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1. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving speech data and data indicating a candidate transcription for the speech data; accessing a phonetic representation for the candidate transcription; extracting, from the phonetic representation, multiple test sequences for a particular phone in the phonetic representation, each of the multiple test sequences including a different set of contextual phones surrounding the particular phone; receiving data indicating that an acoustic model includes data corresponding to one or more of the multiple test sequences; selecting, from among the one or more test sequences for which the acoustic model includes data, the test sequence that includes the highest number of contextual phones, the selected test sequence including fewer than a predetermined maximum number of contextual phones; accessing data from the acoustic model corresponding to the selected test sequence; and generating a score for the candidate transcription based on the accessed data from the acoustic model that corresponds to the selected test sequence, wherein generating the score comprises: determining a penalty based on the selected test sequence including fewer than the predetermined maximum number of contextual phones; and adjusting a first score for the candidate transcription based on the penalty to generate an adjusted score, the adjusted score indicating a lower likelihood than the first score that the candidate transcription is an accurate transcription for the speech data.
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1. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving speech data and data indicating a candidate transcription for the speech data; accessing a phonetic representation for the candidate transcription; extracting, from the phonetic representation, multiple test sequences for a particular phone in the phonetic representation, each of the multiple test sequences including a different set of contextual phones surrounding the particular phone; receiving data indicating that an acoustic model includes data corresponding to one or more of the multiple test sequences; selecting, from among the one or more test sequences for which the acoustic model includes data, the test sequence that includes the highest number of contextual phones, the selected test sequence including fewer than a predetermined maximum number of contextual phones; accessing data from the acoustic model corresponding to the selected test sequence; and generating a score for the candidate transcription based on the accessed data from the acoustic model that corresponds to the selected test sequence, wherein generating the score comprises: determining a penalty based on the selected test sequence including fewer than the predetermined maximum number of contextual phones; and adjusting a first score for the candidate transcription based on the penalty to generate an adjusted score, the adjusted score indicating a lower likelihood than the first score that the candidate transcription is an accurate transcription for the speech data. 5. The system of claim 1 , wherein extracting multiple test sequences for the particular phone comprises extracting at least: a first sequence that includes one contextual phone before the particular phone or one contextual phone after the particular phone, a second sequence that includes two contextual phones before the particular phone or two contextual phones after the particular phone, and a third sequence that includes three contextual phones before the particular phone or three contextual phones after the particular phone.
| 0.590123 |
2. The method of claim 1 , further comprising: determining a score for each of the one or more semantic entities; and identifying a semantic entity with a highest determined score as the at least one likely semantic entity.
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2. The method of claim 1 , further comprising: determining a score for each of the one or more semantic entities; and identifying a semantic entity with a highest determined score as the at least one likely semantic entity. 3. The method of claim 2 , wherein the score for each of the semantic entities is determined based on a similarity of the at least one similar image to the target image.
| 0.935312 |
11. An audio analysis system comprising: a first terminal apparatus that is to be worn by a first user; a second terminal apparatus that is to be worn by a second user; and a host system that acquires information from the first terminal apparatus and the second terminal apparatus, wherein the first terminal apparatus includes a first audio acquisition device that acquires a sound and converts the sound into a first audio signal, the sound containing an utterance of the first user and an utterance of another person who is different from the first user, a first discriminator that discriminates between a portion that corresponds to the utterance of the first user and a portion that corresponds to the utterance of the other person which are contained in the first audio signal, a first utterance feature detector that detects a first utterance feature of the first user, on the basis of the portion that corresponds to the utterance of the first user or the portion that corresponds to the utterance of the other person which is contained in the first audio signal, and a first transmission unit that transmits to the host system first utterance information that contains at least a discrimination result obtained by the first discriminator and a detection result regarding the first utterance feature obtained by the first utterance feature detector, wherein the second terminal apparatus includes a second audio acquisition device that acquires a sound and converts the sound into a second audio signal, a second discriminator that discriminates between a portion that corresponds to an utterance of the second user and a portion that corresponds to an utterance of another person who is different from the second user, the portions being contained in the second audio signal, a second utterance feature detector that detects a second utterance feature of the second user, on the basis of the portion that corresponds to the utterance of the second user or the portion that corresponds to the utterance of the other person which is contained in the second audio signal, and a second transmission unit that transmits to the host system second utterance information that contains at least a discrimination result obtained by the second discriminator and a detection result regarding the second utterance feature obtained by the second utterance feature detector, and wherein the host system includes a reception unit that receives the first utterance information and the second utterance information that have been transmitted from the first and second transmission units, respectively, a conversation information detector that detects a first part corresponding to a first conversation between the first user and the other person who is different from the first user from the first utterance information that has been received by the reception unit, and detects portions of the first part of the first utterance information that correspond to the first user and the other person who are related to the first conversation, and that detects a second part corresponding to a second conversation between the second user and the other person who is different from the second user from the second utterance information that has been received by the reception unit, and detects portions of the second part of the second utterance information that correspond to the second user and the other person who are related to the second conversation, wherein the conversation information detector determines whether or not the first conversation and the second conversation are the same conversation between the first user and the second user on the basis of a comparison of the portions of the first part of the first utterance information that correspond to the first user and the other person who is different from the first user with the portions of the second part of the second utterance information that correspond to the second user and the other person who is different from the second user, a relation information holding unit that holds relation information on a relation between a predetermined emotion name and a combination of a plurality of utterance features of a plurality of speakers who participated in a past conversation, an emotion estimator that compares, with the relation information, a combination of the first and second utterance features related to the conversation between the first user and the second user, and estimates an emotion of at least one of the first user and the second user, and an output unit that outputs information that is based on an estimation result obtained by the emotion estimator.
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11. An audio analysis system comprising: a first terminal apparatus that is to be worn by a first user; a second terminal apparatus that is to be worn by a second user; and a host system that acquires information from the first terminal apparatus and the second terminal apparatus, wherein the first terminal apparatus includes a first audio acquisition device that acquires a sound and converts the sound into a first audio signal, the sound containing an utterance of the first user and an utterance of another person who is different from the first user, a first discriminator that discriminates between a portion that corresponds to the utterance of the first user and a portion that corresponds to the utterance of the other person which are contained in the first audio signal, a first utterance feature detector that detects a first utterance feature of the first user, on the basis of the portion that corresponds to the utterance of the first user or the portion that corresponds to the utterance of the other person which is contained in the first audio signal, and a first transmission unit that transmits to the host system first utterance information that contains at least a discrimination result obtained by the first discriminator and a detection result regarding the first utterance feature obtained by the first utterance feature detector, wherein the second terminal apparatus includes a second audio acquisition device that acquires a sound and converts the sound into a second audio signal, a second discriminator that discriminates between a portion that corresponds to an utterance of the second user and a portion that corresponds to an utterance of another person who is different from the second user, the portions being contained in the second audio signal, a second utterance feature detector that detects a second utterance feature of the second user, on the basis of the portion that corresponds to the utterance of the second user or the portion that corresponds to the utterance of the other person which is contained in the second audio signal, and a second transmission unit that transmits to the host system second utterance information that contains at least a discrimination result obtained by the second discriminator and a detection result regarding the second utterance feature obtained by the second utterance feature detector, and wherein the host system includes a reception unit that receives the first utterance information and the second utterance information that have been transmitted from the first and second transmission units, respectively, a conversation information detector that detects a first part corresponding to a first conversation between the first user and the other person who is different from the first user from the first utterance information that has been received by the reception unit, and detects portions of the first part of the first utterance information that correspond to the first user and the other person who are related to the first conversation, and that detects a second part corresponding to a second conversation between the second user and the other person who is different from the second user from the second utterance information that has been received by the reception unit, and detects portions of the second part of the second utterance information that correspond to the second user and the other person who are related to the second conversation, wherein the conversation information detector determines whether or not the first conversation and the second conversation are the same conversation between the first user and the second user on the basis of a comparison of the portions of the first part of the first utterance information that correspond to the first user and the other person who is different from the first user with the portions of the second part of the second utterance information that correspond to the second user and the other person who is different from the second user, a relation information holding unit that holds relation information on a relation between a predetermined emotion name and a combination of a plurality of utterance features of a plurality of speakers who participated in a past conversation, an emotion estimator that compares, with the relation information, a combination of the first and second utterance features related to the conversation between the first user and the second user, and estimates an emotion of at least one of the first user and the second user, and an output unit that outputs information that is based on an estimation result obtained by the emotion estimator. 12. The audio analysis system according to claim 11 , wherein the first terminal apparatus further includes a third audio acquisition device disposed at a position where a sound pressure of an utterance-based sound that arrives from the mouth of a user differs from a sound pressure of the utterance-based sound that arrives at the first audio acquisition device, the third audio acquisition device acquiring the sound and converting the sound into a third audio signal, wherein the first discriminator discriminates between a portion that corresponds to an utterance of the user and a portion that corresponds to an utterance of another person who is different from the user, the portions being contained in the first audio signal, on the basis of a result of comparing the first audio signal with the third audio signal, and wherein the first utterance feature detector detects an utterance feature of the user or the other person, on the basis of the portion that corresponds to the utterance of the user or the portion that corresponds to the utterance of the other person which is contained in the first audio signal or the third audio signal.
| 0.5 |
1. A computer-implemented method for parsing author names in a document, the method comprising: electronically scanning a document that contains an author name text string, the author name text string comprising a set of initials, one or more surnames, and punctuation, and the author name text string comprising at least one author name in non-standardized format; identifying a character sequence in the document as potentially being the author name text string, wherein the identifying is based on: (i) a sequence of title-case words, capital letters, and punctuation in the character sequence, and (ii) the character sequence ending with a recognized indicator; and parsing the identified character sequence and determining whether the identified character sequence is the author name text string, wherein the parsing and determining comprises: updating the identified character sequence by converting any punctuation or whitespace between terms in the character sequence to single space character, and determining whether one or more author names are contained in the updated character sequence by identifying a pattern of surname and set of initials in the updated character sequence, such that an author name in non-standardized format in the document is identified and output in standardized format.
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1. A computer-implemented method for parsing author names in a document, the method comprising: electronically scanning a document that contains an author name text string, the author name text string comprising a set of initials, one or more surnames, and punctuation, and the author name text string comprising at least one author name in non-standardized format; identifying a character sequence in the document as potentially being the author name text string, wherein the identifying is based on: (i) a sequence of title-case words, capital letters, and punctuation in the character sequence, and (ii) the character sequence ending with a recognized indicator; and parsing the identified character sequence and determining whether the identified character sequence is the author name text string, wherein the parsing and determining comprises: updating the identified character sequence by converting any punctuation or whitespace between terms in the character sequence to single space character, and determining whether one or more author names are contained in the updated character sequence by identifying a pattern of surname and set of initials in the updated character sequence, such that an author name in non-standardized format in the document is identified and output in standardized format. 7. The computer-implemented method of claim 1 , wherein the identified character sequence follows one or more patterns of: (i) surname followed by one or more initials, (ii) one or more initials followed by surname, (iii) sequence of capital letters possibly separated by punctuation, and (iv) punctuation or the term “and”.
| 0.615523 |
36. The product summary generator of claim 33 , wherein said product attribute module determines attribute ranks for each of said plurality of attributes, and processes said attribute ranks together with said importance ratings to derive a severity value for each of said plurality of attributes.
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36. The product summary generator of claim 33 , wherein said product attribute module determines attribute ranks for each of said plurality of attributes, and processes said attribute ranks together with said importance ratings to derive a severity value for each of said plurality of attributes. 37. The product summary generator of claim 36 , wherein said product attribute module derives said severity values using an inflection algorithm.
| 0.863407 |
1. A method of generating a personalized transcription from an audio recording, wherein the method is performed by a mobile device in communication with a server, wherein computational resources of the server are greater than computational resources of the mobile device, the method comprising: maintaining a personal vocabulary of words on the mobile device associated with a user of the mobile device, wherein the personal vocabulary is based on personal data associated with the user; receiving, from the server, a first transcription of an audio recording, wherein the first transcription is generated by a server automatic speech recognition (ASR) engine at the server and using an ASR vocabulary associated with a population of users, wherein the first transcription includes a first word list and confidence scores associated with a plurality of words in the first word list, and wherein the first transcription includes both words that the server ASR engine identified as most likely spoken as well as alternatives to those words; receiving, from the server, audio data corresponding to at least the portion of the audio recording; generating a second transcription, wherein the second transcription is of the received audio data, wherein the second transcription comprises a second word list and confidence scores associated with a plurality of words in the second word list, and wherein the second transcription is generated by a mobile device ASR engine located on the mobile device using the maintained personal vocabulary and an acoustic model associated with the user of the mobile device; re-scoring the first transcription, the re-scoring comprising: comparing the first transcription with the second transcription, and modifying a confidence score associated with an alternative word in the first word list when the mobile device ASR engine indicates a higher confidence score for the alternative word than the confidence score attributed by the server ASR engine to the alternative word; and generating a final transcription based on the re-scored first transcription, the final transcription including a combination of most likely spoken words identified by the UASR engine as well as the re-scored alternative words identified by the mobile device ASR engine.
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1. A method of generating a personalized transcription from an audio recording, wherein the method is performed by a mobile device in communication with a server, wherein computational resources of the server are greater than computational resources of the mobile device, the method comprising: maintaining a personal vocabulary of words on the mobile device associated with a user of the mobile device, wherein the personal vocabulary is based on personal data associated with the user; receiving, from the server, a first transcription of an audio recording, wherein the first transcription is generated by a server automatic speech recognition (ASR) engine at the server and using an ASR vocabulary associated with a population of users, wherein the first transcription includes a first word list and confidence scores associated with a plurality of words in the first word list, and wherein the first transcription includes both words that the server ASR engine identified as most likely spoken as well as alternatives to those words; receiving, from the server, audio data corresponding to at least the portion of the audio recording; generating a second transcription, wherein the second transcription is of the received audio data, wherein the second transcription comprises a second word list and confidence scores associated with a plurality of words in the second word list, and wherein the second transcription is generated by a mobile device ASR engine located on the mobile device using the maintained personal vocabulary and an acoustic model associated with the user of the mobile device; re-scoring the first transcription, the re-scoring comprising: comparing the first transcription with the second transcription, and modifying a confidence score associated with an alternative word in the first word list when the mobile device ASR engine indicates a higher confidence score for the alternative word than the confidence score attributed by the server ASR engine to the alternative word; and generating a final transcription based on the re-scored first transcription, the final transcription including a combination of most likely spoken words identified by the UASR engine as well as the re-scored alternative words identified by the mobile device ASR engine. 3. The method of claim 1 , wherein the audio recording is of a second user, the first transcription includes metadata associated with the second user, and the word from the second word list is added to the first word list based on the metadata.
| 0.551361 |
1. A computer-implemented method for controlling operations of a system in an environment using temporal patterns in data sequences, comprising: constructing a hierarchical tree of nodes, the hierarchical tree of nodes including a root node, a plurality of intermediate nodes, and a plurality of leaf nodes, and in which the root node has a plurality of child nodes, each intermediate node has a parent node and a plurality of child nodes, and each leaf node has a parent node; associating each node with a composite hidden Markov model, in which each composite hidden Markov model associated with the root node or an intermediate node has one independent path model corresponding to each child node of the node, and in which each composite hidden Markov model associated with a leaf node has a plurality of independent final path models; acquiring a set of training data sequences representing known temporal patterns of motion of physical objects in an environment; training the composite hidden Markov models using the set of training data sequences, in which the training further comprises: training the composite hidden Markov model associated with the root node with the set of training data sequences; training the composite hidden Markov models associated with each intermediate node with intermediate subsets of the set of training data sequences, each intermediate subset of the set of training data sequences including a training data sequence generated by the corresponding independent path model of the parent node of the intermediate node; and training the composite hidden Markov model associated with each leaf node with leaf subsets of the set of training data sequences to produce a plurality of trained final path models, each leaf subset of the set of training data sequences including a training data sequence generated by the corresponding independent path model of the parent node of the leaf node; constructing a single final composite hidden Markov model, in which the single final composite hidden Markov model has one independent path model for each trained final path model; acquiring unknown data sequences representing unknown temporal patterns of motion of physical objects in the environment; employing the single final composite hidden Markov model to determine known temporal patterns in the unknown data sequences; and controlling operations of a system in the environment using the determined known temporal patterns.
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1. A computer-implemented method for controlling operations of a system in an environment using temporal patterns in data sequences, comprising: constructing a hierarchical tree of nodes, the hierarchical tree of nodes including a root node, a plurality of intermediate nodes, and a plurality of leaf nodes, and in which the root node has a plurality of child nodes, each intermediate node has a parent node and a plurality of child nodes, and each leaf node has a parent node; associating each node with a composite hidden Markov model, in which each composite hidden Markov model associated with the root node or an intermediate node has one independent path model corresponding to each child node of the node, and in which each composite hidden Markov model associated with a leaf node has a plurality of independent final path models; acquiring a set of training data sequences representing known temporal patterns of motion of physical objects in an environment; training the composite hidden Markov models using the set of training data sequences, in which the training further comprises: training the composite hidden Markov model associated with the root node with the set of training data sequences; training the composite hidden Markov models associated with each intermediate node with intermediate subsets of the set of training data sequences, each intermediate subset of the set of training data sequences including a training data sequence generated by the corresponding independent path model of the parent node of the intermediate node; and training the composite hidden Markov model associated with each leaf node with leaf subsets of the set of training data sequences to produce a plurality of trained final path models, each leaf subset of the set of training data sequences including a training data sequence generated by the corresponding independent path model of the parent node of the leaf node; constructing a single final composite hidden Markov model, in which the single final composite hidden Markov model has one independent path model for each trained final path model; acquiring unknown data sequences representing unknown temporal patterns of motion of physical objects in the environment; employing the single final composite hidden Markov model to determine known temporal patterns in the unknown data sequences; and controlling operations of a system in the environment using the determined known temporal patterns. 5. The computer-implemented method of claim 1 , further comprising: parameterizing each composite hidden Markov model by λ k j , where λ k j includes conventional hidden Markov model parameters {π m , T pq , b m }, π m represents prior probabilities for states of the composite hidden Markov model, T pq is a transition matrix of state transition probabilities, and b m is a parameterization of an output distribution of the composite hidden Markov model, and in which each composite hidden Markov model has a probability P(O i |λ k j ) that an i th data sequence of observations O i is generated by a j th composite hidden Markov model on a k th level of the tree.
| 0.5 |
3. The method of claim 2 , wherein using the at least one cognitive motivation orientation confidence weight recorded for the first text sequence to determine a first dominant cognitive motivation orientation set expressed in the first text sequence further comprises normalizing the first text sequence cognitive motivation orientation weight scores to obtain normalized first text sequence cognitive motivation orientation weight scores, there being one-to-one correspondence between the normalized first text sequence cognitive motivation orientation weight scores and the first text sequence cognitive motivation orientation weight scores.
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3. The method of claim 2 , wherein using the at least one cognitive motivation orientation confidence weight recorded for the first text sequence to determine a first dominant cognitive motivation orientation set expressed in the first text sequence further comprises normalizing the first text sequence cognitive motivation orientation weight scores to obtain normalized first text sequence cognitive motivation orientation weight scores, there being one-to-one correspondence between the normalized first text sequence cognitive motivation orientation weight scores and the first text sequence cognitive motivation orientation weight scores. 4. The method of claim 3 , wherein using the at least one cognitive motivation orientation confidence weight recorded for the first text sequence to determine a first dominant cognitive motivation orientation set expressed in the first text sequence further comprises: maintaining normalized dominance thresholds, there being one normalized dominance threshold corresponding to each first text sequence cognitive motivation orientation weight score in one-to-one correspondence; comparing the normalized first text sequence cognitive motivation orientation weight scores to respective corresponding normalized dominance thresholds; and ranking the normalized first text sequence cognitive motivation orientation weight scores, the ranking being according to a difference between each normalized first text sequence cognitive motivation orientation weight score and its respective corresponding normalized dominance threshold, to thereby obtain ranked normalized first text sequence cognitive motivation orientation weight scores.
| 0.701715 |
1. A current affair political apparatus for entertaining comprising: (a) a game board which includes a movement track divided into four colors wherein each color represents one year of a four year presidential term and each year is subdivided into a plurality of spaces bearing indicia to reflect a plurality of categories of political subjects; (b) a plurality of decks of a plurality of scenario cards with the front side bearing indicia to match the indicia of at least one of the said spaces on the said game board; (c) a deck of a plurality of cards with the front side bearing indicia to match the indicia bearing at least one place setting on the said game board; (d) a deck of a plurality of Voting Paddles comprising the front side representing affirmation and the back side representing rejection; (e) Political Party Pin-back Buttons bearing indicia of one of either two political parties; (f) a simulation of an official source wherein players retrieve talking points, referred to as Foreign Affairs Reference Manual, comprising statistics and notes on a plurality of countries, and a plurality of Alternative Energy Sources; (g) one of a plurality of score sheets referred to as the President's Personal Log comprising any combination of the following: Approval Rating log, Federal Budget log, Unemployment statistics, War Involvement, Party Makeup in Congress, a bills submitted to Congress chart, and a Voting Key; (h) a leader coin bearing indicia on both sides representing the Hippo and the Giraffe political party; (i) a plurality of place markers also referred to as pawns comprising at least one or any of the combinations Air Force One Jet, Limousine, Helicopter, Hummer, Tank, Submarine, Cruise Liner, Eagle, and Donkey; (j) a plurality of War chips; (k) a sixty-second and a thirty second sand timer; (l) and two dice; (m) an oval office device comprises: 1) a base unit comprising: A) a firm oval shaped panel made from non flexible material, wherein said oval shaped panel bears the indicia of an overlapping inlayed inner circle and a larger outer circle wherein both said circles share common center with said oval panel, wherein said outer circle further comprises: i. a diameter equal to width of said oval panel and, ii. a circumference bearing indicia representing time corresponding to player's marker position on said movement track, wherein said inner circle further comprises: i. four pie shaped quarters, wherein each said quarters are divided into four smaller equal pie sections colored to match the colors on the said movement track and, ii. indicia on each said smaller pie section bearing frequency rates that payments are made and aggregate dollar amounts paid during players' administrative terms, B) indicia on either lengthwise end of said oval panel bearing a ten column by four row table wherein the said table is populated with numerical information representing quantities of players' legislation passed into law; 2) an upper radial piece comprising: A) two rectangular slots, through which information on underneath said oval panel may be seen; B) a diameter length the same as diameter of said inlayed inner circle of said oval panel; C) a center that overlaps and intersects the center of said oval panel wherein circumference area of said larger inlayed outer circle of said oval panel is exposed; D) attachment device positioned at point of intersection (both centers), of the said oval panel and said upper radial piece wherein said upper radial piece rotates; E) indicia bearing single payment amount information corresponding to a plurality of scenario cards and; F) indicia bearing emblems representing political theme of the game board; (n) the assumption that each player is the President of their very own country of The United States of America; (o) the said President's Personal Log allows said player to track the progress of their administration during their term.
