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8,731,994 | 1 | 5 | 1. A computer-implemented method comprising: accessing, by one or more computers, a root technology maturity hypothesis and a plurality of associated, intermediate technology maturity hypotheses that must be confirmed for the root technology maturity hypothesis to be proven, each hypothesis forecasting an extent to which a technology will progress and an impact of the progress of the technology, and each intermediate technology maturity hypothesis being associated with one or more precursor technology events that are to be tracked to confirm or disprove the respective intermediate technology maturity hypothesis, each precursor technology event having one or more associated regular expressions; searching one or more information sources to identify information contextually relevant to one or more of the precursor technology events; automatically analyzing, by one or more computers, the identified information retrieved from the one or more information sources to identify one or more text strings matching the regular expressions associated with one or more of the precursor technology events; for each identified text string, determining that the text string either confirms or disproves the precursor technology event associated with the text string; for each precursor technology event confirmed or disproved by an identified text string, determining a respective status of the associated intermediate technology maturity hypothesis to be one of confirmed, disproved, or indeterminate based on a status of its associated one or more precursor technology events; determining the status of the root technology maturity hypothesis as confirmed, disproved, or indeterminate based on the status of the intermediate technology maturity hypotheses, such that the root technology maturity hypothesis is determined to be confirmed only if each of the plurality of intermediate technology maturity hypotheses is confirmed; and providing a status display that displays the status of the plurality of intermediate technology maturity hypotheses and the root technology maturity hypothesis. | 1. A computer-implemented method comprising: accessing, by one or more computers, a root technology maturity hypothesis and a plurality of associated, intermediate technology maturity hypotheses that must be confirmed for the root technology maturity hypothesis to be proven, each hypothesis forecasting an extent to which a technology will progress and an impact of the progress of the technology, and each intermediate technology maturity hypothesis being associated with one or more precursor technology events that are to be tracked to confirm or disprove the respective intermediate technology maturity hypothesis, each precursor technology event having one or more associated regular expressions; searching one or more information sources to identify information contextually relevant to one or more of the precursor technology events; automatically analyzing, by one or more computers, the identified information retrieved from the one or more information sources to identify one or more text strings matching the regular expressions associated with one or more of the precursor technology events; for each identified text string, determining that the text string either confirms or disproves the precursor technology event associated with the text string; for each precursor technology event confirmed or disproved by an identified text string, determining a respective status of the associated intermediate technology maturity hypothesis to be one of confirmed, disproved, or indeterminate based on a status of its associated one or more precursor technology events; determining the status of the root technology maturity hypothesis as confirmed, disproved, or indeterminate based on the status of the intermediate technology maturity hypotheses, such that the root technology maturity hypothesis is determined to be confirmed only if each of the plurality of intermediate technology maturity hypotheses is confirmed; and providing a status display that displays the status of the plurality of intermediate technology maturity hypotheses and the root technology maturity hypothesis. 5. The method of claim 1 , wherein an effect of each precursor technology event on a respective intermediate technology maturity hypothesis is weighted. | 0.718519 |
9,619,439 | 1 | 5 | 1. A computer-implemented method for providing a font, the method comprising: receiving a request from a client device to download a font; accessing the requested font, wherein the accessed font comprises a requested character map and a requested glyph table; creating a supported character list and a modified font based on the requested character map, wherein the modified font comprises a modified character map and a modified glyph table, and wherein the modified character map comprises placeholder data for at least one character of the accessed font; compressing the modified font; sending the supported character list and the compressed modified font to the client device; sending, to the client device after sending the supported character list and the compressed modified font to the client device, character data comprising character map data for the at least one character in the modified font, and glyph data for the at least one character in the modified font, and location data for the character map data and the glyph data; wherein the character map data is for filling in the placeholder data for the at least one character in the modified character map in the modified font based on the location data; and wherein the glyph data is for merging the at least one character into the modified glyph table based on the location data. | 1. A computer-implemented method for providing a font, the method comprising: receiving a request from a client device to download a font; accessing the requested font, wherein the accessed font comprises a requested character map and a requested glyph table; creating a supported character list and a modified font based on the requested character map, wherein the modified font comprises a modified character map and a modified glyph table, and wherein the modified character map comprises placeholder data for at least one character of the accessed font; compressing the modified font; sending the supported character list and the compressed modified font to the client device; sending, to the client device after sending the supported character list and the compressed modified font to the client device, character data comprising character map data for the at least one character in the modified font, and glyph data for the at least one character in the modified font, and location data for the character map data and the glyph data; wherein the character map data is for filling in the placeholder data for the at least one character in the modified character map in the modified font based on the location data; and wherein the glyph data is for merging the at least one character into the modified glyph table based on the location data. 5. The computer-implemented method of claim 1 , wherein the character data sent to the client device represents data for a subset of all characters of the requested font. | 0.848485 |
8,655,642 | 4 | 6 | 4. The method of claim 2 , further comprising: presenting an output table adjacent to the e-mail address field, and further wherein the step of detecting a character key input having an associated non-Latin character includes the steps of: presenting for selection by a user within the output table a first field and at least one second field, the first field presenting the Latin equivalent of the non Latin characters, and the at least one second field presenting a predicted name. | 4. The method of claim 2 , further comprising: presenting an output table adjacent to the e-mail address field, and further wherein the step of detecting a character key input having an associated non-Latin character includes the steps of: presenting for selection by a user within the output table a first field and at least one second field, the first field presenting the Latin equivalent of the non Latin characters, and the at least one second field presenting a predicted name. 6. The method of claim 4 , wherein the first field contains an indication of an action to be taken with respect to the Latin equivalent of the non-Latin character input. | 0.764624 |
9,515,994 | 1 | 6 | 1. A multi-user searchable encryption system, the system comprising: a key generation server configured to generate system parameters, a primary key, and a secondary key; a user terminal configured to receive the primary key, encrypt data to obtain cypher text, encrypt symmetric key to obtain encrypted symmetric key, encrypt keyword to obtain encrypted keyword, generate trapdoor using the primary key for a search keyword inputted by user, and generate a decryption parameter using the primary key; a proxy server configured to receive the cypher text, the encrypted keyword, and the encrypted symmetric key from the user terminal, and the secondary key from the key generation server, encrypt trapdoor received from the user terminal using the secondary key, perform a lookup for search results corresponding to the search keyword; and a database server configured to store the cypher text at a location address and return the location address of the cypher text to the proxy server; wherein the proxy server is further configured to maintain a table of secondary keys, re-encrypt the encrypted symmetric key and encrypted keyword using the secondary key, and maintain a table of re-encrypted symmetric keys. | 1. A multi-user searchable encryption system, the system comprising: a key generation server configured to generate system parameters, a primary key, and a secondary key; a user terminal configured to receive the primary key, encrypt data to obtain cypher text, encrypt symmetric key to obtain encrypted symmetric key, encrypt keyword to obtain encrypted keyword, generate trapdoor using the primary key for a search keyword inputted by user, and generate a decryption parameter using the primary key; a proxy server configured to receive the cypher text, the encrypted keyword, and the encrypted symmetric key from the user terminal, and the secondary key from the key generation server, encrypt trapdoor received from the user terminal using the secondary key, perform a lookup for search results corresponding to the search keyword; and a database server configured to store the cypher text at a location address and return the location address of the cypher text to the proxy server; wherein the proxy server is further configured to maintain a table of secondary keys, re-encrypt the encrypted symmetric key and encrypted keyword using the secondary key, and maintain a table of re-encrypted symmetric keys. 6. The system of claim 1 , wherein the proxy server is further configured to generate a decryption attribute using the decryption parameter, the secondary key, and the re-encrypted symmetric key. | 0.617647 |
7,974,986 | 7 | 10 | 7. A system for distributing a resume of a job seeker to career websites, the system comprising: a server computer connected to a network; a storage device operationally adapted to the server computer; a job seeker profile and resume database stored within the storage device; a user interface presented on a client computer, the client computer communicating with the server computer to capture a list of target career websites from the job seeker; and a plurality of resume blasting bots executing on the server computer, each of the plurality of resume blasting bots navigating to a career website within the list of target career websites without user interaction through the network, if a username and a password for the job seeker for the career website is known, the resume blasting bot logs onto the career website without user interaction using the username and the password; and if the username and the password for the job seeker on the career website is unknown, the resume blasting bot creates a default user account on the career website using a default username and a default password and the resume blasting bot logs onto the career website without user interaction using the default username and the default password and the resume blasting bot fills in fields on the career website using the job seeker profile and resume database without user interaction. | 7. A system for distributing a resume of a job seeker to career websites, the system comprising: a server computer connected to a network; a storage device operationally adapted to the server computer; a job seeker profile and resume database stored within the storage device; a user interface presented on a client computer, the client computer communicating with the server computer to capture a list of target career websites from the job seeker; and a plurality of resume blasting bots executing on the server computer, each of the plurality of resume blasting bots navigating to a career website within the list of target career websites without user interaction through the network, if a username and a password for the job seeker for the career website is known, the resume blasting bot logs onto the career website without user interaction using the username and the password; and if the username and the password for the job seeker on the career website is unknown, the resume blasting bot creates a default user account on the career website using a default username and a default password and the resume blasting bot logs onto the career website without user interaction using the default username and the default password and the resume blasting bot fills in fields on the career website using the job seeker profile and resume database without user interaction. 10. The system according to claim 7 , wherein the resume blasting bot creates a default user account on the career website. | 0.650568 |
10,089,742 | 9 | 10 | 9. The method for claim 8 , further comprising: iteratively generating an n-gram data structure based on a second RNN and the set of token data structures, wherein the second RNN propagates the n-gram data structure during the iterative generation of the n-gram data structure; and iteratively generating the segmentation map further based on a plurality of iteratively generated combinations of the image data structure and the n-gram data structure. | 9. The method for claim 8 , further comprising: iteratively generating an n-gram data structure based on a second RNN and the set of token data structures, wherein the second RNN propagates the n-gram data structure during the iterative generation of the n-gram data structure; and iteratively generating the segmentation map further based on a plurality of iteratively generated combinations of the image data structure and the n-gram data structure. 10. The method of claim 9 , further comprising: training a long short-term memory (LSTM) neural network based on a training data that includes a plurality of other n-grams; and employing the trained LSTM as the second RNN. | 0.5 |
8,588,825 | 10 | 13 | 10. A user device comprising: a display; a communication interface; a memory to store instructions; and a processor to execute the instructions to: receive text authored by a user to create a text message; interpret a meaning of the text; obtain a facial expression of the user; determine a mood of the user based on the facial expression of the user; select a classification for the text message based on the meaning of the text and the mood of the user, wherein a selection of the classification includes to: map the mood of the user and the meaning of the text to the classification; and determine whether a confidence value associated with the classification exceeds a threshold value; display, via the display, text enhancements for the text message from which the user can select, wherein the text enhancements are based on the classification; receive a selection by the user for the text enhancements; include the text enhancements selected by the user with the text message; and send, via the communication interface, the text message with the text enhancements to a recipient. | 10. A user device comprising: a display; a communication interface; a memory to store instructions; and a processor to execute the instructions to: receive text authored by a user to create a text message; interpret a meaning of the text; obtain a facial expression of the user; determine a mood of the user based on the facial expression of the user; select a classification for the text message based on the meaning of the text and the mood of the user, wherein a selection of the classification includes to: map the mood of the user and the meaning of the text to the classification; and determine whether a confidence value associated with the classification exceeds a threshold value; display, via the display, text enhancements for the text message from which the user can select, wherein the text enhancements are based on the classification; receive a selection by the user for the text enhancements; include the text enhancements selected by the user with the text message; and send, via the communication interface, the text message with the text enhancements to a recipient. 13. The user device of claim 10 , wherein the instructions comprise instructions to: assign a confidence value to the mood of the user; and select the classification based on a prior history of classification selections. | 0.789675 |
8,918,317 | 15 | 20 | 15. A non-transitory computer program product tangibly storing computer program instructions executable by a computer processor to perform a method, the method comprising: (A) using a language model to decode a first portion of an audio signal into a first word in a token stream; (B) after (A): (B)(1) selecting a punctuation mark based on the language model and the first word; (B)(2) inserting the punctuation mark into the token stream at a position after the first word, based on a lexical cue provided by the first word; and (C) after (B), using the language model, the punctuation mark, and the first word to decode a second portion of the audio signal into a second word in the token stream at a position after the punctuation mark. | 15. A non-transitory computer program product tangibly storing computer program instructions executable by a computer processor to perform a method, the method comprising: (A) using a language model to decode a first portion of an audio signal into a first word in a token stream; (B) after (A): (B)(1) selecting a punctuation mark based on the language model and the first word; (B)(2) inserting the punctuation mark into the token stream at a position after the first word, based on a lexical cue provided by the first word; and (C) after (B), using the language model, the punctuation mark, and the first word to decode a second portion of the audio signal into a second word in the token stream at a position after the punctuation mark. 20. The computer program product of claim 15 , wherein (B) comprises inserting the punctuation mark into the token stream at the position after the first word, based on the lexical cue provided by the first word and an acoustical cue. | 0.6759 |
8,996,386 | 12 | 13 | 12. The head unit of claim 9 wherein the character recognition modules performs optical character recognition on the representation of the input button. | 12. The head unit of claim 9 wherein the character recognition modules performs optical character recognition on the representation of the input button. 13. The head unit of claim 12 wherein the mobile device voice recognition command determined by the character recognition module is based on a result of the optical character recognition preformed on the representation of the input button. | 0.53861 |
7,831,594 | 1 | 4 | 1. A method for estimating a static execution time of a database query, said method comprising: building a prediction of query runtime tree from historical query information at a computer system, said building comprising utilizing machine learning to build said prediction of query runtime tree such that node elements and leaf elements of said prediction of query runtime tree correspond to execution time ranges; receiving a database query at said computer system; and utilizing said prediction of query runtime tree to estimate said static execution time of said database query at said computer system said utilizing comprising traversing said prediction of query runtime tree on the basis of at least one query feature associated with said database query, such that a time range estimate of said static execution time is associated with said database query based upon a similarity of said at least one query feature to a historical query feature shared by a grouping of historical database queries. | 1. A method for estimating a static execution time of a database query, said method comprising: building a prediction of query runtime tree from historical query information at a computer system, said building comprising utilizing machine learning to build said prediction of query runtime tree such that node elements and leaf elements of said prediction of query runtime tree correspond to execution time ranges; receiving a database query at said computer system; and utilizing said prediction of query runtime tree to estimate said static execution time of said database query at said computer system said utilizing comprising traversing said prediction of query runtime tree on the basis of at least one query feature associated with said database query, such that a time range estimate of said static execution time is associated with said database query based upon a similarity of said at least one query feature to a historical query feature shared by a grouping of historical database queries. 4. The method as recited in claim 1 , wherein said building a prediction of query runtime tree from historical query information comprises: grouping an historical database query of said historical query information into an element of a binary decision tree based upon an execution time of said historical database query; and terminating construction of said element based upon a pre-defined termination condition. | 0.5 |
9,865,281 | 12 | 14 | 12. The method of claim 11 , wherein analyzing the vocal and video recordings for the first user according to one or more parameters for speech and one or more parameters for gestures comprises: identifying, by one or more processors, the one or more parameters for speech, wherein the one or more parameters are selected from a group of measures including: pauses, hesitations, interruptions, vibrato, stress, timbre, stuttering, laughter, volume, and word rate; analyzing, by one or more processors, the one or more parameters for speech; and producing, by one or more processors, at least one output data point for each of the one or more parameters for speech. | 12. The method of claim 11 , wherein analyzing the vocal and video recordings for the first user according to one or more parameters for speech and one or more parameters for gestures comprises: identifying, by one or more processors, the one or more parameters for speech, wherein the one or more parameters are selected from a group of measures including: pauses, hesitations, interruptions, vibrato, stress, timbre, stuttering, laughter, volume, and word rate; analyzing, by one or more processors, the one or more parameters for speech; and producing, by one or more processors, at least one output data point for each of the one or more parameters for speech. 14. The method of claim 12 , wherein determining one or more emotions and a role in the meeting for the first user comprises: identifying, by one or more processors, one or more highest recurring output data points from the at least one output data point for each of the one or more parameters for gestures; identifying, by one or more processors, the one or more highest recurring output data points as the one or more emotions for the first user; and determining, by one or more processors, the role in the meeting for the first user based at least on the identified one or more emotions for the first user. | 0.5 |
10,133,479 | 1 | 14 | 1. A method of text entry for an electronic device, the method comprising: (a) generating a sequence of letter entries from a sequence of keystrokes, wherein for any word a user want to input, a single keystrokes generates a letter entry for a single letter location of the word, and wherein the keystrokes performed over a keyboard with a plurality of keys partitioned into multiple regions, at least one region comprising one or more adjacent keys which are activated by a first keystroke and a plurality of second keystrokes, said first keystroke is configured to output a letter group entry which generates a group of possible letters at a letter location of the word and each keystroke from said plurality of second keystrokes is configured to output a single letter entry which generates a single letter to a letter location of a word, and said group of possible letters generated by said first keystroke only comprises letters generated by all said second keystrokes; (b) creating a list of possible words, each possible word is a word that is created from a combination of possible letters at each step of said sequence of letter entries that matches with a word in a priori database of words; (c) displaying said list of possible words to the user; and (d) receiving from the user a selected word in said list of possible words and providing the selected word for further processing. | 1. A method of text entry for an electronic device, the method comprising: (a) generating a sequence of letter entries from a sequence of keystrokes, wherein for any word a user want to input, a single keystrokes generates a letter entry for a single letter location of the word, and wherein the keystrokes performed over a keyboard with a plurality of keys partitioned into multiple regions, at least one region comprising one or more adjacent keys which are activated by a first keystroke and a plurality of second keystrokes, said first keystroke is configured to output a letter group entry which generates a group of possible letters at a letter location of the word and each keystroke from said plurality of second keystrokes is configured to output a single letter entry which generates a single letter to a letter location of a word, and said group of possible letters generated by said first keystroke only comprises letters generated by all said second keystrokes; (b) creating a list of possible words, each possible word is a word that is created from a combination of possible letters at each step of said sequence of letter entries that matches with a word in a priori database of words; (c) displaying said list of possible words to the user; and (d) receiving from the user a selected word in said list of possible words and providing the selected word for further processing. 14. The method of claim 1 , wherein said keyboard is presented on a touch screen whenever a finger or an object are swiped across the touch screen edge, said keys are regions over the touch screen and the keys activation is performed by a keystroke which is a swipe that starts at the edge of the touch screen and ends inside the key region, and first keystroke is performed by using a shorter swipe and second keystrokes are performed by using longer swipes. | 0.5 |
8,566,358 | 10 | 13 | 10. The system of claim 9 , further comprising: program instructions for automatically populating data of the automatically generated topic maps utilizing information parsed from applicable ones of the plurality of model assets and from the industry model. | 10. The system of claim 9 , further comprising: program instructions for automatically populating data of the automatically generated topic maps utilizing information parsed from applicable ones of the plurality of model assets and from the industry model. 13. The system of claim 10 , wherein the first layer of abstraction is a model level, and the second layer of abstraction is a meta model level. | 0.811518 |
9,223,827 | 3 | 4 | 3. The method according to claim 2 , said performing conceptual model relational inference on said constraint-normalized query statement further comprising performing subsumption inference on said constraint-normalized query statement; and said performing normal-form normalization on said transformed query statement to obtain said logic rules comprising performing disjunctive normal-form normalization on said transformed query statement. | 3. The method according to claim 2 , said performing conceptual model relational inference on said constraint-normalized query statement further comprising performing subsumption inference on said constraint-normalized query statement; and said performing normal-form normalization on said transformed query statement to obtain said logic rules comprising performing disjunctive normal-form normalization on said transformed query statement. 4. The method according to claim 3 , said checking validity of said logic rules further comprising: syntax checking whether said logic rules that have undergone normal-form normalization conform to defined syntax of a logic rule descriptive language. | 0.78185 |
