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7,937,715 | 3 | 5 | 3. The computer implemented method for generating content dynamically without a Web server of claim 2 , where placing the contents of the include file in-line within the parsed information comprises expanding a substitution tag associated with the contents of the include file within the parsed information. | 3. The computer implemented method for generating content dynamically without a Web server of claim 2 , where placing the contents of the include file in-line within the parsed information comprises expanding a substitution tag associated with the contents of the include file within the parsed information. 5. The computer implemented method for generating content dynamically without a Web server of claim 3 , further comprising reading the in-line contents of the include file and the expanded substitution tag from within the parsed information. | 0.732816 |
8,594,993 | 16 | 17 | 16. A system, comprising: one or more processors; and a memory that includes a plurality of computer-executable components, the plurality of computer-executable components comprising: a frequency warping component to perform formant-based frequency warping on fundamental frequencies and coding spectrums of source speech waveforms in a first language to produce transformed fundamental frequencies and transformed coding spectrums; a trajectory generation component to generate warped parameter trajectories based at least on the transformed fundamental frequencies and the transformed coding spectrums; and a trajectory tiling component to produce transformed target speech waveforms with voice characteristics of the first language that retain at least some voice characteristics of a target speaker using the warped parameter trajectories and features from target speech waveforms of the target speaker in the second language. | 16. A system, comprising: one or more processors; and a memory that includes a plurality of computer-executable components, the plurality of computer-executable components comprising: a frequency warping component to perform formant-based frequency warping on fundamental frequencies and coding spectrums of source speech waveforms in a first language to produce transformed fundamental frequencies and transformed coding spectrums; a trajectory generation component to generate warped parameter trajectories based at least on the transformed fundamental frequencies and the transformed coding spectrums; and a trajectory tiling component to produce transformed target speech waveforms with voice characteristics of the first language that retain at least some voice characteristics of a target speaker using the warped parameter trajectories and features from target speech waveforms of the target speaker in the second language. 17. The system of claim 16 , further comprising: a Speech Transformation and Representation using Adaptive Interpolation of Weighted Spectrum (STRAIGHT) analysis component to estimate the coding spectrums of the source speech waveforms; a pitch extraction component to extract fundamental frequencies of the source speech waveforms using pitch extraction; and a feature extraction component to extract the features that include fundamental frequencies, LSPs, and gains from the target speech waveforms. | 0.658503 |
8,381,095 | 10 | 11 | 10. The method of claim 9 , wherein the computer infrastructure refines the table comparisons in the merged node list via the at least one additional longest common subsequence process by: constructing unique table header labels for the table segments in the table node list; comparing the constructed header labels of the tables via a second phase longest common subsequence process to generate column header text for merged table column names in a merged header node list; analyzing the column header text to distinguish between new and modified columns; and generating a first column name map for the first DITA document and a second column name map for the second DITA document from old column names for each input table to the merged table column names. | 10. The method of claim 9 , wherein the computer infrastructure refines the table comparisons in the merged node list via the at least one additional longest common subsequence process by: constructing unique table header labels for the table segments in the table node list; comparing the constructed header labels of the tables via a second phase longest common subsequence process to generate column header text for merged table column names in a merged header node list; analyzing the column header text to distinguish between new and modified columns; and generating a first column name map for the first DITA document and a second column name map for the second DITA document from old column names for each input table to the merged table column names. 11. The method of claim 10 , wherein the computer infrastructure refines the table comparisons in the merged node list via the at least one additional longest common subsequence by: mapping first table metadata from the first DITA document to the merged node list column names via the first column name map and from the second DITA document to the merged node list column names via the second column name map; constructing unique column header labels for the table segments in the table node list; and comparing the constructed column header labels of the tables via a third phase longest common subsequence process to generate a third phase merged table node list for use in the step of building the merged document object model from the merged node list and the refined table comparisons. | 0.5 |
9,241,223 | 12 | 13 | 12. The method of claim 11 , wherein determining the one or more first directional indicator values includes: calculating, for each of the one or more first directional indicator values, a respective plurality of cross-correlation values between two of the respective audible signal data components for a corresponding plurality of time-lag values; and selecting, for each of the one or more first directional indicator values, the one of the plurality of time-lag values for which the corresponding one of the plurality of cross-correlation values more closely satisfies a criterion than the other cross-correlation values. | 12. The method of claim 11 , wherein determining the one or more first directional indicator values includes: calculating, for each of the one or more first directional indicator values, a respective plurality of cross-correlation values between two of the respective audible signal data components for a corresponding plurality of time-lag values; and selecting, for each of the one or more first directional indicator values, the one of the plurality of time-lag values for which the corresponding one of the plurality of cross-correlation values more closely satisfies a criterion than the other cross-correlation values. 13. The method of claim 12 , wherein calculating each of the one or more first directional indicator values includes correspondingly calculating the respective plurality of cross-correlation values on a sub-band basis by utilizing corresponding sets of time-frequency units from each of at least one pair of the respective audible signal data components. | 0.5 |
8,793,246 | 1 | 3 | 1. A computer-implemented method comprising: receiving, from a client device, information indicative of a keyword and information indicative of a user specified network domain of interest; receiving, from search engine systems, search results for the keyword; determining, by one or more computer systems a first search engine ranking score of a search result returned from a first one of the search engine systems and associated with the user specified network domain of interest; determining by the one or more computer systems a second search engine ranking score of a search result returned from a second, different search engine system and associated with the user specified network domain of interest; generating information for: a first visual representation of information indicative of the search result from the first one of the search engine systems that is associated with the user specified network domain of interest; and a second visual representation of information indicative of the search result from the second one of the search engine systems that is associated with the user specified network domain of interest; selecting, from the received search results, a predefined number of search results for the keyword with increased search engine ranking scores relative to other search engine ranking scores for other retrieved search results for the keyword; and transmitting to the client device information indicative of the selected predefined number of search results, the first visual representation and the second visual representation. | 1. A computer-implemented method comprising: receiving, from a client device, information indicative of a keyword and information indicative of a user specified network domain of interest; receiving, from search engine systems, search results for the keyword; determining, by one or more computer systems a first search engine ranking score of a search result returned from a first one of the search engine systems and associated with the user specified network domain of interest; determining by the one or more computer systems a second search engine ranking score of a search result returned from a second, different search engine system and associated with the user specified network domain of interest; generating information for: a first visual representation of information indicative of the search result from the first one of the search engine systems that is associated with the user specified network domain of interest; and a second visual representation of information indicative of the search result from the second one of the search engine systems that is associated with the user specified network domain of interest; selecting, from the received search results, a predefined number of search results for the keyword with increased search engine ranking scores relative to other search engine ranking scores for other retrieved search results for the keyword; and transmitting to the client device information indicative of the selected predefined number of search results, the first visual representation and the second visual representation. 3. The method of claim 1 , further comprising: generating information for a graphical user interface that when rendered on a display device, renders: a first visual representation of a first control, selection of which causes the one or more computer systems to use the first one of the search engine systems in receiving the search results; and a second visual representation of a second control, selection of which causes the one or more computer systems to use the second one of the search engine systems in receiving the search results. | 0.5 |
6,064,958 | 19 | 22 | 19. An article of manufacture, comprising: a computer usable medium having computer readable program code means embodied therein for causing a computer to function as a pattern recognition system, the computer readable program code means including: first computer readable program code means for causing said computer to calculate a probability of each probabilistic model expressing features of each recognition category with respect to each input feature vector derived from each input signal, wherein the probabilistic model represents a feature parameter subspace in which feature vectors of each recognition category exist and the feature parameter subspace is expressed by using mixture distributions of one-dimensional discrete distributions with arbitrary distribution shapes which are arranged in respective dimensions; and second computer readable program code means for causing said computer to output a recognition category expressed by a probabilistic model with a highest probability among a plurality of probabilistic models as a recognition result. | 19. An article of manufacture, comprising: a computer usable medium having computer readable program code means embodied therein for causing a computer to function as a pattern recognition system, the computer readable program code means including: first computer readable program code means for causing said computer to calculate a probability of each probabilistic model expressing features of each recognition category with respect to each input feature vector derived from each input signal, wherein the probabilistic model represents a feature parameter subspace in which feature vectors of each recognition category exist and the feature parameter subspace is expressed by using mixture distributions of one-dimensional discrete distributions with arbitrary distribution shapes which are arranged in respective dimensions; and second computer readable program code means for causing said computer to output a recognition category expressed by a probabilistic model with a highest probability among a plurality of probabilistic models as a recognition result. 22. The article of manufacture of claim 19, wherein the first computer readable program code means uses a scalar quantization code book for the discrete distributions which is shared among distributions existing in an identical dimension of all or a part of the probabilistic models. | 0.856199 |
8,683,314 | 14 | 15 | 14. The non-transitory computer readable medium defined in claim 13 wherein adapting the plurality of visualizations to an available display width comprises evaluating a plurality of subtrees by at least two tree functionals and selecting a subtree that has a preselected ratio among the tree functional values subject to a size constraint on subtree visualization. | 14. The non-transitory computer readable medium defined in claim 13 wherein adapting the plurality of visualizations to an available display width comprises evaluating a plurality of subtrees by at least two tree functionals and selecting a subtree that has a preselected ratio among the tree functional values subject to a size constraint on subtree visualization. 15. The non-transitory computer readable medium defined in claim 14 wherein the preselected ratio of tree functional values comprises a smallest ratio of distortion versus the required visualization area of all subtrees with a specified root node. | 0.575601 |
7,945,469 | 1 | 9 | 1. A computer-implemented method comprising: receiving information at an electronic marketplace from multiple executing programs of multiple task requesters that indicates multiple tasks available to be performed by multiple human task performers who have registered with the electronic marketplace as being able to perform tasks, each of the task requesters supplying one or more of the multiple available tasks and indicating for each of the supplied one or more available tasks one or more associated required qualifications for a human who performs the task and associated compensation to be provided by the task requester for satisfactory performance of the task, the electronic marketplace being provided by one or more configured computer processors to facilitate task performance transactions between the task requesters and the human task performers and otherwise being unaffiliated with the multiple task requesters and with the multiple human task performers; and for each of at least some of the multiple available tasks, automatically facilitating performance of the task by, automatically identifying at least one of the multiple human task performers who each has one or more qualifications that satisfy the required qualifications for the task, the automatic identifying of the at least one human task performers being performed by the one or more computer processors; providing information about the task to each of the at least one identified human task performers to enable one or more of the at least one identified human task performers to select to participate in a transaction with the task requester who supplied the task that involves the one or more identified human task performers performing the task for that task requester in exchange for the associated compensation for the task from that task requester; and after receiving results for the task based on performance of the task by the one or more identified human task performers, and without further human intervention, automatically supplying the received results to an executing program of the task requester who supplied the task and facilitating providing of the associated compensation for the task to the one or more identified human task performers on behalf of that task requester, the automatic supplying and facilitating of the providing of the associated compensation being performed by the one or more configured computer processors. | 1. A computer-implemented method comprising: receiving information at an electronic marketplace from multiple executing programs of multiple task requesters that indicates multiple tasks available to be performed by multiple human task performers who have registered with the electronic marketplace as being able to perform tasks, each of the task requesters supplying one or more of the multiple available tasks and indicating for each of the supplied one or more available tasks one or more associated required qualifications for a human who performs the task and associated compensation to be provided by the task requester for satisfactory performance of the task, the electronic marketplace being provided by one or more configured computer processors to facilitate task performance transactions between the task requesters and the human task performers and otherwise being unaffiliated with the multiple task requesters and with the multiple human task performers; and for each of at least some of the multiple available tasks, automatically facilitating performance of the task by, automatically identifying at least one of the multiple human task performers who each has one or more qualifications that satisfy the required qualifications for the task, the automatic identifying of the at least one human task performers being performed by the one or more computer processors; providing information about the task to each of the at least one identified human task performers to enable one or more of the at least one identified human task performers to select to participate in a transaction with the task requester who supplied the task that involves the one or more identified human task performers performing the task for that task requester in exchange for the associated compensation for the task from that task requester; and after receiving results for the task based on performance of the task by the one or more identified human task performers, and without further human intervention, automatically supplying the received results to an executing program of the task requester who supplied the task and facilitating providing of the associated compensation for the task to the one or more identified human task performers on behalf of that task requester, the automatic supplying and facilitating of the providing of the associated compensation being performed by the one or more configured computer processors. 9. The method of claim 1 wherein the providing of information about the at least some available tasks includes repeatedly providing information to one of the multiple human task performers about available tasks matching specified criteria. | 0.832163 |
7,516,070 | 13 | 14 | 13. The method according to claim 12 , wherein there are two or more other texts, the method further including transcribing audio using two or more speech recognition software programs and configuring each of the two or more speech recognition software programs differently from one another. | 13. The method according to claim 12 , wherein there are two or more other texts, the method further including transcribing audio using two or more speech recognition software programs and configuring each of the two or more speech recognition software programs differently from one another. 14. The method of claim 13 wherein modifying includes formatting a field name in the form such that only a first word in the field name is capitalized. | 0.629902 |
7,665,021 | 13 | 28 | 13. A system comprising: a display; a user interface, including a control device and a microphone; and processor electronics configured to perform operations comprising: displaying a text script on a display; receiving input from the control device positioning a plurality of visual images associated with a plurality of media events adjacent to the text script in a scrollable portion of the display to establish a spatial relationship between the plurality of visual images and the text script, such that the position of each visual image corresponds to one or more words in the text script with which the associated media event is to begin during a presentation; scrolling the text script on the display while maintaining the spatial relationship between the text script and the visual images; causing the media events associated with the visual images to begin approximately upon the corresponding one or more words of the text script scrolling through a predetermined region of the display during the presentation; and generating the presentation, including audio information corresponding to the user speaking at least a portion of the text script. | 13. A system comprising: a display; a user interface, including a control device and a microphone; and processor electronics configured to perform operations comprising: displaying a text script on a display; receiving input from the control device positioning a plurality of visual images associated with a plurality of media events adjacent to the text script in a scrollable portion of the display to establish a spatial relationship between the plurality of visual images and the text script, such that the position of each visual image corresponds to one or more words in the text script with which the associated media event is to begin during a presentation; scrolling the text script on the display while maintaining the spatial relationship between the text script and the visual images; causing the media events associated with the visual images to begin approximately upon the corresponding one or more words of the text script scrolling through a predetermined region of the display during the presentation; and generating the presentation, including audio information corresponding to the user speaking at least a portion of the text script. 28. The system of claim 13 , wherein at least one of the plurality of visual images graphically represents content of the corresponding media event. | 0.779104 |
8,793,238 | 1 | 3 | 1. A computer-implemented method comprising: receiving selection criteria for a campaign, the selection criteria including a plurality of keywords that control distribution of content items associated with the campaign; assigning, by a computer, each of the selection criteria to one or more sets of topic clusters, wherein at least some of the selection criteria are assigned to multiple topic clusters; determining, by a computer and for pairs of selection criteria in one of the topic clusters, a measure of similarity between the topic clusters to which each selection criteria in the pair was assigned; identifying, by a computer and as related pairs of selection criteria, the pairs of selection criteria for which the measure of similarity meets a threshold; creating a new keyword cluster based on the related pairs, the new keyword cluster including fewer than all of the keywords in the received selection criteria, the creating comprising: identifying a first selection keyword and a second selection keyword that are included in one of the related pairs; and including each of the first selection keyword and the second selection keyword in the new keyword cluster; and creating, by a computer, a new group for the campaign, the new group specifying at least one content item that is selected for distribution using keywords in the new keyword cluster. | 1. A computer-implemented method comprising: receiving selection criteria for a campaign, the selection criteria including a plurality of keywords that control distribution of content items associated with the campaign; assigning, by a computer, each of the selection criteria to one or more sets of topic clusters, wherein at least some of the selection criteria are assigned to multiple topic clusters; determining, by a computer and for pairs of selection criteria in one of the topic clusters, a measure of similarity between the topic clusters to which each selection criteria in the pair was assigned; identifying, by a computer and as related pairs of selection criteria, the pairs of selection criteria for which the measure of similarity meets a threshold; creating a new keyword cluster based on the related pairs, the new keyword cluster including fewer than all of the keywords in the received selection criteria, the creating comprising: identifying a first selection keyword and a second selection keyword that are included in one of the related pairs; and including each of the first selection keyword and the second selection keyword in the new keyword cluster; and creating, by a computer, a new group for the campaign, the new group specifying at least one content item that is selected for distribution using keywords in the new keyword cluster. 3. The method of claim 1 , wherein identifying the related pairs of selection criteria comprises: for each of the pairs of selection criteria: determining for each of the pairs of selection criteria a measure of vector similarity between a first topic vector for a first selection criteria in the pair and a second topic vector for a second selection criteria is the pair, the topic vector for each selection criteria specifying the topic clusters to which the selection criteria was assigned; and selecting, as the related pairs of selection criteria, the pairs of selection criteria for which the measure of vector similarity meets a threshold vector similarity. | 0.5 |
6,081,665 | 44 | 45 | 44. The RTVMM of claim 24 wherein the transfer of objects needing finalization from a list of finalizable objects to a finalizee list has been accomplished, the implementing step comprising the step: causing each finalizee on the finalizee list to be transferred to the appropriate activity's finalizee list or onto an orphaned finalizee list. | 44. The RTVMM of claim 24 wherein the transfer of objects needing finalization from a list of finalizable objects to a finalizee list has been accomplished, the implementing step comprising the step: causing each finalizee on the finalizee list to be transferred to the appropriate activity's finalizee list or onto an orphaned finalizee list. 45. The RTVMM of claim 44 wherein an activity's finalizee list is implemented by placing in an "activity pointer" field of a finalizee the address of the next finalizes on the activity's finalizee list. | 0.768349 |