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1. A current affair political apparatus for entertaining comprising: (a) a game board which includes a movement track divided into four colors wherein each color represents one year of a four year presidential term and each year is subdivided into a plurality of spaces bearing indicia to reflect a plurality of categories of political subjects; (b) a plurality of decks of a plurality of scenario cards with the front side bearing indicia to match the indicia of at least one of the said spaces on the said game board; (c) a deck of a plurality of cards with the front side bearing indicia to match the indicia bearing at least one place setting on the said game board; (d) a deck of a plurality of Voting Paddles comprising the front side representing affirmation and the back side representing rejection; (e) Political Party Pin-back Buttons bearing indicia of one of either two political parties; (f) a simulation of an official source wherein players retrieve talking points, referred to as Foreign Affairs Reference Manual, comprising statistics and notes on a plurality of countries, and a plurality of Alternative Energy Sources; (g) one of a plurality of score sheets referred to as the President's Personal Log comprising any combination of the following: Approval Rating log, Federal Budget log, Unemployment statistics, War Involvement, Party Makeup in Congress, a bills submitted to Congress chart, and a Voting Key; (h) a leader coin bearing indicia on both sides representing the Hippo and the Giraffe political party; (i) a plurality of place markers also referred to as pawns comprising at least one or any of the combinations Air Force One Jet, Limousine, Helicopter, Hummer, Tank, Submarine, Cruise Liner, Eagle, and Donkey; (j) a plurality of War chips; (k) a sixty-second and a thirty second sand timer; (l) and two dice; (m) an oval office device comprises: 1) a base unit comprising: A) a firm oval shaped panel made from non flexible material, wherein said oval shaped panel bears the indicia of an overlapping inlayed inner circle and a larger outer circle wherein both said circles share common center with said oval panel, wherein said outer circle further comprises: i. a diameter equal to width of said oval panel and, ii. a circumference bearing indicia representing time corresponding to player's marker position on said movement track, wherein said inner circle further comprises: i. four pie shaped quarters, wherein each said quarters are divided into four smaller equal pie sections colored to match the colors on the said movement track and, ii. indicia on each said smaller pie section bearing frequency rates that payments are made and aggregate dollar amounts paid during players' administrative terms, B) indicia on either lengthwise end of said oval panel bearing a ten column by four row table wherein the said table is populated with numerical information representing quantities of players' legislation passed into law; 2) an upper radial piece comprising: A) two rectangular slots, through which information on underneath said oval panel may be seen; B) a diameter length the same as diameter of said inlayed inner circle of said oval panel; C) a center that overlaps and intersects the center of said oval panel wherein circumference area of said larger inlayed outer circle of said oval panel is exposed; D) attachment device positioned at point of intersection (both centers), of the said oval panel and said upper radial piece wherein said upper radial piece rotates; E) indicia bearing single payment amount information corresponding to a plurality of scenario cards and; F) indicia bearing emblems representing political theme of the game board; (n) the assumption that each player is the President of their very own country of The United States of America; (o) the said President's Personal Log allows said player to track the progress of their administration during their term. 9. Said leader coin of claim 1 is for appointments to serve as leaders of other countries and high office appointments and leadership.
| 0.970106 |
8. The recommendation engine of claim 7 , wherein determining the target query recommendation score includes: determining a coverage rate of the search query from the query record, the coverage rate indicating an average amount of applications indicated in search results provided by the search engine in response to the target search query; and determining the target query recommendation score based on the coverage rate.
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8. The recommendation engine of claim 7 , wherein determining the target query recommendation score includes: determining a coverage rate of the search query from the query record, the coverage rate indicating an average amount of applications indicated in search results provided by the search engine in response to the target search query; and determining the target query recommendation score based on the coverage rate. 9. The recommendation engine of claim 8 , wherein: each application indicated in each set of search results defined in the target query record includes a result score associated therewith, and the result score indicates a degree of confidence in a match of the application to the search query.
| 0.920615 |
11. Non-transitory computer-readable media storing executable instructions that, when executed by one or more processors, cause a system to: classify speech into at least one voice cluster based on identified acoustic features of the speech, the at least one voice cluster corresponding to a text cluster and a customized language model that reflects characteristics of a speaker of the speech; determine a text query based on the customized language model and one or more text strings determined based on the speech; receive search results based on the text query, each of the search results having a ranking indicating a measure of importance relative to other of the search results; re-rank the search results based on re-scoring the search results using the text cluster; receive a user interaction log comprising click data associated with a user interaction with the re-ranked search results; update the at least one voice cluster based on the user interaction with the re-ranked search results; and update the customized language model based on the click data associated with the user interaction with the re-ranked search results.
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11. Non-transitory computer-readable media storing executable instructions that, when executed by one or more processors, cause a system to: classify speech into at least one voice cluster based on identified acoustic features of the speech, the at least one voice cluster corresponding to a text cluster and a customized language model that reflects characteristics of a speaker of the speech; determine a text query based on the customized language model and one or more text strings determined based on the speech; receive search results based on the text query, each of the search results having a ranking indicating a measure of importance relative to other of the search results; re-rank the search results based on re-scoring the search results using the text cluster; receive a user interaction log comprising click data associated with a user interaction with the re-ranked search results; update the at least one voice cluster based on the user interaction with the re-ranked search results; and update the customized language model based on the click data associated with the user interaction with the re-ranked search results. 16. The non-transitory computer-readable media of claim 11 , storing further executable instructions that, when executed by the one or more processors, cause the system to: receive metadata that corresponds to the speech, wherein classifying the speech into the at least one voice cluster based on the identified acoustic features of the speech comprises classifying the speech into the at least one voice cluster based on the identified acoustic features of the speech and the metadata that corresponds to the speech.
| 0.514144 |
10. A system of creating a structural document, the system comprising: a computing device; and a non-transitory computer-readable storage medium in communication with the computing device, wherein the computer-readable storage medium comprises one or more programming instructions that, when executed, cause the computing device to: receive content information pertaining to one or more contents that are to be encased by a structural document, determine a shape of a structural document based at least in part on the received content information, determine a plurality of dimensions of the structural document based at least in part on the received content information, receive content item information associated with one or more content items, wherein the content item information comprises at least one brand identifier associated with a provider of the one or more contents, cause a three-dimensional graphical representation of the structural document to be displayed at a user computing device, wherein a shape of the three-dimensional graphical representation corresponds to the determined shape, wherein a plurality of dimensions of the three-dimensional graphical representation correspond to the determined plurality of dimensions, wherein the three-dimensional graphical representation comprises at least a portion of the received content items; receive an indication that a user is finished creating the structural document, generate a print document comprising an encoded data mark, and provide the print document to one or more print-related devices.
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10. A system of creating a structural document, the system comprising: a computing device; and a non-transitory computer-readable storage medium in communication with the computing device, wherein the computer-readable storage medium comprises one or more programming instructions that, when executed, cause the computing device to: receive content information pertaining to one or more contents that are to be encased by a structural document, determine a shape of a structural document based at least in part on the received content information, determine a plurality of dimensions of the structural document based at least in part on the received content information, receive content item information associated with one or more content items, wherein the content item information comprises at least one brand identifier associated with a provider of the one or more contents, cause a three-dimensional graphical representation of the structural document to be displayed at a user computing device, wherein a shape of the three-dimensional graphical representation corresponds to the determined shape, wherein a plurality of dimensions of the three-dimensional graphical representation correspond to the determined plurality of dimensions, wherein the three-dimensional graphical representation comprises at least a portion of the received content items; receive an indication that a user is finished creating the structural document, generate a print document comprising an encoded data mark, and provide the print document to one or more print-related devices. 11. The system of claim 10 , wherein the one or more programming instructions that, when executed, cause the computing device to receive content information pertaining to one or more contents of a structural document comprise one or more programming instructions that, when executed, cause the computing device to receive one or more of the following: one or more dimensions associated with the one or more contents; and a shape associated with the one or more contents.
| 0.593721 |
14. A non-transitory computer readable medium having stored thereon instructions for translating user keywords into semantic queries the instructions comprising executable code which, when executed by at least one processor, causes the processor to: receive keywords; search the conceptual model to identify one or more concepts relevant to the keywords; transform at least a portion of the conceptual model into a connected graph; generate at least one path through the connected graph, the at least one path connecting the one or more concepts; identify and rank facets that support incremental user navigation from nodes of convergence in the at least one path, wherein the facets are generated at least in part by indexing a number of distinct values for attributes of the one or more concepts; generate at least one structured semantic query from the at least one path with the identified and ranked facets; and execute the at least one structure semantic query on a semantic repository.
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14. A non-transitory computer readable medium having stored thereon instructions for translating user keywords into semantic queries the instructions comprising executable code which, when executed by at least one processor, causes the processor to: receive keywords; search the conceptual model to identify one or more concepts relevant to the keywords; transform at least a portion of the conceptual model into a connected graph; generate at least one path through the connected graph, the at least one path connecting the one or more concepts; identify and rank facets that support incremental user navigation from nodes of convergence in the at least one path, wherein the facets are generated at least in part by indexing a number of distinct values for attributes of the one or more concepts; generate at least one structured semantic query from the at least one path with the identified and ranked facets; and execute the at least one structure semantic query on a semantic repository. 17. The non-transitory computer readable medium of claim 14 , the conceptual model comprises resource description framework (RDF) as a data model and the executable code, when executed by the processor, further causes the processor to: summarize RDF data in a resource description framework schema (RDFS) or an ontology web language (OWL) type class to obtain summarized RDF data; and generate, a summarized RDF type graph; and interconnect the summarized RDF type graph with the concept model.
| 0.712877 |
10. A system comprising: a mobile device network; a plurality of mobile devices configured to take digital images, connect to the mobile device network, and transmit the digital images over the mobile device network; one or more computers configured to receive the digital images from the mobile devices, apply optical character recognition to extract words from the digital images, index the digital images based on the extracted words, and store the digital images for later retrieval based on received search terms; wherein the one or more computers are configured to receive indications of document type along with the digital images, select between at least two dictionary based language models according to the indications of document type, and post-process the extracted words in accordance with the selected dictionary based language model; and wherein an indication of document type comprises a user specified category selected from a group including business cards and credit card receipts.
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10. A system comprising: a mobile device network; a plurality of mobile devices configured to take digital images, connect to the mobile device network, and transmit the digital images over the mobile device network; one or more computers configured to receive the digital images from the mobile devices, apply optical character recognition to extract words from the digital images, index the digital images based on the extracted words, and store the digital images for later retrieval based on received search terms; wherein the one or more computers are configured to receive indications of document type along with the digital images, select between at least two dictionary based language models according to the indications of document type, and post-process the extracted words in accordance with the selected dictionary based language model; and wherein an indication of document type comprises a user specified category selected from a group including business cards and credit card receipts. 21. The system of claim 10 , wherein the one or more computers are configured to pre-process the digital images to improve the optical character recognition.
| 0.644184 |
1. A pegboard organization system for locating at least four products on a pegboard display, wherein each product among the at least four products is positioned according to a respective peg, the respective peg comprising at least one peg shaft for holding a product and at least one peg foot for coupling the peg to the pegboard display, the system comprising: a first strip comprising at least two first color bars, the first strip configured to be positioned in a first direction; and at least two second strips for positioning the at least four products, wherein each second strip is configured to be positioned in a second direction different from the first direction, and wherein each second strip is configured to position at least two products among the at least four products, each second strip comprising: a second color bar, and for each product positioned by each second strip: a product identifier for identifying the product, and a peg indicator for indicating a position of the respective peg on the pegboard display at which the respective peg is to be positioned, wherein the peg indicator comprises at least one first marker for indicating a position of the at least one peg shaft on the pegboard display such that a location for the product identified by the product identifier is indicated by the at least one first marker, wherein each first color bar respectively indicates a position of each second strip, wherein each first color bar is configured to respectively correspond to the second color bar on each second strip.
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1. A pegboard organization system for locating at least four products on a pegboard display, wherein each product among the at least four products is positioned according to a respective peg, the respective peg comprising at least one peg shaft for holding a product and at least one peg foot for coupling the peg to the pegboard display, the system comprising: a first strip comprising at least two first color bars, the first strip configured to be positioned in a first direction; and at least two second strips for positioning the at least four products, wherein each second strip is configured to be positioned in a second direction different from the first direction, and wherein each second strip is configured to position at least two products among the at least four products, each second strip comprising: a second color bar, and for each product positioned by each second strip: a product identifier for identifying the product, and a peg indicator for indicating a position of the respective peg on the pegboard display at which the respective peg is to be positioned, wherein the peg indicator comprises at least one first marker for indicating a position of the at least one peg shaft on the pegboard display such that a location for the product identified by the product identifier is indicated by the at least one first marker, wherein each first color bar respectively indicates a position of each second strip, wherein each first color bar is configured to respectively correspond to the second color bar on each second strip. 15. The system according to claim 1 , wherein the product identifier comprises a bar code for identifying the product.
| 0.530834 |
13. A computer readable storage device for tracking a user, the computer readable storage medium having stored thereon computer executable instructions that, when executed on a computer, cause the computer to perform operations comprising: receiving a depth image; identifying an estimated location or position of a part of the user in the depth image; adjusting a model of the user based on the estimated location or position of the part of the user; and in response to a failure to identify a location or position of the part of the user in a second depth image, associating the part of the user with a portion of the second depth image based on a location or position of a default position of the part of the user.
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13. A computer readable storage device for tracking a user, the computer readable storage medium having stored thereon computer executable instructions that, when executed on a computer, cause the computer to perform operations comprising: receiving a depth image; identifying an estimated location or position of a part of the user in the depth image; adjusting a model of the user based on the estimated location or position of the part of the user; and in response to a failure to identify a location or position of the part of the user in a second depth image, associating the part of the user with a portion of the second depth image based on a location or position of a default position of the part of the user. 16. The computer readable storage device of claim 13 , wherein the model comprises: a skeletal model having joints and bones.
| 0.564177 |
1. A computer implemented method of converting a text form into a phoneme tree, comprising: parsing a data source in the text form to obtain a plurality of partial word lists of the data source, the data source comprising content of a web page; compiling the plurality of partial word lists to create a plurality of phoneme graphs, each phoneme graph corresponding to a respective partial word list, each phoneme graph including a root node, a plurality of phonemes, and an end node; combining the plurality of phoneme graphs to form the phoneme tree, wherein the phoneme tree includes at least a first phoneme graph and a second phoneme graph sharing a common root node and a common end node.
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1. A computer implemented method of converting a text form into a phoneme tree, comprising: parsing a data source in the text form to obtain a plurality of partial word lists of the data source, the data source comprising content of a web page; compiling the plurality of partial word lists to create a plurality of phoneme graphs, each phoneme graph corresponding to a respective partial word list, each phoneme graph including a root node, a plurality of phonemes, and an end node; combining the plurality of phoneme graphs to form the phoneme tree, wherein the phoneme tree includes at least a first phoneme graph and a second phoneme graph sharing a common root node and a common end node. 3. The method according to claim 1 , wherein under a circumstance that the data source changes responsive to a user clicking on a link of a rendering of the web page, continuing the combination of the created phoneme graphs into the phoneme tree and caching the phoneme tree for use by the speech recognizer while a data parser parses the changed data source to obtain updated partial word lists, one or more compilers compile the updated partial word lists to create updated phoneme graphs corresponding, respectively, to the updated partial word lists, and a combiner combines the created updated phoneme graphs into an updated phoneme tree that is then used by the speech recognizer to conduct the speech recognition of the text form in the changed data source.
| 0.524254 |
9. The method of claim 1 comprising: determining, by the first user device, one or more third speaker models, associated with the first user device, for other people who may be located in a physical area near a physical location of the first user device; and determining, by the first user device, that the utterance was likely spoken by the first user based at least on (i) the first score that indicates a likelihood that the utterance was spoken by the first user of the first user device, (ii) the second score that indicates a likelihood that the utterance was spoken by the second user that is associated with the second user device, and (iii) the third speaker models for other people who may be located in a physical area near a physical location of the first user device.
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9. The method of claim 1 comprising: determining, by the first user device, one or more third speaker models, associated with the first user device, for other people who may be located in a physical area near a physical location of the first user device; and determining, by the first user device, that the utterance was likely spoken by the first user based at least on (i) the first score that indicates a likelihood that the utterance was spoken by the first user of the first user device, (ii) the second score that indicates a likelihood that the utterance was spoken by the second user that is associated with the second user device, and (iii) the third speaker models for other people who may be located in a physical area near a physical location of the first user device. 10. The method of claim 9 comprising: generating, by the first user device for each of the third speaker models, a respective third score using the respective third speaker model and a portion of the audio signal; and comparing, by the first user device, the first score, the second score, and the third scores to determine a highest score.
| 0.726024 |
1. A non-transitory program storage device readable by a computer, tangibly embodying a program of instructions executed by the computer to perform the method steps for accelerating time series data base queries, the method comprising the steps of: segmenting an original time series of signal values into non-overlapping chunks, where a time-scale for each of the chunks is much less than the time scale of the entire time series; representing time series signal values in each chunk as a weighted superposition of atoms that are members of a shape dictionary, to create a compressed time series; storing said original time series and said compressed time series into a database, determining whether a query is answerable using said compressed time series or said original time series, and whether answering said query using said compressed time series is faster; and if answering the query is faster using the compressed representation, executing the query on weight coefficients of the compressed time series to produce a query result, and translating the query result back into an uncompressed representation, wherein the original time series is S=(s(t 1 ), . . . , s(t n )) with n values, the shape dictionary is D={φ i , iεI} with each atom φ i =(φ i (t 1 ), . . . ,φ i (t n )) of the dictionary being a set of signal samples, and said weighted superposition of atoms is S ( t ) = ∑ i = 1 k α i φ i ( t ) , wherein the α i are weight coefficients determined to fit the signal samples to the time series.
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1. A non-transitory program storage device readable by a computer, tangibly embodying a program of instructions executed by the computer to perform the method steps for accelerating time series data base queries, the method comprising the steps of: segmenting an original time series of signal values into non-overlapping chunks, where a time-scale for each of the chunks is much less than the time scale of the entire time series; representing time series signal values in each chunk as a weighted superposition of atoms that are members of a shape dictionary, to create a compressed time series; storing said original time series and said compressed time series into a database, determining whether a query is answerable using said compressed time series or said original time series, and whether answering said query using said compressed time series is faster; and if answering the query is faster using the compressed representation, executing the query on weight coefficients of the compressed time series to produce a query result, and translating the query result back into an uncompressed representation, wherein the original time series is S=(s(t 1 ), . . . , s(t n )) with n values, the shape dictionary is D={φ i , iεI} with each atom φ i =(φ i (t 1 ), . . . ,φ i (t n )) of the dictionary being a set of signal samples, and said weighted superposition of atoms is S ( t ) = ∑ i = 1 k α i φ i ( t ) , wherein the α i are weight coefficients determined to fit the signal samples to the time series. 3. The computer readable program storage device of claim 1 , the method further comprising executing said translated query on a higher different compression level to obtain an approximate result more quickly.
| 0.626902 |
14. The computer program product of claim 10 , wherein identifying an abbreviation being present in association with the instance of the full name of the entity further comprises: identifying, within the context window, an abbreviation cue instance being present, wherein the abbreviation cue instance is an instance of one or more previously defined abbreviation cues, and wherein the abbreviation cue instance is associated with a candidate abbreviation; and validating the candidate abbreviation as representing an actual abbreviation present in the context window.
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14. The computer program product of claim 10 , wherein identifying an abbreviation being present in association with the instance of the full name of the entity further comprises: identifying, within the context window, an abbreviation cue instance being present, wherein the abbreviation cue instance is an instance of one or more previously defined abbreviation cues, and wherein the abbreviation cue instance is associated with a candidate abbreviation; and validating the candidate abbreviation as representing an actual abbreviation present in the context window. 15. The computer program product of claim 14 , wherein validating the candidate abbreviation as representing an actual abbreviation comprises: applying one or more abbreviation validation patterns to a string of characters of the candidate abbreviation; and validating the candidate abbreviation as representing an actual abbreviation in response to the candidate abbreviation matching at least one of the one or more abbreviation validation patterns.
| 0.843819 |
1. A method for collaborative note taking based on a speech of a speaker and providing a summary to a user in an audience of the speaker, the method comprising: receiving a first set of information from the speech; performing speech recognition on the first set of information and determining selected portions of the speech; determining portions of context information corresponding to a domain information from a presentation information source temporally associated with the selected portions of the speech; determining at least one language model based on the selected portions of the speech and the temporally associated portions of context information from the presentation information source, wherein the at least one language model is dynamically determined; applying the language model to the first set of information to extract salient tokens from the first set of information; verifying relevance of the salient tokens based on the presentation information source to obtain verified tokens; generating the summary including the extracted salient tokens, wherein generating the summary includes assembling the verified tokens; displaying the summary to the user; and receiving collaborative user feedback information relating to the summary and adjusting the language model according to the collaborative user feedback, wherein the method is implemented by a computer.
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1. A method for collaborative note taking based on a speech of a speaker and providing a summary to a user in an audience of the speaker, the method comprising: receiving a first set of information from the speech; performing speech recognition on the first set of information and determining selected portions of the speech; determining portions of context information corresponding to a domain information from a presentation information source temporally associated with the selected portions of the speech; determining at least one language model based on the selected portions of the speech and the temporally associated portions of context information from the presentation information source, wherein the at least one language model is dynamically determined; applying the language model to the first set of information to extract salient tokens from the first set of information; verifying relevance of the salient tokens based on the presentation information source to obtain verified tokens; generating the summary including the extracted salient tokens, wherein generating the summary includes assembling the verified tokens; displaying the summary to the user; and receiving collaborative user feedback information relating to the summary and adjusting the language model according to the collaborative user feedback, wherein the method is implemented by a computer. 3. The method of claim 1 , wherein the language model recognizes features associated with at least one of: audio information, video information, and tactile information.
| 0.521569 |
1. A system embodied on a computer storage medium that facilitates searching for items for sale on an online classifieds site comprising: an item posting component that receives and posts at least one new geo-tagged item; a monitor that examines the at least one new geo-tagged item for geo-tag information; an analysis component that determines a match exists between at least one new item and a user's geo-tag preferences, wherein the at least one new item is associated with a first portion of geo-tag information comprising a location of the new item and a second portion of geo-tag information comprising a location of the user, wherein the first and second portions of geo-tag information are accessible by the analysis component, and wherein the analysis component determines the at least one new item via an inferential search; a notification component that alerts the user that a match exists between the at least one new item and the user's geo-tag preferences, wherein the first portion of geo-tag information is filtered from view by the user, and wherein the second portion of geo-tag information is accessible by the user; and a mapping component that illustrates directions between the first portion of geo-tag information comprising the location of the new item and the second portion of the geo-tag information comprising the location of the user.
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1. A system embodied on a computer storage medium that facilitates searching for items for sale on an online classifieds site comprising: an item posting component that receives and posts at least one new geo-tagged item; a monitor that examines the at least one new geo-tagged item for geo-tag information; an analysis component that determines a match exists between at least one new item and a user's geo-tag preferences, wherein the at least one new item is associated with a first portion of geo-tag information comprising a location of the new item and a second portion of geo-tag information comprising a location of the user, wherein the first and second portions of geo-tag information are accessible by the analysis component, and wherein the analysis component determines the at least one new item via an inferential search; a notification component that alerts the user that a match exists between the at least one new item and the user's geo-tag preferences, wherein the first portion of geo-tag information is filtered from view by the user, and wherein the second portion of geo-tag information is accessible by the user; and a mapping component that illustrates directions between the first portion of geo-tag information comprising the location of the new item and the second portion of the geo-tag information comprising the location of the user. 8. The system of claim 1 , wherein the monitor examines the new geo-tagged items for at least one of the type of item being listed or the seller of the item.
| 0.516183 |
18. The method of claim 1 , wherein the method further comprises the step of: generating code that represents the graphical model.
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18. The method of claim 1 , wherein the method further comprises the step of: generating code that represents the graphical model. 19. The method of claim 18 , wherein the code that is generated represents an object oriented code.
| 0.95625 |
10. The method of claim 1 , comprising: computing a distribution of labels in the pre-existing relevance ranking; and relabeling a label associated with the query/URL pairs in the click relevance ranking according to the distribution of labels in the pre-existing relevance ranking, the labels decreasing with respect to click relevance.
