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8,401,838 | 11 | 16 | 11. A method of multilanguage text input in a handheld electronic device, the method comprising: implementing a multilanguage text input application in the handheld electronic device; implementing at least one additional application in the handheld electronic device; employing a plurality of language databases containing language data from a plurality of different languages usable by at least the multilanguage text input application; and employing an interface to communicate with the multilanguage text input application and the at least one additional application, the interface providing the multilanguage text input application, at the time of the multilanguage text input, with data from more than one of the plurality of language databases in response to a single request for data from the multilanguage text input application to the interface, the interface further providing the at least one additional application with data from at least some of the language databases accessed for the multilanguage text input application. | 11. A method of multilanguage text input in a handheld electronic device, the method comprising: implementing a multilanguage text input application in the handheld electronic device; implementing at least one additional application in the handheld electronic device; employing a plurality of language databases containing language data from a plurality of different languages usable by at least the multilanguage text input application; and employing an interface to communicate with the multilanguage text input application and the at least one additional application, the interface providing the multilanguage text input application, at the time of the multilanguage text input, with data from more than one of the plurality of language databases in response to a single request for data from the multilanguage text input application to the interface, the interface further providing the at least one additional application with data from at least some of the language databases accessed for the multilanguage text input application. 16. The method of claim 11 , further comprising: including with the at least some of the different languages of the language data a mixture of a plurality of different languages using the same script or alphabet. | 0.718833 |
10,162,904 | 9 | 10 | 9. The system of claim 6 , wherein said knowledge element includes at least one member of a group consisting of: information about social networking users participating in said social networking interaction; a number of submitter names; a submission date; and a number of categories. | 9. The system of claim 6 , wherein said knowledge element includes at least one member of a group consisting of: information about social networking users participating in said social networking interaction; a number of submitter names; a submission date; and a number of categories. 10. The system of claim 9 , wherein a submitter name comprises a name of a person who marked at least one of said question specifier and said answer specifier. | 0.5 |
9,176,944 | 13 | 17 | 13. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, by a computing system, multiple portions of text that were input into different types of fields associated with a resource; selecting (i) a first randomness threshold value for portions of text that are input into a text entry field of a first type, and (ii) a second randomness threshold value for portions of text that are input into a text entry field of a second type; for each of the multiple portions of text: determining, for the portion of text, a randomness value that reflects a level of entropy associated with a sequence of characters in the portion of text; determining a type of text entry field into which the portion of text was input, from among the text entry field of the first type and the text entry field of the second type, determining a randomness threshold value associated with the determined type of text entry field, from among the first randomness threshold value and the second randomness threshold value, where the randomness threshold value associated with the determined type of text entry field reflects a level of entropy permitted in a sequence of characters both input into a text entry field of the determined type and used to adapt a text processing system, and determining whether the randomness value for the portion of text satisfies the determined randomness threshold value; providing the one or more portions of text whose respective randomness values are determined to not satisfy the respective randomness threshold value determined for the portions of text, to adapt a text processing system; and preventing the one or more portions of text whose respective randomness values are determined to satisfy the respective randomness threshold value determined for the portions of text, from being used to adapt the text processing system. | 13. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, by a computing system, multiple portions of text that were input into different types of fields associated with a resource; selecting (i) a first randomness threshold value for portions of text that are input into a text entry field of a first type, and (ii) a second randomness threshold value for portions of text that are input into a text entry field of a second type; for each of the multiple portions of text: determining, for the portion of text, a randomness value that reflects a level of entropy associated with a sequence of characters in the portion of text; determining a type of text entry field into which the portion of text was input, from among the text entry field of the first type and the text entry field of the second type, determining a randomness threshold value associated with the determined type of text entry field, from among the first randomness threshold value and the second randomness threshold value, where the randomness threshold value associated with the determined type of text entry field reflects a level of entropy permitted in a sequence of characters both input into a text entry field of the determined type and used to adapt a text processing system, and determining whether the randomness value for the portion of text satisfies the determined randomness threshold value; providing the one or more portions of text whose respective randomness values are determined to not satisfy the respective randomness threshold value determined for the portions of text, to adapt a text processing system; and preventing the one or more portions of text whose respective randomness values are determined to satisfy the respective randomness threshold value determined for the portions of text, from being used to adapt the text processing system. 17. The medium of claim 13 , wherein selecting the first and second randomness threshold values based at least in part on characteristics of the multiple portions of text comprises: selecting the first and second randomness threshold values for respective particular portions based at least in part on whether or not user input is masked in text entry fields in which the respective particular portions are input. | 0.616883 |
9,486,247 | 26 | 30 | 26. The spinal fixation system of claim 21 , further comprising: a second bone anchor having a bone-engaging portion and a spinal fixation receiving portion with opposed arms configured to receive a spinal fixation element therebetween; and a second clamp that is matable to the spinal fixation element receiving portion of the second bone anchor, the two plates each having an opening extending therethrough, and the two plates being connected by a receiving portion that is offset from the opening, the receiving portion being configured to receive the spinal rod therethrough; wherein the first and second plates of the second clamp are movable toward one another to clamp the spinal rod within the receiving portion of the second clamp. | 26. The spinal fixation system of claim 21 , further comprising: a second bone anchor having a bone-engaging portion and a spinal fixation receiving portion with opposed arms configured to receive a spinal fixation element therebetween; and a second clamp that is matable to the spinal fixation element receiving portion of the second bone anchor, the two plates each having an opening extending therethrough, and the two plates being connected by a receiving portion that is offset from the opening, the receiving portion being configured to receive the spinal rod therethrough; wherein the first and second plates of the second clamp are movable toward one another to clamp the spinal rod within the receiving portion of the second clamp. 30. The spinal fixation system of claim 26 , wherein the offset location of the receiving portions of the first and second clamps is such that when portions of the spinal rod are disposed therein, the spinal rod is offset from the openings of the first and second plates of the first and second clamps. | 0.559767 |
9,710,730 | 17 | 18 | 17. A method of automatic medical image registration comprising: receiving a first medical image and a second medical image, the first medical image and the second medical image being of objects and with at least part of one object being common to the first medical image and the second medical image; for each of the first and second medical images, computing a probability map comprising, for each image element, a probability that the image element is of a specified object; wherein computing the probability map comprises, for at least one specified object, computing a posterior distribution of the location of the specified object in each of the first and second medical images by using a regression forest comprising a plurality of regression trees each having been trained to predict a location of the specified object; finding a mapping to register the first and second medical images by optimizing an energy function which is a function of the intensities of the first and second medical images and also of the probability maps, the energy function comprising: a summation of a term related to a Kullback-Leibler divergence; and a summation of a term related to a marginal entropy of the first medical image and a term related to a marginal entropy of the second medical image, less a term related to a joint entropy of the first and second medical images. | 17. A method of automatic medical image registration comprising: receiving a first medical image and a second medical image, the first medical image and the second medical image being of objects and with at least part of one object being common to the first medical image and the second medical image; for each of the first and second medical images, computing a probability map comprising, for each image element, a probability that the image element is of a specified object; wherein computing the probability map comprises, for at least one specified object, computing a posterior distribution of the location of the specified object in each of the first and second medical images by using a regression forest comprising a plurality of regression trees each having been trained to predict a location of the specified object; finding a mapping to register the first and second medical images by optimizing an energy function which is a function of the intensities of the first and second medical images and also of the probability maps, the energy function comprising: a summation of a term related to a Kullback-Leibler divergence; and a summation of a term related to a marginal entropy of the first medical image and a term related to a marginal entropy of the second medical image, less a term related to a joint entropy of the first and second medical images. 18. The method as claimed in claim 17 , wherein the first and second medical images are three or higher dimensional volumetric images. | 0.689815 |
9,971,839 | 14 | 15 | 14. The system of claim 11 , wherein the instructions, when executed, further cause the system to determine the personalization information from user profiles associated with the first user and the users connect with the first user in the social network. | 14. The system of claim 11 , wherein the instructions, when executed, further cause the system to determine the personalization information from user profiles associated with the first user and the users connect with the first user in the social network. 15. The system of claim 14 , wherein the instructions, when executed, further cause the system to: determine the personalization information based on membership information of a second user in a community, and wherein the second user connects with the first user in the social network and the first user fails to be a member of the community. | 0.5 |
6,166,732 | 1 | 3 | 1. In a persistent object oriented multi-user domain in which objects are distributed between computer readable media associated with a server computer and plural client computers with corresponding users, the improvement comprising: multimedia properties associated with objects in the multi-user domain for presentation on the client computers; and a bystander region property associated with selected ones of the objects and representing a perceptual range of effect on other objects of multimedia properties on the selected objects. | 1. In a persistent object oriented multi-user domain in which objects are distributed between computer readable media associated with a server computer and plural client computers with corresponding users, the improvement comprising: multimedia properties associated with objects in the multi-user domain for presentation on the client computers; and a bystander region property associated with selected ones of the objects and representing a perceptual range of effect on other objects of multimedia properties on the selected objects. 3. The domain of claim 1 further including software instructions for adding a designated method or property at run-time to a designated one of the objects. | 0.677083 |
7,672,007 | 19 | 24 | 19. A method of doing business comprising the step of: utilizing an automated digitizing system configurable to route information identified by content instructions in a document file on a computer to a potential plurality of application programs according to customizable transmission format instructions, said transmission format instructions being customized to requirements of each application program receiving said information. | 19. A method of doing business comprising the step of: utilizing an automated digitizing system configurable to route information identified by content instructions in a document file on a computer to a potential plurality of application programs according to customizable transmission format instructions, said transmission format instructions being customized to requirements of each application program receiving said information. 24. A method as claimed in claim 19 in which said potential plurality of application programs is an unrestricted diversity of application programs operating on an arbitrary remote computer system and said document file is not derived from scanning a hard copy document. | 0.5 |
9,980,009 | 11 | 14 | 11. A non-transitory computer readable storage medium in conjunction with a digital video conversion device storing one or more program modules, wherein the digital video conversion device is communicatively coupled to a TV set and a TV signal source, respectively, so as to pass TV signals from the TV signal source to the TV set, wherein the one or more program modules further include instructions, which, when executed by one or more processors of the digital video conversion device, cause the processors to perform operations including: receiving a TV channel identification request from a mobile terminal via a wireless communication channel; in response to the TV channel identification request: acquiring an image from the TV signals currently broadcasted on the TV set; extracting a plurality of station logo characteristic sets from the image, wherein each station logo characteristic set corresponds to one of a plurality of station logo templates, wherein each station logo template includes a respective station logo type and logo position information for a respective station logo image region, and wherein extracting the plurality of station logo characteristic set for a corresponding station logo template in the plurality of station logo templates includes: in accordance with a determination that the respective station logo type in the corresponding station logo template is a static opaque station logo type, generating a normalized block-level color histogram for a station logo image region in the image; and in accordance with a determination that the respective station logo type in the corresponding station logo template is a static semi-transparent station logo type, generating a perpetual hash value of the station logo image region in the image; calculating a similarity score between each station logo characteristic set and a corresponding station logo template of said each station logo characteristic set; identifying one of the plurality of station logo templates as matching the image based on their similarity scores; and returning TV channel information associated with the identified station logo template to the mobile terminal. | 11. A non-transitory computer readable storage medium in conjunction with a digital video conversion device storing one or more program modules, wherein the digital video conversion device is communicatively coupled to a TV set and a TV signal source, respectively, so as to pass TV signals from the TV signal source to the TV set, wherein the one or more program modules further include instructions, which, when executed by one or more processors of the digital video conversion device, cause the processors to perform operations including: receiving a TV channel identification request from a mobile terminal via a wireless communication channel; in response to the TV channel identification request: acquiring an image from the TV signals currently broadcasted on the TV set; extracting a plurality of station logo characteristic sets from the image, wherein each station logo characteristic set corresponds to one of a plurality of station logo templates, wherein each station logo template includes a respective station logo type and logo position information for a respective station logo image region, and wherein extracting the plurality of station logo characteristic set for a corresponding station logo template in the plurality of station logo templates includes: in accordance with a determination that the respective station logo type in the corresponding station logo template is a static opaque station logo type, generating a normalized block-level color histogram for a station logo image region in the image; and in accordance with a determination that the respective station logo type in the corresponding station logo template is a static semi-transparent station logo type, generating a perpetual hash value of the station logo image region in the image; calculating a similarity score between each station logo characteristic set and a corresponding station logo template of said each station logo characteristic set; identifying one of the plurality of station logo templates as matching the image based on their similarity scores; and returning TV channel information associated with the identified station logo template to the mobile terminal. 14. The non-transitory computer readable storage medium of claim 11 , wherein at least one of the plurality of station logo templates further includes a parent station logo template, the parent station logo template further having multiple child station logo templates. | 0.5 |
7,933,762 | 13 | 14 | 13. The method of claim 12 in which the user is enabled to point and click to cause display of information about the model process validation. | 13. The method of claim 12 in which the user is enabled to point and click to cause display of information about the model process validation. 14. The method of claim 13 in which the information about the model process validation includes at least one of: a statistical report card, a link to a statistical report chart, a cumulative lift chart, a link to the cumulative lift chart, a non-cumulative lift chart, a link to the non-cumulative lift chart. | 0.5 |
7,587,064 | 15 | 24 | 15. A computer program product as set forth in claim 14 , further comprising computer-readable instruction means encoded on a computer-readable medium for causing a computer to: extract a relevant feature set from the potential object candidate using a fixed-basis function decomposition module using Haar wavelets; classify the potential object candidate using a static classifier, thereby generating a classification category selected from a group consisting of a positive identification, a negative identification, a false positive identification, and a false negative identification, and where upon classification, the static classifier communicates the classification to the incremental learning module. | 15. A computer program product as set forth in claim 14 , further comprising computer-readable instruction means encoded on a computer-readable medium for causing a computer to: extract a relevant feature set from the potential object candidate using a fixed-basis function decomposition module using Haar wavelets; classify the potential object candidate using a static classifier, thereby generating a classification category selected from a group consisting of a positive identification, a negative identification, a false positive identification, and a false negative identification, and where upon classification, the static classifier communicates the classification to the incremental learning module. 24. A computer program product as set forth in claim 15 , wherein the fixed-basis function decomposition module is configured to transform the example set of images from image space to wavelet space through operations of: computing a response of wavelet filters over an image, where at least three type of wavelets, vertical, horizontal, and diagonal, are computed at different scales by forming an inner-product (dot-product) of the wavelet basis function to provide wavelet coefficients, where the wavelet coefficients serve as the relevant feature set; and utilizing absolute values of the wavelet coefficients to eliminate differences in features when considering a dark object on light background and a light object on a dark background. | 0.739283 |
9,792,534 | 16 | 19 | 16. One or more non-transitory computer-readable storage media storing instructions executable via the one or more processing devices to implement a caption generator configured to perform operations to automatically generate image captions using word vector representations including: obtaining a target image for caption analysis; applying feature extraction to the target image to generate attributes corresponding to the image; supplying the attributes to the caption generator to initiate caption generation; outputting by the caption generator a word vector in a semantic word vector space indicative of semantic relationships between words in sentences formed as a combination of the attributes; and subsequently using the word vector in post-processing operations to generate a corresponding caption by: selecting a dictionary; and mapping the word vector to words in the semantic word vector space based on the selected dictionary. | 16. One or more non-transitory computer-readable storage media storing instructions executable via the one or more processing devices to implement a caption generator configured to perform operations to automatically generate image captions using word vector representations including: obtaining a target image for caption analysis; applying feature extraction to the target image to generate attributes corresponding to the image; supplying the attributes to the caption generator to initiate caption generation; outputting by the caption generator a word vector in a semantic word vector space indicative of semantic relationships between words in sentences formed as a combination of the attributes; and subsequently using the word vector in post-processing operations to generate a corresponding caption by: selecting a dictionary; and mapping the word vector to words in the semantic word vector space based on the selected dictionary. 19. One or more non-transitory computer-readable storage media as recited in claim 16 , wherein supplying the attributes to a caption generator to initiate caption generation comprises providing the attributes to a recurrent neural network (RNN) designed to implement language modeling and sentence construction techniques for generating a caption for the target image. | 0.5 |
9,640,186 | 10 | 11 | 10. The method of claim 1 , wherein the extracting step further comprises reducing a dimensionality of the deep scattering spectral features. | 10. The method of claim 1 , wherein the extracting step further comprises reducing a dimensionality of the deep scattering spectral features. 11. The method of claim 10 , wherein the dimensionality reducing step further comprises performing a principal component analysis. | 0.5 |
9,424,612 | 15 | 16 | 15. The computer-implemented method of claim 1 , further comprising adjusting a second category-specific reputation score of a second account based on the first category-specific reputation score of the first account. | 15. The computer-implemented method of claim 1 , further comprising adjusting a second category-specific reputation score of a second account based on the first category-specific reputation score of the first account. 16. The computer-implemented method of claim 15 , further comprising adjusting a third category-specific reputation score of a third account based on the second category-specific reputation score of the second account. | 0.5 |
7,970,791 | 3 | 4 | 3. The method according to claim 1 , wherein the received attribute is a recency. | 3. The method according to claim 1 , wherein the received attribute is a recency. 4. The method according to claim 3 , wherein the recency for each query result is a difference in time. | 0.5 |