9,165,072 | 23 | 28 | 23. The method of claim 22 , further comprising: generating, by the at least one computing device, a customized abridgement of another media content feature, the customized abridgement including a plurality of portions of the other media content feature, the portions being selected based at least in part on the interest expressed by the first user in the portion of the media content feature. | 23. The method of claim 22 , further comprising: generating, by the at least one computing device, a customized abridgement of another media content feature, the customized abridgement including a plurality of portions of the other media content feature, the portions being selected based at least in part on the interest expressed by the first user in the portion of the media content feature. 28. The method of claim 23 , further comprising recommending, by the at least one computing device, the customized abridgement of the other media content feature to the first user. | 0.5 |
8,483,518 | 10 | 16 | 10. A computer storage device storing computer-executable instructions that, when executed on one or more processors, perform operations comprising: segmenting an image into objects; assigning a value to each of the segmented objects, wherein the value is corresponds to a likelihood of an object being recognized by humans; identifying an object such that the image surrounding the object visually associates the object as being a part of the image; selecting the object for the object recognition; cropping the object from the image, wherein the object is expanded beyond a boundary of the image without conveying a contour of the object; filling a region on the image where the object has been cropped; and generating candidate objects that have similar low level features to the object cropped from the image, wherein the low level features are features that are determined to be recognizable by a computer. | 10. A computer storage device storing computer-executable instructions that, when executed on one or more processors, perform operations comprising: segmenting an image into objects; assigning a value to each of the segmented objects, wherein the value is corresponds to a likelihood of an object being recognized by humans; identifying an object such that the image surrounding the object visually associates the object as being a part of the image; selecting the object for the object recognition; cropping the object from the image, wherein the object is expanded beyond a boundary of the image without conveying a contour of the object; filling a region on the image where the object has been cropped; and generating candidate objects that have similar low level features to the object cropped from the image, wherein the low level features are features that are determined to be recognizable by a computer. 16. The computer storage device of claim 10 , wherein the operations performed by the execution of the computer-executable instructions by the one or more processors further comprise scaling sizes of the image and the set of candidate objects by a in accordance with a corresponding scaling factor. | 0.868953 |
4,454,610 | 2 | 3 | 2. Apparatus for the classification of patterns as claimed in claim 1 in which said statistical property comprises at least one variance matrix of said plurality of reference representations. | 2. Apparatus for the classification of patterns as claimed in claim 1 in which said statistical property comprises at least one variance matrix of said plurality of reference representations. 3. Apparatus for the classification of patterns as claimed in claim 2 in which said reference patterns are handwritten numerals. | 0.621302 |
8,861,856 | 22 | 24 | 22. A system for determining a logical structure of a document, the system comprising: a processor; a memory configured with instructions to perform a method comprising: acquiring an image of the document; generating at least one document hypothesis for the image of the document, wherein said generating includes referencing a plurality of document models, wherein each document model describes one or more possible logical structures in the image of the document; selecting programmatically as a best document hypothesis the document hypothesis that has a best correspondence with the image of the document; and forming a representation of the document based on the best document hypothesis. | 22. A system for determining a logical structure of a document, the system comprising: a processor; a memory configured with instructions to perform a method comprising: acquiring an image of the document; generating at least one document hypothesis for the image of the document, wherein said generating includes referencing a plurality of document models, wherein each document model describes one or more possible logical structures in the image of the document; selecting programmatically as a best document hypothesis the document hypothesis that has a best correspondence with the image of the document; and forming a representation of the document based on the best document hypothesis. 24. The system of claim 22 , wherein said selecting programmatically as a best document hypothesis the document hypothesis includes selecting programmatically the document hypothesis that has the best degree of correspondence with the selected best block hypotheses for the document. | 0.714141 |
9,373,155 | 17 | 22 | 17. 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: determining an initial height and an initial width of an image that is associated with a search result, wherein the image is to be displayed in the search result in line with text associated with the search result, and wherein the search result includes an in-line image region for displaying the image in line with the text, and a text region for displaying the text; determining an initial height of the text region of the search result based at least on (i) the text associated with the search result, and (ii) an initial width of the text region; determining an initial width of the in-line image region of the search result based at least on (i) the initial height of the text region of the search result, (ii) the initial height of the image, and (iii) the initial width of the image; determining that a) space in the in-line image region or space in the text region will include undesired whitespace, or b) text associated with the search result and for presentation in the search result will be removed from the text region; and in response to determining that a) space in the in-line image region or space in the text region will include undesired whitespace, or b) text associated with the search result and for presentation in the search result will be removed from the text region: determining an adjusted height of the text region of the search result based at least on the initial width of the in-line image region of the search result; determining an adjusted width of the in-line image region of the search result based at least on the adjusted height of the text region of the search result; determining an adjusted height and an adjusted width of the image based at least on the adjusted width of the in-line image region of the search result; scaling at least a portion of the image based at least on the adjusted height and the adjusted width of the image; and outputting the scaled image for display in the search result in line with the text. | 17. 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: determining an initial height and an initial width of an image that is associated with a search result, wherein the image is to be displayed in the search result in line with text associated with the search result, and wherein the search result includes an in-line image region for displaying the image in line with the text, and a text region for displaying the text; determining an initial height of the text region of the search result based at least on (i) the text associated with the search result, and (ii) an initial width of the text region; determining an initial width of the in-line image region of the search result based at least on (i) the initial height of the text region of the search result, (ii) the initial height of the image, and (iii) the initial width of the image; determining that a) space in the in-line image region or space in the text region will include undesired whitespace, or b) text associated with the search result and for presentation in the search result will be removed from the text region; and in response to determining that a) space in the in-line image region or space in the text region will include undesired whitespace, or b) text associated with the search result and for presentation in the search result will be removed from the text region: determining an adjusted height of the text region of the search result based at least on the initial width of the in-line image region of the search result; determining an adjusted width of the in-line image region of the search result based at least on the adjusted height of the text region of the search result; determining an adjusted height and an adjusted width of the image based at least on the adjusted width of the in-line image region of the search result; scaling at least a portion of the image based at least on the adjusted height and the adjusted width of the image; and outputting the scaled image for display in the search result in line with the text. 22. The medium of claim 17 , wherein the initial height of the text region is the same as the adjusted height of the text region. | 0.938571 |
9,478,059 | 11 | 16 | 11. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause performance comprising: receiving a meta-language file comprising a conversion of a script file in a natural language format, the script file including a plurality of natural language statements; interpreting, by a first computing device, the meta-language file for execution of at least a first portion of the meta-language file; dynamically generating and displaying, on the first computing device, one or more visually animated graphical elements in accordance with the execution of the at least a first portion of the meta-language file; wherein the one or more visually animated graphical elements comprise an action element that relates to a background comprising a plurality of zones, and that causes displaying a first zone, of the plurality of zones, of the background; in response to a user interactive action taken on the one or more visually animated graphical elements of the at least a first portion of the meta-language file, by a first user on the first computing device, setting at least one parameter based on the user interactive action; wherein setting the at least one parameter causes a third meta-language file associated with the script file to particularly execute for a second user that is different from execution of the third meta-language file for the second user when the at least one parameter is not set; wherein setting the at least one parameter causes modifying the action element to cause displaying a second zone, of the plurality of zones, of the background; receiving a second meta-language file comprising a conversion of a second script file in a natural language format, the second script file including a plurality of natural language statements, the second script file separate and different from the script file; interpreting the second meta-language file for particular execution of at least a second portion of the second meta-language file in accordance with the at least one parameter, wherein the at least one parameter persists from the third meta-language file to the second meta-language file; dynamically generating and displaying one or more second visually animated graphical elements in accordance with the particular execution of the at least a second portion of the second meta-language file, including displaying the second zone of the background; wherein the at least a second portion of the second meta-language file executes differently from the particular execution when the at least one parameter is not set. | 11. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause performance comprising: receiving a meta-language file comprising a conversion of a script file in a natural language format, the script file including a plurality of natural language statements; interpreting, by a first computing device, the meta-language file for execution of at least a first portion of the meta-language file; dynamically generating and displaying, on the first computing device, one or more visually animated graphical elements in accordance with the execution of the at least a first portion of the meta-language file; wherein the one or more visually animated graphical elements comprise an action element that relates to a background comprising a plurality of zones, and that causes displaying a first zone, of the plurality of zones, of the background; in response to a user interactive action taken on the one or more visually animated graphical elements of the at least a first portion of the meta-language file, by a first user on the first computing device, setting at least one parameter based on the user interactive action; wherein setting the at least one parameter causes a third meta-language file associated with the script file to particularly execute for a second user that is different from execution of the third meta-language file for the second user when the at least one parameter is not set; wherein setting the at least one parameter causes modifying the action element to cause displaying a second zone, of the plurality of zones, of the background; receiving a second meta-language file comprising a conversion of a second script file in a natural language format, the second script file including a plurality of natural language statements, the second script file separate and different from the script file; interpreting the second meta-language file for particular execution of at least a second portion of the second meta-language file in accordance with the at least one parameter, wherein the at least one parameter persists from the third meta-language file to the second meta-language file; dynamically generating and displaying one or more second visually animated graphical elements in accordance with the particular execution of the at least a second portion of the second meta-language file, including displaying the second zone of the background; wherein the at least a second portion of the second meta-language file executes differently from the particular execution when the at least one parameter is not set. 16. The one or more non-transitory machine-readable media of claim 11 , wherein the instructions, when executed by the one or more processors, further cause performance comprising: receiving one or more supporting files; wherein interpreting the meta-language file comprises using the one or more supporting files to identify one or more graphical representations corresponding to the one or more visually animated graphical elements; wherein dynamically generating and displaying comprises dynamically rendering at runtime, the one or more graphical representations in accordance with the meta-language file to dynamically display the one or more visually animated graphical elements. | 0.788841 |
7,487,447 | 12 | 17 | 12. A computer storage medium having a computer program stored thereon, the computer program comprising instructions operable to cause a data processing apparatus to: process a document object model (DOM) representation of web page, wherein the instructions operable to process the DOM representation comprise instructions operable to: if one or more scalable content parameters exist in the DOM representation, modify parameters pertaining to content in accordance with a zoom factor such that a modified DOM representation is displayed to a user; and if one or more scalable layout parameters exist in the DOM representation, modify parameters pertaining to layout in accordance with the zoom factor such that a modified DOM representation is displayed to a user. | 12. A computer storage medium having a computer program stored thereon, the computer program comprising instructions operable to cause a data processing apparatus to: process a document object model (DOM) representation of web page, wherein the instructions operable to process the DOM representation comprise instructions operable to: if one or more scalable content parameters exist in the DOM representation, modify parameters pertaining to content in accordance with a zoom factor such that a modified DOM representation is displayed to a user; and if one or more scalable layout parameters exist in the DOM representation, modify parameters pertaining to layout in accordance with the zoom factor such that a modified DOM representation is displayed to a user. 17. The computer storage medium of claim 12 , further comprising instructions to cause the data processing apparatus to receive a selected zoom factor for a web page. | 0.738994 |
8,073,850 | 17 | 18 | 17. The system of claim 13 , wherein the computer system is programmed to generate the score based additionally on a frequency of occurrence of the key phrase in a set of peer pages associated with said page, said peer pages including pages of one or more additional sites. | 17. The system of claim 13 , wherein the computer system is programmed to generate the score based additionally on a frequency of occurrence of the key phrase in a set of peer pages associated with said page, said peer pages including pages of one or more additional sites. 18. The system of claim 17 , wherein the computer system is programmed to identify the set of peer pages using outbound links from, and inbound links to, said page. | 0.5 |
9,772,990 | 1 | 6 | 1. A method to provide a parsing service, the method comprising: receiving, by a network server from a computing device, a copy of a network application programming interface (API) communication that includes one or more of a network API call made by the computing device or a network API response received by the computing device; parsing, by the network server, the received copy of the network API communication to generate parsed personal assistant data, wherein parsing comprises at least removing repetitive data from the received copy of the network API communication; maintaining, by the network server, a network service library that includes service translation information for a plurality of network APIs; identifying, by the network server, the service translation information in the network service library for a network API that corresponds to the received copy of the network API communication; converting, by the network server, the parsed personal assistant data using the identified service translation information, so as to produce converted data, wherein the identified service translation information comprises: terms used in connection with the network API, and corresponding translation outputs; including, by the network server, the converted data in the parsed personal assistant data; and sending, by the network server, the parsed personal assistant data that includes the converted data to the computing device. | 1. A method to provide a parsing service, the method comprising: receiving, by a network server from a computing device, a copy of a network application programming interface (API) communication that includes one or more of a network API call made by the computing device or a network API response received by the computing device; parsing, by the network server, the received copy of the network API communication to generate parsed personal assistant data, wherein parsing comprises at least removing repetitive data from the received copy of the network API communication; maintaining, by the network server, a network service library that includes service translation information for a plurality of network APIs; identifying, by the network server, the service translation information in the network service library for a network API that corresponds to the received copy of the network API communication; converting, by the network server, the parsed personal assistant data using the identified service translation information, so as to produce converted data, wherein the identified service translation information comprises: terms used in connection with the network API, and corresponding translation outputs; including, by the network server, the converted data in the parsed personal assistant data; and sending, by the network server, the parsed personal assistant data that includes the converted data to the computing device. 6. The method of claim 1 , wherein the parsing the received copy of the network API communication comprises grouping portions of the received copy of the network API communication. | 0.641434 |
9,984,684 | 7 | 8 | 7. The computer-implemented method of claim 6 , wherein determining the first proper subset of the queries comprise: selecting queries that each reference the same entity and that meet threshold similarity to each other; grouping the queries by matching corresponding responses; and selecting the group of queries with the largest number of matching corresponding responses as the first proper subset of queries. | 7. The computer-implemented method of claim 6 , wherein determining the first proper subset of the queries comprise: selecting queries that each reference the same entity and that meet threshold similarity to each other; grouping the queries by matching corresponding responses; and selecting the group of queries with the largest number of matching corresponding responses as the first proper subset of queries. 8. The computer-implemented method of claim 7 , further comprising: selecting second queries from the group of queries, each second query referencing a second entity of the first type and different from the first entity and having a corresponding response of the first response type; querying the second search service for the second entities for an attribute value matching the corresponding responses; and validating the attribute of the response types from the responses received from the second search service. | 0.5 |
10,031,970 | 19 | 20 | 19. A system for facilitating text inputs with long-tail keywords from a user in a social question and answer (Q&A) application, comprising: a memory; a processor; a receiving mechanism configured to receive a text input from the user at a client computer, wherein the text input poses a query within a community associated with the social Q&A application; an evaluating mechanism configured to apply a predictive model to the received text input; a first determining mechanism configured to determine a predicted business outcome associated with the received text input based on the applied predictive model, wherein the predicted business outcome comprises an increase in user traffic resulting from an external search engine, referring users of the external search engine to the community, that is predicted to be generated from the received text input based in part on long-tail keywords within the received text input; a second determining mechanism configured to determine a type of user interface (UI) to be generated for display to the user for subsequent interaction based on the predicted business outcome, wherein the type of UI facilitates one of: a tailored navigation through answer databases before providing a UI component to post the received text input to the community if the predicted business value is below a certain threshold value, or a direct posting of the received text to the community and receiving a further text input from the user if the predicted business value is above a certain threshold value; and a sending mechanism configured to send the determined type of UI to the client computer for display at the client computer to facilitate subsequent user-interaction with the Q&A application. | 19. A system for facilitating text inputs with long-tail keywords from a user in a social question and answer (Q&A) application, comprising: a memory; a processor; a receiving mechanism configured to receive a text input from the user at a client computer, wherein the text input poses a query within a community associated with the social Q&A application; an evaluating mechanism configured to apply a predictive model to the received text input; a first determining mechanism configured to determine a predicted business outcome associated with the received text input based on the applied predictive model, wherein the predicted business outcome comprises an increase in user traffic resulting from an external search engine, referring users of the external search engine to the community, that is predicted to be generated from the received text input based in part on long-tail keywords within the received text input; a second determining mechanism configured to determine a type of user interface (UI) to be generated for display to the user for subsequent interaction based on the predicted business outcome, wherein the type of UI facilitates one of: a tailored navigation through answer databases before providing a UI component to post the received text input to the community if the predicted business value is below a certain threshold value, or a direct posting of the received text to the community and receiving a further text input from the user if the predicted business value is above a certain threshold value; and a sending mechanism configured to send the determined type of UI to the client computer for display at the client computer to facilitate subsequent user-interaction with the Q&A application. 20. The system of claim 19 , wherein the application mechanism is further configured to determine the predicted business outcome for the received input by determining one or more of: a number of potential search engine users who will click on a search engine snippet based on the received input and create an account; or a number of potential search engine users who will click on a search engine snippet based on the received input, create an account, and convert to a specified product. | 0.5 |
8,311,796 | 4 | 7 | 4. The system of claim 1 , wherein the input affix is a prefix. | 4. The system of claim 1 , wherein the input affix is a prefix. 7. The system of claim 4 , wherein the neighboring candidate word includes any one of a candidate word that precedes the input affix or a candidate word that succeeds the input affix. | 0.5 |