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10. The method of claim 1 , comprising: computing a distribution of labels in the pre-existing relevance ranking; and relabeling a label associated with the query/URL pairs in the click relevance ranking according to the distribution of labels in the pre-existing relevance ranking, the labels decreasing with respect to click relevance. 11. The method of claim 10 , comprising: increasing a value of the label associated with a most relevant query/URL pair when the click rate exceeds a specified threshold.
| 0.902785 |
12. A system for collecting metadata for a first multimedia data element, comprising: a plurality of computational cores configured to receive the first multimedia data element, each core having properties to be independent of each other core, each said core generates responsive to the first multimedia data element a first signature element and a second signature element, said first signature element is a robust signature; a storage unit for storing at least one second multimedia data element, metadata associated with said second multimedia data element, and at least one of a first signature and a second signature associated with said second multimedia data element, said first signature is a robust signature; and a comparison unit coupled to said plurality of computational cores and to said storage unit, wherein the comparison unit is configured to compare signatures of multimedia data elements for the purpose of determining matches between multimedia data elements; wherein responsive to receiving the first multimedia data element said plurality of computational cores generate a respective first signature of said first multimedia element and a second signature of said first multimedia data element, for the purpose of determining a match with said at least one second multimedia data element stored in said storage and associating at least a subset of metadata associated with said at least one second multimedia data element with said first multimedia data element.
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12. A system for collecting metadata for a first multimedia data element, comprising: a plurality of computational cores configured to receive the first multimedia data element, each core having properties to be independent of each other core, each said core generates responsive to the first multimedia data element a first signature element and a second signature element, said first signature element is a robust signature; a storage unit for storing at least one second multimedia data element, metadata associated with said second multimedia data element, and at least one of a first signature and a second signature associated with said second multimedia data element, said first signature is a robust signature; and a comparison unit coupled to said plurality of computational cores and to said storage unit, wherein the comparison unit is configured to compare signatures of multimedia data elements for the purpose of determining matches between multimedia data elements; wherein responsive to receiving the first multimedia data element said plurality of computational cores generate a respective first signature of said first multimedia element and a second signature of said first multimedia data element, for the purpose of determining a match with said at least one second multimedia data element stored in said storage and associating at least a subset of metadata associated with said at least one second multimedia data element with said first multimedia data element. 14. The system of claim 12 , wherein said images of signals are images selected from the group consisting of medical signals, geophysical signals, subsonic signals, supersonic signals, electromagnetic signals, and infrared signals.
| 0.596062 |
1. A method comprising: receiving a single input communication from a user in a spoken dialog system; generating, via a processor and in response to the single input communication, a plurality of communication goals, wherein the plurality of communication goals are based on a dialog strategy; generating a plurality of sentence plans corresponding to the plurality of communication goals, wherein each sentence plan of the plurality of sentence plans comprises elementary speech acts and is a viable and potentially usable prompt in response to the single input communication; and presenting to the user a selected sentence plan from the plurality of sentence plans as a response to the single input communication.
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1. A method comprising: receiving a single input communication from a user in a spoken dialog system; generating, via a processor and in response to the single input communication, a plurality of communication goals, wherein the plurality of communication goals are based on a dialog strategy; generating a plurality of sentence plans corresponding to the plurality of communication goals, wherein each sentence plan of the plurality of sentence plans comprises elementary speech acts and is a viable and potentially usable prompt in response to the single input communication; and presenting to the user a selected sentence plan from the plurality of sentence plans as a response to the single input communication. 4. The method of claim 1 , further comprising: realizing the selected sentence plan, wherein realization includes applying a set of linguistic rules to the selected sentence plan.
| 0.677731 |
9. A computer-implemented method, the method comprising: determining a first count of user selections, received by a search engine, of search results that were presented in response to queries that are categorized as referring to a particular site; determining a second count of user selections, received by the search engine, of search results that identify resources in the particular site; and determining a site quality score for the particular site including computing a ratio of a numerator based on the first count and a denominator based on the second count, wherein (i) the numerator is based on the first count reduced by a threshold value which is a predetermined threshold value, (ii) the denominator is based on the second count raised to a power that is greater than zero and less than one, or (iii) both.
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9. A computer-implemented method, the method comprising: determining a first count of user selections, received by a search engine, of search results that were presented in response to queries that are categorized as referring to a particular site; determining a second count of user selections, received by the search engine, of search results that identify resources in the particular site; and determining a site quality score for the particular site including computing a ratio of a numerator based on the first count and a denominator based on the second count, wherein (i) the numerator is based on the first count reduced by a threshold value which is a predetermined threshold value, (ii) the denominator is based on the second count raised to a power that is greater than zero and less than one, or (iii) both. 12. The method of claim 9 , wherein a query is categorized as referring to the particular site when the query is a query that has been determined to be a navigational query to the particular site.
| 0.821558 |
1. A method, comprising: receiving input speech to be decoded; converting a non-back-off language model that assigns a probability to each fixed order n-gram generated with a given vocabulary to a back-off language model that assigns a probability to one or more fixed order n-grams assigned a zero probability by the non-back-off language model by backing off to a given lower order n-gram corresponding to the given fixed order n-gram; and pruning the converted back-off language model; and utilizing the converted back-off language model in a speech decoding process to generate a decoded speech output from the input speech; wherein the converting step comprises, starting with an initial non-back-off language model associated with a lowest order n-gram and hierarchically progressing with one or more higher order non-back-off language models until the fixed order n-gram is reached, converting the initial non-back-off language model and the one or more higher order non-back-off language models into respective back-off language models; wherein the given fixed order n-gram comprises a given word and an associated history; wherein the given lower order n-gram corresponding to the given fixed order n-gram comprises the given word and a truncated version of the associated history; and wherein the method is performed utilizing at least one processing device comprising a processor coupled to a memory.
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1. A method, comprising: receiving input speech to be decoded; converting a non-back-off language model that assigns a probability to each fixed order n-gram generated with a given vocabulary to a back-off language model that assigns a probability to one or more fixed order n-grams assigned a zero probability by the non-back-off language model by backing off to a given lower order n-gram corresponding to the given fixed order n-gram; and pruning the converted back-off language model; and utilizing the converted back-off language model in a speech decoding process to generate a decoded speech output from the input speech; wherein the converting step comprises, starting with an initial non-back-off language model associated with a lowest order n-gram and hierarchically progressing with one or more higher order non-back-off language models until the fixed order n-gram is reached, converting the initial non-back-off language model and the one or more higher order non-back-off language models into respective back-off language models; wherein the given fixed order n-gram comprises a given word and an associated history; wherein the given lower order n-gram corresponding to the given fixed order n-gram comprises the given word and a truncated version of the associated history; and wherein the method is performed utilizing at least one processing device comprising a processor coupled to a memory. 11. The method of claim 1 , wherein the speech decoding process is part of a machine translation system.
| 0.549342 |
8. The method according claim 1 , further comprising providing a user interface for selecting a machine instance on which to perform the first task within the computing environment, and wherein the user interface comprises a dropdown menu, and wherein generating the list of one or more previous machine instances corresponding to the one or more similar tasks comprises displaying the list in the dropdown menu.
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8. The method according claim 1 , further comprising providing a user interface for selecting a machine instance on which to perform the first task within the computing environment, and wherein the user interface comprises a dropdown menu, and wherein generating the list of one or more previous machine instances corresponding to the one or more similar tasks comprises displaying the list in the dropdown menu. 9. The method according to claim 8 , wherein the user interface further comprises a user interface object associated with initiating instructions to commence a previous machine instance selected from the dropdown menu.
| 0.930502 |
55. A computer-implemented method for processing electronically tagged financial data in XBRL format, the method being executed by one or more processors configured to perform a plurality of operations comprising: selecting a plurality of XBRL files, the XBRL files including at least electronically tagged financial data which adhere to different taxonomies that are associated with the same type of content; calculating at least a first common analysis measure for comparison and analysis of electronically tagged financial data from a first file which adheres to a first taxonomy and corresponding electronically tagged financial data from a second file which adheres to a second taxonomy that are associated with the same type of content, including (i) a first formula having components based on the first taxonomy for calculating the first common analysis measure from electronically tagged financial data from the first file, and (ii) a second formula having components based on the second taxonomy for calculating the first common analysis measure from electronically tagged financial data from the second file, wherein the first common analysis measure comprises an analytical metric not present in either the first file or the second file; and presenting information associated with the selected XBRL file, the presented information including data elements and a calculation of at least the first common analysis measure automatically formatted according to presentation information associated with the selected XBRL files so as to provide simultaneous line-by-line display of at least the first calculated common analysis measures that correspond to different taxonomies and another calculated common analysis measure.
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55. A computer-implemented method for processing electronically tagged financial data in XBRL format, the method being executed by one or more processors configured to perform a plurality of operations comprising: selecting a plurality of XBRL files, the XBRL files including at least electronically tagged financial data which adhere to different taxonomies that are associated with the same type of content; calculating at least a first common analysis measure for comparison and analysis of electronically tagged financial data from a first file which adheres to a first taxonomy and corresponding electronically tagged financial data from a second file which adheres to a second taxonomy that are associated with the same type of content, including (i) a first formula having components based on the first taxonomy for calculating the first common analysis measure from electronically tagged financial data from the first file, and (ii) a second formula having components based on the second taxonomy for calculating the first common analysis measure from electronically tagged financial data from the second file, wherein the first common analysis measure comprises an analytical metric not present in either the first file or the second file; and presenting information associated with the selected XBRL file, the presented information including data elements and a calculation of at least the first common analysis measure automatically formatted according to presentation information associated with the selected XBRL files so as to provide simultaneous line-by-line display of at least the first calculated common analysis measures that correspond to different taxonomies and another calculated common analysis measure. 71. The computer-implemented method of claim 55 , further comprising retrieving updated analysis information after a publication date of at least one of the selected XBRL file, generating analysis based on the updated analysis information and replacing presented information with the updated analysis information.
| 0.637977 |
32. A computer-implemented method, comprising: receiving a highlighted passage of a digital work, wherein the digital work comprises a plurality of passages that includes the highlighted passage; receiving a question pertaining to the highlighted passage; comparing the first question to a plurality of questions that pertain to the highlighted passage, wherein comparing the question to the plurality of questions further comprises comparing one or more words of the question to the plurality of questions that pertain to the highlighted passage; and grouping the question and the plurality of questions in one or more groups based at least in part on the comparing the question to the plurality of questions.
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32. A computer-implemented method, comprising: receiving a highlighted passage of a digital work, wherein the digital work comprises a plurality of passages that includes the highlighted passage; receiving a question pertaining to the highlighted passage; comparing the first question to a plurality of questions that pertain to the highlighted passage, wherein comparing the question to the plurality of questions further comprises comparing one or more words of the question to the plurality of questions that pertain to the highlighted passage; and grouping the question and the plurality of questions in one or more groups based at least in part on the comparing the question to the plurality of questions. 36. The computer-implemented method of claim 32 , wherein the highlighted passage is highlighted by a first user, and the question is crafted by a second user.
| 0.835626 |
1. A method of improving classification accuracy and reducing false positives in data mining, computer aided-detection, computer-aided diagnosis and artificial intelligence, the method comprising: choosing a training set from a set of training cases using systematic data scaling, the training set including one or more training cases for true nodules and one or more training cases for false nodules, the systematic data scaling removing only one or more training cases for false nodules, which is proximate a classification boundary for true and false nodules, from the training set; and, creating a classifier based on the training set using a classification method, wherein the systematic data scaling method and the classification method produce the classifier thereby reducing false positives and improving classification accuracy.
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1. A method of improving classification accuracy and reducing false positives in data mining, computer aided-detection, computer-aided diagnosis and artificial intelligence, the method comprising: choosing a training set from a set of training cases using systematic data scaling, the training set including one or more training cases for true nodules and one or more training cases for false nodules, the systematic data scaling removing only one or more training cases for false nodules, which is proximate a classification boundary for true and false nodules, from the training set; and, creating a classifier based on the training set using a classification method, wherein the systematic data scaling method and the classification method produce the classifier thereby reducing false positives and improving classification accuracy. 3. The method according to claim 1 , the method further comprising evaluating the classifier produced by the classification method based on the training set using a testing set.
| 0.581923 |
1. A method for a user to create a report through voice output, comprising: (a) receiving by a computer information from user input via a user input device; (b) processing by the computer the information, wherein said processing step utilizes a heuristic algorithm; (c) performing by the computer a task resultant from said processing step, wherein said performing step further comprises a step of making a heuristic selection of one or more macros from a macro library; (d) preparing by the computer a response based on said performing step; (e) communicating the response as voice output verbalized through use of a voice output device; and (f) repeating said steps (a)-(e) until the report is completed.
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1. A method for a user to create a report through voice output, comprising: (a) receiving by a computer information from user input via a user input device; (b) processing by the computer the information, wherein said processing step utilizes a heuristic algorithm; (c) performing by the computer a task resultant from said processing step, wherein said performing step further comprises a step of making a heuristic selection of one or more macros from a macro library; (d) preparing by the computer a response based on said performing step; (e) communicating the response as voice output verbalized through use of a voice output device; and (f) repeating said steps (a)-(e) until the report is completed. 13. The method of claim 1 , wherein said communicating step further comprises the step of listing partially matching macros.
| 0.535067 |
1. A system for implementing a sliding input of a text based upon an on-screen soft keyboard on an electronic equipment, characterized in that, said system comprises: a memory device configured to store ideal sliding trajectory features for words; and a processor coupled to the memory device, the processor being configured to: record user-sliding trajectories and convert the recorded user-sliding trajectories into a user-sliding trajectory feature set; filter in the memory device and originally choose the words, wherein each of the originally chosen words has similar ideal sliding trajectory features with the user-sliding trajectory feature set; calculate a similarity between the ideal sliding trajectory features of each originally chosen word and said user-sliding trajectory features set according to key points on said trajectory, comprising the steps of: calculating a rough similarity between the ideal sliding trajectory features of each originally chosen word and said user-sliding trajectory features set, wherein said step of calculating the rough similarity comprises calculating a linear matching distance between the ideal trajectory of each originally chosen word and said user-sliding trajectory feature set; and calculating an accurate similarity between the ideal sliding trajectory features of each word obtained from the rough similarity calculation result and said user-sliding trajectory features set; obtain candidate words according to the similarity, wherein the ideal sliding trajectory of each candidate word contains at least one of the key points or at least one of the surrounding points of at least one of the key points on said user-sliding trajectory; and display said candidate words.
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1. A system for implementing a sliding input of a text based upon an on-screen soft keyboard on an electronic equipment, characterized in that, said system comprises: a memory device configured to store ideal sliding trajectory features for words; and a processor coupled to the memory device, the processor being configured to: record user-sliding trajectories and convert the recorded user-sliding trajectories into a user-sliding trajectory feature set; filter in the memory device and originally choose the words, wherein each of the originally chosen words has similar ideal sliding trajectory features with the user-sliding trajectory feature set; calculate a similarity between the ideal sliding trajectory features of each originally chosen word and said user-sliding trajectory features set according to key points on said trajectory, comprising the steps of: calculating a rough similarity between the ideal sliding trajectory features of each originally chosen word and said user-sliding trajectory features set, wherein said step of calculating the rough similarity comprises calculating a linear matching distance between the ideal trajectory of each originally chosen word and said user-sliding trajectory feature set; and calculating an accurate similarity between the ideal sliding trajectory features of each word obtained from the rough similarity calculation result and said user-sliding trajectory features set; obtain candidate words according to the similarity, wherein the ideal sliding trajectory of each candidate word contains at least one of the key points or at least one of the surrounding points of at least one of the key points on said user-sliding trajectory; and display said candidate words. 2. The system according to claim 1 , characterized in that, said processor is further configured to: calculate a rough matching degree between words stored in said memory device according to the ideal sliding trajectory features and said user-sliding trajectory features set.
| 0.558086 |
21. A computer program product encoded on one or more non-transitory computer storage media, the computer program product storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a search query; obtaining a plurality of search results for the search query from a search engine, wherein each search result identifies a respective search result resource, and wherein the plurality of search results includes one or more search results that identify search result resources that are in a particular site; using a site quality score for the particular site to rank the plurality of search results; and determining the site quality score for the particular site, comprising: determining a numerator that is a function of a first count of textually unique queries submitted to the search engine that have been categorized as referring to the particular site, wherein each such textually unique query is counted once in the first count; determining a denominator that is a function of a second count of textually unique queries submitted to the search engine that have been associated with resources in the particular sites, wherein each such textually unique query is counted once in the second count; and determining the site quality score for the particular site as a ratio of the numerator and the denominator.
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21. A computer program product encoded on one or more non-transitory computer storage media, the computer program product storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a search query; obtaining a plurality of search results for the search query from a search engine, wherein each search result identifies a respective search result resource, and wherein the plurality of search results includes one or more search results that identify search result resources that are in a particular site; using a site quality score for the particular site to rank the plurality of search results; and determining the site quality score for the particular site, comprising: determining a numerator that is a function of a first count of textually unique queries submitted to the search engine that have been categorized as referring to the particular site, wherein each such textually unique query is counted once in the first count; determining a denominator that is a function of a second count of textually unique queries submitted to the search engine that have been associated with resources in the particular sites, wherein each such textually unique query is counted once in the second count; and determining the site quality score for the particular site as a ratio of the numerator and the denominator. 22. The computer program product of claim 21 , wherein using the site quality score for the particular site to rank the plurality of search results comprises: using the site quality score as a term in a computation of a respective ranking score for each of the search result resources that are in the particular site.
| 0.5 |
1. A computer-implemented method performed by a data processing apparatus, the method comprising: receiving audio data that corresponds to an utterance; obtaining a first transcription of the utterance that was generated using a limited speech recognizer, wherein the limited speech recognizer comprises a speech recognizer that includes a language model that is trained over a limited speech recognition vocabulary that includes one or more terms from a voice command grammar, but that includes fewer than all terms of an expanded grammar; obtaining a second transcription of the utterance that was generated using an expanded speech recognizer, wherein the expanded speech recognizer comprises a speech recognizer that includes a language model that is trained over an expanded speech recognition vocabulary that includes all of the terms of the expanded grammar; aligning the first and second transcriptions of the utterance to generate an aligned transcription; and classifying the utterance, based at least on a portion of the aligned transcription, as a voice command or a voice query.
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1. A computer-implemented method performed by a data processing apparatus, the method comprising: receiving audio data that corresponds to an utterance; obtaining a first transcription of the utterance that was generated using a limited speech recognizer, wherein the limited speech recognizer comprises a speech recognizer that includes a language model that is trained over a limited speech recognition vocabulary that includes one or more terms from a voice command grammar, but that includes fewer than all terms of an expanded grammar; obtaining a second transcription of the utterance that was generated using an expanded speech recognizer, wherein the expanded speech recognizer comprises a speech recognizer that includes a language model that is trained over an expanded speech recognition vocabulary that includes all of the terms of the expanded grammar; aligning the first and second transcriptions of the utterance to generate an aligned transcription; and classifying the utterance, based at least on a portion of the aligned transcription, as a voice command or a voice query. 5. The method of claim 1 , wherein the expanded speech recognizer is configured to recognize one or more of a collection of general grammar terms, a collection of placeholder terms, a collection of proper names, and a collection of voice command terms.
| 0.650672 |
20. A computer-implemented method, comprising: receiving texts from each of a plurality of text sources, wherein each text source provides a text; deriving a plurality of name-context pairs from the texts, wherein each name-context pair comprises an entity name included in the text from a text source and a context term included in the text from the text source, wherein each entity name is one or more terms used to refer to a respective entity and each context term is a term that appears in text associated with the entity name; calculating a context consistency measure for each distinct name-context pair, wherein the context consistency measure for a particular name-context pair is an estimate of a probability that, if the entity name of the particular name-context pair appears in text, the context term of the particular name-context pair will also appear in the text; and storing context-entity name data, wherein the context-entity name data is searchable data that represents one or more of the distinct name-context pairs and the context consistency measure for each of the one or more name-context pair.
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20. A computer-implemented method, comprising: receiving texts from each of a plurality of text sources, wherein each text source provides a text; deriving a plurality of name-context pairs from the texts, wherein each name-context pair comprises an entity name included in the text from a text source and a context term included in the text from the text source, wherein each entity name is one or more terms used to refer to a respective entity and each context term is a term that appears in text associated with the entity name; calculating a context consistency measure for each distinct name-context pair, wherein the context consistency measure for a particular name-context pair is an estimate of a probability that, if the entity name of the particular name-context pair appears in text, the context term of the particular name-context pair will also appear in the text; and storing context-entity name data, wherein the context-entity name data is searchable data that represents one or more of the distinct name-context pairs and the context consistency measure for each of the one or more name-context pair. 21. The method of claim 20 , wherein the context-entity name data maps each context term in the name-context pairs to a list of entity names and the context consistency measure for each entity name.
| 0.585554 |
30. A non-transitory machine readable storage medium having stored thereon data representing sequences of instructions, which when executed by a server, cause the server to: collect product reviews for a plurality of products, wherein a respective product review provides a critical, subjective evaluation of a corresponding product by a human in electronic form; automatically identify particular products that are associated with particular product reviews; for each particular product in at least a subset of the plurality of products, automatically generate aggregated review information for the particular product including frequently appearing phrases in the product reviews associated with the particular product; automatically store the product reviews and the aggregated review information; receive a request from a client for an aggregated review of a product, the aggregated review of the product including portions of extracted product reviews of the product; and send the aggregated review of the product in response to the request, wherein the aggregated review of the product includes a list of server-suggested search terms that are automatically selected from extracted product reviews of the product in accordance with their respective weighted occurrences in the extracted product reviews of the product.
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30. A non-transitory machine readable storage medium having stored thereon data representing sequences of instructions, which when executed by a server, cause the server to: collect product reviews for a plurality of products, wherein a respective product review provides a critical, subjective evaluation of a corresponding product by a human in electronic form; automatically identify particular products that are associated with particular product reviews; for each particular product in at least a subset of the plurality of products, automatically generate aggregated review information for the particular product including frequently appearing phrases in the product reviews associated with the particular product; automatically store the product reviews and the aggregated review information; receive a request from a client for an aggregated review of a product, the aggregated review of the product including portions of extracted product reviews of the product; and send the aggregated review of the product in response to the request, wherein the aggregated review of the product includes a list of server-suggested search terms that are automatically selected from extracted product reviews of the product in accordance with their respective weighted occurrences in the extracted product reviews of the product. 35. The non-transitory machine readable storage medium of claim 30 , wherein the data representing sequences of instructions include instructions that when executed by the server cause the server to automatically identify a particular product that is associated with particular product reviews by associating a brand name and a model number in the particular product reviews with a particular product.
| 0.5 |
1. A method for creating a mnemonic experience for a user, which comprises: selecting a concentration of information to be remembered; gathering information on said concentration, said information being intended to be remembered by the user; providing a building; placing a display to be observed in said building, said display teaching said information when observed by the user; providing a character to interact with the user and said display, said character being contextually related to said display; interacting said character with the user with while the user observes said display; gathering further information on said concentration; determining an importance of said information relative to an importance of said further information; and not creating a display of said further information when said importance of said further information is less than the importance of said piece of information.
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1. A method for creating a mnemonic experience for a user, which comprises: selecting a concentration of information to be remembered; gathering information on said concentration, said information being intended to be remembered by the user; providing a building; placing a display to be observed in said building, said display teaching said information when observed by the user; providing a character to interact with the user and said display, said character being contextually related to said display; interacting said character with the user with while the user observes said display; gathering further information on said concentration; determining an importance of said information relative to an importance of said further information; and not creating a display of said further information when said importance of said further information is less than the importance of said piece of information. 5. The method according to claim 1 , wherein said information is the same as said display.
| 0.711788 |
1. A distributed computer system implemented method comprising: extracting, by a computer system, identifiers from URLs, each of the identifiers identifying an entity associated with a URL from among the URLs; classifying the extracted identifiers of the URLs as parent identifiers and child identifiers; designating, by the computer system, a sequence of identifiers as attributable for a URL from among the URLs by: (1) determining whether any of one or more child identifiers of a parent identifier of the URLs account for more than a threshold percentage of traffic flowing from the computer system to an entity associated with the parent identifier, (2) responsive to a negative determination, designating a sequence of identifiers including the parent identifier as attributable, and (3) responsive to a positive determination, designating a sequence of identifiers including the one or more child identifiers as attributable; and attributing responsibility for each of the URLs to the entity associated with one of the designated attributable sequences of the URL.