8,233,726 | 11 | 19 | 11. A non-transitory computer-readable storage medium encoded with executable computer program code for identifying a writing system associated with a document image containing one or more words written in the writing system, the program code comprising: program code for identifying a document image fragment based on the document image, wherein the document image fragment contains one or more pixels from one or more of the words in the document image; program code for generating a set of sequential features associated with the document image fragment, wherein each sequential feature describes one dimensional graphic information derived from the one or more pixels in the document image fragment; program code for identifying a plurality of n-grams based on the set of sequential features, wherein each n-gram comprises an ordered subset of sequential features; program code for generating a classification score for the document image fragment based at least in part on a frequency of occurrence of the n-grams in sets of sequential features associated with known writing systems, the classification score indicating a likelihood that the document image fragment is written in the writing system; and program code for identifying the writing system associated with the document image based at least in part on the classification score for the document image fragment. | 11. A non-transitory computer-readable storage medium encoded with executable computer program code for identifying a writing system associated with a document image containing one or more words written in the writing system, the program code comprising: program code for identifying a document image fragment based on the document image, wherein the document image fragment contains one or more pixels from one or more of the words in the document image; program code for generating a set of sequential features associated with the document image fragment, wherein each sequential feature describes one dimensional graphic information derived from the one or more pixels in the document image fragment; program code for identifying a plurality of n-grams based on the set of sequential features, wherein each n-gram comprises an ordered subset of sequential features; program code for generating a classification score for the document image fragment based at least in part on a frequency of occurrence of the n-grams in sets of sequential features associated with known writing systems, the classification score indicating a likelihood that the document image fragment is written in the writing system; and program code for identifying the writing system associated with the document image based at least in part on the classification score for the document image fragment. 19. The medium of claim 11 , further comprising: program code for identifying a set of ordered pixel columns based on the document image fragment wherein each ordered pixel column is comprised of a set of cells and each cell comprises a set of pixels; program code for determining a set of values for each ordered pixel column in the set, wherein each value is based on one or more intensity values of one or more pixels of the set of pixels in one or more cells of the set of cells; and program code for generating the set of sequential features comprising the set of values. | 0.686275 |
8,521,512 | 2 | 15 | 2. The system of claim 1 , wherein the concept is an observation concept, and wherein the construction of the table further comprises: identifying a subject concept and assigning a unique identifier to the subject concept; identifying a seam concept and assigning a unique identifier to the seam concept; identifying a relative concept and assigning a unique identifier to the relative concept constructing a binary concept by either joining the subject concept and the seam concept or joining the seam concept and the relative concept, and assigning a unique identifier to the binary concept; and constructing a first higher order sub-concept by joining either the relative concept or the subject concept with the binary concept and assigning a unique identifier to the first higher order sub-concept. | 2. The system of claim 1 , wherein the concept is an observation concept, and wherein the construction of the table further comprises: identifying a subject concept and assigning a unique identifier to the subject concept; identifying a seam concept and assigning a unique identifier to the seam concept; identifying a relative concept and assigning a unique identifier to the relative concept constructing a binary concept by either joining the subject concept and the seam concept or joining the seam concept and the relative concept, and assigning a unique identifier to the binary concept; and constructing a first higher order sub-concept by joining either the relative concept or the subject concept with the binary concept and assigning a unique identifier to the first higher order sub-concept. 15. The system of claim 2 , wherein the text comprises one or more of a paragraph, chapter, book, article, or publication, and wherein the at least one table comprises a plurality of observation concepts constructed by the builder to represent the knowledge represented in the text. | 0.628947 |
8,280,733 | 1 | 5 | 1. A computer-implemented speech recognition system, comprising: a microphone that receives user speech; a speech recognition engine coupled to the microphone, the speech recognition engine recognizing the user speech and providing a corresponding textual output on a user interface; a change recognition component that automatically assigns a categorization to a user-initiated change to the corresponding textual output, the categorization being automatically assigned based at least in part upon a measurement of time indicative of how long it took the user to initiate the change, upon whether or not the user utilized an alternate list to generate the user initiated change, upon an acoustic similarity between the original textual output and the change to the textual output, and upon a number of words that is changed between the original textual output and the change to the textual output; and wherein automatically assigning the categorization comprises automatically identifying the user-initiated change as being either a correction or an edit operation, wherein the user-initiated change is identified as the correction upon the measurement of time indicating that there was a relatively short amount of time between providing the original textual output and the user initiating the change, wherein the user-initiated change is identified as the correction upon the user utilizing the alternate list, wherein the user-initiated change is identified as the correction upon the original textual output and the change to the textual output being acoustically similar, and wherein the user-initiated change is identified as the correction upon the number of words that is changed between the original textual output and the change to the textual output is determined to be insignificant, and wherein otherwise the categorization is determined to be the edit operation; and an adaptation component that selectively adapts the speech recognition engine depending upon the categorization. | 1. A computer-implemented speech recognition system, comprising: a microphone that receives user speech; a speech recognition engine coupled to the microphone, the speech recognition engine recognizing the user speech and providing a corresponding textual output on a user interface; a change recognition component that automatically assigns a categorization to a user-initiated change to the corresponding textual output, the categorization being automatically assigned based at least in part upon a measurement of time indicative of how long it took the user to initiate the change, upon whether or not the user utilized an alternate list to generate the user initiated change, upon an acoustic similarity between the original textual output and the change to the textual output, and upon a number of words that is changed between the original textual output and the change to the textual output; and wherein automatically assigning the categorization comprises automatically identifying the user-initiated change as being either a correction or an edit operation, wherein the user-initiated change is identified as the correction upon the measurement of time indicating that there was a relatively short amount of time between providing the original textual output and the user initiating the change, wherein the user-initiated change is identified as the correction upon the user utilizing the alternate list, wherein the user-initiated change is identified as the correction upon the original textual output and the change to the textual output being acoustically similar, and wherein the user-initiated change is identified as the correction upon the number of words that is changed between the original textual output and the change to the textual output is determined to be insignificant, and wherein otherwise the categorization is determined to be the edit operation; and an adaptation component that selectively adapts the speech recognition engine depending upon the categorization. 5. The system of claim 1 , wherein selectively adapting comprises adapting only if the categorization indicates that the user-initiated correction is due to a recognition error made by the speech recognition engine, and wherein adapting comprises adapting so as to make it less likely that the speech recognition engine will subsequently repeat the recognition error during a subsequent recognition operation. | 0.5 |
10,165,064 | 12 | 18 | 12. A method of providing third-party content based on keyword performances, comprising: identifying, by a data processing system, based on data stored in a historic online activity database, a cluster of client devices that previously performed a plurality of online activities of an online activity type in relation to a product or service context; determining, by the data processing system, based on the data stored in the historic online activity database, from a plurality of keywords, a subset of keywords associated with the plurality of online activities of the online activity type that the cluster of client devices performed in relation to the product or service context; determining, by the data processing system, a performance metric of the subset of keywords based on the plurality of online activities of the online activity type that the cluster of client devices performed in relation to the product or service context; and providing, by the data processing system, for a computing device of a third-party content provider, access to the subset of keywords and the performance metric, a parameter value determined, by the computing device of the third-party content provider, for a first keyword of the subset of keywords based on the performance metric is used to select a content item of the third-party content provider associated with the product or service context responsive to a request for third-party content, the request for third-party content indicative of the first keyword, and the selected content item is provided for display on a client device. | 12. A method of providing third-party content based on keyword performances, comprising: identifying, by a data processing system, based on data stored in a historic online activity database, a cluster of client devices that previously performed a plurality of online activities of an online activity type in relation to a product or service context; determining, by the data processing system, based on the data stored in the historic online activity database, from a plurality of keywords, a subset of keywords associated with the plurality of online activities of the online activity type that the cluster of client devices performed in relation to the product or service context; determining, by the data processing system, a performance metric of the subset of keywords based on the plurality of online activities of the online activity type that the cluster of client devices performed in relation to the product or service context; and providing, by the data processing system, for a computing device of a third-party content provider, access to the subset of keywords and the performance metric, a parameter value determined, by the computing device of the third-party content provider, for a first keyword of the subset of keywords based on the performance metric is used to select a content item of the third-party content provider associated with the product or service context responsive to a request for third-party content, the request for third-party content indicative of the first keyword, and the selected content item is provided for display on a client device. 18. The method of claim 12 comprising: identifying, by the data processing system, one or more other keywords of the plurality of keywords having similar attributes as the subset of keywords; updating, by the data processing system, the subset of keywords to further include the one or more other keywords; determining, by the data processing system, the performance metric based on the updated subset of keywords. | 0.682515 |
7,899,976 | 7 | 15 | 7. The integrated circuit chip according to claim 4 , wherein the FSA extension architecture further comprises row-wise and column-wise extension architecture to couple two or more of said plurality of programmable search engines in at least one said column or at least one said row or a combination of one said row and one said column of one of said PRISM memory clusters to support a regular expression that results in a finite state automaton with a number of symbols greater than said fixed number of symbol circuits of one of said programmable search engines. | 7. The integrated circuit chip according to claim 4 , wherein the FSA extension architecture further comprises row-wise and column-wise extension architecture to couple two or more of said plurality of programmable search engines in at least one said column or at least one said row or a combination of one said row and one said column of one of said PRISM memory clusters to support a regular expression that results in a finite state automaton with a number of symbols greater than said fixed number of symbol circuits of one of said programmable search engines. 15. The integrated circuit chip according to claim 7 , wherein the FSA extension architecture further comprises rule group FSA extension architecture to enable creation of a plurality of groups of regular expression rules from said plurality of regular expressions and to perform state transition from one regular expression of a first group to at least one regular expression of a second group of said plurality of regular expressions. | 0.904762 |
8,266,133 | 17 | 18 | 17. The one or more computer devices of claim 16 , where, when generating the rules for the model, the model generation system is further to: store the log data as triples of data (u, q, r), where: u represents the information regarding the user that provided a certain search query, q represents the information regarding the certain search query, and r represents the information regarding the repository from which the search results were provided in response to the certain search query. | 17. The one or more computer devices of claim 16 , where, when generating the rules for the model, the model generation system is further to: store the log data as triples of data (u, q, r), where: u represents the information regarding the user that provided a certain search query, q represents the information regarding the certain search query, and r represents the information regarding the repository from which the search results were provided in response to the certain search query. 18. The one or more computer devices of claim 17 , where, when generating the rules for the model, the model generation system is to: determine a label for each of the triples of data (u, q, r), where the label includes information regarding whether the repository r includes information that satisfies the search query q provided by the user u, and train the model based on the triples of data (u, q, r) and the associated labels. | 0.5 |
7,711,544 | 7 | 8 | 7. The method of claim 1 , wherein the supplemental information comprises a command to modify the variable text element. | 7. The method of claim 1 , wherein the supplemental information comprises a command to modify the variable text element. 8. The method of claim 7 , wherein the command comprises at least one of capitalization, first person speech, second person speech, third person speech, accusative speech, nominative speech, past tense, present tense, future tense, participle form, and infinitive form. | 0.5 |
9,208,151 | 14 | 17 | 14. The system according to claim 13 , wherein said processor device is further configured to: form a graph structure by forming nodes from said abstract documents and links from said operations and retaining said abstract documents. | 14. The system according to claim 13 , wherein said processor device is further configured to: form a graph structure by forming nodes from said abstract documents and links from said operations and retaining said abstract documents. 17. The system according to claim 14 , wherein said operation specification comprises a completion condition described by a specific state of said metadata; and wherein said processor device is further configured to: apply a completion mark, among said abstract documents that satisfy said completion condition, to reverse abstract documents that arrived at said graph structure in reverse order; and determine verification failure if said reverse abstract document is without an applied completion mark. | 0.5 |
9,972,305 | 14 | 18 | 14. A speech recognition apparatus comprising: a preprocessor configured to: extract windows of frame data to be input to an acoustic model from frame data of a speech to be recognized; and normalize the frame data to be input to the acoustic model in units of the extracted windows; an acoustic score calculator configured to calculate acoustic scores in units of the normalized windows using the acoustic model based on a deep neural network (DNN); and an interpreter configured to: interpret the acoustic scores calculated in units of the normalized windows; and output a recognition result of the speech to be recognized based on the interpreted scores, wherein the preprocessor is further configured to normalize frames belonging to a current window in consideration of frames belonging to preceding windows of the current window. | 14. A speech recognition apparatus comprising: a preprocessor configured to: extract windows of frame data to be input to an acoustic model from frame data of a speech to be recognized; and normalize the frame data to be input to the acoustic model in units of the extracted windows; an acoustic score calculator configured to calculate acoustic scores in units of the normalized windows using the acoustic model based on a deep neural network (DNN); and an interpreter configured to: interpret the acoustic scores calculated in units of the normalized windows; and output a recognition result of the speech to be recognized based on the interpreted scores, wherein the preprocessor is further configured to normalize frames belonging to a current window in consideration of frames belonging to preceding windows of the current window. 18. The speech recognition apparatus of claim 14 , further comprising a language score calculator configured to calculate language scores using a language model; wherein the interpreter is further configured to output the recognition result based on the interpreted scores and the language scores. | 0.645585 |
9,471,645 | 1 | 3 | 1. A method, in a data processing system having a processor, for anonymizing data comprising a plurality of graph data sets, comprising: receiving, by the processor of the data processing system, input data comprising a plurality of graph data sets, wherein each graph data set comprises data for generating a separate graph from graphs associated with other graph data sets; performing, by the processor, clustering on the graph data sets to generate a plurality of clusters, wherein at least one cluster of the plurality of clusters comprises a plurality of graph data sets and wherein other clusters in the plurality of clusters comprise one or more graph data sets; determining, by the processor, for each cluster in the plurality of clusters, an aggregate property of the cluster; generating, by the processor, for each cluster in the plurality of clusters, synthetic data representing the cluster, from the determined aggregate properties of the clusters; and executing, by the processor or another computing device, one or more applications on the synthetic data to perform an operation on the synthetic data while preserving a privacy aspect of the input data. | 1. A method, in a data processing system having a processor, for anonymizing data comprising a plurality of graph data sets, comprising: receiving, by the processor of the data processing system, input data comprising a plurality of graph data sets, wherein each graph data set comprises data for generating a separate graph from graphs associated with other graph data sets; performing, by the processor, clustering on the graph data sets to generate a plurality of clusters, wherein at least one cluster of the plurality of clusters comprises a plurality of graph data sets and wherein other clusters in the plurality of clusters comprise one or more graph data sets; determining, by the processor, for each cluster in the plurality of clusters, an aggregate property of the cluster; generating, by the processor, for each cluster in the plurality of clusters, synthetic data representing the cluster, from the determined aggregate properties of the clusters; and executing, by the processor or another computing device, one or more applications on the synthetic data to perform an operation on the synthetic data while preserving a privacy aspect of the input data. 3. The method of claim 1 , wherein the aggregate property of the cluster comprises a set of frequent sub-graphs of the cluster. | 0.80581 |
8,300,941 | 1 | 4 | 1. A method of determining a regular grid pattern from a surface coded pattern that comprises the regular grid pattern interleaved with a further data carrying pattern wherein the surface coded pattern is subject to perspective distortion, the method comprising: extracting a set of straight line hypotheses from the surface coded pattern by identifying a plurality of surface pattern points that are co-linear to one another, identifying sets of the plurality of surface pattern points that are co-linear to one another, deleting sets of the plurality of surface pattern points that have a cross-ratio value outside a predetermined range, and fitting a line hypothesis to sets of the plurality of surface pattern points that have a cross-ratio value within the predetermined range; clustering the straight line hypotheses by orientation; for each cluster, extracting a set of line pencil hypotheses; generating a set of regular grid hypotheses from pairs of the line pencil hypotheses; and determining, by a processor, a regular grid hypothesis closest to a true regular grid. | 1. A method of determining a regular grid pattern from a surface coded pattern that comprises the regular grid pattern interleaved with a further data carrying pattern wherein the surface coded pattern is subject to perspective distortion, the method comprising: extracting a set of straight line hypotheses from the surface coded pattern by identifying a plurality of surface pattern points that are co-linear to one another, identifying sets of the plurality of surface pattern points that are co-linear to one another, deleting sets of the plurality of surface pattern points that have a cross-ratio value outside a predetermined range, and fitting a line hypothesis to sets of the plurality of surface pattern points that have a cross-ratio value within the predetermined range; clustering the straight line hypotheses by orientation; for each cluster, extracting a set of line pencil hypotheses; generating a set of regular grid hypotheses from pairs of the line pencil hypotheses; and determining, by a processor, a regular grid hypothesis closest to a true regular grid. 4. The method of claim 1 , wherein clustering the straight line hypotheses comprises grouping the straight line hypotheses into a plurality of sets, each set of the group encompassing straight line hypotheses with an angular orientation about a center of the surface coded pattern within a predetermined range, and for each set of the group clustering the straight line hypotheses about a common angular orientation. | 0.687688 |
9,489,657 | 1 | 2 | 1. A computer-implemented method, comprising: receiving over a communications network a plurality of chat messages from two or more different chat rooms; analyzing the plurality of messages to extract a summary of activity taking place in the two or more chat rooms, wherein the summary of activity further includes a chat room summary to be presented on a distinct region of the display for each of the two or more chat rooms, the distinct region of a plurality of the chat room summaries each including a plurality of subregions, a first subregion presenting one or more infographics reflecting an amount of participant activity in its respective chat room, wherein the infographics provide a real-time indication of a participant's activity in its respective chat room; and causing the summary of activity to be presented on a display. | 1. A computer-implemented method, comprising: receiving over a communications network a plurality of chat messages from two or more different chat rooms; analyzing the plurality of messages to extract a summary of activity taking place in the two or more chat rooms, wherein the summary of activity further includes a chat room summary to be presented on a distinct region of the display for each of the two or more chat rooms, the distinct region of a plurality of the chat room summaries each including a plurality of subregions, a first subregion presenting one or more infographics reflecting an amount of participant activity in its respective chat room, wherein the infographics provide a real-time indication of a participant's activity in its respective chat room; and causing the summary of activity to be presented on a display. 2. The computer-implemented method of claim 1 , a second of the subregions including a title of its respective chat room and a third of the subregions including one or more icons indicating a number of participants currently in its respective chat room. | 0.604688 |
8,200,487 | 25 | 30 | 25. A method for generating a structured text from an unstructured text, the method comprising acts of: segmenting the unstructured text into text sections; assigning, to at least one text section, a topic being indicative of content of the at least one text section; identifying a text portion as being a full or partial verbalization of a section heading for the at least one text section, the section heading corresponding to the topic assigned to the at least one text section; providing to a user a first structured text comprising the at least one text section and the section heading for the at least one text section, wherein the text portion identified as being a full or partial verbalization of the section heading is removed from the first structured text; receiving user input indicating at least one modification to the first structured text; and using a computer system to process the at least one modification received from the user to generate a second structured text. | 25. A method for generating a structured text from an unstructured text, the method comprising acts of: segmenting the unstructured text into text sections; assigning, to at least one text section, a topic being indicative of content of the at least one text section; identifying a text portion as being a full or partial verbalization of a section heading for the at least one text section, the section heading corresponding to the topic assigned to the at least one text section; providing to a user a first structured text comprising the at least one text section and the section heading for the at least one text section, wherein the text portion identified as being a full or partial verbalization of the section heading is removed from the first structured text; receiving user input indicating at least one modification to the first structured text; and using a computer system to process the at least one modification received from the user to generate a second structured text. 30. The method according to claim 25 , wherein the plurality of text sections is a first plurality of text sections, and wherein the method further comprises acts of: re-segmenting at least a portion of the second structured text into a second plurality of text sections, without overruling the at least one modification received from the user; and generating a third structured text comprising the second plurality of text sections and a corresponding section heading for each of the second plurality of text sections. | 0.5 |