9,336,268 | 1 | 3 | 1. A sentiment analyzer for an electronic learning system comprising: one or more client devices of the electronic learning system, each client device comprising: a processing unit comprising one or more processors; an I/O subsystem configured to provide electronic learning content, and to receive user input data relating to the provided electronic learning content via one or more input devices connected to the client device; and memory coupled with and readable by the processing unit and storing therein a set of instructions which, when executed by the processing unit, causes the client device to: provide electronic learning content to one or more users via the I/O subsystem; receive user feedback data relating to the provided electronic learning content via the I/O subsystem; and transmit the user feedback data relating to the provided electronic learning content to a feedback analytics server of the electronic learning system; and a feedback analytics server of the electronic learning system, comprising: a processing unit comprising one or more processors; and memory coupled with and readable by the processing unit and storing therein a set of instructions which, when executed by the processing unit, causes the feedback analytics server of the electronic learning system to: receive a plurality of feedback data from the one or more client devices, the received feedback data corresponding to user feedback of one or more users relating to electronic learning content; determine an associated user and a sentiment score for each of the received plurality of feedback data; group the plurality of feedback data into one or more feedback aggregations associated with the one or more users; calculate a sentiment score for each of the one or more feedback aggregations associated with the one or more users using a language processing engine to determine a sentiment score for text feedback data relating to the electronic learning content; receive user records associated with each of the one or more users, the received user records relating to interactions of the one or more users with the electronic learning system occurring after the receipt of the feedback data; store the user records and associated sentiment scores for each of the one or more users within a data store of the electronic learning system; training a machine learning algorithm based on the stored user records and associated sentiment scores, for each of the one or more users within the data store of the electronic learning system; receive additional feedback data from the one or more client devices, the additional feedback data including user feedback from a first user relating to electronic learning content; calculate a sentiment score for the first user, based on the received additional feedback data; using the stored user records and associated sentiment scores in the data store of the electronic learning system, determine a user record prediction for the first user using the trained machine learning algorithm, based on the calculated sentiment score for the first user; determine a sentiment analyzer output for the electronic learning system and one or more output devices, based on the determined user record prediction for the first user; and provide the determined sentiment analyzer system-output for the electronic learning system to the determined one or more output devices. | 1. A sentiment analyzer for an electronic learning system comprising: one or more client devices of the electronic learning system, each client device comprising: a processing unit comprising one or more processors; an I/O subsystem configured to provide electronic learning content, and to receive user input data relating to the provided electronic learning content via one or more input devices connected to the client device; and memory coupled with and readable by the processing unit and storing therein a set of instructions which, when executed by the processing unit, causes the client device to: provide electronic learning content to one or more users via the I/O subsystem; receive user feedback data relating to the provided electronic learning content via the I/O subsystem; and transmit the user feedback data relating to the provided electronic learning content to a feedback analytics server of the electronic learning system; and a feedback analytics server of the electronic learning system, comprising: a processing unit comprising one or more processors; and memory coupled with and readable by the processing unit and storing therein a set of instructions which, when executed by the processing unit, causes the feedback analytics server of the electronic learning system to: receive a plurality of feedback data from the one or more client devices, the received feedback data corresponding to user feedback of one or more users relating to electronic learning content; determine an associated user and a sentiment score for each of the received plurality of feedback data; group the plurality of feedback data into one or more feedback aggregations associated with the one or more users; calculate a sentiment score for each of the one or more feedback aggregations associated with the one or more users using a language processing engine to determine a sentiment score for text feedback data relating to the electronic learning content; receive user records associated with each of the one or more users, the received user records relating to interactions of the one or more users with the electronic learning system occurring after the receipt of the feedback data; store the user records and associated sentiment scores for each of the one or more users within a data store of the electronic learning system; training a machine learning algorithm based on the stored user records and associated sentiment scores, for each of the one or more users within the data store of the electronic learning system; receive additional feedback data from the one or more client devices, the additional feedback data including user feedback from a first user relating to electronic learning content; calculate a sentiment score for the first user, based on the received additional feedback data; using the stored user records and associated sentiment scores in the data store of the electronic learning system, determine a user record prediction for the first user using the trained machine learning algorithm, based on the calculated sentiment score for the first user; determine a sentiment analyzer output for the electronic learning system and one or more output devices, based on the determined user record prediction for the first user; and provide the determined sentiment analyzer system-output for the electronic learning system to the determined one or more output devices. 3. The sentiment analyzer system of claim 1 , wherein the received plurality of feedback data comprises multimodal user input data relating to the electronic learning content, and wherein determining the sentiment score for the each of the received plurality of feedback data comprises at least two of: using a language processing engine to determine a sentiment score for text feedback data relating to the electronic learning content; using a voice analyzer to determine a sentiment score for voice feedback data relating to the electronic learning content; using a gesture analyzer to determine a sentiment score for movement feedback data relating to the electronic learning content; and using an eye movement analyzer to determine a sentiment score for eye movement feedback data relating to the electronic learning content. | 0.601825 |
8,947,736 | 17 | 20 | 17. A scanner comprising: a scanning section for scanning a hard copy document to generate a gray-scale document image; and a data processing apparatus for processing the gray-scale document image to generate a binary map of the gray-scale document image, wherein the processing of the gray-scale document image includes: (a) identifying text characters in the gray-scale document image, including performing an initial binarization of the gray-scale image to generate an initial binary image, and extracting connected image components in the initial binary image as text characters, (b) classifying each text character identified in step (a) as either a halftone text character which is a character formed by a halftone pattern or a non-halftone text character based on a topological analysis of the text character which determines a number of holes in a connected image component corresponding to the text character, including calculating an Euler number for each text character, and classifying a text character as halftone text if the Euler number for the text character is below a predetermined value, and classifying a text character as non-halftone text if the Euler number of the text character is equal to or above the predetermined value, and (c) binarizing halftone text characters using pixel value characteristics obtained from only halftone text characters classified in step (b). | 17. A scanner comprising: a scanning section for scanning a hard copy document to generate a gray-scale document image; and a data processing apparatus for processing the gray-scale document image to generate a binary map of the gray-scale document image, wherein the processing of the gray-scale document image includes: (a) identifying text characters in the gray-scale document image, including performing an initial binarization of the gray-scale image to generate an initial binary image, and extracting connected image components in the initial binary image as text characters, (b) classifying each text character identified in step (a) as either a halftone text character which is a character formed by a halftone pattern or a non-halftone text character based on a topological analysis of the text character which determines a number of holes in a connected image component corresponding to the text character, including calculating an Euler number for each text character, and classifying a text character as halftone text if the Euler number for the text character is below a predetermined value, and classifying a text character as non-halftone text if the Euler number of the text character is equal to or above the predetermined value, and (c) binarizing halftone text characters using pixel value characteristics obtained from only halftone text characters classified in step (b). 20. The scanner of claim 17 , wherein step (c) comprises applying a local thresholding method to each halftone text region. | 0.927732 |
6,043,815 | 11 | 15 | 11. An operating method for a computer comprising steps for: (a) storing a document written in hypertext markup language (HTML), said HTML document including an applet tag for invoking a Universal Client device. (b) storing computer readable first instructions for generating said Universal Client device; (c) storing computer readable second instructions for permitting said computer to utilize a virtual machine; and (d) executing said Universal Client device on said computer using said virtual machine to thereby generate predetermined graphical user interface (GUI) objects and display said GUI objects on said computer responsible to a GUIScript. | 11. An operating method for a computer comprising steps for: (a) storing a document written in hypertext markup language (HTML), said HTML document including an applet tag for invoking a Universal Client device. (b) storing computer readable first instructions for generating said Universal Client device; (c) storing computer readable second instructions for permitting said computer to utilize a virtual machine; and (d) executing said Universal Client device on said computer using said virtual machine to thereby generate predetermined graphical user interface (GUI) objects and display said GUI objects on said computer responsible to a GUIScript. 15. The operating method for the computer as recited in claim 11, wherein one of said predetermined GUI objects comprises a MultiMedia presentation. | 0.847423 |
8,825,699 | 1 | 4 | 1. A mobile communications device comprising a display device and one or more modules configured to: display search results on the display device of a first search performed in a first context that involves a single application based on a search query; reduce a search query input area on the display device in response to an input to scroll through the search results; during display of the search results of the first search and responsive to receiving an input via a pan gesture that indicates that a scope of the first search is to be expanded to another application, perform a second search that includes a second context that involves the other application, the second search being performed without manual reentry of the search query; and responsive to receiving the input via the pan gesture, cause the second search to expand from searching content in a local storage of the mobile communications device to searching content remote from the mobile communications device. | 1. A mobile communications device comprising a display device and one or more modules configured to: display search results on the display device of a first search performed in a first context that involves a single application based on a search query; reduce a search query input area on the display device in response to an input to scroll through the search results; during display of the search results of the first search and responsive to receiving an input via a pan gesture that indicates that a scope of the first search is to be expanded to another application, perform a second search that includes a second context that involves the other application, the second search being performed without manual reentry of the search query; and responsive to receiving the input via the pan gesture, cause the second search to expand from searching content in a local storage of the mobile communications device to searching content remote from the mobile communications device. 4. A mobile communications device as described in claim 1 , wherein the first context is user selectable through interaction with a user interface displayed on the display device. | 0.65444 |
9,466,073 | 10 | 11 | 10. The method of claim 1 , wherein the first content overlay information further enables the first user device to present a graphical visualization of: a second control that allows the user to indicate a favorable opinion of the relevant advertisement; a third control that, responsive to user selection, causes the first user device to present information relating to the use of the re-publishing control; and a fourth control that, responsive to user selection, causes the first user device to present information relating to the content of the relevant advertisement. | 10. The method of claim 1 , wherein the first content overlay information further enables the first user device to present a graphical visualization of: a second control that allows the user to indicate a favorable opinion of the relevant advertisement; a third control that, responsive to user selection, causes the first user device to present information relating to the use of the re-publishing control; and a fourth control that, responsive to user selection, causes the first user device to present information relating to the content of the relevant advertisement. 11. The method of claim 10 , wherein the first content overlay information further enables the first user device to present a graphical visualization of a fifth control that provides information on the user's interactions with the relevant advertisement or the re-publishing control. | 0.613388 |
9,367,620 | 8 | 12 | 8. A system for handling a query statement generated by local network devices on a network, the system comprising: a hardware identification device for identifying multiple system queries to local network devices on a network, wherein the multiple system queries are autonomously issued by a computer that is coupled to the network, and wherein the multiple system queries request system states of the local network devices; a hardware interception device for intercepting multiple query statements from the local network devices to a wide area network search engine, wherein the multiple query statements are in response to the system queries; a hardware generation device for generating a natural language query from one of the multiple query statements, wherein the natural language query is a logical query that is answered by said one of the multiple query statements; a hardware receiver for receiving a query from a user, wherein the query from the user is an unstructured query about a state of a particular device from the local network devices; and a hardware comparison device for comparing the query from the user with the natural language query to determine if a match between the query from the user with the natural language query exceeds a predetermined threshold value. | 8. A system for handling a query statement generated by local network devices on a network, the system comprising: a hardware identification device for identifying multiple system queries to local network devices on a network, wherein the multiple system queries are autonomously issued by a computer that is coupled to the network, and wherein the multiple system queries request system states of the local network devices; a hardware interception device for intercepting multiple query statements from the local network devices to a wide area network search engine, wherein the multiple query statements are in response to the system queries; a hardware generation device for generating a natural language query from one of the multiple query statements, wherein the natural language query is a logical query that is answered by said one of the multiple query statements; a hardware receiver for receiving a query from a user, wherein the query from the user is an unstructured query about a state of a particular device from the local network devices; and a hardware comparison device for comparing the query from the user with the natural language query to determine if a match between the query from the user with the natural language query exceeds a predetermined threshold value. 12. The system of claim 8 , further comprising: a hardware creation device for creating a proxy search engine, wherein the proxy search engine consolidates the multiple query statements, from the local network devices, with any previous query statements that have been stored in the wide area network search engine for other devices. | 0.528329 |
9,350,863 | 15 | 18 | 15. The method of claim 11 , wherein, after said anchor is built, said chat data is categorized into said team/department names using said filters. | 15. The method of claim 11 , wherein, after said anchor is built, said chat data is categorized into said team/department names using said filters. 18. The method of claim 15 , wherein a priority index is provided to control each of said filters. | 0.863128 |
7,478,192 | 48 | 49 | 48. An associative memory computer program product according to claim 44 wherein the computer-readable program code that is configured to provide a processing system further comprises: computer-readable program code that is configured to provide a reader system that is responsive to the input documents and is configured to produce document IDs and document data therefrom; computer-readable program code that is configured to provide a parser that is responsive to the document data and is configured to extract entities from the document data; and computer-readable program code that is configured to provide a context generator that is responsive to the parser and is configured to identify observer entities and observed entities from the entities that are extracted and to provide the observer entities and observed entities to the entity observer and the document observer. | 48. An associative memory computer program product according to claim 44 wherein the computer-readable program code that is configured to provide a processing system further comprises: computer-readable program code that is configured to provide a reader system that is responsive to the input documents and is configured to produce document IDs and document data therefrom; computer-readable program code that is configured to provide a parser that is responsive to the document data and is configured to extract entities from the document data; and computer-readable program code that is configured to provide a context generator that is responsive to the parser and is configured to identify observer entities and observed entities from the entities that are extracted and to provide the observer entities and observed entities to the entity observer and the document observer. 49. An associative memory computer program product according to claim 48 wherein the computer-readable program code that is configured to provide a processing system further comprises: computer-readable program code that is configured to provide a controller that is configured to control the reader system, the parser and the context generator according to a document itinerary; and computer-readable program code that is configured to provide a whiteboard that is configured to store intermediate results that are produced by the reader system, the parser and the context generator. | 0.5 |
7,822,646 | 1 | 5 | 1. A computer controlled method performed within a review-provider server, the method comprising: receiving a review request by said review-provider server for a reviewed subject from a first networked computer, said review request responsive to processing of a client-side script by said first networked computer, said client-side script caused to be received by said first networked computer by a networked third-party server; selecting by said review-provider server one or more reviews of said reviewed subject responsive to said review request; and sending by said review-provider server at least a portion of said one or more reviews to said first networked computer. | 1. A computer controlled method performed within a review-provider server, the method comprising: receiving a review request by said review-provider server for a reviewed subject from a first networked computer, said review request responsive to processing of a client-side script by said first networked computer, said client-side script caused to be received by said first networked computer by a networked third-party server; selecting by said review-provider server one or more reviews of said reviewed subject responsive to said review request; and sending by said review-provider server at least a portion of said one or more reviews to said first networked computer. 5. The computer controlled method of claim 1 , wherein said one or more reviews includes a first review and a second review, said method further comprising ordering said first review and said second review responsive to a sort order. | 0.851213 |
7,730,007 | 1 | 2 | 1. A computer program product for classifying a message, the computer program product comprising: a computer readable medium having computer readable program code embodied therein, the computer readable program code comprising: computer readable program code configured to receive a message to be classified, said message having a message identifier; computer readable program code configured to determine if said message identifier uniquely maps to a corresponding classification category; computer readable program code configured to label the message with the identified classification category if said message identifier maps directly to a corresponding classification category; computer readable program code configured to parse the message to be classified and identify a plurality of features from the parsed message if said message identifier does not map directly to a corresponding classification category; computer readable program code configured to compare at least one classification rule to the plurality of features if said message identifier does not map directly to a corresponding classification category; computer readable program code configured to rate each classification rule that matches to said plurality of features; computer readable program code configured to identify a classification category from said rating; and computer readable program code configured to label the message with the identified classification category. | 1. A computer program product for classifying a message, the computer program product comprising: a computer readable medium having computer readable program code embodied therein, the computer readable program code comprising: computer readable program code configured to receive a message to be classified, said message having a message identifier; computer readable program code configured to determine if said message identifier uniquely maps to a corresponding classification category; computer readable program code configured to label the message with the identified classification category if said message identifier maps directly to a corresponding classification category; computer readable program code configured to parse the message to be classified and identify a plurality of features from the parsed message if said message identifier does not map directly to a corresponding classification category; computer readable program code configured to compare at least one classification rule to the plurality of features if said message identifier does not map directly to a corresponding classification category; computer readable program code configured to rate each classification rule that matches to said plurality of features; computer readable program code configured to identify a classification category from said rating; and computer readable program code configured to label the message with the identified classification category. 2. The computer program product of claim 1 , further comprising: computer readable program code configured to compare a second classification rule to the plurality of features. | 0.892289 |
7,937,348 | 23 | 40 | 23. A computer implemented method of correlating user profiles to software applications comprising the steps of: reading a first learning objective from a user profile from a storage medium; reading a second learning objective from a software application; determining a relevance of the first learning objective to the second learning objective; and adapting the software application in accordance with the determined relevance and updating the user profile in accordance with the determined relevance. | 23. A computer implemented method of correlating user profiles to software applications comprising the steps of: reading a first learning objective from a user profile from a storage medium; reading a second learning objective from a software application; determining a relevance of the first learning objective to the second learning objective; and adapting the software application in accordance with the determined relevance and updating the user profile in accordance with the determined relevance. 40. The computer implemented method of claim 23 , wherein said software application comprises one or more measured objectives formed from a related group of software application measurements; and is adapted for the assessment of a learning objective, said learning objective being formed from: the selection of one or more measured objectives; defined outcome conditions for the measured objectives; and selected outcome activities that each invoke a command in the learning application. | 0.5 |
9,239,763 | 1 | 5 | 1. A method, comprising: a database server establishing a plurality of database sessions for access to a plurality of pluggable databases in a container database, wherein said container database includes a separate database dictionary for each pluggable database of said plurality of pluggable databases, wherein said database server establishing a plurality of database sessions includes, for each database session of said plurality of database sessions: receiving a connection request; determining that the connection request is for access to a particular pluggable database of said plurality of said pluggable databases; and attaching the respective database dictionary of said particular pluggable database to said each database session. | 1. A method, comprising: a database server establishing a plurality of database sessions for access to a plurality of pluggable databases in a container database, wherein said container database includes a separate database dictionary for each pluggable database of said plurality of pluggable databases, wherein said database server establishing a plurality of database sessions includes, for each database session of said plurality of database sessions: receiving a connection request; determining that the connection request is for access to a particular pluggable database of said plurality of said pluggable databases; and attaching the respective database dictionary of said particular pluggable database to said each database session. 5. The method of claim 1 , wherein at least two pluggable databases of said plurality of pluggable databases each define a schema having the same schema name. | 0.90814 |