10,108,621 | 10 | 17 | 10. A non-transitory computer-readable medium, excluding transitory propagating signals, storing instructions that, when executed by a computing device, which comprises one or more processors and computer memory, cause the computing device to perform operations for content indexing of data files being archived, the operations comprising: executing an indexer that, in the course of one or more data files being archived to respective archive copies, indexes the one or more data files according to content attributes, including at least one of: textual content, picture content, video content, and audio content, wherein each archive copy is stored offline relative to a user computing device that is distinct from the computing device executing the indexer; (a) associating by the indexer content attributes with respective smaller portions of each archive copy, (b) for the one or more data files being archived, generating by the indexer a searchable content index of associated content attributes relative to the smaller portions of each archive copy, and (c) associating by the indexer the content index with the respective archive copies; and executing a search filter that is configured to: (i) search in the content index for one or more search criteria received from the user computing device, (ii) cause only smaller portions of respective archive copies that satisfy the one or more search criteria, to be mounted to the user computing device, wherein archive copies and smaller portions thereof that do not satisfy the one or more search criteria are not mounted and remain offline relative to the user computing device, and (iii) present in response to the search criteria a fast-forward progression through the mounted smaller portions of respective archive copies that satisfy the one or more search criteria, without restoring the respective archive copies in their entireties to the user computing device. | 10. A non-transitory computer-readable medium, excluding transitory propagating signals, storing instructions that, when executed by a computing device, which comprises one or more processors and computer memory, cause the computing device to perform operations for content indexing of data files being archived, the operations comprising: executing an indexer that, in the course of one or more data files being archived to respective archive copies, indexes the one or more data files according to content attributes, including at least one of: textual content, picture content, video content, and audio content, wherein each archive copy is stored offline relative to a user computing device that is distinct from the computing device executing the indexer; (a) associating by the indexer content attributes with respective smaller portions of each archive copy, (b) for the one or more data files being archived, generating by the indexer a searchable content index of associated content attributes relative to the smaller portions of each archive copy, and (c) associating by the indexer the content index with the respective archive copies; and executing a search filter that is configured to: (i) search in the content index for one or more search criteria received from the user computing device, (ii) cause only smaller portions of respective archive copies that satisfy the one or more search criteria, to be mounted to the user computing device, wherein archive copies and smaller portions thereof that do not satisfy the one or more search criteria are not mounted and remain offline relative to the user computing device, and (iii) present in response to the search criteria a fast-forward progression through the mounted smaller portions of respective archive copies that satisfy the one or more search criteria, without restoring the respective archive copies in their entireties to the user computing device. 17. The non-transitory computer-readable medium of claim 10 wherein the content index is stored to a user computing device that is associated with the data files being archived. | 0.841682 |
8,321,396 | 3 | 4 | 3. The system of claim 2 wherein the headline detection module constructs the set of potential headlines by splitting the title meta-tag at all punctuation marks in the title meta-tag, resulting in a set of sub-strings of the title meta-tag. | 3. The system of claim 2 wherein the headline detection module constructs the set of potential headlines by splitting the title meta-tag at all punctuation marks in the title meta-tag, resulting in a set of sub-strings of the title meta-tag. 4. The system of claim 3 wherein the headline detection module further adds any of a plurality of bi-grams of the sub-strings and a plurality of n-grams of the sub-strings to the set of potential headlines. | 0.5 |
9,063,637 | 1 | 4 | 1. A method that alters a view of a document comprising: providing on a display of a computer processing device an editing view of a document at a zoom level such that input from a user can be received to edit content of the document; receiving a first input from the user requesting to zoom-out the editing view of the document from the zoom level; testing whether a resulting zoom level of the document is less than a threshold zoom level; altering the view of the document to provide a semantic zoom view of the document in response to determining the resulting zoom level is less than the threshold zoom level, wherein the semantic view of the document provides a plurality of thumbnails pages on the display and a heading pane comprising a plurality of headings contained in one or more pages of the document; receiving a second input from the user indicating a selection of one of the plurality of headings in the heading pane; and providing on the display of the computer processing device a subset of the plurality of thumbnail pages in the thumbnail pane in response to receiving the second input, wherein the subset of the plurality of thumbnail pages comprises a thumbnail page corresponding to the selection of one of the plurality of headings in the heading pane and a plurality of and preceeding and succeeding thumbnail pages to the thumbnail page. | 1. A method that alters a view of a document comprising: providing on a display of a computer processing device an editing view of a document at a zoom level such that input from a user can be received to edit content of the document; receiving a first input from the user requesting to zoom-out the editing view of the document from the zoom level; testing whether a resulting zoom level of the document is less than a threshold zoom level; altering the view of the document to provide a semantic zoom view of the document in response to determining the resulting zoom level is less than the threshold zoom level, wherein the semantic view of the document provides a plurality of thumbnails pages on the display and a heading pane comprising a plurality of headings contained in one or more pages of the document; receiving a second input from the user indicating a selection of one of the plurality of headings in the heading pane; and providing on the display of the computer processing device a subset of the plurality of thumbnail pages in the thumbnail pane in response to receiving the second input, wherein the subset of the plurality of thumbnail pages comprises a thumbnail page corresponding to the selection of one of the plurality of headings in the heading pane and a plurality of and preceeding and succeeding thumbnail pages to the thumbnail page. 4. The method of claim 1 , wherein the editing view comprises presenting a menu bar. | 0.876471 |
9,047,319 | 1 | 14 | 1. A method comprising: receiving, by a computing device, an image having one or more image tags, wherein each image tag is associated with the image as a whole; identifying a plurality of regions of the image; associating, by the computing device, a particular region of the plurality of regions with a particular image tag of the one or more image tags; determining, by the computing device, that one or more attribute tags describe at least one of the content or context of the particular region based at least in part on determining that the one or more attribute tags are associated with a highest magnitude measurement of diverse density of the particular region; and associating, by the computing device, the one or more attribute tags with the particular image tag to enable image searching based on the image tag and the attribute tags. | 1. A method comprising: receiving, by a computing device, an image having one or more image tags, wherein each image tag is associated with the image as a whole; identifying a plurality of regions of the image; associating, by the computing device, a particular region of the plurality of regions with a particular image tag of the one or more image tags; determining, by the computing device, that one or more attribute tags describe at least one of the content or context of the particular region based at least in part on determining that the one or more attribute tags are associated with a highest magnitude measurement of diverse density of the particular region; and associating, by the computing device, the one or more attribute tags with the particular image tag to enable image searching based on the image tag and the attribute tags. 14. The method of claim 1 , further comprising setting a particular attribute tag of the one or more attribute tags to a default value in response to determining based on thresholding that the particular attribute tag is not relevant. | 0.856442 |
9,544,381 | 14 | 15 | 14. The apparatus of claim 13 , wherein the first behavioral pattern is one of a first plurality of behavioral patterns, and wherein the second behavioral pattern is one of a second plurality of behavioral patterns. | 14. The apparatus of claim 13 , wherein the first behavioral pattern is one of a first plurality of behavioral patterns, and wherein the second behavioral pattern is one of a second plurality of behavioral patterns. 15. The apparatus of claim 14 , wherein the processor is further configured to execute the steps of: determining redundant information data based on the first plurality of behavioral patterns; constructing a plurality of data features, wherein each data feature of the plurality of data features corresponds to a redundant information datum of the redundant information data; and generating a prediction model based on the constructed plurality of data features, wherein determining whether the candidate user information datum and the prior user information data correspond to the same user is further based on the prediction model. | 0.5 |
9,208,153 | 11 | 12 | 11. The method of claim 1 wherein quantifying a relevance value of an event notification for a specific user further comprises: adjusting a relevance value of an event notification for a target user in proportion to a quantification, in the user profile information concerning the target user, of the target user's interest level in the file to which the event is directed, in a file type of the file to which the event is directed or in content of the file to which the event is directed. | 11. The method of claim 1 wherein quantifying a relevance value of an event notification for a specific user further comprises: adjusting a relevance value of an event notification for a target user in proportion to a quantification, in the user profile information concerning the target user, of the target user's interest level in the file to which the event is directed, in a file type of the file to which the event is directed or in content of the file to which the event is directed. 12. The method of claim 11 wherein content of the file further comprises at least one of: content in a body of the file, content in a modification made to the file by a user, content in a comment made by a user concerning the file and metadata of the file. | 0.5 |
8,051,371 | 1 | 7 | 1. A document analysis system comprising: a processor, the processor functioning as: an input unit that receives a document, the document comprising one of structured document or a semi-structured document, renders the received document, and stores the rendered document as an image in a storage unit; a basic layout analysis unit that groups document description elements of the document included in the image that are juxtaposed in a horizontal or vertical direction in the image, relates the grouped document description elements to layout components of the document that describe a layout of the document description elements of the document, and stores the related grouped document description elements and layout components in the storage unit; and an output unit that outputs the layout based on the stored related grouped document description elements and layout components, the layout identifying the layout components, the layout components referencing the grouped document description elements. | 1. A document analysis system comprising: a processor, the processor functioning as: an input unit that receives a document, the document comprising one of structured document or a semi-structured document, renders the received document, and stores the rendered document as an image in a storage unit; a basic layout analysis unit that groups document description elements of the document included in the image that are juxtaposed in a horizontal or vertical direction in the image, relates the grouped document description elements to layout components of the document that describe a layout of the document description elements of the document, and stores the related grouped document description elements and layout components in the storage unit; and an output unit that outputs the layout based on the stored related grouped document description elements and layout components, the layout identifying the layout components, the layout components referencing the grouped document description elements. 7. The document analysis system according to claim 1 , further comprising: an index document output unit generates and outputs an index document based on the document and information of the layout of the document; and an item document output unit that generates and outputs a document which describes a content of an item of the index document based on the information of the layout. | 0.779632 |
8,065,346 | 10 | 14 | 10. A computer readable medium being of non-transitory tangible media containing executable program instructions executed by a processor, comprising: a namespace and storage management application, executing on a computer associated with a management console, the namespace and storage management application initiating performance of commands directed to managed objects including facilitating configuration and management of pathnames in a logical namespace, and configured to spawn a graphical user interface thread for use by a GUI toolkit, the GUI toolkit configured to produce reusable GUI components that allow a user to interface with the application on a computer console to manage various said pathnames exported by heterogeneous namespace services and protocol implementations within the logical namespace, and to input commands as to selected objects on one or more associated servers, said GUI toolkit supporting reusable templates that facilitate reuse of the GUI components within one of the management application and other applications, said templates having optimized operational flow arrangements. | 10. A computer readable medium being of non-transitory tangible media containing executable program instructions executed by a processor, comprising: a namespace and storage management application, executing on a computer associated with a management console, the namespace and storage management application initiating performance of commands directed to managed objects including facilitating configuration and management of pathnames in a logical namespace, and configured to spawn a graphical user interface thread for use by a GUI toolkit, the GUI toolkit configured to produce reusable GUI components that allow a user to interface with the application on a computer console to manage various said pathnames exported by heterogeneous namespace services and protocol implementations within the logical namespace, and to input commands as to selected objects on one or more associated servers, said GUI toolkit supporting reusable templates that facilitate reuse of the GUI components within one of the management application and other applications, said templates having optimized operational flow arrangements. 14. The computer readable medium being of non-transitory tangible media as defined in claim 10 wherein said computer executable instructions include a remote agent module configured to manage a particular namespace and storage management server via application program interfaces exposed by the remote agent. | 0.648402 |
8,156,060 | 3 | 4 | 3. The interactive virtual agent (avatar) system of claim 1 , wherein the knowledge layers included in the corrective knowledge base comprise a combination of a additional word knowledge layer configured to identify misspelled or incorrect words and a set of relations configured to map misspelled or incorrect words to correct words. | 3. The interactive virtual agent (avatar) system of claim 1 , wherein the knowledge layers included in the corrective knowledge base comprise a combination of a additional word knowledge layer configured to identify misspelled or incorrect words and a set of relations configured to map misspelled or incorrect words to correct words. 4. The interactive virtual agent (avatar) system of claim 3 , wherein mapping misspelled words comprises mapping misspelled or incorrect words onto a basic form and mapping a basic form onto many variants. | 0.5 |
5,541,836 | 9 | 10 | 9. The method set forth in claim 8 wherein: there is a plurality of the word/sense pairs; the steps of obtaining the weights and summing the weights are performed for each word/sense pair; and the method includes the further step of selecting the word/sense pair having the summed weights which indicate the greatest likelihood that the sense of the word/sense pair is lexically appropriate to the given position. | 9. The method set forth in claim 8 wherein: there is a plurality of the word/sense pairs; the steps of obtaining the weights and summing the weights are performed for each word/sense pair; and the method includes the further step of selecting the word/sense pair having the summed weights which indicate the greatest likelihood that the sense of the word/sense pair is lexically appropriate to the given position. 10. The method set forth in claim 9 wherein the step of selecting the word/sense pair includes the step of: comparing the sense of the selected word/sense pair with the result of another word sense determination of a sense for the word in the word/sense pair which is lexically most appropriate at another position. | 0.5 |
7,657,522 | 10 | 11 | 10. A system for providing data based on object relevance via a computing device, the computing device having a processor coupled to a computer readable storage memory, the system comprising: a communications interface configured to receive ne or more query terms from a user; a ratings module in communication with the communications interface, the ratings module configured to determine a preliminary relevance of one or more objects associated with an enterprise system based on the query terms, to assign at least one rating to the one or more objects based on the preliminary relevance, and to establish an overall relevance of the one or more objects based on the at least one rating; a search results module in communication with the ratings module, the search results module configured to rank the one or more objects according to the overall relevance and to provide data as search results comprising the one or more objects according to the ranking to the user; a filtering engine configured to filter the search results based on a selected, dynamically generated filter; and a display configured to display the filtered search results that are based on the at least one selected, dynamically generated filter associated with the one or more objects. | 10. A system for providing data based on object relevance via a computing device, the computing device having a processor coupled to a computer readable storage memory, the system comprising: a communications interface configured to receive ne or more query terms from a user; a ratings module in communication with the communications interface, the ratings module configured to determine a preliminary relevance of one or more objects associated with an enterprise system based on the query terms, to assign at least one rating to the one or more objects based on the preliminary relevance, and to establish an overall relevance of the one or more objects based on the at least one rating; a search results module in communication with the ratings module, the search results module configured to rank the one or more objects according to the overall relevance and to provide data as search results comprising the one or more objects according to the ranking to the user; a filtering engine configured to filter the search results based on a selected, dynamically generated filter; and a display configured to display the filtered search results that are based on the at least one selected, dynamically generated filter associated with the one or more objects. 11. The system recited in claim 10 , wherein the filtering engine is further configured to filter the data according to one or more virtual domains. | 0.577143 |
8,983,958 | 1 | 19 | 1. An article of manufacture, comprising: a machine readable non-transient storage medium comprising instructions which when executed by the machine causes the machine to perform operations comprising: receiving one or more documents for indexing; based on a document type, a document size and processing priority, categorizing the one or more documents; assigning buckets to the categorized one or more documents according to the document type, the document size and the processing priority; calculating a document type priority for the document type of the one or more documents in the assigned buckets, wherein the document type priority is calculated as a function of an extraction efficiency for extracting content from the one or more documents for the corresponding document type; and based on the calculated document type priority, a bucket type and number of threads available to process the buckets, scheduling the buckets for indexing process. | 1. An article of manufacture, comprising: a machine readable non-transient storage medium comprising instructions which when executed by the machine causes the machine to perform operations comprising: receiving one or more documents for indexing; based on a document type, a document size and processing priority, categorizing the one or more documents; assigning buckets to the categorized one or more documents according to the document type, the document size and the processing priority; calculating a document type priority for the document type of the one or more documents in the assigned buckets, wherein the document type priority is calculated as a function of an extraction efficiency for extracting content from the one or more documents for the corresponding document type; and based on the calculated document type priority, a bucket type and number of threads available to process the buckets, scheduling the buckets for indexing process. 19. The article of manufacture in claim 1 , wherein the extraction efficiency is calculated as a ratio of a cumulative extraction time required for the one or more documents of a particular document type to a cumulative size of the one or more documents of that particular document type. | 0.697257 |
6,161,093 | 7 | 10 | 7. An information access system according to claim 6 wherein said central control means sends the speech recognition results from the central speech recognition means to the terminal. | 7. An information access system according to claim 6 wherein said central control means sends the speech recognition results from the central speech recognition means to the terminal. 10. An information access system according to claim 7 wherein the central speech recognition means confirms speech by dictation, the speech inputting means re-inputs speech when the speech recognition results from the central speech recognition means transmitted from the central control means are mistaken and the central speech recognition means recognizes speech which was re-inputted to the speech inputting means again, in accordance with the speech recognition results. | 0.503138 |
8,346,754 | 7 | 8 | 7. The method as recited in claim 5 , wherein the generation parameters for a given source include, a probability α s that the given source, when asked to construct a text instance, picks a word from a true title, and a probability β s that the given source, when asked to construct the text instance, picks a word from the context webpage. | 7. The method as recited in claim 5 , wherein the generation parameters for a given source include, a probability α s that the given source, when asked to construct a text instance, picks a word from a true title, and a probability β s that the given source, when asked to construct the text instance, picks a word from the context webpage. 8. The method as recited in claim 7 , wherein computing a likelihood further includes, calculating a word probability that a source generates a specific text instance as a sum of, α s multiplied by a number of times the specific text instance is in the true title divided by a size of the true title, β s multiplied by a number of times the specific text instance is in the context webpage divided by a size of the context webpage, and (1−α s −β s ) divided by a size of a vocabulary of all possible words. | 0.5 |
9,141,705 | 7 | 26 | 7. The system of claim 1 , wherein the indication of an applied filter is only displayed after a command is received from the user. | 7. The system of claim 1 , wherein the indication of an applied filter is only displayed after a command is received from the user. 26. The system of claim 7 , wherein the command comprises a voice command. | 0.614583 |
8,516,606 | 4 | 5 | 4. The computer-implemented method according to claim 1 , wherein the at least two character subsets are sent to the client as separate image files. | 4. The computer-implemented method according to claim 1 , wherein the at least two character subsets are sent to the client as separate image files. 5. The computer-implemented method according to claim 4 , wherein the separate image files comprise one or more of bitmap files, tagged image file format files, joint photographic experts group files, or graphics interchange format files. | 0.5 |
7,970,721 | 15 | 17 | 15. A method for analyzing objects of interest within a context comprising: controlling one or more processors configured with executable instructions for: projecting objects of interest onto a web graph to produce one or more sub graphs, wherein producing the sub graphs comprises: ordering sets of connected nodes by size; identifying a shortest path between a largest set of connected nodes, from among the ordered sets, to a second largest set of connected nodes, from among the ordered sets; adding, according to the shortest path, connection nodes and edges between the largest set of connected nodes and the second largest set of connected nodes; and repeating the step of identifying the shortest path and the step of adding connection nodes while more sets of nodes are available in the sets of connected nodes ordered by size; and making an inference related to at least one of the context or objects of interest based upon graphical properties of the one or more sub graphs. | 15. A method for analyzing objects of interest within a context comprising: controlling one or more processors configured with executable instructions for: projecting objects of interest onto a web graph to produce one or more sub graphs, wherein producing the sub graphs comprises: ordering sets of connected nodes by size; identifying a shortest path between a largest set of connected nodes, from among the ordered sets, to a second largest set of connected nodes, from among the ordered sets; adding, according to the shortest path, connection nodes and edges between the largest set of connected nodes and the second largest set of connected nodes; and repeating the step of identifying the shortest path and the step of adding connection nodes while more sets of nodes are available in the sets of connected nodes ordered by size; and making an inference related to at least one of the context or objects of interest based upon graphical properties of the one or more sub graphs. 17. The method of claim 15 , wherein projecting objects of interest onto the web graph comprises: identifying each node on the web graph that contains an object of interest; identifying each edge on the web graph between identified nodes; and copying each identified node and each identified edge onto a sub graph. | 0.5 |
7,917,841 | 11 | 16 | 11. A system for viewing information associated with data in a spreadsheet, comprising: memory operable to store at least one program; and at least one processor communicatively coupled to the memory, in which the at least one program, when executed by the at least one processor, causes the at least one processor to: provide a document including data and information associated with the data; parse the document to retrieve the associated information; process the associated information to break the associated information down into at least one sentence categorize the at least one sentence based on a likelihood that the at least one sentence corresponds to at least one category in a taxonomy corresponding to the data resulting in at least one categorized sentence; assign an association strength to the at least one categorized sentence, the association strength indicating the likelihood that the at least one categorized sentence corresponds to the at least one category in the taxonomy; filter the at least one categorized sentence based on the association strength; match one or more of the at least one categorized sentence with the at least one category in the taxonomy, based on the filter, resulting in an at least one categorized sentence matched with the at least on category in the taxonomy; and output only the at least one categorized sentence matched with the at least one category in the taxonomy to the spreadsheet. | 11. A system for viewing information associated with data in a spreadsheet, comprising: memory operable to store at least one program; and at least one processor communicatively coupled to the memory, in which the at least one program, when executed by the at least one processor, causes the at least one processor to: provide a document including data and information associated with the data; parse the document to retrieve the associated information; process the associated information to break the associated information down into at least one sentence categorize the at least one sentence based on a likelihood that the at least one sentence corresponds to at least one category in a taxonomy corresponding to the data resulting in at least one categorized sentence; assign an association strength to the at least one categorized sentence, the association strength indicating the likelihood that the at least one categorized sentence corresponds to the at least one category in the taxonomy; filter the at least one categorized sentence based on the association strength; match one or more of the at least one categorized sentence with the at least one category in the taxonomy, based on the filter, resulting in an at least one categorized sentence matched with the at least on category in the taxonomy; and output only the at least one categorized sentence matched with the at least one category in the taxonomy to the spreadsheet. 16. The system of claim 11 , wherein the filtering module comprises a “best match” type filter in which only a match with a highest association strength is output. | 0.604369 |