9,619,910 | 15 | 16 | 15. The computing device according to claim 14 , further comprising: receiving a second customization to a semantic property of the first shape; and updating the semantic property of the first shape with the second customization. | 15. The computing device according to claim 14 , further comprising: receiving a second customization to a semantic property of the first shape; and updating the semantic property of the first shape with the second customization. 16. The computing device according to claim 15 , further comprising: receiving a selection of a second graphical layout; and in response to the selection of the second graphical layout, rendering a second graphical diagram comprising a first shape that includes the first line of text and the updated semantic property but not the updated presentation property. | 0.5 |
10,019,259 | 1 | 2 | 1. A system, comprising: one or more processors; memory that includes a plurality of computer-executable components that are executable by the one or more processors, comprising: an extensibility library that includes one or more transformation directives, the one or more transformation directive specifying a business semantic preserving transform that transforms at least one source application component of a source application into one or more transformed application components of a transformed application, the business semantic preserving transform as specified by the one or more transformation directives of the extensibility library causes an execution of transformed code of the one or more transformed application components of the transformed application in a new execution scenario to produce an identical semantic effect as an execution of source code of the at least one source application component of the source application in an old execution scenario; and an transformation application that transforms the source application into the transformed application using the business semantic preserving transform, the business semantic preserving transform changing one or more original architectural classes of the source application into one or more transformed architectural classes of the transformed application, the one or more original architectural classes having at least one architectural difference from the one or more transformed architectural classes. | 1. A system, comprising: one or more processors; memory that includes a plurality of computer-executable components that are executable by the one or more processors, comprising: an extensibility library that includes one or more transformation directives, the one or more transformation directive specifying a business semantic preserving transform that transforms at least one source application component of a source application into one or more transformed application components of a transformed application, the business semantic preserving transform as specified by the one or more transformation directives of the extensibility library causes an execution of transformed code of the one or more transformed application components of the transformed application in a new execution scenario to produce an identical semantic effect as an execution of source code of the at least one source application component of the source application in an old execution scenario; and an transformation application that transforms the source application into the transformed application using the business semantic preserving transform, the business semantic preserving transform changing one or more original architectural classes of the source application into one or more transformed architectural classes of the transformed application, the one or more original architectural classes having at least one architectural difference from the one or more transformed architectural classes. 2. The system of claim 1 , wherein the at least one architectural difference resulted from a transformation of multiple source application components of the source application into a single transformed application component of the transformed application, or a transformation of a single source application component of the source application into multiple transformed application components of the transformed application based at least on the one or more transformation directives. | 0.5 |
8,411,859 | 13 | 18 | 13. A non-deterministic generator of numbers from a noise source providing a bit flow, the generator comprising: a storage device wherein the bit flow is parallelized to obtain first words, each first word including a first number of bits; a compression circuit configured to apply a compression function to the first words, resulting in second words; a diffusion/confusion circuit, separate and distinct from the compression circuit, configured to apply a diffusion/confusion function to the first words, resulting in third words, the first words being input to the compression circuit and to the diffusion/confusion circuit in parallel; an evaluating circuit configured to determine a second number of bits in the second words; and a selection circuit configured to select a second number of bits from an output of the diffusion/confusion circuit based on an output of the evaluating circuit, wherein the entropy per bit of the noise source is optimized by using the output of the compression circuit to select useful bits in the third words provided by the diffusion/confusion circuit, wherein a drift in the entropy of the noise source can be detected. | 13. A non-deterministic generator of numbers from a noise source providing a bit flow, the generator comprising: a storage device wherein the bit flow is parallelized to obtain first words, each first word including a first number of bits; a compression circuit configured to apply a compression function to the first words, resulting in second words; a diffusion/confusion circuit, separate and distinct from the compression circuit, configured to apply a diffusion/confusion function to the first words, resulting in third words, the first words being input to the compression circuit and to the diffusion/confusion circuit in parallel; an evaluating circuit configured to determine a second number of bits in the second words; and a selection circuit configured to select a second number of bits from an output of the diffusion/confusion circuit based on an output of the evaluating circuit, wherein the entropy per bit of the noise source is optimized by using the output of the compression circuit to select useful bits in the third words provided by the diffusion/confusion circuit, wherein a drift in the entropy of the noise source can be detected. 18. The generator of claim 13 , wherein the compression function is a Huffman function. | 0.713816 |
8,793,598 | 1 | 6 | 1. A method to be executed at least in part in a computing device for providing a cross-browser web dialog platform, the method comprising: presenting a web page to a user from a web application; in response to receiving a user selection, hiding at least a portion of displayed web page elements; presenting a dialog over the hidden web page elements within the web page; displaying a subset of contents of the web page inside the dialog such that common elements with a web page user interface are not displayed when the dialog is presented; in response to a user interaction with the web page inside the dialog changing to a content input mode, hiding controls associated with saving, deleting, and checking entire content by at least one from a set of: graying the controls, rendering the controls transparent, and modifying text and graphics colors; and presenting one or more links within the new web page by: interpreting the links within the new web page for desired link behavior; and specifying separate behaviors for the links based on the interpretation. | 1. A method to be executed at least in part in a computing device for providing a cross-browser web dialog platform, the method comprising: presenting a web page to a user from a web application; in response to receiving a user selection, hiding at least a portion of displayed web page elements; presenting a dialog over the hidden web page elements within the web page; displaying a subset of contents of the web page inside the dialog such that common elements with a web page user interface are not displayed when the dialog is presented; in response to a user interaction with the web page inside the dialog changing to a content input mode, hiding controls associated with saving, deleting, and checking entire content by at least one from a set of: graying the controls, rendering the controls transparent, and modifying text and graphics colors; and presenting one or more links within the new web page by: interpreting the links within the new web page for desired link behavior; and specifying separate behaviors for the links based on the interpretation. 6. The method of claim 1 , further comprising: implementing the web dialog platform in a cross-browser manner by employing a cross-browser script and style class enabling hosting of the new web page in a frame element of the web page. | 0.788427 |
9,830,404 | 1 | 4 | 1. A method, performed by a computing system, for generating trending action statistics that match a query, comprising: receiving, by a server, the query identifying one or more of: a search action or a search action target; selecting a set of posts relevant to the query, the set of posts comprising one or more action posts that contain at least one sentence that specifies a post action and a post action target; for one or more selected action posts of the one or more action posts: dividing the selected action post into one or more sentences; creating, for at least one action sentence of the one or more sentences, a dependency structure correlating a performed action identified in the action sentence with an action target identified in the action sentence, wherein the identification of the performed action comprises a first identifier, within the action sentence, corresponding to the performed action, and wherein the identification of the action target comprises a second identifier, within the action sentence, corresponding to one or more objects of the action sentence; determining, based on the dependency structure, that the selected action post matches the query by: determining that the search action specified in the query matches the performed action identified in the dependency structure; or determining that the search action target specified in the query matches the action target identified in the dependency structure; in response to determining that the selected action post matches the query, updating a count of matching actions or a count of matching action targets corresponding to the action or action target identified in the dependency structure; communicating between the server and a database to generate a response to the query by computing statistics based on the count of matching actions or the count of matching action targets; and providing the response to the query. | 1. A method, performed by a computing system, for generating trending action statistics that match a query, comprising: receiving, by a server, the query identifying one or more of: a search action or a search action target; selecting a set of posts relevant to the query, the set of posts comprising one or more action posts that contain at least one sentence that specifies a post action and a post action target; for one or more selected action posts of the one or more action posts: dividing the selected action post into one or more sentences; creating, for at least one action sentence of the one or more sentences, a dependency structure correlating a performed action identified in the action sentence with an action target identified in the action sentence, wherein the identification of the performed action comprises a first identifier, within the action sentence, corresponding to the performed action, and wherein the identification of the action target comprises a second identifier, within the action sentence, corresponding to one or more objects of the action sentence; determining, based on the dependency structure, that the selected action post matches the query by: determining that the search action specified in the query matches the performed action identified in the dependency structure; or determining that the search action target specified in the query matches the action target identified in the dependency structure; in response to determining that the selected action post matches the query, updating a count of matching actions or a count of matching action targets corresponding to the action or action target identified in the dependency structure; communicating between the server and a database to generate a response to the query by computing statistics based on the count of matching actions or the count of matching action targets; and providing the response to the query. 4. The method of claim 1 wherein: the received query further identifies additional criteria indicating one or more of: author location; author age; author gender; author group association; post keywords; post length; post language; post location; or post timeframe; and selecting the set of posts relevant to the query is based on the additional criteria. | 0.701178 |
9,779,236 | 13 | 14 | 13. A computer implemented method for risk assessment, comprising: a computer system evaluating historical authentication data to identify a set of authentication context properties associated with user authentication sessions; a computer system evaluating compromised user account data to identify a set of malicious account context properties associated with at least one of compromised user accounts or compromised user authentication events; a computer system annotating the set of authentication context properties and the set of malicious account context properties to create an annotated context properties training set; a computer system training a plurality of risk assessment machine learning modules based upon the annotated context properties training set to generate a plurality of risk assessment models, wherein each risk assessment model is responsive to a predefined context property; a computer system identifying a current user account event of a current user; a computer system evaluating a first current user context property of the current user using a first risk assessment model; a computer system evaluating a second current user context property of the current user using a second risk assessment model; a computer system aggregating results from the first and the second risk assessment models to generate a risk analysis metric; and a computer system moderating the current user account event based upon the risk analysis metric, wherein the current user account event is moderated by the computing system blocking the current user for a current session of the current user account event. | 13. A computer implemented method for risk assessment, comprising: a computer system evaluating historical authentication data to identify a set of authentication context properties associated with user authentication sessions; a computer system evaluating compromised user account data to identify a set of malicious account context properties associated with at least one of compromised user accounts or compromised user authentication events; a computer system annotating the set of authentication context properties and the set of malicious account context properties to create an annotated context properties training set; a computer system training a plurality of risk assessment machine learning modules based upon the annotated context properties training set to generate a plurality of risk assessment models, wherein each risk assessment model is responsive to a predefined context property; a computer system identifying a current user account event of a current user; a computer system evaluating a first current user context property of the current user using a first risk assessment model; a computer system evaluating a second current user context property of the current user using a second risk assessment model; a computer system aggregating results from the first and the second risk assessment models to generate a risk analysis metric; and a computer system moderating the current user account event based upon the risk analysis metric, wherein the current user account event is moderated by the computing system blocking the current user for a current session of the current user account event. 14. The method according to claim 13 , wherein the second current user context property is evaluated based on a first result obtained from the first risk assessment model. | 0.841667 |
8,151,292 | 1 | 7 | 1. A system comprising: a processor coupled to a database, the database including a media instance and reaction data, the media instance comprising a plurality of media events, the reaction data received from a plurality of viewers viewing the media instance; a first module coupled to the processor, the first module generating aggregated reaction data by aggregating the reaction data from the plurality of viewers, the first module generating synchronized data by synchronizing the plurality of media events of the media instance with corresponding aggregated reaction data; and a second module coupled to the processor, the second module comprising a plurality of renderings and a user interface (UI) that provide controlled access to the synchronized data from a remote device, wherein the controlled access includes interactive control of analysis of the reaction data and the corresponding events of the media instance. | 1. A system comprising: a processor coupled to a database, the database including a media instance and reaction data, the media instance comprising a plurality of media events, the reaction data received from a plurality of viewers viewing the media instance; a first module coupled to the processor, the first module generating aggregated reaction data by aggregating the reaction data from the plurality of viewers, the first module generating synchronized data by synchronizing the plurality of media events of the media instance with corresponding aggregated reaction data; and a second module coupled to the processor, the second module comprising a plurality of renderings and a user interface (UI) that provide controlled access to the synchronized data from a remote device, wherein the controlled access includes interactive control of analysis of the reaction data and the corresponding events of the media instance. 7. The system of claim 1 , wherein the plurality of renderings includes text, charts, graphs, histograms, images, and video. | 0.801917 |
8,886,626 | 10 | 11 | 10. The system of claim 9 , wherein identifying the user comprises authenticating the user. | 10. The system of claim 9 , wherein identifying the user comprises authenticating the user. 11. The system of claim 10 , wherein authenticating the user comprises authenticating the user based on an internet protocol (IP) address or a client-side cookie. | 0.5 |
7,831,588 | 1 | 10 | 1. A method for processing a search query having a plurality of search terms for searching for documents, the method comprising: segmenting the query to identify two or more units; expanding the query by selecting one or more substitutable units for at least one unit in the query; calculating a substitution probability for each substitutable unit; for each substitutable unit, calculating a co-occurrence probability with each of the remaining units in the search query; determining an occurrence probability for each substitutable unit; calculating a score based on the combination of the substitution probability, the co-occurrence probability, and occurrence probability; and ranking the documents in an order determined by the score. | 1. A method for processing a search query having a plurality of search terms for searching for documents, the method comprising: segmenting the query to identify two or more units; expanding the query by selecting one or more substitutable units for at least one unit in the query; calculating a substitution probability for each substitutable unit; for each substitutable unit, calculating a co-occurrence probability with each of the remaining units in the search query; determining an occurrence probability for each substitutable unit; calculating a score based on the combination of the substitution probability, the co-occurrence probability, and occurrence probability; and ranking the documents in an order determined by the score. 10. The method of claim 1 , wherein documents are retrieved from a corpus based on the segmented units and the substitutable units of the query using a likelihood-type document retrieval process. | 0.617647 |
9,183,832 | 14 | 19 | 14. A display apparatus comprising: a display unit which displays a first display item; a text determination unit which extracts a first text from the first display item; a voice recognition unit which recognizes a voice input from a user; and a controller which: displays the first text so as to distinguish the first text from other texts, determines if the recognized voice input corresponds to the first text, and controls the display unit to select the first display item in response to a determination that the recognized voice input corresponds to the first text, wherein the voice input comprises a voice of the user speaking at least a word from the first text, and wherein the text determination unit extracts the first text comprising at least one word from the display item such that the first text does not share common words with a second text extracted from a second display item. | 14. A display apparatus comprising: a display unit which displays a first display item; a text determination unit which extracts a first text from the first display item; a voice recognition unit which recognizes a voice input from a user; and a controller which: displays the first text so as to distinguish the first text from other texts, determines if the recognized voice input corresponds to the first text, and controls the display unit to select the first display item in response to a determination that the recognized voice input corresponds to the first text, wherein the voice input comprises a voice of the user speaking at least a word from the first text, and wherein the text determination unit extracts the first text comprising at least one word from the display item such that the first text does not share common words with a second text extracted from a second display item. 19. The display apparatus of claim 14 , wherein the first display item comprises a result of a search using a search engine. | 0.688442 |
8,180,751 | 1 | 3 | 1. A method, comprising: crawling a computer network to identify documents that name an individual; generating, by a system having a processor, summaries of the documents with articles in an encyclopedia; building, by the system, a profile of the individual with the summaries; and searching the profile to provide responses to search queries. | 1. A method, comprising: crawling a computer network to identify documents that name an individual; generating, by a system having a processor, summaries of the documents with articles in an encyclopedia; building, by the system, a profile of the individual with the summaries; and searching the profile to provide responses to search queries. 3. The method of claim 1 , wherein the summaries are generated from titles of the articles in the encyclopedia. | 0.82381 |
9,223,871 | 10 | 11 | 10. The system of claim 8 , wherein the processor is further configured to: construct a rule set from the subset of documents in the first domain; and apply the rule set to each page in the first domain. | 10. The system of claim 8 , wherein the processor is further configured to: construct a rule set from the subset of documents in the first domain; and apply the rule set to each page in the first domain. 11. The system of claim 10 , wherein the processor is further configured to: test the rule set to determine whether the rule set should be revised. | 0.5 |
9,547,937 | 17 | 20 | 17. A three-dimensional annotation method comprising: obtaining a source image that is two-dimensional or three-dimensional; displaying said source image on a screen associated with a first computer; accepting an annotation associated with a desired depth of a region within said source image via an input device coupled with said first computer wherein said input device comprises any combination of graphics tablet, mouse, keyboard or microphone; obtaining a at least one depth associated with said annotation by analyzing said annotation with text recognition software or by analyzing motion of a mouse or by parsing alphanumeric data from said keyboard or by asserting voice recognition software or any combination thereof; wherein said at least one depth corresponds with said desired depth of said region; and, annotating said source image with said annotation at said at least one depth in a three-dimensional image wherein said annotating said source image with said annotation at said at least one depth occurs before moving at least a portion of said region in said source image left and right to alter depth within the source image; and, generating an output stereoscopic image with said region at said same depth as said at least one depth of said annotation. | 17. A three-dimensional annotation method comprising: obtaining a source image that is two-dimensional or three-dimensional; displaying said source image on a screen associated with a first computer; accepting an annotation associated with a desired depth of a region within said source image via an input device coupled with said first computer wherein said input device comprises any combination of graphics tablet, mouse, keyboard or microphone; obtaining a at least one depth associated with said annotation by analyzing said annotation with text recognition software or by analyzing motion of a mouse or by parsing alphanumeric data from said keyboard or by asserting voice recognition software or any combination thereof; wherein said at least one depth corresponds with said desired depth of said region; and, annotating said source image with said annotation at said at least one depth in a three-dimensional image wherein said annotating said source image with said annotation at said at least one depth occurs before moving at least a portion of said region in said source image left and right to alter depth within the source image; and, generating an output stereoscopic image with said region at said same depth as said at least one depth of said annotation. 20. The method of claim 17 further comprising: displacing at least a portion of said region in said source image left and right based on said at least one depth to create an output three-dimensional image without said annotation. | 0.5 |
8,090,724 | 16 | 17 | 16. A computer program product including a computer-readable storage medium having instructions stored thereon for processing data information, such that the instructions, when carried out by a processing device, enable the processing device to perform the operations of: receiving a collection of text-based terms; analyzing groupings of consecutive text-based terms in the collection to identify occurrences of different combinations of text-based terms in the collection; based on the analyzing, creating a tree in which a first term in a given grouping of the groupings is defined as a parent node in the tree and a second term in the given grouping is defined as a child node of the parent node in the tree; and maintaining frequency information representing the occurrences of the different combinations of text-based terms in the collection. | 16. A computer program product including a computer-readable storage medium having instructions stored thereon for processing data information, such that the instructions, when carried out by a processing device, enable the processing device to perform the operations of: receiving a collection of text-based terms; analyzing groupings of consecutive text-based terms in the collection to identify occurrences of different combinations of text-based terms in the collection; based on the analyzing, creating a tree in which a first term in a given grouping of the groupings is defined as a parent node in the tree and a second term in the given grouping is defined as a child node of the parent node in the tree; and maintaining frequency information representing the occurrences of the different combinations of text-based terms in the collection. 17. The computer program product as in claim 16 further including instructions to support operations of: creating the tree such that the parent node represents a first word and the child node represents a second word, a combination of the parent node and the child node representing a phrase including the first word and the second word. | 0.73126 |