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1. A distributed computer system implemented method comprising: extracting, by a computer system, identifiers from URLs, each of the identifiers identifying an entity associated with a URL from among the URLs; classifying the extracted identifiers of the URLs as parent identifiers and child identifiers; designating, by the computer system, a sequence of identifiers as attributable for a URL from among the URLs by: (1) determining whether any of one or more child identifiers of a parent identifier of the URLs account for more than a threshold percentage of traffic flowing from the computer system to an entity associated with the parent identifier, (2) responsive to a negative determination, designating a sequence of identifiers including the parent identifier as attributable, and (3) responsive to a positive determination, designating a sequence of identifiers including the one or more child identifiers as attributable; and attributing responsibility for each of the URLs to the entity associated with one of the designated attributable sequences of the URL. 15. The distributed computer system implemented method of claim 1 , wherein the attributable sequence is associated with a hosting provider.
| 0.677727 |
1. A computer-implemented method for publishing a learning application in a modular learning system by a user device, the method comprising steps of: receiving, by a learning application publishing management module, over a network, a plurality of learning application authoring requests from a plurality of user devices each operated by one of a plurality of authoring users; validating, by an authentication module, authoring user credentials of each of the authoring users upon receiving the plurality of learning application authoring requests; providing, by a content editing interface generator, an electronic content editing interface for display on a video display to each of the authoring users over the network; managing, by a collaboration module, access by at least some of the authoring users to an electronic learning application template having a learning framework comprising a choice of modes for a selected learning application in an electronic learning application template database; receiving a request over the network, by one of the authoring users, via the content editing interface to edit the selected learning application and, responsive thereto, accessing by the content editing interface identifier items and electronic interface items associated with the template from the learning application template database, the selected learning application including media metadata; authorizing, by the authentication module, at least one other of the authoring users to edit the selected learning application simultaneously with the editing by the requested one of the authoring users via the corresponding content editing interface accessed by the at least one other of the authoring users; dynamically updating, by a dynamic updation module, content metadata associated with the selected learning application with a plurality of updated metadata, the updated metadata comprising at least one of media metadata, language metadata, certification metadata, learning facility compatibility metadata and tutor compatibility metadata provided by different users of modular learning system over the network, the content metadata describing parameters for performance of the selected learning application; generating, by the dynamic updation module, an update notification responsive to new electronic media being added to an external computer source referenced by media metadata of the selected learning application; dynamically updating, by the dynamic updation module, the media metadata associated with the selected learning application responsive to generating the update notification; storing, by a learning application storage module, the selected learning application including the updated content metadata, the updated media metadata, and the edited identifier items, the selected learning application conforming to the learning application template having a learning framework comprising the choice of modes; determining, by the dynamic updation module, whether a translation or certification is requested by the learning application authoring user from a translating or certifying user, by choosing a preferred translation or certification through an interface generated by generator on the user device operated by the learning application authoring user; if the translation or certification of the learning application is requested by authoring user, reviewing the updated language metadata, or certification metadata of the learning application and adding the updated metadata, or certification metadata to the learning application metadata stored in learning application storage module; receiving, by the learning application publishing module, a publishing request from the one of the authoring users over the network; generating and displaying, by the content editing interface generator, a pricing terms input interface with corresponding areas to be filled in by the authoring user via the user device operated by the authoring user; determining an approval status of the selected learning application from a modular learning system provider; responsive to the approval status being approved, publishing by the learning application publishing module, the selected learning application to a computer-based learning user marketplace or computer-based learning user library; allowing, by a learning application performance analytics module, the selected learning application to be performed by at least one learning user and monitored by at least one tutoring user, wherein the performance of the learning application includes receiving a review request via a review module from the learning user and the monitoring of the learning application includes receiving a review request from the tutoring user to update the content of the learning application; and generating, by the review module, a plurality of review request interface items each associated with the review request from the performance of the selected learning application by the learning user or from the monitoring of the selected learning application by the tutoring user, and displaying the plurality of review request interface items on an interface of the user device of the requesting authoring user.
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1. A computer-implemented method for publishing a learning application in a modular learning system by a user device, the method comprising steps of: receiving, by a learning application publishing management module, over a network, a plurality of learning application authoring requests from a plurality of user devices each operated by one of a plurality of authoring users; validating, by an authentication module, authoring user credentials of each of the authoring users upon receiving the plurality of learning application authoring requests; providing, by a content editing interface generator, an electronic content editing interface for display on a video display to each of the authoring users over the network; managing, by a collaboration module, access by at least some of the authoring users to an electronic learning application template having a learning framework comprising a choice of modes for a selected learning application in an electronic learning application template database; receiving a request over the network, by one of the authoring users, via the content editing interface to edit the selected learning application and, responsive thereto, accessing by the content editing interface identifier items and electronic interface items associated with the template from the learning application template database, the selected learning application including media metadata; authorizing, by the authentication module, at least one other of the authoring users to edit the selected learning application simultaneously with the editing by the requested one of the authoring users via the corresponding content editing interface accessed by the at least one other of the authoring users; dynamically updating, by a dynamic updation module, content metadata associated with the selected learning application with a plurality of updated metadata, the updated metadata comprising at least one of media metadata, language metadata, certification metadata, learning facility compatibility metadata and tutor compatibility metadata provided by different users of modular learning system over the network, the content metadata describing parameters for performance of the selected learning application; generating, by the dynamic updation module, an update notification responsive to new electronic media being added to an external computer source referenced by media metadata of the selected learning application; dynamically updating, by the dynamic updation module, the media metadata associated with the selected learning application responsive to generating the update notification; storing, by a learning application storage module, the selected learning application including the updated content metadata, the updated media metadata, and the edited identifier items, the selected learning application conforming to the learning application template having a learning framework comprising the choice of modes; determining, by the dynamic updation module, whether a translation or certification is requested by the learning application authoring user from a translating or certifying user, by choosing a preferred translation or certification through an interface generated by generator on the user device operated by the learning application authoring user; if the translation or certification of the learning application is requested by authoring user, reviewing the updated language metadata, or certification metadata of the learning application and adding the updated metadata, or certification metadata to the learning application metadata stored in learning application storage module; receiving, by the learning application publishing module, a publishing request from the one of the authoring users over the network; generating and displaying, by the content editing interface generator, a pricing terms input interface with corresponding areas to be filled in by the authoring user via the user device operated by the authoring user; determining an approval status of the selected learning application from a modular learning system provider; responsive to the approval status being approved, publishing by the learning application publishing module, the selected learning application to a computer-based learning user marketplace or computer-based learning user library; allowing, by a learning application performance analytics module, the selected learning application to be performed by at least one learning user and monitored by at least one tutoring user, wherein the performance of the learning application includes receiving a review request via a review module from the learning user and the monitoring of the learning application includes receiving a review request from the tutoring user to update the content of the learning application; and generating, by the review module, a plurality of review request interface items each associated with the review request from the performance of the selected learning application by the learning user or from the monitoring of the selected learning application by the tutoring user, and displaying the plurality of review request interface items on an interface of the user device of the requesting authoring user. 3. The computer-implemented method of claim 1 , wherein the learning application includes additional metadata, and the approval status is determined based on consistency between the content metadata and the additional metadata.
| 0.806452 |
8. A system comprising: a processor; and a computer-readable storage device having instructions stored for controlling the processor to perform operations comprising: receiving data associated with a dialog between a human and a non-human automated spoken dialog service of a service provider, the data being associated with a geographic area; analyzing the data to identify trends for the geographic area to yield identified trends; comparing the identified trends for the geographic area with an average in a wider geographic area containing the geographic area, to yield a comparison; generating top trends headlines based on the identified trends and the comparison which exceed a threshold value; identifying event data for the geographic area affecting operations of the service provider and outside a control of the service provider, the event data being one of weather data and natural disaster data; and modifying the non-human automated spoken dialog service based on the top trends headlines and the event data.
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8. A system comprising: a processor; and a computer-readable storage device having instructions stored for controlling the processor to perform operations comprising: receiving data associated with a dialog between a human and a non-human automated spoken dialog service of a service provider, the data being associated with a geographic area; analyzing the data to identify trends for the geographic area to yield identified trends; comparing the identified trends for the geographic area with an average in a wider geographic area containing the geographic area, to yield a comparison; generating top trends headlines based on the identified trends and the comparison which exceed a threshold value; identifying event data for the geographic area affecting operations of the service provider and outside a control of the service provider, the event data being one of weather data and natural disaster data; and modifying the non-human automated spoken dialog service based on the top trends headlines and the event data. 11. The system of claim 8 , wherein the identified trends relate to user patterns within the geographic area.
| 0.547373 |
25. A machine-readable storage medium storing executable instructions to cause a machine to perform a machine-implemented method comprising: receiving first search input within a search field of a web browser application; determining, based on characteristics of the first search input, whether the first search input triggers an automatic submission of a first query to a search engine; determining, based on characteristics of the first search input, whether to delay the trigger for automatic submission, wherein the first query is automatically submitted to the search engine if the first search input satisfies a temporal trigger, wherein the temporal trigger is based upon a connection speed to the search engine; automatically submitting the first query to the search engine, the first query based on the received first search input; and displaying, within the web browser application, a first results web page returned from the first query submitted to the search engine.
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25. A machine-readable storage medium storing executable instructions to cause a machine to perform a machine-implemented method comprising: receiving first search input within a search field of a web browser application; determining, based on characteristics of the first search input, whether the first search input triggers an automatic submission of a first query to a search engine; determining, based on characteristics of the first search input, whether to delay the trigger for automatic submission, wherein the first query is automatically submitted to the search engine if the first search input satisfies a temporal trigger, wherein the temporal trigger is based upon a connection speed to the search engine; automatically submitting the first query to the search engine, the first query based on the received first search input; and displaying, within the web browser application, a first results web page returned from the first query submitted to the search engine. 30. The machine-readable storage medium of claim 25 , wherein the method further comprises: receiving second search input within the search field, the second search input added to the first search input to create cumulative search input; determining, based on characteristics of the cumulative search input, whether the cumulative search input triggers an automatic submission of a second query to a search engine; determining, based on characteristics of the cumulative search input, whether to delay the trigger for automatic transmission; automatically submitting the second query to the search engine, the second query based on the cumulative search input; and displaying, within the web browser application, a second results web page returned from the second query submitted to the search engine, wherein the second results web page replaces the first results web page.
| 0.5 |
12. A computer system for editing a form calculation, the system comprising: a processor; a memory unit that stores instructions associated with an application executed by the processor; and an interconnect coupling the processor and the memory unit; enabling the computer system to execute the application and perform operations of: displaying a user interface for displaying information to a user and for accepting input from the user; displaying a hyperlink on the user interface for an element in the form calculation, the form calculation being a spreadsheet and the form calculation including a mathematical formula, displaying the hyperlink to indicate to the user that a control is available for the element, the hyperlink including at least one hyperlink target, the hyperlink target identified by a link to a choice satisfying the element on the form calculation, the hyperlink providing one of the group consisting of (i) a link from the form calculation to another location, wherein the another location is identified by a reference to valid variables in the hyperlink target and (ii) a link from the form calculation to another file, wherein the another file is identified by a reference to a selection of choices in the hyperlink target; upon a selection of the hyperlink by the user, displaying the control on the user interface for user interaction, the control including a list of choices satisfying the element in the form calculation; receiving a selection from the list of choices through the user interface: and upon completion of user interaction with the control, and in response to receiving the selection, replacing the element with a new element corresponding to the selection, displaying the hyperlink for the new element in the form calculation, and causing the control to disappear from view.
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12. A computer system for editing a form calculation, the system comprising: a processor; a memory unit that stores instructions associated with an application executed by the processor; and an interconnect coupling the processor and the memory unit; enabling the computer system to execute the application and perform operations of: displaying a user interface for displaying information to a user and for accepting input from the user; displaying a hyperlink on the user interface for an element in the form calculation, the form calculation being a spreadsheet and the form calculation including a mathematical formula, displaying the hyperlink to indicate to the user that a control is available for the element, the hyperlink including at least one hyperlink target, the hyperlink target identified by a link to a choice satisfying the element on the form calculation, the hyperlink providing one of the group consisting of (i) a link from the form calculation to another location, wherein the another location is identified by a reference to valid variables in the hyperlink target and (ii) a link from the form calculation to another file, wherein the another file is identified by a reference to a selection of choices in the hyperlink target; upon a selection of the hyperlink by the user, displaying the control on the user interface for user interaction, the control including a list of choices satisfying the element in the form calculation; receiving a selection from the list of choices through the user interface: and upon completion of user interaction with the control, and in response to receiving the selection, replacing the element with a new element corresponding to the selection, displaying the hyperlink for the new element in the form calculation, and causing the control to disappear from view. 14. The computer system of claim 12 , wherein the control is a dialog box.
| 0.70742 |
3. A method in a computing device for automatically identifying keywords for advertisement placement, the method comprising: extracting one or more keywords from a data feed, the data feed providing information about one or more content data; for each extracted keyword, identifying, facilitated by a computer processor, a category of products to advertise with the extracted keyword from among a plurality of categories of products, the products being related to the keyword but the category being independent of a subject of the keyword, the identification based at least in part on (1) an expected benefit of advertising in a first of the plurality of categories of products and (2) at least one attribute of text contained in at least one product of a second of the plurality of categories of products, the identification including selecting from among the first and the second of the plurality of categories of products based at least in part on scores determined for the expected benefit and the text, the scores normalized to facilitate comparison; generating a link for a landing page for the extracted keyword, the landing page for displaying search results of a query of the identified category based at least in part on the extracted keyword; and generating a creative for the extracted keyword; and submitting to an advertisement placement service an extracted keyword, the link for the extracted keyword, and the creative for the extracted keyword.
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3. A method in a computing device for automatically identifying keywords for advertisement placement, the method comprising: extracting one or more keywords from a data feed, the data feed providing information about one or more content data; for each extracted keyword, identifying, facilitated by a computer processor, a category of products to advertise with the extracted keyword from among a plurality of categories of products, the products being related to the keyword but the category being independent of a subject of the keyword, the identification based at least in part on (1) an expected benefit of advertising in a first of the plurality of categories of products and (2) at least one attribute of text contained in at least one product of a second of the plurality of categories of products, the identification including selecting from among the first and the second of the plurality of categories of products based at least in part on scores determined for the expected benefit and the text, the scores normalized to facilitate comparison; generating a link for a landing page for the extracted keyword, the landing page for displaying search results of a query of the identified category based at least in part on the extracted keyword; and generating a creative for the extracted keyword; and submitting to an advertisement placement service an extracted keyword, the link for the extracted keyword, and the creative for the extracted keyword. 8. The method of claim 3 wherein a multiplicity of keywords are extracted from a data feed and wherein submissions to an advertisement placement service are made for those keywords that satisfy an advertisement submission criterion.
| 0.592435 |
1. A method for detecting relevant stimuli using pupillary response as a correlate to cognitive response, comprising: providing a classifier, said classifier trained to detect patterns of spatio-temporal pupil features and generate an output indicative of the occurrence or absence of a relevant stimulus that evokes both a cognitive response and a pupillary response in a subject; using a sensor to measure the pupillary response of a subject subjected to stimuli in an environment, wherein the occurrence of a relevant stimulus is initially unknown to the classifier; deriving data samples d(n) of the pupil diameter from the pupillary response; segmenting the data samples d(n) into a sequence of time-shifted windows, each window including a response period and a baseline period; extracting a plurality of spatio-temporal pupil features from the data samples d(n) in said response and baseline periods in each said window; and for each said window, presenting the extracted pupil features to the classifier to generate an output indicative of the occurrence or absence of a relevant stimulus.
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1. A method for detecting relevant stimuli using pupillary response as a correlate to cognitive response, comprising: providing a classifier, said classifier trained to detect patterns of spatio-temporal pupil features and generate an output indicative of the occurrence or absence of a relevant stimulus that evokes both a cognitive response and a pupillary response in a subject; using a sensor to measure the pupillary response of a subject subjected to stimuli in an environment, wherein the occurrence of a relevant stimulus is initially unknown to the classifier; deriving data samples d(n) of the pupil diameter from the pupillary response; segmenting the data samples d(n) into a sequence of time-shifted windows, each window including a response period and a baseline period; extracting a plurality of spatio-temporal pupil features from the data samples d(n) in said response and baseline periods in each said window; and for each said window, presenting the extracted pupil features to the classifier to generate an output indicative of the occurrence or absence of a relevant stimulus. 12. The method of claim 1 , wherein the output is paired with a sample of interest d(n) at the leading edge of the window, said response period being the immediately preceding X samples d(n) and said baseline period being the Y samples preceding the response period.
| 0.610241 |
1. A system comprising: a communication module, implemented using one or more processors, that is configured to receive a query, over a network, from a client machine, the query including at least one keyword; and a search engine, implemented using one or more processors, that is configured to identify a filter context based on the query, the filter context including a first plurality of filters, the first plurality of filters including a plurality of attribute-value pairs, the plurality of attribute-value pairs including a first attribute-value pair including a first filter and a second attribute-value pair including a second filter, identify a second plurality of filters responsive to receipt of the query, the second plurality of filters identified based on the filter context and probabilities that describe occurrences of attribute-value pairs in a first plurality of listings that respectively describe items that were previously transacted on a network-based marketplace, and generate a user interface including search results that are identified based on the filter context, the communication module to communicate the user interface, over the network, to the client machine.
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1. A system comprising: a communication module, implemented using one or more processors, that is configured to receive a query, over a network, from a client machine, the query including at least one keyword; and a search engine, implemented using one or more processors, that is configured to identify a filter context based on the query, the filter context including a first plurality of filters, the first plurality of filters including a plurality of attribute-value pairs, the plurality of attribute-value pairs including a first attribute-value pair including a first filter and a second attribute-value pair including a second filter, identify a second plurality of filters responsive to receipt of the query, the second plurality of filters identified based on the filter context and probabilities that describe occurrences of attribute-value pairs in a first plurality of listings that respectively describe items that were previously transacted on a network-based marketplace, and generate a user interface including search results that are identified based on the filter context, the communication module to communicate the user interface, over the network, to the client machine. 2. The system of claim 1 , wherein the second plurality of filters includes a third filter that includes a third attribute and a third value.
| 0.554185 |
8. A system for sharing between friends a dictionary used to generate prediction candidates for converting user input data to language characters, comprising: a first user device for receiving input data from a first user; and a second user device for receiving input data from a second user, wherein the first and second users are communicating with one another during a conversation, wherein the input data comprises a term not yet included in either of a personal dictionary of the first user and a persona dictionary of the second user; wherein input data received in the first user device from the first user generates prediction candidates for converting the input data received in the first user device from the first user, the personal dictionary of the first user is updated as a result of the first user confirming one or more of the prediction candidates, and wherein the one or more prediction candidates that are confirmed by the first user are shared with the second user device of the second user during the same conversation such that during the same conversation input data received from the second user on the second user device is automatically changed during the same conversation using entries in the personal dictionary of the second user having been updated based on the shared one or more prediction candidates confirmed by the first user.
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8. A system for sharing between friends a dictionary used to generate prediction candidates for converting user input data to language characters, comprising: a first user device for receiving input data from a first user; and a second user device for receiving input data from a second user, wherein the first and second users are communicating with one another during a conversation, wherein the input data comprises a term not yet included in either of a personal dictionary of the first user and a persona dictionary of the second user; wherein input data received in the first user device from the first user generates prediction candidates for converting the input data received in the first user device from the first user, the personal dictionary of the first user is updated as a result of the first user confirming one or more of the prediction candidates, and wherein the one or more prediction candidates that are confirmed by the first user are shared with the second user device of the second user during the same conversation such that during the same conversation input data received from the second user on the second user device is automatically changed during the same conversation using entries in the personal dictionary of the second user having been updated based on the shared one or more prediction candidates confirmed by the first user. 9. The system of claim 8 , wherein first user device initiates a communication session with the second user device, and wherein the dictionary shared by at least the first user and the second user includes an aggregate of input history associated with at least the first user and the second user.
| 0.515924 |
1. An information retrieval apparatus, comprising: an input unit for inputting characters; a database for storing a name, an attribute word associated with the name, and a degree of relevance indicating a degree of relevance between the name and the attribute word; a name retrieval unit for retrieving a name including the input characters from the database to output the retrieved name as a candidate name; an attribute word generating unit for extracting an attribute word associated with the candidate name output from the name retrieval unit from the database; and an output unit for displaying the attribute word extracted by the attribute word generating unit and the candidate name from the name retrieval unit, wherein: the attribute word generating unit is configured to: obtain a degree of relevance of the candidate name associated with the attribute word from the database with respect to a combination of the extracted attribute words; calculate a degree of independency indicating a degree of difference between the extracted attribute words; calculate a degree of coverage indicating an extent to which the combination of the extracted attribute words covers the candidate names; and calculate a degree of equality indicating uniformity of a number of corresponding candidate names for each attribute word; the attribute word generating unit comprises a first score calculating unit for calculating a score of the combination of the attribute words based on at least one of the calculated degree of independency, the calculated degree of coverage and the calculated degree of equality; and the attribute word generating unit outputs the combinations of the attribute words to the output unit in a descending order of the score.
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1. An information retrieval apparatus, comprising: an input unit for inputting characters; a database for storing a name, an attribute word associated with the name, and a degree of relevance indicating a degree of relevance between the name and the attribute word; a name retrieval unit for retrieving a name including the input characters from the database to output the retrieved name as a candidate name; an attribute word generating unit for extracting an attribute word associated with the candidate name output from the name retrieval unit from the database; and an output unit for displaying the attribute word extracted by the attribute word generating unit and the candidate name from the name retrieval unit, wherein: the attribute word generating unit is configured to: obtain a degree of relevance of the candidate name associated with the attribute word from the database with respect to a combination of the extracted attribute words; calculate a degree of independency indicating a degree of difference between the extracted attribute words; calculate a degree of coverage indicating an extent to which the combination of the extracted attribute words covers the candidate names; and calculate a degree of equality indicating uniformity of a number of corresponding candidate names for each attribute word; the attribute word generating unit comprises a first score calculating unit for calculating a score of the combination of the attribute words based on at least one of the calculated degree of independency, the calculated degree of coverage and the calculated degree of equality; and the attribute word generating unit outputs the combinations of the attribute words to the output unit in a descending order of the score. 2. The information retrieval apparatus according to claim 1 , wherein the attribute word stored in the database comprises a morpheme constituting a part of the candidate name.
| 0.743454 |
16. A system, comprising: a network interface; a memory storing a mapping document that represents an organization of related network-accessible documents within a website, at least some of the network-accessible documents whose organization is represented by the mapping document being mobile content; a crawler programmed to crawl the website over the network interface based on the mapping document to obtain information from the network-accessible documents, wherein the crawler is programmed to: receive an indication that at least some of the network-accessible documents whose organization is represented by the mapping document are mobile content; select, based on the indication that at least some of the network-accessible documents whose organization is represented by the mapping document are mobile content, a mobile content crawling mode to crawl the network-accessible documents of the website that are mobile content; and crawl the network-accessible documents being mobile content in the mobile content crawling mode and add the information from at least some of the network-accessible documents to a search engine index; a search engine programmed to receive a search request from a mobile device and transmit search results to the mobile device that are responsive to the search request and that are identified at least in part using information in the search engine index.