7,565,345 | 2 | 3 | 2. The method of claim 1 , wherein the initial query is received from a front-end server as entered by a client. | 2. The method of claim 1 , wherein the initial query is received from a front-end server as entered by a client. 3. The method of claim 2 , wherein results of the initial query are returned to the client by the front-end server. | 0.5 |
8,671,078 | 11 | 12 | 11. A system for providing sharing of business logic items, the system comprising: a memory for storing executable program code; and a processor, functionally coupled to the memory, the processor being responsive to computer-executable instructions contained in the program code and operative to: provide application functionality to a user to create, access, and edit a first document, the first document including one or more business logic items; receiving an annotation associated with one or more business logic items in the first document, the annotation designating the one or more business logic items as a connection default business logic item or a shared business logic item; generate an identifier for each of the one or more annotated connection default business logic items and shared business logic items; publish the first document to an integrated server platform document library; automatically store the related connection default business logic items in the first document for access by the second document; crawl documents stored in an integrated server platform document library for annotated business logic items; populate an index component with the one or more annotated business logic items and associated identifiers, the index component being utilized to index and catalog shared business logic items, the index component using one or more of metadata, content and other information when indexing against one or more disparate information sources, the index component being further utilized to identify unique document parts; query the index component for connection default business logic items related to second document based on a data source of the second document; and maintain references to unique business logic items, the references comprising at least a relative path of a parent document site collection and the identifier, the identifier being utilized to repair a reference that is no longer available, the identifier being separate from the relative path. | 11. A system for providing sharing of business logic items, the system comprising: a memory for storing executable program code; and a processor, functionally coupled to the memory, the processor being responsive to computer-executable instructions contained in the program code and operative to: provide application functionality to a user to create, access, and edit a first document, the first document including one or more business logic items; receiving an annotation associated with one or more business logic items in the first document, the annotation designating the one or more business logic items as a connection default business logic item or a shared business logic item; generate an identifier for each of the one or more annotated connection default business logic items and shared business logic items; publish the first document to an integrated server platform document library; automatically store the related connection default business logic items in the first document for access by the second document; crawl documents stored in an integrated server platform document library for annotated business logic items; populate an index component with the one or more annotated business logic items and associated identifiers, the index component being utilized to index and catalog shared business logic items, the index component using one or more of metadata, content and other information when indexing against one or more disparate information sources, the index component being further utilized to identify unique document parts; query the index component for connection default business logic items related to second document based on a data source of the second document; and maintain references to unique business logic items, the references comprising at least a relative path of a parent document site collection and the identifier, the identifier being utilized to repair a reference that is no longer available, the identifier being separate from the relative path. 12. The system of claim 11 , wherein the processor is further operable to: read the first document containing the one or more selected connection default business logic items from the integrated server platform document library upon receiving an indication that one or more of the related connection default business logic items has been selected; provide the one or more selected connection default business logic items to the second document; maintain connection default business logic item relationship data and identifiers; receive an indication that a business logic item in the first document has been modified; and provide the second document with the modified connection default business logic item. | 0.5 |
9,436,649 | 6 | 10 | 6. A system for updating an electronic calendar comprising: a natural language processing module executing on a computer processor for parsing the content of a received incoming electronic mail message in a natural language; a role change detection module executing on the computer processor for automatically detecting a change in role that is expressed within the parsed electronic mail message using a set of established phrases indicative of a role change and identifies a person affected by the detected role change, the role change detection module optionally also providing at least one of a job title and a job location, wherein in response to detecting the change in role expressed in the electronic email message, the role change detection module searches a remote calendar database for meetings in entries already scheduled in a client's electronic-calendar and compares participants of each meeting with each person involved in the change in role in a contacts database to determine if a person associated with the detected change in role also appears as a participant in a given meeting; the contacts database within a client computer in communication with the computer processor for storing the change in role; and a calendar checking module executing on the computer processor for, wherein in response to the role change detection module determining that a person associated with the detected change in role also appears as a participant in a given meeting, proposing an update to an entry in the electronic calendar that corresponds to the meeting. | 6. A system for updating an electronic calendar comprising: a natural language processing module executing on a computer processor for parsing the content of a received incoming electronic mail message in a natural language; a role change detection module executing on the computer processor for automatically detecting a change in role that is expressed within the parsed electronic mail message using a set of established phrases indicative of a role change and identifies a person affected by the detected role change, the role change detection module optionally also providing at least one of a job title and a job location, wherein in response to detecting the change in role expressed in the electronic email message, the role change detection module searches a remote calendar database for meetings in entries already scheduled in a client's electronic-calendar and compares participants of each meeting with each person involved in the change in role in a contacts database to determine if a person associated with the detected change in role also appears as a participant in a given meeting; the contacts database within a client computer in communication with the computer processor for storing the change in role; and a calendar checking module executing on the computer processor for, wherein in response to the role change detection module determining that a person associated with the detected change in role also appears as a participant in a given meeting, proposing an update to an entry in the electronic calendar that corresponds to the meeting. 10. A network computer system comprising the system of claim 6 and a plurality of client computers, each configured for generating out-of-office messages, the system for updating an electronic calendar being resident on at least one of the client computers and a server computer in communication therewith via a network and wherein the database is linked to the at least one of the client computers and the server computer via the network. | 0.5 |
9,507,825 | 23 | 25 | 23. One or more non-transitory computer-readable media storing instructions which, when executed by one or more computing devices, cause the one or more computing devices to perform operations comprising: receiving a query statement comprising a filter predicate on a column of a first database table, the filter predicate comprising a value for the column; pruning a particular partition of a second database table from access paths for processing the query statement; wherein the column of the filter predicate is not a column of a partitioning key used for partitioning the second database table; and wherein the particular partition is identified as pruneable based at least on (a) aggregated zone map information associated with the particular partition and (b) the value for the column in the filter predicate. | 23. One or more non-transitory computer-readable media storing instructions which, when executed by one or more computing devices, cause the one or more computing devices to perform operations comprising: receiving a query statement comprising a filter predicate on a column of a first database table, the filter predicate comprising a value for the column; pruning a particular partition of a second database table from access paths for processing the query statement; wherein the column of the filter predicate is not a column of a partitioning key used for partitioning the second database table; and wherein the particular partition is identified as pruneable based at least on (a) aggregated zone map information associated with the particular partition and (b) the value for the column in the filter predicate. 25. The one or more non-transitory computer-readable media of claim 23 , wherein the first database table and the second database table are the same table. | 0.629187 |
8,024,329 | 1 | 5 | 1. A method for using indexes to search a knowledge base in at least one computer system, the method executed by the computer system and comprising: accessing a knowledge base comprising a semantic network of relationships among concepts, each concept having a set of values associated with it, wherein each concept is an instance of a category and each value is an instance of an attribute and wherein categories and attributes form a knowledge base schema; receiving, from a user searching for one or more target concepts, a query represented as criteria and criteria values that specify constraints on the categories and the attributes; executing a search of the concepts and the values of the knowledge base to retrieve the one or more target concepts using indexes selected from a group consisting of: a) one or more transitive indexes that index transitive relationships from concepts in a first category through at least one second category to concepts in a third category and b) one or more transitive closure indexes that index transitive closure relationships amongst concepts within a category; and retrieving a result subset of the target concepts and the values that satisfies the criteria and criteria values. | 1. A method for using indexes to search a knowledge base in at least one computer system, the method executed by the computer system and comprising: accessing a knowledge base comprising a semantic network of relationships among concepts, each concept having a set of values associated with it, wherein each concept is an instance of a category and each value is an instance of an attribute and wherein categories and attributes form a knowledge base schema; receiving, from a user searching for one or more target concepts, a query represented as criteria and criteria values that specify constraints on the categories and the attributes; executing a search of the concepts and the values of the knowledge base to retrieve the one or more target concepts using indexes selected from a group consisting of: a) one or more transitive indexes that index transitive relationships from concepts in a first category through at least one second category to concepts in a third category and b) one or more transitive closure indexes that index transitive closure relationships amongst concepts within a category; and retrieving a result subset of the target concepts and the values that satisfies the criteria and criteria values. 5. The method of claim 1 , wherein at least one of the indexes is an attribute index of single concepts referring to a set of multiple values. | 0.832151 |
9,286,548 | 12 | 13 | 12. The system of claim 11 , wherein the search engine comprises a first classifier and a second classifier, wherein the first classifier infers the first distribution and the second classifier infers the second distribution. | 12. The system of claim 11 , wherein the search engine comprises a first classifier and a second classifier, wherein the first classifier infers the first distribution and the second classifier infers the second distribution. 13. The system of claim 12 , wherein the first classifier is a text classifier and the second classifier is an image classifier. | 0.5 |
7,657,417 | 2 | 4 | 2. The method of claim 1 , wherein the domain model relates to a simple type or a complex type, the method further comprising: when a property for the domain model is of the simple type, populating the domain model with a value according to the document being represented; and when a property for the domain model is of the complex type, selectively adding another domain model as a value for the property according to the document being represented. | 2. The method of claim 1 , wherein the domain model relates to a simple type or a complex type, the method further comprising: when a property for the domain model is of the simple type, populating the domain model with a value according to the document being represented; and when a property for the domain model is of the complex type, selectively adding another domain model as a value for the property according to the document being represented. 4. The method of claim 2 , comprising: analyzing the set of domain models by determining values of properties from at least one domain model, the values extracted from the document represented by the domain model. | 0.5 |
7,664,638 | 1 | 6 | 1. A method, performed on a computer system, for tracking time using speech recognition, the method comprising the acts of: accessing speech data; recognizing at least two voice commands from the speech data, each voice command occurring at a different time; determining a first time, indicative of a first time of day, associated with a speaking of a first of the voice commands, wherein said first voice command identifies a start of a time interval; determining a second time, indicative of a second time of day, associated with a speaking of a second of the voice commands, wherein said second voice command identifies an end of said time interval; and storing data identifying said time interval and data identifying one or more of said first voice command and second voice command, wherein the speech data comprises a time stamp that indicates a third time of day; and the act of determining a first time comprises: determining an offset time that is a time difference between the time stamp and a time when the first voice command is spoken; and determining the first time through reference to the time stamp and the offset time. | 1. A method, performed on a computer system, for tracking time using speech recognition, the method comprising the acts of: accessing speech data; recognizing at least two voice commands from the speech data, each voice command occurring at a different time; determining a first time, indicative of a first time of day, associated with a speaking of a first of the voice commands, wherein said first voice command identifies a start of a time interval; determining a second time, indicative of a second time of day, associated with a speaking of a second of the voice commands, wherein said second voice command identifies an end of said time interval; and storing data identifying said time interval and data identifying one or more of said first voice command and second voice command, wherein the speech data comprises a time stamp that indicates a third time of day; and the act of determining a first time comprises: determining an offset time that is a time difference between the time stamp and a time when the first voice command is spoken; and determining the first time through reference to the time stamp and the offset time. 6. The method of claim 1 , further comprising the act of: determining at least one task name from the text of the at least two voice commands. | 0.885484 |
8,682,832 | 17 | 20 | 17. A programmable device comprising: a processing unit; a computer readable memory in communication with the processing unit; a tangible computer-readable storage medium in communication with the processing unit; and a network interface in communication with the processing unit and a virtual universe environment; wherein the processing unit, when executing program instructions stored on the tangible computer-readable storage medium via the computer readable memory, is caused to: monitor a behavior of a collective plurality of avatars within a virtual universe environment for compliance with a violation threshold of an avatar behavior rule for the virtual universe environment, and to determine if any of the avatars is complaining that the monitored behavior of another of the avatars is at an objectionable level within the virtual universe environment; determine an amount of compliance of the monitored collective plurality behavior with the rule; compare the determined compliance amount with the violation threshold; if the determined compliance amount does not exceed the violation threshold and any of the avatars is determined to be complaining that the monitored behavior of another of the avatars is at an objectionable level within the virtual universe environment, revise the violation threshold downward, wherein a lower level of the determined compliance amount is required to exceed the violation threshold; and repetitively monitor the behavior of the collective plurality of avatars within the virtual universe environment for compliance with the rule and to determine if any of the avatars is complaining that the monitored behavior of another of the avatars is at the objectionable level within the virtual universe environment, determine an amount of compliance of the monitored collective plurality behavior with the rule, compare the determined compliance amount with the revised violation threshold, and revise the violation threshold downward, until the monitored compliance amount exceeds the revised violation threshold or none of the avatars is determined to be complaining that the monitored behavior of another of the avatars is at the objectionable level within the virtual universe environment. | 17. A programmable device comprising: a processing unit; a computer readable memory in communication with the processing unit; a tangible computer-readable storage medium in communication with the processing unit; and a network interface in communication with the processing unit and a virtual universe environment; wherein the processing unit, when executing program instructions stored on the tangible computer-readable storage medium via the computer readable memory, is caused to: monitor a behavior of a collective plurality of avatars within a virtual universe environment for compliance with a violation threshold of an avatar behavior rule for the virtual universe environment, and to determine if any of the avatars is complaining that the monitored behavior of another of the avatars is at an objectionable level within the virtual universe environment; determine an amount of compliance of the monitored collective plurality behavior with the rule; compare the determined compliance amount with the violation threshold; if the determined compliance amount does not exceed the violation threshold and any of the avatars is determined to be complaining that the monitored behavior of another of the avatars is at an objectionable level within the virtual universe environment, revise the violation threshold downward, wherein a lower level of the determined compliance amount is required to exceed the violation threshold; and repetitively monitor the behavior of the collective plurality of avatars within the virtual universe environment for compliance with the rule and to determine if any of the avatars is complaining that the monitored behavior of another of the avatars is at the objectionable level within the virtual universe environment, determine an amount of compliance of the monitored collective plurality behavior with the rule, compare the determined compliance amount with the revised violation threshold, and revise the violation threshold downward, until the monitored compliance amount exceeds the revised violation threshold or none of the avatars is determined to be complaining that the monitored behavior of another of the avatars is at the objectionable level within the virtual universe environment. 20. The programmable device of claim 17 , wherein the processing unit, when executing the program instructions stored on the tangible computer-readable storage medium via the computer readable memory, is further caused to: select each of the collective plurality of avatars as a function of at least one of: participation in an activity in common with others of the collective plurality; and demographic data associated with a selected avatar correlating to a specified demographic criterion. | 0.506024 |
9,621,624 | 12 | 21 | 12. A method of inserting content, the method comprising: analyzing, by one or more processors, elements of a conversation taking place at a first destination to detect elements relating to expression of need for information in the conversation; identifying a pool of one or more candidate second destinations based on relevance of the second destinations to the expression of need for information in the conversation; identifying a pool of one or more candidate templates relevant to the pool of one or more candidate second destinations; constructing a set of candidate creatives by combining one or more of the pool of candidate templates with one or more of the candidate second destinations; scoring the set of candidate creatives for relevance to the expression of need for information; selecting, by the one or more processors, at least one of the set of candidate creatives based on the scoring for presentation at the first destination; and inserting, by the one or more processors, the selected one of the candidate creatives at the first destination. | 12. A method of inserting content, the method comprising: analyzing, by one or more processors, elements of a conversation taking place at a first destination to detect elements relating to expression of need for information in the conversation; identifying a pool of one or more candidate second destinations based on relevance of the second destinations to the expression of need for information in the conversation; identifying a pool of one or more candidate templates relevant to the pool of one or more candidate second destinations; constructing a set of candidate creatives by combining one or more of the pool of candidate templates with one or more of the candidate second destinations; scoring the set of candidate creatives for relevance to the expression of need for information; selecting, by the one or more processors, at least one of the set of candidate creatives based on the scoring for presentation at the first destination; and inserting, by the one or more processors, the selected one of the candidate creatives at the first destination. 21. The method of claim 12 , wherein the detected elements of the first destination correspond to a message at the first destination, and the instructions comprise instructions for display of the selected one of the set of candidate creatives at a location near to the message. | 0.5 |
9,449,095 | 10 | 13 | 10. A system comprising one or more computers and one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a current search query submitted by a current user of a current user device to a search engine system; determining that the current search query is similar to a first previously submitted search query of a plurality of previously submitted search queries that have previously been submitted by the current user to the search engine system, wherein determining that the current search query is similar to the first previously submitted search query comprises determining that at least one first term from the current search query matches a corresponding term that appears in the first previously submitted search query; determining that a different second term satisfies the condition that: (i) the different second term appears in the first previously submitted search query that is similar to the current search query, (ii) the different second term does not appear in the current search query, and (iii) the different second term appears in at least a threshold number of other distinct search queries of the plurality of previously submitted search queries that have previously been submitted by the current user, wherein each other distinct search query is distinct from both the first previously submitted search query and the current search query; generating a revised search query by adding the different second term to the current search query; obtaining search results for the revised search query from a search engine; and providing the search results to the current user in a response to the current search query. | 10. A system comprising one or more computers and one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a current search query submitted by a current user of a current user device to a search engine system; determining that the current search query is similar to a first previously submitted search query of a plurality of previously submitted search queries that have previously been submitted by the current user to the search engine system, wherein determining that the current search query is similar to the first previously submitted search query comprises determining that at least one first term from the current search query matches a corresponding term that appears in the first previously submitted search query; determining that a different second term satisfies the condition that: (i) the different second term appears in the first previously submitted search query that is similar to the current search query, (ii) the different second term does not appear in the current search query, and (iii) the different second term appears in at least a threshold number of other distinct search queries of the plurality of previously submitted search queries that have previously been submitted by the current user, wherein each other distinct search query is distinct from both the first previously submitted search query and the current search query; generating a revised search query by adding the different second term to the current search query; obtaining search results for the revised search query from a search engine; and providing the search results to the current user in a response to the current search query. 13. The system of claim 10 , wherein determining that the current search query is similar to the first previously submitted search query further comprises: determining that, in response to the current search query, users have frequently selected search results that identify the same resources as search results that users have frequently selected in response to the first previously submitted search query. | 0.563305 |