5,542,024 | 48 | 49 | 48. An information processing system as claimed in claim 47, wherein said second means includes an object oriented command module which responds to selections of options by the developer to generate command statements for said data base manager. | 48. An information processing system as claimed in claim 47, wherein said second means includes an object oriented command module which responds to selections of options by the developer to generate command statements for said data base manager. 49. The information processing system as claimed in claim 48, wherein said command statements include executable computer operating system commands. | 0.5 |
8,566,325 | 11 | 14 | 11. A non-transitory, tangible computer-readable storage medium on which computer readable instructions of a program are stored, the instructions, when executed by a processor, cause the processor to perform a method, the method comprising: accessing a database including a plurality of 3D models of objects, wherein each 3D model of an object of the plurality of 3D models of objects is associated with information defining a geographic area of a base polygon of the respective object; accessing map information including a plurality of points of interest, where each point of interest of the plurality of points of interest is associated with a geographic coordinate; selecting a 3D model of an object from the plurality of 3D models of objects; determining whether the geographic coordinate of a given point of interest of the plurality of points of interest is within the geographic area of the base polygon defined by the information associated with the selected 3D model of the object; when the geographic coordinate of a given point of interest of the plurality of points of interest is within the geographic area of the base polygon defined by the information associated with the selected 3D model of the object, creating, by the processor, a system tag including a search term selected based on the given point of interest; associating the system tag with the selected 3D model of an object; and storing the association in memory. | 11. A non-transitory, tangible computer-readable storage medium on which computer readable instructions of a program are stored, the instructions, when executed by a processor, cause the processor to perform a method, the method comprising: accessing a database including a plurality of 3D models of objects, wherein each 3D model of an object of the plurality of 3D models of objects is associated with information defining a geographic area of a base polygon of the respective object; accessing map information including a plurality of points of interest, where each point of interest of the plurality of points of interest is associated with a geographic coordinate; selecting a 3D model of an object from the plurality of 3D models of objects; determining whether the geographic coordinate of a given point of interest of the plurality of points of interest is within the geographic area of the base polygon defined by the information associated with the selected 3D model of the object; when the geographic coordinate of a given point of interest of the plurality of points of interest is within the geographic area of the base polygon defined by the information associated with the selected 3D model of the object, creating, by the processor, a system tag including a search term selected based on the given point of interest; associating the system tag with the selected 3D model of an object; and storing the association in memory. 14. The medium of claim 11 , wherein the search term is a title of the given point of interest. | 0.886091 |
10,062,104 | 10 | 13 | 10. A client machine system comprising: at least one processor and executable instructions accessible on a computer-readable medium that, when executed, cause the at least one processor to perform operations comprising: sending a connection request, from a seller application, to a network-based transaction facility, the seller application being customizable and being customized by receiving configuration information from the network-based transaction facility, the configuration information including a hierarchal product category structure for generating a listing for a product for sale; receiving, by the seller application, a current version of the configuration information from the network-based transaction facility; sending, by the seller application, configuration confirmation to the network-based transaction facility, the configuration confirmation indicating the seller application is configured using the current version of the configuration information including the hierarchal product category structure; and sending a request for a transaction listing, the transaction listing being generated based on the current version of the configuration information. | 10. A client machine system comprising: at least one processor and executable instructions accessible on a computer-readable medium that, when executed, cause the at least one processor to perform operations comprising: sending a connection request, from a seller application, to a network-based transaction facility, the seller application being customizable and being customized by receiving configuration information from the network-based transaction facility, the configuration information including a hierarchal product category structure for generating a listing for a product for sale; receiving, by the seller application, a current version of the configuration information from the network-based transaction facility; sending, by the seller application, configuration confirmation to the network-based transaction facility, the configuration confirmation indicating the seller application is configured using the current version of the configuration information including the hierarchal product category structure; and sending a request for a transaction listing, the transaction listing being generated based on the current version of the configuration information. 13. The system of claim 10 , wherein: the receiving the configuration information includes receiving the hierarchal product category structure, the configuration information being configured to enable a user of the seller application to classify a listing created by the user for publication by a network-based facility. | 0.559229 |
8,239,360 | 1 | 3 | 1. A content management system comprising: a content acquisition device that acquires content; and a management device that is communicably connected to the content acquisition device and that manages the content in a searchable manner, wherein the content acquisition device comprises: a first registration unit that registers new content in a search database; and a first search unit that searches content registered in the search database, and wherein the management device comprises: a second registration unit that operates in cooperation with the first registration unit; and a second search unit that operates in cooperation with the first search unit, wherein the first registration unit performs the following operations comprising: (1) transmitting the new content to the management device; (2) receiving a content ID for identifying the new content and a plurality of keyword candidates for searching the new content from the management device; (3) displaying the received keyword candidates; and (4) transmitting a keyword candidate designated from among the displayed keyword candidates and the content ID received by the operation (2) to the management device, wherein the second registration unit performs the following operations comprising: (a) receiving the new content from the content acquisition device; (b) generating the plurality of keyword candidates based on the received new content; (c) associating the received new content with the generated keyword candidates and generating the content ID for identifying the new content; (d) transmitting the content ID and the generated keyword candidates to the content acquisition device; (e) receiving the designated keyword candidate and the content ID from the content acquisition device, and (f) registering the designated keyword candidate as a search keyword in the search database in association with content identified by the content ID received through the operation (e), wherein the first search unit performs the following operations comprising: (5) issuing a search keyword request for searching registered content to the management device; (6) receiving a plurality of search keywords from the management device, (7) transmitting a search keyword designated from among the received search keywords to the management device; (8) receiving content associated with the designated search keyword from the management device, and (9) displaying the received content, and wherein the second search unit performs the following operations comprising: (g) transmitting the search keywords registered in the search database to the content acquisition device in response to the search keyword request from the content acquisition device; (h) extracting content associated with the designated search keyword from the search database; and (i) transmitting the extracted content to the content acquisition device. | 1. A content management system comprising: a content acquisition device that acquires content; and a management device that is communicably connected to the content acquisition device and that manages the content in a searchable manner, wherein the content acquisition device comprises: a first registration unit that registers new content in a search database; and a first search unit that searches content registered in the search database, and wherein the management device comprises: a second registration unit that operates in cooperation with the first registration unit; and a second search unit that operates in cooperation with the first search unit, wherein the first registration unit performs the following operations comprising: (1) transmitting the new content to the management device; (2) receiving a content ID for identifying the new content and a plurality of keyword candidates for searching the new content from the management device; (3) displaying the received keyword candidates; and (4) transmitting a keyword candidate designated from among the displayed keyword candidates and the content ID received by the operation (2) to the management device, wherein the second registration unit performs the following operations comprising: (a) receiving the new content from the content acquisition device; (b) generating the plurality of keyword candidates based on the received new content; (c) associating the received new content with the generated keyword candidates and generating the content ID for identifying the new content; (d) transmitting the content ID and the generated keyword candidates to the content acquisition device; (e) receiving the designated keyword candidate and the content ID from the content acquisition device, and (f) registering the designated keyword candidate as a search keyword in the search database in association with content identified by the content ID received through the operation (e), wherein the first search unit performs the following operations comprising: (5) issuing a search keyword request for searching registered content to the management device; (6) receiving a plurality of search keywords from the management device, (7) transmitting a search keyword designated from among the received search keywords to the management device; (8) receiving content associated with the designated search keyword from the management device, and (9) displaying the received content, and wherein the second search unit performs the following operations comprising: (g) transmitting the search keywords registered in the search database to the content acquisition device in response to the search keyword request from the content acquisition device; (h) extracting content associated with the designated search keyword from the search database; and (i) transmitting the extracted content to the content acquisition device. 3. The content management system according to claim 1 , wherein in (b), when the new content is image data, the second registration unit extracts a word from the image data by an optical character reader and uses the extracted word as a keyword candidate of the plurality of keyword candidates. | 0.759411 |
9,189,569 | 1 | 3 | 1. A non-transitory computer readable medium storing a program causing a computer to execute a process, the process comprising: searching a document memory, the document memory storing electronic documents of medical records of patients in association with document types of the electronic documents, for electronic documents associated with a patient specified by a user from among the patients; referring to group definition information that defines document groups and grouping the electronic documents obtained in the searching so as to create the document groups; and generating data of a search result display screen in which an icon associated with a corresponding one of the document groups created as a result of the grouping is arranged at a position of a schema, the position corresponding to a site of a human body associated with the document group, wherein in the generating, in the case where the document groups created as a result of the grouping include two or more document groups associated with the same site of the human body, an image of a schema in which two or more icons respectively associated with the two or more document groups associated with the same site are displayed so as to be superposed with each other at a position of the schema corresponding to the same site is generated and is displayed on the search result display screen, and upon a predetermined operation being accepted from the user in a state where a first icon among the two or more icons displayed so as to be superposed with each other at the same position is selected, the selected icon is switched from the first icon to a second icon among the two or more icons. | 1. A non-transitory computer readable medium storing a program causing a computer to execute a process, the process comprising: searching a document memory, the document memory storing electronic documents of medical records of patients in association with document types of the electronic documents, for electronic documents associated with a patient specified by a user from among the patients; referring to group definition information that defines document groups and grouping the electronic documents obtained in the searching so as to create the document groups; and generating data of a search result display screen in which an icon associated with a corresponding one of the document groups created as a result of the grouping is arranged at a position of a schema, the position corresponding to a site of a human body associated with the document group, wherein in the generating, in the case where the document groups created as a result of the grouping include two or more document groups associated with the same site of the human body, an image of a schema in which two or more icons respectively associated with the two or more document groups associated with the same site are displayed so as to be superposed with each other at a position of the schema corresponding to the same site is generated and is displayed on the search result display screen, and upon a predetermined operation being accepted from the user in a state where a first icon among the two or more icons displayed so as to be superposed with each other at the same position is selected, the selected icon is switched from the first icon to a second icon among the two or more icons. 3. The non-transitory computer readable medium according to claim 1 , wherein in the searching, an operation performed by the user to specify a reference electronic document that is used as a reference in a search is accepted, the content of the reference electronic document is analyzed, and in a case where the analyzed content is related to an inherited factor, another patient who is related to the specified patient by blood in a predetermined range is identified by referring to information about blood relations among the patients, and electronic documents of the specified patient and the other patient who has been identified, among the electronic documents stored in the document memory, are searched for electronic documents related to the reference electronic document. | 0.539505 |
7,607,081 | 1 | 3 | 1. A method for representing header and footer structures in a markup language document, comprising: determining properties corresponding to a mini-document of at least one section of a word processing application document generated on a word processing application, wherein the mini-document includes a body portion, wherein the mini-document includes at least one member of a group comprising: a header and a footer; individually mapping the properties of the mini-document into a markup language element that is stored with each of the markup language section properties of the application document, wherein individually mapping the properties includes: setting an option element in the mini-document markup language element, wherein the option element includes at least one member of a group comprising: a header value and a footer value, setting a type attribute in the mini-document markup language element, wherein the type attribute includes a value that indicates an occurrence pattern of the body of the mini-document within the application document, setting page size properties of the application document in the section properties of the application document, wherein the page size properties includes a size value of the page, and setting a margin properties of the application document in the section properties of the application document, wherein the margin properties include a top margin value, a bottom margin value, a left margin value, a right margin value and a position value of the location of the mini-document within the section of the application document; storing each of the individually mapped properties of the mini-document in the markup language document; validating the markup language document in accordance with a native schema of the word processing application having definitions for the mini-document, wherein the definitions for the mini-document include a definition for headers, a definition for footers, a definition for a context free chunk, a definition for a paragraph element, a definition for a table element and a definition for a mini-document type; and parsing and rendering the markup language document on an application other than the word processing application, wherein the application other than the word processing application does not have access to the native schema of the word processing application having the definitions of the mini-document, wherein the individually mapped option element in the section properties causes the rendering of at least one member of a group comprising, a header according to the header value for the section, and a footer according to the footer value for the section, wherein the individually mapped type attribute in the section properties causes the body portion of the mini-document to be rendered in accordance with the occurrence pattern of the section, wherein the value is at least one member of a group comprising: an odd page value for the section and an even page value for the section, wherein the individually mapped page size properties for the section causes the page to be rendered according to the size value of the page of the section, and wherein the individually mapped margin properties for the section causes the rendering of a top margin according to the top margin value, a bottom margin according to the bottom margin value, a left margin according to the left margin value, a right margin according to a right margin value and a mini-document position according to the position value of the location of the mini-document within the section. | 1. A method for representing header and footer structures in a markup language document, comprising: determining properties corresponding to a mini-document of at least one section of a word processing application document generated on a word processing application, wherein the mini-document includes a body portion, wherein the mini-document includes at least one member of a group comprising: a header and a footer; individually mapping the properties of the mini-document into a markup language element that is stored with each of the markup language section properties of the application document, wherein individually mapping the properties includes: setting an option element in the mini-document markup language element, wherein the option element includes at least one member of a group comprising: a header value and a footer value, setting a type attribute in the mini-document markup language element, wherein the type attribute includes a value that indicates an occurrence pattern of the body of the mini-document within the application document, setting page size properties of the application document in the section properties of the application document, wherein the page size properties includes a size value of the page, and setting a margin properties of the application document in the section properties of the application document, wherein the margin properties include a top margin value, a bottom margin value, a left margin value, a right margin value and a position value of the location of the mini-document within the section of the application document; storing each of the individually mapped properties of the mini-document in the markup language document; validating the markup language document in accordance with a native schema of the word processing application having definitions for the mini-document, wherein the definitions for the mini-document include a definition for headers, a definition for footers, a definition for a context free chunk, a definition for a paragraph element, a definition for a table element and a definition for a mini-document type; and parsing and rendering the markup language document on an application other than the word processing application, wherein the application other than the word processing application does not have access to the native schema of the word processing application having the definitions of the mini-document, wherein the individually mapped option element in the section properties causes the rendering of at least one member of a group comprising, a header according to the header value for the section, and a footer according to the footer value for the section, wherein the individually mapped type attribute in the section properties causes the body portion of the mini-document to be rendered in accordance with the occurrence pattern of the section, wherein the value is at least one member of a group comprising: an odd page value for the section and an even page value for the section, wherein the individually mapped page size properties for the section causes the page to be rendered according to the size value of the page of the section, and wherein the individually mapped margin properties for the section causes the rendering of a top margin according to the top margin value, a bottom margin according to the bottom margin value, a left margin according to the left margin value, a right margin according to a right margin value and a mini-document position according to the position value of the location of the mini-document within the section. 3. The method of claim 1 , further comprising: determining whether properties associated with all mini-documents of the application document have been stored in the markup language document; and processing further mini-documents when the properties associated with all mini-documents have not been stored in the markup language document. | 0.666337 |
8,488,877 | 2 | 3 | 2. A system as set forth in claim 1 , wherein the object recognition block further comprises: a search module, the search module configured to perform a local search for objects using cues from the visual attention cueing block and the geometric grammar block to generate candidate regions of interest (ROIs); and a statistical classifier block, the statistical classifier block being, configured to, within the candidate ROIs, implement multiple machine learning based object classifiers using geometric features generated by the implicit geometry engine, the statistical classifier block further configured to classify the 3D object of interest as a particular object upon the output of the object classifiers reaching a predetermined threshold. | 2. A system as set forth in claim 1 , wherein the object recognition block further comprises: a search module, the search module configured to perform a local search for objects using cues from the visual attention cueing block and the geometric grammar block to generate candidate regions of interest (ROIs); and a statistical classifier block, the statistical classifier block being, configured to, within the candidate ROIs, implement multiple machine learning based object classifiers using geometric features generated by the implicit geometry engine, the statistical classifier block further configured to classify the 3D object of interest as a particular object upon the output of the object classifiers reaching a predetermined threshold. 3. A system as set forth in claim 2 , wherein the implicit geometry engine is further configured to receive the 3D colorized point cloud data and process the 3D colorized point cloud data along separate 2D and 3D pathways, such that in the 3D pathway, the 3D colorized point cloud data is converted into implicit representations, while in the 2D pathway, color information in the 3D colorized cloud point data is projected into 2D representations for cueing and recognition of potential objects. | 0.5 |
9,792,086 | 1 | 9 | 1. A method comprising: constructing, via a processor device, a media interconnection graph which models how media are interconnected by connecting disparate categories of the media; weighting the media interconnection graph based on a popularity of the media, to yield a weighted graph; normalizing the weighted graph, to yield a normalized weighted graph; generating, via the processor device, a speech recognition model based on the normalized weighted graph; receiving audible speech for searching media content; and converting the audible speech to output a graph using the speech recognition model. | 1. A method comprising: constructing, via a processor device, a media interconnection graph which models how media are interconnected by connecting disparate categories of the media; weighting the media interconnection graph based on a popularity of the media, to yield a weighted graph; normalizing the weighted graph, to yield a normalized weighted graph; generating, via the processor device, a speech recognition model based on the normalized weighted graph; receiving audible speech for searching media content; and converting the audible speech to output a graph using the speech recognition model. 9. The method of claim 1 , wherein the media interconnection graph models relative respective popularity of each piece of the media. | 0.635359 |