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16. A system, comprising: a network interface; a memory storing a mapping document that represents an organization of related network-accessible documents within a website, at least some of the network-accessible documents whose organization is represented by the mapping document being mobile content; a crawler programmed to crawl the website over the network interface based on the mapping document to obtain information from the network-accessible documents, wherein the crawler is programmed to: receive an indication that at least some of the network-accessible documents whose organization is represented by the mapping document are mobile content; select, based on the indication that at least some of the network-accessible documents whose organization is represented by the mapping document are mobile content, a mobile content crawling mode to crawl the network-accessible documents of the website that are mobile content; and crawl the network-accessible documents being mobile content in the mobile content crawling mode and add the information from at least some of the network-accessible documents to a search engine index; a search engine programmed to receive a search request from a mobile device and transmit search results to the mobile device that are responsive to the search request and that are identified at least in part using information in the search engine index. 17. The system of claim 16 , further comprising an ad sever programmed to provide a promotional item in combination with the search results.
| 0.540816 |
26. A method according to claim 18, wherein script commands include commands to execute utility functions.
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26. A method according to claim 18, wherein script commands include commands to execute utility functions. 28. A method according to claim 26, wherein the utility functions includes a function to invoke another script.
| 0.963666 |
17. A non-transitory computer-readable storage medium that stores instructions which, when executed by one or more processors, cause the one or more processors to perform steps comprising: receiving an original question from a user; generating two or more queries based on the original question; submitting each of the two or more queries to a search engine; for each particular query of the two or more queries, receiving, from the search engine, a separate search engine result for that particular query, thereby receiving a plurality of search engine results; wherein the search engine result for each particular query corresponds to a separate document set; wherein the plurality of search engine results correspond to a plurality of document sets; generating a single concept set based on term in documents from the plurality of search engine results; wherein the single concept set is generated by, for each search engine result in the plurality of search engine results, identifying terms in documents from the search engine results, and adding at least a subset of said terms to said single concept set; using the single concept set to determine how to respond to the original question by performing at least one of: generating a refined set of search results for the original question based on the single concept set, and returning the refined set of search results as a response to the original question; or using the single concept set to identify questions similar to the original question; wherein the steps are performed by one or more computing devices.
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17. A non-transitory computer-readable storage medium that stores instructions which, when executed by one or more processors, cause the one or more processors to perform steps comprising: receiving an original question from a user; generating two or more queries based on the original question; submitting each of the two or more queries to a search engine; for each particular query of the two or more queries, receiving, from the search engine, a separate search engine result for that particular query, thereby receiving a plurality of search engine results; wherein the search engine result for each particular query corresponds to a separate document set; wherein the plurality of search engine results correspond to a plurality of document sets; generating a single concept set based on term in documents from the plurality of search engine results; wherein the single concept set is generated by, for each search engine result in the plurality of search engine results, identifying terms in documents from the search engine results, and adding at least a subset of said terms to said single concept set; using the single concept set to determine how to respond to the original question by performing at least one of: generating a refined set of search results for the original question based on the single concept set, and returning the refined set of search results as a response to the original question; or using the single concept set to identify questions similar to the original question; wherein the steps are performed by one or more computing devices. 25. The non-transitory computer-readable storage medium of claim 17 , wherein the step of identifying terms in documents from the search engine results comprises ranking particular terms in a particular document within the particular document set based at least in part on an extent to which the particular terms represent an overall topic of the particular document; and wherein ranking the particular terms comprises ranking the particular terms relative to each other based at least in part on positions at which the particular terms occur within the particular document.
| 0.675244 |
13. The method of claim 12 wherein generating the score further comprises: applying the scoring neural network to multiple nodes of the dependency structure to compute corresponding scores for the multiple nodes of the dependency structure; and combining, as the score for the composition, the scores for the multiple nodes of the dependency structure.
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13. The method of claim 12 wherein generating the score further comprises: applying the scoring neural network to multiple nodes of the dependency structure to compute corresponding scores for the multiple nodes of the dependency structure; and combining, as the score for the composition, the scores for the multiple nodes of the dependency structure. 14. The method of claim 13 wherein combining the scores for the multiple nodes of the dependency structure comprises: summing the scores for the multiple nodes for the dependency structure; or multiplying each selected score of the multiple nodes for the dependency structure by (½)^depth, wherein the depth is the maximum number of edges between the node corresponding to that selected score and the root node of the dependency structure, and summing the results of the multiplications.
| 0.849613 |
1. A method of retrieving data from a data store according to a user intent, the method comprising: receiving a query in an intermediate language, the intermediate language specific to a vertical domain, the query comprising multiple query terms from a user expressing the user's intent, the multiple query terms associated with the vertical domain; selecting a parser from a plurality of parsers, the parser configured to support the multiple query terms associated with the vertical domain; parsing the intermediate language query into the multiple query terms using the parser; and converting the multiple query terms to a data retrieval language query using a processor, the data retrieval language query having data retrieval terms specific to retrieving data from the data store, the data retrieval terms configured to operate directly against the data store.
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1. A method of retrieving data from a data store according to a user intent, the method comprising: receiving a query in an intermediate language, the intermediate language specific to a vertical domain, the query comprising multiple query terms from a user expressing the user's intent, the multiple query terms associated with the vertical domain; selecting a parser from a plurality of parsers, the parser configured to support the multiple query terms associated with the vertical domain; parsing the intermediate language query into the multiple query terms using the parser; and converting the multiple query terms to a data retrieval language query using a processor, the data retrieval language query having data retrieval terms specific to retrieving data from the data store, the data retrieval terms configured to operate directly against the data store. 2. The method of claim 1 , wherein the vertical domain of the intermediate language is that of investor relations.
| 0.613372 |
15. The portable electronic terminal of claim 14 , wherein unlocking the touch screen further comprises unlocking the touch screen in response to recognizing the wakeup command and the predetermined speaker of the voice signal.
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15. The portable electronic terminal of claim 14 , wherein unlocking the touch screen further comprises unlocking the touch screen in response to recognizing the wakeup command and the predetermined speaker of the voice signal. 16. The portable electronic terminal of claim 15 , wherein the voice signal is input through a microphone of the portable electronic terminal in an idle mode, and when the wakeup command is detected in the idle mode, a voice command mode is activated.
| 0.831007 |
11. The method according to claim 10 , wherein applying on the letter trie-based dictionary an approximate matching technique for generating at least one suggested word element, further comprises: rejecting and ranking suggested word elements using a proximity factor.
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11. The method according to claim 10 , wherein applying on the letter trie-based dictionary an approximate matching technique for generating at least one suggested word element, further comprises: rejecting and ranking suggested word elements using a proximity factor. 12. The method according to the claim 11 , wherein the proximity factor is based on a phonetic proximity.
| 0.960772 |
4. An automated method of classifying text to one or more target classes in a target classification system, the method comprising: identifying one or more noun-word pairs in a portion of text; and determining one or more scores based on frequencies of one or more of the identified noun-word pairs in the portion of text and one or more noun-word pairs in text associated with one of the target classes.
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4. An automated method of classifying text to one or more target classes in a target classification system, the method comprising: identifying one or more noun-word pairs in a portion of text; and determining one or more scores based on frequencies of one or more of the identified noun-word pairs in the portion of text and one or more noun-word pairs in text associated with one of the target classes. 7. The method of claim 4 , wherein the one or more scores include: at least one score based on similarity of at least one or more portions of the input text to text associated with the target class; at least one score based on similarity of a set of one or more non-target classes associated with the input text and a set of one or more non-target classes associated with the target class; at least one score based on probability of the target class given a set of one or more non-target classes associated with the input text; and at least one score based on probability of the target class given at least a portion of the input text.
| 0.64275 |
19. A computer-based system used to develop executable data mining profiles comprising: a main menu interface listing one or more data mining object types and associated sub-objects, said data mining object types comprising one or more from the group of: data, discretization, mining, name mapping, processing, results, sequence, statistics and taxonomy; a series of context sensitive GUI templates, the selection of subsequent context sensitive templates based on one or more inputs to one or more proceeding GUI templates, said GUI templates requesting data object mining parameters for one of said data mining object types; said data mining sub-objects created by traversal of said series of GUI templates based on data object mining parameters of a previous GUI template; and an executable data mining profile created by a selective grouping of created mining sub-objects, said executable data mining profile comprising sequences of settings that run consecutively, said settings including one or more of processing, mining, sequence or statistics.
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19. A computer-based system used to develop executable data mining profiles comprising: a main menu interface listing one or more data mining object types and associated sub-objects, said data mining object types comprising one or more from the group of: data, discretization, mining, name mapping, processing, results, sequence, statistics and taxonomy; a series of context sensitive GUI templates, the selection of subsequent context sensitive templates based on one or more inputs to one or more proceeding GUI templates, said GUI templates requesting data object mining parameters for one of said data mining object types; said data mining sub-objects created by traversal of said series of GUI templates based on data object mining parameters of a previous GUI template; and an executable data mining profile created by a selective grouping of created mining sub-objects, said executable data mining profile comprising sequences of settings that run consecutively, said settings including one or more of processing, mining, sequence or statistics. 21. A computer-based system used to develop data mining objects as per claim 19, wherein each of said templates in said GUI template sequence may comprise a one or more related templates.
| 0.597455 |
8. A computer system, comprising at least one processor, wherein the at least one processor is configured to perform the operations of: receiving a semantic request submitted by a user to access data entries stored at a primary data server running a relational database management system (DBMS); decomposing the received request into logic query segments, each logic query segment having a corresponding answer set retrievable from the primary data server based on a DBMS query formulated based on the logic query segment; determining whether a corresponding answer set of a particular decomposed logic query segment is stored and ready in an in-memory data storage at the fast query service engine such that a DBMS query submission at the primary data server is obviated, the fast query service engine being different and separate from the primary data server; in response to determining that a corresponding answer set of a particular decomposed logic query segment is not stored in the in-memory data storage at the fast query service engine, formulating a DBMS query based on the particular decomposed logic query segment and fetching answer set of the particular logic query segment from the primary data server; in response to determining that a corresponding answer set of a particular decomposed logic query segment is stored but invalid in the in-memory data storage at the fast query service engine, formulating a DBMS query based on the particular decomposed logic query segment and updating contents of the answer set by synchronizing copies of data on the primary data server and in the in-memory data storage; in response to determining that the corresponding answer set of a particular decomposed logic query segment is stored and ready in the in-memory data storage at the fast query service engine, directing the logic query segment to the fast query service engine and retrieving an answer set of the particular decomposed logic query segment from the in-memory data storage at the fast query service engine; composing query results from the answer set received from the primary data server and the answer set retrieved from the in-memory data storage at the fast query service engine; and providing the composed query results to the user submitting the semantic request.
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8. A computer system, comprising at least one processor, wherein the at least one processor is configured to perform the operations of: receiving a semantic request submitted by a user to access data entries stored at a primary data server running a relational database management system (DBMS); decomposing the received request into logic query segments, each logic query segment having a corresponding answer set retrievable from the primary data server based on a DBMS query formulated based on the logic query segment; determining whether a corresponding answer set of a particular decomposed logic query segment is stored and ready in an in-memory data storage at the fast query service engine such that a DBMS query submission at the primary data server is obviated, the fast query service engine being different and separate from the primary data server; in response to determining that a corresponding answer set of a particular decomposed logic query segment is not stored in the in-memory data storage at the fast query service engine, formulating a DBMS query based on the particular decomposed logic query segment and fetching answer set of the particular logic query segment from the primary data server; in response to determining that a corresponding answer set of a particular decomposed logic query segment is stored but invalid in the in-memory data storage at the fast query service engine, formulating a DBMS query based on the particular decomposed logic query segment and updating contents of the answer set by synchronizing copies of data on the primary data server and in the in-memory data storage; in response to determining that the corresponding answer set of a particular decomposed logic query segment is stored and ready in the in-memory data storage at the fast query service engine, directing the logic query segment to the fast query service engine and retrieving an answer set of the particular decomposed logic query segment from the in-memory data storage at the fast query service engine; composing query results from the answer set received from the primary data server and the answer set retrieved from the in-memory data storage at the fast query service engine; and providing the composed query results to the user submitting the semantic request. 12. The computer system of claim 8 , wherein the operations further comprise: determining whether the request modifies data on the primary data server.
| 0.561248 |
1. A computer-implemented method for facilitating collaboration between users of a plurality of user terminals around a data measure mapped to a multi-dimensional data model, the computer-implemented method comprising: electronically processing, by a computer system, a first request from a first user terminal of a plurality of user terminals to associate a discussion object with a data measure mapped to a multi-dimensional data model, the discussion object including a first entry by a first user and enabling users of the plurality of user terminals to communicate based on the data measure, the multi-dimensional data model configured for access by online analytical processing (OLAP) applications; determining, by the computer system, coordinates of a plurality of data dimensions of the multi-dimensional data model that uniquely identify to the data measure; storing, by the computer system, in an electronic data storage the discussion object in association with the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure; receiving, by the computer system, a second request from a second user terminal of the plurality of user terminals, the second request dynamically generated based on a value of the data measure being displayed by the second user terminal to a second user, the second request comprising the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure, the second request configured to identify discussion objects associated with the coordinates; determining, by the computer system, an existence of discussion objects that are associated with the coordinates received in the second request; retrieving, by the computer system, the discussion object from the electronic data storage using the coordinates of the plurality of data dimensions of the multi-dimensional data model; transmitting, by the computer system, to the second user terminal an indication of the discussion object for display by the second user terminal in association with the value of the data measure; transmitting, by the computer system, to the second user terminal the discussion object in response to a third request for the discussion object from the second user terminal; updating, by the computer system, the discussion object stored in the electronic data storage with a second entry by the second user based on a fourth request to update the discussion object from the second user terminal; determining, by the computer system, an existence of task objects that are associated with the coordinates received in the second request; retrieving, by the computer system, one or more task objects from the electronic data storage using the coordinates of the plurality of data dimensions of the multi-dimensional data model; transmitting, by the computer system, to the second user terminal an indication of the one or more task objects for display by the second user terminal in association with the value of the data measure, the one or more task objects associated with the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure; and transmitting, by the computer system, to the second user terminal a task information indication for display by the second user terminal in association with the value of the data measure, the task information indication comprising a name of a task manager assigned to the one or more task objects, the task information indication comprising a target value, the target value being a percentage difference between the value of the data measure and a desired value of the data measure, the task information indication associated with the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure, wherein the computer system comprises a computer processor and electronic memory.
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1. A computer-implemented method for facilitating collaboration between users of a plurality of user terminals around a data measure mapped to a multi-dimensional data model, the computer-implemented method comprising: electronically processing, by a computer system, a first request from a first user terminal of a plurality of user terminals to associate a discussion object with a data measure mapped to a multi-dimensional data model, the discussion object including a first entry by a first user and enabling users of the plurality of user terminals to communicate based on the data measure, the multi-dimensional data model configured for access by online analytical processing (OLAP) applications; determining, by the computer system, coordinates of a plurality of data dimensions of the multi-dimensional data model that uniquely identify to the data measure; storing, by the computer system, in an electronic data storage the discussion object in association with the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure; receiving, by the computer system, a second request from a second user terminal of the plurality of user terminals, the second request dynamically generated based on a value of the data measure being displayed by the second user terminal to a second user, the second request comprising the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure, the second request configured to identify discussion objects associated with the coordinates; determining, by the computer system, an existence of discussion objects that are associated with the coordinates received in the second request; retrieving, by the computer system, the discussion object from the electronic data storage using the coordinates of the plurality of data dimensions of the multi-dimensional data model; transmitting, by the computer system, to the second user terminal an indication of the discussion object for display by the second user terminal in association with the value of the data measure; transmitting, by the computer system, to the second user terminal the discussion object in response to a third request for the discussion object from the second user terminal; updating, by the computer system, the discussion object stored in the electronic data storage with a second entry by the second user based on a fourth request to update the discussion object from the second user terminal; determining, by the computer system, an existence of task objects that are associated with the coordinates received in the second request; retrieving, by the computer system, one or more task objects from the electronic data storage using the coordinates of the plurality of data dimensions of the multi-dimensional data model; transmitting, by the computer system, to the second user terminal an indication of the one or more task objects for display by the second user terminal in association with the value of the data measure, the one or more task objects associated with the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure; and transmitting, by the computer system, to the second user terminal a task information indication for display by the second user terminal in association with the value of the data measure, the task information indication comprising a name of a task manager assigned to the one or more task objects, the task information indication comprising a target value, the target value being a percentage difference between the value of the data measure and a desired value of the data measure, the task information indication associated with the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure, wherein the computer system comprises a computer processor and electronic memory. 13. The method of claim 1 , further comprising: electronically processing, by the computer system, a sixth request from the second user terminal to associate a different discussion object with the data measure; and storing, by the computer system, in the electronic data storage the different discussion object in association with the coordinates of the plurality of data dimensions of the multi-dimensional data model that uniquely identify the data measure.
| 0.512612 |
1. A text subtitle decoder for decoding text subtitle streams recorded on a recording medium, comprising: a text subtitle processor configured to parse the text subtitle stream into text data to be displayed in the subtitle region, region style information indicating a region style to be applied to an overall region including the text data, and inline style information indicating at least one font related style to be applied to the text data, the parsed text data and inline style information being transferred to a different area of the text subtitle decoder than the parsed region style information; a text renderer configured to receive the text data and the inline style information; and a controller configured to input the region style information into the text renderer, wherein the text renderer is controlled by the controller, and converts the text data into bitmap data using the region style information and the inline style information.
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1. A text subtitle decoder for decoding text subtitle streams recorded on a recording medium, comprising: a text subtitle processor configured to parse the text subtitle stream into text data to be displayed in the subtitle region, region style information indicating a region style to be applied to an overall region including the text data, and inline style information indicating at least one font related style to be applied to the text data, the parsed text data and inline style information being transferred to a different area of the text subtitle decoder than the parsed region style information; a text renderer configured to receive the text data and the inline style information; and a controller configured to input the region style information into the text renderer, wherein the text renderer is controlled by the controller, and converts the text data into bitmap data using the region style information and the inline style information. 8. The text subtitle decoder of claim 1 , wherein the text subtitle processor is configured to parse the text subtitle stream into palette information.
| 0.641674 |
10. A method for managing documents using a document management system, the document management system comprising a storage unit that stores documents to construct a database and a document processing unit comprising a processor that detects a specific document among newly provided documents and informs the user of an information on the detected document, the method comprising: providing a user with a newly received information service application form that includes a service type section for setting a type of a newly received information service and an informing condition section for detecting a user-concerning document; receiving a newly received information service application input from the user, the newly received information service application input comprising an input that selects the type of the newly received information service from among a general selective dissemination of information service, a legal selective dissemination of information service and a similarity retrieval selective dissemination of information service; monitoring newly received documents in accordance with the newly received information service application input; and informing the user of information on a newly received document that corresponds to an informing condition, wherein if the general selective dissemination of information service is selected as the newly received information service, the document management system receives a retrieval expression from the user as the informing condition, determines whether a newly received document corresponds to the retrieval expression, and informs the user of the information on the newly received document if the newly received document corresponds to the retrieval expression, wherein if the legal selective dissemination of information service is selected as the newly received information service, the document management system receives an input that designates a reference document that was previously stored in the storage unit as the informing condition, extracts a representative value of the reference document, compares the reference document with a corresponding newly received document using the representative value, determines whether a legal status of the reference document is different from that of the corresponding newly received document, and informs the user of the information on the newly received document if the legal status of the reference document is different from that of the corresponding newly received document, wherein if the similarity retrieval selective dissemination of information service is selected as the newly received information service, the document management system receives an input that designates a reference document that was previously stored in the storage unit as the informing condition, determines whether a newly received document is similar to the reference document, and informs the user of the information on the newly received document if the newly received document is similar to the reference document.
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10. A method for managing documents using a document management system, the document management system comprising a storage unit that stores documents to construct a database and a document processing unit comprising a processor that detects a specific document among newly provided documents and informs the user of an information on the detected document, the method comprising: providing a user with a newly received information service application form that includes a service type section for setting a type of a newly received information service and an informing condition section for detecting a user-concerning document; receiving a newly received information service application input from the user, the newly received information service application input comprising an input that selects the type of the newly received information service from among a general selective dissemination of information service, a legal selective dissemination of information service and a similarity retrieval selective dissemination of information service; monitoring newly received documents in accordance with the newly received information service application input; and informing the user of information on a newly received document that corresponds to an informing condition, wherein if the general selective dissemination of information service is selected as the newly received information service, the document management system receives a retrieval expression from the user as the informing condition, determines whether a newly received document corresponds to the retrieval expression, and informs the user of the information on the newly received document if the newly received document corresponds to the retrieval expression, wherein if the legal selective dissemination of information service is selected as the newly received information service, the document management system receives an input that designates a reference document that was previously stored in the storage unit as the informing condition, extracts a representative value of the reference document, compares the reference document with a corresponding newly received document using the representative value, determines whether a legal status of the reference document is different from that of the corresponding newly received document, and informs the user of the information on the newly received document if the legal status of the reference document is different from that of the corresponding newly received document, wherein if the similarity retrieval selective dissemination of information service is selected as the newly received information service, the document management system receives an input that designates a reference document that was previously stored in the storage unit as the informing condition, determines whether a newly received document is similar to the reference document, and informs the user of the information on the newly received document if the newly received document is similar to the reference document. 14. The method according to claim 10 , wherein the documents stored in the storage unit comprise at least one of patent publication documents and issued patent documents.
| 0.601162 |
13. A computer system comprising: at least one tangible memory that stores processor-executable instructions encoded for identifying, from at least one of a plurality of documents stored in electronic storage, text for inclusion in a new document; and at least one processor, coupled to the at least one tangible memory, configured to execute the instructions stored in the at least one tangible memory to: issue a user-specified query for documents in the electronic storage matching at least one parameter specified in the query, wherein the query is specified via at least one user interface; receive, in response to issuance of the query, at least one document matching the at least one parameter; identify topical sections in the at least one document; display, via the at least one user interface, names of the identified topical sections in the at least one document without displaying the entirety of the text of each of the identified topical sections; associate at least one indicator with each of the identified topical sections, each of the indicators being in either a selected state or a non-selected state; display for each of the identified topical sections, the at least one indicator associated with it, each displayed indicator comprising information indicating whether it is in the selected state or the non-selected state; provide, in the at least one user interface, a capability for a user to view text from at least one of the identified topical sections, a capability for the user to select at least one portion of the text of the at least one of the identified topical sections for inclusion in the new document, and a capability for the user to selectively alter the state of each displayed indicator for the identified topical sections; and in response to receiving user input via the at least one user interface indicating that the user has finished altering the states of the displayed indicators, copy into the new document text from each identified topical section for which the at least one displayed indicator associated therewith comprises information indicating it is in the selected state.
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13. A computer system comprising: at least one tangible memory that stores processor-executable instructions encoded for identifying, from at least one of a plurality of documents stored in electronic storage, text for inclusion in a new document; and at least one processor, coupled to the at least one tangible memory, configured to execute the instructions stored in the at least one tangible memory to: issue a user-specified query for documents in the electronic storage matching at least one parameter specified in the query, wherein the query is specified via at least one user interface; receive, in response to issuance of the query, at least one document matching the at least one parameter; identify topical sections in the at least one document; display, via the at least one user interface, names of the identified topical sections in the at least one document without displaying the entirety of the text of each of the identified topical sections; associate at least one indicator with each of the identified topical sections, each of the indicators being in either a selected state or a non-selected state; display for each of the identified topical sections, the at least one indicator associated with it, each displayed indicator comprising information indicating whether it is in the selected state or the non-selected state; provide, in the at least one user interface, a capability for a user to view text from at least one of the identified topical sections, a capability for the user to select at least one portion of the text of the at least one of the identified topical sections for inclusion in the new document, and a capability for the user to selectively alter the state of each displayed indicator for the identified topical sections; and in response to receiving user input via the at least one user interface indicating that the user has finished altering the states of the displayed indicators, copy into the new document text from each identified topical section for which the at least one displayed indicator associated therewith comprises information indicating it is in the selected state. 14. The computer system of claim 13 , wherein the at least one parameter specifies a document type.
| 0.692229 |
1. A computer-implemented method for proactive customer experience management in a communication network, comprising: a) obtaining a performance-indicating alert (PA) from at least one probe; b) identifying relevant alerts from an alert database in absence of possible fault condition from the PA; c) determining a possible problem condition from the PA and the identified relevant alerts; d) raising trace trigger for gathering relevant trace data; e) determining specific problem condition and relevant cause, based on gathered trace data and relevant data from PM/FM, CDR and OSS systems; f) determining appropriate recommendation for resolution of the determined specific problem condition; g) recalculating a probe alert threshold value for triggering the performance-indicating probe alert; h) providing the recalculated probe alert threshold value for modifying a configuration of a performance-indicating probe; i) updating a user interface dashboard using the determination of a root cause of the possible problem and the recommendation for resolution of the possible problem; and j) updating new knowledge into a knowledge base with problem-context, resolution, relevant adjustments to alerts, thresholds and rules.
