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6,070,157 | 11 | 14 | 11. In an unstructured database, a method for identifying an electronic document in response to a search request, the method comprising the steps of: augmenting a universal resource locator (URL) of a document to reflect an attribute of that document; determining a plurality of electronic documents to be responsive to a given search request; and presenting as a search result the augmented URL for each document having an augmented URL which is identified to be responsive to the search request. | 11. In an unstructured database, a method for identifying an electronic document in response to a search request, the method comprising the steps of: augmenting a universal resource locator (URL) of a document to reflect an attribute of that document; determining a plurality of electronic documents to be responsive to a given search request; and presenting as a search result the augmented URL for each document having an augmented URL which is identified to be responsive to the search request. 14. The method of claim 11 wherein said attribute of the augmented URL reflects a relative popularity of the corresponding identified document. | 0.544586 |
9,858,256 | 7 | 8 | 7. The memory device of claim 1 , wherein the operations further comprise sending a correction notification to at least one of the plurality of users, the correction notification identifying at least one of the plurality of text data sets. | 7. The memory device of claim 1 , wherein the operations further comprise sending a correction notification to at least one of the plurality of users, the correction notification identifying at least one of the plurality of text data sets. 8. The memory device of claim 7 , wherein sending a correction notification to at least one of the plurality of users includes sending an e-mail correction notification to the at least one of the plurality of users. | 0.5 |
8,495,156 | 7 | 8 | 7. The method of claim 1 , further comprising obtaining approval to populate a database with each matching user identity, wherein the approval is obtained from at least one of the user and the other user associated with the matching user identity. | 7. The method of claim 1 , further comprising obtaining approval to populate a database with each matching user identity, wherein the approval is obtained from at least one of the user and the other user associated with the matching user identity. 8. The method of claim 7 , wherein obtaining approval to populate the database with each matching user identity comprises requesting confirmation from the other user associated with the matching user identity that the respective identified user identity is associated with the other user. | 0.5 |
8,453,110 | 8 | 10 | 8. A system comprising: a processor to: receive information identifying two interface types from a plurality of possible interface types for an interface between two or more components of a model, a first interface type, of the two interface types, including a first signal associated with a first parameter for the model, and a second interface type, of the two interface types, including a second signal associated with a second parameter for the model, the second parameter differing from the first parameter, identify, based on the first parameter and the second parameter, one of the first interface type or the second interface type as an interface type for the interface, the processor, when identifying the one of the first interface type or the second interface type as the interface type, being further to: apply a cost function to at least one parameter of the model to produce cost results, the least one parameter of the model including at least one of: a size parameter, a power parameter, or a clock parameter, and identify the one of the first interface type or the second interface type further based on the produced cost results, and generate code representative of the interface based on the identified interface type. | 8. A system comprising: a processor to: receive information identifying two interface types from a plurality of possible interface types for an interface between two or more components of a model, a first interface type, of the two interface types, including a first signal associated with a first parameter for the model, and a second interface type, of the two interface types, including a second signal associated with a second parameter for the model, the second parameter differing from the first parameter, identify, based on the first parameter and the second parameter, one of the first interface type or the second interface type as an interface type for the interface, the processor, when identifying the one of the first interface type or the second interface type as the interface type, being further to: apply a cost function to at least one parameter of the model to produce cost results, the least one parameter of the model including at least one of: a size parameter, a power parameter, or a clock parameter, and identify the one of the first interface type or the second interface type further based on the produced cost results, and generate code representative of the interface based on the identified interface type. 10. The system of claim 8 , where the model includes at least one of: a graphical model having at least one block representation, or a text-based model. | 0.815981 |
8,656,294 | 9 | 10 | 9. A method of editing text on an electronic device having a touch display, the method comprising: displaying a user interface for a text editing application executing on the electronic device to include a user input area to receive user input and a text composition area to display text output; displaying a user input interface in the input area, wherein the user input interface comprises a touch-sensitive keypad; scrolling through a plurality of user documents within the input area responsive to receiving one or more user commands, each user document being associated with another application and comprising arbitrary text; receiving user input indicating selection of a user document from the plurality of user documents; replacing the user input interface displayed in the input area with the selected user document that includes arbitrary text while continuing to display text output in the text composition area; and copying and pasting arbitrary text selected by the user from the selected user document displayed in the input area into the text composition area. | 9. A method of editing text on an electronic device having a touch display, the method comprising: displaying a user interface for a text editing application executing on the electronic device to include a user input area to receive user input and a text composition area to display text output; displaying a user input interface in the input area, wherein the user input interface comprises a touch-sensitive keypad; scrolling through a plurality of user documents within the input area responsive to receiving one or more user commands, each user document being associated with another application and comprising arbitrary text; receiving user input indicating selection of a user document from the plurality of user documents; replacing the user input interface displayed in the input area with the selected user document that includes arbitrary text while continuing to display text output in the text composition area; and copying and pasting arbitrary text selected by the user from the selected user document displayed in the input area into the text composition area. 10. The method of claim 9 wherein replacing the user input interface displayed in the input area with the selected user document comprises replacing the touch-sensitive keypad displayed in the input area with the selected user document responsive to receiving a user command. | 0.613764 |
8,457,544 | 18 | 21 | 18. A method for making recommendations in educating students, the method comprising: receiving, via an input system, a recommendation request for at least one current student; accessing a data storage facility storing student data, the student data including attributes associated with a plurality of current students and predecessor students, wherein at least one attribute associated with each predecessor student includes at least one educational resource used with the predecessor student; receiving at least one constraint and a weight value for applying to the at least one constraint, wherein the at least one constraint indicating which attribute to use for determining sameness between students, and the weight value indicating a strength of the attribute in making the determination of the sameness; clustering, via a processor, a first group of students into clusters based on the sameness, wherein the first group of students comprises a first one of predecessor students and current students; the clustering including: associating each student of the first group of students with a conceptual location in a multidimensional space including at least two dimensions, each dimension corresponding to an attribute and the location being defined by at least two attributes, and clustering the first group of students into clusters based on a distance between locations such that a cluster defines a conceptual region within the multidimensional space; mapping, via the processor, a second one of the predecessor and current students to the first group of students, the mapping including: for predecessor students in the first group of students, mapping each current student to a cluster of predecessor students based on a location of each current student in the multidimensional space relative to the cluster, and correlating each current student with an educational resource associated with one of a predecessor student in the cluster of predecessor students or the cluster of predecessor students, for current students in the first group of students, mapping a cluster of current students to one of a predecessor student or cluster of predecessor students based on a location of one of the predecessor student or the cluster of predecessor students in the multidimensional space relative to the cluster of current students, and correlating each current student to an educational resource used by the predecessor student or cluster of the predecessor students; and recommending for each of the current students the at least one educational resource associated with the predecessor student or cluster of predecessor students that the current student is mapped with. | 18. A method for making recommendations in educating students, the method comprising: receiving, via an input system, a recommendation request for at least one current student; accessing a data storage facility storing student data, the student data including attributes associated with a plurality of current students and predecessor students, wherein at least one attribute associated with each predecessor student includes at least one educational resource used with the predecessor student; receiving at least one constraint and a weight value for applying to the at least one constraint, wherein the at least one constraint indicating which attribute to use for determining sameness between students, and the weight value indicating a strength of the attribute in making the determination of the sameness; clustering, via a processor, a first group of students into clusters based on the sameness, wherein the first group of students comprises a first one of predecessor students and current students; the clustering including: associating each student of the first group of students with a conceptual location in a multidimensional space including at least two dimensions, each dimension corresponding to an attribute and the location being defined by at least two attributes, and clustering the first group of students into clusters based on a distance between locations such that a cluster defines a conceptual region within the multidimensional space; mapping, via the processor, a second one of the predecessor and current students to the first group of students, the mapping including: for predecessor students in the first group of students, mapping each current student to a cluster of predecessor students based on a location of each current student in the multidimensional space relative to the cluster, and correlating each current student with an educational resource associated with one of a predecessor student in the cluster of predecessor students or the cluster of predecessor students, for current students in the first group of students, mapping a cluster of current students to one of a predecessor student or cluster of predecessor students based on a location of one of the predecessor student or the cluster of predecessor students in the multidimensional space relative to the cluster of current students, and correlating each current student to an educational resource used by the predecessor student or cluster of the predecessor students; and recommending for each of the current students the at least one educational resource associated with the predecessor student or cluster of predecessor students that the current student is mapped with. 21. The method according to claim 18 , the method further comprising the steps of: outputting the result of the recommendation to a user; receiving adjustments to the at least one constraint; and repeating the, determining, clustering, correlating, recommending, and outputting until the user is satisfied with the output results. | 0.698905 |
9,704,477 | 7 | 10 | 7. A non-transitory computer-readable medium having processor-executable instructions stored thereon for providing text-to-speech (TTS) functionality to a telematics unit of a telematics-equipped vehicle in a networked system, the processor-executable instructions, when executed by a processor of the telematics unit or a remote TTS engine on a remote server, facilitating performance of the following steps: receiving text content to be played back by an audio system of the telematics-equipped vehicle; determining a TTS rendering process type to be used for the text content from a plurality of TTS rendering process types supported by the networked system, wherein the plurality of TTS rendering process types include: a local TTS rendering process using a local TTS engine at the telematics-equipped vehicle, a remote TTS rendering process with delayed playback using the remote TTS engine, and a remote TTS rendering process with streaming playback using the remote TTS engine; and causing the text content to be rendered as an audio signal for playback by the telematics-equipped vehicle using the determined TTS rendering process type; wherein the determining is based on a quality of service (QoS) level corresponding to a location of the vehicle and a future expected location of the vehicle, and wherein during the determining, the TTS rendering process type is specified as: the local TTS rendering process for a current location corresponding to a first range of QoS levels, the remote TTS rendering process with delayed playback for a current location corresponding to a second range of QoS levels and for an expected transition from a current location corresponding to a third range of QoS levels to a future expected location corresponding to the first or second range of QoS levels; the remote TTS rendering process with streaming playback for a current location corresponding to the third range of QoS levels where there is not an to an expected transition to a future expected location corresponding to the first or second range of QoS levels. | 7. A non-transitory computer-readable medium having processor-executable instructions stored thereon for providing text-to-speech (TTS) functionality to a telematics unit of a telematics-equipped vehicle in a networked system, the processor-executable instructions, when executed by a processor of the telematics unit or a remote TTS engine on a remote server, facilitating performance of the following steps: receiving text content to be played back by an audio system of the telematics-equipped vehicle; determining a TTS rendering process type to be used for the text content from a plurality of TTS rendering process types supported by the networked system, wherein the plurality of TTS rendering process types include: a local TTS rendering process using a local TTS engine at the telematics-equipped vehicle, a remote TTS rendering process with delayed playback using the remote TTS engine, and a remote TTS rendering process with streaming playback using the remote TTS engine; and causing the text content to be rendered as an audio signal for playback by the telematics-equipped vehicle using the determined TTS rendering process type; wherein the determining is based on a quality of service (QoS) level corresponding to a location of the vehicle and a future expected location of the vehicle, and wherein during the determining, the TTS rendering process type is specified as: the local TTS rendering process for a current location corresponding to a first range of QoS levels, the remote TTS rendering process with delayed playback for a current location corresponding to a second range of QoS levels and for an expected transition from a current location corresponding to a third range of QoS levels to a future expected location corresponding to the first or second range of QoS levels; the remote TTS rendering process with streaming playback for a current location corresponding to the third range of QoS levels where there is not an to an expected transition to a future expected location corresponding to the first or second range of QoS levels. 10. The non-transitory computer-readable medium according to claim 7 , wherein determining the TTS rendering process type to be used is further based on a text-related parameter and a cost-related parameter. | 0.697368 |
8,959,427 | 1 | 7 | 1. A computer-implemented method for JavaScript based HTML website layouts, the method comprising: receiving, by one or more computing devices, a request to generate a website; in response to receiving the request, generating, by the one or more computing devices, a Hypertext Markup Language (HTML) website, wherein the HTML website comprises at least; a first HTML content block, wherein the first HTML content block comprises static HTML content to be published online and a first HTML identification code (ID); at least one second HTML content block, wherein the second HTML content block comprises a second HTML ID, and receiving, by the one or more computing devices, a request to move the static HTML content from the first HTML content block to the second HTML content block; in response to receiving the request to move the static HTML content, inputting, by the one or more computing devices, the first HTML ID of the first HTML content block as an origin location of the static HTML content and the second HTML ID of the second HTML content block as a destination location for the static HTML content; re-writing, by the one or more computing devices, the static HTML content from the first HTML content block to the second HTML content block, based on inputting the first HTML ID as the origin location and the second HTML ID as the destination location; in response to re-writing the static HTML content from the first HTML content block to the second HTML content block, removing, by the one or more computing devices, the static HTML content from the first HTML content block; transmitting, by the one or more computing devices, the HTML website, as modified by the re-writing and the removing, to one or more frontend computing devices. | 1. A computer-implemented method for JavaScript based HTML website layouts, the method comprising: receiving, by one or more computing devices, a request to generate a website; in response to receiving the request, generating, by the one or more computing devices, a Hypertext Markup Language (HTML) website, wherein the HTML website comprises at least; a first HTML content block, wherein the first HTML content block comprises static HTML content to be published online and a first HTML identification code (ID); at least one second HTML content block, wherein the second HTML content block comprises a second HTML ID, and receiving, by the one or more computing devices, a request to move the static HTML content from the first HTML content block to the second HTML content block; in response to receiving the request to move the static HTML content, inputting, by the one or more computing devices, the first HTML ID of the first HTML content block as an origin location of the static HTML content and the second HTML ID of the second HTML content block as a destination location for the static HTML content; re-writing, by the one or more computing devices, the static HTML content from the first HTML content block to the second HTML content block, based on inputting the first HTML ID as the origin location and the second HTML ID as the destination location; in response to re-writing the static HTML content from the first HTML content block to the second HTML content block, removing, by the one or more computing devices, the static HTML content from the first HTML content block; transmitting, by the one or more computing devices, the HTML website, as modified by the re-writing and the removing, to one or more frontend computing devices. 7. The method according to claim 1 , wherein: the request to move static HTML content from the first HTML content block to the second HTML content block is initiated by a script language listening function, the re-writing is performed by a script language re-writing function, and the removing is performed by a script language removing function. | 0.5 |
9,779,063 | 12 | 13 | 12. A computer-implemented method according to claim 1 , further comprising: presenting a document management interface to a user, and receiving the request to create the document from the document management interface. | 12. A computer-implemented method according to claim 1 , further comprising: presenting a document management interface to a user, and receiving the request to create the document from the document management interface. 13. A computer-implemented method according to claim 12 , wherein the request to create the document further comprises a second metadata data object relating to a position of a user within the document management interface. | 0.5 |
8,473,855 | 4 | 7 | 4. A method of creating a graphical user interface for search results, the method comprising: identifying search results for a received query from potential search results based on content data generated based on analyzing the potential search results, the identified search results including a first identified search result associated with a first link to first content and a second identified search result associated with a second link to second content; accessing characteristic data generated for the first and second identified search results based on analyzing the potential search results; determining, based on the accessed characteristic data corresponding to the first identified search result, a first characteristic of the first identified search result; determining, based on the accessed characteristic data corresponding to the second identified search result, a second characteristic of the second identified search result, the second characteristic of the second identified search result being different than the first characteristic of the first identified search result; determining display information for the identified search results based on the first characteristic of the first identified search result and the second characteristic of the second identified search result; creating a graphical user interface enabling display of the identified search results to the user based on the display information, each of the identified search results displayed with prose and an icon at an end thereof, the prose and icon of each identified search result indicating that the second content accessible through invocation of the second link associated with the second identified search result includes; and selecting an icon that reveals a description of (i) at least one characteristic of a search result, (ii) an explanation of the icon, and (iii) a detailed description of die characteristic and how a determination was made that content for which the icon is displayed has the at least one characteristic represented by the icon. | 4. A method of creating a graphical user interface for search results, the method comprising: identifying search results for a received query from potential search results based on content data generated based on analyzing the potential search results, the identified search results including a first identified search result associated with a first link to first content and a second identified search result associated with a second link to second content; accessing characteristic data generated for the first and second identified search results based on analyzing the potential search results; determining, based on the accessed characteristic data corresponding to the first identified search result, a first characteristic of the first identified search result; determining, based on the accessed characteristic data corresponding to the second identified search result, a second characteristic of the second identified search result, the second characteristic of the second identified search result being different than the first characteristic of the first identified search result; determining display information for the identified search results based on the first characteristic of the first identified search result and the second characteristic of the second identified search result; creating a graphical user interface enabling display of the identified search results to the user based on the display information, each of the identified search results displayed with prose and an icon at an end thereof, the prose and icon of each identified search result indicating that the second content accessible through invocation of the second link associated with the second identified search result includes; and selecting an icon that reveals a description of (i) at least one characteristic of a search result, (ii) an explanation of the icon, and (iii) a detailed description of die characteristic and how a determination was made that content for which the icon is displayed has the at least one characteristic represented by the icon. 7. The method of claim 4 wherein: determining, based on the accessed characteristic data corresponding to the first identified search result, the first characteristic of the first identified search result comprises determining, based on the accessed characteristic data corresponding to the first identified search result, that the first content accessible through invocation of the first link associated with the first identified search result includes content provided by a first type of source; determining, based on the accessed characteristic data corresponding to the second identified search result, the second characteristic of the second identified search result comprises determining, based on the accessed characteristic data corresponding to the second identified search result, that the second content includes content provided by a second type of source that is different than the first type of source; creating the graphical user interface enabling display of the identified search results to the user based on the display information comprises creating a graphical user interface enabling display of the identified search results to the user based on the display information, the graphical user interface providing a perceivable indication, other than the second content and the second link, that the second content accessible through invocation of the second link associated with the second identified search result includes content provided by the second type of source; and the perceivable indication is the prose and the icon. | 0.548745 |
8,775,403 | 21 | 23 | 21. A computing system, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: retrieving a number of document identifiers, each document identifier identifying a corresponding document on a network; and for each retrieved document identifier and its corresponding document, determining a query-independent score indicative of a rank of the corresponding document relative to other documents in a set of documents; determining a first score for the document identifier that is a function of the determined query-independent score, a determined content change frequency of the corresponding document, and an age of the corresponding document; comparing the first score against a threshold value thereby obtaining a result, wherein the threshold value is a function of a speed of the engine crawler system; and conditionally scheduling the corresponding document for indexing based on the result. | 21. A computing system, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: retrieving a number of document identifiers, each document identifier identifying a corresponding document on a network; and for each retrieved document identifier and its corresponding document, determining a query-independent score indicative of a rank of the corresponding document relative to other documents in a set of documents; determining a first score for the document identifier that is a function of the determined query-independent score, a determined content change frequency of the corresponding document, and an age of the corresponding document; comparing the first score against a threshold value thereby obtaining a result, wherein the threshold value is a function of a speed of the engine crawler system; and conditionally scheduling the corresponding document for indexing based on the result. 23. The system of claim 21 wherein the first score for the document identifier is a function of the determined content change frequency of the corresponding document. | 0.69145 |
