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7,561,738 | 1 | 4 | 1. A system with a processor and a memory for symbol grouping and recognition of a handwritten mathematical expression, the system comprising: a symbol grouping component configured to group input strokes corresponding to a handwritten mathematical expression into symbols based upon intra-group and inter-group information associated with the input strokes; and a symbol recognition component configured to recognize the symbols based upon information associated with the grouped input strokes wherein the intra-group information associated with the input strokes includes a confidence representative of whether the input strokes are a certain symbol provided by the symbol recognition component, and a score representative of whether the input strokes are a valid symbol based upon intra-group spatial information that includes a size difference among the input strokes and an offset measurement among the input strokes, the score being represented by the following: f ( d , δ , σ ) = 1 1 + ( ( d d 0 ) α + ( δ δ 0 ) β + ( σ σ 0 ) γ ) , ( α , β , γ > 1 ) where d represents a distance feature, δ represents a size difference feature, σ represents an offset feature, and d 0 , δ 0 , and σ 0 ; wherein the symbol grouping component is further configured to receive the input strokes, to determine intra-group spatial information among the input strokes, and to determine whether to group the input strokes into a symbol based upon the intra-group spatial; and wherein the components are implemented as computer-executable instructions stored in the memory for execution by the processor. | 1. A system with a processor and a memory for symbol grouping and recognition of a handwritten mathematical expression, the system comprising: a symbol grouping component configured to group input strokes corresponding to a handwritten mathematical expression into symbols based upon intra-group and inter-group information associated with the input strokes; and a symbol recognition component configured to recognize the symbols based upon information associated with the grouped input strokes wherein the intra-group information associated with the input strokes includes a confidence representative of whether the input strokes are a certain symbol provided by the symbol recognition component, and a score representative of whether the input strokes are a valid symbol based upon intra-group spatial information that includes a size difference among the input strokes and an offset measurement among the input strokes, the score being represented by the following: f ( d , δ , σ ) = 1 1 + ( ( d d 0 ) α + ( δ δ 0 ) β + ( σ σ 0 ) γ ) , ( α , β , γ > 1 ) where d represents a distance feature, δ represents a size difference feature, σ represents an offset feature, and d 0 , δ 0 , and σ 0 ; wherein the symbol grouping component is further configured to receive the input strokes, to determine intra-group spatial information among the input strokes, and to determine whether to group the input strokes into a symbol based upon the intra-group spatial; and wherein the components are implemented as computer-executable instructions stored in the memory for execution by the processor. 4. The system of claim 1 , wherein the inter-group information associated with the input strokes includes spatial relationship information of neighboring symbols and syntax context. | 0.642292 |
7,788,594 | 18 | 19 | 18. A medium as in claim 13 , the method further comprising: displaying a first identifier to identify the first operation and displaying a second identifier to identify the second operation. | 18. A medium as in claim 13 , the method further comprising: displaying a first identifier to identify the first operation and displaying a second identifier to identify the second operation. 19. A medium as in claim 18 wherein the first identifier is displayed after a period of time which is greater than a first certain time in which a cursor is positioned in the first portion of the text input field, the first portion being associated with the first operation, and wherein the second identifier is displayed after another period of time which is greater than the second certain time in which the cursor is positioned in a second portion of the text input field, the second portion being associated with the second operation. | 0.5 |
10,079,792 | 1 | 4 | 1. A method for assisting a user in selecting a desired hashtag, the method comprising: parsing, by a hashtag selector connected to a plurality of client devices, text of a composed message to determine a topic of interest, a sentiment and a target audience of said composed message prior to being posted on a social network system; evaluating, by said hashtag selector, historical and current communications for said target audience who will be receiving said composed message to identify hashtags that are trending on said topic of said composed message and related topics to said topic of said composed message; evaluating, by said hashtag selector, historical and current communications for said target audience who will be receiving said composed message to identify hashtags that match said sentiment of said composed message prior to posting said composed message on said social network system; determining, by said hashtag selector, propagation speeds of said identified hashtags; generating, by a processor said hashtag selector, a recommended hashtag to be populated in said composed message that will increase a propagation speed of said composed message and emphasize said sentiment of said composed message based on identifying said hashtags that are trending on said topic of said composed message and related topics to said topic of said composed message, identifying said hashtags that match said sentiment of said composed message and determining said propagating speeds of said identified hashtags; and populating, by said hashtag selector, said composed message with said recommended hashtag that will increase said propagation speed of said composed message and emphasize said sentiment of said composed message. | 1. A method for assisting a user in selecting a desired hashtag, the method comprising: parsing, by a hashtag selector connected to a plurality of client devices, text of a composed message to determine a topic of interest, a sentiment and a target audience of said composed message prior to being posted on a social network system; evaluating, by said hashtag selector, historical and current communications for said target audience who will be receiving said composed message to identify hashtags that are trending on said topic of said composed message and related topics to said topic of said composed message; evaluating, by said hashtag selector, historical and current communications for said target audience who will be receiving said composed message to identify hashtags that match said sentiment of said composed message prior to posting said composed message on said social network system; determining, by said hashtag selector, propagation speeds of said identified hashtags; generating, by a processor said hashtag selector, a recommended hashtag to be populated in said composed message that will increase a propagation speed of said composed message and emphasize said sentiment of said composed message based on identifying said hashtags that are trending on said topic of said composed message and related topics to said topic of said composed message, identifying said hashtags that match said sentiment of said composed message and determining said propagating speeds of said identified hashtags; and populating, by said hashtag selector, said composed message with said recommended hashtag that will increase said propagation speed of said composed message and emphasize said sentiment of said composed message. 4. The method as recited in claim 1 further comprising: modifying said composed message to enhance said sentiment of said composed message with said recommended hashtag; and posting said modified message with said recommended hashtag on a social network system. | 0.811688 |
7,860,716 | 12 | 15 | 12. A computer-implemented method of error checking, comprising: computing duration probability data by forcing alignment of a speech model and a corpus of transcription data and wave data; computing a confidence score based on recognition processing; detecting errors based on the duration probability data and the confidence score; and retraining the speech model based on removal of the errors from the corpus. | 12. A computer-implemented method of error checking, comprising: computing duration probability data by forcing alignment of a speech model and a corpus of transcription data and wave data; computing a confidence score based on recognition processing; detecting errors based on the duration probability data and the confidence score; and retraining the speech model based on removal of the errors from the corpus. 15. The method of claim 12 , further comprising generating a word lattice based on recognition processing of the speech model and the wave data, the word lattice employed to compute the word confidence score. | 0.5 |
7,761,590 | 10 | 11 | 10. An apparatus according to claim 9 , wherein the memory and computer program code are further configured to, with the processor, cause the apparatus to determine whether the received data includes Schema elements prior to adapting portions of the received data. | 10. An apparatus according to claim 9 , wherein the memory and computer program code are further configured to, with the processor, cause the apparatus to determine whether the received data includes Schema elements prior to adapting portions of the received data. 11. An apparatus according to claim 10 , wherein the memory and computer program code are further configured to, with the processor, cause the apparatus to determine whether the Schema elements are capable of conversion into an XPath expression prior to adapting portions of the received data. | 0.5 |
7,480,897 | 19 | 20 | 19. A program product stored on one or more storage articles of manufacture, which when executed, manages development objects for computer program code, the program product comprising: program code for obtaining a first development object that comprises source code for the computer program code, wherein the source code is written in a positional language and includes a set of lines, and wherein a meaning of a set of characters in a line is defined by a position of the set of characters within the line; program code for obtaining a second development object that comprises a document object model (DOM) that corresponds to the source code, wherein the DOM includes; a set of model objects wherein each model object corresponds to a unique one of the set of lines; and a set of attributes for each model object, wherein each attribute in the set of attributes corresponds to a character position range of the corresponding line; program code for using a set of synchronizer objects to synchronize the source code and the DOM, wherein each synchronizer object in the set of synchronizer objects corresponds to a unique model object in the set of model objects. | 19. A program product stored on one or more storage articles of manufacture, which when executed, manages development objects for computer program code, the program product comprising: program code for obtaining a first development object that comprises source code for the computer program code, wherein the source code is written in a positional language and includes a set of lines, and wherein a meaning of a set of characters in a line is defined by a position of the set of characters within the line; program code for obtaining a second development object that comprises a document object model (DOM) that corresponds to the source code, wherein the DOM includes; a set of model objects wherein each model object corresponds to a unique one of the set of lines; and a set of attributes for each model object, wherein each attribute in the set of attributes corresponds to a character position range of the corresponding line; program code for using a set of synchronizer objects to synchronize the source code and the DOM, wherein each synchronizer object in the set of synchronizer objects corresponds to a unique model object in the set of model objects. 20. The program product of claim 19 , wherein the program product is embodied as an integrated development environment application for generating computer program code based on the positional language and the source code. | 0.5 |
7,694,229 | 11 | 12 | 11. A method of creating a visual style for a set of graphical components for use on a computer system having a graphical operating environment, comprising: selecting a number of graphical components that are desired to have a defined visual style such that the number of graphical components are selected from a schema file that stores each graphical component in a class identified by a unique class name, wherein each class includes at least one part having a part name for identifying the graphical component and each part includes at least one state, wherein the graphical components are controls that perform an associated known operation when selected by a user, wherein the at least one state describes a current appearance and a functional state of the graphical component, and wherein the visual style comprises a layout and shape of the graphical components and associated parts, the layout of the graphical components and the associated parts comprising one or more of a size or a position on a display device; assigning properties to said selected graphical components according to said defined visual style; and grouping pairs of selected graphical components and corresponding assigned properties for the defined visual style together in a first class data file, wherein the first class data file contains data on the defined visual style. | 11. A method of creating a visual style for a set of graphical components for use on a computer system having a graphical operating environment, comprising: selecting a number of graphical components that are desired to have a defined visual style such that the number of graphical components are selected from a schema file that stores each graphical component in a class identified by a unique class name, wherein each class includes at least one part having a part name for identifying the graphical component and each part includes at least one state, wherein the graphical components are controls that perform an associated known operation when selected by a user, wherein the at least one state describes a current appearance and a functional state of the graphical component, and wherein the visual style comprises a layout and shape of the graphical components and associated parts, the layout of the graphical components and the associated parts comprising one or more of a size or a position on a display device; assigning properties to said selected graphical components according to said defined visual style; and grouping pairs of selected graphical components and corresponding assigned properties for the defined visual style together in a first class data file, wherein the first class data file contains data on the defined visual style. 12. The method of claim 11 , wherein the graphical components are defined within a schema file of available graphical components, each component being defined by a unique class name and one or more part names associated with the class name. | 0.583333 |
7,743,030 | 6 | 8 | 6. The method of claim 5 wherein the discovery script is executable on the SAN node, the SAN node operable to generate the identity of the log files from execution of the discovery script, the discovery script independent of the operating system and file system of the SAN node, further comprising: generating the collection script from the identified set of available log files and the discovery script and the received identity of the log files. | 6. The method of claim 5 wherein the discovery script is executable on the SAN node, the SAN node operable to generate the identity of the log files from execution of the discovery script, the discovery script independent of the operating system and file system of the SAN node, further comprising: generating the collection script from the identified set of available log files and the discovery script and the received identity of the log files. 8. The method of claim 6 wherein generating the discovery script further comprises traversing a list of log types, the list of log types indicative of the location of each of the log files, wherein generating the discovery script includes using a log file designator that describes a manner of locating log files by referencing multiple log files via wildcards and directory specifications, wherein generating the discovery script occurs before generating the collection script. | 0.5 |
8,214,242 | 1 | 2 | 1. A method of signaling correspondence between a meeting agenda and a meeting discussion, by a signaling module executing on a device, the method comprising: receiving a meeting agenda specifying one or more topics for a meeting; analyzing, for each topic, one or more documents to identify topic keywords for that topic; receiving, by an automated speech recognition engine, meeting discussions among participants for the meeting, wherein said receiving the meeting discussions among participants for the meeting comprises receiving voice utterances for the meeting of participants; generating, by the automated speech recognition engine, a textual representation of the meeting discussions in a current meeting transcription; identifying a current topic for the meeting in dependence upon the meeting agenda; tracking a frequency at which the topic keywords for the current topic appear in the current meeting transcription; determining a correspondence indicator in dependence upon the tracked frequency at which the topic keywords for the current topic appear in the current meeting transcription, the correspondence indicator specifying the correspondence between the meeting agenda and the meeting discussion; and rendering the correspondence indicator to the participants of the meeting. | 1. A method of signaling correspondence between a meeting agenda and a meeting discussion, by a signaling module executing on a device, the method comprising: receiving a meeting agenda specifying one or more topics for a meeting; analyzing, for each topic, one or more documents to identify topic keywords for that topic; receiving, by an automated speech recognition engine, meeting discussions among participants for the meeting, wherein said receiving the meeting discussions among participants for the meeting comprises receiving voice utterances for the meeting of participants; generating, by the automated speech recognition engine, a textual representation of the meeting discussions in a current meeting transcription; identifying a current topic for the meeting in dependence upon the meeting agenda; tracking a frequency at which the topic keywords for the current topic appear in the current meeting transcription; determining a correspondence indicator in dependence upon the tracked frequency at which the topic keywords for the current topic appear in the current meeting transcription, the correspondence indicator specifying the correspondence between the meeting agenda and the meeting discussion; and rendering the correspondence indicator to the participants of the meeting. 2. The method of claim 1 further comprising repeatedly recording the correspondence indictor throughout the meeting in a historical repository for further evaluation. | 0.868254 |
6,016,395 | 1 | 25 | 1. A method for creating a computer program on a computer readable media for execution by a vector processor, the method comprising: a computer system reading a computer program written in a superset of C programming language, wherein the C programming language defines a plurality of operations and does not specify for each operation in said plurality how the operation is to be implemented in the vector processor, the computer program further including: a declaration of a value having a vector type, the vector type being part of a programming model of the vector processor, the vector type being distinct from an array type included in the C programming language; and a first operation having the vector type value as an operand, the first operation corresponding to a vector processor instruction VPI1 that can be executed by the vector processor and that has at least a vector operand; and the computer system generating one or more vector processor instructions that together implement the first operation, the one or more instructions including one or more VPI1 instructions. | 1. A method for creating a computer program on a computer readable media for execution by a vector processor, the method comprising: a computer system reading a computer program written in a superset of C programming language, wherein the C programming language defines a plurality of operations and does not specify for each operation in said plurality how the operation is to be implemented in the vector processor, the computer program further including: a declaration of a value having a vector type, the vector type being part of a programming model of the vector processor, the vector type being distinct from an array type included in the C programming language; and a first operation having the vector type value as an operand, the first operation corresponding to a vector processor instruction VPI1 that can be executed by the vector processor and that has at least a vector operand; and the computer system generating one or more vector processor instructions that together implement the first operation, the one or more instructions including one or more VPI1 instructions. 25. The method of claim 1, wherein: the vector operand is hereinafter referred to as VA; the first operation has additional vector operands VB, VC and VD; and the first operation indicates multiplication of each element of VA by the corresponding element of VB, then addition of the corresponding element of VC to the double precision result of the multiplication and storing the double precision result of the addition in the corresponding element of VD. | 0.5 |
9,619,526 | 7 | 8 | 7. A system, comprising: a processor device; and a memory device including instructions that, when executed with the processor device, cause the system to, at least: obtain a set of search results related to a search query, individual entries of the set of search results being associated with a category type; determine a plurality of category groups individually comprising a subset of the set of search results, the subset comprising one or more entries that share a common category type; select a plurality of entries, the plurality of entries comprising a single entry from each category group; calculate an entry score for each of the plurality of entries comprising the single entry from each category group, the entry score being based at least in part on a relevancy score that quantifies a relationship between an entry and the search query; determine a position in an ordered list for the plurality of entries, wherein the instructions that determine the position for the subset include further instructions to, at least a threshold number of times: assign a particular entry of the plurality of entries to a particular position in the ordered list according to the entry score calculated for the particular entry; increase entry scores for unassigned entries of the plurality of entries, the entry scores being increased based at least in part on a diversity score that quantifies an increase value of the entry score resulting from an unassigned entry remaining unassigned a number of times; for a category group corresponding to the particular entry, determine a new single entry for the category group; add the new single entry to the plurality of entries; and calculate an additional entry score for the new single entry of the category group; and provide the ordered list for display, the ordered list comprising at least one entry that is assigned a specific position in the ordered list based at least in part on the entry scores that were increased. | 7. A system, comprising: a processor device; and a memory device including instructions that, when executed with the processor device, cause the system to, at least: obtain a set of search results related to a search query, individual entries of the set of search results being associated with a category type; determine a plurality of category groups individually comprising a subset of the set of search results, the subset comprising one or more entries that share a common category type; select a plurality of entries, the plurality of entries comprising a single entry from each category group; calculate an entry score for each of the plurality of entries comprising the single entry from each category group, the entry score being based at least in part on a relevancy score that quantifies a relationship between an entry and the search query; determine a position in an ordered list for the plurality of entries, wherein the instructions that determine the position for the subset include further instructions to, at least a threshold number of times: assign a particular entry of the plurality of entries to a particular position in the ordered list according to the entry score calculated for the particular entry; increase entry scores for unassigned entries of the plurality of entries, the entry scores being increased based at least in part on a diversity score that quantifies an increase value of the entry score resulting from an unassigned entry remaining unassigned a number of times; for a category group corresponding to the particular entry, determine a new single entry for the category group; add the new single entry to the plurality of entries; and calculate an additional entry score for the new single entry of the category group; and provide the ordered list for display, the ordered list comprising at least one entry that is assigned a specific position in the ordered list based at least in part on the entry scores that were increased. 8. The system of claim 7 , including further instructions that determine the entry score based at least in part on determining a similarity between a user of the system and other users of the system, wherein determining the similarity includes instructions that further cause the system to, at least: determine a frequency at which the other users have historically selected the entry in response to submitting a substantially similar search query as the search query; and determine a frequency at which the user historically selects entries from the category group. | 0.5 |
8,914,398 | 7 | 8 | 7. A computer-implemented method, comprising: receiving text input; applying a text reduction function to the text input to generate a reduced text that is a subset of the text input, wherein the text reduction function is based on a term importance scoring of terms in the text input; and providing the reduced text to a keyword suggestion tool, wherein the keyword suggestion tool generates one or more keywords based on the reduced text; based on determining that an amount of the one or more keywords generated based on the reduced text does not satisfy a threshold amount of keywords, providing the text input to the keyword suggestion tool, wherein the keyword suggestion tool generates one or more keywords based on the text input; and returning a keyword set output. | 7. A computer-implemented method, comprising: receiving text input; applying a text reduction function to the text input to generate a reduced text that is a subset of the text input, wherein the text reduction function is based on a term importance scoring of terms in the text input; and providing the reduced text to a keyword suggestion tool, wherein the keyword suggestion tool generates one or more keywords based on the reduced text; based on determining that an amount of the one or more keywords generated based on the reduced text does not satisfy a threshold amount of keywords, providing the text input to the keyword suggestion tool, wherein the keyword suggestion tool generates one or more keywords based on the text input; and returning a keyword set output. 8. The computer-implemented method of claim 7 , wherein said generating further comprises: sorting the keyword set output according to a number of occurrences of a keyword of the keyword set output within the input text. | 0.5 |
9,760,547 | 12 | 13 | 12. The method of claim 11 , further comprising: monitoring, by the server, for creation of a new content item in the content editing environment by a third user identifier associated with the author identifier; and transmitting, by the server, to the first client device, an identification of the new content item associated with the author identifier. | 12. The method of claim 11 , further comprising: monitoring, by the server, for creation of a new content item in the content editing environment by a third user identifier associated with the author identifier; and transmitting, by the server, to the first client device, an identification of the new content item associated with the author identifier. 13. The method of claim 12 , comprising: identifying, by the server, content items created by a second author identifier from a plurality of author identifiers including the author identifier; and transmitting, by the server, to the first client device, an identification of the content items created by the second author identifier from the plurality of author identifiers including the author identifier. | 0.5 |
9,146,967 | 5 | 6 | 5. The method of claim 4 , further comprising: reconstructing one or more portions of the first set of compressed documents using the first set of recovered tokens. | 5. The method of claim 4 , further comprising: reconstructing one or more portions of the first set of compressed documents using the first set of recovered tokens. 6. The method of claim 5 , further comprising: presenting the reconstructed portions to a user in an ordered list of the set of top documents. | 0.5 |
8,983,949 | 10 | 12 | 10. A method comprising: transmitting a first document from a server to a client device, the first document comprising a first subdocument including a text and a link for display on a display of the client device; receiving, at the server, a request from the client device for a second document external from the first document, the request for the second document received via the link included in the first subdocument of the first document; dividing the second document into second subdocuments, each of the second subdocuments including text; assigning a label to each of the second subdocuments; a ranking engine of the server comparing the text of the link included in the first document with the text of each of the second subdocuments included in the second document; the ranking engine generating a link-text value for each of the plurality of second subdocuments according to a degree of association between the text of the link and the text of the corresponding one of the second subdocuments; the ranking engine ranking in ranked order the plurality of second subdocuments based, at least in part, on the link-text values; and communicating the ranking of the plurality of second subdcouments in the ranked order for display on the display of the client device. | 10. A method comprising: transmitting a first document from a server to a client device, the first document comprising a first subdocument including a text and a link for display on a display of the client device; receiving, at the server, a request from the client device for a second document external from the first document, the request for the second document received via the link included in the first subdocument of the first document; dividing the second document into second subdocuments, each of the second subdocuments including text; assigning a label to each of the second subdocuments; a ranking engine of the server comparing the text of the link included in the first document with the text of each of the second subdocuments included in the second document; the ranking engine generating a link-text value for each of the plurality of second subdocuments according to a degree of association between the text of the link and the text of the corresponding one of the second subdocuments; the ranking engine ranking in ranked order the plurality of second subdocuments based, at least in part, on the link-text values; and communicating the ranking of the plurality of second subdcouments in the ranked order for display on the display of the client device. 12. The method of claim 10 , further comprising: receiving the request for the second document associated with the link from the client device in response to selection of the link displayed on the display of the client device. | 0.787992 |