9,588,999 | 1 | 6 | 1. A method for reclaiming database storage, the method comprising: retrieving, by a computer, a list of data elements for deletion from a database catalog, wherein the list of data elements for deletion details one or more data elements contained in a database; determining, by the computer, whether first data elements of the one or more data elements on the list of data elements for deletion have been active in one or more static Structured Query Language (SQL) statements, wherein the one or more static SQL statements are persistent and created before runtime; removing, by the computer, the first data elements of the one or more data elements from the list of data elements for deletion that have been determined to be active in the one or more static SQL statements; determining, by the computer, whether second data elements of the one or more data elements on the list of data elements for deletion have been active in one or more dynamic SQL statements, wherein the one or more dynamic SQL statements are non-persistent and created at runtime; removing, by the computer, the second data elements of the one or more data elements from the list of data elements for deletion that have been determined to be active in the one or more dynamic SQL statements; determining, by the computer, whether third data elements of the one or more data elements on the list of data elements for deletion are associated with one or more data elements not on the list of data elements for deletion; removing, by the computer, the third data elements of the one or more data elements from the list of data elements for deletion that are determined to be associated with the one or more data elements not on the list of data elements for deletion; determining, by the computer, whether fourth data elements of the one or more data elements on the list of data elements for deletion are used in a source code of one or more applications; and removing, by the computer, the fourth data elements of the one or more data elements from the list of data elements for deletion that are determined to be used in the source code of the one or more applications. | 1. A method for reclaiming database storage, the method comprising: retrieving, by a computer, a list of data elements for deletion from a database catalog, wherein the list of data elements for deletion details one or more data elements contained in a database; determining, by the computer, whether first data elements of the one or more data elements on the list of data elements for deletion have been active in one or more static Structured Query Language (SQL) statements, wherein the one or more static SQL statements are persistent and created before runtime; removing, by the computer, the first data elements of the one or more data elements from the list of data elements for deletion that have been determined to be active in the one or more static SQL statements; determining, by the computer, whether second data elements of the one or more data elements on the list of data elements for deletion have been active in one or more dynamic SQL statements, wherein the one or more dynamic SQL statements are non-persistent and created at runtime; removing, by the computer, the second data elements of the one or more data elements from the list of data elements for deletion that have been determined to be active in the one or more dynamic SQL statements; determining, by the computer, whether third data elements of the one or more data elements on the list of data elements for deletion are associated with one or more data elements not on the list of data elements for deletion; removing, by the computer, the third data elements of the one or more data elements from the list of data elements for deletion that are determined to be associated with the one or more data elements not on the list of data elements for deletion; determining, by the computer, whether fourth data elements of the one or more data elements on the list of data elements for deletion are used in a source code of one or more applications; and removing, by the computer, the fourth data elements of the one or more data elements from the list of data elements for deletion that are determined to be used in the source code of the one or more applications. 6. The method of claim 1 , wherein the determining whether the fourth data elements of the one or more data elements on the list of data elements for deletion are used in the source code of the one or more applications includes analyzing one or more application source codes and workload logic in order to extract the one or more SQL statements and cross reference the extracted one or more SQL statements with the one or more data elements on the list of data elements for deletion. | 0.540875 |
9,984,147 | 13 | 20 | 13. A method of clustering a plurality of objects, having object types, object attributes, homogeneous relationships between objects of the same object type, and heterogeneous relationships between objects having different object types which do not comply with an independent and identically distributed (IID) statistical presumption, the method comprising: optimizing an object clustering of the plurality of objects in a plurality of latent object classes based on at least the object types, object attributes, homogeneous relationships, and heterogeneous relationships, by iteratively: updating a set of posteriors to maximize an expectation probability that an object is associated with a respective latent object class comprising, iteratively maximizing an objective function for each respective object while an assigned latent object class for all other objects is fixed, until no object changes in assigned latent object class occurs, and maximizing an objective function for the respective object, comprising minimizing a computed distance between an observation of the object attributes, homogeneous relationships, and heterogeneous relationships of a respective object and parameters of the corresponding expectation probability, and repeating until no object changes in assigned latent object class occurs, and updating the plurality of latent object classes based on the updated set of posteriors; and at least one of: communicating a latent object class associated with an object, communicating a set of objects within a latent object class, and responding to a query based on the optimized object clustering. | 13. A method of clustering a plurality of objects, having object types, object attributes, homogeneous relationships between objects of the same object type, and heterogeneous relationships between objects having different object types which do not comply with an independent and identically distributed (IID) statistical presumption, the method comprising: optimizing an object clustering of the plurality of objects in a plurality of latent object classes based on at least the object types, object attributes, homogeneous relationships, and heterogeneous relationships, by iteratively: updating a set of posteriors to maximize an expectation probability that an object is associated with a respective latent object class comprising, iteratively maximizing an objective function for each respective object while an assigned latent object class for all other objects is fixed, until no object changes in assigned latent object class occurs, and maximizing an objective function for the respective object, comprising minimizing a computed distance between an observation of the object attributes, homogeneous relationships, and heterogeneous relationships of a respective object and parameters of the corresponding expectation probability, and repeating until no object changes in assigned latent object class occurs, and updating the plurality of latent object classes based on the updated set of posteriors; and at least one of: communicating a latent object class associated with an object, communicating a set of objects within a latent object class, and responding to a query based on the optimized object clustering. 20. The method according to claim 13 , wherein the object attributes, homogeneous relationships between objects of the same object type, and heterogeneous relationships between objects having different object types each have a statistical distribution independently selected from a normal distribution, a Bernoulli distribution, a multinomial distribution and an exponential distribution. | 0.5 |
9,858,347 | 6 | 8 | 6. A non-transitory computer-readable medium having information recorded thereon for providing translated web content, wherein the information, when read by a computer, causes the computer to perform the following: receiving a request, via a public network connection, from an online user for content in a second language to be translated from content in a first language; obtaining, upon receiving the request, the content in the first language from an Internet source that hosts the content in the first language; dividing the obtained content in the first language into a plurality of translatable components; determining with respect to at least some of the plurality of translatable components, whether there is a corresponding translated component previously stored; determining, with respect to each of the translatable components that does not have a corresponding translated component previously stored, whether it is to be translated into the second language via machine translation; translating, via machine translation, each translatable component determined to be translated via machine translation; scheduling for human post-editing of the translation of each translatable component translated via machine translation; generating the content in the second language using the machine translated translatable components and the human post-edited translatable components; and providing the content in the second language to the user based on a condition associated with the translated content being satisfied. | 6. A non-transitory computer-readable medium having information recorded thereon for providing translated web content, wherein the information, when read by a computer, causes the computer to perform the following: receiving a request, via a public network connection, from an online user for content in a second language to be translated from content in a first language; obtaining, upon receiving the request, the content in the first language from an Internet source that hosts the content in the first language; dividing the obtained content in the first language into a plurality of translatable components; determining with respect to at least some of the plurality of translatable components, whether there is a corresponding translated component previously stored; determining, with respect to each of the translatable components that does not have a corresponding translated component previously stored, whether it is to be translated into the second language via machine translation; translating, via machine translation, each translatable component determined to be translated via machine translation; scheduling for human post-editing of the translation of each translatable component translated via machine translation; generating the content in the second language using the machine translated translatable components and the human post-edited translatable components; and providing the content in the second language to the user based on a condition associated with the translated content being satisfied. 8. The medium of claim 6 , wherein the information, when read by the computer, causes the computer to further perform the following: scheduling for human post-editing one or more of the machine translated translatable components. | 0.591071 |
8,732,194 | 10 | 13 | 10. A computer-implemented system for generating an issue library from a document corpus, wherein documents within the document corpus are linked by citations, thereby forming a citation network, the computer-implemented system comprising a processor and a non-transitory computer-readable medium storing one or more library metadata entities and computer readable instructions that, when executed by the processor, cause the processor to: semantically link documents within the document corpus to pair reasons-for-citing in citing documents with cited-text-areas in cited documents, wherein a cited-text-area in a cited document is a text area that has a highest semantic similarity value of text present within the cited document; determine reasons-for-citing and cited-text-areas that are semantically similar to at least one issue to thereby group similar documents and reasons-for-citing by issue; group semantically-similar reasons-for-citing and cited-text-areas that are semantically similar to the at least one issue; and store information regarding groups of semantically-similar reasons-for-citing and cited-text-areas in a plurality of issue library metadata entities, wherein each issue library metadata entity is associated with an individual issue, and each issue library metadata entity comprises: an issue identifier corresponding to the at least one issue; at least one taxonomy topic under which the issue identifier is located; and a plurality of issue instances under the at least one taxonomy topic, wherein each issue instance comprises a reason-for-citing or a cited-text-area in a document, each reason-for-citing or cited-text-area being semantically similar to one another and associated with the issue identifier. | 10. A computer-implemented system for generating an issue library from a document corpus, wherein documents within the document corpus are linked by citations, thereby forming a citation network, the computer-implemented system comprising a processor and a non-transitory computer-readable medium storing one or more library metadata entities and computer readable instructions that, when executed by the processor, cause the processor to: semantically link documents within the document corpus to pair reasons-for-citing in citing documents with cited-text-areas in cited documents, wherein a cited-text-area in a cited document is a text area that has a highest semantic similarity value of text present within the cited document; determine reasons-for-citing and cited-text-areas that are semantically similar to at least one issue to thereby group similar documents and reasons-for-citing by issue; group semantically-similar reasons-for-citing and cited-text-areas that are semantically similar to the at least one issue; and store information regarding groups of semantically-similar reasons-for-citing and cited-text-areas in a plurality of issue library metadata entities, wherein each issue library metadata entity is associated with an individual issue, and each issue library metadata entity comprises: an issue identifier corresponding to the at least one issue; at least one taxonomy topic under which the issue identifier is located; and a plurality of issue instances under the at least one taxonomy topic, wherein each issue instance comprises a reason-for-citing or a cited-text-area in a document, each reason-for-citing or cited-text-area being semantically similar to one another and associated with the issue identifier. 13. The computer-implemented system of claim 10 , wherein the computer readable instructions cause the processor to group semantically-similar reasons-for-citing and cited-text-areas that are semantically similar to the at least one issue by: performing a depth-first search in the citation network; and retrieving forward-chained and backward-chained reasons-for-citing and cited-text-areas that are semantically similar to the at least one issue. | 0.5 |
8,949,607 | 1 | 13 | 1. A method of verifying if a request for a second digital document originates from a reference within an authentic copy of a first digital document, the method comprising: a first computer sends the first digital document to a second computer via a computer network; the second computer receives a possibly tampered version of the first digital document via the computer network; the first computer computes a first authentication tag on at least a part of the first digital document; the second computer computes a second authentication tag on at least a part of the possibly tampered version of the first digital document; the second computer sends the request for the second digital document referenced in the possibly tampered version of the first digital document to the first computer via the computer network, the request including the second authentication tag; the first computer receives a possibly tampered version of the request and deducts the second authentication tag; the first computer considers the possibly tampered version of the request as originating from an authentic copy of the first digital document if the second authentication tag is equal to the first authentication tag; and the first computer causes the second document to be sent to the second computer only if the second authentication tag is equal to the first authentication tag. | 1. A method of verifying if a request for a second digital document originates from a reference within an authentic copy of a first digital document, the method comprising: a first computer sends the first digital document to a second computer via a computer network; the second computer receives a possibly tampered version of the first digital document via the computer network; the first computer computes a first authentication tag on at least a part of the first digital document; the second computer computes a second authentication tag on at least a part of the possibly tampered version of the first digital document; the second computer sends the request for the second digital document referenced in the possibly tampered version of the first digital document to the first computer via the computer network, the request including the second authentication tag; the first computer receives a possibly tampered version of the request and deducts the second authentication tag; the first computer considers the possibly tampered version of the request as originating from an authentic copy of the first digital document if the second authentication tag is equal to the first authentication tag; and the first computer causes the second document to be sent to the second computer only if the second authentication tag is equal to the first authentication tag. 13. The method according to claim 1 where an authentication tag that authenticates at least some of the data in the first digital document is also provided in the first digital document itself. | 0.887266 |
5,491,628 | 8 | 10 | 8. The method of claim 1, wherein the step of specifying a second extended attribute grammar comprises the steps of: specifying a vocabulary of the second extended attribute grammar; and specifying at least one production of the second extended attribute grammar. | 8. The method of claim 1, wherein the step of specifying a second extended attribute grammar comprises the steps of: specifying a vocabulary of the second extended attribute grammar; and specifying at least one production of the second extended attribute grammar. 10. The method of claim 8, wherein the step of specifying the vocabulary of the second extended attribute grammar comprises the steps of: specifying a plurality of symbols; specifying at least one logical attribute for each symbol; and specifying at least one non-logical attribute for each symbol. | 0.5 |
8,918,308 | 5 | 6 | 5. The method of claim 4 , wherein the search results are in the target language. | 5. The method of claim 4 , wherein the search results are in the target language. 6. The method of claim 5 , further comprising translating the search results, received from the Internet search engine, from the target language to the source language. | 0.5 |
9,965,548 | 1 | 5 | 1. A method, in a data processing system comprising a processor and a memory configured to implement a question and answer system (QA), for improving answers to an input question, the method comprising: receiving, in the data processing system, the input question; processing, by the data processing system, the input question to generate at least one query; extracting, by the data processing system, one or more selections of evidence portions from a corpus of information which match the at least one query; generating, by the data processing system, one or more candidate answers based on the one or more selections of evidence portions; for at least one candidate answer in the one or more candidate answers, determining, by the data processing system, whether there are one or more missing or ambiguous pieces of information that would refine an inclusion or exclusion of the candidate answer in the one or more candidate answers; outputting, by the data processing system, the one or more candidate answers, the one or more missing or ambiguous pieces of information that would refine the inclusion or exclusion of the candidate answer in the one or more candidate answers, and the selections of evidence portions for evaluation by the user; outputting, by the data processing system, one or more pieces of criteria that identifies conditions met by each candidate answer in the one or more candidate answers in relation to the input question; generating, by the data processing system, one or more confidence scores for each of the one or more candidate answers by applying one or more reasoning algorithms to language of the input question and language of the one or more candidate answers; comparing, by the data processing system, results of each of the one or more reasoning algorithms to a statistical model; based on the comparison of the results to the statistical model, modifying, by the data processing system, the statistical model; applying, by the data processing system, statistical weights to confidence scores associated with each of the one or more reasoning algorithms in accordance with the statistical model; and synthesizing, by the data processing system, the one or more confidence scores for each of the one or more candidate answers, thereby creating a one or more final answers. | 1. A method, in a data processing system comprising a processor and a memory configured to implement a question and answer system (QA), for improving answers to an input question, the method comprising: receiving, in the data processing system, the input question; processing, by the data processing system, the input question to generate at least one query; extracting, by the data processing system, one or more selections of evidence portions from a corpus of information which match the at least one query; generating, by the data processing system, one or more candidate answers based on the one or more selections of evidence portions; for at least one candidate answer in the one or more candidate answers, determining, by the data processing system, whether there are one or more missing or ambiguous pieces of information that would refine an inclusion or exclusion of the candidate answer in the one or more candidate answers; outputting, by the data processing system, the one or more candidate answers, the one or more missing or ambiguous pieces of information that would refine the inclusion or exclusion of the candidate answer in the one or more candidate answers, and the selections of evidence portions for evaluation by the user; outputting, by the data processing system, one or more pieces of criteria that identifies conditions met by each candidate answer in the one or more candidate answers in relation to the input question; generating, by the data processing system, one or more confidence scores for each of the one or more candidate answers by applying one or more reasoning algorithms to language of the input question and language of the one or more candidate answers; comparing, by the data processing system, results of each of the one or more reasoning algorithms to a statistical model; based on the comparison of the results to the statistical model, modifying, by the data processing system, the statistical model; applying, by the data processing system, statistical weights to confidence scores associated with each of the one or more reasoning algorithms in accordance with the statistical model; and synthesizing, by the data processing system, the one or more confidence scores for each of the one or more candidate answers, thereby creating a one or more final answers. 5. The method of claim 1 , wherein the one or more candidate answers are organized based on the confidence scores associated with the at least one candidate answer and the one or more missing or ambiguous pieces of information associated with the candidate answer, and wherein the organization of the one or more candidate answers is modified based on the user providing input that provides or clarifies the one or more missing or ambiguous pieces of information. | 0.895201 |
7,630,880 | 3 | 4 | 3. A machine readable medium containing executable program instructions which cause, when executed, a digital processing system to perform a method comprising: receiving a source character string including a source substring; and converting the source character string to a target character string including a target substring using a first dictionary and a second dictionary different from the first dictionary, wherein the conversion using the second dictionary is used to form the target character string when the first dictionary fails to convert the source character string, and wherein the first and the second dictionaries are updated to include the target substring corresponding to the source substring when the first dictionary fails to convert the source character string. | 3. A machine readable medium containing executable program instructions which cause, when executed, a digital processing system to perform a method comprising: receiving a source character string including a source substring; and converting the source character string to a target character string including a target substring using a first dictionary and a second dictionary different from the first dictionary, wherein the conversion using the second dictionary is used to form the target character string when the first dictionary fails to convert the source character string, and wherein the first and the second dictionaries are updated to include the target substring corresponding to the source substring when the first dictionary fails to convert the source character string. 4. A medium as in claim 3 wherein the second dictionary is a virtual dictionary. | 0.591837 |
8,762,318 | 22 | 24 | 22. The non-transitory computer-readable medium of claim 21 , the behavior of the user is determined using the user's web page interaction data and the trained model is trained using other users' web page interaction data, the instructions further comprising instructions to: generate an incremental user scoring vector using the current item and an item cluster membership vector for the item in the trained model, the item cluster membership vector identifying the item's cluster score for each cluster identified in the trained model, the item's cluster score comprising a probability that the item belongs to the cluster; and generate the short-term cluster membership vector using the incremental user scoring vector. | 22. The non-transitory computer-readable medium of claim 21 , the behavior of the user is determined using the user's web page interaction data and the trained model is trained using other users' web page interaction data, the instructions further comprising instructions to: generate an incremental user scoring vector using the current item and an item cluster membership vector for the item in the trained model, the item cluster membership vector identifying the item's cluster score for each cluster identified in the trained model, the item's cluster score comprising a probability that the item belongs to the cluster; and generate the short-term cluster membership vector using the incremental user scoring vector. 24. The non-transitory computer-readable medium of claim 22 , the instructions to generate the plurality of scores further comprising instructions to: determine, for each item of the plurality of scored items, a product for each cluster association of the item, the product being determined using the item's cluster score and the probability that the user belongs to the cluster; and aggregate the plurality of products. | 0.5 |
9,965,649 | 5 | 8 | 5. The computer device for protecting user data privacy of claim 1 , wherein said set of computer software functional components further comprise: a user application component wherein said user application component is configured to send both said user Intended Query and said Camouflage Queries. | 5. The computer device for protecting user data privacy of claim 1 , wherein said set of computer software functional components further comprise: a user application component wherein said user application component is configured to send both said user Intended Query and said Camouflage Queries. 8. The computer device for protecting user data privacy of claim 5 , wherein said user application component is a toolbar of web browser's or plug-in application to a third party web browse. | 0.520202 |
9,361,587 | 5 | 8 | 5. The method as claimed in claim 4 , further comprising: correcting for linguistic variations amongst statements representing said probabilistic dependence relations. | 5. The method as claimed in claim 4 , further comprising: correcting for linguistic variations amongst statements representing said probabilistic dependence relations. 8. The method as claimed in claim 5 , further comprising: applying transformational rules to map said extracted statements including said probabilistic dependence information to a canonical form. | 0.5 |
8,326,601 | 8 | 10 | 8. A method implemented on a machine that provides multilingual capabilities for text based chat rooms, comprising: receiving, by one or more servers, a message from a first client; ascertaining that the message is written in a first language; temporarily persisting, using the one or more servers, the message in a first queue such that the message is monitored periodically to be dispatched for translation, the first queue being specific to the first language; translating, using the one or more servers, the first language of the message into a second language; and supplying, using the one or more servers, the message in the second language to a second queue for subsequent delivery to a second client, the second queue being specific to the second language. | 8. A method implemented on a machine that provides multilingual capabilities for text based chat rooms, comprising: receiving, by one or more servers, a message from a first client; ascertaining that the message is written in a first language; temporarily persisting, using the one or more servers, the message in a first queue such that the message is monitored periodically to be dispatched for translation, the first queue being specific to the first language; translating, using the one or more servers, the first language of the message into a second language; and supplying, using the one or more servers, the message in the second language to a second queue for subsequent delivery to a second client, the second queue being specific to the second language. 10. The method of claim 8 , further comprising transcribing the message from the first language to the second language utilizing one or more intermediary languages. | 0.707143 |