10,078,631 | 9 | 10 | 9. A non-transitory computer-readable storage medium comprising instructions for causing one or more processors to: receive a first typed character from a user; determine a first entropy of a first set of possible word completions based on first probabilities of the first set of possible word completions, wherein the first probabilities are based on the first typed character; receive a second typed character from the user; determine a second entropy of a second set of possible word completions based on second probabilities of the second set of possible word completions, wherein the second probabilities are based on the first typed character and the second typed character; determine a reduction in entropy from the first entropy to the second entropy, wherein determining the reduction in entropy comprises: determining the reduction in entropy based on third probabilities of a third set of possible word completions, the third set of possible word completions comprising words in the first set of possible word completions other than words in the second set of possible word completions; and in response to the reduction in entropy exceeding a threshold, cause a candidate word to be displayed from the second set of possible word completions. | 9. A non-transitory computer-readable storage medium comprising instructions for causing one or more processors to: receive a first typed character from a user; determine a first entropy of a first set of possible word completions based on first probabilities of the first set of possible word completions, wherein the first probabilities are based on the first typed character; receive a second typed character from the user; determine a second entropy of a second set of possible word completions based on second probabilities of the second set of possible word completions, wherein the second probabilities are based on the first typed character and the second typed character; determine a reduction in entropy from the first entropy to the second entropy, wherein determining the reduction in entropy comprises: determining the reduction in entropy based on third probabilities of a third set of possible word completions, the third set of possible word completions comprising words in the first set of possible word completions other than words in the second set of possible word completions; and in response to the reduction in entropy exceeding a threshold, cause a candidate word to be displayed from the second set of possible word completions. 10. The non-transitory computer-readable storage medium of claim 9 , wherein the first probabilities of the first set of possible word completions are determined by: determining, using a word n-gram model, fourth probabilities of a plurality of predicted words based on the first typed character; determining, using a character m-gram model, fifth probabilities of a plurality of predicted characters based on the first typed character; and determining the first probabilities of the first set of possible word completions based jointly on the fourth probabilities and the fifth probabilities. | 0.5 |
9,563,487 | 12 | 13 | 12. The device of claim 8 , wherein the one or more metadata files are configured to describe an object-oriented class, included in the one or more API modules, in an object-oriented manner. | 12. The device of claim 8 , wherein the one or more metadata files are configured to describe an object-oriented class, included in the one or more API modules, in an object-oriented manner. 13. The device of claim 12 , wherein the object-oriented class comprising a file class. | 0.5 |
7,580,827 | 34 | 36 | 34. The computer-readable memory device of claim 28 , where the variation of context in which the sequence occurs is calculated relative to a collection of documents. | 34. The computer-readable memory device of claim 28 , where the variation of context in which the sequence occurs is calculated relative to a collection of documents. 36. The computer-readable memory device of claim 34 , where the variation of context in which the sequence occurs, HM(S), is calculated as
HM ( S )=MIN( HLM ( S ), HRM ( S )), where MIN defines a minimum operation, S represents the sequence, HLM(S) is defined as a minimum of 1 - f ( wS ) f ( S ) for each term w in the collection of documents, HRM(S) is defined as a minimum of 1 - f ( Sw ) f ( S ) for each term w in the collection of documents, f(wS) defines a number of times a particular term, w, appears in the collection of documents followed by the sequence, f(Sw) refers to a number of times the sequence is followed by w in the collection of documents, and f(S) refers to a number of times the sequence is present in the collection of documents. | 0.536925 |
9,244,964 | 1 | 4 | 1. A computer-implemented method of determining a root cause of an incident, said method comprising: analyzing, via a processor, one or more change records based on text analytics using a dictionary and rules for the analysis in order to generate an index of analyzed data that represents the one or more change records in an abbreviated representation for searching, wherein the indent pertains to a defect with a manufactured product provided by an entity, and wherein the change records each include a change implemented to operations that produce the manufactured product provided by the entity and a corresponding time frame for occurrence of the change; searching, via a processor, the index of analyzed data by applying information from a request for the root cause of the incident to the index of analyzed data to determine one or more change records from the abbreviated representation listing changes serving as one or more candidate causes for the incident, wherein applying the information includes: correlating the request with the changes listed by the one or more change records based on a time associated with the request being within a specified time interval of the corresponding time frame of occurrence of the changes listed by the one or more change records, and identifying the one or more candidate causes in the one or more change records as causes for the incident based on the correlation. | 1. A computer-implemented method of determining a root cause of an incident, said method comprising: analyzing, via a processor, one or more change records based on text analytics using a dictionary and rules for the analysis in order to generate an index of analyzed data that represents the one or more change records in an abbreviated representation for searching, wherein the indent pertains to a defect with a manufactured product provided by an entity, and wherein the change records each include a change implemented to operations that produce the manufactured product provided by the entity and a corresponding time frame for occurrence of the change; searching, via a processor, the index of analyzed data by applying information from a request for the root cause of the incident to the index of analyzed data to determine one or more change records from the abbreviated representation listing changes serving as one or more candidate causes for the incident, wherein applying the information includes: correlating the request with the changes listed by the one or more change records based on a time associated with the request being within a specified time interval of the corresponding time frame of occurrence of the changes listed by the one or more change records, and identifying the one or more candidate causes in the one or more change records as causes for the incident based on the correlation. 4. The method of claim 1 , wherein correlating includes computing a correlation score for each change serving as a candidate cause for the incident that indicates a relative likelihood of the occurrence of that change as a cause of the incident. | 0.588926 |
9,547,690 | 2 | 3 | 2. The method of claim 1 , wherein generating the plurality of candidate query rewrites further comprises concatenating the search query with each prior search query of the plurality of search queries. | 2. The method of claim 1 , wherein generating the plurality of candidate query rewrites further comprises concatenating the search query with each prior search query of the plurality of search queries. 3. The method of claim 2 , wherein each prior search query includes a timestamp, and wherein scoring the candidate query rewrites includes weighting candidate rewrites based, in part, on the age of the corresponding prior query. | 0.5 |
8,793,119 | 7 | 9 | 7. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed on the processor, result in the processor performing operations comprising: at each turn in a dialog, nominating via a processor, using a partially observable Markov decision in parallel with a conventional dialog process, a set of allowed dialog actions and a set of contextual features; outputting allowed dialog actions from the conventional dialog process to the partially observable Markov decision process; selecting an optimal action from the set of allowed dialog actions using a machine learning algorithm to yield a selected optimal action; generating a response based on the selected optimal action at each turn in the dialog. | 7. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed on the processor, result in the processor performing operations comprising: at each turn in a dialog, nominating via a processor, using a partially observable Markov decision in parallel with a conventional dialog process, a set of allowed dialog actions and a set of contextual features; outputting allowed dialog actions from the conventional dialog process to the partially observable Markov decision process; selecting an optimal action from the set of allowed dialog actions using a machine learning algorithm to yield a selected optimal action; generating a response based on the selected optimal action at each turn in the dialog. 9. The system of claim 7 , wherein the system is partially observable Markov decision process based. | 0.673203 |
8,041,694 | 88 | 89 | 88. The method of claim 16 , in which each vector in the set of vectors represents a corresponding user in a community, and each feature of each vector represents the corresponding user's click-behavior with regard to a content item. | 88. The method of claim 16 , in which each vector in the set of vectors represents a corresponding user in a community, and each feature of each vector represents the corresponding user's click-behavior with regard to a content item. 89. The method of claim 88 , further comprising identifying a pair of vectors (x, y) as representing a group of colluding users. | 0.5 |
9,910,554 | 17 | 19 | 17. A data processing system, comprising: a processor; a data storage device coupled to the processor; and program code stored within the data storage device that, when executed by the processor, causes the data processing system to perform: extracting first and second interface elements from a first graphical user interface (GUI) associated with a first cultural background, wherein the first and second interface elements are both of a first interface element type; in a rule repository including a plurality of transformation rules each specifying an interface element type and associated action to be taken on user interface elements of the specified interface element type, locating a first transformation rule that specifies the first interface element type and an associated first action; in response to locating the first transformation rule and utilizing the first action specified by the first transformation rule, transforming the first and second interface elements into third and fourth interface elements, respectively, wherein the third and fourth interface elements are associated with a second cultural background; and providing a second GUI including at least the third and fourth interface elements. | 17. A data processing system, comprising: a processor; a data storage device coupled to the processor; and program code stored within the data storage device that, when executed by the processor, causes the data processing system to perform: extracting first and second interface elements from a first graphical user interface (GUI) associated with a first cultural background, wherein the first and second interface elements are both of a first interface element type; in a rule repository including a plurality of transformation rules each specifying an interface element type and associated action to be taken on user interface elements of the specified interface element type, locating a first transformation rule that specifies the first interface element type and an associated first action; in response to locating the first transformation rule and utilizing the first action specified by the first transformation rule, transforming the first and second interface elements into third and fourth interface elements, respectively, wherein the third and fourth interface elements are associated with a second cultural background; and providing a second GUI including at least the third and fourth interface elements. 19. The program product according to claim 17 , wherein the extracting comprises: obtaining metadata of the first and second interface elements by analyzing code that describes the first GUI. | 0.844463 |
7,734,357 | 7 | 9 | 7. The system according to claim 4 , wherein said data editor uses the buffer-stored, updated configuration data to produce an update data record in a graphics data format. | 7. The system according to claim 4 , wherein said data editor uses the buffer-stored, updated configuration data to produce an update data record in a graphics data format. 9. The system according to claim 7 , wherein the configuration data and/or the update data record are stored in a form of shared memory mapped files and can be used jointly with other system components. | 0.5 |
9,792,323 | 9 | 10 | 9. The device of claim 6 , further operations comprising: validating that the second semantics related resource matches the desired first semantics related resource. | 9. The device of claim 6 , further operations comprising: validating that the second semantics related resource matches the desired first semantics related resource. 10. The device of claim 9 , further operations comprising: determining that the second semantics related resource does not match the desired first semantics related resource; and sending a request to the second semantics node for a modification of the received second semantics related resource. | 0.5 |
7,778,944 | 12 | 13 | 12. The machine-readable medium of claim 11 , wherein partitioning of the plurality of linear rules further comprises partitioning each of the plurality of the linear rules into a respective one of the plurality of types of rules. | 12. The machine-readable medium of claim 11 , wherein partitioning of the plurality of linear rules further comprises partitioning each of the plurality of the linear rules into a respective one of the plurality of types of rules. 13. The machine-readable medium of claim 12 , wherein the machine learning comprises assigning weights to the plurality of linear rules based on using a boosting algorithm. | 0.5 |
9,734,839 | 1 | 7 | 1. A voice controlled system comprising: one or more processors; computer-readable media accessible by the one or more processors; a first application and a second application stored on the computer-readable media to be executed by the one or more processors; a microphone to receive audio input; a speech recognition module to identify first data from a signal representing the audio input, the first data including text representing one or more words; and a command router to determine, using second data that is different from the first data, a first application probability of the first application being a recipient of a next command, wherein the second data is available to the command router prior to identification of the first data, determine, using the second data, a second application probability of the second application being a recipient of the next command, provide, to the first application, the text, receive, from the first application, a first matching probability indicating a degree of matching between the one or more words and a command which the first application can interpret, provide, to the second application, the text, receive, from the second application, a second matching probability indicating a degree of matching between the one or more words and a command which the second application can interpret, and select, based at least in part on the first application probability, the second application probability, the first matching probability, and the second matching probability, the first application to receive the command in the one or more words and to perform at least one operation associated with the next command. | 1. A voice controlled system comprising: one or more processors; computer-readable media accessible by the one or more processors; a first application and a second application stored on the computer-readable media to be executed by the one or more processors; a microphone to receive audio input; a speech recognition module to identify first data from a signal representing the audio input, the first data including text representing one or more words; and a command router to determine, using second data that is different from the first data, a first application probability of the first application being a recipient of a next command, wherein the second data is available to the command router prior to identification of the first data, determine, using the second data, a second application probability of the second application being a recipient of the next command, provide, to the first application, the text, receive, from the first application, a first matching probability indicating a degree of matching between the one or more words and a command which the first application can interpret, provide, to the second application, the text, receive, from the second application, a second matching probability indicating a degree of matching between the one or more words and a command which the second application can interpret, and select, based at least in part on the first application probability, the second application probability, the first matching probability, and the second matching probability, the first application to receive the command in the one or more words and to perform at least one operation associated with the next command. 7. The voice controlled system of claim 1 , wherein the first matching probability is determined at least in part by a statistical parser. | 0.806723 |
9,684,735 | 5 | 7 | 5. The method of claim 1 , wherein the plurality of predetermined correspondences are established by: obtaining access information for a plurality of webpages corresponding to a plurality of products under the product category, wherein the access information includes one or more of: total page views, transaction record, and mean browsing time for each of the plurality of products; determining, using one or more processors, an access rank for each of the plurality of webpages based at least in part on the access information for each of the plurality of webpages; extracting a primary font information from the webpage with a highest access rank; and establishing a predetermined correspondence between the product category and the extracted primary font information. | 5. The method of claim 1 , wherein the plurality of predetermined correspondences are established by: obtaining access information for a plurality of webpages corresponding to a plurality of products under the product category, wherein the access information includes one or more of: total page views, transaction record, and mean browsing time for each of the plurality of products; determining, using one or more processors, an access rank for each of the plurality of webpages based at least in part on the access information for each of the plurality of webpages; extracting a primary font information from the webpage with a highest access rank; and establishing a predetermined correspondence between the product category and the extracted primary font information. 7. The method of claim 5 , wherein the access rank of a first product webpage and a second product webpage in the product category is determined based at least in part on a comparison of a first mean browsing time for the first product webpage and a second mean browsing time for the second product webpage. | 0.832971 |
9,141,964 | 47 | 48 | 47. The method of claim 44 , wherein the electronic content item is associated with an entity, and the act of delivering the electronic content item comprises: positioning the electronic content item for display based on a ranking among content items for the concept, the ranking being based at least in part on a price parameter offered by the entity. | 47. The method of claim 44 , wherein the electronic content item is associated with an entity, and the act of delivering the electronic content item comprises: positioning the electronic content item for display based on a ranking among content items for the concept, the ranking being based at least in part on a price parameter offered by the entity. 48. The method of claim 47 , wherein the entity is offered an incentive to provide at least one electronic content item. | 0.589041 |
8,881,116 | 22 | 23 | 22. A device-implemented method, comprising: receiving computer code, the receiving being performed by the device; performing a static verification analysis of the computer code to locate a point, in the computer code, that, under at least one set of states of variables in the computer code, causes an error in an execution of the computer code, the static verification analysis being performed by analyzing a first plurality of possible execution paths of the computer code, the first plurality of possible execution paths being determined based on an over-approximation of states, and the performing being performed by the device; traversing, from the located point and in a backward direction, through a second plurality of possible execution paths, the second plurality of possible execution paths being determined based on an under-approximation of the states that were over-approximated, and the traversing being performed by the device; analyzing the located point using an empiric analysis technique based on semantic information for the computer code, the analyzing the located point being performed by the device; determining, based on the traversing, a second point in the computer code as a potential cause of the error, the determining being performed by the device; classifying, based on the traversing and the analyzing the located point, the second point as a first error classification, when the error is caused by code of the received computer code, or a second error classification, when the error is caused by an input to the computer code, the classifying being performed by the device; and storing information identifying the classification and information that describes the second point in the computer code, the storing being performed by the device. | 22. A device-implemented method, comprising: receiving computer code, the receiving being performed by the device; performing a static verification analysis of the computer code to locate a point, in the computer code, that, under at least one set of states of variables in the computer code, causes an error in an execution of the computer code, the static verification analysis being performed by analyzing a first plurality of possible execution paths of the computer code, the first plurality of possible execution paths being determined based on an over-approximation of states, and the performing being performed by the device; traversing, from the located point and in a backward direction, through a second plurality of possible execution paths, the second plurality of possible execution paths being determined based on an under-approximation of the states that were over-approximated, and the traversing being performed by the device; analyzing the located point using an empiric analysis technique based on semantic information for the computer code, the analyzing the located point being performed by the device; determining, based on the traversing, a second point in the computer code as a potential cause of the error, the determining being performed by the device; classifying, based on the traversing and the analyzing the located point, the second point as a first error classification, when the error is caused by code of the received computer code, or a second error classification, when the error is caused by an input to the computer code, the classifying being performed by the device; and storing information identifying the classification and information that describes the second point in the computer code, the storing being performed by the device. 23. The device-implemented method of claim 22 , where the static verification is performed through an abstract interpretation of variable states in the computer code. | 0.698182 |
6,138,270 | 23 | 26 | 23. The method of claim 15, wherein, for each respective object in said first graphical program, said matching comprises: comparing the respective object in said first graphical program with one or more objects in said second graphical program; determining a score value for a plurality of object pairs in response to said comparing, wherein each of said plurality of object pairs comprises two object elements, said two object elements comprising said respective object in said first graphical program and an object of said one or more objects in said second graphical program, wherein said score value indicates a degree of matching between said object elements comprising said object pair. | 23. The method of claim 15, wherein, for each respective object in said first graphical program, said matching comprises: comparing the respective object in said first graphical program with one or more objects in said second graphical program; determining a score value for a plurality of object pairs in response to said comparing, wherein each of said plurality of object pairs comprises two object elements, said two object elements comprising said respective object in said first graphical program and an object of said one or more objects in said second graphical program, wherein said score value indicates a degree of matching between said object elements comprising said object pair. 26. The method of claim 23, wherein said score value is a weighted score value, wherein said determining said score value for one of said plurality of object pairs includes examining connectivity of object elements comprising said object pair and examining attributes of object elements comprising said object pair; wherein said connectivity of object elements has greater weight than said attributes of said object elements. | 0.590559 |