9,798,812 | 8 | 11 | 8. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: receive a plurality of data items imported into a social-networking system by a first user of the social-networking system, the plurality of data items being related to an entity; access, by one or more processors associated with one or more computer servers associated with the social-networking system, one or more data stores storing a social graph of the social-networking system, the social graph comprising a plurality of nodes and a plurality of edges between nodes, the nodes comprising user nodes corresponding to users of the social-networking system and concept nodes corresponding to concepts; identify, by the one or more processors, one or more nodes of the social graph that likely match the entity; determine, by the one or more processors, a confidence score for each of the one or more of the identified nodes, the confidence score indicating a relative likelihood that the identified node matches the entity, wherein the confidence score is based in part on an interaction between the entity and a test message sent to the entity; and update, by the one or more processors, at least one of the identified nodes with at least one of the data items. | 8. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: receive a plurality of data items imported into a social-networking system by a first user of the social-networking system, the plurality of data items being related to an entity; access, by one or more processors associated with one or more computer servers associated with the social-networking system, one or more data stores storing a social graph of the social-networking system, the social graph comprising a plurality of nodes and a plurality of edges between nodes, the nodes comprising user nodes corresponding to users of the social-networking system and concept nodes corresponding to concepts; identify, by the one or more processors, one or more nodes of the social graph that likely match the entity; determine, by the one or more processors, a confidence score for each of the one or more of the identified nodes, the confidence score indicating a relative likelihood that the identified node matches the entity, wherein the confidence score is based in part on an interaction between the entity and a test message sent to the entity; and update, by the one or more processors, at least one of the identified nodes with at least one of the data items. 11. The media of claim 8 , wherein the software is further operable when executed to: rank the one or more identified nodes based on the confidence score; select a set of the one or more identified nodes whose confidence score is above a threshold level; and present the selected nodes for confirmation by the user. | 0.5 |
9,195,649 | 8 | 9 | 8. A processor-based method for determining semantic audio information for audio, comprising: extracting a first audio feature from the audio, the first audio feature including at least one of a rhythmic structure, a beat period, a rhythmic fluctuation, or an average tempo; extracting a second audio feature from the audio, the second audio feature including at least one of a temporal feature, a spectral feature, a harmonic feature, or a rhythmic feature, wherein the second audio feature is different from the first audio feature; comparing the first and second audio features to a plurality of stored audio feature ranges having tags associated therewith; and determining the stored audio feature ranges having the closest matches to the first and second audio features, the tags associated with the audio feature ranges having the closest matches to be used to determine the semantic audio information for the audio. | 8. A processor-based method for determining semantic audio information for audio, comprising: extracting a first audio feature from the audio, the first audio feature including at least one of a rhythmic structure, a beat period, a rhythmic fluctuation, or an average tempo; extracting a second audio feature from the audio, the second audio feature including at least one of a temporal feature, a spectral feature, a harmonic feature, or a rhythmic feature, wherein the second audio feature is different from the first audio feature; comparing the first and second audio features to a plurality of stored audio feature ranges having tags associated therewith; and determining the stored audio feature ranges having the closest matches to the first and second audio features, the tags associated with the audio feature ranges having the closest matches to be used to determine the semantic audio information for the audio. 9. The method of claim 8 , wherein the temporal feature includes at least one of amplitude, power, or zero crossing of at least some of the audio. | 0.802703 |
9,552,358 | 1 | 2 | 1. A computer-implemented method for identifying content in a document, the method comprising: identifying within each document of a plurality of open documents, by a computing device, content corresponding to a particular subject matter category; in response to the computing device opening an additional document, identifying within the additional document, by the computer device, additional content corresponding to the particular subject matter category; providing, within the additional document, an indicator that visually distinguishes the identified additional content from the other content within the additional document; in response to the computing device opening a second additional document and content of the second additional document not corresponding to the particular subject matter category, determining a new subject matter category corresponding to the content of the second additional document; determining a majority of the plurality of open documents of the computing device relate to similar subject matter, wherein the particular subject matter category relates to the similar subject matter; in response to determining that the majority of the plurality of open documents of the computing device relate to the similar subject matter, assigning a weight to the similar subject matter and the new subject matter category, wherein the similar subject matter is more heavily weighted than the new subject matter category; and providing, based on the assigned weights, indicators that visually distinguish documents relating to the similar subject matter category from documents relating to the new subject matter category. | 1. A computer-implemented method for identifying content in a document, the method comprising: identifying within each document of a plurality of open documents, by a computing device, content corresponding to a particular subject matter category; in response to the computing device opening an additional document, identifying within the additional document, by the computer device, additional content corresponding to the particular subject matter category; providing, within the additional document, an indicator that visually distinguishes the identified additional content from the other content within the additional document; in response to the computing device opening a second additional document and content of the second additional document not corresponding to the particular subject matter category, determining a new subject matter category corresponding to the content of the second additional document; determining a majority of the plurality of open documents of the computing device relate to similar subject matter, wherein the particular subject matter category relates to the similar subject matter; in response to determining that the majority of the plurality of open documents of the computing device relate to the similar subject matter, assigning a weight to the similar subject matter and the new subject matter category, wherein the similar subject matter is more heavily weighted than the new subject matter category; and providing, based on the assigned weights, indicators that visually distinguish documents relating to the similar subject matter category from documents relating to the new subject matter category. 2. The method of claim 1 , wherein the plurality of open documents and the additional document comprise one or more of word processing documents, spreadsheets, text editing files, presentation documents or web browser pages. | 0.815789 |
7,756,313 | 1 | 7 | 1. A method for computer aided detection of anatomical abnormalities in medical images comprising the steps of: providing a plurality of abnormality candidates and features of said abnormality candidates; and classifying said abnormality candidates as true positives or false positives using a hierarchical cascade of linear classifiers of the form sign(w T x+b), wherein x is a feature vector, w is a weighting vector and b is a model parameter, wherein different weights are used to penalize false negatives and false positives, and wherein more computationally complex features are used for each successive stage of said cascade of classifiers, wherein each stage of said cascade solves a linear program formulated using a training error rate ξ equivalent to max {0,1−y(w T x+b)} and an l 1 -norm equivalent to w 1 = ∑ w i summed over all features, wherein said linear program is equivalent to the system represented by min u , v , ξ λ ∑ j = 1 d ( u j + v j ) + μ l + ∑ i ∈ C + ξ i + 1 - μ l - ∑ i ∈ C - ξ i , y ( ∑ j X ij ( u j - v j ) + b ) + ξ i ≥ 1 , such that ξ i ≥ 0 , i = 1 , … , l , u j , v j ≥ 0 , j = 1 , … , d , ( 1 ) wherein λ>0 is a regularization parameter, {x i , y i }, i=1, . . . , l denotes the abnormality candidates, y denotes a label indicating whether or not a candidate associated with a feature vector is a true positive, X denotes a feature matrix of d features wherein each row represents candidate feature vector x, and each column specifies a feature, l + is the number of positive candidates and l − the number of negative candidates, C + and C − contain, respectively, the sets of indices of positive candidates and negative candidates, 0≦μ≦1 is a tuning parameter for combining the false negative rate and false positive rate, and w j =u j −v j . | 1. A method for computer aided detection of anatomical abnormalities in medical images comprising the steps of: providing a plurality of abnormality candidates and features of said abnormality candidates; and classifying said abnormality candidates as true positives or false positives using a hierarchical cascade of linear classifiers of the form sign(w T x+b), wherein x is a feature vector, w is a weighting vector and b is a model parameter, wherein different weights are used to penalize false negatives and false positives, and wherein more computationally complex features are used for each successive stage of said cascade of classifiers, wherein each stage of said cascade solves a linear program formulated using a training error rate ξ equivalent to max {0,1−y(w T x+b)} and an l 1 -norm equivalent to w 1 = ∑ w i summed over all features, wherein said linear program is equivalent to the system represented by min u , v , ξ λ ∑ j = 1 d ( u j + v j ) + μ l + ∑ i ∈ C + ξ i + 1 - μ l - ∑ i ∈ C - ξ i , y ( ∑ j X ij ( u j - v j ) + b ) + ξ i ≥ 1 , such that ξ i ≥ 0 , i = 1 , … , l , u j , v j ≥ 0 , j = 1 , … , d , ( 1 ) wherein λ>0 is a regularization parameter, {x i , y i }, i=1, . . . , l denotes the abnormality candidates, y denotes a label indicating whether or not a candidate associated with a feature vector is a true positive, X denotes a feature matrix of d features wherein each row represents candidate feature vector x, and each column specifies a feature, l + is the number of positive candidates and l − the number of negative candidates, C + and C − contain, respectively, the sets of indices of positive candidates and negative candidates, 0≦μ≦1 is a tuning parameter for combining the false negative rate and false positive rate, and w j =u j −v j . 7. The method of claim 1 , further comprising providing a digitized medical image comprising a plurality of intensities corresponding to a domain of points on a 3-dimensional grid; segmenting a region-of-interest from said medical image; generating said abnormality candidates and internal features of said abnormality candidates from said region-of-interest; and for each abnormality candidate, computing additional more computationally complex features that characterize the shape, size, intensity statistics, and template matches for each candidate. | 0.5 |
8,341,158 | 10 | 16 | 10. A machine-readable medium having instructions tangibly stored thereon for execution by a processor to perform a method comprising: obtaining a dataset representing a plurality of users, a plurality of items, and a plurality of ratings given to items by users; clustering the plurality of users into a plurality of user-groups such that at least one user belongs to more than one user-group; clustering the plurality of items into a plurality of item-groups such that at least one item belongs to more than one item-group; inducing a model describing a probabilistic relationship between the plurality of users, items, ratings, user-groups, and item-groups, the induced model defined by a plurality of model parameters; and predicting a rating of a user for an item using the induced model. | 10. A machine-readable medium having instructions tangibly stored thereon for execution by a processor to perform a method comprising: obtaining a dataset representing a plurality of users, a plurality of items, and a plurality of ratings given to items by users; clustering the plurality of users into a plurality of user-groups such that at least one user belongs to more than one user-group; clustering the plurality of items into a plurality of item-groups such that at least one item belongs to more than one item-group; inducing a model describing a probabilistic relationship between the plurality of users, items, ratings, user-groups, and item-groups, the induced model defined by a plurality of model parameters; and predicting a rating of a user for an item using the induced model. 16. The machine-readable medium of claim 10 , the method further including predicting the rating of the user by: determining a profile specific to the user; and generating a predicted rating based on the determined profile. | 0.731971 |
9,480,908 | 10 | 11 | 10. The method of claim 9 , further comprising: presenting a shared countdown clock visible in the clue-selection game display and in the guessing game display that indicates a time remaining for paired players to play one game round. | 10. The method of claim 9 , further comprising: presenting a shared countdown clock visible in the clue-selection game display and in the guessing game display that indicates a time remaining for paired players to play one game round. 11. The method of claim 10 , wherein a cost incurred for giving each clue is a specific adjustment to the shared countdown clock. | 0.5 |
10,146,404 | 16 | 17 | 16. The method of claim 11 , wherein determining the first plurality of string predictions based on the first character comprises determining the first plurality of string predictions based on the first character and at least one prediction model. | 16. The method of claim 11 , wherein determining the first plurality of string predictions based on the first character comprises determining the first plurality of string predictions based on the first character and at least one prediction model. 17. The method of claim 16 , wherein the at least one prediction model is one or more of a local prediction model or a global prediction model. | 0.5 |
4,866,778 | 24 | 28 | 24. A speech recognition system comprising: means for receiving an acoustic description of a portion of speech to be recognized; means for storing an acoustic description of each word in a system vocabulary; recognition means for making a determination of which one or more words of a recognition vocabulary which is a sub-vocabulary consisting of one or more words of said system vocabulary most probably correspond to said portion of speech, said recognition means including comparing means for determining how closely the acoustic description of said portion of speech compares to the acoustic descriptions of words from said recognition vocabulary; first-pass means for causing said recognition means to first make a first determination of which one or more words of a first such recognition vocabulary most probably correspond to said portion of speech; re-recognition means for causing said recognition means to start to make a second determination of which one or more words of a second such recognition vocabulary most probably correspond to said portion of speech; and means for aborting said second determination in response to an abort signal from an operator of the system. | 24. A speech recognition system comprising: means for receiving an acoustic description of a portion of speech to be recognized; means for storing an acoustic description of each word in a system vocabulary; recognition means for making a determination of which one or more words of a recognition vocabulary which is a sub-vocabulary consisting of one or more words of said system vocabulary most probably correspond to said portion of speech, said recognition means including comparing means for determining how closely the acoustic description of said portion of speech compares to the acoustic descriptions of words from said recognition vocabulary; first-pass means for causing said recognition means to first make a first determination of which one or more words of a first such recognition vocabulary most probably correspond to said portion of speech; re-recognition means for causing said recognition means to start to make a second determination of which one or more words of a second such recognition vocabulary most probably correspond to said portion of speech; and means for aborting said second determination in response to an abort signal from an operator of the system. 28. A speech recognition system as described in claim 24 wherein: said means for receiving an acoustic description of a portion of speech to be recognized includes means for receiving an acoustic description of each successive utterance spoken by an operator of the system; said speech recognition system is a discrete utterance recognition system and said means for aborting said second determination includes means for detecting the beginning of another such utterance after the utterance associated with said portion of speech for which said first determination is made and for treating such a detection as said abort signal. | 0.665957 |
8,756,527 | 8 | 13 | 8. A non-transitory, computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising: a first executable portion for determining a plurality of candidate words available for selection based on a present text entry position within a document or application and a previous text entry within the document or application; a second executable portion for causing a display of the plurality of candidate words in a candidate word field at a separate location from the document or application, wherein the candidate word field represents a positional format of the document or application, wherein the display of the candidate words in the candidate word field positions the candidate words within the candidate word field in a region of the candidate word field that is substantially similar to a position of a region of the document or application where the present text entry position is located; a third executable portion for receiving a selection of at least one of the candidate words within the candidate word field; a fourth executable portion for including a selected candidate word in the document or application; and a fifth executable portion for causing the updating of a portion of the candidate words in the candidate word field after each selection. | 8. A non-transitory, computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising: a first executable portion for determining a plurality of candidate words available for selection based on a present text entry position within a document or application and a previous text entry within the document or application; a second executable portion for causing a display of the plurality of candidate words in a candidate word field at a separate location from the document or application, wherein the candidate word field represents a positional format of the document or application, wherein the display of the candidate words in the candidate word field positions the candidate words within the candidate word field in a region of the candidate word field that is substantially similar to a position of a region of the document or application where the present text entry position is located; a third executable portion for receiving a selection of at least one of the candidate words within the candidate word field; a fourth executable portion for including a selected candidate word in the document or application; and a fifth executable portion for causing the updating of a portion of the candidate words in the candidate word field after each selection. 13. A non-transitory, computer readable storage medium according to claim 8 , wherein the third executable portion includes instructions for receiving an input defining a sequence of more than one selected candidate words. | 0.615917 |
9,672,554 | 14 | 15 | 14. The system of claim 13 , the instructions further comprising a search engine module configured to process a query to identify item listings, among the plurality of item listings, that satisfy the query. | 14. The system of claim 13 , the instructions further comprising a search engine module configured to process a query to identify item listings, among the plurality of item listings, that satisfy the query. 15. The system of claim 14 , the instructions further comprising a ranking score module configured to determine, for each of the item listings that satisfies the query, a ranking score based, a least in part, on the weighted sums of the predicted listing quality score and the observed listing quality score for the item listing. | 0.5 |
9,952,752 | 7 | 10 | 7. A system, comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: receiving, through a user interface of a social network application presented at a user device, an indication that a user recommended content displayed the user interface, wherein the recommended content includes a plurality of different content components corresponding to different portions of the recommended content; responsive to receiving the indication that the user recommended content displayed in the user interface, requesting user interaction data indicative of the user recommendation of content displayed in the user interface; receiving user interaction data that includes an action taken by the user, a time corresponding to the action, and a content identifier identifying the content the user recommended; mapping at least one annotation specifying the action taken to the different portions of the recommended content; and distributing, based on the mapping, recommended content through a social network with the at least one annotation at a presentation location corresponding to at least one content component of the recommended content. | 7. A system, comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: receiving, through a user interface of a social network application presented at a user device, an indication that a user recommended content displayed the user interface, wherein the recommended content includes a plurality of different content components corresponding to different portions of the recommended content; responsive to receiving the indication that the user recommended content displayed in the user interface, requesting user interaction data indicative of the user recommendation of content displayed in the user interface; receiving user interaction data that includes an action taken by the user, a time corresponding to the action, and a content identifier identifying the content the user recommended; mapping at least one annotation specifying the action taken to the different portions of the recommended content; and distributing, based on the mapping, recommended content through a social network with the at least one annotation at a presentation location corresponding to at least one content component of the recommended content. 10. The system of claim 7 , wherein the instructions cause the data processing apparatus to perform operations further comprising: responsive to receiving the indication that the user recommended content displayed in the user interface, sending to a server in communication with the user device over a network, data identifying the at least one content component of the recommended content selected by the user; and receiving at the user interface of the social network application and from the server, the at least one annotation for display in the user interface of the social network application indicating the at least one content component of the recommended content to which the recommendation of the user applies. | 0.5 |
9,483,736 | 1 | 3 | 1. A method to filter user's actions based on user's mood, the method comprising: detecting a user's mood through one or more of: keystroke dynamics detection, facial feature analysis, body composure analysis, biological parameter analysis, and recent communication content analysis, wherein the biological parameters include one or more of a blood pressure, a heartbeat, and a body temperature; determining a mood indicator value based on the detected user's mood; identifying a user action, wherein the user action comprises posting a message to one or more of a social network, a professional network, an email network, a blog, and an instant message network; determining a system action based on the mood indicator value and the user action, wherein the system action includes one of: blocking an execution of the user action; delaying the execution of the user action for a particular time period, and upon expiration of the particular time period, presenting a confirmation option for execution of the user action; and directing the user action to an alternate destination for execution; and applying the system action. | 1. A method to filter user's actions based on user's mood, the method comprising: detecting a user's mood through one or more of: keystroke dynamics detection, facial feature analysis, body composure analysis, biological parameter analysis, and recent communication content analysis, wherein the biological parameters include one or more of a blood pressure, a heartbeat, and a body temperature; determining a mood indicator value based on the detected user's mood; identifying a user action, wherein the user action comprises posting a message to one or more of a social network, a professional network, an email network, a blog, and an instant message network; determining a system action based on the mood indicator value and the user action, wherein the system action includes one of: blocking an execution of the user action; delaying the execution of the user action for a particular time period, and upon expiration of the particular time period, presenting a confirmation option for execution of the user action; and directing the user action to an alternate destination for execution; and applying the system action. 3. The method of claim 1 , further comprising determining the mood indicator value as one of a plurality of alphanumeric categories. | 0.65445 |
7,725,330 | 28 | 30 | 28. In a program storage device readable by a machine, tangibly embodying a program of instructions executable on the machine to perform steps for processing medical information, the program storage device comprising instructions for: obtaining a medical record of a patient, wherein the medical record comprises patient information from structured and unstructured data sources; analyzing the patient information from at least the unstructured data source in the medical record using domain-specific criteria; and automatically extracting billing information from the medical record as part of the analysis. | 28. In a program storage device readable by a machine, tangibly embodying a program of instructions executable on the machine to perform steps for processing medical information, the program storage device comprising instructions for: obtaining a medical record of a patient, wherein the medical record comprises patient information from structured and unstructured data sources; analyzing the patient information from at least the unstructured data source in the medical record using domain-specific criteria; and automatically extracting billing information from the medical record as part of the analysis. 30. The program storage device of claim 28 , wherein the patient information comprises clinical information and financial information of the patient. | 0.725092 |