9,275,146 | 1 | 2 | 1. A computer-implemented method of generating a semantic query, comprising: receiving a query at a relational database having a processing component and a relational data store; identifying the query as a semantic query; determining whether the semantic query can be directly expressed within the relational database without requiring use of a semantic processing engine that is distinct from the relational database; if the semantic query can be directly expressed within the relational database, generating, by the relational database, a table valued function representing the semantic query and obtaining query results from the relational database using the table valued function: and if the semantic query cannot be directly expressed within the relational database, providing the semantic query, that was received at the relational database, to the semantic processing engine and receiving, at the relational database from the semantic processing engine, a processed semantic query for obtaining query results from the relational database. | 1. A computer-implemented method of generating a semantic query, comprising: receiving a query at a relational database having a processing component and a relational data store; identifying the query as a semantic query; determining whether the semantic query can be directly expressed within the relational database without requiring use of a semantic processing engine that is distinct from the relational database; if the semantic query can be directly expressed within the relational database, generating, by the relational database, a table valued function representing the semantic query and obtaining query results from the relational database using the table valued function: and if the semantic query cannot be directly expressed within the relational database, providing the semantic query, that was received at the relational database, to the semantic processing engine and receiving, at the relational database from the semantic processing engine, a processed semantic query for obtaining query results from the relational database. 2. The computer-implemented method of claim 1 wherein identifying the query as a semantic query comprises: determining that the query depends, for its application, on application of a semantic rule. | 0.5 |
9,002,817 | 10 | 18 | 10. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving in a search engine system a query, the query comprising query text submitted by a user; searching a first collection of resources to obtain one or more first search results, wherein each of the one or more first search results has a respective first search result score; searching a second collection of web resources to obtain one or more second search results, wherein each of the one or more second search results has a respective second search result score, wherein the resources of the first collection of resources are different from the resources of the second collection of web resources; determining from historical user click data that resources from the first collection of resources are more likely to be selected by users than resources from other collections of data when presented by the search engine in a response to the query text; generating enhanced first search result scores for the first search results as a consequence of the determining, the enhanced first search result scores being greater than the respective first search result scores for the first search results; generating a presentation order of first search results and second search results in order of the enhanced first search result scores and the second search result scores; generating a presentation of highest-ranked first search results and second search results in the presentation order; and providing the presentation in a response to the query. | 10. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving in a search engine system a query, the query comprising query text submitted by a user; searching a first collection of resources to obtain one or more first search results, wherein each of the one or more first search results has a respective first search result score; searching a second collection of web resources to obtain one or more second search results, wherein each of the one or more second search results has a respective second search result score, wherein the resources of the first collection of resources are different from the resources of the second collection of web resources; determining from historical user click data that resources from the first collection of resources are more likely to be selected by users than resources from other collections of data when presented by the search engine in a response to the query text; generating enhanced first search result scores for the first search results as a consequence of the determining, the enhanced first search result scores being greater than the respective first search result scores for the first search results; generating a presentation order of first search results and second search results in order of the enhanced first search result scores and the second search result scores; generating a presentation of highest-ranked first search results and second search results in the presentation order; and providing the presentation in a response to the query. 18. The system of claim 10 , wherein each respective first score for the first search results is based on a publication date of a resource corresponding to the first search result. | 0.835766 |
8,869,098 | 1 | 7 | 1. A computer method for generating software development model-to-model transformations from one software program domain having a respective structured hierarchy to a second software program domain, comprising: generating software development model-to-model transformations from a given domain of a software program to a target domain of the software program, at least the given domain having a respective structured hierarchy, by: enabling a user to model and specify a transformation declarative provided by a Model Transformation Authoring Framework (MTAF); in response to the user specified transformation declarative, creating a declarative mapping between a domain specific language modeling software development design of the software program in the given domain and a modeling language modeling software development design of the software program in the target domain, the declarative mapping specifying how the domain specific language of the given domain relates to the modeling language of the target domain; using the declarative mapping, generating a transformation code implementation of transformation from a software development model of the software program in the given domain to a software development model of the software program in the target domain, the generated transformation code being executable to perform a transformation of the domain specific language of the given domain to the modeling language of the target domain, said generating the transformation code implementation including augmenting the transformation code with more transformation logic that is unexpressible in the declarative mapping, wherein the MTAF provides to the user design decisions with respect to specification of the declarative mapping; and outputting instances of models of the software program in the target domain resulting from the performed transformation at runtime. | 1. A computer method for generating software development model-to-model transformations from one software program domain having a respective structured hierarchy to a second software program domain, comprising: generating software development model-to-model transformations from a given domain of a software program to a target domain of the software program, at least the given domain having a respective structured hierarchy, by: enabling a user to model and specify a transformation declarative provided by a Model Transformation Authoring Framework (MTAF); in response to the user specified transformation declarative, creating a declarative mapping between a domain specific language modeling software development design of the software program in the given domain and a modeling language modeling software development design of the software program in the target domain, the declarative mapping specifying how the domain specific language of the given domain relates to the modeling language of the target domain; using the declarative mapping, generating a transformation code implementation of transformation from a software development model of the software program in the given domain to a software development model of the software program in the target domain, the generated transformation code being executable to perform a transformation of the domain specific language of the given domain to the modeling language of the target domain, said generating the transformation code implementation including augmenting the transformation code with more transformation logic that is unexpressible in the declarative mapping, wherein the MTAF provides to the user design decisions with respect to specification of the declarative mapping; and outputting instances of models of the software program in the target domain resulting from the performed transformation at runtime. 7. A method as claimed in claim 1 wherein the MTAF provides to the user design decisions with respect to incrementality in the declarative mapping. | 0.716216 |
7,805,430 | 7 | 8 | 7. A method according to claim 1 , wherein the second values are names. | 7. A method according to claim 1 , wherein the second values are names. 8. A method according to claim 7 , wherein the second values are information corresponding to the names. | 0.5 |
8,316,293 | 5 | 6 | 5. A system for rendering presentation pages, comprising: a main server containing at least one resource including at least one of images and text, the main server comprising an extensible stylesheet transformation (XSLT) module operative for calling an XSL extension and rendering the at least one resource into a presentation page, based on a language requirement at a foreign locale; at least one proxy server configured to support localization of a display of a mobile device, the proxy server comprising a cache that caches at least one resource; and a deployment service deploying services from the main server to the proxy server configured to: save the at least one resource to the main server, notify the at least one proxy server of at least one new resource for retrieval from the main server, check the cache of the proxy server for the at least one new resource before retrieving the at least one new resource from the main server, and render through the proxy and the XSLT module at least one resource for repeated use. | 5. A system for rendering presentation pages, comprising: a main server containing at least one resource including at least one of images and text, the main server comprising an extensible stylesheet transformation (XSLT) module operative for calling an XSL extension and rendering the at least one resource into a presentation page, based on a language requirement at a foreign locale; at least one proxy server configured to support localization of a display of a mobile device, the proxy server comprising a cache that caches at least one resource; and a deployment service deploying services from the main server to the proxy server configured to: save the at least one resource to the main server, notify the at least one proxy server of at least one new resource for retrieval from the main server, check the cache of the proxy server for the at least one new resource before retrieving the at least one new resource from the main server, and render through the proxy and the XSLT module at least one resource for repeated use. 6. A system according to claim 5 , wherein a presentation page is rendered into localized content based on locale. | 0.732394 |
9,726,511 | 11 | 14 | 11. A method of operation of a navigation system comprising: determining candidate locations for a location query for a retail location from a location requestor; determining a candidate associated location, specific to each of the candidate locations, based on the frequency the candidate associated location is selected on a device and subsequently traveled to; generating a list of the candidate locations matching the retail location, wherein the list includes the candidate associated location for each of the candidate locations; determining a waypoint destination from an instance of the candidate locations based on a selected instance of the candidate associated location specific to the instance of the candidate locations; and calculating a travel route including the waypoint destination and the selected instance of the candidate associated location for displaying on the device; and calculating a popularity weighing scheme for the selected instance of the candidate associated location based on travel of the location requestor along the travel route to the selected instance of the candidate associated location. | 11. A method of operation of a navigation system comprising: determining candidate locations for a location query for a retail location from a location requestor; determining a candidate associated location, specific to each of the candidate locations, based on the frequency the candidate associated location is selected on a device and subsequently traveled to; generating a list of the candidate locations matching the retail location, wherein the list includes the candidate associated location for each of the candidate locations; determining a waypoint destination from an instance of the candidate locations based on a selected instance of the candidate associated location specific to the instance of the candidate locations; and calculating a travel route including the waypoint destination and the selected instance of the candidate associated location for displaying on the device; and calculating a popularity weighing scheme for the selected instance of the candidate associated location based on travel of the location requestor along the travel route to the selected instance of the candidate associated location. 14. The method as claimed in claim 11 wherein determining the candidate associated location includes determining the candidate associated location based on an adverting purpose of the candidate associated location. | 0.593156 |
9,569,615 | 17 | 18 | 17. A non-transitory computer readable medium, comprising computer executable instructions that when executed by a hardware processor perform operations comprising: receiving data from a plurality of sensors associated with a cyber physical system, wherein the receiving the data includes receiving time series data from the plurality of sensors monitoring the cyber physical system and wherein the cyber physical system is an electrical power grid system; constructing a metrization of the data utilizing a data structuring; determining at least one ensemble and at least one summary variable from the metrized data, wherein the at least one summary variable is based on automata model utilizing a probabilistic grammatical inference that includes discovering common subtrees of a string parse tree via a nonparametric Bayesian clustering method including a Dirichlet Process or a Beta Process or a diffusion map technique; applying a thermodynamic formalism to the at least one summary variable to classify a plurality of system behaviors; identifying the plurality of system behaviors based at least in part on the classified plurality of system behaviors; obtaining, by the one or more processors, a baseline of the system behavior associated with the classified plurality of systems behaviors; and detecting an anomalous condition based on a deviation of the plurality of system behaviors from the baseline. | 17. A non-transitory computer readable medium, comprising computer executable instructions that when executed by a hardware processor perform operations comprising: receiving data from a plurality of sensors associated with a cyber physical system, wherein the receiving the data includes receiving time series data from the plurality of sensors monitoring the cyber physical system and wherein the cyber physical system is an electrical power grid system; constructing a metrization of the data utilizing a data structuring; determining at least one ensemble and at least one summary variable from the metrized data, wherein the at least one summary variable is based on automata model utilizing a probabilistic grammatical inference that includes discovering common subtrees of a string parse tree via a nonparametric Bayesian clustering method including a Dirichlet Process or a Beta Process or a diffusion map technique; applying a thermodynamic formalism to the at least one summary variable to classify a plurality of system behaviors; identifying the plurality of system behaviors based at least in part on the classified plurality of system behaviors; obtaining, by the one or more processors, a baseline of the system behavior associated with the classified plurality of systems behaviors; and detecting an anomalous condition based on a deviation of the plurality of system behaviors from the baseline. 18. The non-transitory computer readable medium of claim 17 , wherein the determining the at least one summary variable includes a symbolic encoding of the metrized data and wherein the probabilistic grammatical inference comprises an ε-Machine Reconstruction statistical machine learning technique that includes describing a system trajectory as a string of symbols and describing system dynamics in terms of shift dynamics of the associated symbol string. | 0.5 |
8,826,210 | 17 | 20 | 17. A computer program product comprising a computer usable storage medium having readable program code embodied in the usable storage medium, the readable program code readable/executable by a computing device to cause the computing device to: verify whether a received current waveform is of a human voice; create a voiceprint from the received current waveform when the received current waveform is of the human voice; determine one of: whether a match exists between the voiceprint and one library waveform of one or more library waveforms; whether a correlation exists between the voiceprint and a number of library waveforms of the one or more library waveforms; and whether the voiceprint is unique; and transcribe the received current waveform into text; and provide a match indication display (MID) based on the determining. | 17. A computer program product comprising a computer usable storage medium having readable program code embodied in the usable storage medium, the readable program code readable/executable by a computing device to cause the computing device to: verify whether a received current waveform is of a human voice; create a voiceprint from the received current waveform when the received current waveform is of the human voice; determine one of: whether a match exists between the voiceprint and one library waveform of one or more library waveforms; whether a correlation exists between the voiceprint and a number of library waveforms of the one or more library waveforms; and whether the voiceprint is unique; and transcribe the received current waveform into text; and provide a match indication display (MID) based on the determining. 20. The computer program product of claim 17 , wherein the MID provides a temporal indication for the text comprising at least one of: an indicator arrow which change colors based on temporal proximity to current time; an indicator arrow which fade or become translucent based on temporal proximity to current time; and sequential numbers associatively displayed with the text. | 0.5 |
9,626,703 | 16 | 20 | 16. The system of claim 15 , wherein the one or more physical processors are further caused to: select a seller from which the product or service is to be purchased; and obtain seller information associated with the seller, wherein to complete the purchase transaction, the one or more physical processors are further caused to: complete, without further user input after the receipt of the user input, the purchase transaction based on the seller information, the payment information, and the shipping information. | 16. The system of claim 15 , wherein the one or more physical processors are further caused to: select a seller from which the product or service is to be purchased; and obtain seller information associated with the seller, wherein to complete the purchase transaction, the one or more physical processors are further caused to: complete, without further user input after the receipt of the user input, the purchase transaction based on the seller information, the payment information, and the shipping information. 20. The system of claim 16 , wherein the one or more physical processors are further caused to: obtain a predetermined set of sellers specified by an administrator of the system that is different than the user, wherein to select the seller, the one or more physical processors are further caused to: select the seller from the predetermined set of administrator-specified sellers. | 0.584245 |
8,073,818 | 1 | 7 | 1. In a computing environment, a computer-implemented method comprising: performing near-duplicate image retrieval with a computer processor, including detecting, with the computer processor, visual patterns in images, representing the visual patterns as visual pattern vectors, and using the visual pattern vectors and visual word vectors to determine, with the computer processor, similarity between images by ranking database images according to a similarity of each given database image with a query image, including by obtaining a query visual pattern vector for the query image, and for each given image, determining a visual pattern vector and computing a visual pattern-based similarity score for the given image by selecting a set of most similar database images based on a ranking of the database images according to the visual pattern-based similarity scores, and re-ranking the set of most similar database images by evaluating similarity for each specific image in the set of most similar database images via a visual word vector corresponding to the specific image and a query visual word vector corresponding to the query image. | 1. In a computing environment, a computer-implemented method comprising: performing near-duplicate image retrieval with a computer processor, including detecting, with the computer processor, visual patterns in images, representing the visual patterns as visual pattern vectors, and using the visual pattern vectors and visual word vectors to determine, with the computer processor, similarity between images by ranking database images according to a similarity of each given database image with a query image, including by obtaining a query visual pattern vector for the query image, and for each given image, determining a visual pattern vector and computing a visual pattern-based similarity score for the given image by selecting a set of most similar database images based on a ranking of the database images according to the visual pattern-based similarity scores, and re-ranking the set of most similar database images by evaluating similarity for each specific image in the set of most similar database images via a visual word vector corresponding to the specific image and a query visual word vector corresponding to the query image. 7. The computer-implemented method of claim 1 wherein performing the near-duplicate image retrieval comprises merging a visual word vector with a visual pattern vector for a first image into a first merged vector, merging a visual word vector with a visual pattern vector for a second image into a second merged vector, and determining a similarity score from the first merged vector and the second merged vector. | 0.629928 |
8,972,433 | 5 | 7 | 5. A computer-implemented method for retrieving data from a database, the method comprising: storing data in a computer database comprising a plurality of data tables; receiving from an application, executed by a computer system comprising a processor and a memory, a data request in a first language, wherein the data request indicates a data rule and a plurality of attributes corresponding to the data rule; and translating with a code generation engine, comprising a processor circuit and a memory circuit, using one or more translation formulas stored in a metadata database, the data request to a plurality of data queries of the data tables of the computer database, wherein the plurality of data queries are in a second language that is different from the first language, wherein a first data query of the plurality of data queries returns a first data element stored at a first data table of the plurality of data tables as a first attribute of the plurality of attributes, and wherein a second data query of the plurality of data queries returns a result of an application of the one or more translation formulas to a second data element stored at a second table of the plurality of data tables as a second attribute of the plurality of attributes, wherein the first data query comprises a first SQL statement and the second data query comprises a second SQL statement, and wherein the code generation engine is also programmed to execute the first and second SQL statements, and, in response to the data request, return a result set to the application, wherein the result set comprises the first attribute and the second attribute, and wherein the code generation engine comprises a processor circuit, a memory circuit, and a metadata database comprising computer database metadata. | 5. A computer-implemented method for retrieving data from a database, the method comprising: storing data in a computer database comprising a plurality of data tables; receiving from an application, executed by a computer system comprising a processor and a memory, a data request in a first language, wherein the data request indicates a data rule and a plurality of attributes corresponding to the data rule; and translating with a code generation engine, comprising a processor circuit and a memory circuit, using one or more translation formulas stored in a metadata database, the data request to a plurality of data queries of the data tables of the computer database, wherein the plurality of data queries are in a second language that is different from the first language, wherein a first data query of the plurality of data queries returns a first data element stored at a first data table of the plurality of data tables as a first attribute of the plurality of attributes, and wherein a second data query of the plurality of data queries returns a result of an application of the one or more translation formulas to a second data element stored at a second table of the plurality of data tables as a second attribute of the plurality of attributes, wherein the first data query comprises a first SQL statement and the second data query comprises a second SQL statement, and wherein the code generation engine is also programmed to execute the first and second SQL statements, and, in response to the data request, return a result set to the application, wherein the result set comprises the first attribute and the second attribute, and wherein the code generation engine comprises a processor circuit, a memory circuit, and a metadata database comprising computer database metadata. 7. The method of claim 5 , wherein the second language is SQL-based language. | 0.741611 |