7,580,925 | 1 | 6 | 1. A computer-implemented method for searching a collection of machine-readable digital data, the method comprising: a computer receiving a given search word; the computer evaluating the search word against some or all words in a table, said table having rows and columns, each word residing in a different row and each letter of the word occupying a different column in that row, where the words are stored so as to preserve order of the letters within the words, and where each contiguous run of same letters in a column forms an interval, and such that lengths of the intervals are maximized to facilitate data searching, the evaluating operation comprising: for each target word in the table to which the search word is being evaluated, comparing, one letter at a time, letters of the search word to corresponding letters of the target word as represented by the columns in the table; if letters of the search word and the target word satisfy a predetermined matching condition, providing an output representing a successful match, otherwise, skipping ahead in the table to a row where a next interval begins in the column where the comparing operation encountered a letter of the search word failing to match a letter of the target word, and reinitiating the comparing operation; upon completing the evaluating operation without finding a successful match the computer providing an output representing a failed match. | 1. A computer-implemented method for searching a collection of machine-readable digital data, the method comprising: a computer receiving a given search word; the computer evaluating the search word against some or all words in a table, said table having rows and columns, each word residing in a different row and each letter of the word occupying a different column in that row, where the words are stored so as to preserve order of the letters within the words, and where each contiguous run of same letters in a column forms an interval, and such that lengths of the intervals are maximized to facilitate data searching, the evaluating operation comprising: for each target word in the table to which the search word is being evaluated, comparing, one letter at a time, letters of the search word to corresponding letters of the target word as represented by the columns in the table; if letters of the search word and the target word satisfy a predetermined matching condition, providing an output representing a successful match, otherwise, skipping ahead in the table to a row where a next interval begins in the column where the comparing operation encountered a letter of the search word failing to match a letter of the target word, and reinitiating the comparing operation; upon completing the evaluating operation without finding a successful match the computer providing an output representing a failed match. 6. The method of claim 1 , where: the table further includes metadata identifying rows below which no occurrences of words of various letter lengths occur in the table; the operations comprise concluding the comparing operation at a row below which there are no remaining occurrences of words with same length in letters as the search word. | 0.685185 |
7,979,362 | 1 | 9 | 1. A non-transitory computer-readable medium storing a program for interactive data mining including programming instructions for: reading in a set of data vectors wherein each data vector comprises a class attribute, and a plurality of additional attributes; counting a plurality of counts of times each particular attribute of said plurality of additional attributes, takes on each of a set of possible values for the particular attribute; and presenting a plurality of histograms on a computer display wherein each of said plurality of histograms includes counts for one of said plurality of additional attributes versus attribute value and wherein said plurality of histograms are presented in a sorted order; wherein said sorted order is based on a sorting-of the histograms according to a metric of non-randomness of distributions shown in said histograms; wherein the metric of non-randomness is a metric of discriminative power with respect to said class attribute. | 1. A non-transitory computer-readable medium storing a program for interactive data mining including programming instructions for: reading in a set of data vectors wherein each data vector comprises a class attribute, and a plurality of additional attributes; counting a plurality of counts of times each particular attribute of said plurality of additional attributes, takes on each of a set of possible values for the particular attribute; and presenting a plurality of histograms on a computer display wherein each of said plurality of histograms includes counts for one of said plurality of additional attributes versus attribute value and wherein said plurality of histograms are presented in a sorted order; wherein said sorted order is based on a sorting-of the histograms according to a metric of non-randomness of distributions shown in said histograms; wherein the metric of non-randomness is a metric of discriminative power with respect to said class attribute. 9. The computer-readable medium according to claim 1 wherein certain of said histograms are truncated to show only a portion of attribute values and are color coded to indicate truncation. | 0.613169 |
9,082,038 | 8 | 10 | 8. A system for improving automated license plate recognition performance, said system comprising: a processor; a data bus coupled to said processor; and a computer-usable medium embodying computer program code, said computer-usable medium being coupled to said data bus, said computer program code comprising instructions executable by said processor and configured for: capturing at least one image of at least one vehicle via an automated license plate recognition engine; obtaining vehicle class information associated with said at least one vehicle; analyzing said vehicle class information with respect to said at least one vehicle to thereby guide the automated license plate recognition engine; and dynamically adjusting a key aspect of the automated license plate recognition engine based on the vehicle class information to thereby enhance recognition of said at least one vehicle via said automated license plate recognition engine. | 8. A system for improving automated license plate recognition performance, said system comprising: a processor; a data bus coupled to said processor; and a computer-usable medium embodying computer program code, said computer-usable medium being coupled to said data bus, said computer program code comprising instructions executable by said processor and configured for: capturing at least one image of at least one vehicle via an automated license plate recognition engine; obtaining vehicle class information associated with said at least one vehicle; analyzing said vehicle class information with respect to said at least one vehicle to thereby guide the automated license plate recognition engine; and dynamically adjusting a key aspect of the automated license plate recognition engine based on the vehicle class information to thereby enhance recognition of said at least one vehicle via said automated license plate recognition engine. 10. The system of claim 8 wherein said instructions are further configured for dynamically resizing said at least one image to improve a rate of capture of said at least one image and license plate data identified in said at least image. | 0.64521 |
7,788,266 | 10 | 11 | 10. The method of claim 1 further comprising determining descriptors to describe the content items, wherein content items having similar descriptors are grouped into the same subsets of content items. | 10. The method of claim 1 further comprising determining descriptors to describe the content items, wherein content items having similar descriptors are grouped into the same subsets of content items. 11. The method of claim 10 wherein said content items comprise television content items, and wherein each descriptor includes title, cast, director, description, or keyword information relating to a content item. | 0.5 |
8,868,405 | 1 | 5 | 1. A computer-implemented method of comparing the semantic content of two or more documents, comprising: accessing a plurality of documents; performing a linguistic analysis on each document; defining a semantic vector for each document based on the linguistic analysis, said semantic vector having multiple components, wherein each component of said semantic vector has at least: a weighting factor relating to an importance, based on characteristics of the document, of said term; and a frequency value relating to a number of occurrences of said term; processing the semantic vector by a digital computer; and comparing a semantic vector of an identified document to the semantic vector for each document in the plurality of documents to determine at least one document semantically similar to the identified document, and wherein the comparing of the semantic vectors includes using a defined metric, wherein said defined metric is related to: Sqrt(f1 2 +f2 2 +f3 2 +f4 2 + +f(N−1) 2 fN 2 )*100n 2 , wherein f is a difference in frequency of a common term between documents and n is the number of terms those documents have in common if the component has a weighting factor; or Sqrt(sum((w−Delta)^2*w−Avg))/(Log(n)^3*1000), wherein w−Delta is the difference in weight between two common terms, w−Avg is the average weight between two common terms, and n is the number of common terms if the component has a frequency value. | 1. A computer-implemented method of comparing the semantic content of two or more documents, comprising: accessing a plurality of documents; performing a linguistic analysis on each document; defining a semantic vector for each document based on the linguistic analysis, said semantic vector having multiple components, wherein each component of said semantic vector has at least: a weighting factor relating to an importance, based on characteristics of the document, of said term; and a frequency value relating to a number of occurrences of said term; processing the semantic vector by a digital computer; and comparing a semantic vector of an identified document to the semantic vector for each document in the plurality of documents to determine at least one document semantically similar to the identified document, and wherein the comparing of the semantic vectors includes using a defined metric, wherein said defined metric is related to: Sqrt(f1 2 +f2 2 +f3 2 +f4 2 + +f(N−1) 2 fN 2 )*100n 2 , wherein f is a difference in frequency of a common term between documents and n is the number of terms those documents have in common if the component has a weighting factor; or Sqrt(sum((w−Delta)^2*w−Avg))/(Log(n)^3*1000), wherein w−Delta is the difference in weight between two common terms, w−Avg is the average weight between two common terms, and n is the number of common terms if the component has a frequency value. 5. The method of claim 1 , wherein each component of the semantic vector for at least one of the documents further comprises a subordinate concept value. | 0.560345 |
8,533,199 | 1 | 20 | 1. A computer-implemented method for creating an intelligent bookmark to a document, comprising: displaying the document comprising at least an address, a title, and a body; receiving a user selection of content from a portion of the body of the document and user supplemented information; generating the intelligent bookmark by retrieving the address of the document, and by automatically extracting identifier information from the body of the document within the user selection; and storing the address in association with the identifier information and the user supplemented information. | 1. A computer-implemented method for creating an intelligent bookmark to a document, comprising: displaying the document comprising at least an address, a title, and a body; receiving a user selection of content from a portion of the body of the document and user supplemented information; generating the intelligent bookmark by retrieving the address of the document, and by automatically extracting identifier information from the body of the document within the user selection; and storing the address in association with the identifier information and the user supplemented information. 20. The method of claim 1 , further comprising: sharing the intelligent bookmark by publication from within a user interface which a user interacts with intelligent bookmarks including formatting the intelligent bookmark to an appropriate format of the publication. | 0.533451 |
8,837,906 | 14 | 17 | 14. A Computer Assisted Dispatch (CAD) system, comprising: a network interface communicatively coupled to a network; a processor communicatively coupled to the network interface; memory comprising instructions that, when executed, cause the processor to: capture keywords from an incident report related to an incident of interest at a first time period; create an incident-specific dictionary for the incident of interest based on the captured keywords; provide, via the network interface, the incident-specific dictionary from the first time period to at least one video camera capturing video or to a back-end server communicatively coupled to the at least one video camera based on a plurality of factors; capture updated keywords as the incident of interest unfolds at a second time period; update the incident-specific dictionary with the updated keywords; and provide the updated incident-specific dictionary to another video camera or to a back-end server communicatively coupled to the another video camera based on the plurality of factors. | 14. A Computer Assisted Dispatch (CAD) system, comprising: a network interface communicatively coupled to a network; a processor communicatively coupled to the network interface; memory comprising instructions that, when executed, cause the processor to: capture keywords from an incident report related to an incident of interest at a first time period; create an incident-specific dictionary for the incident of interest based on the captured keywords; provide, via the network interface, the incident-specific dictionary from the first time period to at least one video camera capturing video or to a back-end server communicatively coupled to the at least one video camera based on a plurality of factors; capture updated keywords as the incident of interest unfolds at a second time period; update the incident-specific dictionary with the updated keywords; and provide the updated incident-specific dictionary to another video camera or to a back-end server communicatively coupled to the another video camera based on the plurality of factors. 17. The CAD system of claim 14 , wherein the instructions that, when executed, further cause the processor to: receive captured video from the at least one video camera or associated back-end server with the captured video tagged with keywords from the incident-specific dictionary; and perform video analytics on the captured video using the incident-specific dictionary associated therewith. | 0.540888 |
9,715,356 | 1 | 13 | 1. A computer implemented method for controlling an image rendering device to merge intermediate representations of a page to be rendered, the method comprising: receiving a page description language representation of the page, the page description language representation having a plurality of sequential graphic objects ordered by drawing order; forming a plurality of groups of sequentially adjacent graphic objects of the plurality of sequential objects, each group being associated with a z-order according to the drawing order; generating an intermediate representation from each of the groups, wherein at least two of the intermediate representations are generated concurrently; creating a data structure comprising records each corresponding to one of the intermediate representations, a priority of each of the records, and a status of generating the corresponding intermediate representation; merging by the image rendering device, in the z-order, at least two intermediate representations consecutive in the z-order to form a merged intermediate representation independently of an intermediate representation preceding, in the z-order, the at least two intermediate representations, wherein the at least two intermediate representations are selected using the priority and status of the records in the created data structure; and merging, by the image rendering device using the created data structure, the merged intermediate representation and the intermediate representation preceding the merged representation in the z-order to render the page. | 1. A computer implemented method for controlling an image rendering device to merge intermediate representations of a page to be rendered, the method comprising: receiving a page description language representation of the page, the page description language representation having a plurality of sequential graphic objects ordered by drawing order; forming a plurality of groups of sequentially adjacent graphic objects of the plurality of sequential objects, each group being associated with a z-order according to the drawing order; generating an intermediate representation from each of the groups, wherein at least two of the intermediate representations are generated concurrently; creating a data structure comprising records each corresponding to one of the intermediate representations, a priority of each of the records, and a status of generating the corresponding intermediate representation; merging by the image rendering device, in the z-order, at least two intermediate representations consecutive in the z-order to form a merged intermediate representation independently of an intermediate representation preceding, in the z-order, the at least two intermediate representations, wherein the at least two intermediate representations are selected using the priority and status of the records in the created data structure; and merging, by the image rendering device using the created data structure, the merged intermediate representation and the intermediate representation preceding the merged representation in the z-order to render the page. 13. The method according to claim 1 , further comprising selecting, independently of the drawing order of the plurality of sequential graphic objects, the at least two intermediate representations consecutive in z-order from the intermediate representations which have been generated. | 0.568389 |
7,773,738 | 1 | 9 | 1. A method of providing a relayed language interpretation service, comprising: receiving a language interpretation call from a caller at a language interpretation provider; determining a caller language corresponding to a language spoken of the caller; engaging a first interpreter that speaks the caller language and a base language; receiving an indication from the caller that the caller needs interpretation between the caller language and a third-party language; engaging a second interpreter to the language interpretation call that speaks the base language and the third-party language; engaging the third-party to the language interpretation call; and providing over-the-phone interpretation of the caller language into the base language by the first interpreter and over-the-phone interpretation of the base language into the third-party language by the second interpreter such that a conversation is established between the caller and the third-party, the second interpreter hearing the over-the-phone interpretation by the first interpreter so that the second interpreter utilizes the base language for the over-the-phone interpretation of the base language into the third-party language. | 1. A method of providing a relayed language interpretation service, comprising: receiving a language interpretation call from a caller at a language interpretation provider; determining a caller language corresponding to a language spoken of the caller; engaging a first interpreter that speaks the caller language and a base language; receiving an indication from the caller that the caller needs interpretation between the caller language and a third-party language; engaging a second interpreter to the language interpretation call that speaks the base language and the third-party language; engaging the third-party to the language interpretation call; and providing over-the-phone interpretation of the caller language into the base language by the first interpreter and over-the-phone interpretation of the base language into the third-party language by the second interpreter such that a conversation is established between the caller and the third-party, the second interpreter hearing the over-the-phone interpretation by the first interpreter so that the second interpreter utilizes the base language for the over-the-phone interpretation of the base language into the third-party language. 9. The method of claim 1 , wherein permitting over-the-phone interpretation between the language of the caller and the third-party language further comprises: receiving a message from the caller; interpreting the message from a caller language to the base language; interpreting the message from the base language to the third-party language; and providing the message in the third-party language to the third party. | 0.5 |
7,558,792 | 12 | 17 | 12. An apparatus having a central processing unit (CPU) and a memory coupled to said CPU for extracting a human readable list from a document, said apparatus comprising: a display device in operative communication with said CPU for displaying information to a user of said apparatus; a file access mechanism configured to access a file, said file containing data that represents a portion of said document, said data formatted in accordance with a document formatting description (DFD); a parser configured for parsing said data, the parsing including: making corrections to said data when said data is formed incorrectly with respect to the DFD; identifying a plurality of tags in said data; generating a plurality of container tokens, each of said plurality of container tokens corresponding to one of said plurality of tags; and generating a plurality of textual tokens for said data not identified as one of said plurality of tags; a tag path set detection mechanism configured to determine a set of tag paths, each of the tag paths being associated with at least one of the plurality of textual tokens; a tag path of interest detection mechanism configured to determine tag paths of interest, the tag path of interest detection mechanism further configured to: collect all of the tag paths of the set of tag paths; remove duplicate tag paths from the collected tag paths to generate a full tag path set for the document; determine the number of textual tokens for each tag path of the full tag path set; and find tag paths of interest in the full tag path set, each of the tag paths of interest satisfying a predetermined criteria; a semantic analysis mechanism configured to determine a context for each tag path of interest, said context defined by the tag path of interest and a matching pair of said container tokens within the tag path of interest; a contiguous list detection mechanism configured to determine contiguous lists, by performing the steps of: iterating through tokens of the tag oaths of interest to find at least one locatable list; and for each locatable list, perform accumulation of text tokens, the accumulation of text tokens comprising: identifying a first textual token in the respective tag path of interest; accumulating the first textual token into a contiguous list; identifying a second textual token having the same context as the first textual token; accumulating the second textual token into the contiguous list; creating a separator pattern based on tokens between the first textual token and the second textual token, the creating a separator pattern including: discarding white space in the tokens between the first textual token and the second textual token; and discarding tag attributes in the tokens between the first textual token and the second textual token; and checking for another occurrence of the separator pattern following the second textual token, and for each occurrence of the separator pattern: extracting a subsequent text token associated with the occurrence of the separator pattern and accumulating the subsequent textual token into the contiguous list if the subsequent textual token is separated from the previous textual token by only the occurrence of the separator pattern; and terminating the accumulating text tokens for the current locatable list if the subsequent textual token is not separated from the previous textual token by only the occurrence of the separator pattern; the contiguous list detection mechanism including: an interval detection mechanism configured to determine the separator pattern between one of said plurality of textual tokens and an adjacent textual token where both said one of said plurality of textual tokens and said adjacent textual token have said context; and an extraction mechanism configured to extract one or more of said plurality of textual tokens, wherein each of the extracted one or more of said plurality of textual tokens have said context; and a presentation mechanism configured to present one or more of said plurality of textual tokens to said user on said display device as said human readable list, the presentation mechanism including: an audio mechanism to present said human readable list to the user using audio; and a retrievable storage mechanism to store said human readable list in a retrievable electronic file. | 12. An apparatus having a central processing unit (CPU) and a memory coupled to said CPU for extracting a human readable list from a document, said apparatus comprising: a display device in operative communication with said CPU for displaying information to a user of said apparatus; a file access mechanism configured to access a file, said file containing data that represents a portion of said document, said data formatted in accordance with a document formatting description (DFD); a parser configured for parsing said data, the parsing including: making corrections to said data when said data is formed incorrectly with respect to the DFD; identifying a plurality of tags in said data; generating a plurality of container tokens, each of said plurality of container tokens corresponding to one of said plurality of tags; and generating a plurality of textual tokens for said data not identified as one of said plurality of tags; a tag path set detection mechanism configured to determine a set of tag paths, each of the tag paths being associated with at least one of the plurality of textual tokens; a tag path of interest detection mechanism configured to determine tag paths of interest, the tag path of interest detection mechanism further configured to: collect all of the tag paths of the set of tag paths; remove duplicate tag paths from the collected tag paths to generate a full tag path set for the document; determine the number of textual tokens for each tag path of the full tag path set; and find tag paths of interest in the full tag path set, each of the tag paths of interest satisfying a predetermined criteria; a semantic analysis mechanism configured to determine a context for each tag path of interest, said context defined by the tag path of interest and a matching pair of said container tokens within the tag path of interest; a contiguous list detection mechanism configured to determine contiguous lists, by performing the steps of: iterating through tokens of the tag oaths of interest to find at least one locatable list; and for each locatable list, perform accumulation of text tokens, the accumulation of text tokens comprising: identifying a first textual token in the respective tag path of interest; accumulating the first textual token into a contiguous list; identifying a second textual token having the same context as the first textual token; accumulating the second textual token into the contiguous list; creating a separator pattern based on tokens between the first textual token and the second textual token, the creating a separator pattern including: discarding white space in the tokens between the first textual token and the second textual token; and discarding tag attributes in the tokens between the first textual token and the second textual token; and checking for another occurrence of the separator pattern following the second textual token, and for each occurrence of the separator pattern: extracting a subsequent text token associated with the occurrence of the separator pattern and accumulating the subsequent textual token into the contiguous list if the subsequent textual token is separated from the previous textual token by only the occurrence of the separator pattern; and terminating the accumulating text tokens for the current locatable list if the subsequent textual token is not separated from the previous textual token by only the occurrence of the separator pattern; the contiguous list detection mechanism including: an interval detection mechanism configured to determine the separator pattern between one of said plurality of textual tokens and an adjacent textual token where both said one of said plurality of textual tokens and said adjacent textual token have said context; and an extraction mechanism configured to extract one or more of said plurality of textual tokens, wherein each of the extracted one or more of said plurality of textual tokens have said context; and a presentation mechanism configured to present one or more of said plurality of textual tokens to said user on said display device as said human readable list, the presentation mechanism including: an audio mechanism to present said human readable list to the user using audio; and a retrievable storage mechanism to store said human readable list in a retrievable electronic file. 17. The apparatus of claim 12 , further comprising: a specification mechanism configured to specify a list size parameter; and a counting mechanism configured to determine a number of said plurality of textual tokens extracted by the extraction mechanism, wherein the presentation mechanism is conditionally responsive to said list size parameter and said number of said plurality of textual tokens extracted by said extraction mechanism, wherein said number is equal to or greater than said list size parameter. | 0.5 |