9,450,771 | 14 | 38 | 14. A non-transitory computer-readable medium having stored contents that configure a computing system to perform a method, the method comprising: analyzing, by the configured computing system, a plurality of textual comments being supplied by human users during a prior time period and being related to a plurality of topics that are each mentioned in contents of one or more of the plurality of textual comments and that are identified from the analyzing; generating, by the configured computing system, a plurality of comment groups based on the identified topics, each of the generated comment groups being associated with one of the identified topics and including one or more of the plurality of textual comments that have contents mentioning the associated identified topic; determining, by the configured computing system, multiple terms of interest that are distinct from the plurality of topics, and assigning each of the multiple terms to one of multiple graph axes; determining, by the configured computing system, and for each of at least some of the plurality of topics, a relevance of one of the generated comment groups associated with the topic to the multiple terms based at least in part on the textual comments included in the one generated comment group; providing, by the configured computing system, information to initiate display of a multi-dimensional graph that includes the multiple graph axes and that includes visual indicators for multiple of the at least some topics on the multi-dimensional graph, wherein a position of each of the multiple topics on the displayed multi-dimensional graph is based on the determined relevance of the one generated comment group associated with the topic to the multiple terms and is based on the assignment of the multiple terms to the multiple graph axes, to enable a visual determination from the displayed multi-dimensional graph of relative relevance of the multiple topics to the multiple terms; identifying, by the configured computing system, a subset of the plurality of textual comments that are associated with a specified content category based on contents of the textual comments of the identified subset, the textual comments of the identified subset being included in multiple of the generated comment groups; determining, by the configured computing system, a subset of the multiple generated comment groups that correspond to the specified content category for the prior time period; discovering, by the configured computing system, additional content categories that are related to the specified content category, wherein each of the additional content categories corresponds to the topic of at least one of the determined subset of comment groups; and providing, by the configured computing system, indications of the determined additional content categories that are related to the specified content category. | 14. A non-transitory computer-readable medium having stored contents that configure a computing system to perform a method, the method comprising: analyzing, by the configured computing system, a plurality of textual comments being supplied by human users during a prior time period and being related to a plurality of topics that are each mentioned in contents of one or more of the plurality of textual comments and that are identified from the analyzing; generating, by the configured computing system, a plurality of comment groups based on the identified topics, each of the generated comment groups being associated with one of the identified topics and including one or more of the plurality of textual comments that have contents mentioning the associated identified topic; determining, by the configured computing system, multiple terms of interest that are distinct from the plurality of topics, and assigning each of the multiple terms to one of multiple graph axes; determining, by the configured computing system, and for each of at least some of the plurality of topics, a relevance of one of the generated comment groups associated with the topic to the multiple terms based at least in part on the textual comments included in the one generated comment group; providing, by the configured computing system, information to initiate display of a multi-dimensional graph that includes the multiple graph axes and that includes visual indicators for multiple of the at least some topics on the multi-dimensional graph, wherein a position of each of the multiple topics on the displayed multi-dimensional graph is based on the determined relevance of the one generated comment group associated with the topic to the multiple terms and is based on the assignment of the multiple terms to the multiple graph axes, to enable a visual determination from the displayed multi-dimensional graph of relative relevance of the multiple topics to the multiple terms; identifying, by the configured computing system, a subset of the plurality of textual comments that are associated with a specified content category based on contents of the textual comments of the identified subset, the textual comments of the identified subset being included in multiple of the generated comment groups; determining, by the configured computing system, a subset of the multiple generated comment groups that correspond to the specified content category for the prior time period; discovering, by the configured computing system, additional content categories that are related to the specified content category, wherein each of the additional content categories corresponds to the topic of at least one of the determined subset of comment groups; and providing, by the configured computing system, indications of the determined additional content categories that are related to the specified content category. 38. The non-transitory computer-readable medium of claim 14 wherein the configured computing system is part of a group discussion analysis and prediction service, wherein the stored contents further configure the computing system to provide additional information from the group discussion analysis and prediction service to one or more advertisers that includes at least one of discovered additional content categories or determined attributes for two or more of the generated comment groups or information about determined terms of interest, and wherein the providing of the information includes providing promotional information from at least one advertiser in response to instructions from the at least one advertiser based on the provided additional information. | 0.541268 |
6,162,059 | 1 | 5 | 1. A problem solving skills development system using a tactile recognition language, comprising: a supporting board; a plurality of sliding pieces slidably disposed on said supporting board and arranged in a grid having positions, wherein at least one of said positions is an empty position and said sliding pieces adjacent each said empty position are slidable into said empty position, whereby said sliding pieces are movable to any of said positions by shifting appropriate ones of said sliding pieces; and a plurality of tactile recognition blocks for removably engaging said sliding pieces, each of said tactile recognition blocks having a tactilly recognizable region on a surface thereof, wherein said tactilly recognizable regions on said tactile recognition blocks are arranged into a predetermined pattern by shifting said appropriate ones of said sliding pieces. | 1. A problem solving skills development system using a tactile recognition language, comprising: a supporting board; a plurality of sliding pieces slidably disposed on said supporting board and arranged in a grid having positions, wherein at least one of said positions is an empty position and said sliding pieces adjacent each said empty position are slidable into said empty position, whereby said sliding pieces are movable to any of said positions by shifting appropriate ones of said sliding pieces; and a plurality of tactile recognition blocks for removably engaging said sliding pieces, each of said tactile recognition blocks having a tactilly recognizable region on a surface thereof, wherein said tactilly recognizable regions on said tactile recognition blocks are arranged into a predetermined pattern by shifting said appropriate ones of said sliding pieces. 5. The problem solving skills development system of claim 1 wherein said sliding pieces include fifteen (15) sliding pieces arranged in a 4 by 4 grid having sixteen positions. | 0.662162 |
8,208,730 | 7 | 8 | 7. A word search apparatus comprising: a words dictionary for storing a plurality of entries of character strings; a character recognition dictionary for storing coordinate data of a standard character pattern of a character and a character corresponding to said coordinate data; and a character input device for receiving an input of a plurality of coordinate data of input characters; and a processor which performs the steps of: performing a pattern matching between the received coordinate data of input characters and said character recognition dictionary; performing character recognition on each input character, and extracting a plurality of candidate characters for each input character; forming a plurality of candidate strings by combining one of said plurality of candidate characters for each input character; searching, in said words dictionary, for entries containing at least one of said plurality of character strings; extracting the candidate strings contained in the entries found in said searching; displaying, in a partial character string display area, one of said extracted candidate strings and the candidate characters not present in said displayed candidate string for at least one of the characters in said displayed candidate string; receiving a selection of one candidate character among the candidate characters; reconstructing at least one candidate character string based on the selected candidate character and displaying at least the reconstructed candidate string in the partial character string display area; extracting words containing the reconstructed candidate string from the entries found in said searching; and displaying the extracted words in a search result display area. | 7. A word search apparatus comprising: a words dictionary for storing a plurality of entries of character strings; a character recognition dictionary for storing coordinate data of a standard character pattern of a character and a character corresponding to said coordinate data; and a character input device for receiving an input of a plurality of coordinate data of input characters; and a processor which performs the steps of: performing a pattern matching between the received coordinate data of input characters and said character recognition dictionary; performing character recognition on each input character, and extracting a plurality of candidate characters for each input character; forming a plurality of candidate strings by combining one of said plurality of candidate characters for each input character; searching, in said words dictionary, for entries containing at least one of said plurality of character strings; extracting the candidate strings contained in the entries found in said searching; displaying, in a partial character string display area, one of said extracted candidate strings and the candidate characters not present in said displayed candidate string for at least one of the characters in said displayed candidate string; receiving a selection of one candidate character among the candidate characters; reconstructing at least one candidate character string based on the selected candidate character and displaying at least the reconstructed candidate string in the partial character string display area; extracting words containing the reconstructed candidate string from the entries found in said searching; and displaying the extracted words in a search result display area. 8. The word search apparatus according to claim 7 , wherein said processor further performs the steps of: counting the number of entries found in said searching; and determining whether or not said number of counted entries is larger than a predetermined value, wherein only when it is determined that the number of counted entries is larger than the predetermined value, said candidate strings are extracted, while when it is determined that the number of counted entries is not larger than the predetermined value, a selection from the entries found in said searching is received. | 0.5 |
9,602,336 | 1 | 3 | 1. A computer-implemented method, comprising: receiving, from a networking device at a network management computer, a Simple Network Management Protocol (SNMP) notification comprising a columnar varbind that includes one or more varbind indices and corresponding one or more index values and in response thereto automatically performing: using event processing logic at the network management computer, decoding the one or more varbind indices into corresponding one or more index textual names based on compiled Management Information Base (MIB) data that comprises information from one or more MIB definition files that define the one or more varbind indices and the corresponding one or more index textual names; using the event processing logic, retrieving one or more event descriptions from network management system event configuration data; using the event processing logic, comparing the one or more MIB defined index textual names from the compiled MIB data to one or more substitution variables in the one or more event descriptions to identify, from the one or more MIB defined index textual names, a MIB defined index textual name that corresponds to a substitution variable from the one or more substitution variables in the one or more event descriptions; using the event processing logic, based on comparing the one or more MIB defined index textual names from the compiled MIB data to the one or more substitution variables in the one or more event descriptions, replacing the substitution variable with a particular value based on a varbind index value of the one or more varbind index values from the received SNMP notification, wherein the varbind index value corresponds to a varbind index which corresponds to the identified MIB defined index textual name from the compiled MIB data; using the event processing logic, constructing a message based on the one or more event descriptions and the particular value that replaced the substitution variable in the one or more event descriptions. | 1. A computer-implemented method, comprising: receiving, from a networking device at a network management computer, a Simple Network Management Protocol (SNMP) notification comprising a columnar varbind that includes one or more varbind indices and corresponding one or more index values and in response thereto automatically performing: using event processing logic at the network management computer, decoding the one or more varbind indices into corresponding one or more index textual names based on compiled Management Information Base (MIB) data that comprises information from one or more MIB definition files that define the one or more varbind indices and the corresponding one or more index textual names; using the event processing logic, retrieving one or more event descriptions from network management system event configuration data; using the event processing logic, comparing the one or more MIB defined index textual names from the compiled MIB data to one or more substitution variables in the one or more event descriptions to identify, from the one or more MIB defined index textual names, a MIB defined index textual name that corresponds to a substitution variable from the one or more substitution variables in the one or more event descriptions; using the event processing logic, based on comparing the one or more MIB defined index textual names from the compiled MIB data to the one or more substitution variables in the one or more event descriptions, replacing the substitution variable with a particular value based on a varbind index value of the one or more varbind index values from the received SNMP notification, wherein the varbind index value corresponds to a varbind index which corresponds to the identified MIB defined index textual name from the compiled MIB data; using the event processing logic, constructing a message based on the one or more event descriptions and the particular value that replaced the substitution variable in the one or more event descriptions. 3. The method of claim 1 wherein the compiled MIB data comprises at least one of: an allowable index range of the one or more varbind indices, an implied index encoding of the one or more varbind indices, or an index type of the one or more varbind indices. | 0.907421 |
8,751,218 | 1 | 4 | 1. A semantic tagging method that outputs semantically linked tags for text content comprising: inputting the text content to a computer; by the computer, extracting nouns and noun phrases from the text content; by the computer, mapping the extracted nouns and noun phrases to terms of an ontology; by the computer, mapping the extracted nouns and noun phrases to a correct sense of the ontology terms using lexical chaining Word Sense Disambiguation (WSD) algorithms; by the computer, weighting the extracted nouns' and noun phrases' concepts from their ontological and statistical features; by the computer, extracting key-phrases from the weighted concepts; and by the computer, outputting the key-phrases as semantic tags; wherein mapping the extracted nouns and noun phrases to terms of an ontology further comprises: accessing the ontology; comparing the nouns and noun phrases with the ontology terms; and if there is an exact match, retrieving the ontology term, and if there is not an exact match, performing phrase mapping using a rule based algorithm; and wherein the phrase mapping rule based algorithm further comprises: generating two sub phrases by removing the first and last word from the noun phrases and replacing the original noun phrases with the two sub phrases; and repeating the phrase mapping until there is a match or there are no more noun phrases remaining. | 1. A semantic tagging method that outputs semantically linked tags for text content comprising: inputting the text content to a computer; by the computer, extracting nouns and noun phrases from the text content; by the computer, mapping the extracted nouns and noun phrases to terms of an ontology; by the computer, mapping the extracted nouns and noun phrases to a correct sense of the ontology terms using lexical chaining Word Sense Disambiguation (WSD) algorithms; by the computer, weighting the extracted nouns' and noun phrases' concepts from their ontological and statistical features; by the computer, extracting key-phrases from the weighted concepts; and by the computer, outputting the key-phrases as semantic tags; wherein mapping the extracted nouns and noun phrases to terms of an ontology further comprises: accessing the ontology; comparing the nouns and noun phrases with the ontology terms; and if there is an exact match, retrieving the ontology term, and if there is not an exact match, performing phrase mapping using a rule based algorithm; and wherein the phrase mapping rule based algorithm further comprises: generating two sub phrases by removing the first and last word from the noun phrases and replacing the original noun phrases with the two sub phrases; and repeating the phrase mapping until there is a match or there are no more noun phrases remaining. 4. The method according to claim 1 wherein extracting nouns and noun phrases from the text content further comprises using a Natural Language Processing (NLP) Application Programming Interface (API). | 0.859463 |
9,128,927 | 13 | 19 | 13. A device comprising: a network interface; a processor coupled to the network interface; and a memory coupled to the processor and containing a plurality of instructions for execution by the processor, the instructions including instructions for: identifying that a first endpoint running on the device is associated with a first spoken language in an ongoing communication session with a second endpoint and a third endpoint via a bridge, the second endpoint is associate with a second spoken language, and the third endpoint is associated with a third spoken language; sending a request to the bridge for an inbound port and an outbound port to be provisioned on the bridge for the first endpoint; notifying a language translation component in the hybrid peer-to-peer network of the inbound port, wherein the language translation component is accessible to the first endpoint via the hybrid peer-to-peer network, and wherein the notifying instructs the language translation component to send audio received from the first endpoint to the inbound port; sending to the language translation component audio speech input received by the first endpoint from a user of the first endpoint, wherein the audio speech input sent by the first endpoint is in the first spoken language; and receiving audio speech originating from the second and third endpoints from the outbound port on the bridge, wherein the audio speech received by the first endpoint via the outbound port was sent to the bridge by the second and third endpoints in the second and third spoken languages, respectively, translated into the first spoken language, and then sent to the first endpoint in the first spoken language. | 13. A device comprising: a network interface; a processor coupled to the network interface; and a memory coupled to the processor and containing a plurality of instructions for execution by the processor, the instructions including instructions for: identifying that a first endpoint running on the device is associated with a first spoken language in an ongoing communication session with a second endpoint and a third endpoint via a bridge, the second endpoint is associate with a second spoken language, and the third endpoint is associated with a third spoken language; sending a request to the bridge for an inbound port and an outbound port to be provisioned on the bridge for the first endpoint; notifying a language translation component in the hybrid peer-to-peer network of the inbound port, wherein the language translation component is accessible to the first endpoint via the hybrid peer-to-peer network, and wherein the notifying instructs the language translation component to send audio received from the first endpoint to the inbound port; sending to the language translation component audio speech input received by the first endpoint from a user of the first endpoint, wherein the audio speech input sent by the first endpoint is in the first spoken language; and receiving audio speech originating from the second and third endpoints from the outbound port on the bridge, wherein the audio speech received by the first endpoint via the outbound port was sent to the bridge by the second and third endpoints in the second and third spoken languages, respectively, translated into the first spoken language, and then sent to the first endpoint in the first spoken language. 19. The device of claim 13 further comprising instructions for receiving notifications directly from each of the second and third endpoints of inbound and outbound ports corresponding to the second and third endpoints. | 0.605072 |
8,775,341 | 1 | 5 | 1. A method of processing information, comprising: receiving at least one message; processing the at least one message with an artificial neural network based processor, trained to respond to received information and produce at least one set of outputs which represent intelligent discriminations of information in at least one respective stage of cognitive development in a non-arbitrary organization of actions based on an architecture of the artificial neural network based processor and a training of the artificial neural network based processor; representing as a noise vector at least one data pattern in the at least one received message which is incompletely represented as the intelligent discriminations of information in the at least one set of outputs representing the non-arbitrary organization of actions; analyzing at least the noise vector distinctly from the artificial neural network based processor to extract characteristics of the at least one message distinct from the non-arbitrary organization of actions; and generating an output signal at least in dependence on said analyzing. | 1. A method of processing information, comprising: receiving at least one message; processing the at least one message with an artificial neural network based processor, trained to respond to received information and produce at least one set of outputs which represent intelligent discriminations of information in at least one respective stage of cognitive development in a non-arbitrary organization of actions based on an architecture of the artificial neural network based processor and a training of the artificial neural network based processor; representing as a noise vector at least one data pattern in the at least one received message which is incompletely represented as the intelligent discriminations of information in the at least one set of outputs representing the non-arbitrary organization of actions; analyzing at least the noise vector distinctly from the artificial neural network based processor to extract characteristics of the at least one message distinct from the non-arbitrary organization of actions; and generating an output signal at least in dependence on said analyzing. 5. The method according to claim 1 , wherein the intelligent discriminations of information represent a respective order/stage of human cognition. | 0.909988 |
9,552,815 | 4 | 5 | 4. The speech recognition system of claim 3 wherein the controller sends via the transmitter supplemental, non-verbal information based upon the determination that the audible speech has high recognition uncertainty. | 4. The speech recognition system of claim 3 wherein the controller sends via the transmitter supplemental, non-verbal information based upon the determination that the audible speech has high recognition uncertainty. 5. The mobile device of claim 4 wherein the supplemental, non-verbal information includes images of a mouth of a person who is speaking the audible speech. | 0.5 |
9,910,887 | 1 | 2 | 1. A method comprising, by one or more computing devices: receiving, from a client system of a first user of an online social network, a search query input comprising a character string having a first number of characters; accessing one or more verticals, each vertical being external to the client system and storing one or more objects of a particular object-type of a plurality of object types associated with the online social network, wherein: if the first number is less than or equal to a first threshold number, then accessing one or more first verticals, wherein each first vertical stores objects of a first object-type; and if the first number is greater than the first threshold number, then accessing the one or more first verticals and one or more second verticals, wherein each second vertical stores objects of a second object-type different than the first object-type; searching each accessed vertical to identify one or more objects associated with the vertical that substantially match the character string; and sending, to the client system of the first user, one or more references to one or more of the identified objects, respectively. | 1. A method comprising, by one or more computing devices: receiving, from a client system of a first user of an online social network, a search query input comprising a character string having a first number of characters; accessing one or more verticals, each vertical being external to the client system and storing one or more objects of a particular object-type of a plurality of object types associated with the online social network, wherein: if the first number is less than or equal to a first threshold number, then accessing one or more first verticals, wherein each first vertical stores objects of a first object-type; and if the first number is greater than the first threshold number, then accessing the one or more first verticals and one or more second verticals, wherein each second vertical stores objects of a second object-type different than the first object-type; searching each accessed vertical to identify one or more objects associated with the vertical that substantially match the character string; and sending, to the client system of the first user, one or more references to one or more of the identified objects, respectively. 2. The method of claim 1 , wherein accessing one or more verticals further comprises: if the first number is greater than a second threshold number, then accessing the one or more first verticals, the one or more second verticals, and one or more third verticals, wherein each third vertical stores objects of a third object-type different than the first and second object-types, and wherein the second threshold number is greater than the first threshold number. | 0.5 |
7,672,844 | 17 | 21 | 17. A voice processing apparatus as set forth in claim 16 , wherein: speaker data stored in said voiceprint data memory means corresponds to each of said plurality of unidirectional microphones; and said data processing means processes the voice signal collected by said selected one microphone based on comparing first speaker data obtained by comparing voiceprint data stored in the voiceprint data memory means with second speaker data corresponding to said selected one microphone. | 17. A voice processing apparatus as set forth in claim 16 , wherein: speaker data stored in said voiceprint data memory means corresponds to each of said plurality of unidirectional microphones; and said data processing means processes the voice signal collected by said selected one microphone based on comparing first speaker data obtained by comparing voiceprint data stored in the voiceprint data memory means with second speaker data corresponding to said selected one microphone. 21. A voice processing apparatus as set forth in claim 17 , further comprising a voice conversion means for converting a voice signal to character string data, wherein said voice conversion means converts the voice signal collected by said selected one microphone into character string data; and said data processing means processes said character string data by associating the speaker data therewith, the speaker data being obtained by comparison with said voice signal. | 0.5 |
