentially malicious computer item by determining whether the value falls outside an expected range of values associated with a non-malicious computer item. | 1. A method comprising: obtaining, by a visual algorithm stored in memory and executed by at least one processor of a first computer, a candidate character string associated with a potentially malicious computer item operating on a second computer; generating, by the visual algorithm during execution by the at least one processor, a first visual identifier (ID) by at least translating the candidate character string into the first visual ID in accordance with one or more translation rules stored on the first computer, the first visual ID is different from the candidate character string; generating a value representing a characteristic of the potentially malicious computer item, the characteristic being associated with a size of the potentially malicious computer item or a memory location associated with the potentially malicious computer item; analyzing the first virtual ID with a reference ID where a comparison between the first virtual ID and the reference ID is used to determine whether the potentially malicious computer item should be identified as a malicious computer item; and in response to the comparison between the first virtual ID and the reference ID being indeterminate as to whether the potentially malicious computer item is to be identified as a malicious computer item, further analyzing the characteristic of the potentially malicious computer item by determining whether the value falls outside an expected range of values associated with a non-malicious computer item. 14. The method of claim 1 , wherein the translating the candidate character string comprises reducing a plurality of alphanumeric characters of the candidate character string to a single alphanumeric character of the visual ID. | 0.760549 |
7,889,794 | 3 | 5 | 3. The method of claim 2 wherein the rules include a pan rule, a zoom rule, a fast pan rule and a fixed rule. | 3. The method of claim 2 wherein the rules include a pan rule, a zoom rule, a fast pan rule and a fixed rule. 5. The method of claim 3 wherein the pan rule includes extracting a frame located at a point when the pan motion is slowed down. | 0.943612 |
9,983,869 | 1 | 5 | 1. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to: receive a component request from a client, the component request specifying: a requested component, the requested component being executable, and an execution context, the execution context comprising: an attribute that relates to circumstances under which the requested component is executed; process the received component request to access or generate an interface for the specified execution context for invoking the requested component in the specified execution context and to forward the interface to the client; generate an adapted component based on the received component request, the adapted component: having a wrapper that translates input to the component into a format that is understandable by the component and/or translates output from the component into a format that is understandable to the client, and implementing the requested component; wherein the component request further specifies one or more local components; and wherein generating a response to the component request comprises: analyzing the one or more local components, identifying if there is a missing component, the missing component used by the requested component, where there is a missing component, retrieving the missing component from an external component library, and adding the missing component to the adapted component; and execute the requested component. | 1. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to: receive a component request from a client, the component request specifying: a requested component, the requested component being executable, and an execution context, the execution context comprising: an attribute that relates to circumstances under which the requested component is executed; process the received component request to access or generate an interface for the specified execution context for invoking the requested component in the specified execution context and to forward the interface to the client; generate an adapted component based on the received component request, the adapted component: having a wrapper that translates input to the component into a format that is understandable by the component and/or translates output from the component into a format that is understandable to the client, and implementing the requested component; wherein the component request further specifies one or more local components; and wherein generating a response to the component request comprises: analyzing the one or more local components, identifying if there is a missing component, the missing component used by the requested component, where there is a missing component, retrieving the missing component from an external component library, and adding the missing component to the adapted component; and execute the requested component. 5. The medium of claim 1 , further storing instructions that, when executed by one or more processors, cause the one or more processors to: dynamically generate the adapted component when the component request is received. | 0.789374 |
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