9,659,014 | 15 | 18 | 15. A non-transitory computer-readable storage medium comprising computer-readable instructions that, in response to execution, cause a processor to perform operations, comprising: receiving a first media content item that comprises first low-level audio features and first video content having first low-level video features; determining that the first media content item belongs to a first genre of a plurality of genres based on first side channel information, wherein the first side channel information is based at least on the first low-level audio features and the first low-level video features; receiving a second media content item that comprises second audio content having second low-level audio features and second low-level video features; determining that the second media content item belongs to the first genre of the plurality of genres based on second side channel information, wherein the second side channel information is based at least on the second low-level audio features and the second low-level video features; generating a first fingerprint based on the first audio content; in response to determining that the first media content item belongs to the first genre, selecting, based on the first genre, a plurality of audio fingerprints that are associated with the first genre, wherein the selected plurality of audio fingerprints includes a second fingerprint that is based on the second audio content; determining a matching score between the first media content item and the second media content item by comparing the first audio fingerprint of the first audio content and the second audio fingerprint of the second audio content; determining a rate of false-positive matches between media content items that belong to the first genre; applying a weight to the matching score based on the rate of false-positive matches; determining, based on the weighted matching score, that the first audio content matches the second audio content; determining that the second audio content contains copyrighted content, wherein the copyrighted content is associated with a copyright owner; and notifying the copyright owner that the first media content item matches the second media content item. | 15. A non-transitory computer-readable storage medium comprising computer-readable instructions that, in response to execution, cause a processor to perform operations, comprising: receiving a first media content item that comprises first low-level audio features and first video content having first low-level video features; determining that the first media content item belongs to a first genre of a plurality of genres based on first side channel information, wherein the first side channel information is based at least on the first low-level audio features and the first low-level video features; receiving a second media content item that comprises second audio content having second low-level audio features and second low-level video features; determining that the second media content item belongs to the first genre of the plurality of genres based on second side channel information, wherein the second side channel information is based at least on the second low-level audio features and the second low-level video features; generating a first fingerprint based on the first audio content; in response to determining that the first media content item belongs to the first genre, selecting, based on the first genre, a plurality of audio fingerprints that are associated with the first genre, wherein the selected plurality of audio fingerprints includes a second fingerprint that is based on the second audio content; determining a matching score between the first media content item and the second media content item by comparing the first audio fingerprint of the first audio content and the second audio fingerprint of the second audio content; determining a rate of false-positive matches between media content items that belong to the first genre; applying a weight to the matching score based on the rate of false-positive matches; determining, based on the weighted matching score, that the first audio content matches the second audio content; determining that the second audio content contains copyrighted content, wherein the copyrighted content is associated with a copyright owner; and notifying the copyright owner that the first media content item matches the second media content item. 18. The non-transitory computer-readable storage medium of claim 15 , wherein the first media content comprises a plurality of segments that includes a segment of interest, the operations further comprising: expending more resources at the matching on the segment of interest compared to matching other segments of the plurality of segments. | 0.594048 |
8,335,802 | 1 | 11 | 1. A computer-implemented method of distributing information retrieved from one or more data repositories, the method comprising: invoking, at a computer device separate from the one or more data repositories, a producer method to generate a document using data retrieved from one or more data repositories, the producer method selected, at a user interface, from a plurality of producer methods, wherein the plurality of producer methods are configured to generate different documents based on same data retrieved from the one or more data repositories; invoking, at the computer device separate from the one or more data repositories, a converter method to convert the generated document to an output format, the converter method selected, at the user interface, from a plurality of converter methods; and invoking, at the computer device separate from the one or more data repositories, a distributor method to distribute the converted document through a distribution channel, the distributor method selected, at the user interface, from a plurality of distributor methods, wherein the invoking of the producer, converter, and distributor methods is triggered by an event, and wherein the producer, converter, and distributor methods are registered to be selected when the trigger is received; wherein the event is associated, at the user interface, with one or more settings defining the producer, converter, and distributor methods and at least one of the producer, converter, and distributor methods can be added to the one or more settings without affecting existing at least one of producer, converter, and distributor methods defined by the one or more settings, wherein the at least one of the added producer, converter, and distributor methods is configured to operate with the at least one of the invoked producer, converter, and distributor methods; wherein the one or more settings is processed based upon a condition that the event meets a predefined criterion. | 1. A computer-implemented method of distributing information retrieved from one or more data repositories, the method comprising: invoking, at a computer device separate from the one or more data repositories, a producer method to generate a document using data retrieved from one or more data repositories, the producer method selected, at a user interface, from a plurality of producer methods, wherein the plurality of producer methods are configured to generate different documents based on same data retrieved from the one or more data repositories; invoking, at the computer device separate from the one or more data repositories, a converter method to convert the generated document to an output format, the converter method selected, at the user interface, from a plurality of converter methods; and invoking, at the computer device separate from the one or more data repositories, a distributor method to distribute the converted document through a distribution channel, the distributor method selected, at the user interface, from a plurality of distributor methods, wherein the invoking of the producer, converter, and distributor methods is triggered by an event, and wherein the producer, converter, and distributor methods are registered to be selected when the trigger is received; wherein the event is associated, at the user interface, with one or more settings defining the producer, converter, and distributor methods and at least one of the producer, converter, and distributor methods can be added to the one or more settings without affecting existing at least one of producer, converter, and distributor methods defined by the one or more settings, wherein the at least one of the added producer, converter, and distributor methods is configured to operate with the at least one of the invoked producer, converter, and distributor methods; wherein the one or more settings is processed based upon a condition that the event meets a predefined criterion. 11. The method of claim 1 , wherein the document generated with the producer method is an HTML document. | 0.870968 |
8,769,491 | 1 | 2 | 1. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: obtain scripting language code that references a collection of code for executing a first task and a second task, a first portion of the collection of code being associated with a first annotation, of a plurality of annotations, associated with the first task, and a second portion of the collection of code being associated with a second annotation, of the plurality of annotations, associated with the second task, select, for each of the first task and the second task, one of a plurality of threads based on the plurality of annotations, the first annotation specifying a first type of thread to which the first portion of the collection of code should be dispatched, and the second annotation specifying a second type of thread to which the second portion of the collection of code should be dispatched; dispatch, based on the first annotation specifying the first type of thread, the first task to a first thread, of the plurality of threads, for executing the first task in a scripting language environment; dispatch, based on the second annotation specifying the second type of thread, the second task to a second thread, of the plurality of threads, included in a non-scripting language environment, the first task or the second task not being dispatched to one or more threads, of the plurality of threads, based on a third annotation, of the plurality of annotations, the third annotation specifying an identity of the one or more threads and indicating that the first task or the second task should not be dispatched to the identified one or more threads; and cause an execution of the scripting language code, during the execution of the scripting language code, the first task being executed via the first thread in the scripting language environment and the second task being executed via the second thread in the non-scripting language environment. | 1. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: obtain scripting language code that references a collection of code for executing a first task and a second task, a first portion of the collection of code being associated with a first annotation, of a plurality of annotations, associated with the first task, and a second portion of the collection of code being associated with a second annotation, of the plurality of annotations, associated with the second task, select, for each of the first task and the second task, one of a plurality of threads based on the plurality of annotations, the first annotation specifying a first type of thread to which the first portion of the collection of code should be dispatched, and the second annotation specifying a second type of thread to which the second portion of the collection of code should be dispatched; dispatch, based on the first annotation specifying the first type of thread, the first task to a first thread, of the plurality of threads, for executing the first task in a scripting language environment; dispatch, based on the second annotation specifying the second type of thread, the second task to a second thread, of the plurality of threads, included in a non-scripting language environment, the first task or the second task not being dispatched to one or more threads, of the plurality of threads, based on a third annotation, of the plurality of annotations, the third annotation specifying an identity of the one or more threads and indicating that the first task or the second task should not be dispatched to the identified one or more threads; and cause an execution of the scripting language code, during the execution of the scripting language code, the first task being executed via the first thread in the scripting language environment and the second task being executed via the second thread in the non-scripting language environment. 2. The non-transitory computer-readable medium of claim 1 , where the collection of code is written in a non-scripting language. | 0.92669 |
10,007,868 | 1 | 7 | 1. In a digital medium environment to enable font replacement at a destination device for a document created at a source device, at least one computing device including a processing system and memory having instructions stored thereon that are executable by the processing system to perform operations comprising: receiving from a remote computing device a document having a font descriptor appended thereto, the font descriptor corresponding to a font of the document; extracting the font descriptor from the document, the font descriptor including font features derived from a visual appearance of the font using a font visual similarity model trained with machine learning; determining a similar font descriptor by comparing the font descriptor to multiple font descriptors that respectively correspond to multiple local fonts that are available at the at least one computing device; ascertaining from among the multiple local fonts a similar font that corresponds to the similar font descriptor; and controlling presentation of the document using the similar font. | 1. In a digital medium environment to enable font replacement at a destination device for a document created at a source device, at least one computing device including a processing system and memory having instructions stored thereon that are executable by the processing system to perform operations comprising: receiving from a remote computing device a document having a font descriptor appended thereto, the font descriptor corresponding to a font of the document; extracting the font descriptor from the document, the font descriptor including font features derived from a visual appearance of the font using a font visual similarity model trained with machine learning; determining a similar font descriptor by comparing the font descriptor to multiple font descriptors that respectively correspond to multiple local fonts that are available at the at least one computing device; ascertaining from among the multiple local fonts a similar font that corresponds to the similar font descriptor; and controlling presentation of the document using the similar font. 7. The at least one computing device as described in claim 1 , wherein: the determining comprises determining multiple similar font descriptors, including the similar font descriptor; and the controlling presentation comprises: causing display of a collection of local fonts that correspond to the multiple similar font descriptors; detecting a local font selection by a user from among the collection of local fonts; and causing the presentation of the document using the selected local font as the similar font. | 0.644244 |
8,553,065 | 9 | 13 | 9. Logic encoded in non-transitory media that includes code for execution and when executed by a processor is operable to perform operations comprising: identifying a particular word recited by an active speaker in a conference involving a plurality of endpoints in a network environment; evaluating a profile associated with the active speaker in order to identify contextual information associated with the particular word; determining augmented data associated with the particular word based on the contextual information identified from the profile associated with the active speaker; providing augmented data associated with the particular word to at least some of the plurality of endpoints. | 9. Logic encoded in non-transitory media that includes code for execution and when executed by a processor is operable to perform operations comprising: identifying a particular word recited by an active speaker in a conference involving a plurality of endpoints in a network environment; evaluating a profile associated with the active speaker in order to identify contextual information associated with the particular word; determining augmented data associated with the particular word based on the contextual information identified from the profile associated with the active speaker; providing augmented data associated with the particular word to at least some of the plurality of endpoints. 13. The logic of claim 9 , wherein the augmented data is provided on a display of a video conference. | 0.674194 |
9,348,935 | 12 | 21 | 12. A system for delivering related video content for augmented keywords on a web page, the system comprising: a server comprising a processor, the server receiving from an agent executing within a browser, responsive to the agent detecting a mouse over a keyword currently displayed on a web page of a client, the keyword identified for augmentation via a user interface overlay and identifying a plurality of videos related to the keyword, the server configured to dynamically select, responsive to receiving the keyword at a time of the mouse over, one or more videos for the user interface overlay for the keyword; a content relevancy engine determining an order of relevance of the plurality of videos to the keyword; and wherein the server selects one or more videos of the plurality of videos with a higher order of relevance and transmits to the agent of the client, within a predetermined time period from receipt of the keyword from the agent responsive to the agent detecting the mouse over, the user interface overlay, to be displayed by the agent responsive to the mouse over, to include the selected one or more videos of the plurality of videos with a higher order of relevance for at least one of user selection or display in the user interface overlay, the predetermined time period comprising a time threshold within which the server is to complete the selection of the one or more videos and to complete delivery of the selected one or more videos to the client. | 12. A system for delivering related video content for augmented keywords on a web page, the system comprising: a server comprising a processor, the server receiving from an agent executing within a browser, responsive to the agent detecting a mouse over a keyword currently displayed on a web page of a client, the keyword identified for augmentation via a user interface overlay and identifying a plurality of videos related to the keyword, the server configured to dynamically select, responsive to receiving the keyword at a time of the mouse over, one or more videos for the user interface overlay for the keyword; a content relevancy engine determining an order of relevance of the plurality of videos to the keyword; and wherein the server selects one or more videos of the plurality of videos with a higher order of relevance and transmits to the agent of the client, within a predetermined time period from receipt of the keyword from the agent responsive to the agent detecting the mouse over, the user interface overlay, to be displayed by the agent responsive to the mouse over, to include the selected one or more videos of the plurality of videos with a higher order of relevance for at least one of user selection or display in the user interface overlay, the predetermined time period comprising a time threshold within which the server is to complete the selection of the one or more videos and to complete delivery of the selected one or more videos to the client. 21. The system of claim 12 , wherein the server transmits to the client the selected one or more videos that are available to select from before the time threshold and transmit to the client within the predetermined time period. | 0.713568 |
9,836,448 | 17 | 21 | 17. A non-transitory computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to at least perform: responsive to user input corresponding to at least one keystroke received at the apparatus during text entry in a text editing program, disambiguate ambiguous keystrokes from the user input at least based on simultaneous use of a common language dictionary, a user dictionary, and a first specific subject matter lexicon selected by a user of the apparatus, wherein the first selected subject matter lexicon is related to a first particular professional area; then, in response to a user input indicating a lexicon swap, display a plurality of specific subject matter lexicons to the user of the apparatus while causing the apparatus to display text previously entered within the text editing program; receive a selection by the user of the apparatus of a second specific subject matter lexicon from the plurality of specific subject matter lexicons displayed to the user, wherein the second specific subject matter lexicon is related to a second particular professional area; disambiguate the ambiguous keystrokes from the user input at least based on simultaneous use of the common language dictionary, the user dictionary, and the second specific subject matter lexicon; and display at least one disambiguation result to the user of the apparatus. | 17. A non-transitory computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to at least perform: responsive to user input corresponding to at least one keystroke received at the apparatus during text entry in a text editing program, disambiguate ambiguous keystrokes from the user input at least based on simultaneous use of a common language dictionary, a user dictionary, and a first specific subject matter lexicon selected by a user of the apparatus, wherein the first selected subject matter lexicon is related to a first particular professional area; then, in response to a user input indicating a lexicon swap, display a plurality of specific subject matter lexicons to the user of the apparatus while causing the apparatus to display text previously entered within the text editing program; receive a selection by the user of the apparatus of a second specific subject matter lexicon from the plurality of specific subject matter lexicons displayed to the user, wherein the second specific subject matter lexicon is related to a second particular professional area; disambiguate the ambiguous keystrokes from the user input at least based on simultaneous use of the common language dictionary, the user dictionary, and the second specific subject matter lexicon; and display at least one disambiguation result to the user of the apparatus. 21. The non-transitory computer readable storage medium of claim 17 , further configured to cause the apparatus to provide a download link pointing to a lexicon server. | 0.835616 |
7,957,974 | 21 | 22 | 21. The apparatus of claim 20 , wherein the action header field indicates an action, the prerequisite field specifies any prerequisites needed to perform the action, the sub-action field specifies any sub-actions which are needed to complete execution of the action, and the action effect field specifies a result of execution of the action. | 21. The apparatus of claim 20 , wherein the action header field indicates an action, the prerequisite field specifies any prerequisites needed to perform the action, the sub-action field specifies any sub-actions which are needed to complete execution of the action, and the action effect field specifies a result of execution of the action. 22. The apparatus of claim 21 , wherein the action planning unit determines whether or not a prerequisite included in the action data corresponding to the logical command is satisfied, and wherein if the result of determining whether or not a prerequisite included in the action data corresponding to the logical command is satisfied indicates that the prerequisite is not satisfied and an action capable of satisfying the prerequisite is not in the action library, the action planning unit outputs an error message. | 0.515947 |
9,704,177 | 16 | 17 | 16. The computer-readable storage device as defined in claim 15 wherein the Turing test further evaluates the interactivity characteristics of the one or more avatars. | 16. The computer-readable storage device as defined in claim 15 wherein the Turing test further evaluates the interactivity characteristics of the one or more avatars. 17. The computer-readable storage device as defined in claim 16 wherein the Turing test comprises a set of challenge-response questions posed to the one or more avatars to determine the interactivity characteristics each of the one or more avatars. | 0.5 |
9,524,323 | 1 | 4 | 1. A method, implemented at a computer system that includes one or more processors, of evaluating an expression tree, the method comprising: at a first domain, accessing an expression tree comprising a plurality of nested expressions, the plurality of nested expressions spanning a plurality of domains, and including: (i) one or more first nested expressions that are expressed in a first dialect of the first domain in a manner that they are expandable to a second dialect of a second domain for evaluation by the second domain, and (ii) one or more second nested expressions that are expressed in the first dialect of the first domain in a manner that they are expandable to a third dialect of a third domain for evaluation by the third domain, wherein the first dialect, the second dialect, and the third dialect are each different from each other, and wherein the expression tree contains all information needed to expand the one or more first nested expressions from the first dialect to the second dialect and contains all information needed to expand the one or more second nested expressions from the first dialect to the third dialect; determining that the one or more first expressions are to be evaluated by the second domain, and that the one or more second expressions are to be evaluated by the third domain; and based at least on determining that the one or more first expressions and the one or more second expressions are to evaluated by the second and third domains, respectively, expanding the one or more first expressions to the second dialect, and expanding the one or more second expressions to the third dialect. | 1. A method, implemented at a computer system that includes one or more processors, of evaluating an expression tree, the method comprising: at a first domain, accessing an expression tree comprising a plurality of nested expressions, the plurality of nested expressions spanning a plurality of domains, and including: (i) one or more first nested expressions that are expressed in a first dialect of the first domain in a manner that they are expandable to a second dialect of a second domain for evaluation by the second domain, and (ii) one or more second nested expressions that are expressed in the first dialect of the first domain in a manner that they are expandable to a third dialect of a third domain for evaluation by the third domain, wherein the first dialect, the second dialect, and the third dialect are each different from each other, and wherein the expression tree contains all information needed to expand the one or more first nested expressions from the first dialect to the second dialect and contains all information needed to expand the one or more second nested expressions from the first dialect to the third dialect; determining that the one or more first expressions are to be evaluated by the second domain, and that the one or more second expressions are to be evaluated by the third domain; and based at least on determining that the one or more first expressions and the one or more second expressions are to evaluated by the second and third domains, respectively, expanding the one or more first expressions to the second dialect, and expanding the one or more second expressions to the third dialect. 4. The method of claim 1 , wherein determining that the one or more first expressions are to be evaluated by the second domain comprises determining that the one or more first expressions are expressed using a particular type. | 0.555118 |
8,943,100 | 32 | 34 | 32. The method according to claim 29 , wherein a structure in the structure dictionary assigned to a data attribute takes a form of a word built from an alphabet of symbols taking a form of constants corresponding to alpha-numeric strings and characters, as well as variables corresponding to generic data types including numeric, alpha-numeric and binary data types, and further comprising building the word using formation rules of a formal language, the structure sub-collections corresponding to the word being formed out of the symbol sub-collections corresponding to symbols being used in the word, the method of building a symbol sub-collection for portions of the values corresponding to a symbol being used in the word comprising: assigning to the symbol an ordered list of a plurality of possible values of the symbol, the list containing values selected based on at least one of inclusion of all values that previously occurred in data, interaction with a user, automatic detection of values occurring most frequently in data, and automatic detection of values occurring most frequently in a history of queries; and for each collection of values corresponding to the data attribute, forming the symbol sub-collection as a table, wherein each portion of the value that matches the symbol is labeled by an ordinal number of the portion of the value, the value matching the word, the ordinal number being taken as the position of the portion of the value in the list of the plurality of possible values, the list of the plurality of possible values being the same for all collections of values corresponding to the data attribute. | 32. The method according to claim 29 , wherein a structure in the structure dictionary assigned to a data attribute takes a form of a word built from an alphabet of symbols taking a form of constants corresponding to alpha-numeric strings and characters, as well as variables corresponding to generic data types including numeric, alpha-numeric and binary data types, and further comprising building the word using formation rules of a formal language, the structure sub-collections corresponding to the word being formed out of the symbol sub-collections corresponding to symbols being used in the word, the method of building a symbol sub-collection for portions of the values corresponding to a symbol being used in the word comprising: assigning to the symbol an ordered list of a plurality of possible values of the symbol, the list containing values selected based on at least one of inclusion of all values that previously occurred in data, interaction with a user, automatic detection of values occurring most frequently in data, and automatic detection of values occurring most frequently in a history of queries; and for each collection of values corresponding to the data attribute, forming the symbol sub-collection as a table, wherein each portion of the value that matches the symbol is labeled by an ordinal number of the portion of the value, the value matching the word, the ordinal number being taken as the position of the portion of the value in the list of the plurality of possible values, the list of the plurality of possible values being the same for all collections of values corresponding to the data attribute. 34. The method according to claim 32 , wherein the method of storing symbol sub-collections corresponding to a symbol of a word in the structure dictionary corresponding to a data attribute comprises: assigning the collections of portions of the values corresponding to the symbol to a sub-structure dictionary, the sub-structure dictionary being the same for all collections of values corresponding to the attribute; for each sub-structure in the sub-structure dictionary, forming the sub-structure match lists from ordinal numbers of portions of the values matching the sub-structure, and the sub-structure sub-collections from portions of the values matching the sub-structure; forming the sub-outlier match lists from ordinal numbers of portions of the values not matching any sub-structure in the sub-structure dictionary, and the sub-outlier sub-collections out of portions of the values not matching any sub-structure in the sub-structure dictionary; and storing the symbol sub-collections in a form of the sub-structure match lists, the sub-structure sub-collections, the sub-outlier match lists and the sub-outlier sub-collections. | 0.5 |
9,684,430 | 1 | 6 | 1. A method, comprising: receiving a message from a user, the message comprising linguistic content; performing a lexical analysis of the linguistic content to determine one or more tokens within the linguistic content, wherein a token comprises words or phrases of the linguistic content that are indicative of an emotion, and wherein the one or more tokens comprise either emote types or word types, the emote types triggering a higher priority emotion than emotions triggered by the presence of the word types; assigning a higher priority to any of the one or more tokens occurring at an end of the message; selecting one or more facial expressions of an avatar of the user based on the one or more tokens present in the linguistic content, the selection based on the assignment of the higher priority to any of the one or more tokens occurring at the end of the message; and displaying, on a user interface of a computing device, the avatar of the user, with the selected one or more facial expressions. | 1. A method, comprising: receiving a message from a user, the message comprising linguistic content; performing a lexical analysis of the linguistic content to determine one or more tokens within the linguistic content, wherein a token comprises words or phrases of the linguistic content that are indicative of an emotion, and wherein the one or more tokens comprise either emote types or word types, the emote types triggering a higher priority emotion than emotions triggered by the presence of the word types; assigning a higher priority to any of the one or more tokens occurring at an end of the message; selecting one or more facial expressions of an avatar of the user based on the one or more tokens present in the linguistic content, the selection based on the assignment of the higher priority to any of the one or more tokens occurring at the end of the message; and displaying, on a user interface of a computing device, the avatar of the user, with the selected one or more facial expressions. 6. The method according to claim 1 , wherein the token comprises a root token and one or more additional tokens that extend the root token. | 0.726378 |