6,012,027 | 15 | 18 | 15. A computer readable storage medium containing computer readable instructions that when executed by a computer performs the following steps: (a) requesting a user speak a vocabulary word; (b) receiving a first digitized utterance; (c) extracting a plurality of features from the first digitized utterance; (d) determining a signal to noise ratio; (e) when the signal to noise ratio is less than a predetermined signal to noise ratio, returning to step (a); (f) requesting the user speak the vocabulary word; (g) receiving a second digitized utterance of the vocabulary word; (h) extracting the plurality of features from the second digitized utterance; (i) determining a first similarity between the plurality of features from the first digitized utterance and the plurality of features from the second digitized utterance; (j) when the first similarity is less than a predetermined similarity, requesting the user to speak a third utterance of the vocabulary word; (k) extracting the plurality of features from a third digitized utterance; (l) determining a second similarity between the plurality of features from the first digitized utterance and the plurality of features from the third digitized utterance; and (m) when the second similarity is greater than or equal to the predetermined similarity, forming a reference for the vocabulary word. | 15. A computer readable storage medium containing computer readable instructions that when executed by a computer performs the following steps: (a) requesting a user speak a vocabulary word; (b) receiving a first digitized utterance; (c) extracting a plurality of features from the first digitized utterance; (d) determining a signal to noise ratio; (e) when the signal to noise ratio is less than a predetermined signal to noise ratio, returning to step (a); (f) requesting the user speak the vocabulary word; (g) receiving a second digitized utterance of the vocabulary word; (h) extracting the plurality of features from the second digitized utterance; (i) determining a first similarity between the plurality of features from the first digitized utterance and the plurality of features from the second digitized utterance; (j) when the first similarity is less than a predetermined similarity, requesting the user to speak a third utterance of the vocabulary word; (k) extracting the plurality of features from a third digitized utterance; (l) determining a second similarity between the plurality of features from the first digitized utterance and the plurality of features from the third digitized utterance; and (m) when the second similarity is greater than or equal to the predetermined similarity, forming a reference for the vocabulary word. 18. The computer readable storage medium of claim 15, wherein step (e) further includes the steps of: (e1) determining if an amplifier gain is saturated; (e2) when the amplifier gain is saturated, going to step (a). | 0.766811 |
9,836,708 | 11 | 12 | 11. A non-transitory computer-readable storage device storing instructions that, when executed by a computer, cause the computer to perform operations comprising: detecting startup of one or more applications in an analytics engine configured to analyze a set of items based on data models and processing models to dynamically generate graphical user analysis interfaces; populating columns of a plurality of fact tables with first client data, wherein a first portion of the first client data is stored on a first data storage device, and wherein a second portion of the first client data is stored on a second data storage device that is distinct from the first data storage device; populating and storing a table-info table to indicate which columns in each of the plurality of fact tables are populated with the first client data; evaluating a plurality of content measures based on the populated columns of the plurality of fact tables, the table-info table, and at least one of a role or a security access level of a user to determine and store a set of computable content measures that are supported by the first client data; identifying supported items of the set of items based on the stored set of computable content measures; sending data identifying the supported items to the one or more applications, wherein the data excludes unsupported items; receiving an indication that a portion of the first client data has become unavailable; determining that at least one of the supported items relies on the portion of the first client data; sending second data to the one or more applications, wherein display of the second data excludes the at least one of the supported items; receiving, from the one or more applications, a query that requests values spanning both the first portion and the second portion, and responsive to receiving the query, dividing the query into a plurality of data requests, the plurality of data requests including a first request with respect to the first portion and a second request with respect to the second portion. | 11. A non-transitory computer-readable storage device storing instructions that, when executed by a computer, cause the computer to perform operations comprising: detecting startup of one or more applications in an analytics engine configured to analyze a set of items based on data models and processing models to dynamically generate graphical user analysis interfaces; populating columns of a plurality of fact tables with first client data, wherein a first portion of the first client data is stored on a first data storage device, and wherein a second portion of the first client data is stored on a second data storage device that is distinct from the first data storage device; populating and storing a table-info table to indicate which columns in each of the plurality of fact tables are populated with the first client data; evaluating a plurality of content measures based on the populated columns of the plurality of fact tables, the table-info table, and at least one of a role or a security access level of a user to determine and store a set of computable content measures that are supported by the first client data; identifying supported items of the set of items based on the stored set of computable content measures; sending data identifying the supported items to the one or more applications, wherein the data excludes unsupported items; receiving an indication that a portion of the first client data has become unavailable; determining that at least one of the supported items relies on the portion of the first client data; sending second data to the one or more applications, wherein display of the second data excludes the at least one of the supported items; receiving, from the one or more applications, a query that requests values spanning both the first portion and the second portion, and responsive to receiving the query, dividing the query into a plurality of data requests, the plurality of data requests including a first request with respect to the first portion and a second request with respect to the second portion. 12. The non-transitory computer-readable storage device of claim 11 , wherein the operations further comprise sending data identifying the set of computable content measures to the one or more applications. | 0.664495 |
8,166,017 | 37 | 39 | 37. The method of claim 31 , further comprising providing a server-side management tool using a HyperText Markup Language (HTML) interface. | 37. The method of claim 31 , further comprising providing a server-side management tool using a HyperText Markup Language (HTML) interface. 39. The method of claim 37 , wherein the first and second sets of bookmarks are manually synchronized using the server-side management tool. | 0.787234 |
9,767,379 | 1 | 4 | 1. A computer program product, comprising a non-transitory computer readable medium having program instructions embodied therewith, the program instructions executable by a processor to: receive an image of a document captured using a camera of a mobile device; perform optical character recognition (OCR) on the image of the document; extract data of interest from the image based at least in part on the OCR; and validate the extracted data of interest against reference information stored on the mobile device; wherein the validation comprises device-based validation; wherein the device-based validation comprises normalizing the extracted data of interest to match a predetermined format; and wherein the reference information comprises an immutable or substantially immutable identifier of the mobile device. | 1. A computer program product, comprising a non-transitory computer readable medium having program instructions embodied therewith, the program instructions executable by a processor to: receive an image of a document captured using a camera of a mobile device; perform optical character recognition (OCR) on the image of the document; extract data of interest from the image based at least in part on the OCR; and validate the extracted data of interest against reference information stored on the mobile device; wherein the validation comprises device-based validation; wherein the device-based validation comprises normalizing the extracted data of interest to match a predetermined format; and wherein the reference information comprises an immutable or substantially immutable identifier of the mobile device. 4. The computer program product as recited in claim 1 , wherein the program instructions executable by the processor to validate the extracted data of interest further comprise program instructions executable by the processor to perform expectation-based validation. | 0.600601 |
8,275,662 | 1 | 13 | 1. A method for providing geo-targeted messages with a search result, the method comprising: providing a toolbar plug-in for an electronic document for allowing a user to enter a search query term for querying the search query term on at least one Internet search platform; customizing the toolbar plug-in with at least one geographical setting; providing exclusive leasing rights to use a leased term associated with a message, wherein the leased term exclusively corresponds to at least one selected geo-targeted area; saving the leased term; receiving a search query term, via the toolbar plug-in, for performing a search request for the search query term on said search platform(s); displaying the search result for the search query term in a second electronic document; and displaying at least one geo-targeted message corresponding to the leased term in response to the search request in a first electronic document, upon determining that the search query term matches the leased term, wherein the method simultaneously provides for displaying the geo-targeted messages in the first electronic document, and displaying said search result in the second electronic document, wherein the first electronic document and the second electronic document are independent, and wherein providing exclusive leasing rights to use the leased term comprises removing the search query term from the terms available for lease in the at least one selected geo-targeted area. | 1. A method for providing geo-targeted messages with a search result, the method comprising: providing a toolbar plug-in for an electronic document for allowing a user to enter a search query term for querying the search query term on at least one Internet search platform; customizing the toolbar plug-in with at least one geographical setting; providing exclusive leasing rights to use a leased term associated with a message, wherein the leased term exclusively corresponds to at least one selected geo-targeted area; saving the leased term; receiving a search query term, via the toolbar plug-in, for performing a search request for the search query term on said search platform(s); displaying the search result for the search query term in a second electronic document; and displaying at least one geo-targeted message corresponding to the leased term in response to the search request in a first electronic document, upon determining that the search query term matches the leased term, wherein the method simultaneously provides for displaying the geo-targeted messages in the first electronic document, and displaying said search result in the second electronic document, wherein the first electronic document and the second electronic document are independent, and wherein providing exclusive leasing rights to use the leased term comprises removing the search query term from the terms available for lease in the at least one selected geo-targeted area. 13. The method of claim 1 , wherein the geo-targeted message comprises a link. | 0.968007 |
9,064,065 | 5 | 13 | 5. The method of claim 1 , further comprising: defining a port of the first bridge element; associating the port of the first bridge element with an implementable element port of an implementable element of the architectural model and with an implementation element port of an implementation element of the implementation/behavioral model; mapping an interface member of the implementation element port to an interface member of the implementable element port; generating, from a template, skeleton source code applicable for the mapped interface member; generating a usage description element for the architectural model corresponding to the mapped interface member; generating an architectural description document from the architectural model; generating implementation code from the implementation/behavioral model and the generated skeleton source code; and generating a declaration file for an operating system service for use by the implementation code. | 5. The method of claim 1 , further comprising: defining a port of the first bridge element; associating the port of the first bridge element with an implementable element port of an implementable element of the architectural model and with an implementation element port of an implementation element of the implementation/behavioral model; mapping an interface member of the implementation element port to an interface member of the implementable element port; generating, from a template, skeleton source code applicable for the mapped interface member; generating a usage description element for the architectural model corresponding to the mapped interface member; generating an architectural description document from the architectural model; generating implementation code from the implementation/behavioral model and the generated skeleton source code; and generating a declaration file for an operating system service for use by the implementation code. 13. The method of claim 5 wherein the implementable element is an Atomic Software Component of an Automotive Open System Architecture (AUTOSAR) architectural model, and wherein the implementation element is a class of a Uniform Modeling Language (UML)/Systems Modeling Language (SysML) model. | 0.5 |
8,051,080 | 1 | 5 | 1. A method comprising: collecting usage data that indicates how frequently users interact with annotations for entities that are referenced in documents that are presented to the users; based at least in part on the usage data, generating weights for features that are associated with the entities that are referenced in the documents; wherein a particular weight of a particular feature is based at least in part on how frequently users interact with annotations of entities having the particular feature; identifying a set of identified entities within a document; determining a ranking for the identified entities that belong to said set of identified entities based, at least in part, on (a) feature scores for each of the identified entities, wherein the feature scores correspond to features associated with the identified entities, wherein the particular feature is associated with at least one of the identified entities; and (b) weights, including the particular weight, for the features that are associated with the identified entities; based at least in part on the ranking, automatically selecting a subset of the identified entities for annotation, wherein the subset includes fewer than all of the identified entities; automatically generating an annotated version of the document by, for each entity in the subset, adding to the document a control for displaying additional information about the entity, wherein the additional information about the entity and the control associated with the entity were not in the document before the step of automatically generating the annotated version of the document; wherein at least the steps of generating the weights, determining the ranking, automatically selecting the subset, and automatically generating the annotated version are performed by one or more computing devices. | 1. A method comprising: collecting usage data that indicates how frequently users interact with annotations for entities that are referenced in documents that are presented to the users; based at least in part on the usage data, generating weights for features that are associated with the entities that are referenced in the documents; wherein a particular weight of a particular feature is based at least in part on how frequently users interact with annotations of entities having the particular feature; identifying a set of identified entities within a document; determining a ranking for the identified entities that belong to said set of identified entities based, at least in part, on (a) feature scores for each of the identified entities, wherein the feature scores correspond to features associated with the identified entities, wherein the particular feature is associated with at least one of the identified entities; and (b) weights, including the particular weight, for the features that are associated with the identified entities; based at least in part on the ranking, automatically selecting a subset of the identified entities for annotation, wherein the subset includes fewer than all of the identified entities; automatically generating an annotated version of the document by, for each entity in the subset, adding to the document a control for displaying additional information about the entity, wherein the additional information about the entity and the control associated with the entity were not in the document before the step of automatically generating the annotated version of the document; wherein at least the steps of generating the weights, determining the ranking, automatically selecting the subset, and automatically generating the annotated version are performed by one or more computing devices. 5. The method of claim 1 wherein the features that are associated with the entities contained in the documents include one or more context-independent features, and one or more context-dependent features. | 0.869231 |
8,930,389 | 12 | 13 | 12. A computer program product stored in a computer readable memory device, comprising functional descriptive material that, when executed by an information handling system, causes the information handling system to perform actions comprising: searching a first set of one or more unstructured data sources on one or more initial search terms using a search engine; receiving one or more search hits from the searching of the first set of unstructured data sources; retrieving one or more terms from the search hits; extracting one or more entities from the search hits corresponding to the retrieved one or more terms; automatically constructing one or more structured queries using the one or more extracted entities as one or more fields and the corresponding one or more terms as one or more search parameters within the fields; querying one or more structured data sources using the one or more structured queries; receiving one or more query results from the querying; analyzing the one or more query results based on cardinality of the query results, wherein the analyzing further comprises comparing each of the one or more query results to a common terms data store and a generic terms data store, and determining that a selected query result from the one or more query results is a non-common, non-generic term; searching a second set of one or more unstructured data sources using the selected query as a search term using the search engine; and recording the one or more search hits and the one or more extracted entities in a results data store. | 12. A computer program product stored in a computer readable memory device, comprising functional descriptive material that, when executed by an information handling system, causes the information handling system to perform actions comprising: searching a first set of one or more unstructured data sources on one or more initial search terms using a search engine; receiving one or more search hits from the searching of the first set of unstructured data sources; retrieving one or more terms from the search hits; extracting one or more entities from the search hits corresponding to the retrieved one or more terms; automatically constructing one or more structured queries using the one or more extracted entities as one or more fields and the corresponding one or more terms as one or more search parameters within the fields; querying one or more structured data sources using the one or more structured queries; receiving one or more query results from the querying; analyzing the one or more query results based on cardinality of the query results, wherein the analyzing further comprises comparing each of the one or more query results to a common terms data store and a generic terms data store, and determining that a selected query result from the one or more query results is a non-common, non-generic term; searching a second set of one or more unstructured data sources using the selected query as a search term using the search engine; and recording the one or more search hits and the one or more extracted entities in a results data store. 13. The computer program product of claim 12 wherein the actions further comprise: recording one or more search hits that result from performing the searching of the second set of one or more unstructured data sources in the results data store. | 0.850856 |
9,122,318 | 14 | 15 | 14. A predictive text entry system, comprising: an input component controllable to display a set of letters selectable by a user and to display a set of word selections selectable by the user, the input component receiving input by the user; a display component controllable to display one or more letter images or words; a processor operatively coupled to the input component and the display component, and programmed to: control the display component to display a letter or word corresponding to an input by the user on the input component; determine a corpus based on a location of a cursor displayed on the display component; ascertain a set of choices within the determined corpus that are statistically the most likely choices based on a previous input of a letter by the user; control the input component to display the choices within the ascertained set of choices as the set of word selections selectable by the user, wherein the location of the cursor displayed on the display component is a field of a form, wherein the corpus is determined based on a name of the field of the form. | 14. A predictive text entry system, comprising: an input component controllable to display a set of letters selectable by a user and to display a set of word selections selectable by the user, the input component receiving input by the user; a display component controllable to display one or more letter images or words; a processor operatively coupled to the input component and the display component, and programmed to: control the display component to display a letter or word corresponding to an input by the user on the input component; determine a corpus based on a location of a cursor displayed on the display component; ascertain a set of choices within the determined corpus that are statistically the most likely choices based on a previous input of a letter by the user; control the input component to display the choices within the ascertained set of choices as the set of word selections selectable by the user, wherein the location of the cursor displayed on the display component is a field of a form, wherein the corpus is determined based on a name of the field of the form. 15. The predictive text entry system of claim 14 , wherein the display component displays one or more corpuses, and the processor determines the corpus in which to ascertain a set of choices based upon the displayed corpus that is adjacent to the cursor displayed on the display. | 0.5 |
9,141,194 | 12 | 13 | 12. The method of claim 1 , wherein determining the time derivatives of magnetic field strength measured by the magnetometer device along each of the three orthogonal measurement axes comprises: during at least a portion of the time interval W, measuring orthogonal magnetic field components H x , H y , and H z of a magnetic field vector {right arrow over (H)}=[H x , H y , H z ] at consecutive discrete times t i , i=1, . . . , N, wherein N≧2, to obtain samples of the of H x , H y , and H z at the consecutive discrete times t i , i=1, . . . , N; and computing discrete time derivatives of the measured orthogonal magnetic field components H x , H y , and H z from discrete differences between successive samples. | 12. The method of claim 1 , wherein determining the time derivatives of magnetic field strength measured by the magnetometer device along each of the three orthogonal measurement axes comprises: during at least a portion of the time interval W, measuring orthogonal magnetic field components H x , H y , and H z of a magnetic field vector {right arrow over (H)}=[H x , H y , H z ] at consecutive discrete times t i , i=1, . . . , N, wherein N≧2, to obtain samples of the of H x , H y , and H z at the consecutive discrete times t i , i=1, . . . , N; and computing discrete time derivatives of the measured orthogonal magnetic field components H x , H y , and H z from discrete differences between successive samples. 13. The method of claim 12 , wherein each of the one or more sets of pre-determined time derivatives of magnetic field strength comprises a respective triplet of pre-determined sequences of discrete time derivatives of a magnetic field along the three orthogonal measurement axes, and wherein matching the determined time derivatives with the particular set of the one or more sets based on the comparison comprises: determining a closest match between the computed discrete time derivatives and the respective triplet of pre-determined sequences of discrete time derivatives of one of the one or more sets. | 0.5 |