7,505,894 | 1 | 2 | 1. A computer-implemented method of assigning a score to an ordering of a target language dependency structure given a source language dependency structure and an alignment between nodes in the source language dependency structure and nodes in the target language dependency structure, the method comprising: receiving a source language dependency structure indicative of a source language text fragment and a target language dependency structure; assigning a score to the order of dependent nodes, depending directly from a parent node, in the target language dependency structure; and wherein the target language dependency structure comprises a target language dependency tree and the source language dependency structure has nodes aligned with nodes in the target language dependency tree, and wherein assigning a score comprises: computing a metric indicative of a probability that a selected node in the target language dependency tree has changed from one of a pre or post modifier of its parent node to become another of the pre or post modifier of its parent node in the target language dependency tree given that a node in the source language dependency structure aligned to the selected node in the target language dependency tree was a pre or post modifier of its parent node in the source language dependency structure; and providing an output to a component of a machine translation system based on the assigned score. | 1. A computer-implemented method of assigning a score to an ordering of a target language dependency structure given a source language dependency structure and an alignment between nodes in the source language dependency structure and nodes in the target language dependency structure, the method comprising: receiving a source language dependency structure indicative of a source language text fragment and a target language dependency structure; assigning a score to the order of dependent nodes, depending directly from a parent node, in the target language dependency structure; and wherein the target language dependency structure comprises a target language dependency tree and the source language dependency structure has nodes aligned with nodes in the target language dependency tree, and wherein assigning a score comprises: computing a metric indicative of a probability that a selected node in the target language dependency tree has changed from one of a pre or post modifier of its parent node to become another of the pre or post modifier of its parent node in the target language dependency tree given that a node in the source language dependency structure aligned to the selected node in the target language dependency tree was a pre or post modifier of its parent node in the source language dependency structure; and providing an output to a component of a machine translation system based on the assigned score. 2. The method of claim 1 wherein the target language dependency structure includes a plurality of parent nodes and wherein assigning a score to the order of dependent nodes comprises: assigning a score to the order of dependent nodes depending directly from each of the plurality of parent nodes in the target language dependency structure. | 0.674952 |
9,600,806 | 1 | 12 | 1. A computer-implemented method, comprising: analyzing electronic messages of a first user with respect to one or more features associated with the electronic messages; associating descriptive tags with the electronic messages of the first user based on the analyzing; and performing tasks with respect to the electronic messages of the first user, on behalf of the first user, based on the descriptive tags associated with the respective electronic messages; wherein the associating descriptive tags with the electronic messages of the first user includes learning electronic message tagging rules based one or more of a statistical machine learning technique and a parser, and associating the descriptive tags with the electronic messages of the first user based on features associated with the electronic messages and the learned electronic message tagging rules. | 1. A computer-implemented method, comprising: analyzing electronic messages of a first user with respect to one or more features associated with the electronic messages; associating descriptive tags with the electronic messages of the first user based on the analyzing; and performing tasks with respect to the electronic messages of the first user, on behalf of the first user, based on the descriptive tags associated with the respective electronic messages; wherein the associating descriptive tags with the electronic messages of the first user includes learning electronic message tagging rules based one or more of a statistical machine learning technique and a parser, and associating the descriptive tags with the electronic messages of the first user based on features associated with the electronic messages and the learned electronic message tagging rules. 12. The method of claim 1 , further including: hosting a user-programmable electronic messaging client; and performing the analyzing and the performing within the hosted user-programmable electronic messaging client. | 0.890467 |
4,797,811 | 3 | 4 | 3. A numerical control device as claimed in claim 2, wherein said control means determines whether high level language processing is being effected according to the state of a high level language processing flag within said control means. | 3. A numerical control device as claimed in claim 2, wherein said control means determines whether high level language processing is being effected according to the state of a high level language processing flag within said control means. 4. A numerical control device as claimed in claim 3, wherein said determining means in said language discriminating means determine whether said inputted machining program input comprises said high level language end delimiter instruction only when said high level language processing is being effected. | 0.5 |
9,292,366 | 1 | 4 | 1. A method for processing electronic documents, said method comprising: a processor displaying a first electronic document, said displaying comprising displaying first text appearing in the first electronic document; said processor obtaining, from a web page differing from the first electronic document, both selected text and an address of a source electronic document that comprises the selected text; said processor copying a first tag, a second tag, and the obtained address of the source into a header of a temporary computer object, wherein the first tag marks the beginning of the header and the second tag marks the end of the header, and wherein the address of the source electronic document is disposed between the first tag and the second tag in the header; said processor copying the obtained selected text into the temporary computer object; said processor copying the third tag into the temporary computer object, wherein the third tag marks the end of the temporary computer object, and wherein the selected text is disposed between the header of the temporary computer object and the third tag; said processor storing the temporary computer object in a second electronic document after the first text; after said storing the temporary computer object, said processor ascertaining that a portion of text is removed from the selected text or is inserted in the selected text; in response to said ascertaining: said processor inserting the third tag at a first position where the portion of text is removed or at a second position preceding a third position where the portion of text is inserted; and said processor inserting a string at the first position where the portion of text is removed or at the second position preceding the third position where the portion of text is inserted, wherein the string is a concatenation of the first tag, an address associated to the selected text, and the second tag. | 1. A method for processing electronic documents, said method comprising: a processor displaying a first electronic document, said displaying comprising displaying first text appearing in the first electronic document; said processor obtaining, from a web page differing from the first electronic document, both selected text and an address of a source electronic document that comprises the selected text; said processor copying a first tag, a second tag, and the obtained address of the source into a header of a temporary computer object, wherein the first tag marks the beginning of the header and the second tag marks the end of the header, and wherein the address of the source electronic document is disposed between the first tag and the second tag in the header; said processor copying the obtained selected text into the temporary computer object; said processor copying the third tag into the temporary computer object, wherein the third tag marks the end of the temporary computer object, and wherein the selected text is disposed between the header of the temporary computer object and the third tag; said processor storing the temporary computer object in a second electronic document after the first text; after said storing the temporary computer object, said processor ascertaining that a portion of text is removed from the selected text or is inserted in the selected text; in response to said ascertaining: said processor inserting the third tag at a first position where the portion of text is removed or at a second position preceding a third position where the portion of text is inserted; and said processor inserting a string at the first position where the portion of text is removed or at the second position preceding the third position where the portion of text is inserted, wherein the string is a concatenation of the first tag, an address associated to the selected text, and the second tag. 4. The method of claim 1 , wherein the header consists of the first tag, the address of the first electronic document, and the second tag. | 0.884808 |
9,594,542 | 1 | 5 | 1. A system for a dynamically evolving cognitive architecture based on training by third party developers, the system comprising: one or more processors; and a non-transitory computer readable medium storing a plurality of instructions, which when executed, cause the one or more processors to: receive a span of natural language annotated with an annotating object from a third-party developer, the annotating object comprising one of an input action object, an output action object, an input concept object, an intermediate concept object, another intermediate concept object and an output concept object; match a first object and a second object with a user input, the first object comprising one of the input action object, the output action object, the input concept object, the intermediate concept object, the other intermediate concept object and the output concept object, the second object comprising another one of the input action object, the output action object, the input concept object, the intermediate concept object, the other intermediate concept object and the output concept object; form an intent based on the user input; create a plan based on the intent and the annotated span of natural language, the plan comprising the input action object selected from a plurality of action objects that transforms the input concept object associated with the intent into the intermediate concept object, and the output action object selected from the plurality of action objects that transforms the other intermediate concept object into the output concept object associated with a goal of the intent, the other intermediate concept object comprising one of a same object as the intermediate concept object and a different object from the intermediate concept object; execute the plan; and output a value associated with the output concept object associated with the user input. | 1. A system for a dynamically evolving cognitive architecture based on training by third party developers, the system comprising: one or more processors; and a non-transitory computer readable medium storing a plurality of instructions, which when executed, cause the one or more processors to: receive a span of natural language annotated with an annotating object from a third-party developer, the annotating object comprising one of an input action object, an output action object, an input concept object, an intermediate concept object, another intermediate concept object and an output concept object; match a first object and a second object with a user input, the first object comprising one of the input action object, the output action object, the input concept object, the intermediate concept object, the other intermediate concept object and the output concept object, the second object comprising another one of the input action object, the output action object, the input concept object, the intermediate concept object, the other intermediate concept object and the output concept object; form an intent based on the user input; create a plan based on the intent and the annotated span of natural language, the plan comprising the input action object selected from a plurality of action objects that transforms the input concept object associated with the intent into the intermediate concept object, and the output action object selected from the plurality of action objects that transforms the other intermediate concept object into the output concept object associated with a goal of the intent, the other intermediate concept object comprising one of a same object as the intermediate concept object and a different object from the intermediate concept object; execute the plan; and output a value associated with the output concept object associated with the user input. 5. The system of claim 1 , wherein the plurality of instructions, when executed, will further cause the one or more processors to: create a second plan based on the intent, wherein the second plan differs from the first plan by at least one concept object and by at least one action object; and select the plan for execution based on at least one of an action object cost, an action object quality, a number of planned action objects, and a confidence score associated with the annotated span of natural language. | 0.557759 |
9,372,905 | 1 | 2 | 1. A system, comprising: one or more devices configured to: determine metadata information associated with data included in a data structure; identify a category, associated with the data, based on the metadata information; present, for display, a user interface that allows a user to build a graphical query based on the category, the graphical query including a user-defined visual representation of a data structure query associated with the data, the user interface including one or more input elements that allow the user to build the graphical query, at least one input element of the one or more input elements being associated with information that identifies a group of categories including the category, and at least one other input element of the one or more input elements being associated with information that identifies one or more operators associated with filtering the data; receive information associated with the graphical query based on presenting the user interface, the information associated with the graphical query being received based on input provided via the user interface, and the information associated with the graphical query including information associated with the category; present, for display, the information associated with the graphical query by creating a visual tree, the visual tree including at least one representation of the category and at least one representation of an operator of the one or more operators; and provide, to a query device, the information associated with the graphical query to cause the query device to convert the graphical query into the data structure query, and without requiring the user to generate the data structure query. | 1. A system, comprising: one or more devices configured to: determine metadata information associated with data included in a data structure; identify a category, associated with the data, based on the metadata information; present, for display, a user interface that allows a user to build a graphical query based on the category, the graphical query including a user-defined visual representation of a data structure query associated with the data, the user interface including one or more input elements that allow the user to build the graphical query, at least one input element of the one or more input elements being associated with information that identifies a group of categories including the category, and at least one other input element of the one or more input elements being associated with information that identifies one or more operators associated with filtering the data; receive information associated with the graphical query based on presenting the user interface, the information associated with the graphical query being received based on input provided via the user interface, and the information associated with the graphical query including information associated with the category; present, for display, the information associated with the graphical query by creating a visual tree, the visual tree including at least one representation of the category and at least one representation of an operator of the one or more operators; and provide, to a query device, the information associated with the graphical query to cause the query device to convert the graphical query into the data structure query, and without requiring the user to generate the data structure query. 2. The system of claim 1 , where the one or more devices are further configured to: store information associated with the category based on identifying the category; and where the one or more devices, when presenting, for display, the user interface that allows the user to build the graphical query based on the category, are configured to: present, within the user interface, the stored information associated with the category. | 0.5 |
9,632,985 | 77 | 78 | 77. The system of claim 74 , wherein the one or more interactive content presentation objects and one or more interactive assessment objects includes a manipulable image object. | 77. The system of claim 74 , wherein the one or more interactive content presentation objects and one or more interactive assessment objects includes a manipulable image object. 78. The system of claim 77 , wherein the one or more interactive content presentation objects and one or more interactive assessment objects includes a rotatatable manipulable image object. | 0.611111 |
9,412,367 | 29 | 30 | 29. The computerized information and display apparatus of claim 28 , wherein: the computerized information and display apparatus is further configured such that provision of the at least portion of the information can be invoked by application software present on the portable electronic device; and the at least portion of the information comprises a map image or map graphic of a geographic region, the map image or map graphic which is also viewable on the display device of the computerized information and display apparatus, the geographic region comprising a region that is local to a location of the computerized information and display apparatus. | 29. The computerized information and display apparatus of claim 28 , wherein: the computerized information and display apparatus is further configured such that provision of the at least portion of the information can be invoked by application software present on the portable electronic device; and the at least portion of the information comprises a map image or map graphic of a geographic region, the map image or map graphic which is also viewable on the display device of the computerized information and display apparatus, the geographic region comprising a region that is local to a location of the computerized information and display apparatus. 30. The computerized information and display apparatus of claim 29 , wherein the at least portion of the information comprises one or more telephone numbers for respective ones of one or more entities that are local to a location of the computerized information and display apparatus. | 0.650246 |
4,671,684 | 10 | 11 | 10. An electronic typewriter according to claim 9, wherein said storing means stores a word inputted after the depression of said release key, words for which the same spelling of word data exists in said dictionary memory and words whose spelling is regarded as correct by said pass means in said text memory. | 10. An electronic typewriter according to claim 9, wherein said storing means stores a word inputted after the depression of said release key, words for which the same spelling of word data exists in said dictionary memory and words whose spelling is regarded as correct by said pass means in said text memory. 11. An electronic typewriter according to claim 10, wherein said visible outputting means comprises displaying means for displaying a word stored in said working memory and comprising special displaying means controlled by said spelling check control means for specially displaying a misspelled word when said spelling check control means determines that word data corresponding to the spelling of said misspelled word does not exist. | 0.5 |
8,306,810 | 2 | 4 | 2. The system of claim 1 , wherein the user context language model engine further includes: logic to cause the processor to associate the one or more key words with each of one or more types of products/services; logic to cause the processor to identify user prior transaction information associated with products/services for each of the one or more users; and logic to cause the processor to generate a user prior transaction vocabulary of words, for each of the one or more users, from the key words associated with the corresponding user prior transaction information. | 2. The system of claim 1 , wherein the user context language model engine further includes: logic to cause the processor to associate the one or more key words with each of one or more types of products/services; logic to cause the processor to identify user prior transaction information associated with products/services for each of the one or more users; and logic to cause the processor to generate a user prior transaction vocabulary of words, for each of the one or more users, from the key words associated with the corresponding user prior transaction information. 4. The system of claim 2 , wherein the logic to identify user prior transaction information includes: logic to cause the processor to retrieve transaction information from a user wireless device storing transaction information. | 0.630293 |
9,195,661 | 12 | 14 | 12. The automated computer implemented method of claim 11 wherein the image document is a pdf document. | 12. The automated computer implemented method of claim 11 wherein the image document is a pdf document. 14. The automated computer implemented method of claim 12 wherein the pdf document is an image-pdf document. | 0.5 |
10,068,172 | 1 | 7 | 1. A non-transitory, machine readable storage manufacture having stored thereon computer program code for execution by a processor, the computer program code comprising: a graphical editor for building an expert system; and a player component configured to execute the expert system; the graphical editor comprising a page editor component configured to interactively build page entities of the expert system, wherein exactly one of the page entities is identified as a start page to be displayed when execution of the expert system is commenced, each page entity consisting of: one or more content sections and one or more interface sections, wherein each content section of the page entity is constrained to consist of non-interactive static blocks of informational content for display, without any executable elements or interactive elements, and each interface section comprising: at least one widget to acquire input data via a user interface device coupled to the processor, and at least one interface result entity, the interface result entity identifying at least one of (a) a destination page, and (b) one or more result conditions; and further identifying one or more specified actions which are to be performed only if the result conditions are true; the player component arranged to access the start page entity, display the content section of the start page entity, acquire the input data from the user interface device, based on the input data, update zero or more stored variables of the expert system; and then, access the interface result entity of the start page, test the result conditions based on current values of the stored variables, determine whether the result conditions are true, and if the result conditions are true, executing the actions specified in the interface result entity; if the interface result entity of the start page specifies a destination page entity, navigate to the destination page entity, display the content section of the destination page entity, acquire second input data from the user interface device, based on the second input data, update zero or more stored variables of the expert system; and repeat the steps of executing one page entity at a time of the expert system, navigating from each currently displayed page to a selected destination page as determined by analyzing the interface result entity of the currently displayed page; the graphical editor further including an export subsystem configured to convert the page entities into a portable format to export the expert system for use by an independently executable player system, wherein exported expert system is self-contained, meaning capable of execution without specialized tools, plugins, external programs or access to a knowledge base, as the subject matter expert knowledge for the expert system is captured and reflected in the page entities. | 1. A non-transitory, machine readable storage manufacture having stored thereon computer program code for execution by a processor, the computer program code comprising: a graphical editor for building an expert system; and a player component configured to execute the expert system; the graphical editor comprising a page editor component configured to interactively build page entities of the expert system, wherein exactly one of the page entities is identified as a start page to be displayed when execution of the expert system is commenced, each page entity consisting of: one or more content sections and one or more interface sections, wherein each content section of the page entity is constrained to consist of non-interactive static blocks of informational content for display, without any executable elements or interactive elements, and each interface section comprising: at least one widget to acquire input data via a user interface device coupled to the processor, and at least one interface result entity, the interface result entity identifying at least one of (a) a destination page, and (b) one or more result conditions; and further identifying one or more specified actions which are to be performed only if the result conditions are true; the player component arranged to access the start page entity, display the content section of the start page entity, acquire the input data from the user interface device, based on the input data, update zero or more stored variables of the expert system; and then, access the interface result entity of the start page, test the result conditions based on current values of the stored variables, determine whether the result conditions are true, and if the result conditions are true, executing the actions specified in the interface result entity; if the interface result entity of the start page specifies a destination page entity, navigate to the destination page entity, display the content section of the destination page entity, acquire second input data from the user interface device, based on the second input data, update zero or more stored variables of the expert system; and repeat the steps of executing one page entity at a time of the expert system, navigating from each currently displayed page to a selected destination page as determined by analyzing the interface result entity of the currently displayed page; the graphical editor further including an export subsystem configured to convert the page entities into a portable format to export the expert system for use by an independently executable player system, wherein exported expert system is self-contained, meaning capable of execution without specialized tools, plugins, external programs or access to a knowledge base, as the subject matter expert knowledge for the expert system is captured and reflected in the page entities. 7. The storage manufacture of claim 1 wherein a page entity stores a value for a stored variable in a content section. | 0.9375 |
9,015,150 | 11 | 15 | 11. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing devices, cause: receiving a request for data; identifying a group of results responsive to the request, each result in the group of results comprising values assigned to fields in a common set of fields; calculating relevance scores for the fields in the common set of fields; selecting from the common set of fields, based on a comparison of the relevance scores, a subset of highly relevant fields for the group of results, the subset of highly relevant fields being smaller than the common set of fields; generating, for each result in the group of results, a respective view of data in said each result, the view emphasizing data for the subset of highly relevant fields for the group of results; and generating a report comprising, for each result in the group of results, the respective view of data in said each result. | 11. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing devices, cause: receiving a request for data; identifying a group of results responsive to the request, each result in the group of results comprising values assigned to fields in a common set of fields; calculating relevance scores for the fields in the common set of fields; selecting from the common set of fields, based on a comparison of the relevance scores, a subset of highly relevant fields for the group of results, the subset of highly relevant fields being smaller than the common set of fields; generating, for each result in the group of results, a respective view of data in said each result, the view emphasizing data for the subset of highly relevant fields for the group of results; and generating a report comprising, for each result in the group of results, the respective view of data in said each result. 15. The one or more non-transitory computer-readable media of claim 11 , wherein a particular field in the common set of fields conforms to one or more constraints specified by particular metadata associated with the particular field; and wherein the relevance score for the particular field is based at least in part on a metadata score identified for the particular metadata. | 0.5 |