8,111,911 | 12 | 14 | 12. A computer program product comprising a non-transitory computer useable medium having computer readable program code functions embedded in said medium for causing a computer to: acquire a text image containing a line of Arabic characters; digitize the line of the Arabic characters to form a two-dimensional array of pixels each associated with a pixel value, wherein the pixel value is expressed in a binary number; divide the line of the Arabic characters into a plurality of line images, wherein the two-dimensional array of pixels comprises a plurality of rows in a first direction and a plurality of columns in a second direction, wherein the line of Arabic characters is aligned substantially along the first direction, wherein the plurality of line images are sequentially aligned along the first direction and have a width between 2 and 100 columns of pixels; define a plurality of cells in one of the plurality of line images, wherein each of the plurality of cells comprises a group of adjacent pixels; serialize pixel values of pixels in each of the plurality of cells in one of the plurality of line images to form a binary cell number; form a text feature vector according to binary cell numbers obtained from the plurality of cells in one of the plurality of line images; and feed the text feature vector into a Hidden Markov Model to recognize the line of Arabic characters. | 12. A computer program product comprising a non-transitory computer useable medium having computer readable program code functions embedded in said medium for causing a computer to: acquire a text image containing a line of Arabic characters; digitize the line of the Arabic characters to form a two-dimensional array of pixels each associated with a pixel value, wherein the pixel value is expressed in a binary number; divide the line of the Arabic characters into a plurality of line images, wherein the two-dimensional array of pixels comprises a plurality of rows in a first direction and a plurality of columns in a second direction, wherein the line of Arabic characters is aligned substantially along the first direction, wherein the plurality of line images are sequentially aligned along the first direction and have a width between 2 and 100 columns of pixels; define a plurality of cells in one of the plurality of line images, wherein each of the plurality of cells comprises a group of adjacent pixels; serialize pixel values of pixels in each of the plurality of cells in one of the plurality of line images to form a binary cell number; form a text feature vector according to binary cell numbers obtained from the plurality of cells in one of the plurality of line images; and feed the text feature vector into a Hidden Markov Model to recognize the line of Arabic characters. 14. The computer program product of claim 12 , wherein the two-dimensional array of pixels comprises N number of rows of pixels, wherein at least one of the plurality of line images has a height defined by M number of rows in the first direction and a width defined by N number of columns in the second direction, wherein M and N are integers. | 0.690433 |
8,538,790 | 19 | 23 | 19. A computer-implemented method for generating an electronically generated business intelligence report, comprising: generating by a computer system a plurality of category indicators each identifying one predefined business-related category of a plurality of predefined business-related categories, wherein the plurality of predefined business-related categories comprises at least two predefined business-related categories selected from the group consisting of customer service, products, marketing, and sales; and generating by the computer system a plurality of quantitative indicators identifying, for each of the plurality of predefined business-related categories, one or more quantitative values derived from user comments collected from users of one or more web pages using feedback collection software that provides users who access a particular web page a viewable element through which to provide their comments regarding one or more aspects of a business associated with the particular web page, wherein: a quantitative value identified in the report for a particular predefined business-related category comprises a quantity of collected user comments assigned to a particular rating, the collected user comments being assigned to one of the plurality of available ratings based on a subjective assessment of each of the collected user comments; and the subjective assessment comprises a keyword association. | 19. A computer-implemented method for generating an electronically generated business intelligence report, comprising: generating by a computer system a plurality of category indicators each identifying one predefined business-related category of a plurality of predefined business-related categories, wherein the plurality of predefined business-related categories comprises at least two predefined business-related categories selected from the group consisting of customer service, products, marketing, and sales; and generating by the computer system a plurality of quantitative indicators identifying, for each of the plurality of predefined business-related categories, one or more quantitative values derived from user comments collected from users of one or more web pages using feedback collection software that provides users who access a particular web page a viewable element through which to provide their comments regarding one or more aspects of a business associated with the particular web page, wherein: a quantitative value identified in the report for a particular predefined business-related category comprises a quantity of collected user comments assigned to a particular rating, the collected user comments being assigned to one of the plurality of available ratings based on a subjective assessment of each of the collected user comments; and the subjective assessment comprises a keyword association. 23. The method of claim 19 , further comprising generating a bar graph, the plurality of quantitative indicators comprising color-coded bars, each color-coded bar representing one of the plurality of predefined business-related categories, and each color representing one of the plurality of available ratings. | 0.5 |
8,068,657 | 8 | 9 | 8. The method of claim 1 further comprising displaying microcalcification sites corresponding to the positive candidate set on a display screen with markers of a first shape. | 8. The method of claim 1 further comprising displaying microcalcification sites corresponding to the positive candidate set on a display screen with markers of a first shape. 9. The method of claim 8 further comprising displaying microcalcification sites that were added to the positive candidate set by the reclamation classifier process with markers of a second shape. | 0.5 |
6,108,675 | 27 | 28 | 27. The computer program of claim 26 further including: means for calculating the distance by which the width of a screen page exceeds the width of the window within which the page is to be displayed, and means for setting said sequence of horizontal sampling positions at increments of said distance. | 27. The computer program of claim 26 further including: means for calculating the distance by which the width of a screen page exceeds the width of the window within which the page is to be displayed, and means for setting said sequence of horizontal sampling positions at increments of said distance. 28. The computer program of claim 27 wherein said means for sampling said information density sequentially samples the information density along a plurality of horizontal lines, and said means for comparing compares each sequential sample on each of said plurality of lines to said selected density level, and further including means for calculating a mean horizontal position at which said selected density level is attained in said plurality of lines, said mean horizontal position being said reference margin. | 0.5 |
9,658,931 | 1 | 11 | 1. A computer system for testing a remote system, the computer system comprising: a memory unit that stores instructions; and at least one processing unit that executes the instructions to: receive a representation of a graphical user interface of the remote system; and control a flow of execution based on a testing script, the flow of execution including: search the received representation of the remote system graphical user interface for a graphical element based on an image analysis; and responsive to a result of searching the received representation of the remote system graphical user interface for the graphical element, automatically provide a signal through a communications channel to execute an emulated user input action on the remote system graphical user interface, wherein the input action is specified by a specific script command in the testing script. | 1. A computer system for testing a remote system, the computer system comprising: a memory unit that stores instructions; and at least one processing unit that executes the instructions to: receive a representation of a graphical user interface of the remote system; and control a flow of execution based on a testing script, the flow of execution including: search the received representation of the remote system graphical user interface for a graphical element based on an image analysis; and responsive to a result of searching the received representation of the remote system graphical user interface for the graphical element, automatically provide a signal through a communications channel to execute an emulated user input action on the remote system graphical user interface, wherein the input action is specified by a specific script command in the testing script. 11. The computer system of claim 1 , wherein the at least one processing unit further executes the instructions to: capture user input effected with respect to the representation of the remote system graphical user interface display; and generate the testing script based on the captured user input. | 0.674292 |
8,909,667 | 1 | 5 | 1. A method of generating media item recommendations, the method comprising: using at least a processor and memory of a computing device for: obtaining play schedules associated with a plurality of other computing devices, the other computing devices currently playing or recently having played a reference media item, at least one of the play schedules comprising media items scheduled to be played and recently played media items; determining recommendation scores for candidate media items contained in the play schedules; and generating a media item recommendation for the reference media item based on the recommendation scores. | 1. A method of generating media item recommendations, the method comprising: using at least a processor and memory of a computing device for: obtaining play schedules associated with a plurality of other computing devices, the other computing devices currently playing or recently having played a reference media item, at least one of the play schedules comprising media items scheduled to be played and recently played media items; determining recommendation scores for candidate media items contained in the play schedules; and generating a media item recommendation for the reference media item based on the recommendation scores. 5. The method of claim 1 , wherein all of the media items are one of audio, video, and text. | 0.771144 |
9,449,028 | 8 | 11 | 8. A computer-implemented method to access a definitive image, the method comprising: storing, in an image data store, one or more images or references to images stored in other data stores; receiving a request during a query for the definitive image that is representative of a topic of the query; maintaining an inverted index of images that maps one or more query terms to one or more images that are related to the one or more query terms; ranking one or more images identified in the inverted index that potentially match the query terms to sort the identified one or more images by a relative likelihood of being the definitive image for the topic of the query; selecting the definitive image based on one or more images returned from the inverted index, any overridden editor-chosen definitive image, and the ranking, wherein the editor-chosen definitive image is identified by manually overriding a system selected definitive image from a human editor; retrieving an image binary associated with the selected definitive image based on an image identifier associated with the selected definitive image; and sending the retrieved image binary associated with the selected definitive image in response to the received request; wherein the preceding steps are performed by at least one processor. | 8. A computer-implemented method to access a definitive image, the method comprising: storing, in an image data store, one or more images or references to images stored in other data stores; receiving a request during a query for the definitive image that is representative of a topic of the query; maintaining an inverted index of images that maps one or more query terms to one or more images that are related to the one or more query terms; ranking one or more images identified in the inverted index that potentially match the query terms to sort the identified one or more images by a relative likelihood of being the definitive image for the topic of the query; selecting the definitive image based on one or more images returned from the inverted index, any overridden editor-chosen definitive image, and the ranking, wherein the editor-chosen definitive image is identified by manually overriding a system selected definitive image from a human editor; retrieving an image binary associated with the selected definitive image based on an image identifier associated with the selected definitive image; and sending the retrieved image binary associated with the selected definitive image in response to the received request; wherein the preceding steps are performed by at least one processor. 11. The method of claim 8 further comprising accessing a hash table of a store of editorial overrides according to the topic for efficiently looking up editorial overrides for definitive images. | 0.610442 |
10,002,187 | 1 | 7 | 1. A method implemented with a processor, comprising: generating a user interface that displays analysis results identified from within one or more social media data sources, the user interface comprising: (a) a first interface portion of the user interface comprising a list of one or more analysis results identified from within one or more social media data sources, an individual analysis result from among the one or more analysis results being selectable to display a set of terms associated with a selected individual analysis result in a second interface portion, (b) the second interface portion of the user interface comprising the set of terms, a first interface control, and a second interface control, the set of terms associated with the selected individual analysis result, the first interface control constraining a search to include themes that correspond to the selected individual analysis result, the second interface control constraining the search to exclude the themes that correspond to the selected individual analysis result, and (c) a third interface portion of the user interface comprising a set of one or more semantic filters selected according to the second interface portion; receiving a search criteria to perform a search of content from the one or more social media data sources; performing the search of the content from the one or more social media data sources to generate the list of the one or more analysis results, a volatility index corresponding to a level of commonality between two or more themes being generated for the one or more analysis results, the volatility index usable to automatically control creation of a new topic based at least in part upon a threshold value established for the volatility index, the level of commonality between the two or more themes is calculated by computing centroids for the two or more themes and determining distances between the centroids; displaying the list of one or more analysis results identified from within one or more social media data sources pertaining to the search criteria in the first interface portion of the user interface; receiving a selection of the first or second interface control in the second interface portion of the user interface corresponding to an application of a semantic filter, the semantic filter constraining the search of the content from the one or more social media data sources by: (a) adding the semantic filter to definition parameters for the new topic if the first interface control is selected; (b) adding the semantic filter to the set of one or more semantic filters in the third interface portion of the user interface if the second interface control is selected; and (c) performing a modified search of the content with application of the semantic filter, the modified search updating the list of one or more analysis results identified from within one or more social media data sources in the first interface portion of the user interface to either remove or add results in the first interface portion that pertain to the semantic filter; and creating the new topic based at least in part on the definition parameters, wherein the new topic corresponds to the search criteria and the semantic filter. | 1. A method implemented with a processor, comprising: generating a user interface that displays analysis results identified from within one or more social media data sources, the user interface comprising: (a) a first interface portion of the user interface comprising a list of one or more analysis results identified from within one or more social media data sources, an individual analysis result from among the one or more analysis results being selectable to display a set of terms associated with a selected individual analysis result in a second interface portion, (b) the second interface portion of the user interface comprising the set of terms, a first interface control, and a second interface control, the set of terms associated with the selected individual analysis result, the first interface control constraining a search to include themes that correspond to the selected individual analysis result, the second interface control constraining the search to exclude the themes that correspond to the selected individual analysis result, and (c) a third interface portion of the user interface comprising a set of one or more semantic filters selected according to the second interface portion; receiving a search criteria to perform a search of content from the one or more social media data sources; performing the search of the content from the one or more social media data sources to generate the list of the one or more analysis results, a volatility index corresponding to a level of commonality between two or more themes being generated for the one or more analysis results, the volatility index usable to automatically control creation of a new topic based at least in part upon a threshold value established for the volatility index, the level of commonality between the two or more themes is calculated by computing centroids for the two or more themes and determining distances between the centroids; displaying the list of one or more analysis results identified from within one or more social media data sources pertaining to the search criteria in the first interface portion of the user interface; receiving a selection of the first or second interface control in the second interface portion of the user interface corresponding to an application of a semantic filter, the semantic filter constraining the search of the content from the one or more social media data sources by: (a) adding the semantic filter to definition parameters for the new topic if the first interface control is selected; (b) adding the semantic filter to the set of one or more semantic filters in the third interface portion of the user interface if the second interface control is selected; and (c) performing a modified search of the content with application of the semantic filter, the modified search updating the list of one or more analysis results identified from within one or more social media data sources in the first interface portion of the user interface to either remove or add results in the first interface portion that pertain to the semantic filter; and creating the new topic based at least in part on the definition parameters, wherein the new topic corresponds to the search criteria and the semantic filter. 7. The method of claim 1 , wherein snippets are obtained from the content, and the snippets are analyzed to generate search results. | 0.861925 |
8,959,101 | 1 | 13 | 1. A system for enabling a user to locate information of interest in different human languages, comprising: one or more databases containing terms in a first human language, wherein the terms are organized into a hierarchical structure; a first computer executing search interface software recorded on a computer-readable medium and associated with a collection of information in a second human language, wherein the search interface software when executed causes the first computer to receive search queries in the second human language and to communicate search results from the collection of information in the second human language; and a second computer executing user interface software recorded on a computer-readable medium, wherein the user interface software when executed causes the second computer to communicate with the one or more databases, the search interface software, and a user, and to: access the terms in the first human language from the one or more databases; communicate with the user to allow the user to navigate through the terms in accordance with the hierarchical structure; receive an indication that the user has selected one or more of the terms in the first human language; generate a draft search query in the second human language based on a translation of the selected one or more terms; display the draft search query in the second human language to the user; receive a revised search query in the second human language from the user; communicate the revised search query in the second human language to the first computer executing the search interface software; receive from the first computer search results in the second human language; and communicate the search results in the second human language to the user, wherein the one or more databases, the first computer, and the second computer are in communication with a computer network. | 1. A system for enabling a user to locate information of interest in different human languages, comprising: one or more databases containing terms in a first human language, wherein the terms are organized into a hierarchical structure; a first computer executing search interface software recorded on a computer-readable medium and associated with a collection of information in a second human language, wherein the search interface software when executed causes the first computer to receive search queries in the second human language and to communicate search results from the collection of information in the second human language; and a second computer executing user interface software recorded on a computer-readable medium, wherein the user interface software when executed causes the second computer to communicate with the one or more databases, the search interface software, and a user, and to: access the terms in the first human language from the one or more databases; communicate with the user to allow the user to navigate through the terms in accordance with the hierarchical structure; receive an indication that the user has selected one or more of the terms in the first human language; generate a draft search query in the second human language based on a translation of the selected one or more terms; display the draft search query in the second human language to the user; receive a revised search query in the second human language from the user; communicate the revised search query in the second human language to the first computer executing the search interface software; receive from the first computer search results in the second human language; and communicate the search results in the second human language to the user, wherein the one or more databases, the first computer, and the second computer are in communication with a computer network. 13. The system of claim 1 , wherein the one or more databases comprise a commerce terms database. | 0.931303 |
4,656,603 | 1 | 2 | 1. A general purpose interactive rule based system for generating problem solutions in schematic diagram form comprising: a computer processor; a graphics terminal coupled to said processor; means for providing a multi-portion split display on said graphics terminal; a plurality of functions and graphic primitives stored in said computer processor; means for creating a library of icons for an intended application by enabling a methodology designer to: select and arrange said graphic primitives using said graphics terminal, and identify, by way of example, parameters for using each icon in response to prompts initiated by said computer processor; means for generating and storing a specific set of rules pertaining to the use of each icon on the basis of the parameters identified; means for symbolically displaying in one portion of said split display a set of icons from said library; means for displaying in another portion of said split display a set of said functions; and means for enabling a problem solving user to access and select displayed icons and functions, and to build a solution to a problem by using functions to graphically couple icons together on a chart work area portion of said split display in accordance with said rules. | 1. A general purpose interactive rule based system for generating problem solutions in schematic diagram form comprising: a computer processor; a graphics terminal coupled to said processor; means for providing a multi-portion split display on said graphics terminal; a plurality of functions and graphic primitives stored in said computer processor; means for creating a library of icons for an intended application by enabling a methodology designer to: select and arrange said graphic primitives using said graphics terminal, and identify, by way of example, parameters for using each icon in response to prompts initiated by said computer processor; means for generating and storing a specific set of rules pertaining to the use of each icon on the basis of the parameters identified; means for symbolically displaying in one portion of said split display a set of icons from said library; means for displaying in another portion of said split display a set of said functions; and means for enabling a problem solving user to access and select displayed icons and functions, and to build a solution to a problem by using functions to graphically couple icons together on a chart work area portion of said split display in accordance with said rules. 2. The system of claim 1 further comprising means for enabling a methodology designer to select and concatenate functions to each other and to icons, using said graphics terminal, to create more complex functions for display and for use in building problem solutions. | 0.723602 |
7,676,488 | 11 | 13 | 11. A computer processing apparatus comprising a processor and a memory, the memory storing: an XML repository to store XML documents containing a design document for rendering a report, the design document specifying at least one section having a visual format and at least one associated condition, the at least one condition being written in XML and defining at least one criterion for rendering the report according to the corresponding visual format; a grammar repository that stores XML Schema definitions for the XML documents, the XML Schema definitions corresponding to the design document and comprising a pre-defined grammar that defines a correct markup language syntax for the design and the associated conditions; a parser that is implemented by the processor and that retrieves an XML document form the XML repository and a corresponding XML Schema definition from the grammar repository, the parser rendering the report, the rendering comprising evaluating each associated condition for each section to determine if the logical expression is true, and, if the logical expression is true, applying the visual representation described by the condition; a verification unit coupled to the parser, the verification unit applying the predefined grammar to the design document and to the at least one condition to provide an indication whether the design and the at least one condition in the retrieved XML document are syntactically correct; and a graphical user interface to display portions of the retrieved XML document that are not syntactically correct. | 11. A computer processing apparatus comprising a processor and a memory, the memory storing: an XML repository to store XML documents containing a design document for rendering a report, the design document specifying at least one section having a visual format and at least one associated condition, the at least one condition being written in XML and defining at least one criterion for rendering the report according to the corresponding visual format; a grammar repository that stores XML Schema definitions for the XML documents, the XML Schema definitions corresponding to the design document and comprising a pre-defined grammar that defines a correct markup language syntax for the design and the associated conditions; a parser that is implemented by the processor and that retrieves an XML document form the XML repository and a corresponding XML Schema definition from the grammar repository, the parser rendering the report, the rendering comprising evaluating each associated condition for each section to determine if the logical expression is true, and, if the logical expression is true, applying the visual representation described by the condition; a verification unit coupled to the parser, the verification unit applying the predefined grammar to the design document and to the at least one condition to provide an indication whether the design and the at least one condition in the retrieved XML document are syntactically correct; and a graphical user interface to display portions of the retrieved XML document that are not syntactically correct. 13. An apparatus as in claim 11 , further comprising a data repository coupled to the parser, and wherein the parser, during run-time, retrieves data from the repository and renders a report populated with the retrieved data according to an XML document obtained from the XML repository containing a design. | 0.5 |