9,996,670 | 31 | 35 | 31. An analytics system configured to improve content analyzer system accuracy, comprising: at least one processing device comprising hardware; non-transitory media comprising a text extraction module, an entity alignment module, and at least one or a pattern matching engine or a machine learning engine, the when executed by the at least one processing device, are configured to cause the analytics system to perform operations comprising: improving content analyzer system accuracy in identifying CDS document deficiencies and consistencies with respect to reference content, the reference content comprising clinical guidelines, by repeatedly training a machine learning module based on new incoming data, wherein the machine learning module is configured to automatically determine which content features are to be used to determine whether content is to be designated as relevant and matching to the reference content and which content is to be designated as non-relevant and to construct or modify an electronic model accordingly, wherein the features comprise one or more of text length, presence of a medication term, medical intervention language, use of a negation, or context, wherein improving content analyzer system accuracy by training the machine learning module comprises repeatedly: collecting positive and negative cases from CDS documents, training the electronic model using the collected positive and negative cases from CDS documents, taking as input a text segment extracted from a CDS document and returning a likelihood that the text segment matches a reference checklist item, and wherein the new incoming data indicates whether the likelihood that the text segment matches a reference checklist item is correct or incorrect; receiving a clinical decision support document; accessing reference content corresponding at least in part to the clinical decision support document, the reference content comprising clinical guidelines; identifying and extracting, using the electronic model, medical intervention content from the clinical decision support document; using feedback with respect to the identification of the medical intervention content to refine the electronic model; segmenting at least a portion of the extracted medical intervention content into a first plurality of segments including at least a first segment, comprising a first set of text, and a second segment comprising a second set of text, wherein a given segment in the first plurality of segments is evaluated to identify a core concept, wherein identifying the core concept further comprises determining whether a given segment includes a plurality of medical interventions, and determining which of the plurality of medical interventions are part of the core concept and which of the plurality of medical interventions are not part of the core concept, and if the core concept of the given segment comprises at least one a medical intervention, determining whether a negation is associated with the medical intervention; determining, using the trained machine learning engine, if the first segment corresponds to at least a first item included in the reference content, the first item comprising a third set of text different than the first and second sets of text; at least partly in response to determining that the first segment, comprising the first set of text, corresponds to the first item included in the reference content, the first item comprising the third set of text, causing a report be generated to include a visual indication that the first segment corresponds to the first item included in the reference content; determining, using the trained machine learning engine, if a second item included in the reference content corresponds to at least one of the first plurality of segments; at least partly in response to determining that the second item included in the reference content does not correspond to at least one of the first plurality of segments, causing the report to include a visual indication that the first plurality of segments fails to include at least one segment that corresponds to the second item included in the reference content; at least partly in response to determining that the second item included in the reference content does correspond to at least one of the first plurality of segments, causing the report to include a visual indication that the first plurality of segments includes at least one segment that corresponds to the second item included in the reference content. | 31. An analytics system configured to improve content analyzer system accuracy, comprising: at least one processing device comprising hardware; non-transitory media comprising a text extraction module, an entity alignment module, and at least one or a pattern matching engine or a machine learning engine, the when executed by the at least one processing device, are configured to cause the analytics system to perform operations comprising: improving content analyzer system accuracy in identifying CDS document deficiencies and consistencies with respect to reference content, the reference content comprising clinical guidelines, by repeatedly training a machine learning module based on new incoming data, wherein the machine learning module is configured to automatically determine which content features are to be used to determine whether content is to be designated as relevant and matching to the reference content and which content is to be designated as non-relevant and to construct or modify an electronic model accordingly, wherein the features comprise one or more of text length, presence of a medication term, medical intervention language, use of a negation, or context, wherein improving content analyzer system accuracy by training the machine learning module comprises repeatedly: collecting positive and negative cases from CDS documents, training the electronic model using the collected positive and negative cases from CDS documents, taking as input a text segment extracted from a CDS document and returning a likelihood that the text segment matches a reference checklist item, and wherein the new incoming data indicates whether the likelihood that the text segment matches a reference checklist item is correct or incorrect; receiving a clinical decision support document; accessing reference content corresponding at least in part to the clinical decision support document, the reference content comprising clinical guidelines; identifying and extracting, using the electronic model, medical intervention content from the clinical decision support document; using feedback with respect to the identification of the medical intervention content to refine the electronic model; segmenting at least a portion of the extracted medical intervention content into a first plurality of segments including at least a first segment, comprising a first set of text, and a second segment comprising a second set of text, wherein a given segment in the first plurality of segments is evaluated to identify a core concept, wherein identifying the core concept further comprises determining whether a given segment includes a plurality of medical interventions, and determining which of the plurality of medical interventions are part of the core concept and which of the plurality of medical interventions are not part of the core concept, and if the core concept of the given segment comprises at least one a medical intervention, determining whether a negation is associated with the medical intervention; determining, using the trained machine learning engine, if the first segment corresponds to at least a first item included in the reference content, the first item comprising a third set of text different than the first and second sets of text; at least partly in response to determining that the first segment, comprising the first set of text, corresponds to the first item included in the reference content, the first item comprising the third set of text, causing a report be generated to include a visual indication that the first segment corresponds to the first item included in the reference content; determining, using the trained machine learning engine, if a second item included in the reference content corresponds to at least one of the first plurality of segments; at least partly in response to determining that the second item included in the reference content does not correspond to at least one of the first plurality of segments, causing the report to include a visual indication that the first plurality of segments fails to include at least one segment that corresponds to the second item included in the reference content; at least partly in response to determining that the second item included in the reference content does correspond to at least one of the first plurality of segments, causing the report to include a visual indication that the first plurality of segments includes at least one segment that corresponds to the second item included in the reference content. 35. The system as defined in claim 31 , the system further comprising a negation detection and syntactic analysis system. | 0.810938 |
9,002,900 | 2 | 5 | 2. The method of claim 1 , further comprising receiving an input instructing the processor to associate the received additional activity data item with the hierarchical data structure as a child or parent of one of the activity data items of the hierarchical data structure. | 2. The method of claim 1 , further comprising receiving an input instructing the processor to associate the received additional activity data item with the hierarchical data structure as a child or parent of one of the activity data items of the hierarchical data structure. 5. The method of claim 2 , further comprising: receiving a second input on the first computer system instructing the processor to perform a modification on one of a child activity data item and a parent activity data item of the received additional activity data item; and transmitting the modification from the first computer system to the second computer system. | 0.688356 |
9,218,107 | 2 | 3 | 2. The method of claim 1 , wherein the determination that the text caret has been activated comprises identifying that the window is an active top-level window. | 2. The method of claim 1 , wherein the determination that the text caret has been activated comprises identifying that the window is an active top-level window. 3. The method of claim 2 , wherein the determination that the text caret has been activated further comprises identifying the presence of a cursor or other indicator in the active top-level window. | 0.5 |
8,812,473 | 22 | 24 | 22. A computer system, comprising: a data repository that stores search activity data of search engine users, said search activity data encompassing searches conducted by search engine users over a plurality of index-type search engines, wherein each of the plurality of index-type search engines maintains its own proprietary index obtained by crawling web sites for building a unique database for generating search results, wherein each of the search engine users interacts with a search results page of the index-type search engine to view search results; and an analysis component stored on a computer-readable medium, wherein the analysis component analyzes the search activity data stored in the data repository to generate statistical data regarding search queries used over said plurality of index-type search engines to locate and access a particular destination, wherein the analysis component comprises computer hardware. | 22. A computer system, comprising: a data repository that stores search activity data of search engine users, said search activity data encompassing searches conducted by search engine users over a plurality of index-type search engines, wherein each of the plurality of index-type search engines maintains its own proprietary index obtained by crawling web sites for building a unique database for generating search results, wherein each of the search engine users interacts with a search results page of the index-type search engine to view search results; and an analysis component stored on a computer-readable medium, wherein the analysis component analyzes the search activity data stored in the data repository to generate statistical data regarding search queries used over said plurality of index-type search engines to locate and access a particular destination, wherein the analysis component comprises computer hardware. 24. The computer system of claim 22 , wherein the statistical data includes, for a particular search engine and search query, information about a position at which the index-type search engine displayed the destination in search results for said query. | 0.846715 |
7,895,116 | 10 | 11 | 10. The system of claim 8 wherein, when a price request is received, an expected contribution to the seller utility from that request is calculated such that the optimal price will be the price that maximizes such contribution. | 10. The system of claim 8 wherein, when a price request is received, an expected contribution to the seller utility from that request is calculated such that the optimal price will be the price that maximizes such contribution. 11. The system of claim 10 wherein the utility function is selected from the group consisting of substantially of exponential, piecewise exponential, linear, piecewise linear, and hybrid, and wherein each price optimizer is configurable to be one of a sales target optimizer, a market share optimizer, an event optimizer, a supply-break optimizer, a price watch optimizer, or an other optimizer, and each price optimizer is configurable for implementation as a market share-directed implementation, a sales target-directed implementation, a utility derivative-following implementation, or a rules engine implementation. | 0.5 |
9,311,490 | 1 | 4 | 1. A method, comprising: sending, by a first computing device, to a second computing device, first communication data; receiving, by the first computing device, from the second computing device, second communication data; in response to determining that a data privacy attribute of the second computing device is equivalent to a predetermined data privacy attribute, protecting, by the first computing device, the second communication data, by at least: converting, by the first computing device, the first communication data to a first set of text; converting, by the first computing device, the second communication data to a second set of text; and applying, by the first computing device, a privacy filter to the first set of text to generate a first filtered set of filtered text by removing from the first set of text, any text that is repeated in the second set of text; determining, by the first computing device, a first keyword from the filtered set of text; sending, by the first computing device, to a third computing device, the first keyword; and receiving, by the first computing device, from the third computing device, contextual data associated with the first keyword. | 1. A method, comprising: sending, by a first computing device, to a second computing device, first communication data; receiving, by the first computing device, from the second computing device, second communication data; in response to determining that a data privacy attribute of the second computing device is equivalent to a predetermined data privacy attribute, protecting, by the first computing device, the second communication data, by at least: converting, by the first computing device, the first communication data to a first set of text; converting, by the first computing device, the second communication data to a second set of text; and applying, by the first computing device, a privacy filter to the first set of text to generate a first filtered set of filtered text by removing from the first set of text, any text that is repeated in the second set of text; determining, by the first computing device, a first keyword from the filtered set of text; sending, by the first computing device, to a third computing device, the first keyword; and receiving, by the first computing device, from the third computing device, contextual data associated with the first keyword. 4. The method of claim 1 , wherein each of the first communication data and the second communication data is text data. | 0.782051 |
8,135,669 | 8 | 9 | 8. A method according to claim 1 , wherein producing the result page comprises producing the result page such that the result page contains one or more elements for allowing the second user to view the entries in the first metadata object and add entries to the first metadata object when the first metadata object is linked to a combination of the given document and the query. | 8. A method according to claim 1 , wherein producing the result page comprises producing the result page such that the result page contains one or more elements for allowing the second user to view the entries in the first metadata object and add entries to the first metadata object when the first metadata object is linked to a combination of the given document and the query. 9. A method according to claim 8 , further comprising: using users' interaction with metadata objects within a search context to create recommender systems. | 0.5 |
8,055,501 | 7 | 8 | 7. A speech synthesizer generating system, comprising: a speech output specification, describing a plurality of sentence patterns and a plurality of vocabularies desired to be synthesized, a software or a hardware platform for a speech synthesizer, and conditions of a speaker; a source corpus of a target language, comprising a plurality of phonetic units of the target language; a recording script generator, receiving the speech output specification and generating a recording script according to the speech output specification so that a customized or expanded speech material is recorded according to the recording script; a recording interface tool module, for recording the customized or expanded speech material; a synthesis unit generator, receiving the customized or expanded speech material, converting the speech material into speech synthesis units, and combining the synthesis units into the source corpus; and a speech synthesizer generator, receiving the speech output specification and generating a speech synthesizer which can be executed on an appointed platform after selecting a plurality of synthesis units from the source corpus according to the speech output specification, wherein the speech synthesizer comprises a speech synthesis unit inventory and a speech synthesis engine. | 7. A speech synthesizer generating system, comprising: a speech output specification, describing a plurality of sentence patterns and a plurality of vocabularies desired to be synthesized, a software or a hardware platform for a speech synthesizer, and conditions of a speaker; a source corpus of a target language, comprising a plurality of phonetic units of the target language; a recording script generator, receiving the speech output specification and generating a recording script according to the speech output specification so that a customized or expanded speech material is recorded according to the recording script; a recording interface tool module, for recording the customized or expanded speech material; a synthesis unit generator, receiving the customized or expanded speech material, converting the speech material into speech synthesis units, and combining the synthesis units into the source corpus; and a speech synthesizer generator, receiving the speech output specification and generating a speech synthesizer which can be executed on an appointed platform after selecting a plurality of synthesis units from the source corpus according to the speech output specification, wherein the speech synthesizer comprises a speech synthesis unit inventory and a speech synthesis engine. 8. The speech synthesizer generating system according to claim 7 , wherein the sentence pattern and the vocabulary in the speech output specification are defined according to syntax patterns or semantics patterns. | 0.5 |
9,662,143 | 19 | 20 | 19. The polyaxial bone anchor assembly of claim 17 , wherein the insert has upwardly extending arms forming a U-shaped insert channel for receiving the longitudinal connecting member therebetween, and wherein the at least one lateral projection further comprises laterally-projecting top flange portions disposed on the upwardly extending arms. | 19. The polyaxial bone anchor assembly of claim 17 , wherein the insert has upwardly extending arms forming a U-shaped insert channel for receiving the longitudinal connecting member therebetween, and wherein the at least one lateral projection further comprises laterally-projecting top flange portions disposed on the upwardly extending arms. 20. The polyaxial bone anchor assembly of claim 19 , wherein the laterally-projecting top flange portions include an inclined top surface that is operable to engage with an complimentary inclined lower surface of a closure. | 0.5 |
8,869,269 | 3 | 4 | 3. The method of claim 2 , wherein modifying the first domain name further comprises replacing the at least one first character of the first domain name with at least one second character, wherein the at least one first character is an imitation of the at least one second character. | 3. The method of claim 2 , wherein modifying the first domain name further comprises replacing the at least one first character of the first domain name with at least one second character, wherein the at least one first character is an imitation of the at least one second character. 4. The method of claim 3 , wherein the at least one first character comprises a punctuation mark, wherein the punctuation mark is used to imitate a portion of the at least one second character. | 0.5 |
7,529,753 | 1 | 13 | 1. A computer accessible storage hardware having thereon stored a system for providing application-layer functionality between one or more database clients and one or more database servers, the system comprising: one or more decoders residing at a decoding layer above a network layer, the decoders residing at a first network location between one or more database clients residing at one or more second network locations and one or more database servers residing at one or more third network locations, the decoders being operable to: receive database messages communicated from the database clients and intended for the database servers and database messages communicated from the database servers and intended for the database clients; decode the database messages; extract query-language statements from the database messages; a caching application residing at an application layer above the decoding layer, the caching application residing at the first network location, the caching application being operable to: receive query-language statements extracted at the decoders comprising queries; receive query-language statements extracted at the decoders comprising query results corresponding to the queries; record the queries and the query results corresponding to the queries in a cache residing at the first network location wherein the queries are associated with a corresponding query result; a monitoring application operable to receive query-language statements extracted at the decoders and record observations on the database messages based at least in part on the query-language statements extracted at the decoders, wherein at least one observation is associated with a query result stored in the cache and communicate one or more observations associated with the queries to one or more computing systems at a fourth network location according to the needs of the one or more computer systems, wherein at least one of the computer systems maintains a web cache and is operable to modify the web cache based upon the communicated observations wherein observations on the database messages based at least in part on the query-language statement extracted at the decoders comprise the following: subject database instances of the query-language statements; network protocols and versions of the network protocols used to communicate the database messages; devices hosting the subject database instances of the query-language statements; hostnames, Internet Protocol (IP) addresses, Media Access Control (MAC) addresses, and network ports of the database servers; operating systems (OSs), versions of the OSs, and attributes of the OSs of devices hosting the subject database instances; devices hosting the clients; and a number of queries communicated from each of the clients to each of one or more database instances; and an application residing at an application layer above the decoding layer, the application residing at the first network location, the application being operable to receive and process query-language statements extracted at the decoders. | 1. A computer accessible storage hardware having thereon stored a system for providing application-layer functionality between one or more database clients and one or more database servers, the system comprising: one or more decoders residing at a decoding layer above a network layer, the decoders residing at a first network location between one or more database clients residing at one or more second network locations and one or more database servers residing at one or more third network locations, the decoders being operable to: receive database messages communicated from the database clients and intended for the database servers and database messages communicated from the database servers and intended for the database clients; decode the database messages; extract query-language statements from the database messages; a caching application residing at an application layer above the decoding layer, the caching application residing at the first network location, the caching application being operable to: receive query-language statements extracted at the decoders comprising queries; receive query-language statements extracted at the decoders comprising query results corresponding to the queries; record the queries and the query results corresponding to the queries in a cache residing at the first network location wherein the queries are associated with a corresponding query result; a monitoring application operable to receive query-language statements extracted at the decoders and record observations on the database messages based at least in part on the query-language statements extracted at the decoders, wherein at least one observation is associated with a query result stored in the cache and communicate one or more observations associated with the queries to one or more computing systems at a fourth network location according to the needs of the one or more computer systems, wherein at least one of the computer systems maintains a web cache and is operable to modify the web cache based upon the communicated observations wherein observations on the database messages based at least in part on the query-language statement extracted at the decoders comprise the following: subject database instances of the query-language statements; network protocols and versions of the network protocols used to communicate the database messages; devices hosting the subject database instances of the query-language statements; hostnames, Internet Protocol (IP) addresses, Media Access Control (MAC) addresses, and network ports of the database servers; operating systems (OSs), versions of the OSs, and attributes of the OSs of devices hosting the subject database instances; devices hosting the clients; and a number of queries communicated from each of the clients to each of one or more database instances; and an application residing at an application layer above the decoding layer, the application residing at the first network location, the application being operable to receive and process query-language statements extracted at the decoders. 13. The computer accessible storage hardware of claim 1 , wherein the network layer comprises a Transport Control Protocol over Internet Protocol (TCP/IP) interface or an Interprocess Communication (IPC) interface. | 0.804388 |
8,041,701 | 3 | 4 | 3. The method of claim 1 wherein said representation is displayed separately from said first search result data. | 3. The method of claim 1 wherein said representation is displayed separately from said first search result data. 4. The method of claim 3 wherein said representation is displayed in a browser toolbar. | 0.5 |
9,632,772 | 2 | 5 | 2. The computer program product of claim 1 , wherein the wizard uses an XML plug-in to determine how to handle the collection, and the reconstructing using the wizard comprises: retrieving the one or more base objects for the collection using the one or more annotations determined from the one or more objects of the collection; retrieving a template for reconstructing the collection as an XML using the retrieved one or more base objects for the collection; and reconstructing the collection by wrapping the retrieved one or more base objects as elements in the retrieved template. | 2. The computer program product of claim 1 , wherein the wizard uses an XML plug-in to determine how to handle the collection, and the reconstructing using the wizard comprises: retrieving the one or more base objects for the collection using the one or more annotations determined from the one or more objects of the collection; retrieving a template for reconstructing the collection as an XML using the retrieved one or more base objects for the collection; and reconstructing the collection by wrapping the retrieved one or more base objects as elements in the retrieved template. 5. The computer program product of claim 2 , wherein the wizard uses the template comprising a hash, map, or list to convert a complex object into a simpler object. | 0.531429 |