9,706,265 | 1 | 14 | 1. A system comprising: a networked device, residing in a private network of Internet, and configured to: announce a networked service to a discovery service, and enable performing the discovery service for the private network; a client device residing in a same private network of the Internet as the networked device, the client device being configured to execute a sandboxed program in a security sandbox and to automatically instantiate a connection between the sandboxed program and at least one of the networked device and the networked service; and a Network Address Translator (NAT) straddling both the same private network and a public network of the Internet, wherein, as part of the automatic instantiation of the connection between the sandboxed program and the at least one of the networked device and the networked service, the NAT is configured to translate a private address of an announce message related to the announcement of the networked service to a public address thereof including a public Internet Protocol (IP) address, the sandboxed program is configured to address a discovery message to the discovery service from a private address thereof, the NAT is configured to translate the private address of the sandboxed program to a public address thereof including a public IP address when the discovery message transits the NAT, the discovery service is configured to perform a lookup based on the public IP address of the sandboxed program to determine at least one device having a same public IP address to determine that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, and in accordance with the determination that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, the discovery service is configured to respond with service information for the at least one of the networked device and the networked service. | 1. A system comprising: a networked device, residing in a private network of Internet, and configured to: announce a networked service to a discovery service, and enable performing the discovery service for the private network; a client device residing in a same private network of the Internet as the networked device, the client device being configured to execute a sandboxed program in a security sandbox and to automatically instantiate a connection between the sandboxed program and at least one of the networked device and the networked service; and a Network Address Translator (NAT) straddling both the same private network and a public network of the Internet, wherein, as part of the automatic instantiation of the connection between the sandboxed program and the at least one of the networked device and the networked service, the NAT is configured to translate a private address of an announce message related to the announcement of the networked service to a public address thereof including a public Internet Protocol (IP) address, the sandboxed program is configured to address a discovery message to the discovery service from a private address thereof, the NAT is configured to translate the private address of the sandboxed program to a public address thereof including a public IP address when the discovery message transits the NAT, the discovery service is configured to perform a lookup based on the public IP address of the sandboxed program to determine at least one device having a same public IP address to determine that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, and in accordance with the determination that the sandboxed program and the at least one of the networked device and the networked service reside in the same private network, the discovery service is configured to respond with service information for the at least one of the networked device and the networked service. 14. The system of claim 1 : wherein the sandboxed program is configured to process a hardware address associated with the sandboxed program from the at least one of the networked device and the networked service. | 0.882091 |
9,405,856 | 1 | 6 | 1. One or more hardware memory devices storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method for providing task-oriented query-completion suggestions, the method comprising: receiving at least a portion of a search query; determining the received search query portion is suggestive of a task-oriented user intent, wherein the task-oriented user intent includes a user task that occurs subsequent to accessing search results and is an ultimate intent of the search query; and accessing a data store that stores associations between user tasks and query-completion suggestions; based on the determined user task, identifying one or more query-completion suggestions that are associated with the user task in the data store; providing at least one of the identified one or more query-completion suggestions that are associated with the user task of which the received search query portion is suggestive. | 1. One or more hardware memory devices storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method for providing task-oriented query-completion suggestions, the method comprising: receiving at least a portion of a search query; determining the received search query portion is suggestive of a task-oriented user intent, wherein the task-oriented user intent includes a user task that occurs subsequent to accessing search results and is an ultimate intent of the search query; and accessing a data store that stores associations between user tasks and query-completion suggestions; based on the determined user task, identifying one or more query-completion suggestions that are associated with the user task in the data store; providing at least one of the identified one or more query-completion suggestions that are associated with the user task of which the received search query portion is suggestive. 6. The one or more hardware memory devices of claim 1 , wherein providing the at least one query-completion suggestion that represents the suggested task-oriented user intent comprises providing one or more selectable indicators each of which represents an actionable query-completion selection. | 0.591413 |
9,412,363 | 17 | 18 | 17. The computer-readable storage medium of claim 15 , wherein identifying an item among the plurality of items comprises: identifying an explicit reference to the item based on a portion of text in the second utterance; identifying an explicit reference to the item based on a textual cue in the second utterance; and identifying an explicit reference to the item based on screen location data in the second utterance. | 17. The computer-readable storage medium of claim 15 , wherein identifying an item among the plurality of items comprises: identifying an explicit reference to the item based on a portion of text in the second utterance; identifying an explicit reference to the item based on a textual cue in the second utterance; and identifying an explicit reference to the item based on screen location data in the second utterance. 18. The computer-readable storage medium of claim 17 , wherein identifying an item among the plurality of items further comprises: identifying an implicit reference to the item based on the second utterance; and identifying an implicit reference to a position of the item based on the second utterance. | 0.5 |
9,710,613 | 12 | 16 | 12. One or more non-transitory computer-readable media comprising computer executable instructions that, when executed, cause at least one processor to perform actions comprising: receiving a request from a user of a first device to speak with a character, wherein the character is associated with a text-to-speech voice; sending a message to a user of a second device corresponding to the request; entering into a session with the second device, wherein, during the session, the user of the second device specifies a phrase that is spoken by the character to the user of the first device and wherein the user of the first device and the user of the second device participate simultaneously in the session; presenting the character on a display of the first device; obtaining an audio signal from a microphone of the first device; transmitting audio data to the second device, wherein the audio data is generated from the audio signal; receiving, from the second device, phrase data corresponding to the phrase to be spoken by the character; generating an audio signal using the phrase data corresponding to the phrase and the text-to-speech voice of the character; and causing audio to played corresponding to the audio signal. | 12. One or more non-transitory computer-readable media comprising computer executable instructions that, when executed, cause at least one processor to perform actions comprising: receiving a request from a user of a first device to speak with a character, wherein the character is associated with a text-to-speech voice; sending a message to a user of a second device corresponding to the request; entering into a session with the second device, wherein, during the session, the user of the second device specifies a phrase that is spoken by the character to the user of the first device and wherein the user of the first device and the user of the second device participate simultaneously in the session; presenting the character on a display of the first device; obtaining an audio signal from a microphone of the first device; transmitting audio data to the second device, wherein the audio data is generated from the audio signal; receiving, from the second device, phrase data corresponding to the phrase to be spoken by the character; generating an audio signal using the phrase data corresponding to the phrase and the text-to-speech voice of the character; and causing audio to played corresponding to the audio signal. 16. The one or more computer-readable media of claim 12 , the actions comprising: receiving a request from the second device to play an audio or video clip; and causing the audio or video clip to be presented by the first device. | 0.641066 |
8,045,803 | 7 | 8 | 7. A microprocessor implemented method of recognizing handwritten, independent symbols and outputting the corresponding Latin derived alphabetic character comprising the steps of: (a) receiving an electronic stylus input comprising a trace path of one or more symbols selected from a first or second set of a universal computer script of a Latin derived alphabet; (b) sequentially timed Cartesian coordinate mapping of the trace path; (c) if the trace path is a dot made within 0.5 seconds from the last trace path, engaging an edit mode of the program; (d) if not a dot, smoothing of the trace path; (e) determining in which quadrant the trace path starts and assigning that start quadrant to that trace path; (f) assigning change points by determination of changes in x direction, y direction, and in both the x and y direction simultaneously and determining an end point of the trace path; (g) summing the number of direction change points start point and an end point; (h) if the sum is two proceeding to step (k); (i) if the sum is three to seven proceeding to step (w); (j) if the sum is greater than seven non assignment of a character and returning to step (a) with a next new stylus input; (k) determining the slope of the line between the start point and the end point, or the start point and the change point, or a change point and a change point or the change point and an end point; (l) determining if the slope of the line is greater than (shallow) or less than (sharp) an assigned first critical angle (or boundary slope); (m) if the slope is sharp proceeding to step (o); (n) if the slope is shallow, based on start quadrant determining if the trace path is short or long and generating a character and return to step (a); (o) if slope is sharp, based on start quadrant determining the concavity or the convexity; (p) determining if the trace path is long or short, and if long, generating a character and returning to step (l); (q) if trace path is short assigning a flat value to trace path (high or low concavity); (r) establishing a base three identification number or concatenating the change point name(s) (x, y, z) into an ID name; (s) calculating the slope of the lines between all points; (t) checking the trace path flatness and ID name; (u) if trace-path is flat, generating a character and returning to step (a); (v) if trace path is not flat, assigning a character and returning to step (a); (w) checking the trace path for flatness and assigning an ID name; (x) determining the slope between start point, change points and end point (the important points); (y) querying the number of points, the assigned ID and the start quadrant; (z) checking for flatness and assigning a value; (aa) if flat assigning a value, if not flat possible determining output value; (ab) if not flat but an output value is generated checking for presence of a calculate symbol and a math mode, calculating a mathematical formula to generate an output value and returning to step (a); (ac) if not in math mode, outputting no value and returning to step (a); (ad) if unable to generate character and a calculate symbol is not present, testing stroke slope against a first critical angle; (ae) if first critical angle is shallow, generating a character if possible and returning to step (a); (af) if unable to assign a character testing a second stroke slope against a second critical angle (ag) if first critical angle is sharp testing a second stroke slope against a second critical angle; (ah) if identification is possible, assigning a character and returning to step (a); (ai) if identification is not possible, comparing a critical point relationship, assigning a character, and returning to step (a); (aj) if first critical angle is shallow testing a second stroke slope against a second critical angle; (ak) if identification is possible, assigning a character and returning to step (a); (al) if identification is not possible, comparing a critical point relationship, assigning a character, and returning to step (a); (am) if first critical angle is sharp, generating a character if possible and returning to step (a); (an) if unable to assign a character testing a second stroke slope against a second critical angle; (ao) if first critical angle is sharp testing a second stroke slope against a second critical angle; (ap) if identification is possible, assigning a character and returning to step (a); (aq) if identification is not possible, comparing a critical point relationship, assigning a character, and returning to step (a); (ar) if first critical angle is shallow testing a second stroke slope against a second critical angle; (as) if identification is possible, assigning a character and returning to step (a); (at) if identification is not possible, comparing a critical point relationship, assigning a character, and returning to step (a). | 7. A microprocessor implemented method of recognizing handwritten, independent symbols and outputting the corresponding Latin derived alphabetic character comprising the steps of: (a) receiving an electronic stylus input comprising a trace path of one or more symbols selected from a first or second set of a universal computer script of a Latin derived alphabet; (b) sequentially timed Cartesian coordinate mapping of the trace path; (c) if the trace path is a dot made within 0.5 seconds from the last trace path, engaging an edit mode of the program; (d) if not a dot, smoothing of the trace path; (e) determining in which quadrant the trace path starts and assigning that start quadrant to that trace path; (f) assigning change points by determination of changes in x direction, y direction, and in both the x and y direction simultaneously and determining an end point of the trace path; (g) summing the number of direction change points start point and an end point; (h) if the sum is two proceeding to step (k); (i) if the sum is three to seven proceeding to step (w); (j) if the sum is greater than seven non assignment of a character and returning to step (a) with a next new stylus input; (k) determining the slope of the line between the start point and the end point, or the start point and the change point, or a change point and a change point or the change point and an end point; (l) determining if the slope of the line is greater than (shallow) or less than (sharp) an assigned first critical angle (or boundary slope); (m) if the slope is sharp proceeding to step (o); (n) if the slope is shallow, based on start quadrant determining if the trace path is short or long and generating a character and return to step (a); (o) if slope is sharp, based on start quadrant determining the concavity or the convexity; (p) determining if the trace path is long or short, and if long, generating a character and returning to step (l); (q) if trace path is short assigning a flat value to trace path (high or low concavity); (r) establishing a base three identification number or concatenating the change point name(s) (x, y, z) into an ID name; (s) calculating the slope of the lines between all points; (t) checking the trace path flatness and ID name; (u) if trace-path is flat, generating a character and returning to step (a); (v) if trace path is not flat, assigning a character and returning to step (a); (w) checking the trace path for flatness and assigning an ID name; (x) determining the slope between start point, change points and end point (the important points); (y) querying the number of points, the assigned ID and the start quadrant; (z) checking for flatness and assigning a value; (aa) if flat assigning a value, if not flat possible determining output value; (ab) if not flat but an output value is generated checking for presence of a calculate symbol and a math mode, calculating a mathematical formula to generate an output value and returning to step (a); (ac) if not in math mode, outputting no value and returning to step (a); (ad) if unable to generate character and a calculate symbol is not present, testing stroke slope against a first critical angle; (ae) if first critical angle is shallow, generating a character if possible and returning to step (a); (af) if unable to assign a character testing a second stroke slope against a second critical angle (ag) if first critical angle is sharp testing a second stroke slope against a second critical angle; (ah) if identification is possible, assigning a character and returning to step (a); (ai) if identification is not possible, comparing a critical point relationship, assigning a character, and returning to step (a); (aj) if first critical angle is shallow testing a second stroke slope against a second critical angle; (ak) if identification is possible, assigning a character and returning to step (a); (al) if identification is not possible, comparing a critical point relationship, assigning a character, and returning to step (a); (am) if first critical angle is sharp, generating a character if possible and returning to step (a); (an) if unable to assign a character testing a second stroke slope against a second critical angle; (ao) if first critical angle is sharp testing a second stroke slope against a second critical angle; (ap) if identification is possible, assigning a character and returning to step (a); (aq) if identification is not possible, comparing a critical point relationship, assigning a character, and returning to step (a); (ar) if first critical angle is shallow testing a second stroke slope against a second critical angle; (as) if identification is possible, assigning a character and returning to step (a); (at) if identification is not possible, comparing a critical point relationship, assigning a character, and returning to step (a). 8. The method of claim 7 wherein a sharp line is determined as a line having a slope less than a slope of a line bisecting the start quadrant, and a sharp line is determined as a line having a slope greater than the slope of a line bisecting the start quadrant. | 0.588328 |
7,978,353 | 15 | 16 | 15. The document input and output device as claimed in claim 10 , further comprising: restriction means configured to limit use of functions of the document input and output device, wherein the restriction means limits a function of sending a facsimile of the protected document with respect to one or more senders. | 15. The document input and output device as claimed in claim 10 , further comprising: restriction means configured to limit use of functions of the document input and output device, wherein the restriction means limits a function of sending a facsimile of the protected document with respect to one or more senders. 16. The document input and output device as claimed in claim 15 , wherein the restriction means limits e-mail and Web page functions associated with the protected document. | 0.535135 |
8,996,473 | 2 | 3 | 2. The method of claim 1 , wherein processing the extended FSM and the one or more goals comprises generating one or more traces, each trace defining a path of status vectors and actions that are possible through the extended SAM schema. | 2. The method of claim 1 , wherein processing the extended FSM and the one or more goals comprises generating one or more traces, each trace defining a path of status vectors and actions that are possible through the extended SAM schema. 3. The method of claim 2 , wherein processing the extended FSM and the one or more goals further comprises: determining that at least one status vector of each primary goal of the one or more goals appears in at least one trace; determining that every maximal finite trace of the one or more traces ends in a status vector of any goal; determining that from every status vector of any infinite trace, a status vector of any goal is reachable; and in response, indicating that the extended SAM schema is valid. | 0.5 |
9,058,407 | 25 | 26 | 25. The computer-readable medium of claim 23 , where the assembly instructions include a delete instruction that identifies a segment of the binary data associated with the multimedia content to be excluded from a version. | 25. The computer-readable medium of claim 23 , where the assembly instructions include a delete instruction that identifies a segment of the binary data associated with the multimedia content to be excluded from a version. 26. The computer-readable medium of claim 25 , where the assembly instructions include an addition instruction that identifies a segment of binary data to be added to the binary data associated with the multimedia content. | 0.5 |
7,912,795 | 10 | 12 | 10. A system for predicting a future event associated with a business based on historical data associated with a model of past events of the business, comprising: a non-transitory memory communicating with a processor, the non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations comprising: performing a transformation of a plurality of modeling variables to obtain a linear relationship of each of the plurality of modeling variables in relation to the dependent variable, wherein the plurality of modeling variables are associated with the model, and wherein a dependent variable is associated with the model and is dependent on the plurality of modeling variables, and wherein the historical data is associated with the model; selecting a subset of the plurality of transformed modeling variables, wherein the selecting comprises applying a selecting rule based on a log-likelihood difference that comprises determining a difference between a first model-fit statistic derived by utilizing an intercept model and a second model-fit statistic derived by utilizing an intercept-plus-covariate model; determining a set of prediction variables; and generating a predictive model using the set of prediction variables, wherein the predictive model predicts the future event. | 10. A system for predicting a future event associated with a business based on historical data associated with a model of past events of the business, comprising: a non-transitory memory communicating with a processor, the non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations comprising: performing a transformation of a plurality of modeling variables to obtain a linear relationship of each of the plurality of modeling variables in relation to the dependent variable, wherein the plurality of modeling variables are associated with the model, and wherein a dependent variable is associated with the model and is dependent on the plurality of modeling variables, and wherein the historical data is associated with the model; selecting a subset of the plurality of transformed modeling variables, wherein the selecting comprises applying a selecting rule based on a log-likelihood difference that comprises determining a difference between a first model-fit statistic derived by utilizing an intercept model and a second model-fit statistic derived by utilizing an intercept-plus-covariate model; determining a set of prediction variables; and generating a predictive model using the set of prediction variables, wherein the predictive model predicts the future event. 12. The system of claim 10 , wherein the determining is based on a regression of the subset of the plurality of transformed variables. | 0.788644 |
7,761,342 | 1 | 3 | 1. A computer controlled method comprising: receiving by a review-provider server a review request for a first reviewed subject to be provided to a requesting user; selecting by the review-provider server one or more reviews of said first reviewed subject responsive to said review request; computing by the review-provider server one or more social distances between user-authors of said one or more reviews and said requesting user; and sorting by the review-provider server the one or more reviews responsive to said one or more social distances; and sending by the review-provider server the one or more sorted reviews responsive to said review request for presentation to said requesting user. | 1. A computer controlled method comprising: receiving by a review-provider server a review request for a first reviewed subject to be provided to a requesting user; selecting by the review-provider server one or more reviews of said first reviewed subject responsive to said review request; computing by the review-provider server one or more social distances between user-authors of said one or more reviews and said requesting user; and sorting by the review-provider server the one or more reviews responsive to said one or more social distances; and sending by the review-provider server the one or more sorted reviews responsive to said review request for presentation to said requesting user. 3. The computer controlled method as recited in claim 1 , wherein computing further comprises determining whether said user-author is a member of an aggregated group. | 0.715753 |