8,352,455 | 10 | 11 | 10. A system for associating a content item with an event, comprising: a processor configured to: receive a content item; determine a location associated with the received content item; compare the received content item with an existing event, wherein the existing event comprises a previously processed content item and a previously associated location, wherein comparing the received content item with the existing event comprises: determining a weighted overlap between the determined location and the previously associated location of the existing event; determining an indicia of relatedness between the received content item and the existing event, wherein the indicia of relatedness is not based on location; wherein the indicia of relatedness includes a time overlap between a time associated with the received content item and a time associated with the existing event; wherein the time overlap comprises being within a 24 hour window; and associate the received content item with the existing event based on the comparison, wherein the comparison also includes a threshold level of indicia of relatedness between the received content item and the existing event, and wherein the threshold level of indicia of relatedness required for the content item to be determined to be associated with the existing event increases as a degree of the weighted overlap between the determined location and the location previously associated with the existing event decreases; and a memory coupled to the processor and configured to provide the processor with instructions. | 10. A system for associating a content item with an event, comprising: a processor configured to: receive a content item; determine a location associated with the received content item; compare the received content item with an existing event, wherein the existing event comprises a previously processed content item and a previously associated location, wherein comparing the received content item with the existing event comprises: determining a weighted overlap between the determined location and the previously associated location of the existing event; determining an indicia of relatedness between the received content item and the existing event, wherein the indicia of relatedness is not based on location; wherein the indicia of relatedness includes a time overlap between a time associated with the received content item and a time associated with the existing event; wherein the time overlap comprises being within a 24 hour window; and associate the received content item with the existing event based on the comparison, wherein the comparison also includes a threshold level of indicia of relatedness between the received content item and the existing event, and wherein the threshold level of indicia of relatedness required for the content item to be determined to be associated with the existing event increases as a degree of the weighted overlap between the determined location and the location previously associated with the existing event decreases; and a memory coupled to the processor and configured to provide the processor with instructions. 11. The system as in claim 10 , wherein the indicia of relatedness comprises a bi-gram overlap. | 0.730114 |
9,805,031 | 3 | 5 | 3. The method machine language translation of claim 1 wherein the first plurality of user queries in the first language are in a category and evoke a first constraint, and the second plurality of user queries in the second language are in the category and evoke a second constraint that is similar to the first constraint. | 3. The method machine language translation of claim 1 wherein the first plurality of user queries in the first language are in a category and evoke a first constraint, and the second plurality of user queries in the second language are in the category and evoke a second constraint that is similar to the first constraint. 5. The method of machine translation of claim 3 wherein the constraint comprises similar product features. | 0.565574 |
8,568,451 | 15 | 17 | 15. An anchor assembly comprising: an anchor body including a yoke extending from an anchor; said yoke has first and second arms and forms a U shape; a shaft spanning the yoke of the anchor body between the first and second arms of the yoke; said shaft having a saddle mounting element which encircles the shaft; a saddle having a bore mounted about the saddle mounting element; said saddle adapted to hold a member; a set that is received in said saddle and is adapted to selectively apply force against the member held in the saddle and thereby apply force to and through said saddle mounting element to said shaft. | 15. An anchor assembly comprising: an anchor body including a yoke extending from an anchor; said yoke has first and second arms and forms a U shape; a shaft spanning the yoke of the anchor body between the first and second arms of the yoke; said shaft having a saddle mounting element which encircles the shaft; a saddle having a bore mounted about the saddle mounting element; said saddle adapted to hold a member; a set that is received in said saddle and is adapted to selectively apply force against the member held in the saddle and thereby apply force to and through said saddle mounting element to said shaft. 17. The anchor assembly of claim 15 wherein said saddle mounting element is cylindrical. | 0.5 |
8,775,183 | 1 | 5 | 1. A computer-implemented method comprising: receiving, from a client device, a user-specified behavior requirement in a speech recognition system wherein the user-specified behavior requirement changes a setting to an input speech recognition grammar specification prior to recognizing speech to select or de-select a built-in transformation from a set of built-in transformations of the speech recognition system to apply to recognized speech, and wherein the user-specified behavior requirement includes a semantic tag that specifies at least one of: a proper name, a phone number, an address, an email address, an internet protocol address, and a web address; encoding the received user-specified behavior requirement into an input speech recognition grammar specification for the speech recognition system; receiving a request to recognize speech from an application; recognizing the speech to form a recognized word sequence; transforming the recognized word sequence according to the user-specified behavior requirement according to a semantic tag associated with the word sequence; and providing the transformed sequence to the application. | 1. A computer-implemented method comprising: receiving, from a client device, a user-specified behavior requirement in a speech recognition system wherein the user-specified behavior requirement changes a setting to an input speech recognition grammar specification prior to recognizing speech to select or de-select a built-in transformation from a set of built-in transformations of the speech recognition system to apply to recognized speech, and wherein the user-specified behavior requirement includes a semantic tag that specifies at least one of: a proper name, a phone number, an address, an email address, an internet protocol address, and a web address; encoding the received user-specified behavior requirement into an input speech recognition grammar specification for the speech recognition system; receiving a request to recognize speech from an application; recognizing the speech to form a recognized word sequence; transforming the recognized word sequence according to the user-specified behavior requirement according to a semantic tag associated with the word sequence; and providing the transformed sequence to the application. 5. The method of claim 1 wherein the user-specified behavior requirement comprises at least one of: a grammar, an application program interface (API) call, an extensible markup language (XML) element, an XML schema, or speech recognition application parameters. | 0.697216 |
9,542,509 | 21 | 22 | 21. A non-transitory computer-usable medium as in claim 15 , wherein the recycle function returns a signal to a predecessor function, and creates a control law. | 21. A non-transitory computer-usable medium as in claim 15 , wherein the recycle function returns a signal to a predecessor function, and creates a control law. 22. A non-transitory computer-usable medium as in claim 21 , wherein the control law implements a feedback controller. | 0.5 |
8,848,088 | 24 | 25 | 24. The device of claim 22 , wherein the instructions that cause the imaging device to receive the first image of the target object and that cause the processor to analyze the first image comprise instructions to: receive a series of images of the target object; select, from the series of images, the first image; compare information from the first image with information from the database to identify a subset of objects containing similar features; obtain information from the database regarding one or more locations of one or more specific features; and analyze the first image to seek the one or more locations and determine whether the target object as shown in the first image matches any of the objects in the subset. | 24. The device of claim 22 , wherein the instructions that cause the imaging device to receive the first image of the target object and that cause the processor to analyze the first image comprise instructions to: receive a series of images of the target object; select, from the series of images, the first image; compare information from the first image with information from the database to identify a subset of objects containing similar features; obtain information from the database regarding one or more locations of one or more specific features; and analyze the first image to seek the one or more locations and determine whether the target object as shown in the first image matches any of the objects in the subset. 25. The device of claim 24 , wherein: when the processor determines that the target object as shown matches more than one model, the instructions that cause the processor to determine whether the target object comprises the distinguishing point comprise instructions to: select the second image from the series of images; and determine whether the second image contains the distinguishing point in the one or more locations. | 0.5 |
8,037,052 | 6 | 10 | 6. A system of retrieving electronic medical record search results, said system comprising: an interface configured to accept search criteria and display search results; a database interface adapter to interface with an electronic medical record database to transmit and receive data, wherein the database interface adapter facilitates searching identified and de-identified electronic medical record data from a plurality of departmental information systems; and a formatter to format search results for display via the interface, the formatter configured to consolidate results by relevance to search criteria and with respect to a particular patient, the formatter automatically de-identifying at least one of patient and physician data from the search results and providing local re-identification of at least a portion of the search results for an authorized healthcare provider user who has been identified and verified for local re-identification and access to the at least a portion of the search results at a local system, wherein the search results including at least one of de-identified patient data and de-identified physician data are provided to the local system and re-identified at the local system for the authorized healthcare provider user based on re-identification functionality at the authorized healthcare provider user's local system to provide physical separation of re-identified search results available to the authorized healthcare provider user and de-identified search results available to one or more additional users. | 6. A system of retrieving electronic medical record search results, said system comprising: an interface configured to accept search criteria and display search results; a database interface adapter to interface with an electronic medical record database to transmit and receive data, wherein the database interface adapter facilitates searching identified and de-identified electronic medical record data from a plurality of departmental information systems; and a formatter to format search results for display via the interface, the formatter configured to consolidate results by relevance to search criteria and with respect to a particular patient, the formatter automatically de-identifying at least one of patient and physician data from the search results and providing local re-identification of at least a portion of the search results for an authorized healthcare provider user who has been identified and verified for local re-identification and access to the at least a portion of the search results at a local system, wherein the search results including at least one of de-identified patient data and de-identified physician data are provided to the local system and re-identified at the local system for the authorized healthcare provider user based on re-identification functionality at the authorized healthcare provider user's local system to provide physical separation of re-identified search results available to the authorized healthcare provider user and de-identified search results available to one or more additional users. 10. The system of claim 6 , wherein said database interface adapter is configured to interface across a plurality of departmental information systems. | 0.542683 |
10,157,212 | 12 | 14 | 12. A plurality of processing devices for analyzing a plurality of online social networks, each of the plurality of processing devices comprising: at least one processing unit; a memory; a communication unit for communicating with at least one other processing device of the plurality of processing devices; and a communication bus for permitting the at least one processing unit to communicate with the memory and the communication unit, wherein: the memory of each of the plurality of processing devices comprises a plurality of instructions, which when executed by each of the at least one processing unit causes the plurality of processing devices to collectively perform a method comprising: constructing a master actor ontology based on information received from the plurality of online social networks, the constructed master actor ontology including available characteristics identified from the received information, a plurality of derived graph characteristics, a plurality of user behavior classifications, and an introversion/extroversion indicator based on a respective actor's attributes for each of a plurality of actors; inputting at least one logical expression representing at least one correlation of interest with respect to a graph or a subgraph of the master actor ontology; automatically converting the at least one logical expression to a resource description framework query format; performing at least one query over the master actor ontology, based on the converted at least one logical expression, to provide at least one query result of the performed at least one query; after performing the at least one query, determining additional derived values from the master actor ontology based, at least in part, on the at least one query result; and storing the additional derived values from the master actor ontology. | 12. A plurality of processing devices for analyzing a plurality of online social networks, each of the plurality of processing devices comprising: at least one processing unit; a memory; a communication unit for communicating with at least one other processing device of the plurality of processing devices; and a communication bus for permitting the at least one processing unit to communicate with the memory and the communication unit, wherein: the memory of each of the plurality of processing devices comprises a plurality of instructions, which when executed by each of the at least one processing unit causes the plurality of processing devices to collectively perform a method comprising: constructing a master actor ontology based on information received from the plurality of online social networks, the constructed master actor ontology including available characteristics identified from the received information, a plurality of derived graph characteristics, a plurality of user behavior classifications, and an introversion/extroversion indicator based on a respective actor's attributes for each of a plurality of actors; inputting at least one logical expression representing at least one correlation of interest with respect to a graph or a subgraph of the master actor ontology; automatically converting the at least one logical expression to a resource description framework query format; performing at least one query over the master actor ontology, based on the converted at least one logical expression, to provide at least one query result of the performed at least one query; after performing the at least one query, determining additional derived values from the master actor ontology based, at least in part, on the at least one query result; and storing the additional derived values from the master actor ontology. 14. The plurality of processing devices of claim 12 , wherein the master actor ontology is stored in a resource description framework format. | 0.918872 |
8,332,530 | 19 | 20 | 19. An apparatus for navigating a video program segmented into a plurality of segments and having a spoken dialog, comprising: one or more computer processors; and a computer-readable storage medium comprising instructions for controlling the one or more computer processors to be operable for: generating a full textual transcript of the spoken dialog, the full textual transcript comprising a plurality of portions wherein each portion is associated with a segment of the video program; synchronizing each portion of the full textual transcript with the associated segment of the video program; accepting a command to select the video program from a client computer; and transmitting user interface data including the full textual transcript to the client computer for presentation in a user interface, the user interface comprising a concurrently presented video program player playing the video program, a window configured to include portions of the full textual transcript, and a histogram having a plurality of features, each feature representing at least one of the segments of the video program and indicating a popularity of the represented at least one of the segments of the video program; accepting a selection for a portion of the full textual transcript included in the window of the user interface; determining the associated segment for the portion of the full textual transcript based on the synchronizing; and dynamically navigating to the segment of the video program associated with the selected portion of the full textual transcript in the video program player in response to the accepted selection. | 19. An apparatus for navigating a video program segmented into a plurality of segments and having a spoken dialog, comprising: one or more computer processors; and a computer-readable storage medium comprising instructions for controlling the one or more computer processors to be operable for: generating a full textual transcript of the spoken dialog, the full textual transcript comprising a plurality of portions wherein each portion is associated with a segment of the video program; synchronizing each portion of the full textual transcript with the associated segment of the video program; accepting a command to select the video program from a client computer; and transmitting user interface data including the full textual transcript to the client computer for presentation in a user interface, the user interface comprising a concurrently presented video program player playing the video program, a window configured to include portions of the full textual transcript, and a histogram having a plurality of features, each feature representing at least one of the segments of the video program and indicating a popularity of the represented at least one of the segments of the video program; accepting a selection for a portion of the full textual transcript included in the window of the user interface; determining the associated segment for the portion of the full textual transcript based on the synchronizing; and dynamically navigating to the segment of the video program associated with the selected portion of the full textual transcript in the video program player in response to the accepted selection. 20. The apparatus of claim 19 , further comprising: a video player playing the video program; and a decoder for decoding the closed captioning information of the played video program, wherein the video program is encoded with closed captioning information and the generating a full textual transcript of the dialog of the video program comprises: associating the decoded closed captioning information with a temporal index of the video program, and for generating the full textual transcript from the decoded closed captioning information and the temporal index. | 0.5 |
9,786,268 | 11 | 13 | 11. The computer program of claim 10 , the program further causing the processor to: capture the related text and locate the related information on an associated video stored in one or more device and the social media website. | 11. The computer program of claim 10 , the program further causing the processor to: capture the related text and locate the related information on an associated video stored in one or more device and the social media website. 13. The computer program of claim 11 , the program further causing the processor to: determine whether the device is a mobile phone or a computer system; and access a file system of the device based on whether the device is the mobile phone or the computer system. | 0.786062 |
9,262,941 | 4 | 5 | 4. The method of claim 1 , wherein the vowel space metrics comprise a vowel space range, a vowel space area, a vowel space dispersion, a within category vowel dispersion, or a F 2 -F 1 distance. | 4. The method of claim 1 , wherein the vowel space metrics comprise a vowel space range, a vowel space area, a vowel space dispersion, a within category vowel dispersion, or a F 2 -F 1 distance. 5. The method of claim 4 , wherein the vowel space metrics comprise a vowel space range, wherein the vowel space range, F 1 Range, is calculated according to
F 1Range=Max F1 ( AA )−Min F1 ( IY ), where Max F1 (AA) is the maximum value of the first vowel formant measurements for all AA vowel sounds produced by a speaker, and Min F1 (IY) is the minimum value of the first vowel formant measurements for all IY vowel sounds produced by a speaker. | 0.5 |
8,862,581 | 2 | 3 | 2. The method as claimed in claim 1 , wherein the step of extracting temporal features from brain signals further comprises the steps of: computing statistics of brain waveforms in each of a plurality of electrode channels; and concatenating the statistics into a joint feature vector. | 2. The method as claimed in claim 1 , wherein the step of extracting temporal features from brain signals further comprises the steps of: computing statistics of brain waveforms in each of a plurality of electrode channels; and concatenating the statistics into a joint feature vector. 3. The method as claimed in claim 2 , wherein the statistics of the brain waveforms are standard deviations. | 0.5 |
5,533,179 | 9 | 10 | 9. The computer implemented method of claim 8 further including the step of deleting prior mappings of tokens of said modified HDL description that have been changed. | 9. The computer implemented method of claim 8 further including the step of deleting prior mappings of tokens of said modified HDL description that have been changed. 10. The computer implemented method of claim 9 wherein said detecting step includes the step of searching one end of said modified HDL description to identify tokens that match said original HDL description. | 0.5 |
8,560,548 | 1 | 7 | 1. A computer-implemented method for accessing content items in a content store comprising: maintaining a text index of content items in a content store to enable a keyword search on the content items; receiving a query having a keyword and generating a hit list from the text index using the keyword, the hit list comprising two or more content items of the content store; extracting frequent phrases from text within content items of the hit list by estimating an intersection size, wherein the estimating comprises executing an algorithm to intersect a first posting list generated from globally frequent phrases with a second posting list generated from the hit list, wherein the algorithm terminates the executing in response to the earlier of identifying a predetermined M maximum number of comparisons or a predetermined I maximum number of common points; assigning a relative relevance to the frequent phrases wherein frequent phrases having a relatively high relevance are relevant phrases; and grouping content items into topics based on presence of relevant phrases within the content items of the hit list. | 1. A computer-implemented method for accessing content items in a content store comprising: maintaining a text index of content items in a content store to enable a keyword search on the content items; receiving a query having a keyword and generating a hit list from the text index using the keyword, the hit list comprising two or more content items of the content store; extracting frequent phrases from text within content items of the hit list by estimating an intersection size, wherein the estimating comprises executing an algorithm to intersect a first posting list generated from globally frequent phrases with a second posting list generated from the hit list, wherein the algorithm terminates the executing in response to the earlier of identifying a predetermined M maximum number of comparisons or a predetermined I maximum number of common points; assigning a relative relevance to the frequent phrases wherein frequent phrases having a relatively high relevance are relevant phrases; and grouping content items into topics based on presence of relevant phrases within the content items of the hit list. 7. The computer-implemented method of claim 1 , further comprising: preprocessing the content items to enrich the text index, wherein the preprocessing comprises generating a list of globally frequent phrases, wherein the globally frequent phrases are phrases that consist of at least two words that appear in more than a first threshold number of different content items in the content store; and adding the globally frequent phrases to the text index. | 0.623754 |
8,346,536 | 9 | 10 | 9. The system of claim 8 , wherein said translation engine selects one of multiple translation results of a term, uses the selected translation result in a body of the translated document, and stores remaining translation results of the term as meta-data and/or hidden field in the translated document. | 9. The system of claim 8 , wherein said translation engine selects one of multiple translation results of a term, uses the selected translation result in a body of the translated document, and stores remaining translation results of the term as meta-data and/or hidden field in the translated document. 10. The system of claim 9 , wherein said multi-lingual search tool searches said meta-data and hidden field in the translated document. | 0.5 |
8,898,296 | 11 | 13 | 11. The system of claim 4 , wherein the content identified as boilerplate content comprises an anchor list. | 11. The system of claim 4 , wherein the content identified as boilerplate content comprises an anchor list. 13. The system of claim 11 , wherein determining that the selected nodes exhibit the predefined traits that are characteristic of boilerplate content further comprises determining that two or more anchor objects associated with the selected nodes are left aligned with each other. | 0.5 |
9,171,040 | 7 | 9 | 7. The system of claim 6 , wherein the determining further comprises generating a classification tree for a subject, the classification tree specifying subset relationships among the set of subscription queries via hierarchical levels and nodes; wherein each node in a left branch of a parent node at a specified level in the classification tree is a subset of the parent node; and wherein further, subscription queries that are not classified as either of a subset and a superset of the parent node are placed in an empty leaf node by traversing the classification tree for a first available empty leaf node. | 7. The system of claim 6 , wherein the determining further comprises generating a classification tree for a subject, the classification tree specifying subset relationships among the set of subscription queries via hierarchical levels and nodes; wherein each node in a left branch of a parent node at a specified level in the classification tree is a subset of the parent node; and wherein further, subscription queries that are not classified as either of a subset and a superset of the parent node are placed in an empty leaf node by traversing the classification tree for a first available empty leaf node. 9. The system of claim 7 , wherein the query optimization application further performs: processing the left branch of the one or more selected nodes, comprising: comparing contents of the at least one notification message to each of the subscription queries in each of the nodes of the left branch; and transmitting the at least one notification message to those subscription client systems associated with any of the nodes of the left branch for which a match is found in response to the comparing. | 0.5 |
8,812,474 | 1 | 19 | 1. A method, performed by at least one computer, comprising acts of: (A) receiving a query from a user, the query comprising content including at least a first word and a second word; (B) in response to receiving the query, identifying, based at least in part on the content of the query, a first semantic tag indicating a meaning of the first word and a second semantic tag indicating a meaning of the second word; (C) determining a behavior for the user based on the first and second semantic tags, the behavior comprising an inferred intent of the user; and (D) identifying, based on the behavior, (1) at least one search engine from which information related to the content of the query can be retrieved and (2) an action performable by the user that achieves the behavior. | 1. A method, performed by at least one computer, comprising acts of: (A) receiving a query from a user, the query comprising content including at least a first word and a second word; (B) in response to receiving the query, identifying, based at least in part on the content of the query, a first semantic tag indicating a meaning of the first word and a second semantic tag indicating a meaning of the second word; (C) determining a behavior for the user based on the first and second semantic tags, the behavior comprising an inferred intent of the user; and (D) identifying, based on the behavior, (1) at least one search engine from which information related to the content of the query can be retrieved and (2) an action performable by the user that achieves the behavior. 19. The method of claim 1 , wherein the action performable by the user includes playing media identified from the content of the query. | 0.843387 |