9,442,922 | 1 | 10 | 1. A method for updating a reordering model of a statistical machine translation system comprising: at a first time, receiving new training data for retraining an existing statistical machine translation system, the new training data comprising at least one sentence pair, each of the at least one sentence pair comprising a source sentence in a source language and a target sentence in a target language; extracting phrase pairs from the new training data, each phrase pair including a source language phrase and a target language phrase; generating a new reordering file from the extracted phrase pairs, the new reordering file including a set of the phrase pairs extracted from the new training data; updating a reordering model of the existing statistical machine translation system based on the new reordering file, the reordering model including a reordering table, the reordering table comprising phrase pairs and a set of features, the set of features comprising, for each of a set of orientation types, at least one feature which is a function of a count of the orientation type for the respective phrase pair, each phrase pair in the reordering table occurring only once, and wherein the updating of the reordering model includes merging an existing reordering table with the new reordering file or merging the existing reordering table with a new reordering table generated from the new reordering file, the merging including updating feature scores for each of the orientation types for at least some of the phrase pairs based on the counts stored in the existing reordering table; at a second time after the first time, receiving new training data for training the existing statistical machine translation system, the new training data comprising at least one sentence pair, the sentence pair comprising a source sentence in the source language and a target sentence in the target language; and reiterating the extracting of phrase pairs, generating of the new reordering file and the updating the reordering model based on the new training data received at the second time, wherein at least one of the extracting phrase pairs, generating the new reordering file, and updating the reordering model is performed with a computer processor. | 1. A method for updating a reordering model of a statistical machine translation system comprising: at a first time, receiving new training data for retraining an existing statistical machine translation system, the new training data comprising at least one sentence pair, each of the at least one sentence pair comprising a source sentence in a source language and a target sentence in a target language; extracting phrase pairs from the new training data, each phrase pair including a source language phrase and a target language phrase; generating a new reordering file from the extracted phrase pairs, the new reordering file including a set of the phrase pairs extracted from the new training data; updating a reordering model of the existing statistical machine translation system based on the new reordering file, the reordering model including a reordering table, the reordering table comprising phrase pairs and a set of features, the set of features comprising, for each of a set of orientation types, at least one feature which is a function of a count of the orientation type for the respective phrase pair, each phrase pair in the reordering table occurring only once, and wherein the updating of the reordering model includes merging an existing reordering table with the new reordering file or merging the existing reordering table with a new reordering table generated from the new reordering file, the merging including updating feature scores for each of the orientation types for at least some of the phrase pairs based on the counts stored in the existing reordering table; at a second time after the first time, receiving new training data for training the existing statistical machine translation system, the new training data comprising at least one sentence pair, the sentence pair comprising a source sentence in the source language and a target sentence in the target language; and reiterating the extracting of phrase pairs, generating of the new reordering file and the updating the reordering model based on the new training data received at the second time, wherein at least one of the extracting phrase pairs, generating the new reordering file, and updating the reordering model is performed with a computer processor. 10. The method of claim 1 , wherein, the merging compares lines of the reordering tables sequentially and where two lines match the method includes converting the feature scores in each line into counts, summing counts for each orientation, as well as the total count, and converting the updated counts of the orientations back to scores. | 0.5 |
5,526,268 | 13 | 15 | 13. An apparatus for monitoring a process, comprising: a digital processor coupled to an industrial process via means for encoding values of process parameters and process configuration information, the processor being programmed to control a display device and to present on the display device a diagrammatic display including text and graphics for simulating a condition of the process; a memory coupled to the processor, containing programmed definitions of the text and graphics included in the diagrammatic display during predetermined process conditions, the processor normally formatting the diagrammatic display at least partly as a function of said definitions, the memory further containing alternative definitions of at least a portion of at least a subset of one of the text and the graphics, the alternative definitions being different than the programmed definitions but representing the same said condition of the process; a user operated control input coupled to the processor and operable with the processor to select at least a subset of the information on the diagrammatic display, the processor switching between the alternative definitions and thereby converting the subset of the diagrammatic display from one format to another format during operation of the apparatus for monitoring the process. | 13. An apparatus for monitoring a process, comprising: a digital processor coupled to an industrial process via means for encoding values of process parameters and process configuration information, the processor being programmed to control a display device and to present on the display device a diagrammatic display including text and graphics for simulating a condition of the process; a memory coupled to the processor, containing programmed definitions of the text and graphics included in the diagrammatic display during predetermined process conditions, the processor normally formatting the diagrammatic display at least partly as a function of said definitions, the memory further containing alternative definitions of at least a portion of at least a subset of one of the text and the graphics, the alternative definitions being different than the programmed definitions but representing the same said condition of the process; a user operated control input coupled to the processor and operable with the processor to select at least a subset of the information on the diagrammatic display, the processor switching between the alternative definitions and thereby converting the subset of the diagrammatic display from one format to another format during operation of the apparatus for monitoring the process. 15. The apparatus of claim 13, wherein the alternative definitions include alternative graphical presentations representing the condition of the process. | 0.788674 |
10,157,174 | 19 | 20 | 19. The data processing system of claim 16 wherein evaluating the first and contrary set of hypotheses further comprises determining a confidence level for each answer based on the first and second set of evidence for candidate answers supporting each hypothesis. | 19. The data processing system of claim 16 wherein evaluating the first and contrary set of hypotheses further comprises determining a confidence level for each answer based on the first and second set of evidence for candidate answers supporting each hypothesis. 20. The data processing system of claim 19 further comprising ranking the set of answers based on the confidence levels for each set of hypotheses. | 0.5 |
9,741,336 | 7 | 11 | 7. A system comprising: a processor configured to perform speech recognition; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: nominating, via a processor configured to use a partially observable Markov decision process in parallel with a conventional dialog state, a set of dialog actions and a set of contextual features; and generating an audible response in a dialog between a user and a spoken dialog system based at least in part on the set of contextual features. | 7. A system comprising: a processor configured to perform speech recognition; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: nominating, via a processor configured to use a partially observable Markov decision process in parallel with a conventional dialog state, a set of dialog actions and a set of contextual features; and generating an audible response in a dialog between a user and a spoken dialog system based at least in part on the set of contextual features. 11. The system of claim 7 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, cause the processor to perform operations comprising: assigning a reward to the set of dialog actions as part of the machine learning algorithm. | 0.558642 |
4,493,655 | 1 | 4 | 1. A radio-controlled teaching device comprising in combination: a teacher transmitter unit containing tone generation means, timing means associated with and controlling the duration of tones generated by said tone generation means, manual switching means operatively connected to said timing means for actuating said timing means and said tone generation means at selected points during oral reading of textual material or test material, counting and readout means operatively associated with said timing means for counting and displaying the number of times said tone generation means are actuated, manual reset means operatively connected to said counting and readout means for selectively resetting said readout means to zero, and a radio transmitter operatively coupled to the output of said tone generation means for transmitting tones generated by said tone generation means; and a plurality of portable student receiver units containing a battery power supply, a radio receiver tuned to the carrier frequency of said transmitter, a tone decoder operatively connected to the output of said radio receiver, a first timing means operatively connected to and actuated by the output of said tone decoder for providing a short time period during which a student is expected to respond at said selected points during oral reading of textual or test material, a response switch which is momentarily closed by the student at said selected points during oral reading of textual or test material, a second timing means operatively connected to and actuated by said response switch for providing a brief time period when said response switch is closed, a first logic gate and a second logic gate operatively connected to said first and second timing means wherein a "right" pulse is conducted by said first logic gate when said response switch is momentarily closed during said short time period of said first timing means and, wherein a "wrong" pulse is conducted by said second logic gate when said response switch is momentarily closed when said short time period of said first timing means is not occuring, a third timing means operatively connected to the outputs of said first logic gate and second logic gate and actuated by said "right" pulse or "wrong" pulse for momentarily disabling said second timing means and said first logic gate and second logic gate when said response switch is momentarily closed, a first counter operatively connected to the output of said first logic gate, whereby a said "right" pulse advances said first counter one count when said "right" pulse occurs, a second counter operatively connected to said second logic gate, whereby said "wrong" pulse advances said second counter one count when said "wrong" pulse occurs, first decoder/drivers and liquid crystal readouts operatively connected to the outputs of said first counter for displaying the current count of said first counter, and second decoder/drivers and liquid crystal readouts operatively connected to the outputs of said second counter for displaying the current count of said second counter. | 1. A radio-controlled teaching device comprising in combination: a teacher transmitter unit containing tone generation means, timing means associated with and controlling the duration of tones generated by said tone generation means, manual switching means operatively connected to said timing means for actuating said timing means and said tone generation means at selected points during oral reading of textual material or test material, counting and readout means operatively associated with said timing means for counting and displaying the number of times said tone generation means are actuated, manual reset means operatively connected to said counting and readout means for selectively resetting said readout means to zero, and a radio transmitter operatively coupled to the output of said tone generation means for transmitting tones generated by said tone generation means; and a plurality of portable student receiver units containing a battery power supply, a radio receiver tuned to the carrier frequency of said transmitter, a tone decoder operatively connected to the output of said radio receiver, a first timing means operatively connected to and actuated by the output of said tone decoder for providing a short time period during which a student is expected to respond at said selected points during oral reading of textual or test material, a response switch which is momentarily closed by the student at said selected points during oral reading of textual or test material, a second timing means operatively connected to and actuated by said response switch for providing a brief time period when said response switch is closed, a first logic gate and a second logic gate operatively connected to said first and second timing means wherein a "right" pulse is conducted by said first logic gate when said response switch is momentarily closed during said short time period of said first timing means and, wherein a "wrong" pulse is conducted by said second logic gate when said response switch is momentarily closed when said short time period of said first timing means is not occuring, a third timing means operatively connected to the outputs of said first logic gate and second logic gate and actuated by said "right" pulse or "wrong" pulse for momentarily disabling said second timing means and said first logic gate and second logic gate when said response switch is momentarily closed, a first counter operatively connected to the output of said first logic gate, whereby a said "right" pulse advances said first counter one count when said "right" pulse occurs, a second counter operatively connected to said second logic gate, whereby said "wrong" pulse advances said second counter one count when said "wrong" pulse occurs, first decoder/drivers and liquid crystal readouts operatively connected to the outputs of said first counter for displaying the current count of said first counter, and second decoder/drivers and liquid crystal readouts operatively connected to the outputs of said second counter for displaying the current count of said second counter. 4. A radio-controlled teaching device according to claim 1, wherein said tone generation means of said teacher transmitter unit are actuated by the teacher during oral reading by said teacher of a correct answer associated with a previously presented multiple-choice or true or false question, whereby a tone signal is transmitted by said teacher transmitter unit to a plurality of said student receiver units, one of said student receiver units being provided for each student of a classroom, said tone signal being detected by all of said student receiver units and causing a "right" score to be displayed by an associated digital readout when said response switch of a student receiver unit is momentarily closed within a short time period following reception of said tone signal, and causing a "wrong" score to be displayed by an associated digital readout when said response switch is momentarily closed when said tone signal has not been transmitted and received for extemporaneously testing each member of a school classroom without requiring written student responses. | 0.5 |
8,386,926 | 1 | 3 | 1. A computer-implemented method comprising: receiving, at a server, a valid login request from a user for an account maintained on the server; identifying, on the server, a set of text-entry preferences associated with the account, wherein the text-entry preferences are configured for use with a plurality of network-based applications; receiving, at the server, a request from the user to execute a first network-based application on the server; receiving, from the user at the server, user-entered text associated with the first network-based application; applying, by the server, the set of text-entry preferences to the received user-entered text; and providing, after applying the set of text-entry preferences, the received user-entered text to the first network-based application. | 1. A computer-implemented method comprising: receiving, at a server, a valid login request from a user for an account maintained on the server; identifying, on the server, a set of text-entry preferences associated with the account, wherein the text-entry preferences are configured for use with a plurality of network-based applications; receiving, at the server, a request from the user to execute a first network-based application on the server; receiving, from the user at the server, user-entered text associated with the first network-based application; applying, by the server, the set of text-entry preferences to the received user-entered text; and providing, after applying the set of text-entry preferences, the received user-entered text to the first network-based application. 3. The computer-implemented method of claim 1 , wherein the set of text-entry preferences are included in one of a table and a database. | 0.930256 |
6,112,304 | 2 | 20 | 2. The method of claim 1, wherein each location provides access to a processor for executing instructions and each location provides a memory accessible to the processor for storing instructions. | 2. The method of claim 1, wherein each location provides access to a processor for executing instructions and each location provides a memory accessible to the processor for storing instructions. 20. The method of claim 2, wherein the providing step includes providing a user denizen which handles exceptions internally to limit the impact of execution errors. | 0.583756 |
9,514,737 | 1 | 9 | 1. A navigation apparatus including a voice receiver to receive an instruction by voice input, and a voice recognizer to carry out voice recognition of the instruction received by the voice receiver, the navigation apparatus comprising: a recognition vocabulary comprehension level decider to decide a user comprehension level of a recognition vocabulary for instructions recognizable by the voice recognizer, from at least one of correction operation frequency and time-out frequency in an operation of recognizing the instruction which is carried out during the voice recognition by the voice recognizer and corresponds to the instruction; an operational transition determiner to determine an operational transition from a plurality of potential operational transitions in accordance with a decision result of the recognition vocabulary comprehension level decider, each of the potential operational transitions including a different number of input steps by which the instruction is voice-recognized, such that different input steps correspond to different subsets of the recognition vocabulary for each potential operation transition that includes multiple input steps; and an operational transition provider to provide the operational transition determined by the operational transition determiner, wherein the operational transition determiner, when determining the operational transition in accordance with the decision result output from the recognition vocabulary comprehension level decider, switches the operational transition thereby limiting an input content per step by increasing the number of input steps in a specific operational transition, or reducing the number of input steps by increasing an amount of information capable of being input per step in the specific operational transition. | 1. A navigation apparatus including a voice receiver to receive an instruction by voice input, and a voice recognizer to carry out voice recognition of the instruction received by the voice receiver, the navigation apparatus comprising: a recognition vocabulary comprehension level decider to decide a user comprehension level of a recognition vocabulary for instructions recognizable by the voice recognizer, from at least one of correction operation frequency and time-out frequency in an operation of recognizing the instruction which is carried out during the voice recognition by the voice recognizer and corresponds to the instruction; an operational transition determiner to determine an operational transition from a plurality of potential operational transitions in accordance with a decision result of the recognition vocabulary comprehension level decider, each of the potential operational transitions including a different number of input steps by which the instruction is voice-recognized, such that different input steps correspond to different subsets of the recognition vocabulary for each potential operation transition that includes multiple input steps; and an operational transition provider to provide the operational transition determined by the operational transition determiner, wherein the operational transition determiner, when determining the operational transition in accordance with the decision result output from the recognition vocabulary comprehension level decider, switches the operational transition thereby limiting an input content per step by increasing the number of input steps in a specific operational transition, or reducing the number of input steps by increasing an amount of information capable of being input per step in the specific operational transition. 9. The navigation apparatus according to claim 1 , wherein the navigation apparatus, when switching the operational transition in accordance with a decision result by the recognition vocabulary comprehension level decider, provides a user with a manner of the alteration before the alteration through voice output or screen output. | 0.634658 |
9,373,359 | 8 | 14 | 8. A method for transcribing dialog associated with moving image content, the method comprising: storing, in a provider computer system including at least one electronic processor and at least one data storage device, a master version of moving image content being classified by title, producer or genre; providing access to a copy of the master version of the moving image content by multiple client devices associated with multiple transcribers, wherein each client device includes at least one electronic processor and at least one data storage device; transmitting an interface to at least one of the multiple client devices, wherein the interface is programmed with instructions for: (i) requesting the copy of the master version of the moving image content from the provider computer system, (ii) interactively playing the moving image content, (iii) receiving input data representative of a transcription of dialog associated with the master version of the moving image content, and (iv) receiving input data indicative of at least one starting time-stamp and at least one ending time-stamp for at least one segment of multiple segments of the transcription; receiving, in the provider computer system, the transcription of the at least one segment of the multiple segments, and the input data indicative of the at least one starting time-stamp and the at least one ending time-stamp for the at least one segment of the multiple segments of the transcription of the dialog associated with the master version of the moving image content; and storing, in the provider computer system, the transcription together with the starting and ending time-stamps for each segment of the multiple segments as a copy of the master version of the moving image content being reclassified as transcribed and time-stamped. | 8. A method for transcribing dialog associated with moving image content, the method comprising: storing, in a provider computer system including at least one electronic processor and at least one data storage device, a master version of moving image content being classified by title, producer or genre; providing access to a copy of the master version of the moving image content by multiple client devices associated with multiple transcribers, wherein each client device includes at least one electronic processor and at least one data storage device; transmitting an interface to at least one of the multiple client devices, wherein the interface is programmed with instructions for: (i) requesting the copy of the master version of the moving image content from the provider computer system, (ii) interactively playing the moving image content, (iii) receiving input data representative of a transcription of dialog associated with the master version of the moving image content, and (iv) receiving input data indicative of at least one starting time-stamp and at least one ending time-stamp for at least one segment of multiple segments of the transcription; receiving, in the provider computer system, the transcription of the at least one segment of the multiple segments, and the input data indicative of the at least one starting time-stamp and the at least one ending time-stamp for the at least one segment of the multiple segments of the transcription of the dialog associated with the master version of the moving image content; and storing, in the provider computer system, the transcription together with the starting and ending time-stamps for each segment of the multiple segments as a copy of the master version of the moving image content being reclassified as transcribed and time-stamped. 14. The method of claim 8 , wherein at least one of the multiple client devices includes a network-enabled mobile phone or a personal digital assistant. | 0.703125 |
8,554,696 | 15 | 19 | 15. A non-transitory, tangible computer-readable medium having computer-executable code, when executed by a computer operable to: access an inverted index comprising a plurality of inverted index lists, each inverted index list corresponding to a term, each inverted index list comprising a term identifier of the term and one or more document identifiers indicating one or more documents of a document set in which the term appears; generating a plurality of ordered pairs from the inverted index, each ordered pair comprising a term identifier and a document identifier of an inverted index list, the ordered pairs being organized primarily based on the document identifiers of the ordered pairs; and generate a term identifier index according to the inverted index, the term identifier index comprising a plurality of sections, each section corresponding to a document, each section comprising one or more term identifiers of one or more terms that appear in the document, the generating the term identifier index according to the inverted index comprising organizing the term identifiers of the ordered pairs in the sections of the term identifier index, wherein organizing the term identifiers of the ordered pairs comprises: removing a selected ordered pair from a data structure; generating a next ordered pair from the inverted index, the next ordered pair comprising a term identifier equivalent to a term identifier of the selected ordered pair; and placing the next ordered pair into the data structure. | 15. A non-transitory, tangible computer-readable medium having computer-executable code, when executed by a computer operable to: access an inverted index comprising a plurality of inverted index lists, each inverted index list corresponding to a term, each inverted index list comprising a term identifier of the term and one or more document identifiers indicating one or more documents of a document set in which the term appears; generating a plurality of ordered pairs from the inverted index, each ordered pair comprising a term identifier and a document identifier of an inverted index list, the ordered pairs being organized primarily based on the document identifiers of the ordered pairs; and generate a term identifier index according to the inverted index, the term identifier index comprising a plurality of sections, each section corresponding to a document, each section comprising one or more term identifiers of one or more terms that appear in the document, the generating the term identifier index according to the inverted index comprising organizing the term identifiers of the ordered pairs in the sections of the term identifier index, wherein organizing the term identifiers of the ordered pairs comprises: removing a selected ordered pair from a data structure; generating a next ordered pair from the inverted index, the next ordered pair comprising a term identifier equivalent to a term identifier of the selected ordered pair; and placing the next ordered pair into the data structure. 19. The medium of claim 15 , further operable to: initialize an ontology affinity matrix comprising a plurality of entries, each entry comprising a count value, each entry corresponding to an affinity of a term pair comprising a first term and a second term; and increment the count value of an entry corresponding to the affinity of a selected term pair for each section of the term identifier index that comprises the term identifiers of the selected term pair. | 0.644939 |