9,760,637 | 1 | 5 | 1. A method for performing wildcard search of encrypted cloud stored data comprising: receiving, at a network intermediary, a document destined for a cloud service provider; encrypting, at a network intermediary, the document using a document encryption algorithm; generating a set of permuted keyword strings for each of some or all of the keywords in the document, the set of permuted keyword strings for each keyword being generated by adding a first character delimiter before the first character of the keyword and applying cyclic rotation of the characters of the keyword, including the first character delimiter; encrypting the permuted keyword strings using an order preserving encryption algorithm; storing the encrypted permuted keyword strings in a database; transmitting the encrypted document to the cloud service provider; receiving, at a network intermediary, a search request with a search term directed to encrypted documents stored in a cloud service provider, the search term comprising a wildcard search term; transforming the wildcard search term to a permuted search term having a prefix search format; generating a minimum possible plaintext string using the permuted search term as prefix and padding the permuted search term to a first character length using one or more trailing characters indicative of a minimum possible value related to the search term; generating a maximum possible plaintext string using the permuted search term as prefix and padding the permuted search term to the first character length using one or more trailing characters indicative of a maximum possible value related to the search term; encrypting the minimum possible plaintext string and the maximum possible plaintext string using the order-preserving encryption algorithm used to encrypt the permuted keyword strings; generating a minimum ciphertext from the minimum possible plaintext string and a maximum ciphertext from the maximum possible plaintext string; determining a set of common leading digits from the minimum ciphertext and the maximum ciphertext; generating a range query including the set of common leading digits; sending the range query to the database of encrypted permuted keyword strings; and receiving a search result from the database including encrypted permuted keyword strings having ciphertext values that fall within the range query. | 1. A method for performing wildcard search of encrypted cloud stored data comprising: receiving, at a network intermediary, a document destined for a cloud service provider; encrypting, at a network intermediary, the document using a document encryption algorithm; generating a set of permuted keyword strings for each of some or all of the keywords in the document, the set of permuted keyword strings for each keyword being generated by adding a first character delimiter before the first character of the keyword and applying cyclic rotation of the characters of the keyword, including the first character delimiter; encrypting the permuted keyword strings using an order preserving encryption algorithm; storing the encrypted permuted keyword strings in a database; transmitting the encrypted document to the cloud service provider; receiving, at a network intermediary, a search request with a search term directed to encrypted documents stored in a cloud service provider, the search term comprising a wildcard search term; transforming the wildcard search term to a permuted search term having a prefix search format; generating a minimum possible plaintext string using the permuted search term as prefix and padding the permuted search term to a first character length using one or more trailing characters indicative of a minimum possible value related to the search term; generating a maximum possible plaintext string using the permuted search term as prefix and padding the permuted search term to the first character length using one or more trailing characters indicative of a maximum possible value related to the search term; encrypting the minimum possible plaintext string and the maximum possible plaintext string using the order-preserving encryption algorithm used to encrypt the permuted keyword strings; generating a minimum ciphertext from the minimum possible plaintext string and a maximum ciphertext from the maximum possible plaintext string; determining a set of common leading digits from the minimum ciphertext and the maximum ciphertext; generating a range query including the set of common leading digits; sending the range query to the database of encrypted permuted keyword strings; and receiving a search result from the database including encrypted permuted keyword strings having ciphertext values that fall within the range query. 5. The method of claim 1 , further comprising: decrypting the encrypted permuted keyword strings in the search result using the order preserving encryption algorithm; and unpermuting, using the first character delimiter, the decrypted permuted keyword strings to obtain plaintext keyword strings with the first character of each plaintext keyword string in a first position in the plaintext keyword string. | 0.672052 |
9,158,839 | 10 | 11 | 10. A system comprising: a memory; a processing device coupled to the memory, the processing device configured to: receive a data set, wherein the data set is annotated with at least a first annotation and at least a second annotation, wherein at least the first annotation and the second annotation represent within the data set; determine a first identifier from the first annotation and a second identifier from the second annotation; associate the first identifier to the second identifier to generate at least one joined identifier, wherein the at least one joined identifier is placed between the first annotation and the second annotation; compute a feature weight and a transition weight for the annotated data set based on the first annotation, the second annotation, and the at least one joined identifier and a transition between each of the first annotation, the second annotation and the at least one joined identifier; receive a second data set, wherein the second data set is un-annotated; and classify the second data set based on the computed feature weight and the transition weight from the first data set. | 10. A system comprising: a memory; a processing device coupled to the memory, the processing device configured to: receive a data set, wherein the data set is annotated with at least a first annotation and at least a second annotation, wherein at least the first annotation and the second annotation represent within the data set; determine a first identifier from the first annotation and a second identifier from the second annotation; associate the first identifier to the second identifier to generate at least one joined identifier, wherein the at least one joined identifier is placed between the first annotation and the second annotation; compute a feature weight and a transition weight for the annotated data set based on the first annotation, the second annotation, and the at least one joined identifier and a transition between each of the first annotation, the second annotation and the at least one joined identifier; receive a second data set, wherein the second data set is un-annotated; and classify the second data set based on the computed feature weight and the transition weight from the first data set. 11. The system of claim 10 wherein the processing device is further configured to provide the classified second data set to a user. | 0.511194 |
9,699,490 | 6 | 7 | 6. A system comprising: a computing system comprising one or more hardware computing devices, said computing system configured to at least: access contextual information associated with a browse session for a user, wherein the contextual information includes one or more attributes indicative of a user browsing context for the browse session; determine the user browsing context with respect to items available from an electronic catalog based at least in part on the contextual information; generate a candidate list of candidate digital content recommendation items for the user such that the candidate list includes (i) one or more items from a watch list associated with the user and (ii) one or more additional items not in the watch list, the watch list indicative of one or more items added to the watch list and when the one or more items were added to the watch list; determine, based at least in part on an amount of time elapsed between (i) when a given item is added to the watch list and (ii) when the given item is watched, a time interval by which to filter the candidate list; remove one or more candidate items that do not satisfy the determined time interval from the candidate list; and output one or more digital content item recommendations from the candidate list that does not include the one or more removed candidate items. | 6. A system comprising: a computing system comprising one or more hardware computing devices, said computing system configured to at least: access contextual information associated with a browse session for a user, wherein the contextual information includes one or more attributes indicative of a user browsing context for the browse session; determine the user browsing context with respect to items available from an electronic catalog based at least in part on the contextual information; generate a candidate list of candidate digital content recommendation items for the user such that the candidate list includes (i) one or more items from a watch list associated with the user and (ii) one or more additional items not in the watch list, the watch list indicative of one or more items added to the watch list and when the one or more items were added to the watch list; determine, based at least in part on an amount of time elapsed between (i) when a given item is added to the watch list and (ii) when the given item is watched, a time interval by which to filter the candidate list; remove one or more candidate items that do not satisfy the determined time interval from the candidate list; and output one or more digital content item recommendations from the candidate list that does not include the one or more removed candidate items. 7. The system of claim 6 , wherein the determined user browsing context is indicative of the user exploring video content items to add to the watch list during the browse session of the user. | 0.756378 |
8,756,515 | 11 | 12 | 11. The method of claim 1 , further comprising instantiating a data flow engine to support transformations of collections, records and atoms and track dependencies across declarative model data items. | 11. The method of claim 1 , further comprising instantiating a data flow engine to support transformations of collections, records and atoms and track dependencies across declarative model data items. 12. The method of claim 11 , further comprising implementing a UI model interpreter to perform the following in real-time: receive the declaratively defined UI model, interpret the UI model via functional transformation using the data flow engine and present the resulting UI to the user. | 0.5 |
7,523,077 | 1 | 2 | 1. A computer-implemented method of creating a knowledge repository for containing instances of knowledge entities, the method comprising: receiving, in a computer system, a first input to form a configuration template for a knowledge repository, the configuration template describing a class of knowledge entities to be included in the knowledge repository; receiving a second input identifying a document template to be used in displaying instances of the class of knowledge entities, the document template being selected from a predefined group of document templates and the configuration template specifying how contents of the instances of the class of knowledge entities are displayed using the selected document template; and creating the knowledge repository by storing at least one of the instances of the class of knowledge entities in the computer system, the document template being associated with the configuration template in the computer system for use in creating a remainder of the instances of the class of knowledge entities. | 1. A computer-implemented method of creating a knowledge repository for containing instances of knowledge entities, the method comprising: receiving, in a computer system, a first input to form a configuration template for a knowledge repository, the configuration template describing a class of knowledge entities to be included in the knowledge repository; receiving a second input identifying a document template to be used in displaying instances of the class of knowledge entities, the document template being selected from a predefined group of document templates and the configuration template specifying how contents of the instances of the class of knowledge entities are displayed using the selected document template; and creating the knowledge repository by storing at least one of the instances of the class of knowledge entities in the computer system, the document template being associated with the configuration template in the computer system for use in creating a remainder of the instances of the class of knowledge entities. 2. The method of claim 1 , wherein the configuration template defines each of the knowledge entities as including a basic entity and a content entity, the content entity to be merged with the document template for displaying the knowledge entity. | 0.631737 |
8,078,965 | 9 | 12 | 9. The method of claim 1 , prior to querying the font scheme definition for the selected font scheme to determine the at least two different font types associated with only the first and different languages in the first and second text runs, passing a parameter identifying a language associated with each of the first and second text runs to the font scheme definition. | 9. The method of claim 1 , prior to querying the font scheme definition for the selected font scheme to determine the at least two different font types associated with only the first and different languages in the first and second text runs, passing a parameter identifying a language associated with each of the first and second text runs to the font scheme definition. 12. The method of claim 9 , wherein passing a parameter identifying a language associated with each of the first and second text runs to the font scheme definition includes passing a script (ID) parameter for each of the first and second text runs via an application programming interface operative to map the script ID for each of the first and second text runs to each of the at least two different font types in the font scheme definition. | 0.5 |
8,260,604 | 7 | 8 | 7. A system for providing an interface to translate automatically timed text for web video, comprising: a computing device; a web browser implemented on the computing device; a video player downloaded from a web server to the computing device and run within the web browser that: (a) plays the web video with timed text in a language of audio for the web video; (b) while the web video is being played in (a), presents, in a single view, a first user interface control, the first user interface control including an first option to translate from the language of the audio for the web video to a default language and a second option to present a second user interface control; when the user selects the second option: (c) presents the second user interface control, the second user interface control enabling input of a target language; (d) receives a user's selection of the target language in the second user interface control presented in (c); (e) sends a request for a translation, the request including a target translation language, wherein the target translation language is the default language when the user selects the first option, and wherein the target translation language is the target language selected in (c) when the user selects the second option; (f) in response to the request, receives a timed text track including text automatically translated to the target language; and (g) displays at least a portion of the timed text track synchronized with the web video according to timing data in the timed text track. | 7. A system for providing an interface to translate automatically timed text for web video, comprising: a computing device; a web browser implemented on the computing device; a video player downloaded from a web server to the computing device and run within the web browser that: (a) plays the web video with timed text in a language of audio for the web video; (b) while the web video is being played in (a), presents, in a single view, a first user interface control, the first user interface control including an first option to translate from the language of the audio for the web video to a default language and a second option to present a second user interface control; when the user selects the second option: (c) presents the second user interface control, the second user interface control enabling input of a target language; (d) receives a user's selection of the target language in the second user interface control presented in (c); (e) sends a request for a translation, the request including a target translation language, wherein the target translation language is the default language when the user selects the first option, and wherein the target translation language is the target language selected in (c) when the user selects the second option; (f) in response to the request, receives a timed text track including text automatically translated to the target language; and (g) displays at least a portion of the timed text track synchronized with the web video according to timing data in the timed text track. 8. The system of claim 7 , wherein the first user interface control is a first menu and the second user interface control is a second menu. | 0.5 |
9,704,486 | 6 | 7 | 6. The computer-implemented method of claim 5 , wherein: the first module comprises a processor that is switchable between a low-power state and a high-power state; and the processor only performs the operation when it is in the high-power state. | 6. The computer-implemented method of claim 5 , wherein: the first module comprises a processor that is switchable between a low-power state and a high-power state; and the processor only performs the operation when it is in the high-power state. 7. The computer-implemented method of claim 6 , wherein activating the first module comprises switching the processor from the low-power state to the high-power state. | 0.615207 |
8,170,873 | 11 | 12 | 11. The method of claim 9 wherein computing the quantity characterizing the comparison of the two acoustic events includes time aligning the two acoustic events. | 11. The method of claim 9 wherein computing the quantity characterizing the comparison of the two acoustic events includes time aligning the two acoustic events. 12. The method of claim 11 wherein time aligning the two acoustic events includes optimizing a time alignment based on an optimization of the quantity characterizing the comparison. | 0.5 |
8,516,458 | 13 | 14 | 13. A code-portion-handling tool as claimed in claim 12 , wherein: said second data structure is in an input form in which its instance nodes and links therebetween are not explicitly expressed; and the at least one processor is configured for converting the received candidate code portion into an abstracted form in which the instance nodes and links therebetween are explicitly expressed. | 13. A code-portion-handling tool as claimed in claim 12 , wherein: said second data structure is in an input form in which its instance nodes and links therebetween are not explicitly expressed; and the at least one processor is configured for converting the received candidate code portion into an abstracted form in which the instance nodes and links therebetween are explicitly expressed. 14. A code-portion-handling tool as claimed in claim 13 , wherein: said candidate code portion is a code portion expressed in said computer-programming language; said input form is a text-based version of said code portion; and said abstracted form is at least one of an abstract syntax tree and a graph version of said code portion. | 0.5 |
7,614,003 | 13 | 14 | 13. A system comprising: an input device; a display device; a computer platform including an operating system and a virtual machine, the virtual machine configured to create a virtualized environment between the computer platform and a software application programmed to operate on the virtual machine; and the virtual machine operable to generate a user interface for the software application, using the input device and the display device, by rendering and dynamically updating interactive HTML content through a vector graphics rendering engine, wherein the virtual machine comprises an HTML rendering engine, separate from the vector graphics rendering engine, configured to render the interactive HTML content to primitives of the vector graphics rendering engine, and the virtual machine comprises the vector graphics rendering engine configured to render the primitives to provide the user interface. | 13. A system comprising: an input device; a display device; a computer platform including an operating system and a virtual machine, the virtual machine configured to create a virtualized environment between the computer platform and a software application programmed to operate on the virtual machine; and the virtual machine operable to generate a user interface for the software application, using the input device and the display device, by rendering and dynamically updating interactive HTML content through a vector graphics rendering engine, wherein the virtual machine comprises an HTML rendering engine, separate from the vector graphics rendering engine, configured to render the interactive HTML content to primitives of the vector graphics rendering engine, and the virtual machine comprises the vector graphics rendering engine configured to render the primitives to provide the user interface. 14. The system of claim 13 , the HTML rendering engine configured to retain information regarding the rendered primitives, to determine that a change in appearance for the user interface, caused by an input event, affects only a portion of the user interface, and to update only primitives that intersect the portion of the user interface affected by the change. | 0.5 |
8,892,480 | 1 | 4 | 1. A method of providing contextual information to a user, comprising: receiving context data describing the user's current context; identifying a plurality of information items corresponding to the user's current context; applying a personalized user behavior model for the user to determine, for each of the plurality of information items, a likelihood that the information item will be of value to the user, the user behavior model including a routine model describing correlations between contexts, the routine model comprising a plurality of transition rules; selecting an information item from among the plurality of information items based on the corresponding likelihood; providing the selected information item for presentation to the user; receiving feedback indicating the user found value in presentation of the selected information item; identifying a contributing transition rule from among the plurality of transition rules based on the contributing transition rule having contributed to selection of the selected information item, the contributing transition rule comprising a source context and a destination context; and storing an indication that the user found value in presentation of the selected information item in conjunction with the contributing transition rule such that information items associated with the destination context are in future determined to have a higher likelihood when the user is associated with the source context. | 1. A method of providing contextual information to a user, comprising: receiving context data describing the user's current context; identifying a plurality of information items corresponding to the user's current context; applying a personalized user behavior model for the user to determine, for each of the plurality of information items, a likelihood that the information item will be of value to the user, the user behavior model including a routine model describing correlations between contexts, the routine model comprising a plurality of transition rules; selecting an information item from among the plurality of information items based on the corresponding likelihood; providing the selected information item for presentation to the user; receiving feedback indicating the user found value in presentation of the selected information item; identifying a contributing transition rule from among the plurality of transition rules based on the contributing transition rule having contributed to selection of the selected information item, the contributing transition rule comprising a source context and a destination context; and storing an indication that the user found value in presentation of the selected information item in conjunction with the contributing transition rule such that information items associated with the destination context are in future determined to have a higher likelihood when the user is associated with the source context. 4. The method of claim 1 , wherein identifying a plurality of items corresponding to the user's current context comprises: applying the routine model to the user's current context to predict a likely future location for the user; determining a distance between the likely future location and a location corresponding to a first information item in a corpus; and including the first information item in the plurality of information items responsive to the distance being less than a threshold. | 0.555957 |
8,578,265 | 1 | 10 | 1. A method of generating a dynamic document, the method comprising: providing a web-based visual editor structured to facilitate generation of a markup language version of the dynamic document, the markup language version of the dynamic document including first data indicative of a dynamic field; converting the markup language version of the dynamic document to a stylesheet version of the dynamic document, the stylesheet version of the dynamic document including second data indicative of the dynamic field; deploying the stylesheet version of the dynamic document via a network at an application server, wherein when the stylesheet version of the dynamic document is executed by a first user, a first instance of the dynamic document is generated using data associated with the first user as a first output document, and when the stylesheet version of the dynamic document is executed by a second different user, a second different instance of the dynamic document is generated using data associated with the second user as a second output document; transmitting the first output document to a first client device of the first user from the application server; and transmitting the second output document to a second client device of the second user from the application server, wherein the markup language version of the dynamic document is displayed as an XHTML page within a web browser at a designer terminal that provides the web-based visual editor, the stylesheet version of the dynamic document is an XSL:FO file stored at the application server, and the first and second output documents are at least one of PDF and RTF files stored locally at the first and second client devices, the client devices being located remotely from the application server. | 1. A method of generating a dynamic document, the method comprising: providing a web-based visual editor structured to facilitate generation of a markup language version of the dynamic document, the markup language version of the dynamic document including first data indicative of a dynamic field; converting the markup language version of the dynamic document to a stylesheet version of the dynamic document, the stylesheet version of the dynamic document including second data indicative of the dynamic field; deploying the stylesheet version of the dynamic document via a network at an application server, wherein when the stylesheet version of the dynamic document is executed by a first user, a first instance of the dynamic document is generated using data associated with the first user as a first output document, and when the stylesheet version of the dynamic document is executed by a second different user, a second different instance of the dynamic document is generated using data associated with the second user as a second output document; transmitting the first output document to a first client device of the first user from the application server; and transmitting the second output document to a second client device of the second user from the application server, wherein the markup language version of the dynamic document is displayed as an XHTML page within a web browser at a designer terminal that provides the web-based visual editor, the stylesheet version of the dynamic document is an XSL:FO file stored at the application server, and the first and second output documents are at least one of PDF and RTF files stored locally at the first and second client devices, the client devices being located remotely from the application server. 10. The method of claim 1 , including enabling the first user to enter data after deploying the stylesheet version of the dynamic document. | 0.833732 |