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1. A computer-implemented method for proactive customer experience management in a communication network, comprising: a) obtaining a performance-indicating alert (PA) from at least one probe; b) identifying relevant alerts from an alert database in absence of possible fault condition from the PA; c) determining a possible problem condition from the PA and the identified relevant alerts; d) raising trace trigger for gathering relevant trace data; e) determining specific problem condition and relevant cause, based on gathered trace data and relevant data from PM/FM, CDR and OSS systems; f) determining appropriate recommendation for resolution of the determined specific problem condition; g) recalculating a probe alert threshold value for triggering the performance-indicating probe alert; h) providing the recalculated probe alert threshold value for modifying a configuration of a performance-indicating probe; i) updating a user interface dashboard using the determination of a root cause of the possible problem and the recommendation for resolution of the possible problem; and j) updating new knowledge into a knowledge base with problem-context, resolution, relevant adjustments to alerts, thresholds and rules. 8. The method of claim 1 , wherein the possible problem condition includes degradation of an end-user service quality indicator.
| 0.551573 |
1. A machine translation apparatus comprising: a central processing unit; an identification information detection unit that detects, from a designated physical object or an attachment thereto, identification information of the designated object; a receiving unit that receives a source language sentence; a word dividing unit that divides the source language sentence into a plurality of first words by morphological analysis; a deixis detection unit that detects, from the first words, a deixis indicating the designated object; a correspondence setting unit that sets a correspondence between the identification information of the designated object and the deixis; a semantic class determining unit executing on the central processing unit that determines a semantic class indicating a semantic attribute of the designated object previously associated with the identification information of the designated object; and a translation unit that translates the source language sentence according to the determined semantic class of the designated object corresponding to the deixis.
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1. A machine translation apparatus comprising: a central processing unit; an identification information detection unit that detects, from a designated physical object or an attachment thereto, identification information of the designated object; a receiving unit that receives a source language sentence; a word dividing unit that divides the source language sentence into a plurality of first words by morphological analysis; a deixis detection unit that detects, from the first words, a deixis indicating the designated object; a correspondence setting unit that sets a correspondence between the identification information of the designated object and the deixis; a semantic class determining unit executing on the central processing unit that determines a semantic class indicating a semantic attribute of the designated object previously associated with the identification information of the designated object; and a translation unit that translates the source language sentence according to the determined semantic class of the designated object corresponding to the deixis. 13. The machine translation apparatus according to claim 1 , wherein the identification information detection unit includes an image pickup unit that picks-up an image of the designated object; and an image recognition unit that analyzes the image picked up and acquiring the identification information including the semantic class of the designated object.
| 0.655542 |
1. A method for translating a textual message into a semantic music composition, said method comprising the steps of: (a) receiving a first text message, including a plurality of words, through a user interface; (b) parsing the first text message through an automated computer parsing program to obtain a parsed message representing a semantic meaning of the first text message with a plurality of parsed words in an order; (c) automatically selecting a music element for each parsed word in the parsed message from a database that correlates parsed words to music elements; (d) creating a music composition by combining said selected music elements in the order of the parsed words; and (e) outputting the music composition in an audio format, whereby the music composition is the same as a music composition created from a second text message having the same semantic meaning, wherein the first text message is in a natural language and the second text message is in a different natural language.
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1. A method for translating a textual message into a semantic music composition, said method comprising the steps of: (a) receiving a first text message, including a plurality of words, through a user interface; (b) parsing the first text message through an automated computer parsing program to obtain a parsed message representing a semantic meaning of the first text message with a plurality of parsed words in an order; (c) automatically selecting a music element for each parsed word in the parsed message from a database that correlates parsed words to music elements; (d) creating a music composition by combining said selected music elements in the order of the parsed words; and (e) outputting the music composition in an audio format, whereby the music composition is the same as a music composition created from a second text message having the same semantic meaning, wherein the first text message is in a natural language and the second text message is in a different natural language. 4. The method according to claim 1 further comprising outputting the music composition in metered pitch.
| 0.665328 |
15. A system comprising: a computer system; and a related query processor of the computer system to determine a score for a document as a result for a search query, the score based, at least in part, on one or more related search queries that have at least a threshold relationship to the search query, wherein the score is determined by performing operations comprising: identifying click data associated with the document and the one or more related search queries, wherein the click data indicates how frequently the document was selected when the document was presented in search results for the one or more related search queries over a period of time; weighting the click data based on weights for the one or more related search queries, wherein the weights indicate how strongly the one or more related queries are related to the search query; and combining the weighted click data to generate at least a component of the score; wherein the related query processor is further configured to provide the score for the document as a result for the search query to a ranking processor.
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15. A system comprising: a computer system; and a related query processor of the computer system to determine a score for a document as a result for a search query, the score based, at least in part, on one or more related search queries that have at least a threshold relationship to the search query, wherein the score is determined by performing operations comprising: identifying click data associated with the document and the one or more related search queries, wherein the click data indicates how frequently the document was selected when the document was presented in search results for the one or more related search queries over a period of time; weighting the click data based on weights for the one or more related search queries, wherein the weights indicate how strongly the one or more related queries are related to the search query; and combining the weighted click data to generate at least a component of the score; wherein the related query processor is further configured to provide the score for the document as a result for the search query to a ranking processor. 21. The system of claim 15 , wherein the click data corresponds to a number of times that the document was selected when it was presented in the search results for the one or more related search queries over the period of time.
| 0.629804 |
16. The system of claim 15 , wherein the one or more processors are further configured to host a chat board in the electronic collaboration forum that is accessible to the client and the collaboration team, wherein the access to the chat board enables the client and at least one advisor of the collaboration team to interact with one another in a real-time online conference to perform one or more of the scheduled additional interactions.
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16. The system of claim 15 , wherein the one or more processors are further configured to host a chat board in the electronic collaboration forum that is accessible to the client and the collaboration team, wherein the access to the chat board enables the client and at least one advisor of the collaboration team to interact with one another in a real-time online conference to perform one or more of the scheduled additional interactions. 17. The system of claim 16 , wherein the one or more processors are further configured to host, within the electronic collaboration forum, visual content associated with the client and the collaboration team performing one or more of the scheduled additional interactions such that the client is enabled to view the hosted visual content.
| 0.88941 |
35. A machine readable storage medium having instructions stored thereon that when executed by a processor cause a system to: provide a plurality of type system, wherein each of the plurality of type systems is maintained in a separate type repository of a plurality of type repositories, wherein each of the plurality of type repositories is associated with a type repository interface, and wherein the type repository interface provides a set of services supported by the type repository; provide a compiler that includes a plurality of language modules wherein each one of the plurality of language modules is associated with a different programming language, wherein the compiler operates to compile one or more types defined in one of the plurality of language modules into one or more types in one of the plurality of type systems, maintain at each of the plurality of type repositories references to one or more data structures provided by the compiler, wherein each data structure is used by the type repository to determine a location of a particular type in a source code.
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35. A machine readable storage medium having instructions stored thereon that when executed by a processor cause a system to: provide a plurality of type system, wherein each of the plurality of type systems is maintained in a separate type repository of a plurality of type repositories, wherein each of the plurality of type repositories is associated with a type repository interface, and wherein the type repository interface provides a set of services supported by the type repository; provide a compiler that includes a plurality of language modules wherein each one of the plurality of language modules is associated with a different programming language, wherein the compiler operates to compile one or more types defined in one of the plurality of language modules into one or more types in one of the plurality of type systems, maintain at each of the plurality of type repositories references to one or more data structures provided by the compiler, wherein each data structure is used by the type repository to determine a location of a particular type in a source code. 36. The machine readable storage medium of claim 35 , wherein: the references to one or more data structures by the type repository prevent the one or more data structures from being garbage collected.
| 0.5 |
19. The electronic device according to claim 17 , wherein the touch sensitive input device detects a left to right swipe of the simultaneous multiple touches by the user.
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19. The electronic device according to claim 17 , wherein the touch sensitive input device detects a left to right swipe of the simultaneous multiple touches by the user. 20. The electronic device according to claim 19 , wherein the control circuitry interprets the detected gesture as a command to navigate to a first page of the current chapter C of the electronic book.
| 0.945183 |
9. The computing system of claim 7 , wherein the operations further comprise: identifying, by the computing system, that a second user input selected, from among a third set of search results provided to a computing device responsive to a third query, a particular search result that references the first electronic document; and generating, by the computing system and in response to identifying that the second user input selected the particular search result that references the first electronic document, a second association between the first electronic document and the one or more terms derived from the third query.
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9. The computing system of claim 7 , wherein the operations further comprise: identifying, by the computing system, that a second user input selected, from among a third set of search results provided to a computing device responsive to a third query, a particular search result that references the first electronic document; and generating, by the computing system and in response to identifying that the second user input selected the particular search result that references the first electronic document, a second association between the first electronic document and the one or more terms derived from the third query. 10. The computing system of claim 9 , wherein the operations comprise, after generating the second association between the first electronic document and the one or more terms derived from the third query: receiving a fourth query; determining a relevance of the first electronic document to the fourth query based at least in part on a level of similarity between (i) the one or more terms derived from the third query and associated with the first electronic document and (ii) one or more terms derived from the fourth query; generating a fourth set of search results responsive to the fourth query, including selecting or ranking the first electronic document in the fourth set of search results based on the determined relevance; and transmitting the fourth set of search results.
| 0.749685 |
11. The computer-readable storage device of claim 9 , wherein the detailed clinical model defines concepts, relationships, constraints, and rules that specify semantics of an item of clinical information.
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11. The computer-readable storage device of claim 9 , wherein the detailed clinical model defines concepts, relationships, constraints, and rules that specify semantics of an item of clinical information. 12. The computer-readable storage device of claim 11 , wherein an item of clinical information involves a plurality of relationships, constraints, and rules specified by one or more detailed clinical models.
| 0.952216 |
1. A method of improving accuracy of computerized topic identification comprising: a domain independent, language independent, computer processor automated topic identification analysis method, the method comprising: a) deriving, by at least one computer processor, a lexicon from at least one hypertext corpus data set to associate at least one term with at least one topic, wherein said at least one term comprises at least one word, wherein at least one sense is derived from at least one hypertext link of the at least one hypertext corpus data set, and is associated with each of said at least one term, wherein each of said at least one sense refers to a single topic of said at least one term, wherein said at least one topic referred to by said at least one sense is to be used as a candidate topic at runtime, wherein a prior probability is associated with each of said at least one sense of said each said term, wherein each said prior probability is a fraction of occurrences of a given one of said at least one term as a relationship comprising a hypertext link that links to said single topic from said each of said at least one sense; b) receiving, by the at least one computer processor, at least one content document; c) searching for, by the at least one computer processor, at least one term from the lexicon derived from the at least one hypertext corpus data set, and finding the at least one term from the lexicon appearing in the at least one content document to determine at least one candidate topic of the at least one content document; d) lexically scoring, by the at least one computer processor, each of said at least one candidate topic found appearing in the at least one content document based on the at least one term found in said search of said (c) of the at least one content document to obtain a lexical score for each of said at least one candidate topic, and accumulating said lexical score for each of said at least one candidate topic for each occurrence in the at least one content document of a term, wherein the term has an associated sense, wherein the associated sense refers to said each said candidate topic, wherein said lexically scoring comprises lexically scoring, by the at least one computer processor, based on: a number of occurrences of the at least one term found in the at least one content document, a weighting factor representing a relative importance of the at least one term found, and the prior probability of the sense of the at least one term found; and e) semantically scoring, by the at least one computer processor, the at least one candidate topic found in the at least one content document, based on a degree to which any plurality of candidate topics are semantically related to each other comprising: i. quantifying a semantic relatedness score, by the at least one computer processor, of said any plurality of topics of the at least one hypertext corpus data set, and wherein said quantifying of the semantic relatedness score is based on theoretical information content of co-adjacent links of a graph representation of the at least one hypertext corpus data set; evaluating the semantic relatedness score during quantifying, by the at least one computer processor, comprising evaluating the theoretical information content of an edge of said graph representation of the at least one hypertext corpus data set, wherein a vertex of said graph representation of the at least one hypertext corpus data set represents one of said plurality of topics, and an edge of said co-adjacent edges represents a relationship between two topics; wherein the theoretical information content of an edge is based on information theory and comprises at least one of: A. self-information, or B. surprisal ii. semantically scoring, by the at least one computer processor, based on said lexical score of said each of said at least one candidate topic found appearing in the at least one content document, wherein said lexical score of said each of said at least one candidate topic was determined from the at least one term of said lexicon derived from the hypertext corpus data set, and based on said semantic relatedness score from said quantifying.
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1. A method of improving accuracy of computerized topic identification comprising: a domain independent, language independent, computer processor automated topic identification analysis method, the method comprising: a) deriving, by at least one computer processor, a lexicon from at least one hypertext corpus data set to associate at least one term with at least one topic, wherein said at least one term comprises at least one word, wherein at least one sense is derived from at least one hypertext link of the at least one hypertext corpus data set, and is associated with each of said at least one term, wherein each of said at least one sense refers to a single topic of said at least one term, wherein said at least one topic referred to by said at least one sense is to be used as a candidate topic at runtime, wherein a prior probability is associated with each of said at least one sense of said each said term, wherein each said prior probability is a fraction of occurrences of a given one of said at least one term as a relationship comprising a hypertext link that links to said single topic from said each of said at least one sense; b) receiving, by the at least one computer processor, at least one content document; c) searching for, by the at least one computer processor, at least one term from the lexicon derived from the at least one hypertext corpus data set, and finding the at least one term from the lexicon appearing in the at least one content document to determine at least one candidate topic of the at least one content document; d) lexically scoring, by the at least one computer processor, each of said at least one candidate topic found appearing in the at least one content document based on the at least one term found in said search of said (c) of the at least one content document to obtain a lexical score for each of said at least one candidate topic, and accumulating said lexical score for each of said at least one candidate topic for each occurrence in the at least one content document of a term, wherein the term has an associated sense, wherein the associated sense refers to said each said candidate topic, wherein said lexically scoring comprises lexically scoring, by the at least one computer processor, based on: a number of occurrences of the at least one term found in the at least one content document, a weighting factor representing a relative importance of the at least one term found, and the prior probability of the sense of the at least one term found; and e) semantically scoring, by the at least one computer processor, the at least one candidate topic found in the at least one content document, based on a degree to which any plurality of candidate topics are semantically related to each other comprising: i. quantifying a semantic relatedness score, by the at least one computer processor, of said any plurality of topics of the at least one hypertext corpus data set, and wherein said quantifying of the semantic relatedness score is based on theoretical information content of co-adjacent links of a graph representation of the at least one hypertext corpus data set; evaluating the semantic relatedness score during quantifying, by the at least one computer processor, comprising evaluating the theoretical information content of an edge of said graph representation of the at least one hypertext corpus data set, wherein a vertex of said graph representation of the at least one hypertext corpus data set represents one of said plurality of topics, and an edge of said co-adjacent edges represents a relationship between two topics; wherein the theoretical information content of an edge is based on information theory and comprises at least one of: A. self-information, or B. surprisal ii. semantically scoring, by the at least one computer processor, based on said lexical score of said each of said at least one candidate topic found appearing in the at least one content document, wherein said lexical score of said each of said at least one candidate topic was determined from the at least one term of said lexicon derived from the hypertext corpus data set, and based on said semantic relatedness score from said quantifying. 6. The method according to claim 1 , wherein said searching for said lexically scoring comprises at least one of: i) finding a plurality of said at least one term used in the lexicon, appearing in said at least one received content document in a lexical stage, ii) calculating a calculated lexical score for each of said at least one term appearing in said at least one received content document; and iii) identifying said at least one candidate topic based on at least one topic to which a given term refers in the lexicon.
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10. The passive, non-amplified audio switch of claim 1 further comprising a damp operatively coupled to the sixth audio signal.
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10. The passive, non-amplified audio switch of claim 1 further comprising a damp operatively coupled to the sixth audio signal. 11. The passive, non-amplified audio switch of claim 10 wherein the damp comprises a variable resistor.
| 0.933297 |
8. The apparatus of claim 2 wherein said processor inserts a plurality of first markers into said audio data and a plurality of second markers in the text, said processor inserting each second marker in the text in a position corresponding to the location of a particular first marker in the audio data.
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8. The apparatus of claim 2 wherein said processor inserts a plurality of first markers into said audio data and a plurality of second markers in the text, said processor inserting each second marker in the text in a position corresponding to the location of a particular first marker in the audio data. 9. The apparatus of claim 8 further comprising a user interface in communication with said processor for delivering proximately each particular first marker audio data with corresponding second marker text on said user interface.
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8. An information search system, comprising: an information processing apparatus configured to send a search option input by a user; and an information search apparatus coupled to the information processing apparatus via a network and configured to: determine a search term based on the search option received from the information processing apparatus, the search term including an extracted search term that is extracted from the search option; search a document database to obtain a document that matches the search term; send a search result to the information processing apparatus, the search result including document information identifying the document that matches the search term and relevancy information indicating a degree of relevancy between the search term and the document, wherein the information processing apparatus is further configured to display the search result in a format indicating the correspondence relationship of the document information, the search term, and the relevancy information, wherein the format indicating the correspondence relationship is a matrix, the matrix including a cell that represents relevancy information between the search term and the document, the matrix is displayed on a display device, and the cell, which is linked to the document, is configured to be activated by a user input and to cause the information processing apparatus to display at least a portion of the document having the search term with the search term displayed in the document differently from the other words in the document, wherein the matrix includes a row including a matrix element representing one of the search term or the document information, a column including a matrix element representing another one of the search term or the document information, and the cell being provided at a location where the matrix element representing the search term and the matrix element representing the document information meet and indicating the degree of relevancy between the search term represented by the corresponding matrix element and the document identified by the document information represented by the corresponding matrix element, and wherein, when the search term includes a plurality of search terms, the information search apparatus is further configured to generate a plurality of search results for each one of the plurality of search terms, and the information processing apparatus is configured to display the plurality of search results in the format indicating the correspondence relationship of the document information, the search term, and the relevancy information for each one of the plurality of search results; and the relevancy information is displayed visually in a graphical image having a shape representing the relevancy information.
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8. An information search system, comprising: an information processing apparatus configured to send a search option input by a user; and an information search apparatus coupled to the information processing apparatus via a network and configured to: determine a search term based on the search option received from the information processing apparatus, the search term including an extracted search term that is extracted from the search option; search a document database to obtain a document that matches the search term; send a search result to the information processing apparatus, the search result including document information identifying the document that matches the search term and relevancy information indicating a degree of relevancy between the search term and the document, wherein the information processing apparatus is further configured to display the search result in a format indicating the correspondence relationship of the document information, the search term, and the relevancy information, wherein the format indicating the correspondence relationship is a matrix, the matrix including a cell that represents relevancy information between the search term and the document, the matrix is displayed on a display device, and the cell, which is linked to the document, is configured to be activated by a user input and to cause the information processing apparatus to display at least a portion of the document having the search term with the search term displayed in the document differently from the other words in the document, wherein the matrix includes a row including a matrix element representing one of the search term or the document information, a column including a matrix element representing another one of the search term or the document information, and the cell being provided at a location where the matrix element representing the search term and the matrix element representing the document information meet and indicating the degree of relevancy between the search term represented by the corresponding matrix element and the document identified by the document information represented by the corresponding matrix element, and wherein, when the search term includes a plurality of search terms, the information search apparatus is further configured to generate a plurality of search results for each one of the plurality of search terms, and the information processing apparatus is configured to display the plurality of search results in the format indicating the correspondence relationship of the document information, the search term, and the relevancy information for each one of the plurality of search results; and the relevancy information is displayed visually in a graphical image having a shape representing the relevancy information. 15. The information search system of claim 8 , wherein the graphical image represents the relevancy information by circular shape.
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21. A medical device, comprising: a sensor configured to sense one or more patient parameters used to sense field data about a patient, the field data derived from a Cardio Pulmonary Resuscitation (CPR) session and including events occurring to the patient over time, the events including at least one of chest compressions and ventilations within the CPR session; a processor; a non-transitory memory configured to store one or more programs which, when executed cause the medical device to: generate annotations from the field data, the annotations identifying one or more events within the field data, obtain at least one accuracy criterion indicating an expected order of an event sequence, compute at least one accuracy score for the annotations based on the accuracy criterion, and assign, out of a plurality of possible grades, at least one grade based on the accuracy score, the assigned grade indicating an accuracy with which the annotations identify the events; and a transmitter for transmitting a wireless output signal that includes the at least one grade for the annotations.
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21. A medical device, comprising: a sensor configured to sense one or more patient parameters used to sense field data about a patient, the field data derived from a Cardio Pulmonary Resuscitation (CPR) session and including events occurring to the patient over time, the events including at least one of chest compressions and ventilations within the CPR session; a processor; a non-transitory memory configured to store one or more programs which, when executed cause the medical device to: generate annotations from the field data, the annotations identifying one or more events within the field data, obtain at least one accuracy criterion indicating an expected order of an event sequence, compute at least one accuracy score for the annotations based on the accuracy criterion, and assign, out of a plurality of possible grades, at least one grade based on the accuracy score, the assigned grade indicating an accuracy with which the annotations identify the events; and a transmitter for transmitting a wireless output signal that includes the at least one grade for the annotations. 22. The medical device of claim 21 , in which the execution of the one or more programs further cause the medical device to: compare the at least one grade to a threshold, adjust at least one parameter used to generate at least one of the annotations when the grade does not meet the threshold, generate adjusted annotations based on the adjusted parameter, and assign at least one adjusted grade to the adjusted annotations for inclusion in the wireless output signal.
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15. The media of claim 14 , wherein providing real-time handwriting recognition results to the user further comprises: segmenting the user's handwriting input into one or more recognition units, each recognition unit comprising one or more of the handwritten strokes provided by the user; providing a respective image of each of the one or more recognition units as an input to the multi-script handwriting recognition model; and for at least one of the one or more recognition units, obtaining from the multi-script handwriting recognition model, at least a first output character from a first script, and at least a second output character from a second script different from the first script.
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15. The media of claim 14 , wherein providing real-time handwriting recognition results to the user further comprises: segmenting the user's handwriting input into one or more recognition units, each recognition unit comprising one or more of the handwritten strokes provided by the user; providing a respective image of each of the one or more recognition units as an input to the multi-script handwriting recognition model; and for at least one of the one or more recognition units, obtaining from the multi-script handwriting recognition model, at least a first output character from a first script, and at least a second output character from a second script different from the first script. 16. The media of claim 15 , wherein providing real-time handwriting recognition results to the user further comprises: displaying both the first output character and the second output character in a candidate display area of a handwriting input user interface of the user device.
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7. The method of claim 1 , further comprising: resolving, by at least one of the data processors, segmentation discrepancies with confidence values by using string starting and ending positions to resolve ties.