8,954,374 | 1 | 14 | 1. A method for creating and enabling access to a community-augmented map, wherein the method comprises: uploading user-generated content, wherein said user-generated content comprises content pertaining to one or more locations on a map and content pertaining to a relationship between the one or more locations and one or more additional locations on a map, and wherein said user-generated content comprises multiple modalities; processing the user-generated content and storing the user-generated content in an intelligent knowledgebase; applying one or more existing items of user-generated content from the intelligent knowledgebase to the uploaded user-generated content to infer one or more characteristics of one or more locations on the map based on the content pertaining to the relationship between the one or more locations in the uploaded user-generated content and the one or more additional locations on a map, wherein said one or more inferred characteristics are inferred from one or more human-originated non-numeric relationships, derived via one or more human community members, of the one or more locations relative to one or more surrounding locations; retrieving the one or more inferred characteristics of the one or more locations on the map from the intelligent knowledgebase; augmenting metadata on the map based on the one or more inferred characteristics, wherein said augmenting comprises (i) providing real-time information about one or more locations on the map, (ii) identifying one or more traversable routes between two or more locations on the map, and (iii) super-imposing user-generated content pertaining to one or more locations on the one or more traversable routes; and outputting one of the one or more traversable routes in response to a query comprising a source location name and a destination location name, wherein said output traversable route comprises (i) a sequential list of multiple location names that represents a path traversal from the source location to the destination location and (ii) at least one inferred characteristic, from the one or more inferred characteristics, associated with each of the multiple location names in the sequential list. | 1. A method for creating and enabling access to a community-augmented map, wherein the method comprises: uploading user-generated content, wherein said user-generated content comprises content pertaining to one or more locations on a map and content pertaining to a relationship between the one or more locations and one or more additional locations on a map, and wherein said user-generated content comprises multiple modalities; processing the user-generated content and storing the user-generated content in an intelligent knowledgebase; applying one or more existing items of user-generated content from the intelligent knowledgebase to the uploaded user-generated content to infer one or more characteristics of one or more locations on the map based on the content pertaining to the relationship between the one or more locations in the uploaded user-generated content and the one or more additional locations on a map, wherein said one or more inferred characteristics are inferred from one or more human-originated non-numeric relationships, derived via one or more human community members, of the one or more locations relative to one or more surrounding locations; retrieving the one or more inferred characteristics of the one or more locations on the map from the intelligent knowledgebase; augmenting metadata on the map based on the one or more inferred characteristics, wherein said augmenting comprises (i) providing real-time information about one or more locations on the map, (ii) identifying one or more traversable routes between two or more locations on the map, and (iii) super-imposing user-generated content pertaining to one or more locations on the one or more traversable routes; and outputting one of the one or more traversable routes in response to a query comprising a source location name and a destination location name, wherein said output traversable route comprises (i) a sequential list of multiple location names that represents a path traversal from the source location to the destination location and (ii) at least one inferred characteristic, from the one or more inferred characteristics, associated with each of the multiple location names in the sequential list. 14. The method of claim 1 , further comprising providing a system, wherein the system comprises one or more distinct software modules, each of the one or more distinct software modules being embodied on a tangible computer-readable recordable storage medium, and wherein the one or more distinct software modules comprise a knowledgebase module, a location finding module, a path finder module, a location insertion module, a location removal module, an ontology module, a graph database module, an input module and an output module executing on a hardware processor. | 0.58 |
8,503,797 | 19 | 20 | 19. The medium of claim 18 , wherein the instructions for extracting the physical attributes of the scanned document comprises instructions for cropping and/or rotating the scanned document as needed to create a processed scanned document for feature extraction. | 19. The medium of claim 18 , wherein the instructions for extracting the physical attributes of the scanned document comprises instructions for cropping and/or rotating the scanned document as needed to create a processed scanned document for feature extraction. 20. The medium of claim 19 , wherein the instructions for extracting physical attributes of the scanned document comprises instructions for extracting the size of the processed scanned document. | 0.570796 |
9,563,741 | 4 | 5 | 4. The method of claim 3 , wherein automatically extracting the plurality of assertions from the plurality of publications comprises utilizing natural language processing software to derive the plurality of assertions from the text of the plurality of publications. | 4. The method of claim 3 , wherein automatically extracting the plurality of assertions from the plurality of publications comprises utilizing natural language processing software to derive the plurality of assertions from the text of the plurality of publications. 5. The method of claim 4 , wherein the plurality of publications comprise peer-reviewed articles selected by the subject matter experts. | 0.661692 |
9,501,549 | 9 | 11 | 9. The system of claim 8 , wherein determining the ranking score for the particular criterion comprises combining the transformed auxiliary scores to generate a combined auxiliary score, wherein the function comprises a function of the primary score and the combined auxiliary score. | 9. The system of claim 8 , wherein determining the ranking score for the particular criterion comprises combining the transformed auxiliary scores to generate a combined auxiliary score, wherein the function comprises a function of the primary score and the combined auxiliary score. 11. The system of claim 9 , wherein determining the ranking score for the particular criterion comprises: adding the combined auxiliary score to a constant value to generate an adjusted auxiliary score; and determining a product of the adjusted auxiliary score and the primary score. | 0.700212 |
8,612,489 | 1 | 6 | 1. A method for transforming an extensible business reporting language (XBRL) instance into a structured extensible markup language (XML) data model instance, the method comprising: for each of a plurality of concepts indicated in an XBRL schema associated with the XBRL instance, determining concept relationship information for the concept from the XBRL schema, context information indicated in the XBRL instance, and at least one of a plurality of files that constitute a taxonomy set for the XBRL instance; determining attribute information for the concept based, at least in part, on the XBRL schema and at least one of the files that constitute the taxonomy set; generating an XML document with XML elements structured in accordance with the concept relationship information, wherein the XML elements correspond to the plurality of concepts and have attributes set based, at least in part, on the attribute information; populating each of the XML elements with corresponding ones of XBRL facts to yield the structured XML data model instance, wherein the XBRL instance indicates the XBRL facts and the XML data model instance comprises at least the XML document; retrieving an XBRL dimension document via a second reference indicated in the taxonomy set, the XBRL dimension document including at least one hypercube having a plurality of dimensions; adding a parent element to an XML dimension mapping document, the parent element corresponding to the hypercube; and adding to the XML dimension document one or more child elements of the parent element, the one or more child elements representing one or more dimensions in the hypercube. | 1. A method for transforming an extensible business reporting language (XBRL) instance into a structured extensible markup language (XML) data model instance, the method comprising: for each of a plurality of concepts indicated in an XBRL schema associated with the XBRL instance, determining concept relationship information for the concept from the XBRL schema, context information indicated in the XBRL instance, and at least one of a plurality of files that constitute a taxonomy set for the XBRL instance; determining attribute information for the concept based, at least in part, on the XBRL schema and at least one of the files that constitute the taxonomy set; generating an XML document with XML elements structured in accordance with the concept relationship information, wherein the XML elements correspond to the plurality of concepts and have attributes set based, at least in part, on the attribute information; populating each of the XML elements with corresponding ones of XBRL facts to yield the structured XML data model instance, wherein the XBRL instance indicates the XBRL facts and the XML data model instance comprises at least the XML document; retrieving an XBRL dimension document via a second reference indicated in the taxonomy set, the XBRL dimension document including at least one hypercube having a plurality of dimensions; adding a parent element to an XML dimension mapping document, the parent element corresponding to the hypercube; and adding to the XML dimension document one or more child elements of the parent element, the one or more child elements representing one or more dimensions in the hypercube. 6. The method of claim 1 , wherein the at least one of the plurality of files that constitute the taxonomy set for the XBRL instance comprise at least one of a presentation linkbase and a definition linkbase. | 0.83876 |
9,442,810 | 1 | 3 | 1. A system to enable visual management of a service, the system comprising: one or more modules implemented by one or more processors, the one or more modules configured to: receive a specification of an abstract type of a resource on which the service is to be deployed; generate a visual representation of the abstract type of the resource for presentation in a user interface; identify concrete types of resources in an infrastructure environment that correspond to the abstract type of the resource; generate visual representations of the concrete types of resources for presentation in the user interface; based on a detecting of a manipulation of the visual representation of the abstract type of the resource with respect to one of the visual representations of one of the concrete types of resources, establish a mapping between the abstract type of the resource and the one of the concrete types of the resources; establish a binding between the abstract type of the resource and one of the instances of the actual resources, the one of the instances of the actual resources selected from the infrastructure environment based on the establishing of the mapping between the abstract type of the resource and the one of the concrete types of the resources, the establishing of the binding between the abstract type of the resource and one of the instances of the actual resources being performed automatically based on a set of policies for minimizing resource consumption but maintaining service-level agreements; generate a visual representation of the binding between the abstract type of the resource and the one of the instances of the actual resources; send a request to a management system to allocate the one of the instances of the actual resources for deploying of the service; and send a command to a management system to deploy the service such that the service uses the one of the instances of the actual resources. | 1. A system to enable visual management of a service, the system comprising: one or more modules implemented by one or more processors, the one or more modules configured to: receive a specification of an abstract type of a resource on which the service is to be deployed; generate a visual representation of the abstract type of the resource for presentation in a user interface; identify concrete types of resources in an infrastructure environment that correspond to the abstract type of the resource; generate visual representations of the concrete types of resources for presentation in the user interface; based on a detecting of a manipulation of the visual representation of the abstract type of the resource with respect to one of the visual representations of one of the concrete types of resources, establish a mapping between the abstract type of the resource and the one of the concrete types of the resources; establish a binding between the abstract type of the resource and one of the instances of the actual resources, the one of the instances of the actual resources selected from the infrastructure environment based on the establishing of the mapping between the abstract type of the resource and the one of the concrete types of the resources, the establishing of the binding between the abstract type of the resource and one of the instances of the actual resources being performed automatically based on a set of policies for minimizing resource consumption but maintaining service-level agreements; generate a visual representation of the binding between the abstract type of the resource and the one of the instances of the actual resources; send a request to a management system to allocate the one of the instances of the actual resources for deploying of the service; and send a command to a management system to deploy the service such that the service uses the one of the instances of the actual resources. 3. The system of claim 1 , wherein the one or more modules are further configured to send a request to a management system to control the service. | 0.773292 |
7,814,405 | 1 | 7 | 1. A method, embodied in at least one computer system, for automatic association by said computer system of tags with received content items based on type of communication and content state in an activities oriented collaboration tool, comprising: receiving content items from a plurality of content sources at said activities oriented collaboration tool; automatically associating content type tags with corresponding ones of said received content items, wherein each of said content type tags indicates a content source from which a corresponding one of said received content items was received, and further indicates a current state of said corresponding one of said received content items; providing a top level content type tags view, wherein said top level content type tags view includes a list of content type tags automatically associated with received content items across all activities defined in said activities oriented collaboration tool, wherein said top level content type tags view enables a user to select individual content type tags from said list of content type tags automatically associated with received content items across all said activities defined in said activities oriented collaboration tool; and responsive to said user selecting one of said content type tags in said list of content type tags automatically associated with received content items across all activities defined in said activities oriented collaboration tool, displaying a list of those activities defined in said activities oriented collaboration tool that contain at least one received content item with which said user selected content type tag was previously automatically associated. | 1. A method, embodied in at least one computer system, for automatic association by said computer system of tags with received content items based on type of communication and content state in an activities oriented collaboration tool, comprising: receiving content items from a plurality of content sources at said activities oriented collaboration tool; automatically associating content type tags with corresponding ones of said received content items, wherein each of said content type tags indicates a content source from which a corresponding one of said received content items was received, and further indicates a current state of said corresponding one of said received content items; providing a top level content type tags view, wherein said top level content type tags view includes a list of content type tags automatically associated with received content items across all activities defined in said activities oriented collaboration tool, wherein said top level content type tags view enables a user to select individual content type tags from said list of content type tags automatically associated with received content items across all said activities defined in said activities oriented collaboration tool; and responsive to said user selecting one of said content type tags in said list of content type tags automatically associated with received content items across all activities defined in said activities oriented collaboration tool, displaying a list of those activities defined in said activities oriented collaboration tool that contain at least one received content item with which said user selected content type tag was previously automatically associated. 7. The method of claim 1 , further comprising: automatically updating each of said content type tags to indicate state changes in their corresponding received content items. | 0.601382 |
9,158,860 | 19 | 21 | 19. A non-transitory computer readable storage medium storing computer instructions executable by a processor to perform a method comprising: identifying a partial query entered into a search field; providing for display a query completion template, the query completion template provided for display in response to identifying the partial query and being for a category of information associated with one or more terms within the partial query, the query completion template including an interactive field that is user editable and including one or more additional fields, the query completion template defining the number of terms, type of terms, and ordering of terms within a search query formed using the query template; identifying user interaction with the interactive field; updating the display of the query completion template to include the results of the user interaction within the interactive field of the query completion template; identifying user selection of the updated query completion template; and transmitting the updated display of the query completion template as a search query in response to the user selection, the search query including one or more query terms that are based on the results of the user interaction with the interactive field and one or more additional query terms based on the one or more additional fields, the one or more query terms and the one or more additional query terms being ordered based on the ordering of terms defined by the query completion template. | 19. A non-transitory computer readable storage medium storing computer instructions executable by a processor to perform a method comprising: identifying a partial query entered into a search field; providing for display a query completion template, the query completion template provided for display in response to identifying the partial query and being for a category of information associated with one or more terms within the partial query, the query completion template including an interactive field that is user editable and including one or more additional fields, the query completion template defining the number of terms, type of terms, and ordering of terms within a search query formed using the query template; identifying user interaction with the interactive field; updating the display of the query completion template to include the results of the user interaction within the interactive field of the query completion template; identifying user selection of the updated query completion template; and transmitting the updated display of the query completion template as a search query in response to the user selection, the search query including one or more query terms that are based on the results of the user interaction with the interactive field and one or more additional query terms based on the one or more additional fields, the one or more query terms and the one or more additional query terms being ordered based on the ordering of terms defined by the query completion template. 21. The non-transitory computer readable storage medium of claim 19 , wherein the one or more additional fields includes a non-editable field and the one or more additional query terms are defined for the non-editable field. | 0.817886 |
9,395,880 | 1 | 10 | 1. One or more non-transitory computer storage media storing computer executable instructions which when executed perform a method in a computer system for graphically defining a channel for processing messages, the method comprising: displaying, on a display device, a visual channel editor in which graphical representations of channel nodes can be arranged and interconnected to define a channel; receiving user input to the visual channel editor that creates a plurality of graphical representations of channel nodes in the visual channel editor, the plurality of graphical representations including a graphical representation of a source node and at least one graphical representation of a destination node; receiving user input that selects one of the graphical representations, the selected graphical representation corresponding to a first channel node; in response to the selection of the graphical representation, displaying, on the display device, a node configuration panel that displays one or more user interface controls that the user can manipulate to define configurable parameters for the first channel node, wherein the one or more user interface controls displayed in the node configuration panel include one or more fields that each list a number of predefined types for the first channel node that a user can select, and wherein the first channel node is a source node, and wherein the one or more fields include a source field and a format field, the source field for defining a source of messages to be processed in the channel, and the format field for defining a format for the messages; receiving user input to the one or more user interface controls, the user input defining configurable parameters for the first channel node; and using the user input to the one or more user interface controls to automatically generate one or more scripts to implement functionality specified in the defined configurable parameters on messages that are processed by the first channel node. | 1. One or more non-transitory computer storage media storing computer executable instructions which when executed perform a method in a computer system for graphically defining a channel for processing messages, the method comprising: displaying, on a display device, a visual channel editor in which graphical representations of channel nodes can be arranged and interconnected to define a channel; receiving user input to the visual channel editor that creates a plurality of graphical representations of channel nodes in the visual channel editor, the plurality of graphical representations including a graphical representation of a source node and at least one graphical representation of a destination node; receiving user input that selects one of the graphical representations, the selected graphical representation corresponding to a first channel node; in response to the selection of the graphical representation, displaying, on the display device, a node configuration panel that displays one or more user interface controls that the user can manipulate to define configurable parameters for the first channel node, wherein the one or more user interface controls displayed in the node configuration panel include one or more fields that each list a number of predefined types for the first channel node that a user can select, and wherein the first channel node is a source node, and wherein the one or more fields include a source field and a format field, the source field for defining a source of messages to be processed in the channel, and the format field for defining a format for the messages; receiving user input to the one or more user interface controls, the user input defining configurable parameters for the first channel node; and using the user input to the one or more user interface controls to automatically generate one or more scripts to implement functionality specified in the defined configurable parameters on messages that are processed by the first channel node. 10. The one or more computer storage media of claim 1 , wherein the first channel node is a source node, and the predefined types include one or more of CSV, database query results, fixed width, HL7, ISO 8583, JSON, plain text, XML, or X12 (ASC X12). | 0.692875 |
7,551,082 | 12 | 17 | 12. A computer-readable storage medium including computer-executable instructions that, when executed by a computer, cause the computer to: collect data captured at a plurality of locations from objects equipped with a radio frequency identification (RFID) tag including an RFID code, the RFID code including components matched to a trading-related ontology, wherein the trading-related ontology includes interrelated hierarchies of concepts including geography, inventory control, shipping, fulfillment, and ordering; search the collected data using a search engine; and process the collected data in accordance with a rules engine, wherein the rules engine includes encoded business rules associated with one or more operations of a system, wherein the collected data is related to the system. | 12. A computer-readable storage medium including computer-executable instructions that, when executed by a computer, cause the computer to: collect data captured at a plurality of locations from objects equipped with a radio frequency identification (RFID) tag including an RFID code, the RFID code including components matched to a trading-related ontology, wherein the trading-related ontology includes interrelated hierarchies of concepts including geography, inventory control, shipping, fulfillment, and ordering; search the collected data using a search engine; and process the collected data in accordance with a rules engine, wherein the rules engine includes encoded business rules associated with one or more operations of a system, wherein the collected data is related to the system. 17. The computer-readable storage medium of claim 12 , further comprising computer-executable instructions that, when executed by the computer, cause the computer to: perform exact match searching of the collected data; perform fuzzy match searching of the collected data; and perform reasoning-based searching of the collected data. | 0.5 |