8,862,582 | 2 | 3 | 2. The method of claim 1 , wherein the scene description information comprises one of environmental data, chronologically relevant audio input to a device, network time difference of arrival data, and device orientation data. | 2. The method of claim 1 , wherein the scene description information comprises one of environmental data, chronologically relevant audio input to a device, network time difference of arrival data, and device orientation data. 3. The method of claim 2 , wherein environmental data comprises one of time, color, object detection, temperature, received audio when the image was received by the device, and audio. | 0.5 |
5,412,804 | 6 | 7 | 6. The method as claimed in claim 5, wherein said another linked data structure includes a series of nodes defining a sequence of join and outer-join operations including a consecutive series of m joins, and wherein the first i joins are evaluated at a time first for i=1, then for i=2, then for i=3, . . . , and finally for i=m. | 6. The method as claimed in claim 5, wherein said another linked data structure includes a series of nodes defining a sequence of join and outer-join operations including a consecutive series of m joins, and wherein the first i joins are evaluated at a time first for i=1, then for i=2, then for i=3, . . . , and finally for i=m. 7. The method as claimed in claim 6, wherein said evaluating generates a respective linked data structure for each value of i representing an alternative query plan. | 0.5 |
7,650,286 | 253 | 255 | 253. A system for using a computer to identify a matching resume for a job description, comprising: means for receiving the job description that includes at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; means for storing the job description; means for associating, for each said at least one job requirement, the required skill or experience-related phrase with at least one implying skill or experience-related phrase; means for storing at least one searchable phrase for each said at least one job requirement, one of said at least one searchable phrase including the required skill or experience-related phrase, and said at least one searchable phrase including each said at least one implying skill or experience-related phrase; means for receiving at least one resume; means for parsing each said at least one resume to: locate at least one of said at least one searchable phrase in the resume; determine an experience range for each searchable phrase located in the resume by examining a use of each searchable phrase in the resume; and compute a term of experience for each searchable phrase located in the resume based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range, wherein each resume summarizes a candidate's career and qualifications, and wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer; means for storing each said at least one resume; means for computing, for each said at least one resume, a term of experience for the required skill or experience-related phrase for each said at least one job requirement; and means for determining whether each said at least one resume is the matching resume that satisfies the job description. | 253. A system for using a computer to identify a matching resume for a job description, comprising: means for receiving the job description that includes at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; means for storing the job description; means for associating, for each said at least one job requirement, the required skill or experience-related phrase with at least one implying skill or experience-related phrase; means for storing at least one searchable phrase for each said at least one job requirement, one of said at least one searchable phrase including the required skill or experience-related phrase, and said at least one searchable phrase including each said at least one implying skill or experience-related phrase; means for receiving at least one resume; means for parsing each said at least one resume to: locate at least one of said at least one searchable phrase in the resume; determine an experience range for each searchable phrase located in the resume by examining a use of each searchable phrase in the resume; and compute a term of experience for each searchable phrase located in the resume based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range, wherein each resume summarizes a candidate's career and qualifications, and wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer; means for storing each said at least one resume; means for computing, for each said at least one resume, a term of experience for the required skill or experience-related phrase for each said at least one job requirement; and means for determining whether each said at least one resume is the matching resume that satisfies the job description. 255. The system of claim 253 , wherein the storing of each said at least one resume is to a database. | 0.889254 |
7,917,842 | 11 | 14 | 11. A method of producing a template for producing a printout of a paper form from an electronic form, comprising: displaying an image of the paper form in a window on a computer screen; extracting a list of variables from one or more electronic forms and displaying the list of variables in a window on the computer screen; selecting variables from the list of variables and positioning a representation of the selected variables onto the image of the paper form; and producing a template file including the selected variable names and positions of selected variable names on the image of the paper form, the template file including information for automated processing of multiple data sets corresponding to one or more electronic forms by printing images of the paper form with the data from the data set placed in accordance with the information in the template file. | 11. A method of producing a template for producing a printout of a paper form from an electronic form, comprising: displaying an image of the paper form in a window on a computer screen; extracting a list of variables from one or more electronic forms and displaying the list of variables in a window on the computer screen; selecting variables from the list of variables and positioning a representation of the selected variables onto the image of the paper form; and producing a template file including the selected variable names and positions of selected variable names on the image of the paper form, the template file including information for automated processing of multiple data sets corresponding to one or more electronic forms by printing images of the paper form with the data from the data set placed in accordance with the information in the template file. 14. The method of claim 11 in which extracting a list of variables includes storing the variables in a database and in which displaying a list of variables includes searching the database to locate a variable that was placed on the paper form image and other variables storing the same information and indicating on the display that that variable and the other variables have been placed. | 0.5 |
5,583,921 | 6 | 7 | 6. A data processing apparatus according to claim 1, further comprising outputting means for outputting signals corresponding to said first information converted by said converting means. | 6. A data processing apparatus according to claim 1, further comprising outputting means for outputting signals corresponding to said first information converted by said converting means. 7. A data processing apparatus according to claim 6, wherein said signals outputted by said outputting means comprise tone signals. | 0.5 |
10,019,205 | 1 | 4 | 1. A distributed computing system for managing solutions for print device support requests, the distributed computing system comprising: a solution data store comprising one or more non-transitory computer-readable media sectors that store content representing a plurality of solutions to a plurality of print device issues; a solution processing system comprising a processor and programming instructions that are configured to cause the processor to: output a user interface, receive a support request via the user interface, wherein the support request comprises input data and one or more search terms that pertain to an issue with a print device, use the input data and the one or more search terms to generate a search query, query the solution data store using the search query to identify a list of possible solutions for the support request, wherein each possible solution is associated with a plurality of factors, wherein each factor has a weight value, output, via the user interface the list of possible solutions for the support request, receive a selection of one or more of the possible solutions, for each selection: receive, via the user interface, an indication of an exit status for the support request, wherein the exit status represents a resolution to the support request, generate a session record for the support request comprising the input data, the search terms, the possible solution associated with the selection and the exit status, correlate the possible solution associated with the selection with the input data and search terms, generate one or more factors based on the correlation, and use the one or more generated factors to update one or more fields of a solution index in the data store for the possible solution by, for each of the one or more factors: determining whether the factor is already present in the solution index, and in response to determining that the factor is not already present in the index, adding a field for the factor to the index and assign the factor a weight value. | 1. A distributed computing system for managing solutions for print device support requests, the distributed computing system comprising: a solution data store comprising one or more non-transitory computer-readable media sectors that store content representing a plurality of solutions to a plurality of print device issues; a solution processing system comprising a processor and programming instructions that are configured to cause the processor to: output a user interface, receive a support request via the user interface, wherein the support request comprises input data and one or more search terms that pertain to an issue with a print device, use the input data and the one or more search terms to generate a search query, query the solution data store using the search query to identify a list of possible solutions for the support request, wherein each possible solution is associated with a plurality of factors, wherein each factor has a weight value, output, via the user interface the list of possible solutions for the support request, receive a selection of one or more of the possible solutions, for each selection: receive, via the user interface, an indication of an exit status for the support request, wherein the exit status represents a resolution to the support request, generate a session record for the support request comprising the input data, the search terms, the possible solution associated with the selection and the exit status, correlate the possible solution associated with the selection with the input data and search terms, generate one or more factors based on the correlation, and use the one or more generated factors to update one or more fields of a solution index in the data store for the possible solution by, for each of the one or more factors: determining whether the factor is already present in the solution index, and in response to determining that the factor is not already present in the index, adding a field for the factor to the index and assign the factor a weight value. 4. The distributed computing system of claim 1 , wherein the input data comprises one or more of the following: a problem description; or a fault code experienced by the print device. | 0.901719 |
7,512,633 | 1 | 8 | 1. A method for storing communication messages in a relational database, comprising: accepting an object model comprising data elements having respective data type definitions and further comprising associations between the data elements, wherein the data elements, the data type definitions and the associations are derived from a hierarchically-structured HL7 specification and comprise at least one data element whose data type definition corresponds to multiple possible data types; defining a relational database that represents the object model based on the data elements and the associations; receiving a communication message that conforms to the HL7 specification and comprises data items corresponding to one or more of the data elements, including at least one data item having the data type definition that corresponds to the multiple possible data types; processing the received communication message so as to identify an actual data type, selected from among the possible data types, to which the at least one data item belongs; and storing the data items, including the at least one data item, in the relational database so as to preserve the data type definitions of the data items, including the identified actual data type, and the associations between the data items, as defined in the object model, wherein the data elements comprise classes, each having one or more class attributes, wherein defining the relational database comprises creating for each class a respective class table comprising at least one unique identifier in the relational database, and mapping at least one of the class attributes to columns of the class table, and wherein the object model comprises at least one of an association of cardinality 1:n representing a relationship between a parent class and a child class, an association of cardinality n:m representing a relationship between one or more parent classes and one or more child classes, a recursive association representing a relationship between a parent class and a child class wherein the parent class is equal to the child class, and a group association representing a relationship between a group comprising two or more classes and a child class. | 1. A method for storing communication messages in a relational database, comprising: accepting an object model comprising data elements having respective data type definitions and further comprising associations between the data elements, wherein the data elements, the data type definitions and the associations are derived from a hierarchically-structured HL7 specification and comprise at least one data element whose data type definition corresponds to multiple possible data types; defining a relational database that represents the object model based on the data elements and the associations; receiving a communication message that conforms to the HL7 specification and comprises data items corresponding to one or more of the data elements, including at least one data item having the data type definition that corresponds to the multiple possible data types; processing the received communication message so as to identify an actual data type, selected from among the possible data types, to which the at least one data item belongs; and storing the data items, including the at least one data item, in the relational database so as to preserve the data type definitions of the data items, including the identified actual data type, and the associations between the data items, as defined in the object model, wherein the data elements comprise classes, each having one or more class attributes, wherein defining the relational database comprises creating for each class a respective class table comprising at least one unique identifier in the relational database, and mapping at least one of the class attributes to columns of the class table, and wherein the object model comprises at least one of an association of cardinality 1:n representing a relationship between a parent class and a child class, an association of cardinality n:m representing a relationship between one or more parent classes and one or more child classes, a recursive association representing a relationship between a parent class and a child class wherein the parent class is equal to the child class, and a group association representing a relationship between a group comprising two or more classes and a child class. 8. The method according to claim 1 , wherein the class has an attribute of cardinality n, and wherein mapping the class attributes comprises creating a respective attribute table in the relational database, the respective attribute table comprising a key to the class table, and mapping the attribute of cardinality n to the respective attribute table. | 0.658915 |
9,037,606 | 1 | 7 | 1. A computer-implemented method comprising: clustering hierarchical database records into a first set of clusters having corresponding first cluster identifications (IDs), each hierarchical database record comprising one or more field values, the clustering based at least in part on determining similarity among corresponding field values of the hierarchical database records; determining parent-child hierarchical relationships among the hierarchical database records; associating related hierarchical database records by: determining highest compelling linkages among the hierarchical database records, the determining comprising: identifying mutually preferred pairs of records from the hierarchical database records, each mutually preferred pair of records consisting of a first record and a second record, the first record consisting of a preferred record associated with the second record and the second record consisting of a preferred record associated with the first record, wherein the mutually preferred pairs of records each has a match score that meets pre-specified match criteria; assigning, for each record from the hierarchical database records, at least one associated preferred record, wherein a match value assigned to a given record together with its associated preferred record is at least as great as a match value assigned to the record together with any other record in the database records; and forming and storing a plurality of entity representations in the database, each entity representation of the plurality of entity representations comprising at least one linked pair of mutually preferred records; applying a hierarchal directional linking process, the hierarchal directional linking process comprising selecting and applying at least an upward process based on the determined parent-child hierarchical relationship wherein the upward process comprises: determining, from the parent-child hierarchical relationships, similarity among a plurality of child records having initial separate parent records; in response to determining a threshold similarity among the plurality of child records, inferring that the initial separate parent records correspond to the same entity; and linking, responsive to the inferring, the initial separate parent records as inferred common parent records; re-clustering at least a portion of the database records into a second set of clusters having corresponding second cluster IDs, the re-clustering based at least in part on the associating related hierarchical database records and on the determining similarity among corresponding field values of the database records; and outputting database record information, based at least in part on the re-clustering. | 1. A computer-implemented method comprising: clustering hierarchical database records into a first set of clusters having corresponding first cluster identifications (IDs), each hierarchical database record comprising one or more field values, the clustering based at least in part on determining similarity among corresponding field values of the hierarchical database records; determining parent-child hierarchical relationships among the hierarchical database records; associating related hierarchical database records by: determining highest compelling linkages among the hierarchical database records, the determining comprising: identifying mutually preferred pairs of records from the hierarchical database records, each mutually preferred pair of records consisting of a first record and a second record, the first record consisting of a preferred record associated with the second record and the second record consisting of a preferred record associated with the first record, wherein the mutually preferred pairs of records each has a match score that meets pre-specified match criteria; assigning, for each record from the hierarchical database records, at least one associated preferred record, wherein a match value assigned to a given record together with its associated preferred record is at least as great as a match value assigned to the record together with any other record in the database records; and forming and storing a plurality of entity representations in the database, each entity representation of the plurality of entity representations comprising at least one linked pair of mutually preferred records; applying a hierarchal directional linking process, the hierarchal directional linking process comprising selecting and applying at least an upward process based on the determined parent-child hierarchical relationship wherein the upward process comprises: determining, from the parent-child hierarchical relationships, similarity among a plurality of child records having initial separate parent records; in response to determining a threshold similarity among the plurality of child records, inferring that the initial separate parent records correspond to the same entity; and linking, responsive to the inferring, the initial separate parent records as inferred common parent records; re-clustering at least a portion of the database records into a second set of clusters having corresponding second cluster IDs, the re-clustering based at least in part on the associating related hierarchical database records and on the determining similarity among corresponding field values of the database records; and outputting database record information, based at least in part on the re-clustering. 7. The method of claim 1 , wherein each hierarchical database record corresponds to an entity representation, each hierarchical database record comprising a plurality of fields, each field configured to contain a field value, and each field value assigned a field value weight corresponding to a specificity of the field value in relation to all field values in a corresponding field of the records. | 0.727086 |
9,372,878 | 1 | 7 | 1. A method for determining social proximity between users of an online system, the method comprising: accessing a profile of a user of the online system maintained by each of a plurality of social networking systems, each profile specifying a first plurality of additional users of a social networking system connected to the user via the social networking system; identifying a user of the first plurality of additional users of an identified social networking system; identifying a second plurality of additional users of the identified social networking system connected to both the user of the online system via the identified social networking system and to the identified user of the first plurality of additional users; generating a social proximity score based at least in part on a number of users in the second plurality of additional users connected to the identified user of the first plurality of additional users, the social proximity score indicating a relative social proximity of the user of the online system to the identified user of the first plurality of additional users; and recommending a content item to the user of the online system based at least in part on an interaction of the identified user of the first plurality of additional users with the content item and the generated social proximity score. | 1. A method for determining social proximity between users of an online system, the method comprising: accessing a profile of a user of the online system maintained by each of a plurality of social networking systems, each profile specifying a first plurality of additional users of a social networking system connected to the user via the social networking system; identifying a user of the first plurality of additional users of an identified social networking system; identifying a second plurality of additional users of the identified social networking system connected to both the user of the online system via the identified social networking system and to the identified user of the first plurality of additional users; generating a social proximity score based at least in part on a number of users in the second plurality of additional users connected to the identified user of the first plurality of additional users, the social proximity score indicating a relative social proximity of the user of the online system to the identified user of the first plurality of additional users; and recommending a content item to the user of the online system based at least in part on an interaction of the identified user of the first plurality of additional users with the content item and the generated social proximity score. 7. The method of claim 1 , further comprising: adjusting the social proximity score based on a directionality of a connection between the user of the online system and the identified user of the first plurality of additional users, wherein a social proximity score for a bidirectional connection is greater than a social proximity score for a unidirectional connection. | 0.830579 |
8,627,195 | 20 | 22 | 20. The computer-implemented method of claim 18 , further comprising causing display of an object graphically representing a geographic relationship between the client computing devices associated with the common characteristic. | 20. The computer-implemented method of claim 18 , further comprising causing display of an object graphically representing a geographic relationship between the client computing devices associated with the common characteristic. 22. The computer-implemented method of claim 20 , wherein the common characteristic comprises the requested network resource. | 0.765918 |