9,824,404 | 1 | 4 | 1. A computer implemented method for providing a social media ecosystem cooperative marketplace, comprising: configuring a plurality of non-transitory computer readable mediums in plurality of hardware components on a cloud communications network comprising a social media ecosystem with a three level social media ecosystem framework, the plurality of hardware components comprising a plurality of cloud server network devices, target network devices, each with one or more processors and each with one or more wired or wireless communications interfaces interacting as the social media ecosystem through data flows between the plurality of hardware components over a cloud communications network, the three level social media ecosystem framework including: (1) a Level 1 comprising electronic information describing what cause events individual target network devices to carry out actions within the social media ecosystem; (2) a Level 2 comprising electronic information describing rules used to determine whether the individual target network devices take or not take Level 1 actions within the social media ecosystem; and (3) a Level 3 comprising electronic information describing methods for target network devices for completing Level 1 and Level 2 actions within the social media ecosystem, the social media ecosystem configured for facilitating and automating a plurality of social interactions and social connections by enabling social collaboration at any time and eliminating a need for travel and direct human personal interactions for participating in the social media ecosystem; accepting on the first cloud application on the first cloud server network device a plurality of electronic information from a plurality of different social media merchants offering a plurality of goods or services comprising the one or more of the plurality of hardware components on the social media ecosystem, the plurality of electronic information including a sharing discount percentage associated with a plurality of social media index values on the social media ecosystem and electronic information from the three level social media framework; selecting automatically from the first cloud application on the first cloud server network device with one or more processors the plurality of different social media merchants offering the plurality of goods or services including the sharing discount percentage associated with the plurality of social media index values and including the electronic information from the three level social media framework; calculating from the first cloud application on the first cloud server network device with the one or more processors the plurality of social media index values for the plurality of different social media merchants from a (X)multi-dimensional entity of social commerce connections for the plurality of different social media merchants with each dimension in the (X)multi-dimensional entity assigned a pre-determined numeric percentage and with dimensions in the (X)multi-dimensional entity including a positive integer number with a value in a range from (1) to (X), wherein (X) is a maximum positive integer value pre-determined for the social media ecosystem cooperative marketplace and including a smallest dimension(1)in the (X)multi-dimensional entity assigned a largest numeric percentage with a range of zero percent to one hundred percent and including a set of highest value social connections for the plurality of different social media merchants and a largest dimension(X) in the (X)multi-dimensional entity assigned a smallest numeric percentage with a range of zero percent to one hundred percent and including a set of lowest value social connections for the plurality of different social media merchants; creating with the first cloud application on the first cloud server network device a plurality of social commerce connections for the plurality of different social media merchants, the plurality of social commerce connections comprising off-site social commerce connections including electronic commerce transactions and activities resulting from other than a web-site provided by a selected social media merchant and on-site social commerce connections including electronic commerce transactions and activities resulting from the web-site provided by the selected social media merchant; receiving a plurality of electronic information from a plurality of applications on a plurality of network devices each with one or more processors on the first cloud application stored in a first non-transitory computer readable medium on the cloud server network device with the one or more processors via the cloud communications network for the social media ecosystem, wherein the plurality of electronic information includes a plurality of goods and services offered by the plurality of different social media merchants and the social media ecosystem sharing discount percentage, wherein the plurality of electronic information includes the plurality of social media index values and the plurality of social commerce connections for the plurality of different social media merchants; providing with the social media ecosystem the sharing discount percentage used to provide lower purchase prices for the plurality of goods and services for social media purchasers in the social media ecosystem and the social media ecosystem cooperative marketplace for social media purchasers and social media merchants in the social media ecosystem; storing from the first cloud application the received plurality of electronic information in a plurality of pre-determined search index structures in a plurality of cloud storage objects; receiving on the first cloud application from the first target application on the first target network device via the cloud communications network a request to purchase one or more of the plurality of goods or services offered by the selected social media merchant identified by a social media index value; creating automatically from the first cloud application a new social commerce connection between the selected social media merchant and a first user sending the purchase request from the first target network device; re-calculating automatically from the first cloud application the social media index value associated with the selected social media merchant; storing from the first cloud application the re-calculated social media index value in the pre-determined search index structure in the stored cloud storage objects for the selected social media merchant; storing from the first cloud application the new social commerce connection in the pre-determined search index structures in the stored cloud storage objects for the selected social media merchant and for the first user; receiving on the first cloud application from the first target application on the first target network device via the cloud communications network an electronic fee to purchase a good or service offered by the selected social media merchant; subtracting on the first cloud application a social media ecosystem sharing discount fee from the electronic fee for the selected electronic merchant; depositing with an electronic payment from the first cloud application in an electronic account for the social media ecosystem marketplace the subtracted social media ecosystem sharing discount fee support a social media ecosystem cooperative marketplace for social media purchasers and social media merchants; and depositing with an electronic payment from the first cloud application in another electronic account for the selected merchant the remaining portion of the electronic fee for the purchase of the good or service offered by the selected social media merchant. | 1. A computer implemented method for providing a social media ecosystem cooperative marketplace, comprising: configuring a plurality of non-transitory computer readable mediums in plurality of hardware components on a cloud communications network comprising a social media ecosystem with a three level social media ecosystem framework, the plurality of hardware components comprising a plurality of cloud server network devices, target network devices, each with one or more processors and each with one or more wired or wireless communications interfaces interacting as the social media ecosystem through data flows between the plurality of hardware components over a cloud communications network, the three level social media ecosystem framework including: (1) a Level 1 comprising electronic information describing what cause events individual target network devices to carry out actions within the social media ecosystem; (2) a Level 2 comprising electronic information describing rules used to determine whether the individual target network devices take or not take Level 1 actions within the social media ecosystem; and (3) a Level 3 comprising electronic information describing methods for target network devices for completing Level 1 and Level 2 actions within the social media ecosystem, the social media ecosystem configured for facilitating and automating a plurality of social interactions and social connections by enabling social collaboration at any time and eliminating a need for travel and direct human personal interactions for participating in the social media ecosystem; accepting on the first cloud application on the first cloud server network device a plurality of electronic information from a plurality of different social media merchants offering a plurality of goods or services comprising the one or more of the plurality of hardware components on the social media ecosystem, the plurality of electronic information including a sharing discount percentage associated with a plurality of social media index values on the social media ecosystem and electronic information from the three level social media framework; selecting automatically from the first cloud application on the first cloud server network device with one or more processors the plurality of different social media merchants offering the plurality of goods or services including the sharing discount percentage associated with the plurality of social media index values and including the electronic information from the three level social media framework; calculating from the first cloud application on the first cloud server network device with the one or more processors the plurality of social media index values for the plurality of different social media merchants from a (X)multi-dimensional entity of social commerce connections for the plurality of different social media merchants with each dimension in the (X)multi-dimensional entity assigned a pre-determined numeric percentage and with dimensions in the (X)multi-dimensional entity including a positive integer number with a value in a range from (1) to (X), wherein (X) is a maximum positive integer value pre-determined for the social media ecosystem cooperative marketplace and including a smallest dimension(1)in the (X)multi-dimensional entity assigned a largest numeric percentage with a range of zero percent to one hundred percent and including a set of highest value social connections for the plurality of different social media merchants and a largest dimension(X) in the (X)multi-dimensional entity assigned a smallest numeric percentage with a range of zero percent to one hundred percent and including a set of lowest value social connections for the plurality of different social media merchants; creating with the first cloud application on the first cloud server network device a plurality of social commerce connections for the plurality of different social media merchants, the plurality of social commerce connections comprising off-site social commerce connections including electronic commerce transactions and activities resulting from other than a web-site provided by a selected social media merchant and on-site social commerce connections including electronic commerce transactions and activities resulting from the web-site provided by the selected social media merchant; receiving a plurality of electronic information from a plurality of applications on a plurality of network devices each with one or more processors on the first cloud application stored in a first non-transitory computer readable medium on the cloud server network device with the one or more processors via the cloud communications network for the social media ecosystem, wherein the plurality of electronic information includes a plurality of goods and services offered by the plurality of different social media merchants and the social media ecosystem sharing discount percentage, wherein the plurality of electronic information includes the plurality of social media index values and the plurality of social commerce connections for the plurality of different social media merchants; providing with the social media ecosystem the sharing discount percentage used to provide lower purchase prices for the plurality of goods and services for social media purchasers in the social media ecosystem and the social media ecosystem cooperative marketplace for social media purchasers and social media merchants in the social media ecosystem; storing from the first cloud application the received plurality of electronic information in a plurality of pre-determined search index structures in a plurality of cloud storage objects; receiving on the first cloud application from the first target application on the first target network device via the cloud communications network a request to purchase one or more of the plurality of goods or services offered by the selected social media merchant identified by a social media index value; creating automatically from the first cloud application a new social commerce connection between the selected social media merchant and a first user sending the purchase request from the first target network device; re-calculating automatically from the first cloud application the social media index value associated with the selected social media merchant; storing from the first cloud application the re-calculated social media index value in the pre-determined search index structure in the stored cloud storage objects for the selected social media merchant; storing from the first cloud application the new social commerce connection in the pre-determined search index structures in the stored cloud storage objects for the selected social media merchant and for the first user; receiving on the first cloud application from the first target application on the first target network device via the cloud communications network an electronic fee to purchase a good or service offered by the selected social media merchant; subtracting on the first cloud application a social media ecosystem sharing discount fee from the electronic fee for the selected electronic merchant; depositing with an electronic payment from the first cloud application in an electronic account for the social media ecosystem marketplace the subtracted social media ecosystem sharing discount fee support a social media ecosystem cooperative marketplace for social media purchasers and social media merchants; and depositing with an electronic payment from the first cloud application in another electronic account for the selected merchant the remaining portion of the electronic fee for the purchase of the good or service offered by the selected social media merchant. 4. The method of claim 1 wherein the social media ecosystem sharing discount percentage includes a first portion for supporting the social media ecosystem cooperative marketplace for the social media purchasers and the social media merchants and a second portion for pay potential social media purchasers to view advertising for new or existing goods or services offered by the plurality of social media merchants. | 0.85402 |
10,102,193 | 9 | 10 | 9. The method of claim 1 , wherein determining longest contiguous common subsequences comprises: aligning pairs of strings having possible contextual matches; normalizing the pairs of strings by extracting matching segments having a given length; and aggregating the normalized pairs of strings. | 9. The method of claim 1 , wherein determining longest contiguous common subsequences comprises: aligning pairs of strings having possible contextual matches; normalizing the pairs of strings by extracting matching segments having a given length; and aggregating the normalized pairs of strings. 10. The method of claim 9 , further comprising applying a greedy contiguity heuristic to the aggregated normalized pairs of strings. | 0.5 |
8,135,729 | 8 | 12 | 8. At least one computer-readable medium storing computer-executable instructions that, when executed by a computer, cause the computer to perform a method comprising: detecting, in a query string being entered into a query entry box by a user, a character pattern of a plurality of patterns, wherein the detecting does not require that an explicit indicator of submission of the query string be provided by the user, and wherein the plurality of patterns comprises: a first pattern indicating a series of characters followed by a space character, and a second pattern indicating one or more characters followed by a predefined time delay before any additional characters are entered into the query entry box by the user; and providing, in response to the detecting, both an updated query result list and an updated list of one or more query refinement options, wherein both the updated query result list and the updated list of one or more query refinement options correspond to the detected search query character pattern. | 8. At least one computer-readable medium storing computer-executable instructions that, when executed by a computer, cause the computer to perform a method comprising: detecting, in a query string being entered into a query entry box by a user, a character pattern of a plurality of patterns, wherein the detecting does not require that an explicit indicator of submission of the query string be provided by the user, and wherein the plurality of patterns comprises: a first pattern indicating a series of characters followed by a space character, and a second pattern indicating one or more characters followed by a predefined time delay before any additional characters are entered into the query entry box by the user; and providing, in response to the detecting, both an updated query result list and an updated list of one or more query refinement options, wherein both the updated query result list and the updated list of one or more query refinement options correspond to the detected search query character pattern. 12. The at least one computer-readable medium of claim 8 wherein the updated list of one or more query refinement options includes a spelling correction option. | 0.578947 |
9,142,219 | 1 | 3 | 1. A method comprising: receiving, by a computing device, an acoustic input signal at a speech recognizer; identifying, by the computing device, a user that is speaking based on the acoustic input signal; recognizing, by the computing device via the speech recognizer, speech uttered by the user in the acoustic input signal; determining, by the computing device, speaker-specific information previously stored for the user; determining, by the computing device, a set of potential responses based on the recognized speech and the speaker-specific information for the user; ranking, by the computing device, the set of potential responses based on one or more criteria and the speaker-specific information; determining, by the computing device for each response in the set of potential responses, whether the response should be output or should not be output based on the response's ranking; and if the response should be output: selecting, by the computing device from among a plurality of preconfigured output methods, an output method for outputting the response to the user, the selecting being based on the response's ranking; and outputting, by the computing device, the response to the user using the selected output method. | 1. A method comprising: receiving, by a computing device, an acoustic input signal at a speech recognizer; identifying, by the computing device, a user that is speaking based on the acoustic input signal; recognizing, by the computing device via the speech recognizer, speech uttered by the user in the acoustic input signal; determining, by the computing device, speaker-specific information previously stored for the user; determining, by the computing device, a set of potential responses based on the recognized speech and the speaker-specific information for the user; ranking, by the computing device, the set of potential responses based on one or more criteria and the speaker-specific information; determining, by the computing device for each response in the set of potential responses, whether the response should be output or should not be output based on the response's ranking; and if the response should be output: selecting, by the computing device from among a plurality of preconfigured output methods, an output method for outputting the response to the user, the selecting being based on the response's ranking; and outputting, by the computing device, the response to the user using the selected output method. 3. The method of claim 1 wherein the response is outputted after a user speaks a trigger phrase to activate the speech recognizer. | 0.846698 |
9,245,254 | 1 | 34 | 1. A method for ability enhancement, the method comprising: by a computer system, receiving data representing speech signals from a voice conference amongst multiple speakers, wherein the multiple speakers are remotely located from one another, wherein each of the multiple speakers uses a separate conferencing device to participate in the voice conference; determining speaker-related information associated with the multiple speakers, based on the data representing speech signals from the voice conference; recording conference history information based on the speaker-related information, by recording indications of topics discussed during the voice conference by: performing speech recognition to convert the data representing speech signals into text; analyzing the text to identify frequently used terms or phrases; and determining the topics discussed during the voice conference based on the frequently used terms or phrases; audibly notifying a user to view the conference history information on a display device, wherein the user is notified in a manner that is not audible to at least some of the multiple speakers; and presenting, on the display device, at least some of the conference history information to the user; translating an utterance of one of the multiple speakers in a first language into a message in a second language, based on the speaker-related information, wherein the speaker related information is determined by automatically determining the second and the first language comprising steps of: concurrently or simultaneously applying multiple speech recognizers and using GPS information indicating the speakers' locations; and recording the message in the second language as part of the conference history information. | 1. A method for ability enhancement, the method comprising: by a computer system, receiving data representing speech signals from a voice conference amongst multiple speakers, wherein the multiple speakers are remotely located from one another, wherein each of the multiple speakers uses a separate conferencing device to participate in the voice conference; determining speaker-related information associated with the multiple speakers, based on the data representing speech signals from the voice conference; recording conference history information based on the speaker-related information, by recording indications of topics discussed during the voice conference by: performing speech recognition to convert the data representing speech signals into text; analyzing the text to identify frequently used terms or phrases; and determining the topics discussed during the voice conference based on the frequently used terms or phrases; audibly notifying a user to view the conference history information on a display device, wherein the user is notified in a manner that is not audible to at least some of the multiple speakers; and presenting, on the display device, at least some of the conference history information to the user; translating an utterance of one of the multiple speakers in a first language into a message in a second language, based on the speaker-related information, wherein the speaker related information is determined by automatically determining the second and the first language comprising steps of: concurrently or simultaneously applying multiple speech recognizers and using GPS information indicating the speakers' locations; and recording the message in the second language as part of the conference history information. 34. The method of claim 1 , further comprising: performing one or more of the receiving data representing speech signals from a voice conference amongst multiple speakers, the determining speaker-related information associated with the multiple speakers, the recording conference history information based on the speaker-related information, and/or the presenting at least some of the conference history information on each of multiple computing systems, wherein each of the multiple systems is associated with one of the multiple speakers. | 0.589666 |
8,098,976 | 15 | 16 | 15. A non-transitory computer-readable medium having sets of instructions stored thereon which, when executed by a computer, cause the computer to: receive a list of candidate tags for a video file; receive a transcript of audio associated with the video file; rank the list of candidate tags for the video file based on a plurality of ranking factors; filter candidate tags from the list of candidate tags which rank below a threshold value; present the filtered list of candidate tags in a user interface; receive a selection of one or more of the filtered list of candidate tags; receive one or more additional tags; based on the selected one or more of the filtered list of candidate tags and the evaluate the transcript and the one or more additional tags, evaluating the transcript and producing an updated list of candidate tags for the video file; establish a top concepts threshold value; determine that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associate information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file. | 15. A non-transitory computer-readable medium having sets of instructions stored thereon which, when executed by a computer, cause the computer to: receive a list of candidate tags for a video file; receive a transcript of audio associated with the video file; rank the list of candidate tags for the video file based on a plurality of ranking factors; filter candidate tags from the list of candidate tags which rank below a threshold value; present the filtered list of candidate tags in a user interface; receive a selection of one or more of the filtered list of candidate tags; receive one or more additional tags; based on the selected one or more of the filtered list of candidate tags and the evaluate the transcript and the one or more additional tags, evaluating the transcript and producing an updated list of candidate tags for the video file; establish a top concepts threshold value; determine that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associate information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file. 16. The non-transitory computer-readable medium of claim 15 , wherein the sets of instructions when further executed by the computer cause the computer to based on the updated list of candidate tags, provide suggested video files associated with the video file. | 0.833333 |
8,145,488 | 3 | 4 | 3. The speech recognition system of claim 1 , wherein the class of piecewise functions corresponds to a class of spline functions. | 3. The speech recognition system of claim 1 , wherein the class of piecewise functions corresponds to a class of spline functions. 4. The speech recognition system of claim 3 , wherein the spline functions are cubic spline functions. | 0.5 |
9,665,564 | 2 | 4 | 2. The method of claim 1 , wherein generating a logical parse of the first parse representation of the natural language content comprises: inputting the first parse into a logical parser implemented in the data processing system; and normalizing, by the logical parser, logical triggers in the first parse indicative of a logical relationship to a predefined set of logical operators to thereby generate the logical parse. | 2. The method of claim 1 , wherein generating a logical parse of the first parse representation of the natural language content comprises: inputting the first parse into a logical parser implemented in the data processing system; and normalizing, by the logical parser, logical triggers in the first parse indicative of a logical relationship to a predefined set of logical operators to thereby generate the logical parse. 4. The method of claim 2 , wherein generating a logical parse of the first parse representation of the natural language content further comprises: simplifying the logical parse by removing redundancy in the logical parse to generate a simplified logical parse that replaces the logical parse, wherein simplifying the logical parse comprises implementing DeMorgan's Law, Factorization, and Disjunctive Syllogism. | 0.5 |
7,716,224 | 6 | 12 | 6. A method, implemented at least partially by a handheld electronic book reader device, the method comprising: under control of one or more systems of the handheld electronic book reader device configured with executable instructions, generating a searchable item index of terms in an electronic item; and generating a searchable master index of terms in the electronic item and other electronic items in a collection of electronic items stored in memory of the handheld electronic book reader device, wherein the master index comprises a list of terms used in electronic items in the collection and, for each term, a reference to one or more item index entries for the respective term, and wherein each reference to an item index entry comprises an identifier of the electronic item in which the term appears, a number of times the term appears in the respective electronic item, and a position at which the term is indexed in the item index for the respective electronic item. | 6. A method, implemented at least partially by a handheld electronic book reader device, the method comprising: under control of one or more systems of the handheld electronic book reader device configured with executable instructions, generating a searchable item index of terms in an electronic item; and generating a searchable master index of terms in the electronic item and other electronic items in a collection of electronic items stored in memory of the handheld electronic book reader device, wherein the master index comprises a list of terms used in electronic items in the collection and, for each term, a reference to one or more item index entries for the respective term, and wherein each reference to an item index entry comprises an identifier of the electronic item in which the term appears, a number of times the term appears in the respective electronic item, and a position at which the term is indexed in the item index for the respective electronic item. 12. The method of claim 6 , wherein the item index of terms is organized in order of a number of occurrences of each term in the electronic item. | 0.731481 |
9,792,335 | 1 | 2 | 1. A computer program product for learning content discovery in a social learning system, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a processor to cause the processor to perform a method comprising: providing, by a social learning system: social learning mechanisms and social media mechanisms accessible to a learning content administrator system, a plurality of learner client systems, and at least one learning content creator client system; one or more formal courses in a given curriculum provided by an institution or enterprise and managed by the learning content administrator system; and an analytic query mechanism configurable by the learning content administrator system; receiving, from the at least one learning content creator client system via the social learning mechanisms, one or more informal courses not in the given curriculum and created by a learning content creator, each informal course comprising learning content and metadata describing the learning content and the learning content creator; providing, by the social learning system, access to the one or more informal courses to the plurality of learner client systems; receiving, from the plurality of learner client systems via the social media mechanisms, social data for the one or more informal courses; receiving, from the learning content administrator system via the analytic query mechanism, a query comprising query parameters for types of informal courses relevant to the given curriculum; analyzing, by the social learning system, the metadata and the social data for the one or more informal courses to determine which of the one or more informal courses match the query parameters; returning, by the social learning system, a list of the one or more informal courses matching the query parameters as a query result; and automatically incorporating, by the social learning system, the learning content of the at least one informal course in the list into the given curriculum. | 1. A computer program product for learning content discovery in a social learning system, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a processor to cause the processor to perform a method comprising: providing, by a social learning system: social learning mechanisms and social media mechanisms accessible to a learning content administrator system, a plurality of learner client systems, and at least one learning content creator client system; one or more formal courses in a given curriculum provided by an institution or enterprise and managed by the learning content administrator system; and an analytic query mechanism configurable by the learning content administrator system; receiving, from the at least one learning content creator client system via the social learning mechanisms, one or more informal courses not in the given curriculum and created by a learning content creator, each informal course comprising learning content and metadata describing the learning content and the learning content creator; providing, by the social learning system, access to the one or more informal courses to the plurality of learner client systems; receiving, from the plurality of learner client systems via the social media mechanisms, social data for the one or more informal courses; receiving, from the learning content administrator system via the analytic query mechanism, a query comprising query parameters for types of informal courses relevant to the given curriculum; analyzing, by the social learning system, the metadata and the social data for the one or more informal courses to determine which of the one or more informal courses match the query parameters; returning, by the social learning system, a list of the one or more informal courses matching the query parameters as a query result; and automatically incorporating, by the social learning system, the learning content of the at least one informal course in the list into the given curriculum. 2. The computer program product of claim 1 , wherein the analyzing of the metadata and the social data and the returning of the list of the one or more informal courses comprise: analyzing the social data to determine content quality metrics for the one or more informal courses; organizing the list of the one or more informal courses according to at least one of the content quality metrics; and returning the list of the one or more informal courses with the content quality metrics matching the query parameters. | 0.646091 |