8,381,236 | 1 | 10 | 1. A method to execute one or more functions of a new service module on a document personalization production system, the method comprising: establishing communication between an application framework of the document personalization production system and the new service module, wherein the new service module is located on a server and the application framework is configured to integrate the new service module in the document personalization production system without reprogramming a production manager of the document personalization production system; registering a machine of the document personalization production system to the application framework by communicating a name, a capability, a control system, and a metadata to the application framework in order to execute the new service module and determining the machine's operating parameters to execute the one or more functions of the new service module; the application framework providing one or more interfaces to enable the production manager to issue instructions and data transmission for executing the one or more functions of the new service module without reprogramming the production manager; and the application framework providing one or more plugins to execute the one or more functions of the new service module in the document personalization production system. | 1. A method to execute one or more functions of a new service module on a document personalization production system, the method comprising: establishing communication between an application framework of the document personalization production system and the new service module, wherein the new service module is located on a server and the application framework is configured to integrate the new service module in the document personalization production system without reprogramming a production manager of the document personalization production system; registering a machine of the document personalization production system to the application framework by communicating a name, a capability, a control system, and a metadata to the application framework in order to execute the new service module and determining the machine's operating parameters to execute the one or more functions of the new service module; the application framework providing one or more interfaces to enable the production manager to issue instructions and data transmission for executing the one or more functions of the new service module without reprogramming the production manager; and the application framework providing one or more plugins to execute the one or more functions of the new service module in the document personalization production system. 10. The method to execute a new service module on a document personalization production system, as in claim 1 , wherein the new service module embeds an integrated circuit into a personalized document. | 0.7 |
8,131,874 | 4 | 5 | 4. The meta data customizing method as claimed in claim 1 , comprising: replacing the contents of the corresponding element of the description of the structured language designated by the meta data obtaining request, in the meta data, with the contents of another element corresponding to the designated format. | 4. The meta data customizing method as claimed in claim 1 , comprising: replacing the contents of the corresponding element of the description of the structured language designated by the meta data obtaining request, in the meta data, with the contents of another element corresponding to the designated format. 5. The meta data customizing method as claimed in claim 4 , comprising: replacing the contents of the corresponding element of the description of the structured language designated by the meta data obtaining request, in the meta data, with the contents of an extension tag corresponding to the variable of the format designation of the meta data obtaining request. | 0.5 |
7,596,559 | 7 | 9 | 7. A method of automated data integration comprising: establishing extensible markup language (XML) mappings between XML source schemas and an XML target schema, wherein said XML source schemas comprise data; and wherein said XML target schema comprises a set of constraints, said set of constraints comprising: data merging rules for integrating said data from multiple said XML source schemas comprising overlapping information; and nested equality-generating dependencies (NEGDs), said NEGDs comprising rules specifying that fields in two different data tuples must be merged; querying multiple XML source schemas through a common XML target schema, wherein said common XML target schema defines a set of terms and a structure that a target query refers to; rewriting said target query in terms of said XML source schemas based on said XML mappings; integrating said data based on said set of constraints; evaluating a union of a set of source queries, wherein said evaluating occurs at query run-time; and displaying results of said rewriting and said integrating to a user. | 7. A method of automated data integration comprising: establishing extensible markup language (XML) mappings between XML source schemas and an XML target schema, wherein said XML source schemas comprise data; and wherein said XML target schema comprises a set of constraints, said set of constraints comprising: data merging rules for integrating said data from multiple said XML source schemas comprising overlapping information; and nested equality-generating dependencies (NEGDs), said NEGDs comprising rules specifying that fields in two different data tuples must be merged; querying multiple XML source schemas through a common XML target schema, wherein said common XML target schema defines a set of terms and a structure that a target query refers to; rewriting said target query in terms of said XML source schemas based on said XML mappings; integrating said data based on said set of constraints; evaluating a union of a set of source queries, wherein said evaluating occurs at query run-time; and displaying results of said rewriting and said integrating to a user. 9. The method according to claim 7 , wherein said target query comprises an XML query (XQuery). | 0.737569 |
9,455,945 | 1 | 5 | 1. A method comprising: by one or more computers of a social-networking system, accessing a social graph of the social-networking system, the social graph comprising a plurality of nodes and edges connecting the nodes, the nodes comprising user nodes that are each associated with a particular user of the social-networking system; by the one or more computers of the social-networking system, determining, from the social graph, that a user “likes” a first page associated with a particular version of a media content; by the one or more computers of the social-networking system, determining that one or more other versions of the media content exist, wherein each of the one or more other versions of the media content has one or more associated pages; by the one or more computers of the social-networking system, determining that a main page is associated with the particular version and the one or more other versions of the media content; and by the one or more computers of the social-networking system, aggregating the user's “like” of the first page to the main page. | 1. A method comprising: by one or more computers of a social-networking system, accessing a social graph of the social-networking system, the social graph comprising a plurality of nodes and edges connecting the nodes, the nodes comprising user nodes that are each associated with a particular user of the social-networking system; by the one or more computers of the social-networking system, determining, from the social graph, that a user “likes” a first page associated with a particular version of a media content; by the one or more computers of the social-networking system, determining that one or more other versions of the media content exist, wherein each of the one or more other versions of the media content has one or more associated pages; by the one or more computers of the social-networking system, determining that a main page is associated with the particular version and the one or more other versions of the media content; and by the one or more computers of the social-networking system, aggregating the user's “like” of the first page to the main page. 5. The method of claim 1 , wherein the particular version and the one or more other versions comprise one or more of: an episode of a show; a season of the show; a series of the show; and a movie. | 0.715942 |
10,049,087 | 2 | 9 | 2. The apparatus of claim 1 , wherein the text selection context comprises elements selected from the group consisting of content-type, touchscreen device configuration, application type, application status, communication status, override policy parameters, and combinations thereof. | 2. The apparatus of claim 1 , wherein the text selection context comprises elements selected from the group consisting of content-type, touchscreen device configuration, application type, application status, communication status, override policy parameters, and combinations thereof. 9. The apparatus of claim 2 , the processor further parsing one or more content-types selected from the group consisting of names, phone numbers, numbers, addresses, languages, sentences, phrases, poetry, variable-length character groups, and combinations thereof. | 0.668342 |
9,348,499 | 1 | 10 | 1. A method for sharing information, the method comprising: at a first server of a first data system, receiving a request to send a copy of a document to a second server of a second data system; wherein the first data system comprises at least the first server and a first repository that is accessible to the first server, wherein the document comprises a reference to a first object that is stored outside of the document and within the first repository, the document further comprising one or more instructions configured to cause generation of one or more presented components of the document based on retrieving data that belongs to the first object; at the first server, based at least partially upon the retrieved data belonging to the first object, generating evidence data that describes one or more aspects of the first object; wherein the evidence data is not identical to the reference or the retrieved data; responsive to the request to send the copy of the document to the second server, the first server at the first data system sending, to the second server at the second data system, the copy of the document and the evidence data; wherein the method is performed by one or more computing devices. | 1. A method for sharing information, the method comprising: at a first server of a first data system, receiving a request to send a copy of a document to a second server of a second data system; wherein the first data system comprises at least the first server and a first repository that is accessible to the first server, wherein the document comprises a reference to a first object that is stored outside of the document and within the first repository, the document further comprising one or more instructions configured to cause generation of one or more presented components of the document based on retrieving data that belongs to the first object; at the first server, based at least partially upon the retrieved data belonging to the first object, generating evidence data that describes one or more aspects of the first object; wherein the evidence data is not identical to the reference or the retrieved data; responsive to the request to send the copy of the document to the second server, the first server at the first data system sending, to the second server at the second data system, the copy of the document and the evidence data; wherein the method is performed by one or more computing devices. 10. The method of claim 1 , wherein generating the evidence data occurs in response to determining that a copy of the first object is inaccessible to a recipient at the second data system. | 0.691803 |
7,716,162 | 9 | 14 | 9. A memory device containing programming instructions for execution by a processor, the memory device comprising: programming instructions for generating a plurality of histograms associated with a respective plurality of strings in a document by examining the document to locate strings for the respective plurality of strings by comparing strings in the document to a pre-existing plurality of strings for which histograms were previously generated, the histograms defining a geographical relevance of the plurality of strings with respect to geographical regions; programming instructions for combining the plurality of histograms to obtain a combined histogram for the document by multiplying together values for each histogram of the plurality of histograms; and programming instructions for determining a geographical relevance of the document based on the combined histogram. | 9. A memory device containing programming instructions for execution by a processor, the memory device comprising: programming instructions for generating a plurality of histograms associated with a respective plurality of strings in a document by examining the document to locate strings for the respective plurality of strings by comparing strings in the document to a pre-existing plurality of strings for which histograms were previously generated, the histograms defining a geographical relevance of the plurality of strings with respect to geographical regions; programming instructions for combining the plurality of histograms to obtain a combined histogram for the document by multiplying together values for each histogram of the plurality of histograms; and programming instructions for determining a geographical relevance of the document based on the combined histogram. 14. The memory device of claim 9 , where the document includes a search query. | 0.820276 |
9,560,152 | 11 | 15 | 11. A computer program product for generating a summary of an online communication session, the computer program product comprising: one or more computer readable storage medium(s) and program instructions stored on the one or more computer readable storage medium(s), the program instructions comprising: program instructions to receive a particular topic and summary information for each of one or more episodes of a current online communication session, and information regarding topics of interests for each member of a group of users, wherein content of the current online communication session is generated by members of the group of users; program instructions to receive a pictorial representation of the particular topic for the one or more episodes of the current online communication session, wherein determining the pictorial representation of each episode of the one or more episodes of the current online communication session is based on the particular topic of each episode; and program instructions to generate a summary of the current online communication session that is personalized for members of the group of users, wherein the program instructions to generate the summary that is personalized includes: program instructions to determine a level of interest in a first topic of a first episode and a second topic of a second episode, of the one or more episodes of the current online communication session, for a member of the group of users, based on one or a combination of: an amount of participation and contribution by the member of the group of users during the current online communication session, an amount of participation and contribution by the member of the group of users during previous online communication sessions that include the first topic, and interest preferences input by the member of the group of users; program instructions to list the summary and pictorial representation of the one or more episodes of the current online communication session in an order that corresponds to the level of interest in a first topic of a first episode and a second topic of a second episode, of the one or more episodes of the current online communication session held by the member of the group of users; and responsive to determining the level of interest held by the member of the group of users, for the first topic of the first episode of the one or more episodes, to be greater than the level of interest held by the member of the group of users for the second topic of the second episode of the one or more episodes, program instructions to provide a complete summary of the first topic of the first episode positioned before a condensed summary of the second topic of the second episode. | 11. A computer program product for generating a summary of an online communication session, the computer program product comprising: one or more computer readable storage medium(s) and program instructions stored on the one or more computer readable storage medium(s), the program instructions comprising: program instructions to receive a particular topic and summary information for each of one or more episodes of a current online communication session, and information regarding topics of interests for each member of a group of users, wherein content of the current online communication session is generated by members of the group of users; program instructions to receive a pictorial representation of the particular topic for the one or more episodes of the current online communication session, wherein determining the pictorial representation of each episode of the one or more episodes of the current online communication session is based on the particular topic of each episode; and program instructions to generate a summary of the current online communication session that is personalized for members of the group of users, wherein the program instructions to generate the summary that is personalized includes: program instructions to determine a level of interest in a first topic of a first episode and a second topic of a second episode, of the one or more episodes of the current online communication session, for a member of the group of users, based on one or a combination of: an amount of participation and contribution by the member of the group of users during the current online communication session, an amount of participation and contribution by the member of the group of users during previous online communication sessions that include the first topic, and interest preferences input by the member of the group of users; program instructions to list the summary and pictorial representation of the one or more episodes of the current online communication session in an order that corresponds to the level of interest in a first topic of a first episode and a second topic of a second episode, of the one or more episodes of the current online communication session held by the member of the group of users; and responsive to determining the level of interest held by the member of the group of users, for the first topic of the first episode of the one or more episodes, to be greater than the level of interest held by the member of the group of users for the second topic of the second episode of the one or more episodes, program instructions to provide a complete summary of the first topic of the first episode positioned before a condensed summary of the second topic of the second episode. 15. The computer program product of claim 11 , wherein a pictorial representation of the particular topic and the summary information of an episode of the one or more episodes of the online communication session is obtained by a graphical engine, based on the graphical engine receiving a topic and summary information from a cognitive engine that analyzes the content of the current online communication session. | 0.699855 |
8,001,064 | 7 | 8 | 7. The method of claim 1 , wherein at least one of the one or more profiles is a user profile that pertains to the user's general preferences that are not specifically associated with a search, and wherein at least one of the one or more profiles is a search profile that pertains to a particular query or query type not specifically associated with the user. | 7. The method of claim 1 , wherein at least one of the one or more profiles is a user profile that pertains to the user's general preferences that are not specifically associated with a search, and wherein at least one of the one or more profiles is a search profile that pertains to a particular query or query type not specifically associated with the user. 8. The method of claim 7 , further comprising combining the user profile and the search profile to create a biased profile, wherein weights in the search profile are biased by weights in the user profile using a biasing function. | 0.5 |
9,971,804 | 1 | 3 | 1. A method comprising: reading a plurality of entity population rules, each entity population rule describing a mapping from an input schema to an output schema, the output schema conforming to an entity declaration, the entity declaration describing an entity including at least one nested entity; compiling the plurality of entity population rules into at least one executable query, wherein compiling the plurality of entity population rules comprises topologically sorting the entities defined by the plurality of entity population rules based on at least one dependency among the plurality of entity population rules and generating a query by traversing from a leaf to a root of the topologically sorted entities; reading a plurality of input records from a first data store, the input records conforming to the input schema; applying a compiled entity resolution rule to the plurality of input records to determine a link between members of the plurality of input records; applying one of the plurality of entity population rules to the plurality of input records to create a plurality of output records complying with the output schema; subsequent to applying one of the plurality of entity population rules, recompiling the plurality of entity population rules; and populating an index of nested entities using the at least one executable query, the index complying with an index declaration, the index declaration describing an index of nested entities, and the index including the link. | 1. A method comprising: reading a plurality of entity population rules, each entity population rule describing a mapping from an input schema to an output schema, the output schema conforming to an entity declaration, the entity declaration describing an entity including at least one nested entity; compiling the plurality of entity population rules into at least one executable query, wherein compiling the plurality of entity population rules comprises topologically sorting the entities defined by the plurality of entity population rules based on at least one dependency among the plurality of entity population rules and generating a query by traversing from a leaf to a root of the topologically sorted entities; reading a plurality of input records from a first data store, the input records conforming to the input schema; applying a compiled entity resolution rule to the plurality of input records to determine a link between members of the plurality of input records; applying one of the plurality of entity population rules to the plurality of input records to create a plurality of output records complying with the output schema; subsequent to applying one of the plurality of entity population rules, recompiling the plurality of entity population rules; and populating an index of nested entities using the at least one executable query, the index complying with an index declaration, the index declaration describing an index of nested entities, and the index including the link. 3. The method of claim 1 , wherein the index of nested entities is shared between the plurality of entity population rules. | 0.89433 |
9,619,118 | 1 | 23 | 1. A computer-implemented method comprising: displaying, on a touchscreen of a user device, a first browse wheel having a circular shape and comprising a plurality of category regions within the first browse wheel, each category region associated with an application category and having a visual representation of the associated application category; receiving a user selection of an application category, the user selection of the application category comprising a touchscreen interaction with the first browse wheel; displaying, in response to the received user selection, a second browse wheel having a circular shape and comprising a plurality of subcategory regions within the second browse wheel, each subcategory region associated with an application subcategory of the selected application category and including a visual representation of the associated application subcategory, wherein a center of the second browse wheel is at a first location of the touchscreen; receiving a user selection of an application subcategory, the user selection of the application subcategory comprising a touchscreen interaction with the second browse wheel; generating, in response to the received user selection of the application subcategory, an application search query using the selected application category and the selected application subcategory; and in response to receiving search results corresponding to the application search query, displaying a search results interface, wherein displaying the search results interface includes: displaying the search results, wherein the search results include a set of applications; and displaying only a portion of the second browse wheel, wherein the portion of the second browse wheel (i) is centered at a second location of the touchscreen that is different than the first location, (ii) is less than an entirety of the second browse wheel, (iii) includes at least the subcategory region associated with the selected application subcategory, and (iv) is adjoining an edge of the touchscreen of the user device. | 1. A computer-implemented method comprising: displaying, on a touchscreen of a user device, a first browse wheel having a circular shape and comprising a plurality of category regions within the first browse wheel, each category region associated with an application category and having a visual representation of the associated application category; receiving a user selection of an application category, the user selection of the application category comprising a touchscreen interaction with the first browse wheel; displaying, in response to the received user selection, a second browse wheel having a circular shape and comprising a plurality of subcategory regions within the second browse wheel, each subcategory region associated with an application subcategory of the selected application category and including a visual representation of the associated application subcategory, wherein a center of the second browse wheel is at a first location of the touchscreen; receiving a user selection of an application subcategory, the user selection of the application subcategory comprising a touchscreen interaction with the second browse wheel; generating, in response to the received user selection of the application subcategory, an application search query using the selected application category and the selected application subcategory; and in response to receiving search results corresponding to the application search query, displaying a search results interface, wherein displaying the search results interface includes: displaying the search results, wherein the search results include a set of applications; and displaying only a portion of the second browse wheel, wherein the portion of the second browse wheel (i) is centered at a second location of the touchscreen that is different than the first location, (ii) is less than an entirety of the second browse wheel, (iii) includes at least the subcategory region associated with the selected application subcategory, and (iv) is adjoining an edge of the touchscreen of the user device. 23. The method of claim 1 wherein displaying the search results interface includes displaying a portion of the first browse wheel, wherein the portion of the first browse wheel (i) indicates the selected application category, (ii) is less than an entirety of the first browse wheel, and (iii) adjoins the edge of the touchscreen. | 0.5 |
8,868,408 | 34 | 35 | 34. A method, comprising: receiving, using one or more processors, a first plurality of offensive words, wherein each of the first plurality of offensive words is associated with a first offensiveness score; receiving, using one or more processors, a string of words; determining a distance measurement between a potentially offensive word in the string of words and an offensive word in the first plurality of offensive words, wherein the distance measurement is based on a spelling difference between the potentially offensive word and the offensive word in the first plurality of offensive words; determining an offensiveness score for the potentially offensive word based on the distance measurement and the first offensiveness score associated with the offensive word in the first plurality of offensive words; processing the string of words, using one or more processors to mitigate the potentially offensive word when the offensiveness score meets an offensiveness threshold value. | 34. A method, comprising: receiving, using one or more processors, a first plurality of offensive words, wherein each of the first plurality of offensive words is associated with a first offensiveness score; receiving, using one or more processors, a string of words; determining a distance measurement between a potentially offensive word in the string of words and an offensive word in the first plurality of offensive words, wherein the distance measurement is based on a spelling difference between the potentially offensive word and the offensive word in the first plurality of offensive words; determining an offensiveness score for the potentially offensive word based on the distance measurement and the first offensiveness score associated with the offensive word in the first plurality of offensive words; processing the string of words, using one or more processors to mitigate the potentially offensive word when the offensiveness score meets an offensiveness threshold value. 35. The method of claim 34 , wherein the offensiveness score is determined based on a product of the distance measurement and the first offensiveness score associated with the offensive word in the first plurality of offensive words. | 0.5 |