8,949,247 | 2 | 3 | 2. The method according to claim 1 , further comprising: grouping all updates of the database log together at specified intervals moving the grouped updates to the posting file; and storing each keyword respectively in an occurrence list in the form of occurrences of the keyword older than a determined update generation and in a delta list in the form of a set of smaller updates more recent than the same update generation, such that the dictionary contains one entry for each keyword in the posting file and a reference to the occurrence list and the delta list. | 2. The method according to claim 1 , further comprising: grouping all updates of the database log together at specified intervals moving the grouped updates to the posting file; and storing each keyword respectively in an occurrence list in the form of occurrences of the keyword older than a determined update generation and in a delta list in the form of a set of smaller updates more recent than the same update generation, such that the dictionary contains one entry for each keyword in the posting file and a reference to the occurrence list and the delta list. 3. The method according to claim 2 , further comprising storing the occurrence list and the delta list in the posting file. | 0.831044 |
8,185,096 | 2 | 3 | 2. The method of claim 1 , wherein the response comprises a unique command alias. | 2. The method of claim 1 , wherein the response comprises a unique command alias. 3. The method of claim 2 , wherein the unique command alias is at least one of a number, a letter, multiples of letters, short words, or a number and a letter. | 0.5 |
9,110,904 | 11 | 13 | 11. A device comprising: a communication interface; one or more memories, wherein the one or more memories store instructions; and one or more processors, wherein the one or more processors execute the instructions to: obtain metadata pertaining to programs originating from metadata sources; compare metadata of a first type from one of the metadata sources with one or more metadata of the first type from one or more others of the metadata sources; determine whether compared metadata of the first type from the one of the metadata sources matches the one or more metadata of the first type from the one or more others of the metadata sources based on a comparison; transform the compared metadata based on one or more transformation rules when the compared metadata does not match; store transformed metadata, wherein the transformed metadata of the first type from the one of the metadata sources matches at least one of the one or more metadata of the first type from at least one other of the metadata sources; identify when metadata of a same metadata type is obtained from the one of the metadata sources and the at least one other of the metadata sources, wherein the metadata of the same metadata type is other than the first type; determine which metadata of the same metadata type to aggregate based on a quality metric that indicates a quality of each metadata; and select metadata of the same metadata type from the one of the metadata sources or the at least one other of the metadata sources based on a determination of which metadata of the same metadata type to aggregate, wherein, when making the determination of which metadata of the same metadata type to aggregate based on the quality metric, the one or more processors further execute the instructions to: count a number of words in the metadata of the same metadata type from the one of the metadata sources; count a number of words in the metadata of the same metadata type from the at least one other of the metadata sources; and determine whether the number of words in the metadata of the same metadata type from the one of the metadata sources is greater than the number of words in the metadata of the same metadata type from the at least one other of the metadata sources, and wherein, when making a selection of metadata of the same metadata type, the one or more processors further execute the instructions to: select the metadata of the same metadata type from the one of the metadata sources or from the at least one other of the metadata sources in response to a determination that the number of words in the metadata of the same metadata type from the one of the metadata sources or from the at least one other of the metadata sources is greater. | 11. A device comprising: a communication interface; one or more memories, wherein the one or more memories store instructions; and one or more processors, wherein the one or more processors execute the instructions to: obtain metadata pertaining to programs originating from metadata sources; compare metadata of a first type from one of the metadata sources with one or more metadata of the first type from one or more others of the metadata sources; determine whether compared metadata of the first type from the one of the metadata sources matches the one or more metadata of the first type from the one or more others of the metadata sources based on a comparison; transform the compared metadata based on one or more transformation rules when the compared metadata does not match; store transformed metadata, wherein the transformed metadata of the first type from the one of the metadata sources matches at least one of the one or more metadata of the first type from at least one other of the metadata sources; identify when metadata of a same metadata type is obtained from the one of the metadata sources and the at least one other of the metadata sources, wherein the metadata of the same metadata type is other than the first type; determine which metadata of the same metadata type to aggregate based on a quality metric that indicates a quality of each metadata; and select metadata of the same metadata type from the one of the metadata sources or the at least one other of the metadata sources based on a determination of which metadata of the same metadata type to aggregate, wherein, when making the determination of which metadata of the same metadata type to aggregate based on the quality metric, the one or more processors further execute the instructions to: count a number of words in the metadata of the same metadata type from the one of the metadata sources; count a number of words in the metadata of the same metadata type from the at least one other of the metadata sources; and determine whether the number of words in the metadata of the same metadata type from the one of the metadata sources is greater than the number of words in the metadata of the same metadata type from the at least one other of the metadata sources, and wherein, when making a selection of metadata of the same metadata type, the one or more processors further execute the instructions to: select the metadata of the same metadata type from the one of the metadata sources or from the at least one other of the metadata sources in response to a determination that the number of words in the metadata of the same metadata type from the one of the metadata sources or from the at least one other of the metadata sources is greater. 13. The device of claim 11 , wherein the one or more processors further execute the instructions to: aggregate one or more other types of metadata, wherein an aggregation comprises: identify a metadata type obtained from the one of the metadata sources that is not included in metadata obtained from the at least one other of the metadata sources; identify another metadata type obtained from the at least one other of the metadata sources that is not included in metadata obtained from the one of the metadata sources; and combine metadata of the metadata type with metadata of the other metadata type, wherein combined metadata includes aggregated metadata. | 0.5 |
7,533,338 | 1 | 6 | 1. A computer-implemented method for asynchronous receipt and processing of electronic ink annotation of a document, comprising: generating a first analysis context object, the first analysis context object providing a translation layer for a document model of a current state of a relationship of elements in the document and comprising a tree data structure for storing document elements in a hierarchical relationship; staffing a first thread, wherein the first thread updates the first analysis context object based upon a user interaction with the document, the user interaction including electronic ink annotation; upon an event requiring analysis of new data in the document: suspending execution of the first thread so as to prevent changes to the first analysis context object; starting a second thread, wherein the second thread generates a second analysis context object corresponding to a portion of the first analysis context object, wherein the portion corresponds to a designated region of the document; upon completion of generation of the second analysis context object: suspending execution of the second thread; restarting the first thread; performing a first analysis of the second analysis context object to generate a third analysis context object from the second analysis context object, wherein the third analysis context object is generated by parsing the new data and modifying the second analysis context object based on the new data and further includes classification information for the new data; upon completion of the first analysis: suspending execution of the first thread so as to prevent any changes to the first analysis context object; starting a third thread, wherein the third thread reconciles the third analysis context object with the first analysis context object to generate first reconciled analysis results; upon completion of the reconciliation of the first analysis context object and the third analysis context object: updating the first analysis context object with the first reconciled analysis results; suspending execution of the third threat; and restarting the first thread. | 1. A computer-implemented method for asynchronous receipt and processing of electronic ink annotation of a document, comprising: generating a first analysis context object, the first analysis context object providing a translation layer for a document model of a current state of a relationship of elements in the document and comprising a tree data structure for storing document elements in a hierarchical relationship; staffing a first thread, wherein the first thread updates the first analysis context object based upon a user interaction with the document, the user interaction including electronic ink annotation; upon an event requiring analysis of new data in the document: suspending execution of the first thread so as to prevent changes to the first analysis context object; starting a second thread, wherein the second thread generates a second analysis context object corresponding to a portion of the first analysis context object, wherein the portion corresponds to a designated region of the document; upon completion of generation of the second analysis context object: suspending execution of the second thread; restarting the first thread; performing a first analysis of the second analysis context object to generate a third analysis context object from the second analysis context object, wherein the third analysis context object is generated by parsing the new data and modifying the second analysis context object based on the new data and further includes classification information for the new data; upon completion of the first analysis: suspending execution of the first thread so as to prevent any changes to the first analysis context object; starting a third thread, wherein the third thread reconciles the third analysis context object with the first analysis context object to generate first reconciled analysis results; upon completion of the reconciliation of the first analysis context object and the third analysis context object: updating the first analysis context object with the first reconciled analysis results; suspending execution of the third threat; and restarting the first thread. 6. The method according to claim 1 , wherein the new data is an electronic ink annotation, the annotation includes at least one unclassified ink node. | 0.855212 |
7,672,865 | 28 | 29 | 28. The method of claim 18 , further comprising: using, by at least one data processor, context to define the nature of relationship between two entities by way of their juxtaposition in said transaction data, wherein types of available contexts depend on the domain and nature of said transaction data. | 28. The method of claim 18 , further comprising: using, by at least one data processor, context to define the nature of relationship between two entities by way of their juxtaposition in said transaction data, wherein types of available contexts depend on the domain and nature of said transaction data. 29. The method of claim 28 , further comprising: for every context, using, by at least one data processor, a process to quantify pair-wise co-occurrence consistencies for all product pairs for each level at which analysis is to be done, said process comprising: creating context instances from said transaction data; counting a number of times two products co-occurred in said context instances; and creating information theoretic measures to quantify consistency between said context instances. | 0.5 |
5,558,520 | 1 | 20 | 1. An interactive coordinated book assembly useful for teaching in a parent/child, teacher/student or self study environment, comprising: a plurality of left and right main pages, each containing textual material and at least one key word; a plurality of left and fight activity pages, each of said activity pages containing an activity area and a direction text area; said main pages and said activity pages being alternately interleaved and bound along one edge to form a book; said direction text areas on said activity pages containing at least one activity to be read, said direction text area on said fight activity page being reverse coordinated with said key word appearing on said left main page and said direction text area on said left activity page being reverse coordinated with said key word appearing on said right main page; wherein at least one of said activities is coordinated with said key word appearing on said fight main page; and wherein said left activity page contains said key word present in said adjacent fight main page, and said right activity page contains said key word present in said adjacent left main page. | 1. An interactive coordinated book assembly useful for teaching in a parent/child, teacher/student or self study environment, comprising: a plurality of left and right main pages, each containing textual material and at least one key word; a plurality of left and fight activity pages, each of said activity pages containing an activity area and a direction text area; said main pages and said activity pages being alternately interleaved and bound along one edge to form a book; said direction text areas on said activity pages containing at least one activity to be read, said direction text area on said fight activity page being reverse coordinated with said key word appearing on said left main page and said direction text area on said left activity page being reverse coordinated with said key word appearing on said right main page; wherein at least one of said activities is coordinated with said key word appearing on said fight main page; and wherein said left activity page contains said key word present in said adjacent fight main page, and said right activity page contains said key word present in said adjacent left main page. 20. The assembly of claim 1, wherein said main pages and said activity pages are substantially the same size and are offset with respect to their top and bottom edges while being bound at a seam along a common edge. | 0.777433 |
7,526,059 | 21 | 22 | 21. The method according to claim 12 , wherein the count code comprises at least a third count word in addition to the less significant and more significant words, and wherein making the first assignment comprises assigning a third group of the memory cells to store the third count word, and wherein making the second assignment comprises swapping the less significant word, the more significant word, and the third count word among the groups of the memory cells. | 21. The method according to claim 12 , wherein the count code comprises at least a third count word in addition to the less significant and more significant words, and wherein making the first assignment comprises assigning a third group of the memory cells to store the third count word, and wherein making the second assignment comprises swapping the less significant word, the more significant word, and the third count word among the groups of the memory cells. 22. The method according to claim 21 , wherein the third count word has a level of significance that is intermediate between the more and less significant words. | 0.5 |
9,349,132 | 24 | 25 | 24. The system of claim 22 , wherein the request interface exposes a Predictive Query Language Application Programming Interface (PreQL API) directly to authenticated users, wherein the PreQL API is accessible to the authenticated users via a public Internet. | 24. The system of claim 22 , wherein the request interface exposes a Predictive Query Language Application Programming Interface (PreQL API) directly to authenticated users, wherein the PreQL API is accessible to the authenticated users via a public Internet. 25. The system of claim 24 , wherein the query interface is to pass a Predictive Query Language (PreQL) structured query to the predictive database to execute the query, the PreQL structured query having a query syntax of: the GROUP command term as a required term; a COLUMN term as a required term, the COLUMN term specifying the column to be passed with the GROUP command term; an optional FROM term specifying one or more tables, datasets, data sources, or indices or any combination thereof, to be queried when the optional FROM term is specified; wherein a default value is used when the optional FROM term is not specified; and an optional CONFIDENCE term that, when provided, specifies a minimum acceptable threshold for respective confidence indicators corresponding to each row of the rows to be returned with the groups of the predictive record set. | 0.5 |
9,754,045 | 19 | 22 | 19. The system of claim 18 where: the web feed document includes a list of one or more web page documents; and the aggregation module iterates through the list and generates a request for at least one of the web page documents in the list. | 19. The system of claim 18 where: the web feed document includes a list of one or more web page documents; and the aggregation module iterates through the list and generates a request for at least one of the web page documents in the list. 22. The system of claim 19 further comprising a data storage module that stores the text-based content. | 0.815412 |
8,170,880 | 1 | 2 | 1. In a system where an annotation guide is used to label utterances in speech data with a call type, a method for monitoring a labeler of the speech data, the method comprising: presenting, via a processor of a computing device, a test utterance to the labeler; generating a determination indicating whether the labeler correctly labeled the test utterance as one call type from a list of call types; and based on the determination, performing at least one of revising the annotation guide, retraining the labeler, and altering the test utterance. | 1. In a system where an annotation guide is used to label utterances in speech data with a call type, a method for monitoring a labeler of the speech data, the method comprising: presenting, via a processor of a computing device, a test utterance to the labeler; generating a determination indicating whether the labeler correctly labeled the test utterance as one call type from a list of call types; and based on the determination, performing at least one of revising the annotation guide, retraining the labeler, and altering the test utterance. 2. The method of claim 1 , wherein the test utterance is selected from a group of labeled utterances. | 0.751232 |
9,959,259 | 18 | 19 | 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. 19. The apparatus of claim 18 , wherein the set of instructions for identifying overlapping primitive graphic elements as subsets of primitive graphic elements comprises sets of instructions for: selecting a first graphic element in the set and assigning the graphic element to a new subset; assigning a second graphic element in the set to the new subset when a bounding box of the second graphic element overlaps a bounding box of the new subset. | 0.5 |
8,874,577 | 11 | 22 | 11. A method for triaging information feeds, comprising: receiving a plurality of information feeds, wherein each information feed comprises at one or more feed items; determining one or more facets for each feed item, comprising: generating the one or more facets comprising at least one of a creator facet comprising creators, a source facet comprising sources, and a time facet comprising times by directly extracting the creators, sources and times from each of the feed items; and generating a topic facet comprising at least one topic for each feed item based on at least one of nouns and noun phrases included in that feed item and designating the nouns and noun phrases as the topics for that feed item; displaying within a user interface, the creator, source, time and topic facets; receiving from the user a selection of one of the plurality of topics from the topic facet displayed within the user interface; displaying only the feed items that are associated with the selected topic within the user interface; updating the topics in the topic facet displayed within the user interface by presenting for display only those topics that are associated with the displayed feed items; and filtering in or filtering out one or more of the extracted creators, sources, and times within at least one of the creator, source and time facets in the display of the user interface based on the feed items associated with the selected topic. | 11. A method for triaging information feeds, comprising: receiving a plurality of information feeds, wherein each information feed comprises at one or more feed items; determining one or more facets for each feed item, comprising: generating the one or more facets comprising at least one of a creator facet comprising creators, a source facet comprising sources, and a time facet comprising times by directly extracting the creators, sources and times from each of the feed items; and generating a topic facet comprising at least one topic for each feed item based on at least one of nouns and noun phrases included in that feed item and designating the nouns and noun phrases as the topics for that feed item; displaying within a user interface, the creator, source, time and topic facets; receiving from the user a selection of one of the plurality of topics from the topic facet displayed within the user interface; displaying only the feed items that are associated with the selected topic within the user interface; updating the topics in the topic facet displayed within the user interface by presenting for display only those topics that are associated with the displayed feed items; and filtering in or filtering out one or more of the extracted creators, sources, and times within at least one of the creator, source and time facets in the display of the user interface based on the feed items associated with the selected topic. 22. A method according to claim 11 , further comprising at least one of: receiving a selection of one of the elements, adding the feed items that are associated with the selected element to the feed items displayed within the user interface, and filtering in one or more of the elements based on the added feed items; and deselecting a selected element, removing the feed items that are associated with the deselected element from the user interface, and filtering out one or more of the elements displayed with the other remaining facets based on the removed feed items. | 0.5 |
9,483,733 | 13 | 19 | 13. A querying system comprising: memory which stores instructions for executing a query for retrieving results from an associated knowledge resource, the instructions including: a query engine which executes a query containing a global backreference and retrieves results from the knowledge resource responsive to the query, the query including a set of conditions, a first of the conditions including a regular expression that identifies strings in the knowledge resource that match the regular expression, the regular expression including a capturing group for capturing a substring of an identified matching string, the global backreference retrieving the substring captured by the capturing group and wherein the global backreference comprises a remote backreference which is outside the first condition and outputs at least one of the results of the query containing the global backreference and information based on the results; and a processor which executes the instructions. | 13. A querying system comprising: memory which stores instructions for executing a query for retrieving results from an associated knowledge resource, the instructions including: a query engine which executes a query containing a global backreference and retrieves results from the knowledge resource responsive to the query, the query including a set of conditions, a first of the conditions including a regular expression that identifies strings in the knowledge resource that match the regular expression, the regular expression including a capturing group for capturing a substring of an identified matching string, the global backreference retrieving the substring captured by the capturing group and wherein the global backreference comprises a remote backreference which is outside the first condition and outputs at least one of the results of the query containing the global backreference and information based on the results; and a processor which executes the instructions. 19. The system of claim 13 , further comprising a knowledge base which stores information in a relation database a knowledge base management system that updates the relation database with information that is based on the retrieved results. | 0.70125 |
8,863,055 | 13 | 14 | 13. A data processing system to provide a capacitance to a design an integrated circuit comprising: a memory, and a processor coupled to the memory, the processor is configured to receive a layout of the integrated circuit; to apply canonical hierarchical models to the layout, wherein the canonical hierarchical models include a first type canonical model representing a device having a plurality of first conductors to capture a first capacitance and a second type canonical model representing at least a portion of the device and one or more second conductors of the integrated circuit outside the device to capture a second capacitance; and to determine a capacitance for the layout based on the applying. | 13. A data processing system to provide a capacitance to a design an integrated circuit comprising: a memory, and a processor coupled to the memory, the processor is configured to receive a layout of the integrated circuit; to apply canonical hierarchical models to the layout, wherein the canonical hierarchical models include a first type canonical model representing a device having a plurality of first conductors to capture a first capacitance and a second type canonical model representing at least a portion of the device and one or more second conductors of the integrated circuit outside the device to capture a second capacitance; and to determine a capacitance for the layout based on the applying. 14. The data processing system of claim 13 , wherein the processor is further configured to determine one or more third conductors of a first domain of the layout; to select the first type canonical model for the first domain based on the one or more third conductors; to determine one or more fourth conductors of a second domain of the layout; and to select the second type canonical model for the second domain based on the one or more fourth conductors. | 0.5 |
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