9,411,799 | 13 | 14 | 13. A document and template creation system comprising: a document and template creation device including a processor and a memory, the processor configured to execute computer-readable instructions to, auto-complete a first text string based on at least one domain ontology concept and a context of a portion of the first text string in a clinical document for a clinical indication; analyze the clinical document to identify at least one first candidate for structural content, the clinical document including documentation of at least clinical observations by a physician, the at least one first candidate for structural content including a free form second text-string entry input into the clinical document by a user, identify a parent node corresponding to the at least one first candidate in a domain ontology database, obtain at least one domain specific structural element from the domain ontology database based on the identified parent node, the at least one domain specific structural element including the at least one first candidate and a plurality of second candidates, the plurality of second candidates being additional concepts identified as siblings of the at least one first candidate, and create a template for the clinical document by inserting, into the clinical document for the clinical indication, structural content including the at least one domain specific structural element, the at least one domain specific structural element including the at least one first candidate and the plurality of second candidates, wherein the structural content forms a structured part of the template for creating subsequent clinical documents for subsequent clinical indications, the plurality of second candidates are in the form of one or more third text-strings, and the at least one first candidate and the plurality of second candidates are displayed and selectable by the user for insertion into the subsequent clinical documents when creating the subsequent clinical documents from the created template. | 13. A document and template creation system comprising: a document and template creation device including a processor and a memory, the processor configured to execute computer-readable instructions to, auto-complete a first text string based on at least one domain ontology concept and a context of a portion of the first text string in a clinical document for a clinical indication; analyze the clinical document to identify at least one first candidate for structural content, the clinical document including documentation of at least clinical observations by a physician, the at least one first candidate for structural content including a free form second text-string entry input into the clinical document by a user, identify a parent node corresponding to the at least one first candidate in a domain ontology database, obtain at least one domain specific structural element from the domain ontology database based on the identified parent node, the at least one domain specific structural element including the at least one first candidate and a plurality of second candidates, the plurality of second candidates being additional concepts identified as siblings of the at least one first candidate, and create a template for the clinical document by inserting, into the clinical document for the clinical indication, structural content including the at least one domain specific structural element, the at least one domain specific structural element including the at least one first candidate and the plurality of second candidates, wherein the structural content forms a structured part of the template for creating subsequent clinical documents for subsequent clinical indications, the plurality of second candidates are in the form of one or more third text-strings, and the at least one first candidate and the plurality of second candidates are displayed and selectable by the user for insertion into the subsequent clinical documents when creating the subsequent clinical documents from the created template. 14. The system of claim 13 , wherein the structured part of the template includes a pick list including children of the identified parent node as an option, the children including the at least one first candidate and the plurality of second candidates. | 0.5 |
7,599,938 | 1 | 15 | 1. A news method, the method comprising the following steps: receiving at a first computer system a first submission, said first submission comprising first content, said first content comprising first account information, said first computer system comprising a first memory; storing said first account information in said first memory; receiving a second submission, said second submission comprising second content, said second content comprising first article information, said first article information comprising at least a first resource location or a first headline; receiving a plurality of additional submissions, said plurality of additional submissions comprising a third submission and a fourth submission, said third submission comprising third content, said fourth submission comprising fourth content, said fourth content comprising at least an indication of either approval or disapproval; storing at least some of said submissions in a first database system, said first database system comprising at least a first database; calculating a first content approval score, said step of calculating said first content approval score being performed at least partly according to a first time criterion and comprising a step of performing a first count, said step of performing said first count comprising a first step of counting at least some of said plurality of additional submissions; providing a first resource, said first resource comprising a plurality of items, said plurality of items comprising a first item, said first item comprising at least first indicia, said first indicia indicating a first value, said first value pertaining to said third content; performing a second count, said step of performing said second count comprising a second step of counting at least some of said plurality of additional submissions; providing first display information, said step of providing said first display information comprising a step of at least partly causing second indicia to appear in a second resource, said second indicia indicating a second value, said second value being based at least in part upon an outcome of said step of performing said second count; providing first submission-facilitation information, said step of providing said first submission-facilitation information comprising a step of at least partly causing a first submission-facilitation mechanism to appear in a third resource; providing fifth content; receiving a fifth submission, said fifth submission comprising sixth content, said sixth content comprising second article information, said second article information comprising at least a second resource location or a second headline; updating said fifth content, said step of updating said fifth content comprising a step of including said sixth content in said fifth content; associating a second item with a first probational status; associating a third item with said first probational status; determining a first measure of community approval; comparing said first measure of community approval to a first threshold; promoting said second item to a first elevated status, said step of promoting said second item to said first elevated status being performed at least partly according to an outcome of said step of comparing said first measure of community approval to said first threshold; determining a second measure of community approval; comparing said second measure of community approval to a second threshold; keeping said third item in association with said first probational status, said step of keeping said third item in association with said first probational status being performed at least partly according to an outcome of said step of comparing said second measure of community approval to said second threshold; promoting a fourth item to said first elevated status; and removing said second item from said first elevated status, wherein said first resource is different from said second resource and from said third resource. | 1. A news method, the method comprising the following steps: receiving at a first computer system a first submission, said first submission comprising first content, said first content comprising first account information, said first computer system comprising a first memory; storing said first account information in said first memory; receiving a second submission, said second submission comprising second content, said second content comprising first article information, said first article information comprising at least a first resource location or a first headline; receiving a plurality of additional submissions, said plurality of additional submissions comprising a third submission and a fourth submission, said third submission comprising third content, said fourth submission comprising fourth content, said fourth content comprising at least an indication of either approval or disapproval; storing at least some of said submissions in a first database system, said first database system comprising at least a first database; calculating a first content approval score, said step of calculating said first content approval score being performed at least partly according to a first time criterion and comprising a step of performing a first count, said step of performing said first count comprising a first step of counting at least some of said plurality of additional submissions; providing a first resource, said first resource comprising a plurality of items, said plurality of items comprising a first item, said first item comprising at least first indicia, said first indicia indicating a first value, said first value pertaining to said third content; performing a second count, said step of performing said second count comprising a second step of counting at least some of said plurality of additional submissions; providing first display information, said step of providing said first display information comprising a step of at least partly causing second indicia to appear in a second resource, said second indicia indicating a second value, said second value being based at least in part upon an outcome of said step of performing said second count; providing first submission-facilitation information, said step of providing said first submission-facilitation information comprising a step of at least partly causing a first submission-facilitation mechanism to appear in a third resource; providing fifth content; receiving a fifth submission, said fifth submission comprising sixth content, said sixth content comprising second article information, said second article information comprising at least a second resource location or a second headline; updating said fifth content, said step of updating said fifth content comprising a step of including said sixth content in said fifth content; associating a second item with a first probational status; associating a third item with said first probational status; determining a first measure of community approval; comparing said first measure of community approval to a first threshold; promoting said second item to a first elevated status, said step of promoting said second item to said first elevated status being performed at least partly according to an outcome of said step of comparing said first measure of community approval to said first threshold; determining a second measure of community approval; comparing said second measure of community approval to a second threshold; keeping said third item in association with said first probational status, said step of keeping said third item in association with said first probational status being performed at least partly according to an outcome of said step of comparing said second measure of community approval to said second threshold; promoting a fourth item to said first elevated status; and removing said second item from said first elevated status, wherein said first resource is different from said second resource and from said third resource. 15. The method in claim 1 wherein: said step of comparing said first measure of community approval to said first threshold comprises a step of determining whether said second item is popular, wherein said second item is popular if at least a first quantity or proportion of users has indicated approval of said second item; and said step of promoting second item to said first elevated status comprises a step of displaying said second item in a first manner at a first point in time when said second item is popular at said first point in time. | 0.853495 |
7,507,897 | 8 | 9 | 8. A dictionary-based method for compressing melody data into compressed data having a command part and a data part, the method comprising: placing a plurality of musical notes from the melody data in a sliding window; comparing a first musical note received from the sliding window to a plurality of following notes received from the sliding window to determine a statistical significance of the first musical note according to a statistical model; placing the first musical note received from the sliding window in a dictionary as a dictionary entry when the musical note has statistical significance according to the model; and storing an index for the dictionary entry in the command part. | 8. A dictionary-based method for compressing melody data into compressed data having a command part and a data part, the method comprising: placing a plurality of musical notes from the melody data in a sliding window; comparing a first musical note received from the sliding window to a plurality of following notes received from the sliding window to determine a statistical significance of the first musical note according to a statistical model; placing the first musical note received from the sliding window in a dictionary as a dictionary entry when the musical note has statistical significance according to the model; and storing an index for the dictionary entry in the command part. 9. The dictionary-based method of claim 8 , further comprising: finding a difference between a musical note and an existing dictionary entry in the dictionary; and storing the difference in the data part of the compressed data. | 0.5 |
7,483,870 | 1 | 3 | 1. An automated method of updating data within a peer-to-peer enterprise information system comprising: publishing a data change from a first source system over a broadcast channel, wherein said data change is of a first data type; in response to said data change, a join engine peer accessing a global attribute object model to identify a second data type and additional attributes of said second data type, wherein said global attribute object model defines a first dependency between at least one attribute of said first data type and at least one attribute of a third data type and a second dependency between said additional attributes and attributes of said third data type, wherein said first dependency requires synchronization of said third data type with said data change; using a query to obtain said additional attributes from a second source system, wherein said query is generated using said global attribute object model; generating a modified attribute set comprising said additional attributes and said data change; and publishing said modified attribute set to a third source system, wherein said third source system is associated with said third data type, wherein said third data type is synchronized, as specified in said first dependency, with said data change in said modified attribute set. | 1. An automated method of updating data within a peer-to-peer enterprise information system comprising: publishing a data change from a first source system over a broadcast channel, wherein said data change is of a first data type; in response to said data change, a join engine peer accessing a global attribute object model to identify a second data type and additional attributes of said second data type, wherein said global attribute object model defines a first dependency between at least one attribute of said first data type and at least one attribute of a third data type and a second dependency between said additional attributes and attributes of said third data type, wherein said first dependency requires synchronization of said third data type with said data change; using a query to obtain said additional attributes from a second source system, wherein said query is generated using said global attribute object model; generating a modified attribute set comprising said additional attributes and said data change; and publishing said modified attribute set to a third source system, wherein said third source system is associated with said third data type, wherein said third data type is synchronized, as specified in said first dependency, with said data change in said modified attribute set. 3. A method as described in claim 1 wherein said data change includes at least one changed attribute and all other attributes of said first data type. | 0.581006 |
7,831,423 | 11 | 16 | 11. A computer-implemented method comprising: (A) identifying a first phrase, the first phrase representing an expanded written form of a concept; (B) receiving an instruction from a user to modify the first phrase; (C) in response to receipt of the instruction, identifying a second phrase representing an abbreviated written form of the concept; and (D) replacing the first phrase with the second phrase; and (E) after (D), replacing the second phrase with the first phrase; wherein the instruction does not include the second phrase. | 11. A computer-implemented method comprising: (A) identifying a first phrase, the first phrase representing an expanded written form of a concept; (B) receiving an instruction from a user to modify the first phrase; (C) in response to receipt of the instruction, identifying a second phrase representing an abbreviated written form of the concept; and (D) replacing the first phrase with the second phrase; and (E) after (D), replacing the second phrase with the first phrase; wherein the instruction does not include the second phrase. 16. The method of claim 11 , wherein (D) comprises identifying a second phrase from among a plurality of second phrases representing the concept. | 0.610215 |
9,031,898 | 1 | 10 | 1. A method performed by one or more server devices, the method comprising: identifying, by a processor of the one or more server devices, a document relating to a search term, the document comprising structural elements; locating, by a processor of the one or more server devices, occurrences of the search term in the document; grouping, by a processor of the one or more server devices, the occurrences of the search term into at least one cluster, the grouping being based on relative locations of the occurrences of the search term, and the grouping favoring a cluster that lies within a particular structural element, of the structural elements, over a cluster that lies within multiple structural elements of the structural elements; identifying, by a processor of the one or more server devices, a structural element, of the structural elements, encompassing the at least one cluster; and providing, by a processor of the one or more server devices and for presentation, information associated with the identified structural element. | 1. A method performed by one or more server devices, the method comprising: identifying, by a processor of the one or more server devices, a document relating to a search term, the document comprising structural elements; locating, by a processor of the one or more server devices, occurrences of the search term in the document; grouping, by a processor of the one or more server devices, the occurrences of the search term into at least one cluster, the grouping being based on relative locations of the occurrences of the search term, and the grouping favoring a cluster that lies within a particular structural element, of the structural elements, over a cluster that lies within multiple structural elements of the structural elements; identifying, by a processor of the one or more server devices, a structural element, of the structural elements, encompassing the at least one cluster; and providing, by a processor of the one or more server devices and for presentation, information associated with the identified structural element. 10. The method of claim 1 , where the document is a book, and the structural elements comprise at least one of: the book, a set of chapters of the book, or a set of pages of the book. | 0.761719 |
8,732,758 | 1 | 3 | 1. A method for recommending television programming to a user, comprising: monitoring, using a processor within user television equipment, which television programming is being viewed by the user; automatically identifying, using the processor, a currently viewed program based on the monitoring, wherein the currently viewed program has a plurality of program attributes each included within a respective attribute category; determining that a user has selected an attribute category of actor as a criterion for recommending programs; automatically identifying an actor who performs in the currently viewed program responsive to determining that the user has selected the attribute category of actor as a criterion for recommending programs; and recommending using the processor, another program having an actor that matches the identified actor of the currently viewed program. | 1. A method for recommending television programming to a user, comprising: monitoring, using a processor within user television equipment, which television programming is being viewed by the user; automatically identifying, using the processor, a currently viewed program based on the monitoring, wherein the currently viewed program has a plurality of program attributes each included within a respective attribute category; determining that a user has selected an attribute category of actor as a criterion for recommending programs; automatically identifying an actor who performs in the currently viewed program responsive to determining that the user has selected the attribute category of actor as a criterion for recommending programs; and recommending using the processor, another program having an actor that matches the identified actor of the currently viewed program. 3. The method of claim 1 further comprising allowing the user to set a minimum viewing duration, wherein automatically identifying a currently viewed program based on the monitoring comprises determining that the currently viewed program has been viewed by the user for at least the minimum viewing duration. | 0.631579 |
9,990,346 | 10 | 12 | 10. A method for editing a document using a document editing application on an electronic device, the method comprising: controlling to display the document in a display area of the document editing application; and controlling to, while displaying the document in the display area of the document editing application, use the document editing application for at least: controlling to receive, in the display area of the document editing application, a drag input for selecting a first one word from the document, controlling to identify, based on receiving an input for a user interface item provided by the document editing application, invoke a web search using both the selected first one word and a second one word associated with the selected first one word, wherein the second one word is identified in the electronic device, the identified second one word is other than the selected first one word, and the selected first one word and the identified second one word for the web search are transmitted toward a web search server, controlling to display a plurality of images together in another display area of the document editing application while displaying the document in the display area of the document editing application, wherein the plurality of the images are obtained based on the web search invoked from the document editing application using both the selected first one word and the identified second one word, and the web search is performed by the web search server, and controlling to, based on receiving an input for inserting an image selected from the obtained plurality of images, insert the selected image at a location in the document while displaying the obtained plurality of images in the other display area of the document editing application. | 10. A method for editing a document using a document editing application on an electronic device, the method comprising: controlling to display the document in a display area of the document editing application; and controlling to, while displaying the document in the display area of the document editing application, use the document editing application for at least: controlling to receive, in the display area of the document editing application, a drag input for selecting a first one word from the document, controlling to identify, based on receiving an input for a user interface item provided by the document editing application, invoke a web search using both the selected first one word and a second one word associated with the selected first one word, wherein the second one word is identified in the electronic device, the identified second one word is other than the selected first one word, and the selected first one word and the identified second one word for the web search are transmitted toward a web search server, controlling to display a plurality of images together in another display area of the document editing application while displaying the document in the display area of the document editing application, wherein the plurality of the images are obtained based on the web search invoked from the document editing application using both the selected first one word and the identified second one word, and the web search is performed by the web search server, and controlling to, based on receiving an input for inserting an image selected from the obtained plurality of images, insert the selected image at a location in the document while displaying the obtained plurality of images in the other display area of the document editing application. 12. The method of claim 10 , wherein the controlling to insert the selected image at the location in the document comprises controlling to insert the selected image at a location of a cursor placed in the document. | 0.5 |
9,645,994 | 14 | 15 | 14. The system of claim 13 , wherein the two or more tasks include at least one of a task to determine a status of an issue in the conversation exchanged between multiple users of the platform, and a task to determine a nature of the conversation exchanged between multiple users of the platform. | 14. The system of claim 13 , wherein the two or more tasks include at least one of a task to determine a status of an issue in the conversation exchanged between multiple users of the platform, and a task to determine a nature of the conversation exchanged between multiple users of the platform. 15. The system of claim 14 , wherein calculating the parameter value further includes: processing, by the one or more processors, the at least one equation for the two or more tasks for a pre-defined number of iterations. | 0.5 |
7,686,682 | 11 | 12 | 11. A computer game for tagging stored digital images, comprising: a randomizer for selecting: m images of the stored digital images, to be used in a game round, m being an integer larger than zero; and x letters of the alphabet, to be used in the game round, x being an integer larger than zero; an image display for simultaneously displaying n images out of m images, n being an integer larger than zero, wherein said display comprises n screens and wherein n=m and each of the n images is displayed on one of the screens; a letter tray for displaying a plurality of letter tiles, each letter tile representing one of the x letters; a highlighter for selectively highlighting one of the letter tiles according to a user pointer; a word tray enabling a user to construct words by selecting letter tiles from the letter tray; a tag generator generating tags linking words constructed in the word tray to corresponding images of the n images; and a timer counting a time period T 1 , wherein after each period T 1 each of then images is displayed on a different one of the screens. | 11. A computer game for tagging stored digital images, comprising: a randomizer for selecting: m images of the stored digital images, to be used in a game round, m being an integer larger than zero; and x letters of the alphabet, to be used in the game round, x being an integer larger than zero; an image display for simultaneously displaying n images out of m images, n being an integer larger than zero, wherein said display comprises n screens and wherein n=m and each of the n images is displayed on one of the screens; a letter tray for displaying a plurality of letter tiles, each letter tile representing one of the x letters; a highlighter for selectively highlighting one of the letter tiles according to a user pointer; a word tray enabling a user to construct words by selecting letter tiles from the letter tray; a tag generator generating tags linking words constructed in the word tray to corresponding images of the n images; and a timer counting a time period T 1 , wherein after each period T 1 each of then images is displayed on a different one of the screens. 12. The computer game of claim 11 , wherein the x letter tiles are divided to n groups of randomly selected letter tiles, and wherein the letter tiles of each of the n groups are oriented towards a corresponding one of the screens. | 0.510593 |
8,430,301 | 12 | 13 | 12. A computer program product comprising a computer usable medium having a computer readable program code embedded therein for controlling a data processing apparatus, the computer readable program code configured to cause the data processing apparatus to execute a process for generating a self-authenticating printed document, the process comprising: (a) receiving an original document image; (b) processing the original document image to generate processed data; (c) generating a barcode stamp element encoding a code calculated from the processed data generated in step (b); (d) generating a hierarchical barcode stamp by repeating the barcode stamp element in accordance with a pre-defined pattern; (e) controlling a printer to print the hierarchical barcode stamp and the original document image on a front side of a recording medium, wherein the hierarchical barcode stamp is printed with gray tone tiles and the original document image is printed in a black color, the hierarchical barcode stamp and the original document image overlapping each other such that at least some content of the original document image printed in the black color overlaps some gray tone tiles of the hierarchical barcode stamp. | 12. A computer program product comprising a computer usable medium having a computer readable program code embedded therein for controlling a data processing apparatus, the computer readable program code configured to cause the data processing apparatus to execute a process for generating a self-authenticating printed document, the process comprising: (a) receiving an original document image; (b) processing the original document image to generate processed data; (c) generating a barcode stamp element encoding a code calculated from the processed data generated in step (b); (d) generating a hierarchical barcode stamp by repeating the barcode stamp element in accordance with a pre-defined pattern; (e) controlling a printer to print the hierarchical barcode stamp and the original document image on a front side of a recording medium, wherein the hierarchical barcode stamp is printed with gray tone tiles and the original document image is printed in a black color, the hierarchical barcode stamp and the original document image overlapping each other such that at least some content of the original document image printed in the black color overlaps some gray tone tiles of the hierarchical barcode stamp. 13. The computer program product of claim 12 , wherein step (c) comprises: generating a hash code from the processed data generated in step (b); and generating the barcode stamp element which encodes the hash code; and wherein step (d) comprises: generating the hierarchical barcode stamp from the barcode stamp element by repeating the barcode stamp element in accordance with the pre-defined pattern. | 0.5 |