8,239,749 | 18 | 19 | 18. The method of claim 17 , wherein the file further includes a command to retrieve the drawing space on which the procedural language command can be performed. | 18. The method of claim 17 , wherein the file further includes a command to retrieve the drawing space on which the procedural language command can be performed. 19. The method of claim 18 , wherein the drawing space comprises a two-dimensional drawing space. | 0.5 |
9,189,240 | 1 | 7 | 1. A processor comprising: a front end unit including an instruction fetch unit and a decode unit; an execution engine coupled to the front end unit; and a memory unit coupled to the execution engine and including a first cache, wherein the processor is to read a first portion of a plurality of portions of a data word from a first portion of the first cache and read a second portion of the plurality of portions from a second memory, wherein the first portion is to be processed before the second portion, and the second memory is distinct from the first cache based on at least a physical attribute. | 1. A processor comprising: a front end unit including an instruction fetch unit and a decode unit; an execution engine coupled to the front end unit; and a memory unit coupled to the execution engine and including a first cache, wherein the processor is to read a first portion of a plurality of portions of a data word from a first portion of the first cache and read a second portion of the plurality of portions from a second memory, wherein the first portion is to be processed before the second portion, and the second memory is distinct from the first cache based on at least a physical attribute. 7. The processor of claim 1 , wherein the processor is to process the first portion, and upon a determination that the second portion is to be processed, to process the second portion. | 0.55122 |
7,640,498 | 20 | 22 | 20. A client for enabling a document to be remotely displayed, comprising: a memory for storing instructions; a processor for enabling actions, including: providing a request for a document to a server; enabling the server to determine a type of a platform for the client and selectively associating a size ratio between a plurality of font sizes with the determined type of the remote platform by the server, the type of the platform including a type of an operating system and type of a native browser that are employed to display the document, the enabling the server to determine the type of the remote platform comprising enabling the server to determine the type of the operating system and to determine the type of the native browser, and the selective association based on the determined type of the operating system and the determined type of the native browser; receiving the document for display, the received document being locally scaled for display by the operation of the native browser with the size ratio for the plurality of font sizes; and enabling the plurality of font sizes to be changed with at least one control of the native browser operating on the client, a size change to the font sizes being determined by the operation of the native browser, the size ratio between the plurality of font sizes being maintained for a change to a size of at least one font displayed in the document at the remote platform, the at least one control changes the at least one font associated with at least one markup language text element displayed within the document. | 20. A client for enabling a document to be remotely displayed, comprising: a memory for storing instructions; a processor for enabling actions, including: providing a request for a document to a server; enabling the server to determine a type of a platform for the client and selectively associating a size ratio between a plurality of font sizes with the determined type of the remote platform by the server, the type of the platform including a type of an operating system and type of a native browser that are employed to display the document, the enabling the server to determine the type of the remote platform comprising enabling the server to determine the type of the operating system and to determine the type of the native browser, and the selective association based on the determined type of the operating system and the determined type of the native browser; receiving the document for display, the received document being locally scaled for display by the operation of the native browser with the size ratio for the plurality of font sizes; and enabling the plurality of font sizes to be changed with at least one control of the native browser operating on the client, a size change to the font sizes being determined by the operation of the native browser, the size ratio between the plurality of font sizes being maintained for a change to a size of at least one font displayed in the document at the remote platform, the at least one control changes the at least one font associated with at least one markup language text element displayed within the document. 22. The client of claim 20 , wherein the actions further comprise enabling a determination of a font color for the plurality of fonts, wherein the font color is provided with the document to the platform. | 0.695522 |
7,761,436 | 13 | 14 | 13. The method according to claim 12 , further comprising receiving a selection for a communication type for the communication from a set of communication types. | 13. The method according to claim 12 , further comprising receiving a selection for a communication type for the communication from a set of communication types. 14. The method according to claim 13 , wherein the set of communication types includes e-mail, text messaging, and/or telephonic messaging. | 0.5 |
9,071,571 | 7 | 10 | 7. A system configurable to communicate with a mobile device, the system comprising: a memory; and a processor coupled to the memory, wherein the processor performs: receiving, by an interface application, a first text message in a text messaging format from a mobile device to access a website that stores information in a markup language format, wherein the information includes both static content and dynamic content, wherein the mobile device is not configurable to support a browser that is configurable to interact with the website in the markup language format, wherein the interface application comprises a parser, an input field extractor, and an input field converter for the information stored in the markup language format, wherein the parser parses tokens stored in a markup language deck to generate a data structure of the tokens and relationships among the tokens, wherein the input field extractor determines which of the tokens are inputs fields in the markup language format, and wherein the input field converter converts the input fields in the markup language format to input fields in the text messaging format; sending the static content of the stored information to the mobile device; parsing and converting one or more elements of the dynamic content of the stored information from the markup language format into corresponding static content that is usable via the text messaging format from the mobile device, wherein the dynamic content includes a drop down menu interface with a first plurality of selections and a radio button user interface with a second plurality of selections, and wherein the first and the second plurality of selections are parsed and converted into a plurality of numbers in the text messaging format; and sending to the mobile device, the corresponding static content in a second text message that indicates how to interact with the website in the text messaging format, wherein: the text messaging format is Short Message Service (SMS); and the markup language is Wireless Markup Language (WML) format, wherein the information is stored via a WML deck comprising a plurality of WML cards, wherein a first WML card is for input of login and password information via the browser, and wherein a second WML card is for providing a plurality of selectable options to the browser. | 7. A system configurable to communicate with a mobile device, the system comprising: a memory; and a processor coupled to the memory, wherein the processor performs: receiving, by an interface application, a first text message in a text messaging format from a mobile device to access a website that stores information in a markup language format, wherein the information includes both static content and dynamic content, wherein the mobile device is not configurable to support a browser that is configurable to interact with the website in the markup language format, wherein the interface application comprises a parser, an input field extractor, and an input field converter for the information stored in the markup language format, wherein the parser parses tokens stored in a markup language deck to generate a data structure of the tokens and relationships among the tokens, wherein the input field extractor determines which of the tokens are inputs fields in the markup language format, and wherein the input field converter converts the input fields in the markup language format to input fields in the text messaging format; sending the static content of the stored information to the mobile device; parsing and converting one or more elements of the dynamic content of the stored information from the markup language format into corresponding static content that is usable via the text messaging format from the mobile device, wherein the dynamic content includes a drop down menu interface with a first plurality of selections and a radio button user interface with a second plurality of selections, and wherein the first and the second plurality of selections are parsed and converted into a plurality of numbers in the text messaging format; and sending to the mobile device, the corresponding static content in a second text message that indicates how to interact with the website in the text messaging format, wherein: the text messaging format is Short Message Service (SMS); and the markup language is Wireless Markup Language (WML) format, wherein the information is stored via a WML deck comprising a plurality of WML cards, wherein a first WML card is for input of login and password information via the browser, and wherein a second WML card is for providing a plurality of selectable options to the browser. 10. The system of claim 7 , wherein at least a processing power, a storage capacity and a bandwidth of the mobile device precludes a browser from being used in the mobile device to access the information stored in the markup language format. | 0.673442 |
9,727,629 | 10 | 12 | 10. The system of claim 9 , wherein the at least one hardware processor also automatically identifies classification rules for classifying objects. | 10. The system of claim 9 , wherein the at least one hardware processor also automatically identifies classification rules for classifying objects. 12. The system of claim 10 , wherein the at least one hardware processor also removes an object from an in-memory, non-relational store when it has been expired or based on total hits on the object during a predefined period and an amount of time since the object was last requested. | 0.5 |
10,162,883 | 1 | 3 | 1. A method for automatically linking text to concepts in a knowledge base using a differential analysis, the method comprising: receiving, at a computer system, a plurality of text strings; building a conceptual index that links the text strings to the knowledge base, the building comprising for each of the text strings: selecting a plurality of data sources that correspond to at least a subset of the concepts in the knowledge base, the selecting based on contents of the text string; calculating, for each of the selected data sources, a probability that the text string is output by a language model built using the selected data source; calculating a probability that the text string is output by a generic language model that is not related to any particular concept in the knowledge base; calculating link confidence scores for each of the at least a subset of the concepts based on a differential analysis of the probabilities; and creating an entry in the conceptual index that includes a link between the text string and one of the concepts in the knowledge base, the creating based at least in part on a link confidence score of the concept being more than a first threshold value away from a prescribed threshold; generating a conceptual inverted index based on entries in the conceptual index, each entry of the conceptual inverted index corresponding to a different one of the concepts in the knowledge base and comprising pointers to at least a subset of text strings of the plurality of text strings linked to the concept in the conceptual index; receiving a query from an agent external to the computer system, the query specifying a concept in the knowledge base; processing the query by the computer system, the processing comprising searching the conceptual inverted index for the concept specified in the query and returning a pointer to a text string in an entry of the conceptual inverted index corresponding to the concept; and returning a set of documents to the external agent through the use of the conceptual inverted index, based on the received query. | 1. A method for automatically linking text to concepts in a knowledge base using a differential analysis, the method comprising: receiving, at a computer system, a plurality of text strings; building a conceptual index that links the text strings to the knowledge base, the building comprising for each of the text strings: selecting a plurality of data sources that correspond to at least a subset of the concepts in the knowledge base, the selecting based on contents of the text string; calculating, for each of the selected data sources, a probability that the text string is output by a language model built using the selected data source; calculating a probability that the text string is output by a generic language model that is not related to any particular concept in the knowledge base; calculating link confidence scores for each of the at least a subset of the concepts based on a differential analysis of the probabilities; and creating an entry in the conceptual index that includes a link between the text string and one of the concepts in the knowledge base, the creating based at least in part on a link confidence score of the concept being more than a first threshold value away from a prescribed threshold; generating a conceptual inverted index based on entries in the conceptual index, each entry of the conceptual inverted index corresponding to a different one of the concepts in the knowledge base and comprising pointers to at least a subset of text strings of the plurality of text strings linked to the concept in the conceptual index; receiving a query from an agent external to the computer system, the query specifying a concept in the knowledge base; processing the query by the computer system, the processing comprising searching the conceptual inverted index for the concept specified in the query and returning a pointer to a text string in an entry of the conceptual inverted index corresponding to the concept; and returning a set of documents to the external agent through the use of the conceptual inverted index, based on the received query. 3. The method of claim 1 , wherein the differential analysis compares the probability that the text string is output by a language model built using a data source to a probability that the text string is output by a language model built using a competing data source. | 0.601493 |
8,175,865 | 2 | 3 | 2. The method of text script generation for a corpus-based text-to-speech system according to claim 1 , wherein said searching from said step (a) up to said step (c) is further characterized by a method of scalable multi-stage search. | 2. The method of text script generation for a corpus-based text-to-speech system according to claim 1 , wherein said searching from said step (a) up to said step (c) is further characterized by a method of scalable multi-stage search. 3. The method of text script generation for a corpus-based text-to-speech system according to claim 2 , wherein said multi-stage search method allows the fewer core unit types are selected first, and the larger amount of variant unit types are searched in a latter stage. | 0.5 |
8,014,634 | 22 | 28 | 22. A computer-implemented method comprising: storing a first graphical document; comparing graphical content of the first graphical document to graphical content of a second graphical document by a processor; flagging the first graphical document based on the comparison; providing the flagged first graphical document to one or more evaluator terminals for rating information; and approving or disapproving the flagged first graphical document based on the rating information received from the one or more evaluator terminals by the processor. | 22. A computer-implemented method comprising: storing a first graphical document; comparing graphical content of the first graphical document to graphical content of a second graphical document by a processor; flagging the first graphical document based on the comparison; providing the flagged first graphical document to one or more evaluator terminals for rating information; and approving or disapproving the flagged first graphical document based on the rating information received from the one or more evaluator terminals by the processor. 28. The method of claim 22 , further comprising: associating the first graphical document with one or more keywords or concepts; and delivering the first graphical document, after approval, to a requestor requesting a document associated with the one or more keywords or concepts. | 0.575758 |
10,026,506 | 7 | 20 | 7. A server device comprising: a transceiver configured to receive one or more messages from a location tracking device, the one or more messages from the location tracking device including location information and identification information, the transceiver further configured to receive one or more messages from a client device, the one or messages from the client device including a pick-up request, the pick-up request including a pick-up location and a drop-off location; a controller operatively coupled to the transceiver; and one or more memory sources operatively coupled to the controller, the one or more memory sources configuring the controller to: store data indicative of the identification information and location information of the location tracking device within the one or more memory sources; send the pick-up request to the location tracking device if determined that the location tracking device is within a predetermined distance from the pick-up location; and determining an output value associated with the pick-up request based upon a trained model. | 7. A server device comprising: a transceiver configured to receive one or more messages from a location tracking device, the one or more messages from the location tracking device including location information and identification information, the transceiver further configured to receive one or more messages from a client device, the one or messages from the client device including a pick-up request, the pick-up request including a pick-up location and a drop-off location; a controller operatively coupled to the transceiver; and one or more memory sources operatively coupled to the controller, the one or more memory sources configuring the controller to: store data indicative of the identification information and location information of the location tracking device within the one or more memory sources; send the pick-up request to the location tracking device if determined that the location tracking device is within a predetermined distance from the pick-up location; and determining an output value associated with the pick-up request based upon a trained model. 20. The server device of claim 7 , wherein: the transceiver receives a plurality of present events, each including a plurality of input attributes; the server is further configured to generate a graphical image including clusters of the input attributes for each of the plurality of present events; the server receives a graphical display request from a remote client device and transmits the graphical image to the remote client device as a response; the trained model is a trained SOM; and the graphical image is a cluster diagram including a plurality of clusters of present events having a similar characteristic. | 0.625607 |
8,762,867 | 17 | 18 | 17. A computer program product having a non-transitory computer-readable storage medium storing computer-executable code for displaying reports, the code comprising: an input/output driver module configured to: display a chart representation of a report on a display of a device, the report including data associated with a first value of a first category type and a second value of a second category type; display a first plurality of values of the first category type adjacent to a first side of the chart representation, the first plurality of values displayed textually; display a second plurality of values of the second category type adjacent to a second side of the chart representation, the second plurality of category values displayed graphically as magnitudes; and responsive to a user input, change the display to present the first plurality of values of the first category type graphically as magnitudes and present the second plurality of values of the second category type textually. | 17. A computer program product having a non-transitory computer-readable storage medium storing computer-executable code for displaying reports, the code comprising: an input/output driver module configured to: display a chart representation of a report on a display of a device, the report including data associated with a first value of a first category type and a second value of a second category type; display a first plurality of values of the first category type adjacent to a first side of the chart representation, the first plurality of values displayed textually; display a second plurality of values of the second category type adjacent to a second side of the chart representation, the second plurality of category values displayed graphically as magnitudes; and responsive to a user input, change the display to present the first plurality of values of the first category type graphically as magnitudes and present the second plurality of values of the second category type textually. 18. The computer program product of claim 17 , wherein changing the display responsive to the user input comprises: presenting the second plurality of values in a textual representation adjacent to the first side of the chart representation; and presenting the first plurality of values in a graphical representation of magnitudes, adjacent to the second side of the chart representation. | 0.769048 |
8,126,984 | 10 | 11 | 10. The method of claim 9 , wherein adapting the user interface comprises selecting a sensory communication path for interaction of the user with the enterprise service that is suited to a context described by the context information. | 10. The method of claim 9 , wherein adapting the user interface comprises selecting a sensory communication path for interaction of the user with the enterprise service that is suited to a context described by the context information. 11. The method of claim 10 wherein the sensory communication path selected comprises at least one of a voice communication path, a text communication path, and a graphical communication path. | 0.5 |
8,688,728 | 1 | 6 | 1. A search method comprising: creating a list of candidate probe words; for each candidate probe word, counting a number of item descriptions that contain the candidate probe word; choosing, with a computer, q i probe words from the candidate probe words whose word count is closest to |D i |/(q i +1), where D i is a set of remaining item descriptions after a previous repetition, and q i represents a number of probe words presented for user selection for the ith repetition and is an integer greater than 1; presenting the q i probe words for selection by the user; receiving a selection of one of the q i probe words by the user; pruning the list of candidate probe words to eliminate item descriptions that include non-selected ones of the q i probe words to create a pruned list of candidate probe words; choosing q i+1 probe words from the pruned list of candidate probe words that is closest to |D i+1 |/(q i+1 +1), wherein D i+1 is a set of remaining item descriptions after the ith repetition, q i+1 represents a number of probe words presented for user selection for the i+1 repetition and is an integer greater than 1, and the pruned list of candidate probe words includes the selected one of the q i probe words; and presenting the q i+1 probe words for selection by the user. | 1. A search method comprising: creating a list of candidate probe words; for each candidate probe word, counting a number of item descriptions that contain the candidate probe word; choosing, with a computer, q i probe words from the candidate probe words whose word count is closest to |D i |/(q i +1), where D i is a set of remaining item descriptions after a previous repetition, and q i represents a number of probe words presented for user selection for the ith repetition and is an integer greater than 1; presenting the q i probe words for selection by the user; receiving a selection of one of the q i probe words by the user; pruning the list of candidate probe words to eliminate item descriptions that include non-selected ones of the q i probe words to create a pruned list of candidate probe words; choosing q i+1 probe words from the pruned list of candidate probe words that is closest to |D i+1 |/(q i+1 +1), wherein D i+1 is a set of remaining item descriptions after the ith repetition, q i+1 represents a number of probe words presented for user selection for the i+1 repetition and is an integer greater than 1, and the pruned list of candidate probe words includes the selected one of the q i probe words; and presenting the q i+1 probe words for selection by the user. 6. The method recited in claim 1 , wherein creating the list of candidate probe words further includes eliminating any noise words from the list of candidate probe words and normalizing the list of candidate probe words. | 0.601449 |
7,676,457 | 9 | 14 | 9. An article of manufacture, comprising a computer-readable storage medium including data that, when accessed by a computer, cause the computer to perform a method comprising: receiving a query for a lightweight directory access protocol (LDAP) repository; reorganizing search terms in the query based on a uniqueness value of corresponding LDAP indexes to generate a modified query, wherein the uniqueness value of each LDAP index is based on a ratio of targets to keys in the corresponding LDAP index; executing the modified query; generating a candidate list of entries based on the search terms; and detecting a threshold number of entries in the candidate list. | 9. An article of manufacture, comprising a computer-readable storage medium including data that, when accessed by a computer, cause the computer to perform a method comprising: receiving a query for a lightweight directory access protocol (LDAP) repository; reorganizing search terms in the query based on a uniqueness value of corresponding LDAP indexes to generate a modified query, wherein the uniqueness value of each LDAP index is based on a ratio of targets to keys in the corresponding LDAP index; executing the modified query; generating a candidate list of entries based on the search terms; and detecting a threshold number of entries in the candidate list. 14. The article of manufacture of claim 9 , further comprising: counting a number of targets in an index; and dividing the number of targets by a number of keys in the index to generate a uniqueness value for the index. | 0.5 |