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7. The method of claim 1 , further comprising: resolving, by at least one of the data processors, segmentation discrepancies with confidence values by using string starting and ending positions to resolve ties. 8. The method of claim 7 , further comprising: detecting and repairing, by at least one of the data processors, at least some NER segmentation errors using document-level token sequence counts and word lists.
| 0.940827 |
1. A computer-implemented method for associating categories with business names for generalizing search queries, the method comprising: receiving, using one or more computing devices, an indication of a search query from a user containing one or more search terms or phrases; identifying, using the one or more computing devices, one or more businesses within a first geographic region associated with the user; determining, using the one or more computing devices, a business name and one or more categories associated with each of the one or more businesses; generating, using the one or more computing devices, one or more name components for each of the one or more businesses, each name component comprising a subset of the business name of the business; generating, using the one or more computing devices, one or more name component groups from the name components of the one or more businesses, wherein each name component group comprises one or more identical name components; determining, using the one or more computing devices, for each name component group, if the one or more name components within the name component group share one or more common categories; associating, using the one or more computing devices, the one or more common categories with the name component of the name component group, when the one or more name components within the name component group share one or more common categories; and providing, using the one or more computing devices, the one or more common categories to the user for inclusion within the query.
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1. A computer-implemented method for associating categories with business names for generalizing search queries, the method comprising: receiving, using one or more computing devices, an indication of a search query from a user containing one or more search terms or phrases; identifying, using the one or more computing devices, one or more businesses within a first geographic region associated with the user; determining, using the one or more computing devices, a business name and one or more categories associated with each of the one or more businesses; generating, using the one or more computing devices, one or more name components for each of the one or more businesses, each name component comprising a subset of the business name of the business; generating, using the one or more computing devices, one or more name component groups from the name components of the one or more businesses, wherein each name component group comprises one or more identical name components; determining, using the one or more computing devices, for each name component group, if the one or more name components within the name component group share one or more common categories; associating, using the one or more computing devices, the one or more common categories with the name component of the name component group, when the one or more name components within the name component group share one or more common categories; and providing, using the one or more computing devices, the one or more common categories to the user for inclusion within the query. 6. The method of claim 1 , wherein generating the one or more name component groups comprises: determining if a name component group represented by the name component exists; generating a name component group represented by the name component if the name component group represented by the name component does not exist; and adding the name component to the name component group represented by the name component.
| 0.57933 |
17. The article of claim 14 , wherein instructions for traversing comprises instructions for traversing the hierarchy structure a certain level upward or downward from the name in the entry based on the special character and the level indicator.
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17. The article of claim 14 , wherein instructions for traversing comprises instructions for traversing the hierarchy structure a certain level upward or downward from the name in the entry based on the special character and the level indicator. 20. The article of claim 17 , wherein if the hierarchy structure is an organization hierarchy structure and the special character is a “+” and the level indicator indicates all levels, instructions for traversing the hierarchy structure of the name in the entry based on the predefined notation include instructions for traversing the hierarchy structure upward to obtain each manager in the hierarchy chain for the name in the entry.
| 0.81241 |
1. A computer-implemented method comprising: detecting, by a mobile computing device, a current context associated with the mobile computing device, the current context being external to the mobile computing device and indicating a current state of the mobile computing device in its surrounding environment, wherein the current context includes information that identifies a received signal strength, at the mobile computing device, of a short or medium-range wireless network that the mobile computing device is currently able to access, and wherein the current context further includes information from a scheduling application that identifies scheduled activities for a user who is associated with the mobile computing device; comparing the received signal strength to a plurality of values of received signal strengths for the short or medium-range wireless network, the plurality of values of received signal strengths being associated with a plurality of different physical locations; identifying, based on at least the comparison of the received signal strength to the plurality of values of received signal strengths, a particular physical location where the mobile computing device is currently located from among the plurality of different physical locations from which the mobile computing device is able to access the short or medium-range wireless network; determining, based on the current context, a current activity of the user; determining, based on the identified particular physical location and the determined current activity of the user, whether to switch the mobile computing device from operating using a current profile to operating using a second profile, wherein the current profile and the second profile each define one or more settings of the mobile computing device, and wherein determining whether to switch the mobile computing device to operating using the second profile is based on applying one or more learned rules to the identified particular physical location and the determined current activity of the user; and in response to determining whether to switch to the second profile, adjusting one or more setting of the mobile computing device based on the second profile, further comprising, over a period of time before determining whether to switch the mobile computing device to operating using the second profile, defining the rules based on user adjustment of the settings of the mobile computing device and a detected context or change in context of the mobile computing device at or around a time the settings were adjusted.
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1. A computer-implemented method comprising: detecting, by a mobile computing device, a current context associated with the mobile computing device, the current context being external to the mobile computing device and indicating a current state of the mobile computing device in its surrounding environment, wherein the current context includes information that identifies a received signal strength, at the mobile computing device, of a short or medium-range wireless network that the mobile computing device is currently able to access, and wherein the current context further includes information from a scheduling application that identifies scheduled activities for a user who is associated with the mobile computing device; comparing the received signal strength to a plurality of values of received signal strengths for the short or medium-range wireless network, the plurality of values of received signal strengths being associated with a plurality of different physical locations; identifying, based on at least the comparison of the received signal strength to the plurality of values of received signal strengths, a particular physical location where the mobile computing device is currently located from among the plurality of different physical locations from which the mobile computing device is able to access the short or medium-range wireless network; determining, based on the current context, a current activity of the user; determining, based on the identified particular physical location and the determined current activity of the user, whether to switch the mobile computing device from operating using a current profile to operating using a second profile, wherein the current profile and the second profile each define one or more settings of the mobile computing device, and wherein determining whether to switch the mobile computing device to operating using the second profile is based on applying one or more learned rules to the identified particular physical location and the determined current activity of the user; and in response to determining whether to switch to the second profile, adjusting one or more setting of the mobile computing device based on the second profile, further comprising, over a period of time before determining whether to switch the mobile computing device to operating using the second profile, defining the rules based on user adjustment of the settings of the mobile computing device and a detected context or change in context of the mobile computing device at or around a time the settings were adjusted. 9. The computer-implemented method of claim 1 , further comprising, at a previous time before identifying the particular physical location, defining a location description for the particular physical location based on a detected context for the mobile computing device at the previous time and additional information that indicates a name for the location description.
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7. One or more computer-readable storage media having computer-readable instructions thereon which, when executed by a computer, cause the computer to: automatically displaying, by the computer, a window on a display device, the window generated by the document-centric application program, the document-centric application program operating at the computer, the window containing a work area and a controls area, the work area containing a document, the controls area not initially containing a context block; storing, by the computer at one or more computer-readable storage media, Hyper-Text Markup Language (HTML) code that specifies a title of the context block and a set of commands of the context block, the set of commands executable by the document-centric application program, the title identifying a task, the set of commands useful to a user in accomplishing the task; store a tree data structure at the computer, the tree data structure comprising an overall set of nodes, each node in the overall set of nodes being an independent data structure, the overall set of nodes including a root node and a set of child nodes, each node in the set of child nodes being a child of one other node in the overall set of nodes, the overall set of nodes comprising a set of leaf nodes and a set of non-leaf nodes, no node in the overall set of nodes being a child of any node in the set of leaf nodes, each node in the set of non-leaf nodes having at least one child node in the overall set of nodes, the root node not being a child of any node in the overall set of nodes, each node in the overall set of nodes associated with a value, each node in the overall set of nodes associated with a Boolean expression, the Boolean expressions associated with each of node in the set of non-leaf nodes taking as operands the values associated with each child node of the node, the set of leaf nodes including a first leaf node; ascertain whether a change has occurred to selected text portions of the document, the selected text portions of the document being portions of the document selected using a cursor, the cursor being controlled by a user, the document being a document in which the user is working; in response to ascertaining that the change has occurred to the selected text portions of the document, make a change to the value associated with the first leaf node; in response to a change to the value associated with any non-root node, use the Boolean expression associated with a parent node to make a determination whether to change a value associated with the parent node, the non-root node being in the set of child nodes, the parent node being a parent of the non-root node; in response to making a determination to change the value associated with the parent node, change the value associated with the parent node; in response to determining that the value associated with the root node has changed from a first value to a second value, automatically cause the controls area of the user interface to contain the context block, the context block containing the title of the context block and the set of commands of the context block, the context block not obscuring the document, at least one command in the set of commands of the context block being displayed in a modeless fashion in which the user is able to continue to work within the document while said at least one command is displayed, and wherein said at least one command in the set of commands of the context block is selectable by the user to perform an action on the selected text portions of the document; and in response to determining that the value associated with the root node has changed from the second value to the first value, automatically cause the user interface not to contain the context block.
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7. One or more computer-readable storage media having computer-readable instructions thereon which, when executed by a computer, cause the computer to: automatically displaying, by the computer, a window on a display device, the window generated by the document-centric application program, the document-centric application program operating at the computer, the window containing a work area and a controls area, the work area containing a document, the controls area not initially containing a context block; storing, by the computer at one or more computer-readable storage media, Hyper-Text Markup Language (HTML) code that specifies a title of the context block and a set of commands of the context block, the set of commands executable by the document-centric application program, the title identifying a task, the set of commands useful to a user in accomplishing the task; store a tree data structure at the computer, the tree data structure comprising an overall set of nodes, each node in the overall set of nodes being an independent data structure, the overall set of nodes including a root node and a set of child nodes, each node in the set of child nodes being a child of one other node in the overall set of nodes, the overall set of nodes comprising a set of leaf nodes and a set of non-leaf nodes, no node in the overall set of nodes being a child of any node in the set of leaf nodes, each node in the set of non-leaf nodes having at least one child node in the overall set of nodes, the root node not being a child of any node in the overall set of nodes, each node in the overall set of nodes associated with a value, each node in the overall set of nodes associated with a Boolean expression, the Boolean expressions associated with each of node in the set of non-leaf nodes taking as operands the values associated with each child node of the node, the set of leaf nodes including a first leaf node; ascertain whether a change has occurred to selected text portions of the document, the selected text portions of the document being portions of the document selected using a cursor, the cursor being controlled by a user, the document being a document in which the user is working; in response to ascertaining that the change has occurred to the selected text portions of the document, make a change to the value associated with the first leaf node; in response to a change to the value associated with any non-root node, use the Boolean expression associated with a parent node to make a determination whether to change a value associated with the parent node, the non-root node being in the set of child nodes, the parent node being a parent of the non-root node; in response to making a determination to change the value associated with the parent node, change the value associated with the parent node; in response to determining that the value associated with the root node has changed from a first value to a second value, automatically cause the controls area of the user interface to contain the context block, the context block containing the title of the context block and the set of commands of the context block, the context block not obscuring the document, at least one command in the set of commands of the context block being displayed in a modeless fashion in which the user is able to continue to work within the document while said at least one command is displayed, and wherein said at least one command in the set of commands of the context block is selectable by the user to perform an action on the selected text portions of the document; and in response to determining that the value associated with the root node has changed from the second value to the first value, automatically cause the user interface not to contain the context block. 8. The computer-readable storage media of claim 7 , wherein the set of leaf nodes includes a second leaf node; and wherein the instructions further cause the computer to: ascertain whether a change has occurred to a position of the cursor; and in response to making ascertaining that the change has occurred to the position of the cursor, making a change to the value associated with the second leaf node.
| 0.541667 |
17. A system for automatically switching fonts on multilingual text runs in a text selection, comprising: a memory for storing executable program code; and a processor, functionally coupled to the memory, the processor being responsive to computer-executable instructions contained in the program code and operative: to receive a text selection having a plurality of text runs, wherein a first text run is in a first language and wherein a second text run is in a second language; to tag each of the first and second text runs with a language identification (ID) associated with each of the first and second languages; to receive an indication of a selection of a font scheme for applying to the text selection, wherein the font scheme comprises a plurality of different font types for each of the plurality of text runs, the plurality of different font types including at least two different font types associated with only the first language in the first text run and at least two different font types associated with only the second language in the second text run, wherein the plurality of different font types in the font scheme are predefined font types, wherein an application of the at least two different font types associated with only the first language in the first text run to the second text run renders the second text run illegible; to pass the language ID to an application programming interface (API) for querying a font scheme definition for the selected font scheme to determine the at least two different font types associated with only the first language in the first text run and the at least two different font types associated with only the different language in the second text run; to map, via the API, the language ID to each of the at least two different font types; to return, via the API, a reference value to a client application for each of the at least two different retrieved font types; to call the plurality of font types for each of the first and second text runs; to render the text selection, wherein the first text run is rendered according to the at least two different font types associated with only the first language retrieved for the first text run and wherein, after the first text run is rendered, the second text run is rendered according to the at least two different font types associated with only the different language retrieved for the second text run, wherein the second text run is automatically rendered immediately following the rendering of the first text run after the selection of the font scheme for applying to the text selection; wherein the selection of the font scheme for applying the text selection comprises a single action.
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17. A system for automatically switching fonts on multilingual text runs in a text selection, comprising: a memory for storing executable program code; and a processor, functionally coupled to the memory, the processor being responsive to computer-executable instructions contained in the program code and operative: to receive a text selection having a plurality of text runs, wherein a first text run is in a first language and wherein a second text run is in a second language; to tag each of the first and second text runs with a language identification (ID) associated with each of the first and second languages; to receive an indication of a selection of a font scheme for applying to the text selection, wherein the font scheme comprises a plurality of different font types for each of the plurality of text runs, the plurality of different font types including at least two different font types associated with only the first language in the first text run and at least two different font types associated with only the second language in the second text run, wherein the plurality of different font types in the font scheme are predefined font types, wherein an application of the at least two different font types associated with only the first language in the first text run to the second text run renders the second text run illegible; to pass the language ID to an application programming interface (API) for querying a font scheme definition for the selected font scheme to determine the at least two different font types associated with only the first language in the first text run and the at least two different font types associated with only the different language in the second text run; to map, via the API, the language ID to each of the at least two different font types; to return, via the API, a reference value to a client application for each of the at least two different retrieved font types; to call the plurality of font types for each of the first and second text runs; to render the text selection, wherein the first text run is rendered according to the at least two different font types associated with only the first language retrieved for the first text run and wherein, after the first text run is rendered, the second text run is rendered according to the at least two different font types associated with only the different language retrieved for the second text run, wherein the second text run is automatically rendered immediately following the rendering of the first text run after the selection of the font scheme for applying to the text selection; wherein the selection of the font scheme for applying the text selection comprises a single action. 18. The system of claim 17 , wherein the processor is further operative to convert, via the API, the language ID into a script ID for mapping the script ID to each of the at least two different font types.
| 0.55178 |
11. A method for generating a keyword performance landscape for one or more keyword-advertiser relationships representing one or more advertisers with one or more advertisements corresponding to a keyword, the method comprising: connecting to a data resource containing data for the one or more keyword-advertiser relationships, the data including historical data of the one or more keyword-advertiser relationships; fetching the historical data for the one or more keyword-advertiser relationships, the historical data including a historical keyword monetization property for the one or more keyword-advertiser relationships; predicting a future keyword monetization property comprising a prediction of a performance for the one or more advertisements corresponding to the keyword for a period of time, wherein the predicting the future keyword monetization property includes generating a global model incorporating the one or more keyword-advertiser relationships and evaluating the one or more keyword-advertiser relationships according to a time-series analysis; and generating the keyword performance landscape for the one or more keyword-advertiser relationships from the historical data and the predicted future keyword monetization property, wherein instructions to perform the connecting, the fetching, the predicting, and the generating are comprised on computer readable media and the method comprises executing the instructions with a computing system.
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11. A method for generating a keyword performance landscape for one or more keyword-advertiser relationships representing one or more advertisers with one or more advertisements corresponding to a keyword, the method comprising: connecting to a data resource containing data for the one or more keyword-advertiser relationships, the data including historical data of the one or more keyword-advertiser relationships; fetching the historical data for the one or more keyword-advertiser relationships, the historical data including a historical keyword monetization property for the one or more keyword-advertiser relationships; predicting a future keyword monetization property comprising a prediction of a performance for the one or more advertisements corresponding to the keyword for a period of time, wherein the predicting the future keyword monetization property includes generating a global model incorporating the one or more keyword-advertiser relationships and evaluating the one or more keyword-advertiser relationships according to a time-series analysis; and generating the keyword performance landscape for the one or more keyword-advertiser relationships from the historical data and the predicted future keyword monetization property, wherein instructions to perform the connecting, the fetching, the predicting, and the generating are comprised on computer readable media and the method comprises executing the instructions with a computing system. 23. The method of claim 11 , wherein the fetching comprises referencing the historical data, the historical data being for advertising between a plurality of advertisers and a plurality of advertiser publishers with respect to the keyword.
| 0.610024 |
1. A method for optimizing pattern query searches on a graph database, the method being implemented by a computer including at least one processor and comprising: providing a pattern search engine operative to generate a search plan on the graph database from a first pattern query, the pattern search engine being executed by the processor; identifying, by the at least one processor, in the first pattern query a first subpattern query and a second subpattern query that is structurally equivalent to the first subpattern query; wherein the first subpattern query and the second subpattern query each comprise a single path; wherein the structural equivalence meets criteria of: the paths have a same number of nodes; nodes in a same position on the paths are of a same type; nodes in a same position on the paths have same qualifications; only start and end nodes are shared; none of non-shared nodes between the paths are exported; any shared node is shared with both paths in a same position; having one shared node between both paths; and non-shared nodes in the paths are not used in pattern query language (PQL) value or constraint expressions; and reducing the number of search expressions in the search plan based on the structural equivalence between the first subpattern query and the second subpattern query.
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1. A method for optimizing pattern query searches on a graph database, the method being implemented by a computer including at least one processor and comprising: providing a pattern search engine operative to generate a search plan on the graph database from a first pattern query, the pattern search engine being executed by the processor; identifying, by the at least one processor, in the first pattern query a first subpattern query and a second subpattern query that is structurally equivalent to the first subpattern query; wherein the first subpattern query and the second subpattern query each comprise a single path; wherein the structural equivalence meets criteria of: the paths have a same number of nodes; nodes in a same position on the paths are of a same type; nodes in a same position on the paths have same qualifications; only start and end nodes are shared; none of non-shared nodes between the paths are exported; any shared node is shared with both paths in a same position; having one shared node between both paths; and non-shared nodes in the paths are not used in pattern query language (PQL) value or constraint expressions; and reducing the number of search expressions in the search plan based on the structural equivalence between the first subpattern query and the second subpattern query. 5. The method of claim 1 , wherein the pattern query comprises one or more branches and one or more cycles.
| 0.522993 |
43. Apparatus for use in accessing an application in association with one or more computer-based devices, the apparatus comprising: one or more processors operative to: (i) obtain the application from an application server, the application being programmatically represented by interactions that the user is permitted to have with the one or more computer-based devices by interaction-based programming components, wherein the interaction-based programming components are independent of content/application logic and presentation requirements associated with the application; and (ii) transcode the interaction-based programming components on a component by component basis to generate one or more modality-specific renderings of the application renderable in accordance with one or more modaility-specific browsers associated with the one or more computer-based devices, the interaction-based programming components being independent of any modality and any modality-specific browser wherein representation by the interaction-based programming components permits synchronization of the one or more modality-specific renderings of the application on the one or more computer-based devices.
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43. Apparatus for use in accessing an application in association with one or more computer-based devices, the apparatus comprising: one or more processors operative to: (i) obtain the application from an application server, the application being programmatically represented by interactions that the user is permitted to have with the one or more computer-based devices by interaction-based programming components, wherein the interaction-based programming components are independent of content/application logic and presentation requirements associated with the application; and (ii) transcode the interaction-based programming components on a component by component basis to generate one or more modality-specific renderings of the application renderable in accordance with one or more modaility-specific browsers associated with the one or more computer-based devices, the interaction-based programming components being independent of any modality and any modality-specific browser wherein representation by the interaction-based programming components permits synchronization of the one or more modality-specific renderings of the application on the one or more computer-based devices. 47. The apparatus of claim 43 , wherein the one or more modality-specific renderings comprise a speech-based representation of portions of the application.
| 0.586545 |
21. The system of claim 16 , wherein the processing system is configured to execute steps comprising: for each content word in the plurality of training texts, determining a concreteness feature score based on a predetermined concreteness rating assigned to the content word; wherein the generating of the prediction model is further based on the concreteness feature scores.
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21. The system of claim 16 , wherein the processing system is configured to execute steps comprising: for each content word in the plurality of training texts, determining a concreteness feature score based on a predetermined concreteness rating assigned to the content word; wherein the generating of the prediction model is further based on the concreteness feature scores. 23. The system of claim 21 , wherein determining a concreteness feature score includes: defining a plurality of bins, each bin being associated with a concreteness rating condition; selecting one or more of the plurality of bins, each selected bin's concreteness rating condition being satisfied by the predetermined concreteness rating assigned to the content word; determining the concreteness feature score based on the one or more bins selected.
| 0.910536 |
15. A tangible, computer-readable medium storing instructions that when executed by a processor cause a computer system to: create an initial contact guide to direct a patient interaction occurring at the beginning of the outpatient oral oncology regimen, wherein the initial contact guide includes one or more questions about the outpatient oral oncology regimen, one or more informational scripts providing information to the patient regarding the outpatient oral oncology regimen, and branching logic to determine which questions and informational scripts to present and an order in which questions and informational scripts are presented, wherein the one or more questions are selected from a plurality of questions which are filtered based at least in part on teratogenicity of the outpatient oral oncology regimen and at least some of the filtered plurality of questions are automatically answered based on medical history data and treatment data for the patient from a medical history database and a treatment database, respectively, and wherein the one or more questions include at least one experimental question in a different format than an original format for a corresponding question to determine whether the different format improves patient compliance; use the initial contact guide to conduct an initial contact with the patient by: (i) present a first initial contact question to the patient, (ii) receive an initial contact answer from the patient wherein the initial contact answer is stored in a patient interaction database, (iii) use the branching logic of the initial contact guide to determine which initial contact guide questions and informational scripts to present based on the initial contact answer, and (iv) present one or more subsequent questions or informational scripts based on the determination of which initial contact guide questions and informational scripts to present based on the initial contact answer, wherein the initial contact with the patient is conducted by an automated representative; create a secondary contact guide to direct a patient interaction occurring a first period of time after the beginning of the outpatient oral oncology regimen, wherein the secondary contact guide includes one or more questions about the outpatient oral oncology regimen, one or more informational scripts providing information to the patient regarding the outpatient oral oncology regimen, and branching logic to determine which questions and informational scripts to present and an order in which questions and informational scripts are presented; use the secondary contact guide to conduct a secondary contact with the patient by: (i) after the first period of time after the beginning of the outpatient oral oncology regimen, present a first secondary contact question to the patient, (ii) receive a secondary contact answer from the patient wherein the secondary contact answer is stored in a patient interaction database, (iii) use the branching logic of the secondary contact guide to determine which secondary contact guide questions and informational scripts to present based on the secondary contact answer, and (iv) present one or more subsequent questions or informational scripts based on the determination of which secondary contact guide questions and informational scripts to present based on the secondary contact answer, wherein the secondary contact with the patient is conducted by the automated representative; prepare a report based on one or more of the initial contact or secondary contact; and send the report to a third party including one or more of a prescriber of the outpatient oral oncology regimen, a government agency, or an insurance provider, wherein the report includes indications of one or more adverse effects caused by the outpatient oral oncology regimen.