9,015,033 | 7 | 8 | 7. A non-transitory computer-readable medium storing a plurality of instructions which, when executed by a processor, cause the processor to perform operations for detecting a sentiment for a short message, the operations comprising: receiving the short message, wherein the short message contains less than 140 characters; obtaining an abstraction of the short message, wherein the obtaining the abstraction of the short message comprises translating the short message into a plurality of features of the short message, wherein the plurality of features comprises syntax features, wherein the syntax features comprise a punctuation feature and an upper case feature; and determining the sentiment of the short message based upon the abstraction, wherein the determining the sentiment of the short message is performed in a hierarchical fashion, wherein the determining the sentiment of the short message comprises: identifying if the short message is subjective based upon the abstraction; and identifying a polarity of the short message based upon the abstraction when the short message is subjective. | 7. A non-transitory computer-readable medium storing a plurality of instructions which, when executed by a processor, cause the processor to perform operations for detecting a sentiment for a short message, the operations comprising: receiving the short message, wherein the short message contains less than 140 characters; obtaining an abstraction of the short message, wherein the obtaining the abstraction of the short message comprises translating the short message into a plurality of features of the short message, wherein the plurality of features comprises syntax features, wherein the syntax features comprise a punctuation feature and an upper case feature; and determining the sentiment of the short message based upon the abstraction, wherein the determining the sentiment of the short message is performed in a hierarchical fashion, wherein the determining the sentiment of the short message comprises: identifying if the short message is subjective based upon the abstraction; and identifying a polarity of the short message based upon the abstraction when the short message is subjective. 8. The non-transitory computer-readable medium of claim 7 , wherein the plurality of features further comprises meta-features. | 0.5 |
8,560,615 | 27 | 29 | 27. A non-transitory computer readable storage medium storing one or more programs for execution by one or more processors of a computer system, the one or more programs in the computer readable storage medium comprising instructions for: receiving a plurality of messages directed to a particular user, each message having a unique message identifier; associating each of the plurality of messages with a respective conversation; associating with each conversation a sender list, the sender list identifying a set of senders of messages included in the conversation; and providing presentation information for displaying a list of conversations and their associated sender lists comprising a set of rows, wherein the presentation information is formatted such that: conversation identifying information for each conversation in the list of conversations is displayed as a single row in the set of rows; and the sender list associated with the conversation is displayed in the same single row, along with the conversation identifying information; and wherein a displayed sender list of at least one respective conversation in the list of conversations identifies two or more distinct senders of messages in the respective conversation. | 27. A non-transitory computer readable storage medium storing one or more programs for execution by one or more processors of a computer system, the one or more programs in the computer readable storage medium comprising instructions for: receiving a plurality of messages directed to a particular user, each message having a unique message identifier; associating each of the plurality of messages with a respective conversation; associating with each conversation a sender list, the sender list identifying a set of senders of messages included in the conversation; and providing presentation information for displaying a list of conversations and their associated sender lists comprising a set of rows, wherein the presentation information is formatted such that: conversation identifying information for each conversation in the list of conversations is displayed as a single row in the set of rows; and the sender list associated with the conversation is displayed in the same single row, along with the conversation identifying information; and wherein a displayed sender list of at least one respective conversation in the list of conversations identifies two or more distinct senders of messages in the respective conversation. 29. The computer readable storage medium of claim 27 , wherein, the at least one respective conversation in the list of conversations includes a message sent by a first sender and one or more messages sent by a second sender, the wherein the instructions for providing presentation information for displaying include instructions for providing presentation information for displaying in a first distinct format an identifier of the first sender in the sender list when the message sent by the first sender has not been viewed or marked as read by the user, and providing presentation information for displaying in second distinct format an identifier of the second sender in the sender list when all the messages sent by the second sender have been viewed or marked as read by the user. | 0.5 |
9,031,962 | 9 | 10 | 9. The method of claim 1 , wherein the ordered and presented one or more items are presented on a display constrained device. | 9. The method of claim 1 , wherein the ordered and presented one or more items are presented on a display constrained device. 10. The method of claim 9 , wherein the display device is a phone, a mobile computing device, or a non-intrusive interface display area of a television. | 0.5 |
7,895,512 | 7 | 8 | 7. A method of expressing a change history for a markup language document comprising: identifying a plurality of source markup language documents and a modification to each of the plurality of source markup language documents; creating a delta document specifying the modifications for each of the plurality of source markup language documents, wherein the delta document is independent of each of the plurality of source markup language documents and is coded in a different language than each of the plurality of source markup language documents, wherein creating the delta document comprises specifying each modification to the plurality of source markup language documents, within the delta document, as an “add” operation or a “remove” operation comprising a reference to a location in the source markup language document of the plurality of source markup language documents to which each respective modification is to be applied and including, within each “add” operation and “remove” operation, a time stamp indicating when the modification was implemented; and storing, within a data storage device, the plurality of source markup language documents and the delta document. | 7. A method of expressing a change history for a markup language document comprising: identifying a plurality of source markup language documents and a modification to each of the plurality of source markup language documents; creating a delta document specifying the modifications for each of the plurality of source markup language documents, wherein the delta document is independent of each of the plurality of source markup language documents and is coded in a different language than each of the plurality of source markup language documents, wherein creating the delta document comprises specifying each modification to the plurality of source markup language documents, within the delta document, as an “add” operation or a “remove” operation comprising a reference to a location in the source markup language document of the plurality of source markup language documents to which each respective modification is to be applied and including, within each “add” operation and “remove” operation, a time stamp indicating when the modification was implemented; and storing, within a data storage device, the plurality of source markup language documents and the delta document. 8. The method of claim 7 , further comprising selectively applying at least one change specified by the delta document to at least one corresponding source markup language document of the plurality of source markup language documents to generate a modified version of the at least one corresponding source markup language document. | 0.5 |
9,761,228 | 1 | 2 | 1. A voice recognition system including a server device and a voice recognition device on a client side, which is connected to said server device, wherein said server device comprises: a server-side receiver that receives voice data from said voice recognition device; a server-side voice recognizer that performs voice recognition on said voice data received by said server-side receiver, and generates a plurality of server-side voice recognition result candidates; and a server-side transmitter that transmits said plurality of server-side voice recognition result candidates generated by said server-side voice recognizer to said voice recognition device, and wherein said voice recognition device comprises: a voice inputter that converts a voice into said voice data; a client-side voice recognizer that performs voice recognition on said voice data converted by said voice inputter, and generates a client-side voice recognition result candidate; a client-side transmitter that transmits said voice data converted by said voice inputter to said server device; a client-side receiver that receives said plurality of server-side voice recognition result candidates transmitted by said server-side transmitter, a recognition result candidate comparator that compares said plurality of server-side voice recognition result candidates received by said client-side receiver, to detect texts having a difference; a recognition result integrator that integrates said client-side voice recognition result candidate and said plurality of server-side voice recognition result candidates by replacing a portion of one of said plurality of server-side voice recognition result candidates with a portion of said client-side voice recognition result candidate based on said client-side voice recognition result candidate, said plurality of server-side voice recognition result candidates, and a detection result provided by said recognition result candidate comparator, to decide a voice recognition result; and an outputter that outputs said voice recognition result decided by said recognition result integrator. | 1. A voice recognition system including a server device and a voice recognition device on a client side, which is connected to said server device, wherein said server device comprises: a server-side receiver that receives voice data from said voice recognition device; a server-side voice recognizer that performs voice recognition on said voice data received by said server-side receiver, and generates a plurality of server-side voice recognition result candidates; and a server-side transmitter that transmits said plurality of server-side voice recognition result candidates generated by said server-side voice recognizer to said voice recognition device, and wherein said voice recognition device comprises: a voice inputter that converts a voice into said voice data; a client-side voice recognizer that performs voice recognition on said voice data converted by said voice inputter, and generates a client-side voice recognition result candidate; a client-side transmitter that transmits said voice data converted by said voice inputter to said server device; a client-side receiver that receives said plurality of server-side voice recognition result candidates transmitted by said server-side transmitter, a recognition result candidate comparator that compares said plurality of server-side voice recognition result candidates received by said client-side receiver, to detect texts having a difference; a recognition result integrator that integrates said client-side voice recognition result candidate and said plurality of server-side voice recognition result candidates by replacing a portion of one of said plurality of server-side voice recognition result candidates with a portion of said client-side voice recognition result candidate based on said client-side voice recognition result candidate, said plurality of server-side voice recognition result candidates, and a detection result provided by said recognition result candidate comparator, to decide a voice recognition result; and an outputter that outputs said voice recognition result decided by said recognition result integrator. 2. The voice recognition system according to claim 1 , wherein said voice recognition device includes an input rule determinator that compares said client-side voice recognition result candidate with utterance rule patterns in each of which a predetermined key word is brought into correspondence with an utterance rule of said predetermined key word, and determines an utterance rule of said voice data, and wherein said recognition result integrator integrates said client-side voice recognition result candidate and said plurality of server-side voice recognition result candidates based on said client-side voice recognition result candidate, said plurality of server-side voice recognition result candidates, the detection result provided by said recognition result candidate comparator, and the utterance rule determined by said input rule determinator. | 0.5 |
7,792,353 | 1 | 7 | 1. A method of machine learning, comprising: (a) obtaining a training set that includes training samples and corresponding assigned classification labels; (b) training an automated classifier against the training set; (c) selecting at least one of the training samples; (d) requesting confirmation/re-labeling of said at least one training sample; (e) in response to step (d), receiving a reply classification label for said at least one training sample; (f) retraining the automated classifier using the reply classification label; and, predicting a label for said at least one training sample, wherein said at least one training sample is selected in step (c) based on a comparison between the assigned classification label and the predicted label for said at least one training sample. | 1. A method of machine learning, comprising: (a) obtaining a training set that includes training samples and corresponding assigned classification labels; (b) training an automated classifier against the training set; (c) selecting at least one of the training samples; (d) requesting confirmation/re-labeling of said at least one training sample; (e) in response to step (d), receiving a reply classification label for said at least one training sample; (f) retraining the automated classifier using the reply classification label; and, predicting a label for said at least one training sample, wherein said at least one training sample is selected in step (c) based on a comparison between the assigned classification label and the predicted label for said at least one training sample. 7. A method according to claim 1 , wherein plural similar training samples are selected and presented for confirmation/re-labeling, as a group of similar training samples, in said requesting step (d). | 0.846861 |
8,204,913 | 23 | 36 | 23. A computer program product having a computer readable storage medium having a computer program recorded therein for converting a dataset into at least one table, said computer program product comprising: computer program code for identifying at least one hierarchical structure in said dataset; computer program code for converting said dataset associated with said at least one identified hierarchical structure, said computer program code comprising: computer program code for determining a node element set for said at least one identified hierarchical structure of said dataset, wherein at least one node element in said node element set is a discrete level of said at least one identified hierarchical structure of said dataset; computer program code for determining one or more nodes of said dataset, each of said one or more nodes being an instance of a node element from said node element set; computer program code for allocating to said instance of said node element a unique node identifier; and computer program code for generating said at least one table, said at least one table containing one or more records, each record corresponding to a respective one of said allocated node identifiers; wherein said node element set is selected to reduce the need for at least one downstream application to assemble data from an elemental level; wherein said at least one table is as required by at least one downstream application; wherein said dataset comprises a plurality of predefined portions of text-based data, at least one of said plurality of predefined portions of text-based data being associated with at least one attribute for organizing at least one of said plurality of predefined portions of text-based data; and wherein said plurality of predefined portions of text-based data comprise at least one modified and stored predefined portion of text based data associated with at least one attribute for organizing at least one of said plurality of predefined portions of text based data and said at least one modified and stored predefined portion of text-based data. | 23. A computer program product having a computer readable storage medium having a computer program recorded therein for converting a dataset into at least one table, said computer program product comprising: computer program code for identifying at least one hierarchical structure in said dataset; computer program code for converting said dataset associated with said at least one identified hierarchical structure, said computer program code comprising: computer program code for determining a node element set for said at least one identified hierarchical structure of said dataset, wherein at least one node element in said node element set is a discrete level of said at least one identified hierarchical structure of said dataset; computer program code for determining one or more nodes of said dataset, each of said one or more nodes being an instance of a node element from said node element set; computer program code for allocating to said instance of said node element a unique node identifier; and computer program code for generating said at least one table, said at least one table containing one or more records, each record corresponding to a respective one of said allocated node identifiers; wherein said node element set is selected to reduce the need for at least one downstream application to assemble data from an elemental level; wherein said at least one table is as required by at least one downstream application; wherein said dataset comprises a plurality of predefined portions of text-based data, at least one of said plurality of predefined portions of text-based data being associated with at least one attribute for organizing at least one of said plurality of predefined portions of text-based data; and wherein said plurality of predefined portions of text-based data comprise at least one modified and stored predefined portion of text based data associated with at least one attribute for organizing at least one of said plurality of predefined portions of text based data and said at least one modified and stored predefined portion of text-based data. 36. The computer program product according to claim 23 , wherein the dataset is an XML encoded dataset and the tables are SQL tables. | 0.822193 |
8,386,478 | 4 | 5 | 4. A method in accordance with claim 1 further comprising displaying a search document collection panel that includes a document repository and the notes panel. | 4. A method in accordance with claim 1 further comprising displaying a search document collection panel that includes a document repository and the notes panel. 5. A method in accordance with claim 4 wherein presenting at least one search result comprises presenting the one or more file identifiers to the user in the search document collection panel. | 0.567873 |
8,572,106 | 1 | 6 | 1. A token stitcher for determining whether an input string of characters matches a regular expression comprising a number of sub-expressions, the token stitcher comprising: a flag bank storing a number of flags, where each flag identifies one or more of the sub-expressions that match the input string; and a token stitcher engine configured to implement an unbounded sub-expression without utilizing resources of a deterministic finite state automaton (DFA) engine or a non-deterministic finite state automaton (NFA) engine and to identify one or lore programs stored in a program memory that are associated with a new token received by the token stitcher, wherein a particular program in the program memory is configured to indicate a match when a particular set of flags in the flag bank are asserted, and wherein the flag bank is configured to discard one or more flags upon satisfaction of a predetermined condition and wherein the token stitcher is implemented by at least one processor-based computing device. | 1. A token stitcher for determining whether an input string of characters matches a regular expression comprising a number of sub-expressions, the token stitcher comprising: a flag bank storing a number of flags, where each flag identifies one or more of the sub-expressions that match the input string; and a token stitcher engine configured to implement an unbounded sub-expression without utilizing resources of a deterministic finite state automaton (DFA) engine or a non-deterministic finite state automaton (NFA) engine and to identify one or lore programs stored in a program memory that are associated with a new token received by the token stitcher, wherein a particular program in the program memory is configured to indicate a match when a particular set of flags in the flag bank are asserted, and wherein the flag bank is configured to discard one or more flags upon satisfaction of a predetermined condition and wherein the token stitcher is implemented by at least one processor-based computing device. 6. The token stitcher of claim 1 , wherein the flag bank is configured to discard, upon satisfaction of the predetermined condition, one flag associated with a sub-expression that was matched at an offset which is further from a current offset being examined in the input string than any other sub-expression. | 0.501613 |
9,978,002 | 4 | 14 | 4. A computer-implemented system, comprising: one or more data processors; and one or more computer readable mediums encoded with instructions that, when executed by the one or more data processors, cause the system to perform operations that include: applying a plurality of view-based classifiers to a digital image, wherein each classifier corresponds to a respective portion of the digital image and is configured to determine whether at least a portion of a type of object is within the respective portion of the digital image to which the classifier is applied; computing, based on the applying, a sum of a plurality of log-likelihood ratios for the plurality of view-based classifiers, each log-likelihood ratio of the plurality of log-likelihood ratios being for a respective classifier of the plurality of view-based classifiers and including a ratio of two graphical probability models, a graphical probability model including a probability distribution over a set of variables where statistical independence and conditional statistical independence exist among various combinations of the variables, and wherein the graphical probability model is a probability distribution representation derived from statistical dependencies among image input variables; determining that the type of object is within the digital image based on the sum satisfying a first predetermined threshold; identifying a detection location of the type of object within the digital image based on respective locations within the digital image to which the plurality of classifiers were applied and the plurality of log-likelihood ratios for the plurality of classifiers; and displaying a marked-up version of the digital image identifying the identified detection location of the type of object within the digital image. | 4. A computer-implemented system, comprising: one or more data processors; and one or more computer readable mediums encoded with instructions that, when executed by the one or more data processors, cause the system to perform operations that include: applying a plurality of view-based classifiers to a digital image, wherein each classifier corresponds to a respective portion of the digital image and is configured to determine whether at least a portion of a type of object is within the respective portion of the digital image to which the classifier is applied; computing, based on the applying, a sum of a plurality of log-likelihood ratios for the plurality of view-based classifiers, each log-likelihood ratio of the plurality of log-likelihood ratios being for a respective classifier of the plurality of view-based classifiers and including a ratio of two graphical probability models, a graphical probability model including a probability distribution over a set of variables where statistical independence and conditional statistical independence exist among various combinations of the variables, and wherein the graphical probability model is a probability distribution representation derived from statistical dependencies among image input variables; determining that the type of object is within the digital image based on the sum satisfying a first predetermined threshold; identifying a detection location of the type of object within the digital image based on respective locations within the digital image to which the plurality of classifiers were applied and the plurality of log-likelihood ratios for the plurality of classifiers; and displaying a marked-up version of the digital image identifying the identified detection location of the type of object within the digital image. 14. The system of claim 4 , wherein the type of object is a human face. | 0.923326 |
9,152,722 | 31 | 32 | 31. The non-transitory computer readable storage medium of claim 30 , wherein determining if the first metadata item is relevant to the content object comprises: generating a content vector based upon the content object; generating a profile vector based upon the first metadata item; and performing a similarity operation to compare the content vector to the profile vector. | 31. The non-transitory computer readable storage medium of claim 30 , wherein determining if the first metadata item is relevant to the content object comprises: generating a content vector based upon the content object; generating a profile vector based upon the first metadata item; and performing a similarity operation to compare the content vector to the profile vector. 32. The non-transitory computer readable storage medium of claim 31 , wherein the content vector comprises numeric weight values based upon the content object, and the profile vector comprises numeric weight values based upon the first metadata item. | 0.5 |
7,937,265 | 6 | 7 | 6. The method of claim 1 , further comprising: counting the number of unique anchors associated with each identified potential paraphrase pair to determine the quality of each potential paraphrase pair; and identifying potential paraphrase pairs that are associated with a larger number of anchors as being of higher quality than potential paraphrase pairs that are associated with a smaller number of anchors. | 6. The method of claim 1 , further comprising: counting the number of unique anchors associated with each identified potential paraphrase pair to determine the quality of each potential paraphrase pair; and identifying potential paraphrase pairs that are associated with a larger number of anchors as being of higher quality than potential paraphrase pairs that are associated with a smaller number of anchors. 7. The method of claim 6 , further comprising: identifying each potential paraphrase pair as being a higher quality paraphrase pair if the number of unique anchors associated with the potential paraphrase pair is equal to or greater than a threshold value. | 0.5 |
5,412,714 | 28 | 29 | 28. The method of claim 26 wherein: the step of storing information comprises the step of including in each symbol string's stored definition an indication of the length of the defined symbol string. | 28. The method of claim 26 wherein: the step of storing information comprises the step of including in each symbol string's stored definition an indication of the length of the defined symbol string. 29. The method of claim 28 wherein: the step of including comprises the step of including in a symbol string's stored definition an indication of a permitted range of length of the defined symbol string. | 0.5 |