8,914,354 | 1 | 8 | 1. A method of estimating selectivity of a base table predicate, the method comprising: receiving, with a processor, a database query, the query comprising one or more query predicates and referencing one or more database tables; identifying, with the processor, one or more join indexes, wherein each of the one or more join index(es) is respectively defined on a single one of database tables referenced by the database query, the join index(es) comprising one or more join index predicates; calculating, with the processor, a row count of rows of the database tables referenced by the database query selected by the query predicates at least partly using a row count of the one or more join indexes or statistics of the one or more join indexes; and calculating, with the processor, selectivity of at least one of the query predicates at least partly from the calculated row count. | 1. A method of estimating selectivity of a base table predicate, the method comprising: receiving, with a processor, a database query, the query comprising one or more query predicates and referencing one or more database tables; identifying, with the processor, one or more join indexes, wherein each of the one or more join index(es) is respectively defined on a single one of database tables referenced by the database query, the join index(es) comprising one or more join index predicates; calculating, with the processor, a row count of rows of the database tables referenced by the database query selected by the query predicates at least partly using a row count of the one or more join indexes or statistics of the one or more join indexes; and calculating, with the processor, selectivity of at least one of the query predicates at least partly from the calculated row count. 8. The method of claim 1 further comprising calculating, with the processor, the row count of the join index(es) from random sampling. | 0.737255 |
10,127,231 | 1 | 2 | 1. A method comprising: receiving, at a processor, first media content for annotation by the processor based on an associated audio annotation; identifying, by the processor, the audio annotation, wherein the audio annotation is stored within a digital file; generating, via the processor, text from the audio annotation using a grammar; parsing, via the processor, the text to identify first metadata indicative of one or more of a location, an individual or an activity; based on weights assigned to the first metadata, identifying, via the processor, second media content having an associated weighted second metadata corresponding to the first metadata; generating, via the processor, at least one descriptive annotation for the first media content based on the first metadata and the second metadata; receiving, by the processor, additional metadata via a dialog with a user who recorded the first media content; annotating, via the processor, the first media content using the at least one descriptive annotation and the additional metadata to yield annotated first media content; and providing the first annotated media content to users. | 1. A method comprising: receiving, at a processor, first media content for annotation by the processor based on an associated audio annotation; identifying, by the processor, the audio annotation, wherein the audio annotation is stored within a digital file; generating, via the processor, text from the audio annotation using a grammar; parsing, via the processor, the text to identify first metadata indicative of one or more of a location, an individual or an activity; based on weights assigned to the first metadata, identifying, via the processor, second media content having an associated weighted second metadata corresponding to the first metadata; generating, via the processor, at least one descriptive annotation for the first media content based on the first metadata and the second metadata; receiving, by the processor, additional metadata via a dialog with a user who recorded the first media content; annotating, via the processor, the first media content using the at least one descriptive annotation and the additional metadata to yield annotated first media content; and providing the first annotated media content to users. 2. The method of claim 1 , wherein additional data elements are also associated with the first media content. | 0.610714 |
8,510,308 | 1 | 3 | 1. A method performed by data processing apparatus, the method comprising: receiving a collection of text; identifying a first collection of instance-class pairs for the collection of text, wherein the first collection of instance-class pairs are identified by applying one or more template patterns to a collection of documents; clustering a collection of semantically similar phrases using the collection of text; determining, for each class in the first collection of instance-class pairs: whether a threshold number of instances within a cluster in the semantically similar phrase clusters are labeled by the class, and whether a threshold number of clusters in the semantically similar phrase clusters include at least one instance that is labeled by the class; in response to determining that a threshold number of instances within a cluster are labeled by a class and a threshold number of clusters in the semantically similar phrase clusters include at least one instance that is labeled by the class, selecting each instance in the first collection of instance-class pairs that are labeled by the class to be included in a second collection of instance-class pairs; and storing the second collection of instance-class pairs for use in information retrieval. | 1. A method performed by data processing apparatus, the method comprising: receiving a collection of text; identifying a first collection of instance-class pairs for the collection of text, wherein the first collection of instance-class pairs are identified by applying one or more template patterns to a collection of documents; clustering a collection of semantically similar phrases using the collection of text; determining, for each class in the first collection of instance-class pairs: whether a threshold number of instances within a cluster in the semantically similar phrase clusters are labeled by the class, and whether a threshold number of clusters in the semantically similar phrase clusters include at least one instance that is labeled by the class; in response to determining that a threshold number of instances within a cluster are labeled by a class and a threshold number of clusters in the semantically similar phrase clusters include at least one instance that is labeled by the class, selecting each instance in the first collection of instance-class pairs that are labeled by the class to be included in a second collection of instance-class pairs; and storing the second collection of instance-class pairs for use in information retrieval. 3. The method of claim 1 , where the threshold number of clusters is a maximum number of clusters that includes an instance of the class. | 0.848115 |
9,596,228 | 19 | 22 | 19. A system, comprising: a service provider device associated with a service provider, the service provider device being configured for: receiving a document account number associated with a user of a document banking system hosted on a server in communication with the service provider device, wherein the document account number is received upon the user swiping a document card at the service provider device; and sending content to the document banking system corresponding to a service along with details of the service provider via secure Application Program Interfaces (APIs); a content handler hosted on the server, the content handler being configured for: authenticating, on a one-time basis, the service provider for sending the content to the user via the document banking system, wherein the authenticating is based on receiving the document account number from the service provider device; receiving the content from the service provider corresponding to a service used by the user, the content being received via secure Application Program Interfaces (APIs), the content being received along with details of the service provider, the user having a document bank account with the document banking system; identifying a template corresponding to the service for which the content is received, wherein the template is stored in a storage module associated with the document bank account; overlaying the received content over the identified template to generate or to update an electronic document with the content received from the service provider; adding the generated or updated electronic document to the storage module associated with the document bank account of the user; and a user interface hosted on the server, the user interface being configured for: displaying the generated or updated electronic document. | 19. A system, comprising: a service provider device associated with a service provider, the service provider device being configured for: receiving a document account number associated with a user of a document banking system hosted on a server in communication with the service provider device, wherein the document account number is received upon the user swiping a document card at the service provider device; and sending content to the document banking system corresponding to a service along with details of the service provider via secure Application Program Interfaces (APIs); a content handler hosted on the server, the content handler being configured for: authenticating, on a one-time basis, the service provider for sending the content to the user via the document banking system, wherein the authenticating is based on receiving the document account number from the service provider device; receiving the content from the service provider corresponding to a service used by the user, the content being received via secure Application Program Interfaces (APIs), the content being received along with details of the service provider, the user having a document bank account with the document banking system; identifying a template corresponding to the service for which the content is received, wherein the template is stored in a storage module associated with the document bank account; overlaying the received content over the identified template to generate or to update an electronic document with the content received from the service provider; adding the generated or updated electronic document to the storage module associated with the document bank account of the user; and a user interface hosted on the server, the user interface being configured for: displaying the generated or updated electronic document. 22. The system of claim 19 , wherein the document banking system includes a billing and payment module for handling billing and payment related activities. | 0.705323 |
8,620,911 | 16 | 19 | 16. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor-based system, cause the processor-based system to perform a method for responding to a request entry, comprising: receiving the request entry for information related to at least one document-based workflow; identifying an originator of the request entry; determining information access rules for the identified originator; mapping the request entry into a query, based upon the information access rules, for i) either a specific task sub-database ( 22 ) or an analytics-supporting general task sub-database ( 24 ) of a registry database ( 20 ) and ii) at least one source (NS 1 , NS 2 ) other than a source (S 1 , S 2 , S 3 , S 4 ) that subscribes to the registry database ( 20 ); actively collecting data based upon the query from the specific task sub-database ( 22 ) or the analytics-supporting general task sub-database ( 24 ), and from the at least one source (NS 1 , NS 2 ) other than the source (S 1 , S 2 , S 3 , S 4 ) that subscribes to the registry database ( 20 ); running the mapped query; and at least one of: i) repopulating a pre-existing field of the specific task sub-database ( 22 ) based upon data received from the running of the mapped query; or ii) depopulating or deleting a pre-existing field of the specific task sub-database ( 22 ) based upon data received from the running of the mapped query; or iii) creating at least one de novo field in the specific task sub-database ( 22 ); and populating the at least one de novo field with data retrieved from the running of the mapped query. | 16. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor-based system, cause the processor-based system to perform a method for responding to a request entry, comprising: receiving the request entry for information related to at least one document-based workflow; identifying an originator of the request entry; determining information access rules for the identified originator; mapping the request entry into a query, based upon the information access rules, for i) either a specific task sub-database ( 22 ) or an analytics-supporting general task sub-database ( 24 ) of a registry database ( 20 ) and ii) at least one source (NS 1 , NS 2 ) other than a source (S 1 , S 2 , S 3 , S 4 ) that subscribes to the registry database ( 20 ); actively collecting data based upon the query from the specific task sub-database ( 22 ) or the analytics-supporting general task sub-database ( 24 ), and from the at least one source (NS 1 , NS 2 ) other than the source (S 1 , S 2 , S 3 , S 4 ) that subscribes to the registry database ( 20 ); running the mapped query; and at least one of: i) repopulating a pre-existing field of the specific task sub-database ( 22 ) based upon data received from the running of the mapped query; or ii) depopulating or deleting a pre-existing field of the specific task sub-database ( 22 ) based upon data received from the running of the mapped query; or iii) creating at least one de novo field in the specific task sub-database ( 22 ); and populating the at least one de novo field with data retrieved from the running of the mapped query. 19. The computer-readable medium of claim 16 , the method further comprising generating output, based upon the collected data, for one of a plurality of document-based workflows in the registry database ( 20 ), the output affecting a condition of the one of the plurality of document-based workflows upstream, downstream, or at a point at which the request entry is received. | 0.81003 |
6,108,004 | 22 | 23 | 22. A computer-based system used to develop data mining objects as per claim 19, wherein said main menu comprises a plurality of windows, a first window displaying said listed data mining object types and additionally sub-objects, a second window displaying said sub-objects and a third window displaying a heterogenous selection of said sub-objects. | 22. A computer-based system used to develop data mining objects as per claim 19, wherein said main menu comprises a plurality of windows, a first window displaying said listed data mining object types and additionally sub-objects, a second window displaying said sub-objects and a third window displaying a heterogenous selection of said sub-objects. 23. A computer-based system used to develop data mining objects as per claim 22, wherein said sub-objects are graphically ordered in various configurations creating variant data mining profiles. | 0.5 |
4,476,724 | 1 | 3 | 1. Audiometer to obtain test sounds, or frequency, versus perceived amplitude in diagrammatic x-y coordinate output form for testing hearing of a person for tones, music and speech having an output unit (11) in form of a coordinate system in which amplitude forms one coordinate parameter and sound, or frequency another coordinate parameter; means (21) for generating electrical test signals representative of test sounds or tones; amplitude control means (15, 16) connected to said test sound or tone generating means for controlling the amplitude of the output thereof and providing an amplitude control output signal; tone control means (17, 18) connected to said test sound or tone generating means for controlling the nature of the test sound or frequency of the test tone thereof, and providing a test sound control output signal; test person transducer means (TX) transducing the test sound, or tone signals of the nature of the sound or at the frequency of the test tone and the level controlled by the tone control means and the amplitude control means, respectively; and test person controlled response means (13, 14) providing an electrical perception output signal if a predetermined test sound, or tone has been perceived, comprising, in accordance with the invention, an electronic digital matrix control circuit (10) receiving said amplitude control output signal, said test sound or tone control output signal and the perception output signal; and wherein the output unit comprises a liquid crystal display (LCD) in matrix form (11, 26) connected to and controlled by said digital matrix control circuit and providing an output in x-y coordinate form of perceived amplitude of a respective test sound or frequency at the instant of reception of the perception output signal. | 1. Audiometer to obtain test sounds, or frequency, versus perceived amplitude in diagrammatic x-y coordinate output form for testing hearing of a person for tones, music and speech having an output unit (11) in form of a coordinate system in which amplitude forms one coordinate parameter and sound, or frequency another coordinate parameter; means (21) for generating electrical test signals representative of test sounds or tones; amplitude control means (15, 16) connected to said test sound or tone generating means for controlling the amplitude of the output thereof and providing an amplitude control output signal; tone control means (17, 18) connected to said test sound or tone generating means for controlling the nature of the test sound or frequency of the test tone thereof, and providing a test sound control output signal; test person transducer means (TX) transducing the test sound, or tone signals of the nature of the sound or at the frequency of the test tone and the level controlled by the tone control means and the amplitude control means, respectively; and test person controlled response means (13, 14) providing an electrical perception output signal if a predetermined test sound, or tone has been perceived, comprising, in accordance with the invention, an electronic digital matrix control circuit (10) receiving said amplitude control output signal, said test sound or tone control output signal and the perception output signal; and wherein the output unit comprises a liquid crystal display (LCD) in matrix form (11, 26) connected to and controlled by said digital matrix control circuit and providing an output in x-y coordinate form of perceived amplitude of a respective test sound or frequency at the instant of reception of the perception output signal. 3. Audiometer according to claim 1 wherein the digital matrix control circuit (10, 40) includes a data bus (20); and wherein a digital control unit (25) is provided, connected to the data bus. | 0.755102 |
8,133,121 | 16 | 19 | 16. An electronic game table stacking component, comprising: a table list sub-component and a player information sub-component; said table list sub-component including a grid for displaying a plurality of categories of information about a plurality of game tables opened by a player; said player information sub-component including information about a plurality of players at a selected one of said plurality of game tables; wherein said table list sub-component includes an indicator for said selected one of said plurality of game tables; and wherein said stacking component includes an indicator notifying said player of tables for which action is needed and displaying a relative priority for said tables. | 16. An electronic game table stacking component, comprising: a table list sub-component and a player information sub-component; said table list sub-component including a grid for displaying a plurality of categories of information about a plurality of game tables opened by a player; said player information sub-component including information about a plurality of players at a selected one of said plurality of game tables; wherein said table list sub-component includes an indicator for said selected one of said plurality of game tables; and wherein said stacking component includes an indicator notifying said player of tables for which action is needed and displaying a relative priority for said tables. 19. An electronic game table stacking component according to claim 16 , further comprising an action area component. | 0.833333 |
10,089,549 | 8 | 14 | 8. A computer implemented method for estimating ego-motion from video scenes, the method comprising an act of: causing one or more processers to execute instructions encoded on a non-transitory computer-readable medium, such that upon execution, the one or more processors perform operations of: for consecutive frames in a video captured by a moving camera, determining a first ego-translation estimate between the consecutive frames from a first local minimum (h 0 ,v 0 ); determining a second ego-translation estimate from a second local minimum (h′ 0 ,v′ 0 ); if the second ego-translation estimate does not equal the first ego-translation estimate, determining an optimal solution by minimizing a cost function until the first ego-translation estimate and the second ego-translation estimate are a matching estimate; estimating ego-motion of the camera using the optimal solution; and detecting independent moving objects in the video after compensating for ego-motion of the camera. | 8. A computer implemented method for estimating ego-motion from video scenes, the method comprising an act of: causing one or more processers to execute instructions encoded on a non-transitory computer-readable medium, such that upon execution, the one or more processors perform operations of: for consecutive frames in a video captured by a moving camera, determining a first ego-translation estimate between the consecutive frames from a first local minimum (h 0 ,v 0 ); determining a second ego-translation estimate from a second local minimum (h′ 0 ,v′ 0 ); if the second ego-translation estimate does not equal the first ego-translation estimate, determining an optimal solution by minimizing a cost function until the first ego-translation estimate and the second ego-translation estimate are a matching estimate; estimating ego-motion of the camera using the optimal solution; and detecting independent moving objects in the video after compensating for ego-motion of the camera. 14. The method as set forth in claim 8 , wherein the one or more processors further perform operations of: performing a line search method to a function based on the first ego-translation estimate in combination with a scaled difference between the first ego-translation estimate and the second ego-translation estimate; using an alternate line search method to determine a third ego-translation estimate by starting from a position determined using a round function; and resetting the second ego-translation estimate equal to the results of the alternate line search method based on the third ego-translation estimate. | 0.660263 |
9,377,948 | 10 | 17 | 10. An information handling device, comprising: a display; an input surface; one or more processors; a memory device storing instructions accessible to the one or more processors, the instructions being executable by the one or more processors to: accept, at the input surface, one or more inputs, the one or more inputs comprising handwriting inputs including a special handwriting input pre-associated with a request for assistance; determine, using the one or more processors, a candidate list of inputs based on the handwriting inputs and the special handwriting input; and provide, using the one or more processors, a display of the candidate list on the display. | 10. An information handling device, comprising: a display; an input surface; one or more processors; a memory device storing instructions accessible to the one or more processors, the instructions being executable by the one or more processors to: accept, at the input surface, one or more inputs, the one or more inputs comprising handwriting inputs including a special handwriting input pre-associated with a request for assistance; determine, using the one or more processors, a candidate list of inputs based on the handwriting inputs and the special handwriting input; and provide, using the one or more processors, a display of the candidate list on the display. 17. The information handling device of claim 10 , wherein the input surface is selected from the group consisting of a touch screen and a touch pad. | 0.784884 |
8,600,925 | 1 | 5 | 1. A computer system comprising: a logical processor; a memory in operable communication with the logical processor; a data context instance residing in the memory; a database connection residing in the memory; an object model residing in the memory, the object model mapped by an object-relational mapper; and an initialization monitor residing in the memory and having code which upon execution monitors for a first attempted use at runtime of the database connection with the data context instance and the object model. | 1. A computer system comprising: a logical processor; a memory in operable communication with the logical processor; a data context instance residing in the memory; a database connection residing in the memory; an object model residing in the memory, the object model mapped by an object-relational mapper; and an initialization monitor residing in the memory and having code which upon execution monitors for a first attempted use at runtime of the database connection with the data context instance and the object model. 5. The system of claim 1 , wherein the system further comprises at least one of the following residing in the memory: a model-hash of at least a portion of the object model, a schema-hash of at least a portion of a schema of a database. | 0.5 |
7,974,912 | 17 | 29 | 17. A method that manages pay-per-click advertising, by determining an amount to be charged in response to a click of a hyperlink associated with a target keyword, comprising accessing with a computer processor, a particular amount a first advertiser is willing to be charged in response to a click of a hyperlink associated with said first advertiser, accessing with a computer processor, first and second different statistics related to one or more of a rate of use by users, number of times a hyperlink was viewed, data that relates to an increase or decrease in the use of a keyword by users, demographics of users associated with a keyword or demographics of advertisers associated with a keyword, and without human intervention, determining with a computer processor, an amount to be charged to a second advertiser in response to a click of a hyperlink associated with said target keyword and said second advertiser, wherein said amount to be charged to said second advertiser is determined using said particular amount, and is also determined using said first and second statistics. | 17. A method that manages pay-per-click advertising, by determining an amount to be charged in response to a click of a hyperlink associated with a target keyword, comprising accessing with a computer processor, a particular amount a first advertiser is willing to be charged in response to a click of a hyperlink associated with said first advertiser, accessing with a computer processor, first and second different statistics related to one or more of a rate of use by users, number of times a hyperlink was viewed, data that relates to an increase or decrease in the use of a keyword by users, demographics of users associated with a keyword or demographics of advertisers associated with a keyword, and without human intervention, determining with a computer processor, an amount to be charged to a second advertiser in response to a click of a hyperlink associated with said target keyword and said second advertiser, wherein said amount to be charged to said second advertiser is determined using said particular amount, and is also determined using said first and second statistics. 29. The method of claim 17 wherein determining the amount includes the use of a minimum currency amount. | 0.752381 |
8,934,661 | 8 | 14 | 8. A computer program product for selecting a subset of a plurality of images for a viewer, the computer program product comprising a computer-readable storage medium containing computer program code for: storing user profiles for each of a plurality of users of a social networking system; storing information for each of a plurality of objects in the social networking system; storing a plurality of connections between each of the plurality of the users and the other users or objects in the social networking system; accessing a plurality of images provided by a posting user of the plurality of users; receiving a request from a viewing user of the plurality of users to access an album, the album comprising a set of images selected from the plurality of images; identifying one or more tagged objects in the images in the album, where a tagged object is an object of the plurality of objects in the social networking system; computing a score for one or more of the plurality of images, where the score for an image is based at least in part on an association between information from a user profile of the viewing user and the one or more tagged objects in the image; selecting a subset of the plurality of images based on the computed scores, wherein one or more of the computed scores are adjusted to select a diverse subset of images that include a diversity of tagged objects across the one or more of the plurality of images; and sending for display to the viewing user an album, the album comprising the selected subset of the plurality of images. | 8. A computer program product for selecting a subset of a plurality of images for a viewer, the computer program product comprising a computer-readable storage medium containing computer program code for: storing user profiles for each of a plurality of users of a social networking system; storing information for each of a plurality of objects in the social networking system; storing a plurality of connections between each of the plurality of the users and the other users or objects in the social networking system; accessing a plurality of images provided by a posting user of the plurality of users; receiving a request from a viewing user of the plurality of users to access an album, the album comprising a set of images selected from the plurality of images; identifying one or more tagged objects in the images in the album, where a tagged object is an object of the plurality of objects in the social networking system; computing a score for one or more of the plurality of images, where the score for an image is based at least in part on an association between information from a user profile of the viewing user and the one or more tagged objects in the image; selecting a subset of the plurality of images based on the computed scores, wherein one or more of the computed scores are adjusted to select a diverse subset of images that include a diversity of tagged objects across the one or more of the plurality of images; and sending for display to the viewing user an album, the album comprising the selected subset of the plurality of images. 14. The computer program product of claim 8 , wherein the score for an image is further based in part on tagged objects associated with the other images in the plurality of images. | 0.782609 |
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