7,483,831 | 18 | 25 | 18. The method of claim 17 , wherein the process includes performing one or more frequency-wise gain adjustments on a prior candidate frequency-wise gain. | 18. The method of claim 17 , wherein the process includes performing one or more frequency-wise gain adjustments on a prior candidate frequency-wise gain. 25. The method of claim 18 , wherein the process includes selecting as a current candidate frequency-wise gain any of a current candidate frequency-wise gain and one or more prior candidate frequency-wise gains, where such selection is a function of which of such gains is associated with the highest intelligibility metric. | 0.5 |
7,669,112 | 1 | 16 | 1. A computer-implemented method of analyzing linguistic terms, the method comprising: (a) scanning a plurality of documents for variants of a linguistic term; and (b) tracking relative occurrences of a plurality of variants of the linguistic term found in the plurality of documents during scanning to determine an acceptable usage of the linguistic term, wherein each variant of the linguistic term found in each document is of the type that is intentionally chosen by an author of such document and wherein the acceptable usage is determined by the variant having the greatest frequency of occurrences among the plurality of variants. | 1. A computer-implemented method of analyzing linguistic terms, the method comprising: (a) scanning a plurality of documents for variants of a linguistic term; and (b) tracking relative occurrences of a plurality of variants of the linguistic term found in the plurality of documents during scanning to determine an acceptable usage of the linguistic term, wherein each variant of the linguistic term found in each document is of the type that is intentionally chosen by an author of such document and wherein the acceptable usage is determined by the variant having the greatest frequency of occurrences among the plurality of variants. 16. The method of claim 1 , wherein tracking relative occurrences of the plurality of variants includes weighting occurrences based upon locations of such occurrences within the plurality of documents. | 0.646127 |
8,892,990 | 18 | 19 | 18. The computer program product of claim 17 further comprises: receive a request to modify the table from the user device; generate a query in response to receiving the request; retrieve the at least one field image and the label image using the query; recreate the table based on the at least one field image and the label image; and provide the table for display to the user device. | 18. The computer program product of claim 17 further comprises: receive a request to modify the table from the user device; generate a query in response to receiving the request; retrieve the at least one field image and the label image using the query; recreate the table based on the at least one field image and the label image; and provide the table for display to the user device. 19. The computer program product of claim 18 , further comprising converting the column to symbolic representations and graphically changing at least one character in the symbolic representation. | 0.5 |
7,613,666 | 1 | 7 | 1. A method for generating an object-oriented model from a vocabulary, the method comprising the operations of: (a) receiving the vocabulary comprising terms and sentential forms, each of the terms comprising a word or phrase representing a concept, each of the sentential forms comprising a prepositional statement representing a fact type and including at least one placeholder, the placeholder being specified by a term; (b) automatically creating a first class for each of the terms in the vocabulary; (c) making a classification superclass to be a superclass for each of the first classes, wherein the classification superclass is a subclass of a fact superclass, wherein the fact superclass is a superclass whose instances are facts, such that each instance of the first class represents a fact that a thing is classified to be an instance of the concept represented by the corresponding term rather than representing an instance of the concept, and wherein the classification superclass is a superclass whose instances are classifications; (d) automatically creating a second class for each sentential form in the vocabulary; (e) making the fact superclass to be a superclass for each of the second classes, wherein the fact superclass is a superclass whose instances are facts, such that each instance of the second class represents a fact that is an instance of the fact type represented by the corresponding sentential form; and wherein acts (a)-(e) are performed so as to limit the granularity of encapsulation of information in each of the first classes and the second classes to no larger than the representation of a single fact. | 1. A method for generating an object-oriented model from a vocabulary, the method comprising the operations of: (a) receiving the vocabulary comprising terms and sentential forms, each of the terms comprising a word or phrase representing a concept, each of the sentential forms comprising a prepositional statement representing a fact type and including at least one placeholder, the placeholder being specified by a term; (b) automatically creating a first class for each of the terms in the vocabulary; (c) making a classification superclass to be a superclass for each of the first classes, wherein the classification superclass is a subclass of a fact superclass, wherein the fact superclass is a superclass whose instances are facts, such that each instance of the first class represents a fact that a thing is classified to be an instance of the concept represented by the corresponding term rather than representing an instance of the concept, and wherein the classification superclass is a superclass whose instances are classifications; (d) automatically creating a second class for each sentential form in the vocabulary; (e) making the fact superclass to be a superclass for each of the second classes, wherein the fact superclass is a superclass whose instances are facts, such that each instance of the second class represents a fact that is an instance of the fact type represented by the corresponding sentential form; and wherein acts (a)-(e) are performed so as to limit the granularity of encapsulation of information in each of the first classes and the second classes to no larger than the representation of a single fact. 7. The method of claim 1 further comprising: creating a thing superclass whose instances are representations of things; creating the fact superclass class whose instances are representations of facts; making the fact superclass to be a subclass of the thing superclass; creating the classification superclass whose instances are representations of classifications; making the classification superclass to be a subclass of the fact superclass; creating a text superclass whose instances are representations of texts; and making the text superclass to be a subclass of the thing superclass. | 0.5 |
6,092,034 | 19 | 32 | 19. A method for translating a series of source words in a first language to a series of target words in a second language, comprising the steps of: inputting the series of source words; generating at least one fertility hypotheses for a fertility of a source word, based on a source word and a context of the source word; generating sense hypotheses for a translation of the source word, based on the source word and the context of the source word; determining a probability of a fertility of a source word, based on the source word and the context of the source word; determining a probability of a target word being a correct translation of the source word, based on the source word and the context of the source word; and generating a list of target words for the translation of the source word, based on the probability of the fertility and the probability of the target word. | 19. A method for translating a series of source words in a first language to a series of target words in a second language, comprising the steps of: inputting the series of source words; generating at least one fertility hypotheses for a fertility of a source word, based on a source word and a context of the source word; generating sense hypotheses for a translation of the source word, based on the source word and the context of the source word; determining a probability of a fertility of a source word, based on the source word and the context of the source word; determining a probability of a target word being a correct translation of the source word, based on the source word and the context of the source word; and generating a list of target words for the translation of the source word, based on the probability of the fertility and the probability of the target word. 32. The method of claim 19, wherein the method is trained on a sentence-aligned training text including a plurality of sentences in the source language and a plurality of sentences in the target language, wherein each sentence in the plurality of source language sentences is a translation of a corresponding sentence in the plurality of target language sentences, and a training portion of the method comprises: determining an alignment between the words of each of the plurality of source language sentences and the corresponding target language sentence; accumulating fertility-context events from the alignments for at least some occurrence of the source word in a source language sentence, each fertility-context event including a number of target language words that the source language word is aligned to, the source language word, and the context of the source-language word; accumulating sense-context events from the alignments for at least some occurrence of the source word in a source language sentence, each sense-context event including the target word, the source-language word to which the target language word is aligned, and the context of the source-language word; and wherein the probability of the fertility of the source word and the probability of the target are determined using the accumulated fertility-context and sense-context events, respectively. | 0.5 |
7,587,395 | 4 | 5 | 4. The method according to claim 1 , wherein the calculating is comprised of generating a list of qualified documents based on meeting or surpassing a predefined score threshold corresponding to the set of synonyms represented by each keyword. | 4. The method according to claim 1 , wherein the calculating is comprised of generating a list of qualified documents based on meeting or surpassing a predefined score threshold corresponding to the set of synonyms represented by each keyword. 5. The method according to claim 4 , wherein the generating includes tracking statistics associated with the documents'degree of conformity to a predefined score threshold. | 0.5 |
9,407,768 | 1 | 11 | 1. A customer analysis method for analyzing electronic customer communication data and generating behavioral assessment data, which method comprises: receiving electronic customer communication data of two or more types by one or more servers configured to provide a user interface comprising a web site, web portal, or virtual portal, wherein at least one of the two or more types of electronic customer communication data comprises social media data, update status, media feed, social media review, social media data stream, social media profile or social media account setup; identifying a customer associated with the electronic customer communication data received by the one or more servers; analyzing the electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data for that identified customer; generating behavioral assessment data based on the analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data for that identified customer; and displaying instructions to a user via a reporting engine, wherein the instructions are based on the generated behavioral assessment data, wherein the user includes the identified customer or a customer service agent. | 1. A customer analysis method for analyzing electronic customer communication data and generating behavioral assessment data, which method comprises: receiving electronic customer communication data of two or more types by one or more servers configured to provide a user interface comprising a web site, web portal, or virtual portal, wherein at least one of the two or more types of electronic customer communication data comprises social media data, update status, media feed, social media review, social media data stream, social media profile or social media account setup; identifying a customer associated with the electronic customer communication data received by the one or more servers; analyzing the electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data for that identified customer; generating behavioral assessment data based on the analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data for that identified customer; and displaying instructions to a user via a reporting engine, wherein the instructions are based on the generated behavioral assessment data, wherein the user includes the identified customer or a customer service agent. 11. The customer analysis method of claim 1 , further comprising analyzing a telephonic communication associated with the electronic customer communication data, wherein analyzing the telephonic voice communication includes: receiving a telephonic communication between a first communicant to the telephonic communication and a second communicant to the telephonic communication; separating the telephonic communication into at least first constituent voice data, the first constituent voice data being generated by the first communicant and the second constituent voice data being generated by the second communicant; analyzing one of the separated first and second constituent voice data by mining the separated one of the first and second constituent voice data and applying a predetermined linguistic-based psychological behavioral model to the one of the separated first and second constituent voice data; and, generating behavioral assessment data including a personality type corresponding to the analyzed one of the separated first and second constituent voice data based on the analyzing of constituent voice data and based on behavioral assessment data for the electronic customer communication data. | 0.5 |
9,053,099 | 8 | 13 | 8. An apparatus for validating a data structure, comprising: a processor comprising a central processing unit; a mapping component that executes operations on the processor for identifying an equivalent data structure in a second programming language, in response to the mapping component identifying a data structure in a first programming language; a comparing component for comparing a data definition of the data structure with a data definition of the equivalent data structure; a determining component for determining whether there is an incompatibility between a compared data definition of the data structure and a compared data definition of the equivalent data structure by analyzing characteristics of all data fields in a generated assembler data structure of the first programming language corresponding to the data structure in the first programming language and corresponding data fields in a generated assembler data structure of the second programming language corresponding to the equivalent data structure in the second programming language, wherein the generated assembler data structures of the first and the second programming languages are allocated in memory; responsive to determining an incompatibility between the generated assembler data structure of the first programming language and the generated assembler data structure of the second programming language, generating an alert and communicating the alert to a mitigation component to identify a rule which defines an action to be taken in order to correct the incompatibility, wherein a messaging component and a rendering component reports the action to a user via a graphical user interface; and responsive to determining a compatibility between the generated assembler data structure of the first programming language and the generated assembler data structure of the second programming language, generating a message that the data structure in the first programming language and the equivalent data structure in the second programming language are synchronized, and communicating the message to the messaging component to display via the graphical user interface. | 8. An apparatus for validating a data structure, comprising: a processor comprising a central processing unit; a mapping component that executes operations on the processor for identifying an equivalent data structure in a second programming language, in response to the mapping component identifying a data structure in a first programming language; a comparing component for comparing a data definition of the data structure with a data definition of the equivalent data structure; a determining component for determining whether there is an incompatibility between a compared data definition of the data structure and a compared data definition of the equivalent data structure by analyzing characteristics of all data fields in a generated assembler data structure of the first programming language corresponding to the data structure in the first programming language and corresponding data fields in a generated assembler data structure of the second programming language corresponding to the equivalent data structure in the second programming language, wherein the generated assembler data structures of the first and the second programming languages are allocated in memory; responsive to determining an incompatibility between the generated assembler data structure of the first programming language and the generated assembler data structure of the second programming language, generating an alert and communicating the alert to a mitigation component to identify a rule which defines an action to be taken in order to correct the incompatibility, wherein a messaging component and a rendering component reports the action to a user via a graphical user interface; and responsive to determining a compatibility between the generated assembler data structure of the first programming language and the generated assembler data structure of the second programming language, generating a message that the data structure in the first programming language and the equivalent data structure in the second programming language are synchronized, and communicating the message to the messaging component to display via the graphical user interface. 13. The apparatus of claim 8 , wherein the determined incompatibility includes fields of the data structure that are declared in a correct order in the first programming language but have inconsistent declared character lengths. | 0.564885 |
7,827,029 | 22 | 37 | 22. A system for generating a user-interest note comprising: a processor that selects a text passage by highlighting the text or by inputting the text; user interest information received from at least one of entered keywords, monitored internet browsing patterns, and user academic or professional information; at least one condensation transformation expressed as rewrite rules and functions which reduces the selected passage by merging, deleting and changing the elements of the selected passage to remove modifiers and less salient information; a meaning structure determined by using a parsing grammar; a reduced meaning structure derived from the selected passage and based on input user information; meaning distortion constraints beyond which the meaning structure is identified as being distorted after the at least one condensation transformation is applied; and a plurality of candidate condensate based on the reduced meaning structure which are optimally ranked based on a predictive model or a statistical disambiguation model; wherein the processor further selects a user-interest note from the candidate condensates based on the input user interests. | 22. A system for generating a user-interest note comprising: a processor that selects a text passage by highlighting the text or by inputting the text; user interest information received from at least one of entered keywords, monitored internet browsing patterns, and user academic or professional information; at least one condensation transformation expressed as rewrite rules and functions which reduces the selected passage by merging, deleting and changing the elements of the selected passage to remove modifiers and less salient information; a meaning structure determined by using a parsing grammar; a reduced meaning structure derived from the selected passage and based on input user information; meaning distortion constraints beyond which the meaning structure is identified as being distorted after the at least one condensation transformation is applied; and a plurality of candidate condensate based on the reduced meaning structure which are optimally ranked based on a predictive model or a statistical disambiguation model; wherein the processor further selects a user-interest note from the candidate condensates based on the input user interests. 37. The system of claim 22 , in which the passage is converted into a packed meaning structure and the condensation transformations are applied to the packed structure based on meaning distortion constraints. | 0.555556 |
7,552,864 | 1 | 2 | 1. A method for testing the authenticity of documents wherein a document is tested by authenticity criteria, comprising providing at least two different authenticity classes each with one or more authenticity criteria for a valid document, the individual authenticity classes differing in at least one authenticity criterion, so that requirements for authenticity vary in strictness depending on the authenticity class, determining fitness or denomination of the documents; selecting an authenticity class from the different authenticity classes in dependence on the determined fitness or denomination of the document, testing the document by the authenticity criteria of the selected authenticity class, and assigning the document the selected authenticity class if the document meets the authenticity criteria thereof; wherein if the authenticity criteria of the selected authenticity class are not met, a further authenticity class with lower requirements for authenticity is selected and the authenticity testing repeated by the authenticity criteria of the selected further authenticity class. | 1. A method for testing the authenticity of documents wherein a document is tested by authenticity criteria, comprising providing at least two different authenticity classes each with one or more authenticity criteria for a valid document, the individual authenticity classes differing in at least one authenticity criterion, so that requirements for authenticity vary in strictness depending on the authenticity class, determining fitness or denomination of the documents; selecting an authenticity class from the different authenticity classes in dependence on the determined fitness or denomination of the document, testing the document by the authenticity criteria of the selected authenticity class, and assigning the document the selected authenticity class if the document meets the authenticity criteria thereof; wherein if the authenticity criteria of the selected authenticity class are not met, a further authenticity class with lower requirements for authenticity is selected and the authenticity testing repeated by the authenticity criteria of the selected further authenticity class. 2. The method according to claim 1 , wherein the fitness of the document is dividable into fitness classes, the document is assigned a fitness class corresponding to the fitness and the authenticity class for testing the authenticity of the document is selected in dependence on the fitness class assigned to the document. | 0.5 |
8,615,419 | 45 | 47 | 45. An apparatus for calculating an interaction churn score in an organization with which the customer has an interaction, the apparatus comprising: a voice recording device for capturing the interaction; a category definition component for defining a plurality of categories, each category characterized by an at least one parameter of a voiced expression; an extraction engine for extracting information from the interaction; a category score determination component for determining at least one category-interaction indication associating the interaction with at least one churning category out of a total number of categories; an interaction churn score determination component for determining an interaction churn score related to the interaction, wherein the interaction churn score comprises a term directly related to the number of churning categories the interaction is associated with and inversely related to the total number of churning categories using a formula:
A *(maximal score for a churning category)+ B *((number of churning categories into which the interaction is categorized)/(number of churning categories)*100), wherein A and B are coefficients set by a user and satisfy a condition of A+B=1; a transactional churn score determination component for determining a transaction churn score for the customer, based on additional data related to the customer or to the organization; a combined churn score determination component for combining the interaction churn score and the transaction churn score into a combined churn score; a retention offer engine for making a retention offer to the customer; and a capturing or logging component for capturing the interaction; and wherein the cited components comprise processing apparatus configured to perform the corresponding tasks cited above and wherein the cited engines comprise processing apparatus configured to perform the corresponding tasks cited above. | 45. An apparatus for calculating an interaction churn score in an organization with which the customer has an interaction, the apparatus comprising: a voice recording device for capturing the interaction; a category definition component for defining a plurality of categories, each category characterized by an at least one parameter of a voiced expression; an extraction engine for extracting information from the interaction; a category score determination component for determining at least one category-interaction indication associating the interaction with at least one churning category out of a total number of categories; an interaction churn score determination component for determining an interaction churn score related to the interaction, wherein the interaction churn score comprises a term directly related to the number of churning categories the interaction is associated with and inversely related to the total number of churning categories using a formula:
A *(maximal score for a churning category)+ B *((number of churning categories into which the interaction is categorized)/(number of churning categories)*100), wherein A and B are coefficients set by a user and satisfy a condition of A+B=1; a transactional churn score determination component for determining a transaction churn score for the customer, based on additional data related to the customer or to the organization; a combined churn score determination component for combining the interaction churn score and the transaction churn score into a combined churn score; a retention offer engine for making a retention offer to the customer; and a capturing or logging component for capturing the interaction; and wherein the cited components comprise processing apparatus configured to perform the corresponding tasks cited above and wherein the cited engines comprise processing apparatus configured to perform the corresponding tasks cited above. 47. The apparatus according to claim 45 , wherein the categories are provided by a user. | 0.645161 |
10,055,103 | 7 | 9 | 7. The method of claim 6 , wherein cycling through the characters comprises: transitioning from the empty state to a first cycling state, wherein the first cycling state represents the state of the application when the cycling operation is active for a first time; shifting the characters during the duration of the first input gesture; selecting a first character among the shifted characters; and performing a first autocomplete operation to present one or more proposed words based on the first character. | 7. The method of claim 6 , wherein cycling through the characters comprises: transitioning from the empty state to a first cycling state, wherein the first cycling state represents the state of the application when the cycling operation is active for a first time; shifting the characters during the duration of the first input gesture; selecting a first character among the shifted characters; and performing a first autocomplete operation to present one or more proposed words based on the first character. 9. The method of claim 7 , wherein performing the first autocomplete operation comprises generating a first proposed word based on a search history. | 0.581921 |
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