10,114,894 | 1 | 5 | 1. A method for online searching, the method comprising: monitoring for user activity occurring at an application other than a search application, wherein the monitoring occurs because of a permission to monitor by the user, the permission being configured by the user in a user profile associated with the user, wherein the search application is used for online searching; detecting, responsive to the monitoring, the user activity at the application; collecting data of the user activity from the application responsive to the detecting; analyzing, using a processor and a memory, the data of the user activity, the user activity occurring at the application; identifying, responsive to the analyzing, a topic of interest of the user; detecting a search term input at the search application; identifying a subject of the search term; modifying the search term using a modifier, wherein the modifier is a term related to the topic of interest, and wherein the online searching occurs responsive to the modified search term; further modifying the search term to use a mandatory term, wherein the mandatory term must appear in a preview of each result in a result set, the result set being responsive to the online searching using the modified search term, wherein the mandatory term is selected by the user from a list of mandatory terms; receiving a result set responsive to the online searching using the modified search term; determining whether a preview of a result in the result set includes a portion corresponding to one of (i) the topic of interest, (ii) the modifier, and (iii) a term stored in a modifier repository in association with the modifier; highlighting the portion; and highlighting in each result in the result set, the mandatory term, wherein the mandatory term is highlighted differently than the portion. | 1. A method for online searching, the method comprising: monitoring for user activity occurring at an application other than a search application, wherein the monitoring occurs because of a permission to monitor by the user, the permission being configured by the user in a user profile associated with the user, wherein the search application is used for online searching; detecting, responsive to the monitoring, the user activity at the application; collecting data of the user activity from the application responsive to the detecting; analyzing, using a processor and a memory, the data of the user activity, the user activity occurring at the application; identifying, responsive to the analyzing, a topic of interest of the user; detecting a search term input at the search application; identifying a subject of the search term; modifying the search term using a modifier, wherein the modifier is a term related to the topic of interest, and wherein the online searching occurs responsive to the modified search term; further modifying the search term to use a mandatory term, wherein the mandatory term must appear in a preview of each result in a result set, the result set being responsive to the online searching using the modified search term, wherein the mandatory term is selected by the user from a list of mandatory terms; receiving a result set responsive to the online searching using the modified search term; determining whether a preview of a result in the result set includes a portion corresponding to one of (i) the topic of interest, (ii) the modifier, and (iii) a term stored in a modifier repository in association with the modifier; highlighting the portion; and highlighting in each result in the result set, the mandatory term, wherein the mandatory term is highlighted differently than the portion. 5. The method of claim 1 , wherein the identifying uses Natural Language Processing (NLP). | 0.890511 |
8,595,175 | 9 | 15 | 9. A computer-readable storage medium configured with data and with instructions that when executed by at least one processor causes the processor(s) to perform a process for managing object persistence, the process comprising the steps of: obtaining an ORM session from an object-relational mapper; receiving in a memory a code which contains calls to a fluent interface in an API Pattern; executing the code with at least one processor; and in the course of executing the code, automatically manipulating a persistence ignorant object within the ORM session in a manner consistent with the API Pattern. | 9. A computer-readable storage medium configured with data and with instructions that when executed by at least one processor causes the processor(s) to perform a process for managing object persistence, the process comprising the steps of: obtaining an ORM session from an object-relational mapper; receiving in a memory a code which contains calls to a fluent interface in an API Pattern; executing the code with at least one processor; and in the course of executing the code, automatically manipulating a persistence ignorant object within the ORM session in a manner consistent with the API Pattern. 15. The configured medium of claim 9 , wherein executing the code includes manipulating a persistence ignorant object in at least one of the following ways: accessing a non-scalar property that depends on the containing object for persistence; checking whether a property of the object is marked as modified; marking a property of the object as modified. | 0.835959 |
8,364,686 | 16 | 17 | 16. The computer-readable memory device of claim 10 , further comprising: one or more instructions to reduce a length of a checksum value, in the set of checksum values, to a particular length, where the checksum value, of the particular length, corresponds to an address of one of the plurality of bits of the fingerprint based on the checksum value matching the address of the one of the plurality of bits of the fingerprint. | 16. The computer-readable memory device of claim 10 , further comprising: one or more instructions to reduce a length of a checksum value, in the set of checksum values, to a particular length, where the checksum value, of the particular length, corresponds to an address of one of the plurality of bits of the fingerprint based on the checksum value matching the address of the one of the plurality of bits of the fingerprint. 17. The computer-readable memory device of claim 16 , where the one or more instructions to reduce the length of the checksum value include one or more instructions to subject the checksum value to a hashing algorithm to reduce the length of the checksum value to the particular length. | 0.508591 |
9,164,962 | 1 | 19 | 1. A computer system for assembling a document, the computer system comprising: one or more processors; a system memory; a display capable of providing information to a user, the display controlled by the one or more processors; and one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by the one or more processors perform the acts of: receiving an entry from the user, the entry comprising a predetermined number of words counted to the left of a current position of a cursor in the document; after receiving the entry, retrieving a plurality of relevant texts from stored text, retrieving the plurality of relevant texts being at least partially based on the entry from the user; after retrieving the plurality of relevant texts from the stored text, displaying the relevant texts on the display; after displaying the retrieved relevant texts on the display, receiving at least one selection of the relevant texts from the user; and after receiving the at least one selection of the relevant text, adding to the document the relevant text from the at least one received selection of the relevant texts. | 1. A computer system for assembling a document, the computer system comprising: one or more processors; a system memory; a display capable of providing information to a user, the display controlled by the one or more processors; and one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by the one or more processors perform the acts of: receiving an entry from the user, the entry comprising a predetermined number of words counted to the left of a current position of a cursor in the document; after receiving the entry, retrieving a plurality of relevant texts from stored text, retrieving the plurality of relevant texts being at least partially based on the entry from the user; after retrieving the plurality of relevant texts from the stored text, displaying the relevant texts on the display; after displaying the retrieved relevant texts on the display, receiving at least one selection of the relevant texts from the user; and after receiving the at least one selection of the relevant text, adding to the document the relevant text from the at least one received selection of the relevant texts. 19. The computer system of claim 1 , wherein the predetermined number is received from the user. | 0.824176 |
8,077,812 | 11 | 15 | 11. For a signal processing application, a receiver-implemented method of detecting a data pattern from a plurality of received signals, the method comprising the steps of: (a) the receiver providing a sequence of scan values derived from a sequence of count values, each scan value selecting one of a set of candidates in a varying pattern, wherein step (a) includes the step of generating the sequence of scan values so as to select each of the set of candidates in a waveform-shaped periodic scan pattern; (b) the receiver generating, for each of the sequence of count values, a difference term between a current metric value and a previous metric value based on a set of coefficients for a received symbol; (c) the receiver combining, for each of a sequence of count values, the difference term with one or more previous difference terms to provide one of a set of metric values; and (d) the receiver generating, based on the set of metric values corresponding to the sequence of scan values, soft-output values corresponding to the data pattern. | 11. For a signal processing application, a receiver-implemented method of detecting a data pattern from a plurality of received signals, the method comprising the steps of: (a) the receiver providing a sequence of scan values derived from a sequence of count values, each scan value selecting one of a set of candidates in a varying pattern, wherein step (a) includes the step of generating the sequence of scan values so as to select each of the set of candidates in a waveform-shaped periodic scan pattern; (b) the receiver generating, for each of the sequence of count values, a difference term between a current metric value and a previous metric value based on a set of coefficients for a received symbol; (c) the receiver combining, for each of a sequence of count values, the difference term with one or more previous difference terms to provide one of a set of metric values; and (d) the receiver generating, based on the set of metric values corresponding to the sequence of scan values, soft-output values corresponding to the data pattern. 15. The method as recited in claim 11 , wherein, for step (b), the metric value for the received symbol is based on an error between the received symbol and one of the set of candidates. | 0.573394 |
8,296,127 | 18 | 20 | 18. A computer system, comprising: a database, storing a first collection of texts in a first language, and a second collection of texts, which are not parallel to said first collection of texts, that are in a second language; a training processor, that processes said texts to determine portions in the first collection of texts whose meaning is substantially the same as portions within the second collection of texts, by comparing a plurality of sentences within the collection of texts, and determining at least one parameter indicative of a first portion within the first collection and a second portion within the second collection, and using said at least one parameter to determine portions which have similar meanings; and a translation processor, using training data based on said portions which have similar meanings to translate input text between said first and second languages. | 18. A computer system, comprising: a database, storing a first collection of texts in a first language, and a second collection of texts, which are not parallel to said first collection of texts, that are in a second language; a training processor, that processes said texts to determine portions in the first collection of texts whose meaning is substantially the same as portions within the second collection of texts, by comparing a plurality of sentences within the collection of texts, and determining at least one parameter indicative of a first portion within the first collection and a second portion within the second collection, and using said at least one parameter to determine portions which have similar meanings; and a translation processor, using training data based on said portions which have similar meanings to translate input text between said first and second languages. 20. The system recited in claim 18 , wherein said training processor uses dates of texts as said parameter. | 0.834365 |
8,234,494 | 9 | 15 | 9. A non-transitory machine-readable storage medium having stored therein instructions which, when executed by a computing device, cause the computing device to perform a method comprising: receiving a first request from a first end-user system for a speaker-verification digital signature for a corresponding communication; authenticating a claimed identity associated with a sender of the corresponding communication, the authenticating comprising obtaining an audio signal from the first end-user system corresponding to a text-phrase provided at the first end-user system and a voice template that corresponds to the claimed identity, comparing the audio signal and voice template to generate a confidence score, and generating an authentication certificate when the confidence score exceeds a threshold; after authenticating the claimed identity, generating a session ID to be inserted in the corresponding communication, the session ID being unique with respect to other communications for a destination address of the corresponding communication, and the session ID being available for use as another session ID for a different destination address; and responsive to generating the session ID, separately transmitting the corresponding communication and authentication information having the session ID to the destination address indicated in the corresponding communication, wherein the authentication information is generated by packaging the session ID with the authentication certificate if the confidence score exceeded the threshold, else the authentication information is generated by packaging the session ID with the confidence score. | 9. A non-transitory machine-readable storage medium having stored therein instructions which, when executed by a computing device, cause the computing device to perform a method comprising: receiving a first request from a first end-user system for a speaker-verification digital signature for a corresponding communication; authenticating a claimed identity associated with a sender of the corresponding communication, the authenticating comprising obtaining an audio signal from the first end-user system corresponding to a text-phrase provided at the first end-user system and a voice template that corresponds to the claimed identity, comparing the audio signal and voice template to generate a confidence score, and generating an authentication certificate when the confidence score exceeds a threshold; after authenticating the claimed identity, generating a session ID to be inserted in the corresponding communication, the session ID being unique with respect to other communications for a destination address of the corresponding communication, and the session ID being available for use as another session ID for a different destination address; and responsive to generating the session ID, separately transmitting the corresponding communication and authentication information having the session ID to the destination address indicated in the corresponding communication, wherein the authentication information is generated by packaging the session ID with the authentication certificate if the confidence score exceeded the threshold, else the authentication information is generated by packaging the session ID with the confidence score. 15. The non-transitory machine-readable storage medium of claim 9 , the instructions, when executed by the computing device, cause the computing device to perform a method further comprising: receiving in a third end-user system an authenticated communication; searching for an authentication information having a second session ID that corresponds to a first session ID included in the authenticated communication; and displaying the authenticated communication and the authentication information when an end-user selects the authenticated communication for display. | 0.5 |
9,251,289 | 3 | 4 | 3. The method of claim 1 , comprising populating a string database with a plurality of known strings, including the known string, respective known strings in the string database associated with known string IDs. | 3. The method of claim 1 , comprising populating a string database with a plurality of known strings, including the known string, respective known strings in the string database associated with known string IDs. 4. The method of claim 3 , a second known string in the string database associated with a second known string ID different than the known string ID. | 0.716475 |
7,996,351 | 1 | 6 | 1. A computer implemented method comprising: on a computing device, performing an automated process for estimating a country where the computing device is configured to operate, said performing comprising: gathering a time setting and a language setting of the computing device; and using the time setting and the language setting to derive an estimate for the country where the computing device is configured to operate by applying country estimation programming to the gathered time setting and language setting, wherein said automated process does not require human intervention to perform said gathering of the time setting and language setting and said using of the gathered time setting and language setting, wherein the country estimation programming comprises a rule engine implemented by rule programming, the rule engine comprising a set of rules, a processing relationship between rules in the set of rules, and a recursive rule program. | 1. A computer implemented method comprising: on a computing device, performing an automated process for estimating a country where the computing device is configured to operate, said performing comprising: gathering a time setting and a language setting of the computing device; and using the time setting and the language setting to derive an estimate for the country where the computing device is configured to operate by applying country estimation programming to the gathered time setting and language setting, wherein said automated process does not require human intervention to perform said gathering of the time setting and language setting and said using of the gathered time setting and language setting, wherein the country estimation programming comprises a rule engine implemented by rule programming, the rule engine comprising a set of rules, a processing relationship between rules in the set of rules, and a recursive rule program. 6. The method of claim 1 , wherein the gathering and deriving the estimate are performed by an application executing on the computing device. | 0.832143 |
6,031,174 | 1 | 14 | 1. A method of generating a musical tone signal, comprising the steps of: (a) selecting one of a plurality of phrases in response to a combination of simultaneous manipulations of phrase select operators by a user; and (b) reading performance data of the selected phrase from performance data pre-stored by phrase and generating musical tone signals of the read performance data in response to said manipulations. | 1. A method of generating a musical tone signal, comprising the steps of: (a) selecting one of a plurality of phrases in response to a combination of simultaneous manipulations of phrase select operators by a user; and (b) reading performance data of the selected phrase from performance data pre-stored by phrase and generating musical tone signals of the read performance data in response to said manipulations. 14. A method according to claim 1, further comprising the step of: (c) selecting a musical instrument before said step (b), in response to manipulation of a musical instrument select operator, wherein said step (b) reads performance data different for each selected musical instrument and generates the musical tone signal. | 0.5 |
9,967,380 | 42 | 43 | 42. A communication system comprising: a hard of hearing user's captioned device, the captioned device including a display screen and a processor, the captioned device configured to: establish communication with a hard of hearing user's wireless phone device that is independent of the hard of hearing user's captioned device; receive a hearing user's voice signal originating at a hearing user's phone device from the hard of hearing user's phone device; establish a first communication link with a relay; route the hearing user's voice signal via the first communication link to the relay for transcription; receive a text communication originating at the relay on a second communication link that is separate from the first communication link, the text communication corresponding to a transcription of the hearing user's voice signal; and display a text caption corresponding to the text communication on the display. | 42. A communication system comprising: a hard of hearing user's captioned device, the captioned device including a display screen and a processor, the captioned device configured to: establish communication with a hard of hearing user's wireless phone device that is independent of the hard of hearing user's captioned device; receive a hearing user's voice signal originating at a hearing user's phone device from the hard of hearing user's phone device; establish a first communication link with a relay; route the hearing user's voice signal via the first communication link to the relay for transcription; receive a text communication originating at the relay on a second communication link that is separate from the first communication link, the text communication corresponding to a transcription of the hearing user's voice signal; and display a text caption corresponding to the text communication on the display. 43. The communication system of claim 42 wherein the captioned device routes the hearing user's voice signal through the hard of hearing user's phone device to the relay. | 0.623894 |
9,298,693 | 8 | 10 | 8. The system of claim 1 , wherein: the plurality of transformation rules are generated from training data; and further comprising assembling at least a part of the plurality of transformation rules into a rules index based at least in part on the weights. | 8. The system of claim 1 , wherein: the plurality of transformation rules are generated from training data; and further comprising assembling at least a part of the plurality of transformation rules into a rules index based at least in part on the weights. 10. The system of claim 8 , wherein the generating of the plurality of transformation rules is based at least in part on string alignment of the string pairs. | 0.512346 |
9,317,760 | 21 | 27 | 21. A system of determining one or more input characters based upon character recognition output, the system comprising: a computing device; and a non-transitory computer-readable storage medium in communication with the computing device, wherein the computer-readable storage medium comprises one or more programming instructions that, when executed, cause the computing device to: receive a proposed character string generated using character recognition, wherein the proposed character string is associated with a plurality of handwritten characters of an assessment of a student, wherein the proposed character string comprises a first proposed character and a second proposed character, identify one or more possible characters, determine whether the first proposed character is correct, by, for one or more of the possible characters, determining an ultimate probability that the first proposed character is the possible character given the character string by: determining a first probability equal to a probability that if a true value of the first proposed character is the possible character that the first proposed character was identified, determining a second probability equal to a probability that if the true value of the first proposed character is the possible character that a following character is the second proposed character, determining a third probability equal to a probability that the student wrote the possible character, and determining a product of the first probability, the second probability and the third probability; and select the ultimate probability having the highest value. | 21. A system of determining one or more input characters based upon character recognition output, the system comprising: a computing device; and a non-transitory computer-readable storage medium in communication with the computing device, wherein the computer-readable storage medium comprises one or more programming instructions that, when executed, cause the computing device to: receive a proposed character string generated using character recognition, wherein the proposed character string is associated with a plurality of handwritten characters of an assessment of a student, wherein the proposed character string comprises a first proposed character and a second proposed character, identify one or more possible characters, determine whether the first proposed character is correct, by, for one or more of the possible characters, determining an ultimate probability that the first proposed character is the possible character given the character string by: determining a first probability equal to a probability that if a true value of the first proposed character is the possible character that the first proposed character was identified, determining a second probability equal to a probability that if the true value of the first proposed character is the possible character that a following character is the second proposed character, determining a third probability equal to a probability that the student wrote the possible character, and determining a product of the first probability, the second probability and the third probability; and select the ultimate probability having the highest value. 27. The system of claim 21 , wherein the computer-readable storage medium further comprises one or more programming instructions that, when executed, cause the computing device to, in response to not identifying the first proposed character as the possible character having the highest ultimate value: determine that the first proposed character is incorrect; and update a score associated with the assessment in response to determining that the first proposed character is incorrect. | 0.715629 |
8,972,372 | 1 | 8 | 1. A computer implemented method of providing search results, the method comprising: receiving a first specification that comprises an input-output pair including a first data entity and a second data entity; for each module of program code of a plurality of modules of program code, supplying to a constraint solver one or more input-output constraints based on the input-output pair of the first specification and one or more code constraints based on the module of program code; receiving from the constraint solver, for each module of program code, a result indicating whether the code constraints based on the module of program code are satisfiable with the input-output constraints; and generating search results referencing one or more modules of program code having a positive result from the constraint solver and providing the search results to a user. | 1. A computer implemented method of providing search results, the method comprising: receiving a first specification that comprises an input-output pair including a first data entity and a second data entity; for each module of program code of a plurality of modules of program code, supplying to a constraint solver one or more input-output constraints based on the input-output pair of the first specification and one or more code constraints based on the module of program code; receiving from the constraint solver, for each module of program code, a result indicating whether the code constraints based on the module of program code are satisfiable with the input-output constraints; and generating search results referencing one or more modules of program code having a positive result from the constraint solver and providing the search results to a user. 8. The method of claim 1 , wherein the specification is a Uniform Resource Locator (URL) and the first data entity includes one or more RSS feeds and the second data entity includes a subset of the RSS feeds that match the specification. | 0.709559 |
8,954,415 | 13 | 19 | 13. A method for retrieving regulatory information, comprising: indexing a plurality of regulatory corpuses, thereby forming a plurality of full-text searchable databases; receiving a search query comprising at least one search term; executing the search query on the plurality of full-text searchable databases to identify a plurality of relevant passages; emphasizing search terms within the plurality of relevant passages; emphasizing regulatory words within the plurality of relevant passages, thereby forming emphasized relevant passages; and storing the emphasized relevant passages in an emphasized document database. | 13. A method for retrieving regulatory information, comprising: indexing a plurality of regulatory corpuses, thereby forming a plurality of full-text searchable databases; receiving a search query comprising at least one search term; executing the search query on the plurality of full-text searchable databases to identify a plurality of relevant passages; emphasizing search terms within the plurality of relevant passages; emphasizing regulatory words within the plurality of relevant passages, thereby forming emphasized relevant passages; and storing the emphasized relevant passages in an emphasized document database. 19. The method of claim 13 , further comprising: applying a stemming process to the regulatory words, thereby creating stemmed regulatory words; and emphasizing the stemmed regulatory words in said relevant passages. | 0.631399 |