8,762,153 | 16 | 17 | 16. The computer-readable storage device of claim 15 , wherein identifying of the first meta-data and the second meta-data comprises identifying multiple pieces of the unique information when necessary to completely disambiguate the matches. | 16. The computer-readable storage device of claim 15 , wherein identifying of the first meta-data and the second meta-data comprises identifying multiple pieces of the unique information when necessary to completely disambiguate the matches. 17. The computer-readable storage device of claim 16 , wherein a hierarchy establishes priority of multiple pieces of the unique information for use in the spoken disambiguation statement. | 0.5 |
4,460,975 | 45 | 47 | 45. The process of claim 24 wherein the user selects to print out according to commands already stored and wherein the second prompting stimulus indicating that a choice of source of the commands to be printed out is to be made, the second prompting stimulus is presented in combination with a menu of command choices including from workspace and from file. | 45. The process of claim 24 wherein the user selects to print out according to commands already stored and wherein the second prompting stimulus indicating that a choice of source of the commands to be printed out is to be made, the second prompting stimulus is presented in combination with a menu of command choices including from workspace and from file. 47. The process of claim 45 wherein the user selects to print out commands stored in the files and further comprising third, fourth, fifth and sixth stimuli indicating that a choice is to be made of file name designating the commands to print out that a choice is to be made of frequency of data to be printed out, that a choice is to be made of interval of data to be printed out, and that a choice is to be made of run title. | 0.5 |
9,081,626 | 19 | 21 | 19. A non-transitory computer readable medium comprising instructions, when executed by a processor, causes the processor to implement a method, the method comprising: translating source code written in a first assembly language to be implemented by a first microcontroller into source code written in an pseudo assembly language; wherein the translating comprises converting a set of sequential instructions of the source code written in the first assembly language to a set of sequential instructions, respectively, written in the pseudo assembly language; converting the source code written in the pseudo assembly language into source code written in a second assembly language for implementation by a non-PIC microcontroller; wherein the converting the source code written in the pseudo assembly language further comprises; identifying a first source code segment written in the pseudo assembly language that includes a conditional statement for checking a status of a bit in a register of the PIC microcontroller; generating a first source code segment written in the second assembly language that implements an interrupt service routine for the non-PIC microcontroller in response to the identifying. | 19. A non-transitory computer readable medium comprising instructions, when executed by a processor, causes the processor to implement a method, the method comprising: translating source code written in a first assembly language to be implemented by a first microcontroller into source code written in an pseudo assembly language; wherein the translating comprises converting a set of sequential instructions of the source code written in the first assembly language to a set of sequential instructions, respectively, written in the pseudo assembly language; converting the source code written in the pseudo assembly language into source code written in a second assembly language for implementation by a non-PIC microcontroller; wherein the converting the source code written in the pseudo assembly language further comprises; identifying a first source code segment written in the pseudo assembly language that includes a conditional statement for checking a status of a bit in a register of the PIC microcontroller; generating a first source code segment written in the second assembly language that implements an interrupt service routine for the non-PIC microcontroller in response to the identifying. 21. The non-transitory computer readable medium of claim 19 , wherein the converting further comprises: applying contextual recognition and reconstruction to the source code written in the pseudo assembly language to generate the source code written in the second assembly language; wherein the contextual recognition and reconstruction further comprises determining an objective of a segment of the source code written in the pseudo language; generating a segment of source code written in the second assembly language that achieves the determined objective of the segment of the source code written in the pseudo assembly language. | 0.5 |
8,510,118 | 2 | 3 | 2. The computer implemented method of claim 1 further comprising: determining whether the script should be immediately run or run at a later time; responsive to determining that the script should be run immediately, determining whether the script is to be sent to another user; responsive to determining the script is to be sent to another user, forwarding the script to another user to make changes to the document as indicated in the script commands; responsive to determining the script is not to be sent to another user, saving the script for later review or execution; and receiving an indication that a change should be made to a document identified by the document identifier. | 2. The computer implemented method of claim 1 further comprising: determining whether the script should be immediately run or run at a later time; responsive to determining that the script should be run immediately, determining whether the script is to be sent to another user; responsive to determining the script is to be sent to another user, forwarding the script to another user to make changes to the document as indicated in the script commands; responsive to determining the script is not to be sent to another user, saving the script for later review or execution; and receiving an indication that a change should be made to a document identified by the document identifier. 3. The computer implemented method of claim 2 , wherein the indication is selected from the group consisting of an alphanumeric text based indication and an audio indication. | 0.5 |
4,839,853 | 1 | 2 | 1. An information retrieval method comprising the steps of generating term-by-data object matrix data to represent information files stored in a computer system, said matrix data being indicative of the frequency of occurrence of selected terms contained in the data objects stored in the information files, decomposing said matrix into a reduced singular value representation composed of distinct term and data object files, in response to a user query, generating a pseudo-object utilizing said selected terms and inserting said pseudo-object into said matrix data, and examining the similarity between said pseudo-object and said term and data object files to generate an information response and storing said response in the system in a form accessible by the user. | 1. An information retrieval method comprising the steps of generating term-by-data object matrix data to represent information files stored in a computer system, said matrix data being indicative of the frequency of occurrence of selected terms contained in the data objects stored in the information files, decomposing said matrix into a reduced singular value representation composed of distinct term and data object files, in response to a user query, generating a pseudo-object utilizing said selected terms and inserting said pseudo-object into said matrix data, and examining the similarity between said pseudo-object and said term and data object files to generate an information response and storing said response in the system in a form accessible by the user. 2. The method as recited in claim 1 wherein said step of generating said matrix data includes the step of producing a lexicon database defining said selected terms. | 0.89295 |
7,765,102 | 1 | 10 | 1. A method for creating a mnemonic pronunciation of a character for computer-recognition of the character, the method comprising: using a processing device, selecting the character to be recognized; using the processing device, selecting a word that begins with the character; and using the processing device, constructing a mnemonic pronunciation representing the character including a pronunciation representing the character, a pronunciation representing a term meaning “as in”, and a pronunciation of the word. | 1. A method for creating a mnemonic pronunciation of a character for computer-recognition of the character, the method comprising: using a processing device, selecting the character to be recognized; using the processing device, selecting a word that begins with the character; and using the processing device, constructing a mnemonic pronunciation representing the character including a pronunciation representing the character, a pronunciation representing a term meaning “as in”, and a pronunciation of the word. 10. The method of claim 1 , wherein the word based on at least one of Chinese, Russian, Spanish or French language. | 0.745575 |
8,926,672 | 20 | 21 | 20. In a spinal fixation structure having a bone anchor and a closure, the anchor for holding a spinal fixation longitudinal connecting member, the anchor having an open receiver with spaced apart arms defining a longitudinal connecting member receiving channel therebetween and the closure sized for being received within the channel and adapted for rotation and advancement into the channel between the arms to capture a portion of the longitudinal connecting member in the channel, the improvement comprising: a) a closure guide and advancement flange form extending helically along the closure and about a central axis of the closure, the flange form having a pitch of between 0.045 and 0.055 inches, and having a crest portion with a first axial height and a root portion having a second axial height, the first height measured from a top of an upwardly extending toe of the flange form to a stab flank and taken substantially along a crest surface of the flange form, the second height measured from a load flank of the flange form to the stab flank and taken substantially along a root surface of the flange form, the first height being one of slightly less and substantially equal to the second height, the flange form having a splay control ramp surface located between the toe and the load flank running substantially at an oblique angle with respect to a radius of the closure running perpendicular to the closure axis; and b) a discontinuous receiver guide and advancement flange form extending helically about and along an inner surface of each receiver arm, the receiver flang form having a cooperating splay control ramp engaging the closure flange form control ramp during mating of the closure flange form with the receiver flange form, the receiver flange form having a clearance surfaces disposed in close spaced relation to the closure toe, the toe remaining unloaded during mating engagement and torquing of the closure flange form with the receiver flange form. | 20. In a spinal fixation structure having a bone anchor and a closure, the anchor for holding a spinal fixation longitudinal connecting member, the anchor having an open receiver with spaced apart arms defining a longitudinal connecting member receiving channel therebetween and the closure sized for being received within the channel and adapted for rotation and advancement into the channel between the arms to capture a portion of the longitudinal connecting member in the channel, the improvement comprising: a) a closure guide and advancement flange form extending helically along the closure and about a central axis of the closure, the flange form having a pitch of between 0.045 and 0.055 inches, and having a crest portion with a first axial height and a root portion having a second axial height, the first height measured from a top of an upwardly extending toe of the flange form to a stab flank and taken substantially along a crest surface of the flange form, the second height measured from a load flank of the flange form to the stab flank and taken substantially along a root surface of the flange form, the first height being one of slightly less and substantially equal to the second height, the flange form having a splay control ramp surface located between the toe and the load flank running substantially at an oblique angle with respect to a radius of the closure running perpendicular to the closure axis; and b) a discontinuous receiver guide and advancement flange form extending helically about and along an inner surface of each receiver arm, the receiver flang form having a cooperating splay control ramp engaging the closure flange form control ramp during mating of the closure flange form with the receiver flange form, the receiver flange form having a clearance surfaces disposed in close spaced relation to the closure toe, the toe remaining unloaded during mating engagement and torquing of the closure flange form with the receiver flange form. 21. The improvement of claim 20 wherein the closure splay control ramp has a frusto-conical surface portion. | 0.605839 |
8,091,023 | 12 | 14 | 12. A handheld electronic device structured to identify a proposed spelling correction for a word that has been determined to at least potentially be misspelled, the handheld electronic device comprising: a processor apparatus comprising a processor and a memory and having available thereto a data source comprising a plurality of words; an input apparatus structured to provide input to the processor apparatus, the input apparatus comprising a plurality of input member, at least some of the input members each having a plurality of characters assigned thereto; an output apparatus structured to receive output signals from the processor apparatus; the memory having stored therein a number of routines which, when executed on the processor, cause the handheld electronic device to perform operations comprising: receiving from a data source a series of characters of a candidate spelling correction; making a determination for each character of at least a portion of the series that at least one of: the character validly corresponds with a predetermined portion of a canonical version of the word, and the character is, according to at least one spell check algorithm from among a number of spell check algorithms, within a predetermined edit distance from a predetermined portion of the canonical version of the word; determining for one character of the series that the character is, according to the at least one spell check algorithm, within an edit distance of one from a predetermined portion of the canonical version of the word; and outputting at least a portion of the candidate spelling correction as a proposed spelling correction. | 12. A handheld electronic device structured to identify a proposed spelling correction for a word that has been determined to at least potentially be misspelled, the handheld electronic device comprising: a processor apparatus comprising a processor and a memory and having available thereto a data source comprising a plurality of words; an input apparatus structured to provide input to the processor apparatus, the input apparatus comprising a plurality of input member, at least some of the input members each having a plurality of characters assigned thereto; an output apparatus structured to receive output signals from the processor apparatus; the memory having stored therein a number of routines which, when executed on the processor, cause the handheld electronic device to perform operations comprising: receiving from a data source a series of characters of a candidate spelling correction; making a determination for each character of at least a portion of the series that at least one of: the character validly corresponds with a predetermined portion of a canonical version of the word, and the character is, according to at least one spell check algorithm from among a number of spell check algorithms, within a predetermined edit distance from a predetermined portion of the canonical version of the word; determining for one character of the series that the character is, according to the at least one spell check algorithm, within an edit distance of one from a predetermined portion of the canonical version of the word; and outputting at least a portion of the candidate spelling correction as a proposed spelling correction. 14. The handheld electronic device of claim 12 wherein the predetermined edit distance is an edit distance of one. | 0.92963 |
6,029,002 | 13 | 14 | 13. The method of claim 10 further comprising the steps of: selecting a direction to traverse said sliced set of IL statements; and performing a forward analysis of said sliced set of IL statements when the direction is forward and performing a backward analysis when the direction is backward. | 13. The method of claim 10 further comprising the steps of: selecting a direction to traverse said sliced set of IL statements; and performing a forward analysis of said sliced set of IL statements when the direction is forward and performing a backward analysis when the direction is backward. 14. The method of claim 13 wherein said backward analysis comprises the step of substituting a select IL statement with a skip statement when said select IL statement is an alternation statement and fails to assign a new value to a variable contained in an associated postcondition. | 0.5 |
6,088,699 | 23 | 24 | 23. The device of claim 22, where each dictionary includes multiple sub-dictionaries each sub-dictionary exclusively containing dictionary index codes of a different type of data object. | 23. The device of claim 22, where each dictionary includes multiple sub-dictionaries each sub-dictionary exclusively containing dictionary index codes of a different type of data object. 24. The device of claim 23, the flags further including one or more sub-dictionary identifiers identifying sub-dictionaries containing the dictionary index codes in the composed message. | 0.5 |
6,018,749 | 1 | 4 | 1. A method of generating a new document from a source text document and a source image document, comprising the steps of: (1) accessing said source text document and said source image document; (2) at least partially paginating said source text document with said source image document to produce at least partial pagination information; and (3) generating said new document using said at least partial pagination information, wherein said new document is an equivalent text file comprising one or more of (A)-(M): (A) information representing an approximate arrangement of at least some bibliographic data as represented in said source image document, (B) information that effectively provides an association between at least a portion of said source text document and at least a portion of said source image document, (C) special character information specifying at least one mapping of a group of characters in said source text document to at least one special character in said source image document, (D) column information representing at least an approximate arrangement of text in columns, (E) line information representing at least an approximate arrangement of text in lines, (F) line number information representing approximate line numbers of lines, (G) section information representing at least approximate positions of sections, (H) font information representing font styles of characters, (I) font size information representing font sizes of characters, (J) superscript information indicating characters that are represented using superscripts, (K) subscript information indicating characters that are represented using subscripts, (L) bold attribute information indicating characters that are bolded, and (M) italicized attribute information indicating characters that are italicized. | 1. A method of generating a new document from a source text document and a source image document, comprising the steps of: (1) accessing said source text document and said source image document; (2) at least partially paginating said source text document with said source image document to produce at least partial pagination information; and (3) generating said new document using said at least partial pagination information, wherein said new document is an equivalent text file comprising one or more of (A)-(M): (A) information representing an approximate arrangement of at least some bibliographic data as represented in said source image document, (B) information that effectively provides an association between at least a portion of said source text document and at least a portion of said source image document, (C) special character information specifying at least one mapping of a group of characters in said source text document to at least one special character in said source image document, (D) column information representing at least an approximate arrangement of text in columns, (E) line information representing at least an approximate arrangement of text in lines, (F) line number information representing approximate line numbers of lines, (G) section information representing at least approximate positions of sections, (H) font information representing font styles of characters, (I) font size information representing font sizes of characters, (J) superscript information indicating characters that are represented using superscripts, (K) subscript information indicating characters that are represented using subscripts, (L) bold attribute information indicating characters that are bolded, and (M) italicized attribute information indicating characters that are italicized. 4. The method of claim 1, wherein step (2) is performed at a user-specified synchronization level. | 0.9326 |
8,688,450 | 8 | 10 | 8. 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 audio data encoding an utterance, and data specifying a time when the utterance was spoken; determining, for each of multiple communications that were initiated by a user of a mobile device, a time when the communication was initiated or received; determining, for each of the multiple communications, a similarity score based on a similarity between the time when the communication was initiated or received, and the time when the utterance was spoken; determining, for each of multiple contacts associated with the user, a probability associated with the contact based at least on the similarity score for the communications that were initiated or received; weighting a contact disambiguation grammar according to the probabilities; and processing the audio data using the contact disambiguation grammar to select a particular contact. | 8. 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 audio data encoding an utterance, and data specifying a time when the utterance was spoken; determining, for each of multiple communications that were initiated by a user of a mobile device, a time when the communication was initiated or received; determining, for each of the multiple communications, a similarity score based on a similarity between the time when the communication was initiated or received, and the time when the utterance was spoken; determining, for each of multiple contacts associated with the user, a probability associated with the contact based at least on the similarity score for the communications that were initiated or received; weighting a contact disambiguation grammar according to the probabilities; and processing the audio data using the contact disambiguation grammar to select a particular contact. 10. The system of claim 8 , wherein the operations comprise: receiving data specifying a location of the mobile device when the utterance was spoken; determining, for each of the multiple communications that were initiated by the user of the mobile device, a location of the mobile device when the communication was initiated or received; and wherein the respective similarity score is determined further based on a similarity between the location of the mobile device when the communication was initiated or received, and the location of the mobile device when the utterance was spoken. | 0.570906 |
9,058,360 | 1 | 5 | 1. A method comprising: receiving, by a computer system, a query expressed in an event processing language, the query including a reference to a complex type implemented in another language distinct from the event processing language; and compiling, by the computer system, the query by: retrieving metadata pertaining to the complex type from information stored in a data cartridge for the complex type without requiring definition of a function interface for the complex type using data types that are defined in the event processing language; and generating, based on the metadata, executable instructions for executing the query; wherein the reference to the complex type within the query specifies both (a) a class identifier of a class written in said language distinct from the event processing language and (b) a method identifier of a particular method of the class; wherein the class written in said language distinct from the event processing language includes a plurality of methods that are invocable as complex types referenced in queries expressed in the event processing language; and wherein the particular method is one of the plurality of methods. | 1. A method comprising: receiving, by a computer system, a query expressed in an event processing language, the query including a reference to a complex type implemented in another language distinct from the event processing language; and compiling, by the computer system, the query by: retrieving metadata pertaining to the complex type from information stored in a data cartridge for the complex type without requiring definition of a function interface for the complex type using data types that are defined in the event processing language; and generating, based on the metadata, executable instructions for executing the query; wherein the reference to the complex type within the query specifies both (a) a class identifier of a class written in said language distinct from the event processing language and (b) a method identifier of a particular method of the class; wherein the class written in said language distinct from the event processing language includes a plurality of methods that are invocable as complex types referenced in queries expressed in the event processing language; and wherein the particular method is one of the plurality of methods. 5. The method of claim 1 , wherein: the query is configured for processing one or more events received via one or more event streams. | 0.721757 |
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