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15. A tangible, computer-readable medium storing instructions that when executed by a processor cause a computer system to: create an initial contact guide to direct a patient interaction occurring at the beginning of the outpatient oral oncology regimen, wherein the initial contact guide includes one or more questions about the outpatient oral oncology regimen, one or more informational scripts providing information to the patient regarding the outpatient oral oncology regimen, and branching logic to determine which questions and informational scripts to present and an order in which questions and informational scripts are presented, wherein the one or more questions are selected from a plurality of questions which are filtered based at least in part on teratogenicity of the outpatient oral oncology regimen and at least some of the filtered plurality of questions are automatically answered based on medical history data and treatment data for the patient from a medical history database and a treatment database, respectively, and wherein the one or more questions include at least one experimental question in a different format than an original format for a corresponding question to determine whether the different format improves patient compliance; use the initial contact guide to conduct an initial contact with the patient by: (i) present a first initial contact question to the patient, (ii) receive an initial contact answer from the patient wherein the initial contact answer is stored in a patient interaction database, (iii) use the branching logic of the initial contact guide to determine which initial contact guide questions and informational scripts to present based on the initial contact answer, and (iv) present one or more subsequent questions or informational scripts based on the determination of which initial contact guide questions and informational scripts to present based on the initial contact answer, wherein the initial contact with the patient is conducted by an automated representative; create a secondary contact guide to direct a patient interaction occurring a first period of time after the beginning of the outpatient oral oncology regimen, wherein the secondary contact guide includes one or more questions about the outpatient oral oncology regimen, one or more informational scripts providing information to the patient regarding the outpatient oral oncology regimen, and branching logic to determine which questions and informational scripts to present and an order in which questions and informational scripts are presented; use the secondary contact guide to conduct a secondary contact with the patient by: (i) after the first period of time after the beginning of the outpatient oral oncology regimen, present a first secondary contact question to the patient, (ii) receive a secondary contact answer from the patient wherein the secondary contact answer is stored in a patient interaction database, (iii) use the branching logic of the secondary contact guide to determine which secondary contact guide questions and informational scripts to present based on the secondary contact answer, and (iv) present one or more subsequent questions or informational scripts based on the determination of which secondary contact guide questions and informational scripts to present based on the secondary contact answer, wherein the secondary contact with the patient is conducted by the automated representative; prepare a report based on one or more of the initial contact or secondary contact; and send the report to a third party including one or more of a prescriber of the outpatient oral oncology regimen, a government agency, or an insurance provider, wherein the report includes indications of one or more adverse effects caused by the outpatient oral oncology regimen. 20. The tangible, computer-readable medium of claim 15 , further storing instructions that that when executed by the processor cause the computer system to receive information about the patient from a patient information database prior to presenting the first initial contact question to the patient.
| 0.575684 |
11. The method according to claim 1 , wherein a generative process for the corpus leads to a joint distribution of c, z, θ represented as: α→θ→z→w |c d→c→t→w |d| θ→t Ξ→c w |c| ←Λ→w |z| and update rules for the iterative process comprise: Φ sjhl ∝ Ξ js Λ hl exp ( Ψ ( γ jl ) - Ψ ( ∑ t = 1 K γ jt ) ) ( 2 ) γ sl = α l + ∑ g = 1 N ∑ h = 1 M A hg Φ gshl ( 3 ) Λ hl ∝ ∑ s = 1 N ∑ j = 1 N A hs Φ sjhl where A hs = ∑ i = 1 L s w si h ( 4 ) and Ψ(•) is digamma function.
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11. The method according to claim 1 , wherein a generative process for the corpus leads to a joint distribution of c, z, θ represented as: α→θ→z→w |c d→c→t→w |d| θ→t Ξ→c w |c| ←Λ→w |z| and update rules for the iterative process comprise: Φ sjhl ∝ Ξ js Λ hl exp ( Ψ ( γ jl ) - Ψ ( ∑ t = 1 K γ jt ) ) ( 2 ) γ sl = α l + ∑ g = 1 N ∑ h = 1 M A hg Φ gshl ( 3 ) Λ hl ∝ ∑ s = 1 N ∑ j = 1 N A hs Φ sjhl where A hs = ∑ i = 1 L s w si h ( 4 ) and Ψ(•) is digamma function. 13. The method according to claim 11 , wherein the iterative update rules Φ sjhl ∝ Ξ js Λ hl exp ( Ψ ( γ jl ) - Ψ ( ∑ t = 1 K γ jt ) ) ( 2 ) γ sl = α l + ∑ g = 1 N ∑ h = 1 M A hg Φ gshl ( 3 ) are performed in order until convergence to learn the topic distribution of new corpus.
| 0.867675 |
16. A method comprising: transmitting, by at least one computing device and via a network, first one or more signals identifying a plurality of items of video content and a plurality of channels via which the plurality of items of video content are scheduled to be delivered; receiving, from a client device via the network, second one or more signals indicating a user selection of a first channel of the plurality of channels; determining, in response to the second one or more signals and based on first data stored by at least one data storage device that is communicatively coupled with the at least one computing device, whether a first one of the items of video content, that is scheduled to be delivered via the first channel, is associated with any of a plurality of supplemental services, wherein the first data associates the plurality of items of video content with the plurality of channels and with the plurality of supplemental services; and transmitting, via the network and in response to determining that the first one of the items of video content is associated with a first supplemental service of the plurality of supplemental services, third one or more signals identifying the first supplemental service.
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16. A method comprising: transmitting, by at least one computing device and via a network, first one or more signals identifying a plurality of items of video content and a plurality of channels via which the plurality of items of video content are scheduled to be delivered; receiving, from a client device via the network, second one or more signals indicating a user selection of a first channel of the plurality of channels; determining, in response to the second one or more signals and based on first data stored by at least one data storage device that is communicatively coupled with the at least one computing device, whether a first one of the items of video content, that is scheduled to be delivered via the first channel, is associated with any of a plurality of supplemental services, wherein the first data associates the plurality of items of video content with the plurality of channels and with the plurality of supplemental services; and transmitting, via the network and in response to determining that the first one of the items of video content is associated with a first supplemental service of the plurality of supplemental services, third one or more signals identifying the first supplemental service. 19. The method of claim 16 , wherein the first supplemental service comprises one or both of a web site or a web page.
| 0.883333 |
14. At least one non-transitory machine accessible medium comprising: instructions that, when executed by a mobile computing device, enable the mobile computing device to perform operations comprising: in a first portion of a display of the mobile computing device, displaying at least part of an electronic form containing input objects to accept user input; displaying a virtual keyboard in a second portion of the display, wherein the second portion of the display is distinct from the first portion of the display, and wherein the virtual keyboard comprises at least a first alphabetic button to enable a user to enter a first alphabetic character and a second alphabetic button to enable the user to enter a second alphabetic character; automatically parsing the electronic form to discover attributes of at least one of the input objects in the electronic form; automatically determining whether the electronic form includes a non-textual input object, based on results of the parsing; and in response to discovering that the electronic form includes a non-textual input object, automatically adding a corresponding non-textual virtual keyboard component to the virtual keyboard; wherein displaying the virtual keyboard comprises displaying the virtual keyboard with the first and second alphabetic buttons and with the added non-textual virtual keyboard component in the second portion of the display; and wherein the added non-textual virtual keyboard component is configured to allow a user to invoke, from the virtual keyboard, a function associated with the corresponding non-textual input object in the electronic form.
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14. At least one non-transitory machine accessible medium comprising: instructions that, when executed by a mobile computing device, enable the mobile computing device to perform operations comprising: in a first portion of a display of the mobile computing device, displaying at least part of an electronic form containing input objects to accept user input; displaying a virtual keyboard in a second portion of the display, wherein the second portion of the display is distinct from the first portion of the display, and wherein the virtual keyboard comprises at least a first alphabetic button to enable a user to enter a first alphabetic character and a second alphabetic button to enable the user to enter a second alphabetic character; automatically parsing the electronic form to discover attributes of at least one of the input objects in the electronic form; automatically determining whether the electronic form includes a non-textual input object, based on results of the parsing; and in response to discovering that the electronic form includes a non-textual input object, automatically adding a corresponding non-textual virtual keyboard component to the virtual keyboard; wherein displaying the virtual keyboard comprises displaying the virtual keyboard with the first and second alphabetic buttons and with the added non-textual virtual keyboard component in the second portion of the display; and wherein the added non-textual virtual keyboard component is configured to allow a user to invoke, from the virtual keyboard, a function associated with the corresponding non-textual input object in the electronic form. 15. At least one non-transitory machine accessible medium according to claim 14 , wherein: the non-textual input object in the electronic form comprises a command button; and the added non-textual virtual keyboard component in the virtual keyboard comprises a corresponding command button configured to allow the user to invoke, from the virtual keyboard, the function associated with the command button in the electronic form.
| 0.575132 |
5. The method of claim 1 , further comprising, responsive to detecting the instruction, transmitting a communication.
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5. The method of claim 1 , further comprising, responsive to detecting the instruction, transmitting a communication. 6. The method of claim 5 , wherein the communication comprises a portion of the transcript.
| 0.945882 |
12. A computer system comprising a computer processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the computer processor implements a method comprising: computing, by said computer processor, a term frequency-inverse document frequency (tf-idf) associated with n-grams of an n-gram model of a domain; determining, by said computer processor based on said tf-idf, a frequently occurring group of n-grams of said n-grams; generating, by said computer processor executing a deep parser component of said computing system with respect to said frequently occurring group of n-grams, a deep parse output comprising results of said executing said deep parser component with respect to said frequently occurring group of n-grams; storing, by said computer processor in a database cache, said deep parse output; indexing, by said computer processor executing said frequently occurring group of n-grams in said database cache, said deep parse output; and verifying, by said computer processor, if a pre-computed specified text word sequence of said deep parse output is available in said database cache, wherein said verifying comprises: retrieving from said deep parse output, a plurality of tokens of said deep parser output, wherein said plurality of tokens are associated with a portion of said pre-computed specified text word sequence, wherein said plurality of tokens comprise suffixes associated with structures of said deep parser output, and wherein said plurality of tokens comprise a version token; and determining based on said plurality of tokens, variations associated with said pre-computed specified text word sequence.
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12. A computer system comprising a computer processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the computer processor implements a method comprising: computing, by said computer processor, a term frequency-inverse document frequency (tf-idf) associated with n-grams of an n-gram model of a domain; determining, by said computer processor based on said tf-idf, a frequently occurring group of n-grams of said n-grams; generating, by said computer processor executing a deep parser component of said computing system with respect to said frequently occurring group of n-grams, a deep parse output comprising results of said executing said deep parser component with respect to said frequently occurring group of n-grams; storing, by said computer processor in a database cache, said deep parse output; indexing, by said computer processor executing said frequently occurring group of n-grams in said database cache, said deep parse output; and verifying, by said computer processor, if a pre-computed specified text word sequence of said deep parse output is available in said database cache, wherein said verifying comprises: retrieving from said deep parse output, a plurality of tokens of said deep parser output, wherein said plurality of tokens are associated with a portion of said pre-computed specified text word sequence, wherein said plurality of tokens comprise suffixes associated with structures of said deep parser output, and wherein said plurality of tokens comprise a version token; and determining based on said plurality of tokens, variations associated with said pre-computed specified text word sequence. 15. The computer system of claim 12 , wherein each n-gram of said frequently occurring group of n-grams comprises a cache key.
| 0.770642 |
10. One or more non-transitory computer-readable tangible media encoding software operable when executed to: access a corpus stored in one or more tangible media, the corpus comprising a plurality of terms; perform the following for each term of one or more terms of the plurality of terms to yield a plurality of parent-child relationships: identify one or more parent terms of the each term according to directional affinity, the plurality of terms comprising the one or more parent terms, the directional affinity being the number of co-occurrence contexts that include two terms, over the number of co-occurrence contexts that include one term; and establish one or more parent-child relationships from the one or more parent terms and the each term; and automatically generate a hierarchical graph from the plurality of parent-child relationships, wherein the automatically generating the hierarchical graph from the plurality of parent-child relationships comprises reducing the hierarchical graph by: identifying a parent-child relationship and a redundant parent-child relationship of the hierarchical graph; and removing the redundant parent-child relationship from the hierarchical graph.
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10. One or more non-transitory computer-readable tangible media encoding software operable when executed to: access a corpus stored in one or more tangible media, the corpus comprising a plurality of terms; perform the following for each term of one or more terms of the plurality of terms to yield a plurality of parent-child relationships: identify one or more parent terms of the each term according to directional affinity, the plurality of terms comprising the one or more parent terms, the directional affinity being the number of co-occurrence contexts that include two terms, over the number of co-occurrence contexts that include one term; and establish one or more parent-child relationships from the one or more parent terms and the each term; and automatically generate a hierarchical graph from the plurality of parent-child relationships, wherein the automatically generating the hierarchical graph from the plurality of parent-child relationships comprises reducing the hierarchical graph by: identifying a parent-child relationship and a redundant parent-child relationship of the hierarchical graph; and removing the redundant parent-child relationship from the hierarchical graph. 17. The computer-readable tangible media of claim 10 , the software further operable to: receive a search query comprising a parent term of the hierarchical graph; identify one or more child terms of the parent term; and search the corpus using the parent term and the one or more child terms.
| 0.719231 |
8. A system for connecting information resources, the system comprising: at least one of a processor and a memory providing: a collaborative work environment accessible by a plurality of users who contribute collaboration data to the collaborative work environment via one or more user interfaces; a repository framework including a plurality of collaboration data sources that includes the collaborative work environment; and a collaborative bot service connected with the repository framework, the collaborative bot service including one or more bots that perform functions comprising: maintaining a topic list of topics previously identified in the plurality of collaboration data sources automatically and autonomously monitoring the collaboration work environment, the monitoring comprising traversing the collaboration information provided within the collaborative work environment via a user interface by the plurality of users; extracting, using a text-mining tool upon detection via the monitoring of new collaboration information contributed by one of the plurality of users in the collaborative work environment for use by at least one other of the plurality of users in the collaborative work environment, an extracted topic of the new collaboration information, the extracted topic comprising at least one of a theme, a question, a problem, and a subject matter of the new collaboration information; identifying an information resource within the plurality of collaboration data sources that is related to the extracted topic, the identifying comprising comparing the extracted topic to the topic list and determining that previously contributed collaboration information available from the information resource has a topic related to the extracted topic; creating a link insertable into a collaborative process, through which the plurality of users can send communications, of the collaborative work environment, the link being to the information resource identified as related to the extracted topic of the new collaboration information contributed by the one of the plurality of users for use by the at least one other of the plurality of users in the collaborative work environment; and inserting the link into the collaborative process through which the plurality of users can send communications and into the user interface in a close proximal relation to the new collaboration information.
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8. A system for connecting information resources, the system comprising: at least one of a processor and a memory providing: a collaborative work environment accessible by a plurality of users who contribute collaboration data to the collaborative work environment via one or more user interfaces; a repository framework including a plurality of collaboration data sources that includes the collaborative work environment; and a collaborative bot service connected with the repository framework, the collaborative bot service including one or more bots that perform functions comprising: maintaining a topic list of topics previously identified in the plurality of collaboration data sources automatically and autonomously monitoring the collaboration work environment, the monitoring comprising traversing the collaboration information provided within the collaborative work environment via a user interface by the plurality of users; extracting, using a text-mining tool upon detection via the monitoring of new collaboration information contributed by one of the plurality of users in the collaborative work environment for use by at least one other of the plurality of users in the collaborative work environment, an extracted topic of the new collaboration information, the extracted topic comprising at least one of a theme, a question, a problem, and a subject matter of the new collaboration information; identifying an information resource within the plurality of collaboration data sources that is related to the extracted topic, the identifying comprising comparing the extracted topic to the topic list and determining that previously contributed collaboration information available from the information resource has a topic related to the extracted topic; creating a link insertable into a collaborative process, through which the plurality of users can send communications, of the collaborative work environment, the link being to the information resource identified as related to the extracted topic of the new collaboration information contributed by the one of the plurality of users for use by the at least one other of the plurality of users in the collaborative work environment; and inserting the link into the collaborative process through which the plurality of users can send communications and into the user interface in a close proximal relation to the new collaboration information. 13. A system in accordance with claim 8 , further comprising an administration interface for receiving user commands and for configuring each of the one or more bots.
| 0.526765 |
2. The method of claim 1 , comprising: receiving, at the first communication device, provisioning information via the user interface, the provisioning information indicating types of alerts and a level of auto-correction to be applied for the second communication device; and storing, by the first communication device, the provisioning information in a memory of the first communication device indexed to the second communication device, wherein the receiving and storing of the provisioning information is prior to the receiving of the input data comprising the group of words, and wherein the performing of the auto-correction and the presenting of the correction alert are according to the provisioning information.
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2. The method of claim 1 , comprising: receiving, at the first communication device, provisioning information via the user interface, the provisioning information indicating types of alerts and a level of auto-correction to be applied for the second communication device; and storing, by the first communication device, the provisioning information in a memory of the first communication device indexed to the second communication device, wherein the receiving and storing of the provisioning information is prior to the receiving of the input data comprising the group of words, and wherein the performing of the auto-correction and the presenting of the correction alert are according to the provisioning information. 3. The method of claim 2 , comprising providing, by the first communication device, a recipient alert with the transmission of the corrected text message to the second communication device, wherein the recipient alert is configured for presentation at the second communication device to indicate the target word that has been auto-corrected, wherein the recipient alert enables the second communication device to remotely access an unmodified version of the target word from a messaging server that is remote from the first communication device, and wherein the types of alerts indicate at least one of audio or graphical alerts corresponding to types of words being corrected.
| 0.712468 |
10. A computer-implemented method of providing annotated electronic documents, the method being executed on a computer and comprising: providing, in a computer processor, access to an electronic storage configured to store at least one annotation as annotation data in a first data storage and at least one document as document data in a second data storage, the first and second data storage being searchable databases; receiving, in the computer processor from the electronic storage, a unitary single logical document for display that includes document data with at least one annotation represented by annotation data embedded seamlessly in the document data, the annotation data being retrieved from the first data storage, the document data being retrieved from the second data storage which is stored separately from the first data storage; and extracting, in the computer processor, by a split component, from the single logical document, the annotation data and the document data; updating the at least one annotation in the first data storage from the extracted annotation data; and updating the at least one document in the second data storage from the extracted document data, wherein the annotation data indexes into a predetermined section within the document as stored in the second data storage into which the annotation is to be embedded as indicated by a document-image-independent data schema, wherein the annotations data further includes, specific to the predetermined section within the document to which the annotation is embedded, a pre-defined conflict indication user-selected from at least two of pass possible and fail, and wherein the processor is further configured to search, responsive to a search request from at least one user, the search request includes annotation search criteria which includes at least one of the pre-defined conflict indications content of the annotation data in the first data storage for the annotation data that satisfies the annotation search criteria, and to output, as a search result, the at least one document indicated by the annotation data that satisfies the annotation search criteria.
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10. A computer-implemented method of providing annotated electronic documents, the method being executed on a computer and comprising: providing, in a computer processor, access to an electronic storage configured to store at least one annotation as annotation data in a first data storage and at least one document as document data in a second data storage, the first and second data storage being searchable databases; receiving, in the computer processor from the electronic storage, a unitary single logical document for display that includes document data with at least one annotation represented by annotation data embedded seamlessly in the document data, the annotation data being retrieved from the first data storage, the document data being retrieved from the second data storage which is stored separately from the first data storage; and extracting, in the computer processor, by a split component, from the single logical document, the annotation data and the document data; updating the at least one annotation in the first data storage from the extracted annotation data; and updating the at least one document in the second data storage from the extracted document data, wherein the annotation data indexes into a predetermined section within the document as stored in the second data storage into which the annotation is to be embedded as indicated by a document-image-independent data schema, wherein the annotations data further includes, specific to the predetermined section within the document to which the annotation is embedded, a pre-defined conflict indication user-selected from at least two of pass possible and fail, and wherein the processor is further configured to search, responsive to a search request from at least one user, the search request includes annotation search criteria which includes at least one of the pre-defined conflict indications content of the annotation data in the first data storage for the annotation data that satisfies the annotation search criteria, and to output, as a search result, the at least one document indicated by the annotation data that satisfies the annotation search criteria. 14. The method of claim 10 , further comprising: marking-up, in the computer processor responsive to the user, the at least one document to at least one of add and edit the at least one annotation, wherein each annotation is different from every other annotation; and responsive to the user, at least one of establishing, traversing, indicating, and removing, at least one reference between the at least one portion and at least one of an other portion of the at least one document, an other document, and at least one other portion of the other document.
| 0.5 |
1. A method comprising: receiving, by a computer system, first event data indicative of computer network activity of a plurality of users and network devices in a computer network; generating, by the computer system, classification metadata for each of the network devices and users, based on the first event data, to indicate relevance in a network security context of each of the users and network devices; identifying, by the computer system, usage relationships between one or more of the users and one or more of the network devices, based on first event data; assigning, by the computer system, usage similarity scores to the network devices based on the identified usage relationships, the usage similarity scores being indicative of which of the network devices have been used by the same or similar group of users; receiving, by the computer system, second event data indicative of computer network activity of a particular user of the plurality of users; and detecting, by the computer system and in response to the second event data, an anomaly indicative that the particular user has interacted with a particular network device with which the particular user does not normally interact, based on the usage similarity scores and the classification metadata.
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1. A method comprising: receiving, by a computer system, first event data indicative of computer network activity of a plurality of users and network devices in a computer network; generating, by the computer system, classification metadata for each of the network devices and users, based on the first event data, to indicate relevance in a network security context of each of the users and network devices; identifying, by the computer system, usage relationships between one or more of the users and one or more of the network devices, based on first event data; assigning, by the computer system, usage similarity scores to the network devices based on the identified usage relationships, the usage similarity scores being indicative of which of the network devices have been used by the same or similar group of users; receiving, by the computer system, second event data indicative of computer network activity of a particular user of the plurality of users; and detecting, by the computer system and in response to the second event data, an anomaly indicative that the particular user has interacted with a particular network device with which the particular user does not normally interact, based on the usage similarity scores and the classification metadata. 15. The method of claim 1 , wherein said assigning usage similarity scores comprises: assigning usage similarity scores to the network devices based on relationships between the users and the network devices, such that particular network devices having multiple exclusive users interacting with only the particular network devices tend to have usage similarity scores that have differences less than a threshold value.
| 0.790709 |
7. A method that uses a processor to provide a search query and an advertising word related to the search query, the method comprising: receiving a search query in real-time from a user terminal, wherein a plurality of search queries and a plurality of advertising words related to the search queries are stored in a database; indexing, by the processor, the search queries and the advertising words by correlating the search queries and the advertising words with one of a consonant/vowel, a syllable, a suffix, or any combination thereof, wherein the indexed search queries and advertising words are classified and stored in the database; upon detection of the partial or full search query, providing an auto-completed search query and an auto-completed advertising word according to the indexing, the providing occurring in real-time as the partial or full search query is received; and causing display of the auto-completed search query and the auto-completed advertising word in a user interface window associated with a search display area of the user terminal, the displaying including using a visual indicator to distinguish the auto-completed advertising word from the auto-completed search query.
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7. A method that uses a processor to provide a search query and an advertising word related to the search query, the method comprising: receiving a search query in real-time from a user terminal, wherein a plurality of search queries and a plurality of advertising words related to the search queries are stored in a database; indexing, by the processor, the search queries and the advertising words by correlating the search queries and the advertising words with one of a consonant/vowel, a syllable, a suffix, or any combination thereof, wherein the indexed search queries and advertising words are classified and stored in the database; upon detection of the partial or full search query, providing an auto-completed search query and an auto-completed advertising word according to the indexing, the providing occurring in real-time as the partial or full search query is received; and causing display of the auto-completed search query and the auto-completed advertising word in a user interface window associated with a search display area of the user terminal, the displaying including using a visual indicator to distinguish the auto-completed advertising word from the auto-completed search query. 16. The method of claim 7 wherein the displaying the auto-completed search query and the auto-completed advertising word comprises distinguishably displaying the auto-completed search query or the auto-completed advertising word according to a setting mode corresponding to the indexing.
| 0.582488 |
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