9,483,535 | 13 | 14 | 13. The system of claim 11 , wherein the presentation module presents the option to the user by, after the user performs the search: displaying a prompt to the user indicating that at least one partial document family was included in the search results; displaying a prompt to the user allowing the user to expand the partial document family by including, within the search results, an entire document family associated with the partial document family. | 13. The system of claim 11 , wherein the presentation module presents the option to the user by, after the user performs the search: displaying a prompt to the user indicating that at least one partial document family was included in the search results; displaying a prompt to the user allowing the user to expand the partial document family by including, within the search results, an entire document family associated with the partial document family. 14. The system of claim 13 , wherein the document family comprises the partial document family. | 0.910714 |
7,627,588 | 1 | 23 | 1. A computer-readable storage medium storing codes that when executed by a processor perform a method, comprising: receiving from a user a selection of a first category and a second category from among a plurality of categories associated with a set of objects, the first category being associated with a first subset of objects from among a plurality of subsets of objects, and the second category being associated with a second subset of objects from among the plurality of subsets of objects, each of the first subset and the second subset being included in the set of objects and including at least one object; receiving from a user a selection of a concept from among a plurality of concepts associated with the first category; performing multi-dimensional analysis on the concept to determine a presence or absence of the concept in each of the first subset and the second subset; for each of the first subset and second subset, if the concept is present in that subset, providing an indication of a strength of presence of the concept in that subset; and if the concept is absent from the second subset, providing an indication of an absence of the concept from the second subset, the indication of the absence including a reference to the concept and the second category. | 1. A computer-readable storage medium storing codes that when executed by a processor perform a method, comprising: receiving from a user a selection of a first category and a second category from among a plurality of categories associated with a set of objects, the first category being associated with a first subset of objects from among a plurality of subsets of objects, and the second category being associated with a second subset of objects from among the plurality of subsets of objects, each of the first subset and the second subset being included in the set of objects and including at least one object; receiving from a user a selection of a concept from among a plurality of concepts associated with the first category; performing multi-dimensional analysis on the concept to determine a presence or absence of the concept in each of the first subset and the second subset; for each of the first subset and second subset, if the concept is present in that subset, providing an indication of a strength of presence of the concept in that subset; and if the concept is absent from the second subset, providing an indication of an absence of the concept from the second subset, the indication of the absence including a reference to the concept and the second category. 23. The computer-readable storage medium of claim 1 , further comprising codes that when executed by a processor perform the steps of: receiving from a user a selection of a subconcept from a plurality of subconcepts associated with the concept; performing multi-dimensional analysis on the subconcept to determine a presence or absence of the subconcept in each of the first subset and second subset; for each of the first subset and the second subset, if the subconcept is present that subset, providing an indication of a strength of presence of the subconcept in that subset; and if the subconcept is not present in the second subset, providing an indication of an absence of the subconcept from the second subset, the indication of the absence including a reference to the subconcept and the second category. | 0.680425 |
9,785,632 | 9 | 16 | 9. A method comprising: displaying audiovisual content in a first language on a display screen of a smart sign; determining that a mobile device is in proximity to the smart sign; determining a location of the mobile device relative to the display screen of the smart sign; receiving device-specific information from the mobile device, including a preferred language of a user of the mobile device; translating the displayed audiovisual content based on the preferred language of the user; and modifying at least one visual characteristic of the translated audiovisual content based on the location of the mobile device; displaying the translated audiovisual content on the display screen of the smart sign based on the at least one modified visual characteristic. | 9. A method comprising: displaying audiovisual content in a first language on a display screen of a smart sign; determining that a mobile device is in proximity to the smart sign; determining a location of the mobile device relative to the display screen of the smart sign; receiving device-specific information from the mobile device, including a preferred language of a user of the mobile device; translating the displayed audiovisual content based on the preferred language of the user; and modifying at least one visual characteristic of the translated audiovisual content based on the location of the mobile device; displaying the translated audiovisual content on the display screen of the smart sign based on the at least one modified visual characteristic. 16. The method of claim 9 , further comprising: determining a movement of the mobile device relative to the smart sign; and instructing a motor to move the display screen of the smart sign to track the movement of the mobile device. | 0.857669 |
9,489,171 | 14 | 15 | 14. A computing system, comprising: a logic machine; and a storage machine holding instructions executable by the logic machine to: identify a user identity of a user interacting with the computing system; select a parameterized voice command from a set of voice commands based on the user identity, the parameterized voice command including a root operation and a parameter that modifies the root operation; select a first personalized value of the parameter based on the user identity; identify a parameterized voice-command suggestion corresponding to the selected parameterized voice command; present via a display a graphical user interface including the parameterized voice-command suggestion with the first personalized value of the parameter; in response to exceeding a duration, select a second personalized value of the parameter based on the user identity, the second personalized value differing from the first personalized value; and present via the display the parameterized voice-command suggestion with the second personalized value of the parameter. | 14. A computing system, comprising: a logic machine; and a storage machine holding instructions executable by the logic machine to: identify a user identity of a user interacting with the computing system; select a parameterized voice command from a set of voice commands based on the user identity, the parameterized voice command including a root operation and a parameter that modifies the root operation; select a first personalized value of the parameter based on the user identity; identify a parameterized voice-command suggestion corresponding to the selected parameterized voice command; present via a display a graphical user interface including the parameterized voice-command suggestion with the first personalized value of the parameter; in response to exceeding a duration, select a second personalized value of the parameter based on the user identity, the second personalized value differing from the first personalized value; and present via the display the parameterized voice-command suggestion with the second personalized value of the parameter. 15. The computing system of claim 14 , wherein the personalized value of the parameter is a first personalized value selected based on a first user identity of a first user, and wherein the storage machine further holds instructions executable by the logic machine to: identify a plurality of user identities of users interacting with the computing system; in response to exceeding a duration, select a second personalized value of the parameter based on a second user identity of a second user of the plurality of users, the second personalized value differing from the first personalized value; and present via the display the parameterized voice-command suggestion with the second personalized value of the parameter. | 0.5 |
8,176,555 | 3 | 4 | 3. The method of claim 1 , wherein the list of known non-malicious processes is maintained on a server. | 3. The method of claim 1 , wherein the list of known non-malicious processes is maintained on a server. 4. The method of claim 3 , wherein determining that the process represents a security risk comprises: transmitting, from a client-side computing system, a process-information request that identifies the process; receiving a response to the process-information request from the server; determining, based at least in part on the response received from the server, that the process represents a security risk. | 0.5 |
8,521,675 | 13 | 16 | 13. A computer-implemented system of integrated automatic support and assistance, comprising: a user profile knowledge base in communication with an Al inference or semantic based engine, the user profile knowledge base storing a plurality of user information; a semantic enhanced search engine in communication with the Al inference or semantic based engine, the semantic enhanced search engine disposed to accept user queries from the Al or semantic based inference engine and to restructure the user queries into semantic components; wherein, the Al inference or semantic based engine is disposed to perform a method of integrated automatic support and assistance, the method comprising: identifying a user, wherein identifying the user includes retrieving models representing a system operated by the user; receiving a query or statement from the user through the Al inference or semantic based engine, the query or statement being related to a question about or a problem with at least one component on the system; determining a set of response time expectations based upon the received query or statement; relaying the set of response time expectations to the user; receiving feedback from the user based on the relaying; determining a user satisfaction value from the feedback; storing the user satisfaction value in the user profile for subsequent queries; determining if the received query or statement is a machine translatable query or statement; restructuring machine translatable terms of the received query or statement into semantic components based upon the retrieved models; determining a set of candidate knowledge bases both internal and external to the assistance providing system related to the semantic components; submitting the machine translatable query or statement to each knowledge base of the set of candidate knowledge bases; receiving a set of responses from each knowledge base of the set of knowledge bases in response to the submitting; formatting the set of responses; submitting the formatted set of responses to the user through the Al inference or semantic based engine; determining if a response of the submitted formatted set of responses is accepted by the user; applying updated weights within the formatted set of responses; and storing the updated weights for future queries. | 13. A computer-implemented system of integrated automatic support and assistance, comprising: a user profile knowledge base in communication with an Al inference or semantic based engine, the user profile knowledge base storing a plurality of user information; a semantic enhanced search engine in communication with the Al inference or semantic based engine, the semantic enhanced search engine disposed to accept user queries from the Al or semantic based inference engine and to restructure the user queries into semantic components; wherein, the Al inference or semantic based engine is disposed to perform a method of integrated automatic support and assistance, the method comprising: identifying a user, wherein identifying the user includes retrieving models representing a system operated by the user; receiving a query or statement from the user through the Al inference or semantic based engine, the query or statement being related to a question about or a problem with at least one component on the system; determining a set of response time expectations based upon the received query or statement; relaying the set of response time expectations to the user; receiving feedback from the user based on the relaying; determining a user satisfaction value from the feedback; storing the user satisfaction value in the user profile for subsequent queries; determining if the received query or statement is a machine translatable query or statement; restructuring machine translatable terms of the received query or statement into semantic components based upon the retrieved models; determining a set of candidate knowledge bases both internal and external to the assistance providing system related to the semantic components; submitting the machine translatable query or statement to each knowledge base of the set of candidate knowledge bases; receiving a set of responses from each knowledge base of the set of knowledge bases in response to the submitting; formatting the set of responses; submitting the formatted set of responses to the user through the Al inference or semantic based engine; determining if a response of the submitted formatted set of responses is accepted by the user; applying updated weights within the formatted set of responses; and storing the updated weights for future queries. 16. The system of claim 13 , wherein determining if the received query or statement is machine translatable includes parsing the query based on a set of associating algorithms or relationships associated with the user, and determining if the parsed query includes associations with the retrieved models. | 0.731858 |
9,715,553 | 12 | 19 | 12. A computer-implemented method comprising: receiving at a current time a current location of a user's electronic device; retrieving a plurality of updates associated with a plurality of points of interests, where each update: comprises data about the point of interest input by an author other than the user into an online social network that includes the user; is associated with a point of interest that is within a predetermined distance to the current location; and was input into the online social network within a predetermined time interval to the current time; ranking each of the plurality of updates based on the proximity of author to the user in the online social network; and providing data identifying one or more points of interest associated with one or more of the plurality of updates to the user's electronic device based on the ranking. | 12. A computer-implemented method comprising: receiving at a current time a current location of a user's electronic device; retrieving a plurality of updates associated with a plurality of points of interests, where each update: comprises data about the point of interest input by an author other than the user into an online social network that includes the user; is associated with a point of interest that is within a predetermined distance to the current location; and was input into the online social network within a predetermined time interval to the current time; ranking each of the plurality of updates based on the proximity of author to the user in the online social network; and providing data identifying one or more points of interest associated with one or more of the plurality of updates to the user's electronic device based on the ranking. 19. The method of claim 12 , wherein providing data identifying one or more of the points of interest to the electronic device for presentation to the user on a display of the electronic device comprises providing the one or more points of interest as suggested search queries. | 0.80493 |
7,490,043 | 7 | 9 | 7. A method for verifying an identity of a speaker, comprising: receiving feature vectors extracted from an utterance received from a microphone and made by a speaker claiming an identity; measuring dissimilarity between the feature vectors and a codebook associated with a version of the utterance known to be made by the identity; analyzing the utterance to ascertain information about repeating occurrences of the feature vectors in the utterance; comparing the information about repeating occurrences of feature vectors occurring in the utterance with information about repeating occurrences of feature vectors in a version of the utterance known to be made by the claimed identity; assigning a penalty to the measured dissimilarity based on the comparison; and determining whether to accept the speaker as the identity using the measured dissimilarity modified by the assigned penalty, wherein the assigned penalty comprises a penalty for each of the feature vectors of the utterance, wherein the assigned penalty for each feature vector is based on a difference between a number of repeating occurrences of the respective feature vector of the utterance and a number of repeating occurrences of the corresponding feature vector of the version of the utterance know to be made by the identity. | 7. A method for verifying an identity of a speaker, comprising: receiving feature vectors extracted from an utterance received from a microphone and made by a speaker claiming an identity; measuring dissimilarity between the feature vectors and a codebook associated with a version of the utterance known to be made by the identity; analyzing the utterance to ascertain information about repeating occurrences of the feature vectors in the utterance; comparing the information about repeating occurrences of feature vectors occurring in the utterance with information about repeating occurrences of feature vectors in a version of the utterance known to be made by the claimed identity; assigning a penalty to the measured dissimilarity based on the comparison; and determining whether to accept the speaker as the identity using the measured dissimilarity modified by the assigned penalty, wherein the assigned penalty comprises a penalty for each of the feature vectors of the utterance, wherein the assigned penalty for each feature vector is based on a difference between a number of repeating occurrences of the respective feature vector of the utterance and a number of repeating occurrences of the corresponding feature vector of the version of the utterance know to be made by the identity. 9. The method of claim 7 , wherein the assigned penalty for given feature vector is adjusted based on the degree of difference between the number of repeating occurrences of the respective feature vector of the utterance and the number of repeating occurrences of the corresponding feature vector of the version of the utterance know to be made by the identity. | 0.605895 |
9,858,524 | 3 | 11 | 3. The method of claim 1 , wherein the third neural network is a long-short term memory (LSTM) neural network. | 3. The method of claim 1 , wherein the third neural network is a long-short term memory (LSTM) neural network. 11. The method of claim 3 , wherein processing the alternative representation for the input image using the third neural network comprises: processing the alternative representation using the LSTM neural network using a left to right beam search decoding to generate a plurality of possible sequences and a respective sequence score for each of the possible sequences; and selecting one or more highest-scoring possible sequences as descriptions of the input image. | 0.559659 |
9,965,704 | 1 | 3 | 1. A system comprising: a memory having instructions embodied thereon; a processor configured by the instructions to perform operations comprising: accessing a set of images uploaded to a network-based system by a plurality of users of a network-based service provided by the network-based system, each image of the set of images having a text description of the corresponding image as provided by a user of the plurality of users who uploaded the corresponding image; generating a set of associated weak labels for each image of the set of images based on the corresponding text description of the respective image, each set of associated weak labels including one or more weak labels for the respective image that are derived from the corresponding text description of the respective image; generating a weakly-labeled dataset comprising the set of images; clustering images of the set of images based on each of the clustered images sharing a particular label of the weak labels; accessing a set of examples selected from the set of images uploaded to the network-based system, each example of the set of examples being selected based on the respective example not being associated with the particular label associated with the clustered images; training a recognition engine using the clustered images as positive examples and the set of examples as negative examples; and generating strong labels for the clustered images using the trained recognition engine, the strong labels including the particular label based on a ranking of the particular label with respect to the cluster as provided by the trained recognition engine. | 1. A system comprising: a memory having instructions embodied thereon; a processor configured by the instructions to perform operations comprising: accessing a set of images uploaded to a network-based system by a plurality of users of a network-based service provided by the network-based system, each image of the set of images having a text description of the corresponding image as provided by a user of the plurality of users who uploaded the corresponding image; generating a set of associated weak labels for each image of the set of images based on the corresponding text description of the respective image, each set of associated weak labels including one or more weak labels for the respective image that are derived from the corresponding text description of the respective image; generating a weakly-labeled dataset comprising the set of images; clustering images of the set of images based on each of the clustered images sharing a particular label of the weak labels; accessing a set of examples selected from the set of images uploaded to the network-based system, each example of the set of examples being selected based on the respective example not being associated with the particular label associated with the clustered images; training a recognition engine using the clustered images as positive examples and the set of examples as negative examples; and generating strong labels for the clustered images using the trained recognition engine, the strong labels including the particular label based on a ranking of the particular label with respect to the cluster as provided by the trained recognition engine. 3. The system of claim 1 , wherein the operations further comprise: using the recognition engine to determine weak instances in the set of examples; in accordance with a determination that a weak instance is in the set of examples: modifying the set of examples by: removing the weak instance from the set of examples; and adding to the set of examples a replacement image selected from the set of images, the replacement image not being associated with the weak label associated with the clustered images; and training the recognition engine using the clustered images as positive examples and the modified set of examples as negative examples. | 0.5 |
8,938,463 | 26 | 27 | 26. The machine-readable storage of claim 19 wherein the search engine is further configured to use comparisons of the predictive outputs of the model with an implicit user feedback model to adjust respective ranking scores of the given search results. | 26. The machine-readable storage of claim 19 wherein the search engine is further configured to use comparisons of the predictive outputs of the model with an implicit user feedback model to adjust respective ranking scores of the given search results. 27. The machine-readable storage of claim 26 wherein the implicit user feedback model is a click fraction, and the search engine is configured to use a comparison of the predicted click through rate and the click fraction to adjust the respective ranking scores of the given search results, the comparison including at least one of a ratio of the predicted click through rate and the click fraction or a value difference between the predicted click through rate and the click fraction. | 0.5 |
9,430,547 | 6 | 7 | 6. The system according to claim 4 , further comprising a dependency manager node associated with the supervisor node and comprising a processor monitoring a node configuration status of a node monitored by the supervisor using a machine-readable dependency tree file stored in a non-transitory machine-readable storage medium. | 6. The system according to claim 4 , further comprising a dependency manager node associated with the supervisor node and comprising a processor monitoring a node configuration status of a node monitored by the supervisor using a machine-readable dependency tree file stored in a non-transitory machine-readable storage medium. 7. The system according to claim 6 , wherein the status of the heartbeat signal indicates the node configuration status, and wherein the supervisor node transmits a machine-readable configuration package file responsive to the dependency manager determining the node configuration status indicates the node is misconfigured. | 0.5 |
9,563,680 | 12 | 13 | 12. The method of claim 1 wherein after converting the document from the first format to the second format, the method further comprising: the at least one static object associated with the converted document is rendered in the converted document when the converted document is accessed via the at least one web portal, the at least one static object including at least one of a multi-media file, a glossary, an index and a table of contents. | 12. The method of claim 1 wherein after converting the document from the first format to the second format, the method further comprising: the at least one static object associated with the converted document is rendered in the converted document when the converted document is accessed via the at least one web portal, the at least one static object including at least one of a multi-media file, a glossary, an index and a table of contents. 13. The method of claim 12 wherein the at least one static object is associated with an identifier and the method further comprises generating a static object mapping file associated with the document that maps the identifier of the at least one static object to at least one of the document and a location in the document and transmitting the static object mapping file to the at least one web portal. | 0.77081 |
4,128,737 | 59 | 60 | 59. The speech synthesizer of claim 55 further including amplitude control means responsive to said input data to vary the relative overall amplitude of said audio output by continuously modulating a preselected signal characteristic of said first and second control signals by a certain percentage determined by said input data. | 59. The speech synthesizer of claim 55 further including amplitude control means responsive to said input data to vary the relative overall amplitude of said audio output by continuously modulating a preselected signal characteristic of said first and second control signals by a certain percentage determined by said input data. 60. The speech synthesizer of claim 59 wherein said circuit means is adapted to preserve said certain percentage of modulation that existed prior to the silent phoneme so that the relative overall amplitude level of the audio output that existed prior to the silent phoneme will continue to exist after the silent phoneme. | 0.5 |
8,825,471 | 4 | 6 | 4. The method of claim 1 , further comprising: associating the first fact with a first object. | 4. The method of claim 1 , further comprising: associating the first fact with a first object. 6. The method of claim 4 , further comprising associating the second fact with the first object. | 0.779817 |
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